Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism

NASA Astrophysics Data System (ADS)

Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.

2015-04-01

We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.

A novel manifold-manifold distance index applied to looseness state assessment of viscoelastic sandwich structures

NASA Astrophysics Data System (ADS)

Sun, Chuang; Zhang, Zhousuo; Guo, Ting; Luo, Xue; Qu, Jinxiu; Zhang, Chenxuan; Cheng, Wei; Li, Bing

2014-06-01

Viscoelastic sandwich structures (VSS) are widely used in mechanical equipment; their state assessment is necessary to detect structural states and to keep equipment running with high reliability. This paper proposes a novel manifold-manifold distance-based assessment (M2DBA) method for assessing the looseness state in VSSs. In the M2DBA method, a manifold-manifold distance is viewed as a health index. To design the index, response signals from the structure are firstly acquired by condition monitoring technology and a Hankel matrix is constructed by using the response signals to describe state patterns of the VSS. Thereafter, a subspace analysis method, that is, principal component analysis (PCA), is performed to extract the condition subspace hidden in the Hankel matrix. From the subspace, pattern changes in dynamic structural properties are characterized. Further, a Grassmann manifold (GM) is formed by organizing a set of subspaces. The manifold is mapped to a reproducing kernel Hilbert space (RKHS), where support vector data description (SVDD) is used to model the manifold as a hypersphere. Finally, a health index is defined as the cosine of the angle between the hypersphere centers corresponding to the structural baseline state and the looseness state. The defined health index contains similarity information existing in the two structural states, so structural looseness states can be effectively identified. Moreover, the health index is derived by analysis of the global properties of subspace sets, which is different from traditional subspace analysis methods. The effectiveness of the health index for state assessment is validated by test data collected from a VSS subjected to different degrees of looseness. The results show that the health index is a very effective metric for detecting the occurrence and extension of structural looseness. Comparison results indicate that the defined index outperforms some existing state-of-the-art ones.

Grassmann phase space theory and the Jaynes–Cummings model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dalton, B.J., E-mail: bdalton@swin.edu.au; Centre for Atom Optics and Ultrafast Spectroscopy, Swinburne University of Technology, Melbourne, Victoria 3122; Garraway, B.M.

2013-07-15

The Jaynes–Cummings model of a two-level atom in a single mode cavity is of fundamental importance both in quantum optics and in quantum physics generally, involving the interaction of two simple quantum systems—one fermionic system (the TLA), the other bosonic (the cavity mode). Depending on the initial conditions a variety of interesting effects occur, ranging from ongoing oscillations of the atomic population difference at the Rabi frequency when the atom is excited and the cavity is in an n-photon Fock state, to collapses and revivals of these oscillations starting with the atom unexcited and the cavity mode in a coherentmore » state. The observation of revivals for Rydberg atoms in a high-Q microwave cavity is key experimental evidence for quantisation of the EM field. Theoretical treatments of the Jaynes–Cummings model based on expanding the state vector in terms of products of atomic and n-photon states and deriving coupled equations for the amplitudes are a well-known and simple method for determining the effects. In quantum optics however, the behaviour of the bosonic quantum EM field is often treated using phase space methods, where the bosonic mode annihilation and creation operators are represented by c-number phase space variables, with the density operator represented by a distribution function of these variables. Fokker–Planck equations for the distribution function are obtained, and either used directly to determine quantities of experimental interest or used to develop c-number Langevin equations for stochastic versions of the phase space variables from which experimental quantities are obtained as stochastic averages. Phase space methods have also been developed to include atomic systems, with the atomic spin operators being represented by c-number phase space variables, and distribution functions involving these variables and those for any bosonic modes being shown to satisfy Fokker–Planck equations from which c-number Langevin equations are often developed. However, atomic spin operators satisfy the standard angular momentum commutation rules rather than the commutation rules for bosonic annihilation and creation operators, and are in fact second order combinations of fermionic annihilation and creation operators. Though phase space methods in which the fermionic operators are represented directly by c-number phase space variables have not been successful, the anti-commutation rules for these operators suggest the possibility of using Grassmann variables—which have similar anti-commutation properties. However, in spite of the seminal work by Cahill and Glauber and a few applications, the use of phase space methods in quantum optics to treat fermionic systems by representing fermionic annihilation and creation operators directly by Grassmann phase space variables is rather rare. This paper shows that phase space methods using a positive P type distribution function involving both c-number variables (for the cavity mode) and Grassmann variables (for the TLA) can be used to treat the Jaynes–Cummings model. Although it is a Grassmann function, the distribution function is equivalent to six c-number functions of the two bosonic variables. Experimental quantities are given as bosonic phase space integrals involving the six functions. A Fokker–Planck equation involving both left and right Grassmann differentiations can be obtained for the distribution function, and is equivalent to six coupled equations for the six c-number functions. The approach used involves choosing the canonical form of the (non-unique) positive P distribution function, in which the correspondence rules for the bosonic operators are non-standard and hence the Fokker–Planck equation is also unusual. Initial conditions, such as those above for initially uncorrelated states, are discussed and used to determine the initial distribution function. Transformations to new bosonic variables rotating at the cavity frequency enable the six coupled equations for the new c-number functions–that are also equivalent to the canonical Grassmann distribution function–to be solved analytically, based on an ansatz from an earlier paper by Stenholm. It is then shown that the distribution function is exactly the same as that determined from the well-known solution based on coupled amplitude equations. In quantum–atom optics theories for many atom bosonic and fermionic systems are needed. With large atom numbers, treatments must often take into account many quantum modes—especially for fermions. Generalisations of phase space distribution functions of phase space variables for a few modes to phase space distribution functionals of field functions (which represent the field operators, c-number fields for bosons, Grassmann fields for fermions) are now being developed for large systems. For the fermionic case, the treatment of the simple two mode problem represented by the Jaynes–Cummings model is a useful test case for the future development of phase space Grassmann distribution functional methods for fermionic applications in quantum–atom optics. -- Highlights: •Novel phase space theory of the Jaynes–Cummings model using Grassmann variables. •Fokker–Planck equations solved analytically. •Results agree with the standard quantum optics treatment. •Grassmann phase space theory applicable to fermion many-body problems.« less

Theoretical princi les of constructing the equations of motion for a spin color-charged particle in gauge and fermion fields

NASA Astrophysics Data System (ADS)

Markov, Yu. A.; Shishmarev, A. A.

2010-11-01

Based on the most general principles of materiality, gauge, and re-parameterized invariance, the problem of constructing an action describing the dynamics of a classical color-charged particle moving in external non-Abelian gauge and fermion fields is considered. The case of a linear Lagrangian dependence on the external fermion fields is discussed. Within the framework of the description of the color degree of freedom of the particle with half-integer spin by the Grassmann color charges, a new concept of the Grassmann color source of the particle being a fermion analog of the conventional color current is introduced.

Grassmann phase space theory and the Jaynes-Cummings model

NASA Astrophysics Data System (ADS)

Dalton, B. J.; Garraway, B. M.; Jeffers, J.; Barnett, S. M.

2013-07-01

The Jaynes-Cummings model of a two-level atom in a single mode cavity is of fundamental importance both in quantum optics and in quantum physics generally, involving the interaction of two simple quantum systems—one fermionic system (the TLA), the other bosonic (the cavity mode). Depending on the initial conditions a variety of interesting effects occur, ranging from ongoing oscillations of the atomic population difference at the Rabi frequency when the atom is excited and the cavity is in an n-photon Fock state, to collapses and revivals of these oscillations starting with the atom unexcited and the cavity mode in a coherent state. The observation of revivals for Rydberg atoms in a high-Q microwave cavity is key experimental evidence for quantisation of the EM field. Theoretical treatments of the Jaynes-Cummings model based on expanding the state vector in terms of products of atomic and n-photon states and deriving coupled equations for the amplitudes are a well-known and simple method for determining the effects. In quantum optics however, the behaviour of the bosonic quantum EM field is often treated using phase space methods, where the bosonic mode annihilation and creation operators are represented by c-number phase space variables, with the density operator represented by a distribution function of these variables. Fokker-Planck equations for the distribution function are obtained, and either used directly to determine quantities of experimental interest or used to develop c-number Langevin equations for stochastic versions of the phase space variables from which experimental quantities are obtained as stochastic averages. Phase space methods have also been developed to include atomic systems, with the atomic spin operators being represented by c-number phase space variables, and distribution functions involving these variables and those for any bosonic modes being shown to satisfy Fokker-Planck equations from which c-number Langevin equations are often developed. However, atomic spin operators satisfy the standard angular momentum commutation rules rather than the commutation rules for bosonic annihilation and creation operators, and are in fact second order combinations of fermionic annihilation and creation operators. Though phase space methods in which the fermionic operators are represented directly by c-number phase space variables have not been successful, the anti-commutation rules for these operators suggest the possibility of using Grassmann variables—which have similar anti-commutation properties. However, in spite of the seminal work by Cahill and Glauber and a few applications, the use of phase space methods in quantum optics to treat fermionic systems by representing fermionic annihilation and creation operators directly by Grassmann phase space variables is rather rare. This paper shows that phase space methods using a positive P type distribution function involving both c-number variables (for the cavity mode) and Grassmann variables (for the TLA) can be used to treat the Jaynes-Cummings model. Although it is a Grassmann function, the distribution function is equivalent to six c-number functions of the two bosonic variables. Experimental quantities are given as bosonic phase space integrals involving the six functions. A Fokker-Planck equation involving both left and right Grassmann differentiations can be obtained for the distribution function, and is equivalent to six coupled equations for the six c-number functions. The approach used involves choosing the canonical form of the (non-unique) positive P distribution function, in which the correspondence rules for the bosonic operators are non-standard and hence the Fokker-Planck equation is also unusual. Initial conditions, such as those above for initially uncorrelated states, are discussed and used to determine the initial distribution function. Transformations to new bosonic variables rotating at the cavity frequency enable the six coupled equations for the new c-number functions-that are also equivalent to the canonical Grassmann distribution function-to be solved analytically, based on an ansatz from an earlier paper by Stenholm. It is then shown that the distribution function is exactly the same as that determined from the well-known solution based on coupled amplitude equations. In quantum-atom optics theories for many atom bosonic and fermionic systems are needed. With large atom numbers, treatments must often take into account many quantum modes—especially for fermions. Generalisations of phase space distribution functions of phase space variables for a few modes to phase space distribution functionals of field functions (which represent the field operators, c-number fields for bosons, Grassmann fields for fermions) are now being developed for large systems. For the fermionic case, the treatment of the simple two mode problem represented by the Jaynes-Cummings model is a useful test case for the future development of phase space Grassmann distribution functional methods for fermionic applications in quantum-atom optics.

Fermionic Field Theory for Trees and Forests

NASA Astrophysics Data System (ADS)

Caracciolo, Sergio; Jacobsen, Jesper Lykke; Saleur, Hubert; Sokal, Alan D.; Sportiello, Andrea

2004-08-01

We prove a generalization of Kirchhoff’s matrix-tree theorem in which a large class of combinatorial objects are represented by non-Gaussian Grassmann integrals. As a special case, we show that unrooted spanning forests, which arise as a q→0 limit of the Potts model, can be represented by a Grassmann theory involving a Gaussian term and a particular bilocal four-fermion term. We show that this latter model can be mapped, to all orders in perturbation theory, onto the N-vector model at N=-1 or, equivalently, onto the σ model taking values in the unit supersphere in R1|2. It follows that, in two dimensions, this fermionic model is perturbatively asymptotically free.

Nonlinear dynamic model for visual object tracking on Grassmann manifolds with partial occlusion handling.

PubMed

Khan, Zulfiqar Hasan; Gu, Irene Yu-Hua

2013-12-01

This paper proposes a novel Bayesian online learning and tracking scheme for video objects on Grassmann manifolds. Although manifold visual object tracking is promising, large and fast nonplanar (or out-of-plane) pose changes and long-term partial occlusions of deformable objects in video remain a challenge that limits the tracking performance. The proposed method tackles these problems with the main novelties on: 1) online estimation of object appearances on Grassmann manifolds; 2) optimal criterion-based occlusion handling for online updating of object appearances; 3) a nonlinear dynamic model for both the appearance basis matrix and its velocity; and 4) Bayesian formulations, separately for the tracking process and the online learning process, that are realized by employing two particle filters: one is on the manifold for generating appearance particles and another on the linear space for generating affine box particles. Tracking and online updating are performed in an alternating fashion to mitigate the tracking drift. Experiments using the proposed tracker on videos captured by a single dynamic/static camera have shown robust tracking performance, particularly for scenarios when target objects contain significant nonplanar pose changes and long-term partial occlusions. Comparisons with eight existing state-of-the-art/most relevant manifold/nonmanifold trackers with evaluations have provided further support to the proposed scheme.

Lattice Methods and the Nuclear Few- and Many-Body Problem

NASA Astrophysics Data System (ADS)

Lee, Dean

This chapter builds upon the review of lattice methods and effective field theory of the previous chapter. We begin with a brief overview of lattice calculations using chiral effective field theory and some recent applications. We then describe several methods for computing scattering on the lattice. After that we focus on the main goal, explaining the theory and algorithms relevant to lattice simulations of nuclear few- and many-body systems. We discuss the exact equivalence of four different lattice formalisms, the Grassmann path integral, transfer matrix operator, Grassmann path integral with auxiliary fields, and transfer matrix operator with auxiliary fields. Along with our analysis we include several coding examples and a number of exercises for the calculations of few- and many-body systems at leading order in chiral effective field theory.

Anticommutative extension of the Adler map

NASA Astrophysics Data System (ADS)

Konstantinou-Rizos, S.; Mikhailov, A. V.

2016-07-01

We construct a noncommutative (Grassmann) extension of the well-known Adler Yang-Baxter map. It satisfies the Yang-Baxter equation, it is reversible and birational. Our extension preserves all the properties of the original map except the involutivity.

Canonical Formulation of Supermechanics

NASA Astrophysics Data System (ADS)

Matsumoto, S.

1990-07-01

The canonical formulation of a theory of dynamical systems with both Grassmann even and odd variables is investigated. The sufficient condition for the system being analytically solvable is given. The geodesic motion of a particle in the super Poincaré upper half plane is solved as an example.

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2006-11-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2010-06-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Rejoice in unexpected gifts from parrots and butterflies

NASA Astrophysics Data System (ADS)

Lakhtakia, Akhlesh

2016-04-01

New biological structures usually evolve from gradual modifications of old structures. Sometimes, biological structures contain hidden features, possibly vestigial. In addition to learning about functionalities, mechanisms, and structures readily apparent in nature, one must be alive to hidden features that could be useful. This aspect of engineered biomimicry is exemplified by two optical structures of psittacine and lepidopteran provenances. In both examples, a schemochrome is hidden by pigments.

Dimension independence in exterior algebra.

PubMed Central

Hawrylycz, M

1995-01-01

The identities between homogeneous expressions in rank 1 vectors and rank n - 1 covectors in a Grassmann-Cayley algebra of rank n, in which one set occurs multilinearly, are shown to represent a set of dimension-independent identities. The theorem yields an infinite set of nontrivial geometric identities from a given identity. PMID:11607520

On an Assumption of Geometric Foundation of Numbers

ERIC Educational Resources Information Center

Anatriello, Giuseppina; Tortoriello, Francesco Saverio; Vincenzi, Giovanni

2016-01-01

In line with the latest positions of Gottlob Frege, this article puts forward the hypothesis that the cognitive bases of mathematics are geometric in nature. Starting from the geometry axioms of the "Elements" of Euclid, we introduce a geometric theory of proportions along the lines of the one introduced by Grassmann in…

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Commitment-Based Learning of Hidden Linguistic Structures

ERIC Educational Resources Information Center

Akers, Crystal Gayle

2012-01-01

Learners must simultaneously learn a grammar and a lexicon from observed forms, yet some structures that the grammar and lexicon reference are unobservable in the acoustic signal. Moreover, these "hidden" structures interact: the grammar maps an underlying form to a particular interpretation. Learning one structure depends on learning…

Detect and exploit hidden structure in fatty acid signature data

USGS Publications Warehouse

Budge, Suzanne; Bromaghin, Jeffrey F.; Thiemann, Gregory

2017-01-01

Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis (QFASA) is a popular method that continues to be refined and extended. Quantitative fatty acid signature analysis is based on differences in the signatures of prey types, often species, which are recognized and designated by investigators. Similarly, predator signatures may be structured by known factors such as sex or age class, and the season or region of sample collection. The recognized structure in signature data inherently influences QFASA results in important and typically beneficial ways. However, predator and prey signatures may contain additional, hidden structure that investigators either choose not to incorporate into an analysis or of which they are unaware, being caused by unknown ecological mechanisms. Hidden structure also influences QFASA results, most often negatively. We developed a new method to explore signature data for hidden structure, called divisive magnetic clustering (DIMAC). Our DIMAC approach is based on the same distance measure used in diet estimation, closely linking methods of data exploration and parameter estimation, and it does not require data transformation or distributional assumptions, as do many multivariate ordination methods in common use. We investigated the potential benefits of the DIMAC method to detect and subsequently exploit hidden structure in signature data using two prey signature libraries with quite different characteristics. We found that the existence of hidden structure in prey signatures can increase the confusion between prey types and thereby reduce the accuracy and precision of QFASA diet estimates. Conversely, the detection and exploitation of hidden structure represent a potential opportunity to improve predator diet estimates and may lead to new insights into the ecology of either predator or prey. The DIMAC algorithm is implemented in the R diet estimation package qfasar.

Hidden Farmworker Labor Camps in North Carolina: An Indicator of Structural Vulnerability

PubMed Central

Summers, Phillip; Quandt, Sara A.; Talton, Jennifer W.; Galván, Leonardo

2015-01-01

Objectives. We used geographic information systems (GIS) to delineate whether farmworker labor camps were hidden and to determine whether hidden camps differed from visible camps in terms of physical and resident characteristics. Methods. We collected data using observation, interview, and public domain GIS data for 180 farmworker labor camps in east central North Carolina. A hidden camp was defined as one that was at least 0.15 miles from an all-weather road or located behind natural or manufactured objects. Hidden camps were compared with visible camps in terms of physical and resident characteristics. Results. More than one third (37.8%) of the farmworker labor camps were hidden. Hidden camps were significantly larger (42.7% vs 17.0% with 21 or more residents; P ≤ .001; and 29.4% vs 13.5% with 3 or more dwellings; P = .002) and were more likely to include barracks (50% vs 19.6%; P ≤ .001) than were visible camps. Conclusions. Poor housing conditions in farmworker labor camps often go unnoticed because they are hidden in the rural landscape, increasing farmworker vulnerability. Policies that promote greater community engagement with farmworker labor camp residents to reduce structural vulnerability should be considered. PMID:26469658

The Politics of the Hidden Curriculum

ERIC Educational Resources Information Center

Giroux, Henry A.

1977-01-01

Schools teach much more than the traditional curriculum. They also teach a "hidden curriculum"--those unstated norms, values, and beliefs promoting hierarchic and authoritarian social relations that are transmitted to students through the underlying educational structure. Discusses the effects of the "hidden curriculum" on the…

Multitask TSK fuzzy system modeling by mining intertask common hidden structure.

PubMed

Jiang, Yizhang; Chung, Fu-Lai; Ishibuchi, Hisao; Deng, Zhaohong; Wang, Shitong

2015-03-01

The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.

Polynomial solution of quantum Grassmann matrices

NASA Astrophysics Data System (ADS)

Tierz, Miguel

2017-05-01

We study a model of quantum mechanical fermions with matrix-like index structure (with indices N and L) and quartic interactions, recently introduced by Anninos and Silva. We compute the partition function exactly with q-deformed orthogonal polynomials (Stieltjes-Wigert polynomials), for different values of L and arbitrary N. From the explicit evaluation of the thermal partition function, the energy levels and degeneracies are determined. For a given L, the number of states of different energy is quadratic in N, which implies an exponential degeneracy of the energy levels. We also show that at high-temperature we have a Gaussian matrix model, which implies a symmetry that swaps N and L, together with a Wick rotation of the spectral parameter. In this limit, we also write the partition function, for generic L and N, in terms of a single generalized Hermite polynomial.

Sacrificial bonds and hidden length in biomaterials -- a kinetic description of strength and toughness in bone

NASA Astrophysics Data System (ADS)

Lieou, Charles K. C.; Elbanna, Ahmed E.; Carlson, Jean M.

2013-03-01

Sacrificial bonds and hidden length in structural molecules account for the greatly increased fracture toughness of biological materials compared to synthetic materials without such structural features, by providing a molecular-scale mechanism of energy dissipation. One example of occurrence of sacrificial bonds and hidden length is in the polymeric glue connection between collagen fibrils in animal bone. In this talk, we propose a simple kinetic model that describes the breakage of sacrificial bonds and the revelation of hidden length, based on Bell's theory. We postulate a master equation governing the rates of bond breakage and formation, at the mean-field level, allowing for the number of bonds and hidden lengths to take up non-integer values between successive, discrete bond-breakage events. This enables us to predict the mechanical behavior of a quasi-one-dimensional ensemble of polymers at different stretching rates. We find that both the rupture peak heights and maximum stretching distance increase with the stretching rate. In addition, our theory naturally permits the possibility of self-healing in such biological structures.

Inferring hidden causal relations between pathway members using reduced Google matrix of directed biological networks

PubMed Central

2018-01-01

Signaling pathways represent parts of the global biological molecular network which connects them into a seamless whole through complex direct and indirect (hidden) crosstalk whose structure can change during development or in pathological conditions. We suggest a novel methodology, called Googlomics, for the structural analysis of directed biological networks using spectral analysis of their Google matrices, using parallels with quantum scattering theory, developed for nuclear and mesoscopic physics and quantum chaos. We introduce analytical “reduced Google matrix” method for the analysis of biological network structure. The method allows inferring hidden causal relations between the members of a signaling pathway or a functionally related group of genes. We investigate how the structure of hidden causal relations can be reprogrammed as a result of changes in the transcriptional network layer during cancerogenesis. The suggested Googlomics approach rigorously characterizes complex systemic changes in the wiring of large causal biological networks in a computationally efficient way. PMID:29370181

Developing Educational Programs: Overcoming the Hidden Curriculum.

ERIC Educational Resources Information Center

Giroux, Henry A.

1978-01-01

What students learn in school is determined more by the hidden curriculum of rigid classroom structures and power relationships than formal curriculum. A less alienating classroom environment must replace these traditional structures, such as tracking, grading, and student powerlessness, if education is really to be reformed. (SJL)

On representations of the filiform Lie superalgebra Lm,n

NASA Astrophysics Data System (ADS)

Wang, Qi; Chen, Hongjia; Liu, Wende

2015-11-01

In this paper, we study the representations for the filiform Lie superalgebras Lm,n, a particular class of nilpotent Lie superalgebras. We determine the minimal dimension of a faithful module over Lm,n using the theory of linear algebra. In addition, using the method of Feingold and Frenkel (1985), we construct some finite and infinite dimensional modules over Lm,n on the Grassmann algebra and the mixed Clifford-Weyl algebra.

Harmonic maps of S into a complex Grassmann manifold.

PubMed

Chern, S S; Wolfson, J

1985-04-01

Let G(k, n) be the Grassmann manifold of all C(k) in C(n), the complex spaces of dimensions k and n, respectively, or, what is the same, the manifold of all projective spaces P(k-1) in P(n-1), so that G(1, n) is the complex projective space P(n-1) itself. We study harmonic maps of the two-dimensional sphere S(2) into G(k, n). The case k = 1 has been the subject of investigation by several authors [see, for example, Din, A. M. & Zakrzewski, W. J. (1980) Nucl. Phys. B 174, 397-406; Eells, J. & Wood, J. C. (1983) Adv. Math. 49, 217-263; and Wolfson, J. G. Trans. Am. Math. Soc., in press]. The harmonic maps S(2) --> G(2, 4) have been studied by Ramanathan [Ramanathan, J. (1984) J. Differ. Geom. 19, 207-219]. We shall describe all harmonic maps S(2) --> G(2, n). The method is based on several geometrical constructions, which lead from a given harmonic map to new harmonic maps, in which the image projective spaces are related by "fundamental collineations." The key result is the degeneracy of some fundamental collineations, which is a global consequence, following from the fact that the domain manifold is S(2). The method extends to G(k, n).

The Hidden Curriculum, Ethics Teaching, and the Structure of Medical Education.

ERIC Educational Resources Information Center

Hafferty, Frederic W.; Franks, Ronald

1994-01-01

Issues concerning inclusion of ethics instruction in the medical school curriculum are discussed, including whether ethics should be presented as a body of knowledge or matter of professional identity and the "hidden curriculum" of medicine as a form of socialization. Recommendations for the structuring of an ethics curriculum are…

Wireless ultrasonic wavefield imaging via laser for hidden damage detection inside a steel box girder bridge

NASA Astrophysics Data System (ADS)

An, Yun-Kyu; Song, Homin; Sohn, Hoon

2014-09-01

This paper presents a wireless ultrasonic wavefield imaging (WUWI) technique for detecting hidden damage inside a steel box girder bridge. The proposed technique allows (1) complete wireless excitation of piezoelectric transducers and noncontact sensing of the corresponding responses using laser beams, (2) autonomous damage visualization without comparing against baseline data previously accumulated from the pristine condition of a target structure and (3) robust damage diagnosis even for real structures with complex structural geometries. First, a new WUWI hardware system was developed by integrating optoelectronic-based signal transmitting and receiving devices and a scanning laser Doppler vibrometer. Next, a damage visualization algorithm, self-referencing f-k filter (SRF), was introduced to isolate and visualize only crack-induced ultrasonic modes from measured ultrasonic wavefield images. Finally, the performance of the proposed technique was validated through hidden crack visualization at a decommissioned Ramp-G Bridge in South Korea. The experimental results reveal that the proposed technique instantaneously detects and successfully visualizes hidden cracks even in the complex structure of a real bridge.

Discrete Wigner formalism for qubits and noncontextuality of Clifford gates on qubit stabilizer states

NASA Astrophysics Data System (ADS)

Kocia, Lucas; Love, Peter

2017-12-01

We show that qubit stabilizer states can be represented by non-negative quasiprobability distributions associated with a Wigner-Weyl-Moyal formalism where Clifford gates are positive state-independent maps. This is accomplished by generalizing the Wigner-Weyl-Moyal formalism to three generators instead of two—producing an exterior, or Grassmann, algebra—which results in Clifford group gates for qubits that act as a permutation on the finite Weyl phase space points naturally associated with stabilizer states. As a result, a non-negative probability distribution can be associated with each stabilizer state's three-generator Wigner function, and these distributions evolve deterministically to one another under Clifford gates. This corresponds to a hidden variable theory that is noncontextual and local for qubit Clifford gates while Clifford (Pauli) measurements have a context-dependent representation. Equivalently, we show that qubit Clifford gates can be expressed as propagators within the three-generator Wigner-Weyl-Moyal formalism whose semiclassical expansion is truncated at order ℏ0 with a finite number of terms. The T gate, which extends the Clifford gate set to one capable of universal quantum computation, requires a semiclassical expansion of the propagator to order ℏ1. We compare this approach to previous quasiprobability descriptions of qubits that relied on the two-generator Wigner-Weyl-Moyal formalism and find that the two-generator Weyl symbols of stabilizer states result in a description of evolution under Clifford gates that is state-dependent, in contrast to the three-generator formalism. We have thus extended Wigner non-negative quasiprobability distributions from the odd d -dimensional case to d =2 qubits, which describe the noncontextuality of Clifford gates and contextuality of Pauli measurements on qubit stabilizer states.

Towards a Theoretical Basis for Energy Economics.

DTIC Science & Technology

1980-08-01

of Exhaustion, Journal of Political Economy, Vol 7, 1967, pp 274-286 Grassmann, P, Energie und Exergie , Brennstoff-Wdrme-Kraft, Vol 13, 1961, pp 482...Availability and Irreversibility in Thermo- dynamics, British Journal of Applied Physics, Vol 2, 1951, pp 183-192 Koefoed, J, Thermal Exergy and its...of thermodynamics and for attaching an economic value (a price) to energy in different qualities. It is ’ shown that exergy (potential amount of work

A scheme of hidden-structure attribute-based encryption with multiple authorities

NASA Astrophysics Data System (ADS)

Ling, J.; Weng, A. X.

2018-05-01

In the most of the CP-ABE schemes with hidden access structure, both all the user attributes and the key generation are managed by only one authority. The key generation efficiency will decrease as the number of user increases, and the data will encounter security issues as the only authority is attacked. We proposed a scheme of hidden-structure attribute-based encryption with multiple authorities, which introduces multiple semi-trusted attribute authorities, avoiding the threat even though one or more authorities are attacked. We also realized user revocation by managing a revocation list. Based on DBDH assumption, we proved that our scheme is of IND-CMA security. The analysis shows that our scheme improves the key generation efficiency.

Riemannian multi-manifold modeling and clustering in brain networks

NASA Astrophysics Data System (ADS)

Slavakis, Konstantinos; Salsabilian, Shiva; Wack, David S.; Muldoon, Sarah F.; Baidoo-Williams, Henry E.; Vettel, Jean M.; Cieslak, Matthew; Grafton, Scott T.

2017-08-01

This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Riemannian manifold. Distinguishing disparate time series amounts thus to clustering multiple Riemannian submanifolds. To this end, two feature-generation schemes for brain-network time series are put forth. The first one is motivated by Granger-causality arguments and uses an auto-regressive moving average model to map low-rank linear vector subspaces, spanned by column vectors of appropriately defined observability matrices, to points into the Grassmann manifold. The second one utilizes (non-linear) dependencies among network nodes by introducing kernel-based partial correlations to generate points in the manifold of positivedefinite matrices. Based on recently developed research on clustering Riemannian submanifolds, an algorithm is provided for distinguishing time series based on their Riemannian-geometry properties. Numerical tests on time series, synthetically generated from real brain-network structural connectivity matrices, reveal that the proposed scheme outperforms classical and state-of-the-art techniques in clustering brain-network states/structures.

A Representation for Fermionic Correlation Functions

NASA Astrophysics Data System (ADS)

Feldman, Joel; Knörrer, Horst; Trubowitz, Eugene

Let dμS(a) be a Gaussian measure on the finitely generated Grassmann algebra A. Given an even W(a)∈A, we construct an operator R on A such that for all f(a)∈A. This representation of the Schwinger functional iteratively builds up Feynman graphs by successively appending lines farther and farther from f. It allows the Pauli exclusion principle to be implemented quantitatively by a simple application of Gram's inequality.

An adaptive proper orthogonal decomposition method for model order reduction of multi-disc rotor system

NASA Astrophysics Data System (ADS)

Jin, Yulin; Lu, Kuan; Hou, Lei; Chen, Yushu

2017-12-01

The proper orthogonal decomposition (POD) method is a main and efficient tool for order reduction of high-dimensional complex systems in many research fields. However, the robustness problem of this method is always unsolved, although there are some modified POD methods which were proposed to solve this problem. In this paper, a new adaptive POD method called the interpolation Grassmann manifold (IGM) method is proposed to address the weakness of local property of the interpolation tangent-space of Grassmann manifold (ITGM) method in a wider parametric region. This method is demonstrated here by a nonlinear rotor system of 33-degrees of freedom (DOFs) with a pair of liquid-film bearings and a pedestal looseness fault. The motion region of the rotor system is divided into two parts: simple motion region and complex motion region. The adaptive POD method is compared with the ITGM method for the large and small spans of parameter in the two parametric regions to present the advantage of this method and disadvantage of the ITGM method. The comparisons of the responses are applied to verify the accuracy and robustness of the adaptive POD method, as well as the computational efficiency is also analyzed. As a result, the new adaptive POD method has a strong robustness and high computational efficiency and accuracy in a wide scope of parameter.

Quantum Sets and Clifford Algebras

NASA Astrophysics Data System (ADS)

Finkelstein, David

1982-06-01

The mathematical language presently used for quantum physics is a high-level language. As a lowest-level or basic language I construct a quantum set theory in three stages: (1) Classical set theory, formulated as a Clifford algebra of “ S numbers” generated by a single monadic operation, “bracing,” Br = {…}. (2) Indefinite set theory, a modification of set theory dealing with the modal logical concept of possibility. (3) Quantum set theory. The quantum set is constructed from the null set by the familiar quantum techniques of tensor product and antisymmetrization. There are both a Clifford and a Grassmann algebra with sets as basis elements. Rank and cardinality operators are analogous to Schroedinger coordinates of the theory, in that they are multiplication or “ Q-type” operators. “ P-type” operators analogous to Schroedinger momenta, in that they transform the Q-type quantities, are bracing (Br), Clifford multiplication by a set X, and the creator of X, represented by Grassmann multiplication c( X) by the set X. Br and its adjoint Br* form a Bose-Einstein canonical pair, and c( X) and its adjoint c( X)* form a Fermi-Dirac or anticanonical pair. Many coefficient number systems can be employed in this quantization. I use the integers for a discrete quantum theory, with the usual complex quantum theory as limit. Quantum set theory may be applied to a quantum time space and a quantum automaton.

Field-induced spin-density wave beyond hidden order in URu2Si2

NASA Astrophysics Data System (ADS)

Knafo, W.; Duc, F.; Bourdarot, F.; Kuwahara, K.; Nojiri, H.; Aoki, D.; Billette, J.; Frings, P.; Tonon, X.; Lelièvre-Berna, E.; Flouquet, J.; Regnault, L.-P.

2016-10-01

URu2Si2 is one of the most enigmatic strongly correlated electron systems and offers a fertile testing ground for new concepts in condensed matter science. In spite of >30 years of intense research, no consensus on the order parameter of its low-temperature hidden-order phase exists. A strong magnetic field transforms the hidden order into magnetically ordered phases, whose order parameter has also been defying experimental observation. Here, thanks to neutron diffraction under pulsed magnetic fields up to 40 T, we identify the field-induced phases of URu2Si2 as a spin-density-wave state. The transition to the spin-density wave represents a unique touchstone for understanding the hidden-order phase. An intimate relationship between this magnetic structure, the magnetic fluctuations and the Fermi surface is emphasized, calling for dedicated band-structure calculations.

Discovering Hidden Controlling Parameters using Data Analytics and Dimensional Analysis

NASA Astrophysics Data System (ADS)

Del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca

2017-11-01

Dimensional Analysis is a powerful tool, one which takes a priori information and produces important simplifications. However, if this a priori information - the list of relevant parameters - is missing a relevant quantity, then the conclusions from Dimensional Analysis will be incorrect. In this work, we present novel conclusions in Dimensional Analysis, which provide a means to detect this failure mode of missing or hidden parameters. These results are based on a restated form of the Buckingham Pi theorem that reveals a ridge function structure underlying all dimensionless physical laws. We leverage this structure by constructing a hypothesis test based on sufficient dimension reduction, allowing for an experimental data-driven detection of hidden parameters. Both theory and examples will be presented, using classical turbulent pipe flow as the working example. Keywords: experimental techniques, dimensional analysis, lurking variables, hidden parameters, buckingham pi, data analysis. First author supported by the NSF GRFP under Grant Number DGE-114747.

Unsupervised deep learning reveals prognostically relevant subtypes of glioblastoma.

PubMed

Young, Jonathan D; Cai, Chunhui; Lu, Xinghua

2017-10-03

One approach to improving the personalized treatment of cancer is to understand the cellular signaling transduction pathways that cause cancer at the level of the individual patient. In this study, we used unsupervised deep learning to learn the hierarchical structure within cancer gene expression data. Deep learning is a group of machine learning algorithms that use multiple layers of hidden units to capture hierarchically related, alternative representations of the input data. We hypothesize that this hierarchical structure learned by deep learning will be related to the cellular signaling system. Robust deep learning model selection identified a network architecture that is biologically plausible. Our model selection results indicated that the 1st hidden layer of our deep learning model should contain about 1300 hidden units to most effectively capture the covariance structure of the input data. This agrees with the estimated number of human transcription factors, which is approximately 1400. This result lends support to our hypothesis that the 1st hidden layer of a deep learning model trained on gene expression data may represent signals related to transcription factor activation. Using the 3rd hidden layer representation of each tumor as learned by our unsupervised deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery of clusters of glioblastoma multiforme with differential survival. One of these clusters contained all of the glioblastoma samples with G-CIMP, a known methylation phenotype driven by the IDH1 mutation and associated with favorable prognosis, suggesting that the hidden units in the 3rd hidden layer representations captured a methylation signal without explicitly using methylation data as input. We also found differentially expressed genes and well-known mutations (NF1, IDH1, EGFR) that were uniquely correlated with each of these clusters. Exploring these unique genes and mutations will allow us to further investigate the disease mechanisms underlying each of these clusters. In summary, we show that a deep learning model can be trained to represent biologically and clinically meaningful abstractions of cancer gene expression data. Understanding what additional relationships these hidden layer abstractions have with the cancer cellular signaling system could have a significant impact on the understanding and treatment of cancer.

Hidden charged dark matter and chiral dark radiation

NASA Astrophysics Data System (ADS)

Ko, P.; Nagata, Natsumi; Tang, Yong

2017-10-01

In the light of recent possible tensions in the Hubble constant H0 and the structure growth rate σ8 between the Planck and other measurements, we investigate a hidden-charged dark matter (DM) model where DM interacts with hidden chiral fermions, which are charged under the hidden SU(N) and U(1) gauge interactions. The symmetries in this model assure these fermions to be massless. The DM in this model, which is a Dirac fermion and singlet under the hidden SU(N), is also assumed to be charged under the U(1) gauge symmetry, through which it can interact with the chiral fermions. Below the confinement scale of SU(N), the hidden quark condensate spontaneously breaks the U(1) gauge symmetry such that there remains a discrete symmetry, which accounts for the stability of DM. This condensate also breaks a flavor symmetry in this model and Nambu-Goldstone bosons associated with this flavor symmetry appear below the confinement scale. The hidden U(1) gauge boson and hidden quarks/Nambu-Goldstone bosons are components of dark radiation (DR) above/below the confinement scale. These light fields increase the effective number of neutrinos by δNeff ≃ 0.59 above the confinement scale for N = 2, resolving the tension in the measurements of the Hubble constant by Planck and Hubble Space Telescope if the confinement scale is ≲1 eV. DM and DR continuously scatter with each other via the hidden U(1) gauge interaction, which suppresses the matter power spectrum and results in a smaller structure growth rate. The DM sector couples to the Standard Model sector through the exchange of a real singlet scalar mixing with the Higgs boson, which makes it possible to probe our model in DM direct detection experiments. Variants of this model are also discussed, which may offer alternative ways to investigate this scenario.

A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

PubMed Central

Wen, Hui; Xie, Weixin; Pei, Jihong

2016-01-01

This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-04-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

The hidden and informal curriculum across the continuum of training: A cross-sectional qualitative study.

PubMed

Doja, Asif; Bould, M Dylan; Clarkin, Chantalle; Eady, Kaylee; Sutherland, Stephanie; Writer, Hilary

2016-01-01

The hidden and informal curricula refer to learning in response to unarticulated processes and constraints, falling outside the formal medical curriculum. The hidden curriculum has been identified as requiring attention across all levels of learning. We sought to assess the knowledge and perceptions of the hidden and informal curricula across the continuum of learning at a single institution. Focus groups were held with undergraduate and postgraduate learners and faculty to explore knowledge and perceptions relating to the hidden and informal curricula. Thematic analysis was conducted both inductively by research team members and deductively using questions structured by the existing literature. Participants highlighted several themes related to the presence of the hidden and informal curricula in medical training and practice, including: the privileging of some specialties over others; the reinforcement of hierarchies within medicine; and a culture of tolerance towards unprofessional behaviors. Participants acknowledged the importance of role modeling in the development of professional identities and discussed the deterioration in idealism that occurs. Common issues pertaining to the hidden curriculum exist across all levels of learners, including faculty. Increased awareness of these issues could allow for the further development of methods to address learning within the hidden curriculum.

EPR and Bell's theorem: A critical review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stapp, H.P.

1991-01-01

The argument of Einstein, Podolsky, and Rosen is reviewed with attention to logical structure and character of assumptions. Bohr's reply is discussed. Bell's contribution is formulated without use of hidden variables, and efforts to equate hidden variables to realism are critically examined. An alternative derivation of nonlocality that makes no use of hidden variables, microrealism, counterfactual definiteness, or any other assumption alien to orthodox quantum thinking is described in detail, with particular attention to the quartet or broken-square question.

STRUCTURAL AND HIDDEN BARRIERS TO A LOCAL PRIMARY HEALTH CARE INFRASTRUCTURE: AUTONOMY, DECISIONS ABOUT PRIMARY HEALTH CARE, AND THE CENTRALITY AND SIGNIFICANCE OF POWER.

PubMed

Freed, Christopher R; Hansberry, Shantisha T; Arrieta, Martha I

2013-09-01

To examine a local primary health care infrastructure and the reality of primary health care from the perspective of residents of a small, urban community in the southern United States. Data derive from 13 semi-structured focus groups, plus three semi-structured interviews, and were analyzed inductively consistent with a grounded theory approach. Structural barriers to the local primary health care infrastructure include transportation, clinic and appointment wait time, and co-payments and health insurance. Hidden barriers consist of knowledge about local health care services, non-physician gatekeepers, and fear of medical care. Community residents have used home remedies and the emergency department at the local academic medical center to manage these structural and hidden barriers. Findings might not generalize to primary health care infrastructures in other communities, respondent perspectives can be biased, and the data are subject to various interpretations and conceptual and thematic frameworks. Nevertheless, the structural and hidden barriers to the local primary health care infrastructure have considerably diminished the autonomy community residents have been able to exercise over their decisions about primary health care, ultimately suggesting that efforts concerned with increasing the access of medically underserved groups to primary health care in local communities should recognize the centrality and significance of power. This study addresses a gap in the sociological literature regarding the impact of specific barriers to primary health care among medically underserved groups.

Hidden asymmetry and forward-backward correlations

NASA Astrophysics Data System (ADS)

Bialas, A.; Zalewski, K.

2010-09-01

A model-independent method of studying the forward-backward correlations in symmetric high-energy processes is developed. The method allows a systematic study of the properties of various particle sources and allows one to uncover asymmetric structures hidden in symmetric hadron-hadron and nucleus-nucleus inelastic reactions.

Momentum-resolved hidden-order gap reveals symmetry breaking and origin of entropy loss in URu2Si2

NASA Astrophysics Data System (ADS)

Bareille, C.; Boariu, F. L.; Schwab, H.; Lejay, P.; Reinert, F.; Santander-Syro, A. F.

2014-07-01

Spontaneous symmetry breaking in physical systems leads to salient phenomena at all scales, from the Higgs mechanism and the emergence of the mass of the elementary particles, to superconductivity and magnetism in solids. The hidden-order state arising below 17.5 K in URu2Si2 is a puzzling example of one of such phase transitions: its associated broken symmetry and gap structure have remained longstanding riddles. Here we directly image how, across the hidden-order transition, the electronic structure of URu2Si2 abruptly reconstructs. We observe an energy gap of 7 meV opening over 70% of a large diamond-like heavy-fermion Fermi surface, resulting in the formation of four small Fermi petals, and a change in the electronic periodicity from body-centred tetragonal to simple tetragonal. Our results explain the large entropy loss in the hidden-order phase, and the similarity between this phase and the high-pressure antiferromagnetic phase found in quantum-oscillation experiments.

Design Graphics

NASA Technical Reports Server (NTRS)

1990-01-01

A mathematician, David R. Hedgley, Jr. developed a computer program that considers whether a line in a graphic model of a three-dimensional object should or should not be visible. Known as the Hidden Line Computer Code, the program automatically removes superfluous lines and displays an object from a specific viewpoint, just as the human eye would see it. An example of how one company uses the program is the experience of Birdair which specializes in production of fabric skylights and stadium covers. The fabric called SHEERFILL is a Teflon coated fiberglass material developed in cooperation with DuPont Company. SHEERFILL glazed structures are either tension structures or air-supported tension structures. Both are formed by patterned fabric sheets supported by a steel or aluminum frame or cable network. Birdair uses the Hidden Line Computer Code, to illustrate a prospective structure to an architect or owner. The program generates a three- dimensional perspective with the hidden lines removed. This program is still used by Birdair and continues to be commercially available to the public.

Sacrificial bonds and hidden length in biomaterials: A kinetic constitutive description of strength and toughness in bone

NASA Astrophysics Data System (ADS)

Lieou, Charles K. C.; Elbanna, Ahmed E.; Carlson, Jean M.

2013-07-01

Sacrificial bonds and hidden length in structural molecules account for the greatly increased fracture toughness of biological materials compared to synthetic materials without such structural features by providing a molecular-scale mechanism for energy dissipation. One example is in the polymeric glue connection between collagen fibrils in animal bone. In this paper we propose a simple kinetic model that describes the breakage of sacrificial bonds and the release of hidden length, based on Bell's theory. We postulate a master equation governing the rates of bond breakage and formation. This enables us to predict the mechanical behavior of a quasi-one-dimensional ensemble of polymers at different stretching rates. We find that both the rupture peak heights and maximum stretching distance increase with the stretching rate. In addition, our theory naturally permits the possibility of self-healing in such biological structures.

Infinite hidden conditional random fields for human behavior analysis.

PubMed

Bousmalis, Konstantinos; Zafeiriou, Stefanos; Morency, Louis-Philippe; Pantic, Maja

2013-01-01

Hidden conditional random fields (HCRFs) are discriminative latent variable models that have been shown to successfully learn the hidden structure of a given classification problem (provided an appropriate validation of the number of hidden states). In this brief, we present the infinite HCRF (iHCRF), which is a nonparametric model based on hierarchical Dirichlet processes and is capable of automatically learning the optimal number of hidden states for a classification task. We show how we learn the model hyperparameters with an effective Markov-chain Monte Carlo sampling technique, and we explain the process that underlines our iHCRF model with the Restaurant Franchise Rating Agencies analogy. We show that the iHCRF is able to converge to a correct number of represented hidden states, and outperforms the best finite HCRFs--chosen via cross-validation--for the difficult tasks of recognizing instances of agreement, disagreement, and pain. Moreover, the iHCRF manages to achieve this performance in significantly less total training, validation, and testing time.

A Top-down versus a Bottom-up Hidden-variables Description of the Stern-Gerlach Experiment

NASA Astrophysics Data System (ADS)

Arsenijević, M.; Jeknić-Dugić, J.; Dugić, M.

We employ the Stern-Gerlach experiment to highlight the basics of a minimalist, non-interpretational top-down approach to quantum foundations. Certain benefits of the "quantum structural studies" (QSS) highlightedhere are detected and discussed. While the top-down approach can be described without making any reference to the fundamental structure of a closed system, the hidden variables (HV) theory á la Bohm proves to be more subtle than it is typically regarded.

Modelling proteins' hidden conformations to predict antibiotic resistance

NASA Astrophysics Data System (ADS)

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-10-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM's specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models' prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.

Modelling proteins’ hidden conformations to predict antibiotic resistance

PubMed Central

Hart, Kathryn M.; Ho, Chris M. W.; Dutta, Supratik; Gross, Michael L.; Bowman, Gregory R.

2016-01-01

TEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design. PMID:27708258

Multivariate generalized hidden Markov regression models with random covariates: Physical exercise in an elderly population.

PubMed

Punzo, Antonio; Ingrassia, Salvatore; Maruotti, Antonello

2018-04-22

A time-varying latent variable model is proposed to jointly analyze multivariate mixed-support longitudinal data. The proposal can be viewed as an extension of hidden Markov regression models with fixed covariates (HMRMFCs), which is the state of the art for modelling longitudinal data, with a special focus on the underlying clustering structure. HMRMFCs are inadequate for applications in which a clustering structure can be identified in the distribution of the covariates, as the clustering is independent from the covariates distribution. Here, hidden Markov regression models with random covariates are introduced by explicitly specifying state-specific distributions for the covariates, with the aim of improving the recovering of the clusters in the data with respect to a fixed covariates paradigm. The hidden Markov regression models with random covariates class is defined focusing on the exponential family, in a generalized linear model framework. Model identifiability conditions are sketched, an expectation-maximization algorithm is outlined for parameter estimation, and various implementation and operational issues are discussed. Properties of the estimators of the regression coefficients, as well as of the hidden path parameters, are evaluated through simulation experiments and compared with those of HMRMFCs. The method is applied to physical activity data. Copyright © 2018 John Wiley & Sons, Ltd.

Algorithms for Hidden Markov Models Restricted to Occurrences of Regular Expressions

PubMed Central

Tataru, Paula; Sand, Andreas; Hobolth, Asger; Mailund, Thomas; Pedersen, Christian N. S.

2013-01-01

Hidden Markov Models (HMMs) are widely used probabilistic models, particularly for annotating sequential data with an underlying hidden structure. Patterns in the annotation are often more relevant to study than the hidden structure itself. A typical HMM analysis consists of annotating the observed data using a decoding algorithm and analyzing the annotation to study patterns of interest. For example, given an HMM modeling genes in DNA sequences, the focus is on occurrences of genes in the annotation. In this paper, we define a pattern through a regular expression and present a restriction of three classical algorithms to take the number of occurrences of the pattern in the hidden sequence into account. We present a new algorithm to compute the distribution of the number of pattern occurrences, and we extend the two most widely used existing decoding algorithms to employ information from this distribution. We show experimentally that the expectation of the distribution of the number of pattern occurrences gives a highly accurate estimate, while the typical procedure can be biased in the sense that the identified number of pattern occurrences does not correspond to the true number. We furthermore show that using this distribution in the decoding algorithms improves the predictive power of the model. PMID:24833225

Bayesian structural inference for hidden processes.

PubMed

Strelioff, Christopher C; Crutchfield, James P

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ε-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ε-machines, irrespective of estimated transition probabilities. Properties of ε-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

Bayesian structural inference for hidden processes

NASA Astrophysics Data System (ADS)

Strelioff, Christopher C.; Crutchfield, James P.

2014-04-01

We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ɛ-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ɛ-machines, irrespective of estimated transition probabilities. Properties of ɛ-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

The use of exergetic indicators in the food industry - A review.

PubMed

Zisopoulos, Filippos K; Rossier-Miranda, Francisco J; van der Goot, Atze Jan; Boom, Remko M

2017-01-02

Assessment of sustainability will become more relevant for the food industry in the years to come. Analysis based on exergy, including the use of exergetic indicators and Grassmann diagrams, is a useful tool for the quantitative and qualitative assessment of the efficiency of industrial food chains. In this paper, we review the methodology of exergy analysis and the exergetic indicators that are most appropriate for use in the food industry. The challenges of applying exergy analysis in industrial food chains and the specific features of food processes are also discussed.

Contractions from grading

NASA Astrophysics Data System (ADS)

Krishnan, Chethan; Raju, Avinash

2018-04-01

We note that large classes of contractions of algebras that arise in physics can be understood purely algebraically via identifying appropriate Zm-gradings (and their generalizations) on the parent algebra. This includes various types of flat space/Carroll limits of finite and infinite dimensional (A)dS algebras, as well as Galilean and Galilean conformal algebras. Our observations can be regarded as providing a natural context for the Grassmann approach of Krishnan et al. [J. High Energy Phys. 2014(3), 36]. We also introduce a related notion, which we call partial grading, that arises naturally in this context.

A fast hidden line algorithm for plotting finite element models

NASA Technical Reports Server (NTRS)

Jones, G. K.

1982-01-01

Effective plotting of finite element models requires the use of fast hidden line plot techniques that provide interactive response. A high speed hidden line technique was developed to facilitate the plotting of NASTRAN finite element models. Based on testing using 14 different models, the new hidden line algorithm (JONES-D) appears to be very fast: its speed equals that for normal (all lines visible) plotting and when compared to other existing methods it appears to be substantially faster. It also appears to be very reliable: no plot errors were observed using the new method to plot NASTRAN models. The new algorithm was made part of the NPLOT NASTRAN plot package and was used by structural analysts for normal production tasks.

A composite model for the 750 GeV diphoton excess

DOE PAGES

Harigaya, Keisuke; Nomura, Yasunori

2016-03-14

We study a simple model in which the recently reported 750 GeV diphoton excess arises from a composite pseudo Nambu-Goldstone boson — hidden pion — produced by gluon fusion and decaying into two photons. The model only introduces an extra hidden gauge group at the TeV scale with a vectorlike quark in the bifundamental representation of the hidden and standard model gauge groups. We calculate the masses of all the hidden pions and analyze their experimental signatures and constraints. We find that two colored hidden pions must be near the current experimental limits, and hence are probed in the nearmore » future. We study physics of would-be stable particles — the composite states that do not decay purely by the hidden and standard model gauge dynamics — in detail, including constraints from cosmology. We discuss possible theoretical structures above the TeV scale, e.g. conformal dynamics and supersymmetry, and their phenomenological implications. We also discuss an extension of the minimal model in which there is an extra hidden quark that is singlet under the standard model and has a mass smaller than the hidden dynamical scale. This provides two standard model singlet hidden pions that can both be viewed as diphoton/diboson resonances produced by gluon fusion. We discuss several scenarios in which these (and other) resonances can be used to explain various excesses seen in the LHC data.« less

Parsing Social Network Survey Data from Hidden Populations Using Stochastic Context-Free Grammars

PubMed Central

Poon, Art F. Y.; Brouwer, Kimberly C.; Strathdee, Steffanie A.; Firestone-Cruz, Michelle; Lozada, Remedios M.; Kosakovsky Pond, Sergei L.; Heckathorn, Douglas D.; Frost, Simon D. W.

2009-01-01

Background Human populations are structured by social networks, in which individuals tend to form relationships based on shared attributes. Certain attributes that are ambiguous, stigmatized or illegal can create a ÔhiddenÕ population, so-called because its members are difficult to identify. Many hidden populations are also at an elevated risk of exposure to infectious diseases. Consequently, public health agencies are presently adopting modern survey techniques that traverse social networks in hidden populations by soliciting individuals to recruit their peers, e.g., respondent-driven sampling (RDS). The concomitant accumulation of network-based epidemiological data, however, is rapidly outpacing the development of computational methods for analysis. Moreover, current analytical models rely on unrealistic assumptions, e.g., that the traversal of social networks can be modeled by a Markov chain rather than a branching process. Methodology/Principal Findings Here, we develop a new methodology based on stochastic context-free grammars (SCFGs), which are well-suited to modeling tree-like structure of the RDS recruitment process. We apply this methodology to an RDS case study of injection drug users (IDUs) in Tijuana, México, a hidden population at high risk of blood-borne and sexually-transmitted infections (i.e., HIV, hepatitis C virus, syphilis). Survey data were encoded as text strings that were parsed using our custom implementation of the inside-outside algorithm in a publicly-available software package (HyPhy), which uses either expectation maximization or direct optimization methods and permits constraints on model parameters for hypothesis testing. We identified significant latent variability in the recruitment process that violates assumptions of Markov chain-based methods for RDS analysis: firstly, IDUs tended to emulate the recruitment behavior of their own recruiter; and secondly, the recruitment of like peers (homophily) was dependent on the number of recruits. Conclusions SCFGs provide a rich probabilistic language that can articulate complex latent structure in survey data derived from the traversal of social networks. Such structure that has no representation in Markov chain-based models can interfere with the estimation of the composition of hidden populations if left unaccounted for, raising critical implications for the prevention and control of infectious disease epidemics. PMID:19738904

Hidden One-Dimensional Electronic Structure of η-Mo_4O_11

NASA Astrophysics Data System (ADS)

Gweon, G.-H.; Mo, S.-K.; Allen, J. W.; Höchst, H.; Sarrao, J. L.; Fisk, Z.

2002-03-01

η-Mo_4O_11 is a layered metal that undergoes two charge density wave (CDW) transitions at 109 K and 30 K, and is unique in showing a bulk quantum Hall effect. Research so far indicates that this material has a ``hidden one-dimensional'' (hidden-1d) Fermi surface (FS) in the normal state (T > 109 K), whose nesting property drives the 109 K CDW formation. Here, we directly confirm this picture by angle resolved photoemission spectroscopy (ARPES). We also observe a gap opening associated with the 109 K transition. Most interesting, this material shows the same ARPES line shape anomalies that suggest electron fractionalization in other hidden-1d materials like NaMo_6O_17 and KMo_6O_17. Studies of the 30 K transition are in progress.

What the Shadow Knows: Exploring the Hidden Dimensions of the Consumer Metaphor in Management Education

ERIC Educational Resources Information Center

Gross, Michael A.; Hogler, Raymond

2005-01-01

This article aims to uncover hidden dimensions of the metaphor of consumerism in management education. By exploring the metaphor, the authors elucidate the implicit claims in the assertion that teachers produce business education and students consume that product. The image of commodification structures a discourse that involves conceptions of…

High-frequency guided ultrasonic waves for hidden defect detection in multi-layered aircraft structures.

PubMed

Masserey, Bernard; Raemy, Christian; Fromme, Paul

2014-09-01

Aerospace structures often contain multi-layered metallic components where hidden defects such as fatigue cracks and localized disbonds can develop, necessitating non-destructive testing. Employing standard wedge transducers, high frequency guided ultrasonic waves that penetrate through the complete thickness were generated in a model structure consisting of two adhesively bonded aluminium plates. Interference occurs between the wave modes during propagation along the structure, resulting in a frequency dependent variation of the energy through the thickness with distance. The wave propagation along the specimen was measured experimentally using a laser interferometer. Good agreement with theoretical predictions and two-dimensional finite element simulations was found. Significant propagation distance with a strong, non-dispersive main wave pulse was achieved. The interaction of the high frequency guided ultrasonic waves with small notches in the aluminium layer facing the sealant and on the bottom surface of the multilayer structure was investigated. Standard pulse-echo measurements were conducted to verify the detection sensitivity and the influence of the stand-off distance predicted from the finite element simulations. The results demonstrated the potential of high frequency guided waves for hidden defect detection at critical and difficult to access locations in aerospace structures from a stand-off distance. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Process-Based Species Pools Reveal the Hidden Signature of Biotic Interactions Amid the Influence of Temperature Filtering.

PubMed

Lessard, Jean-Philippe; Weinstein, Ben G; Borregaard, Michael K; Marske, Katharine A; Martin, Danny R; McGuire, Jimmy A; Parra, Juan L; Rahbek, Carsten; Graham, Catherine H

2016-01-01

A persistent challenge in ecology is to tease apart the influence of multiple processes acting simultaneously and interacting in complex ways to shape the structure of species assemblages. We implement a heuristic approach that relies on explicitly defining species pools and permits assessment of the relative influence of the main processes thought to shape assemblage structure: environmental filtering, dispersal limitations, and biotic interactions. We illustrate our approach using data on the assemblage composition and geographic distribution of hummingbirds, a comprehensive phylogeny and morphological traits. The implementation of several process-based species pool definitions in null models suggests that temperature-but not precipitation or dispersal limitation-acts as the main regional filter of assemblage structure. Incorporating this environmental filter directly into the definition of assemblage-specific species pools revealed an otherwise hidden pattern of phylogenetic evenness, indicating that biotic interactions might further influence hummingbird assemblage structure. Such hidden patterns of assemblage structure call for a reexamination of a multitude of phylogenetic- and trait-based studies that did not explicitly consider potentially important processes in their definition of the species pool. Our heuristic approach provides a transparent way to explore patterns and refine interpretations of the underlying causes of assemblage structure.

Hidden simplicity of gauge theory amplitudes

NASA Astrophysics Data System (ADS)

Drummond, J. M.

2010-11-01

These notes were given as lectures at the CERN Winter School on Supergravity, Strings and Gauge Theory 2010. We describe the structure of scattering amplitudes in gauge theories, focussing on the maximally supersymmetric theory to highlight the hidden symmetries which appear. Using the Britto, Cachzo, Feng and Witten (BCFW) recursion relations we solve the tree-level S-matrix in \\ {N}=4 super Yang-Mills theory and describe how it produces a sum of invariants of a large symmetry algebra. We review amplitudes in the planar theory beyond tree level, describing the connection between amplitudes and Wilson loops, and discuss the implications of the hidden symmetries.

"The School, Whose Place Is This"? The Deep Structures of the Hidden Curriculum in Indigenous Education in Bolivia

ERIC Educational Resources Information Center

Regalsky, Pablo; Laurie, Nina

2007-01-01

In this paper we examine state and indigenous education in Bolivia. Focusing on debates about the hidden curriculum, we conceptualize the school as a political space where tensions between the overlapping jurisdictional powers of the hispanicizing state and indigenous authorities are played out. Our analysis of these tensions highlights the…

Mother-Child Communication about Location: Giving and Following Directions for Finding Hidden Objects

ERIC Educational Resources Information Center

Plumert, Jodie M.; Haggerty, Kathryn A.; Mickunas, Andrew; Herzog, Lauren; Shadrick, Courtney

2012-01-01

We conducted 2 experiments to examine how mothers structure directions to young children for finding hidden objects and how young children use these directions to guide their searches. In Experiment 1, we examined the reference frames mothers use to communicate with their 2.5-, 3-, and 3.5-year-old children about location by asking mothers to…

Ward identities and chiral anomalies for coupled fermionic chains

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costa, L. C.; Ferraz, A.; Mastropietro, Vieri

2013-12-15

Coupled fermionic chains are usually described by an effective model written in terms of bonding and anti-bonding fermionic fields with linear dispersion in the vicinities of the respective Fermi points. We derive for the first time exact Ward Identities (WI) for this model, proving the existence of chiral anomalies which verify the Adler-Bardeen non-renormalization property. Such WI are expected to play a crucial role in the understanding of the thermodynamic properties of the system. Our results are non-perturbative and are obtained analyzing Grassmann functional integrals by means of constructive quantum field theory methods.

Combinatorics associated with inflections and bitangents of plane quartics

NASA Astrophysics Data System (ADS)

Gizatullin, M. Kh

2013-08-01

After a preliminary survey and a description of some small Steiner systems from the standpoint of the theory of invariants of binary forms, we construct a binary Golay code (of length 24) using ideas from J. Grassmann's thesis of 1875. One of our tools is a pair of disjoint Fano planes. Another application of such pairs and properties of plane quartics is a construction of a new block design on 28 objects. This block design is a part of a dissection of the set of 288 Aronhold sevens. The dissection distributes the Aronhold sevens into 8 disjoint block designs of this type.

Bilinear approach to Kuperschmidt super-KdV type equations

NASA Astrophysics Data System (ADS)

Babalic, Corina N.; Carstea, A. S.

2018-06-01

Hirota bilinear form and soliton solutions for the super-KdV (Korteweg–de Vries) equation of Kuperschmidt (Kuper–KdV) are given. It is shown that even though the collision of supersolitons is more complicated than in the case of the supersymmetric KdV equation of Manin–Radul, the asymptotic effect of the interaction is simpler. As a physical application it is shown that the well-known FPU problem, having a phonon-mediated interaction of some internal degrees of freedom expressed through Grassmann fields, transforms to the Kuper–KdV equation in a multiple-scale approach.

Observables and density matrices embedded in dual Hilbert spaces

NASA Astrophysics Data System (ADS)

Prosen, T.; Martignon, L.; Seligman, T. H.

2015-06-01

The introduction of operator states and of observables in various fields of quantum physics has raised questions about the mathematical structures of the corresponding spaces. In the framework of third quantization it had been conjectured that we deal with Hilbert spaces although the mathematical background was not entirely clear, particularly, when dealing with bosonic operators. This in turn caused some doubts about the correct way to combine bosonic and fermionic operators or, in other words, regular and Grassmann variables. In this paper we present a formal answer to the problems on a simple and very general basis. We illustrate the resulting construction by revisiting the Bargmann transform and finding the known connection between {{L}}2({{R}}) and the Bargmann-Hilbert space. We pursue this line of thinking one step further and discuss the representations of complex extensions of linear canonical transformations as isometries between dual Hilbert spaces. We then use the formalism to give an explicit formulation for Fock spaces involving both fermions and bosons thus solving the problem at the origin of our considerations.

Automatic Hidden-Web Table Interpretation by Sibling Page Comparison

NASA Astrophysics Data System (ADS)

Tao, Cui; Embley, David W.

The longstanding problem of automatic table interpretation still illudes us. Its solution would not only be an aid to table processing applications such as large volume table conversion, but would also be an aid in solving related problems such as information extraction and semi-structured data management. In this paper, we offer a conceptual modeling solution for the common special case in which so-called sibling pages are available. The sibling pages we consider are pages on the hidden web, commonly generated from underlying databases. We compare them to identify and connect nonvarying components (category labels) and varying components (data values). We tested our solution using more than 2,000 tables in source pages from three different domains—car advertisements, molecular biology, and geopolitical information. Experimental results show that the system can successfully identify sibling tables, generate structure patterns, interpret tables using the generated patterns, and automatically adjust the structure patterns, if necessary, as it processes a sequence of hidden-web pages. For these activities, the system was able to achieve an overall F-measure of 94.5%.

Non-Equilibrium Effects on the Hidden Order of Microstructured URu2Si2

NASA Astrophysics Data System (ADS)

Winter, Laurel E.; Moll, Philip J. W.; Ramshaw, B. J.; Shekhter, Arkady; Harrison, N.; Bauer, Eric D.; McDonald, Ross D.

Despite extensive studies on the heavy-fermion URu2Si2, the order parameter associated with the hidden order state has yet to be established. It is known, however that the hidden order can be suppressed with pressure and high magnetic fields, which results in the development of antiferromagnetism, and the realization of a polarized state respectively. Focused Ion Beam lithography (FIB) of URu2Si2 has enabled high magnetic field observation of quantum oscillations in the resistance, indicating the preservation of sample quality to micron scale structures. These recent advances in FIB lithography have enabled the application of unprecedented electric fields while minimizing the effects of Joule heating in highly conductive metals at cryogenic temperatures. To this end, we have been able to create the necessary sample geometry to study the effect of an electric field upon hidden order in magnetic fields up to 15 T. Preliminary results suggest that above a characteristic threshold electric field, hidden order is suppressed revealing a state with similar magnetoresistive properties to the Kondo lattice in the absence of hidden order. Work supported by US Dept. of Energy through LANL/LDRD Program and G.T. Seaborg Institute, as well as NSF DMR-1157490 and the State of Florida.

The Hidden Ethics Curriculum in Two Canadian Psychiatry Residency Programs: A Qualitative Study.

PubMed

Gupta, Mona; Forlini, Cynthia; Lenton, Keith; Duchen, Raquel; Lohfeld, Lynne

2016-08-01

The authors describe the hidden ethics curriculum in two postgraduate psychiatry programs. Researchers investigated the formal, informal, and hidden ethics curricula at two demographically different postgraduate psychiatry programs in Canada. Using a case study design, they compared three sources: individual interviews with residents and with faculty and a semi-structured review of program documents. They identified the formal, informal, and hidden curricula at each program for six ethics topics and grouped the topics under two thematic areas. They tested the applicability of the themes against the specific examples under each topic. Results pertaining to one of the themes and its three topics are reported here. Divergences occurred between the curricula for each topic. The nature of these divergences differed according to local program characteristics. Yet, in both programs, choices for action in ethically challenging situations were mediated by a minimum standard of ethics that led individuals to avoid trouble even if this meant their behavior fell short of the accepted ideal. Effective ethics education in postgraduate psychiatry training will require addressing the hidden curriculum. In addition to profession-wide efforts to articulate high-level values, program-specific action on locally relevant issues constitutes a necessary mechanism for handling the impact of the hidden curriculum.

Humanism, the Hidden Curriculum, and Educational Reform: A Scoping Review and Thematic Analysis.

PubMed

Martimianakis, Maria Athina Tina; Michalec, Barret; Lam, Justin; Cartmill, Carrie; Taylor, Janelle S; Hafferty, Frederic W

2015-11-01

Medical educators have used the hidden curriculum concept for over three decades to make visible the effects of tacit learning, including how culture, structures, and institutions influence professional identity formation. In response to calls to see more humanistic-oriented training in medicine, the authors examined how the hidden curriculum construct has been applied in the English language medical education literature with a particular (and centering) look at its use within literature pertaining to humanism. They also explored the ends to which the hidden curriculum construct has been used in educational reform efforts (at the individual, organizational, and/or systems levels) related to nurturing and/or increasing humanism in health care. The authors conducted a scoping review and thematic analysis that draws from the tradition of critical discourse analysis. They identified 1,887 texts in the literature search, of which 200 met inclusion criteria. The analysis documents a strong preoccupation with negative effects of the hidden curriculum, particularly the moral erosion of physicians and the perceived undermining of humanistic values in health care. A conflation between professionalism and humanism was noted. Proposals for reform largely target medical students and medical school faculty, with very little consideration for how organizations, institutions, and sociopolitical relations more broadly contribute to problematic behaviors. The authors argue that there is a need to transcend conceptualizations of the hidden curriculum as antithetical to humanism and offer suggestions for future research that explores the necessity and value of humanism and the hidden curriculum in medical education and training.

Detection and electrical characterization of hidden layers using time-domain analysis of terahertz reflections

NASA Astrophysics Data System (ADS)

Geltner, I.; Hashimshony, D.; Zigler, A.

2002-07-01

We use a time-domain analysis method to characterize the outer layer of a multilayer structure regardless of the inner ones, thus simplifying the characterization of all the layers. We combine this method with THz reflection spectroscopy to detect nondestructively a hidden aluminum oxide layer under opaque paint and to measure its conductivity and high-frequency dielectric constant in the THz range.

Hidden mission of the psyche in abuse and addiction.

PubMed

Gostecnik, Christian; Repic, Tanja; Cvetek, Mateja; Cvetek, Robert

2010-09-01

Traumatic experiences can become the central mental content in our psychic structure and can deeply mark all our later perceptions and experiences of our surroundings. We can claim something similar also for addictions of all kinds. In this article, we will demonstrate that recurring traumatic experiences and abuse as well as addiction represent a hidden mission of psyche for resolution and a great cry of longing for salvation.

Free energy and hidden barriers of the β-sheet structure of prion protein.

PubMed

Paz, S Alexis; Abrams, Cameron F

2015-10-13

On-the-fly free-energy parametrization is a new collective variable biasing approach akin to metadynamics with one important distinction: rather than acquiring an accelerated distribution via a history-dependent bias potential, sampling on this distribution is achieved from the beginning of the simulation using temperature-accelerated molecular dynamics. In the present work, we compare the performance of both approaches to compute the free-energy profile along a scalar collective variable measuring the H-bond registry of the β-sheet structure of the mouse Prion protein. Both methods agree on the location of the free-energy minimum, but free-energy profiles from well-tempered metadynamics are subject to a much higher degree of statistical noise due to hidden barriers. The sensitivity of metadynamics to hidden barriers is shown to be a consequence of the history dependence of the bias potential, and we detail the nature of these barriers for the prion β-sheet. In contrast, on-the-fly parametrization is much less sensitive to these barriers and thus displays improved convergence behavior relative to that of metadynamics. While hidden barriers are a frequent and central issue in free-energy methods, on-the-fly free-energy parametrization appears to be a robust and preferable method to confront this issue.

Hidden Markov model analysis of force/torque information in telemanipulation

NASA Technical Reports Server (NTRS)

Hannaford, Blake; Lee, Paul

1991-01-01

A model for the prediction and analysis of sensor information recorded during robotic performance of telemanipulation tasks is presented. The model uses the hidden Markov model to describe the task structure, the operator's or intelligent controller's goal structure, and the sensor signals. A methodology for constructing the model parameters based on engineering knowledge of the task is described. It is concluded that the model and its optimal state estimation algorithm, the Viterbi algorithm, are very succesful at the task of segmenting the data record into phases corresponding to subgoals of the task. The model provides a rich modeling structure within a statistical framework, which enables it to represent complex systems and be robust to real-world sensory signals.

Hidden Markov model-derived structural alphabet for proteins: the learning of protein local shapes captures sequence specificity.

PubMed

Camproux, A C; Tufféry, P

2005-08-05

Understanding and predicting protein structures depend on the complexity and the accuracy of the models used to represent them. We have recently set up a Hidden Markov Model to optimally compress protein three-dimensional conformations into a one-dimensional series of letters of a structural alphabet. Such a model learns simultaneously the shape of representative structural letters describing the local conformation and the logic of their connections, i.e. the transition matrix between the letters. Here, we move one step further and report some evidence that such a model of protein local architecture also captures some accurate amino acid features. All the letters have specific and distinct amino acid distributions. Moreover, we show that words of amino acids can have significant propensities for some letters. Perspectives point towards the prediction of the series of letters describing the structure of a protein from its amino acid sequence.

Generating a New Higher-Dimensional Coupled Integrable Dispersionless System: Algebraic Structures, Bäcklund Transformation and Hidden Structural Symmetries

NASA Astrophysics Data System (ADS)

Souleymanou, Abbagari; Thomas, B. Bouetou; Timoleon, C. Kofane

2013-08-01

The prolongation structure methodologies of Wahlquist—Estabrook [H.D. Wahlquist and F.B. Estabrook, J. Math. Phys. 16 (1975) 1] for nonlinear differential equations are applied to a more general set of coupled integrable dispersionless system. Based on the obtained prolongation structure, a Lie-Algebra valued connection of a closed ideal of exterior differential forms related to the above system is constructed. A Lie-Algebra representation of some hidden structural symmetries of the previous system, its Bäcklund transformation using the Riccati form of the linear eigenvalue problem and their general corresponding Lax-representation are derived. In the wake of the previous results, we extend the above prolongation scheme to higher-dimensional systems from which a new (2 + 1)-dimensional coupled integrable dispersionless system is unveiled along with its inverse scattering formulation, which applications are straightforward in nonlinear optics where additional propagating dimension deserves some attention.

Ghost free systems with coexisting bosons and fermions

NASA Astrophysics Data System (ADS)

Kimura, Rampei; Sakakihara, Yuki; Yamaguchi, Masahide

2017-08-01

We study the coexistence system of both bosonic and fermionic degrees of freedom. Even if a Lagrangian does not include higher derivatives, fermionic ghosts exist. For a Lagrangian with up to first derivatives, we find the fermionic ghost free condition in Hamiltonian analysis, which is found to be the same as requiring that the equations of motion of fermions be first order in Lagrangian formulation. When fermionic degrees of freedom are present, the uniqueness of time evolution is not guaranteed a priori because of the Grassmann property. We confirm that the additional condition, which is introduced to close Hamiltonian analysis, also ensures the uniqueness of the time evolution of the system.

Unsupervised Learning Through Randomized Algorithms for High-Volume High-Velocity Data (ULTRA-HV).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pinar, Ali; Kolda, Tamara G.; Carlberg, Kevin Thomas

Through long-term investments in computing, algorithms, facilities, and instrumentation, DOE is an established leader in massive-scale, high-fidelity simulations, as well as science-leading experimentation. In both cases, DOE is generating more data than it can analyze and the problem is intensifying quickly. The need for advanced algorithms that can automatically convert the abundance of data into a wealth of useful information by discovering hidden structures is well recognized. Such efforts however, are hindered by the massive volume of the data and its high velocity. Here, the challenge is developing unsupervised learning methods to discover hidden structure in high-volume, high-velocity data.

Bio-inspired passive actuator simulating an abalone shell mechanism for structural control

NASA Astrophysics Data System (ADS)

Yang, Henry T. Y.; Lin, Chun-Hung; Bridges, Daniel; Randall, Connor J.; Hansma, Paul K.

2010-10-01

An energy dispersion mechanism called 'sacrificial bonds and hidden length', which is found in some biological systems, such as abalone shells and bones, is the inspiration for new strategies for structural control. Sacrificial bonds and hidden length can substantially increase the stiffness and enhance energy dissipation in the constituent molecules of abalone shells and bone. Having been inspired by the usefulness and effectiveness of such a mechanism, which has evolved over millions of years and countless cycles of evolutions, the authors employ the conceptual underpinnings of this mechanism to develop a bio-inspired passive actuator. This paper presents a fundamental method for optimally designing such bio-inspired passive actuators for structural control. To optimize the bio-inspired passive actuator, a simple method utilizing the force-displacement-velocity (FDV) plots based on LQR control is proposed. A linear regression approach is adopted in this research to find the initial values of the desired parameters for the bio-inspired passive actuator. The illustrative examples, conducted by numerical simulation with experimental validation, suggest that the bio-inspired passive actuator based on sacrificial bonds and hidden length may be comparable in performance to state-of-the-art semi-active actuators.

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study.

PubMed

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students' teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. Students' perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students' assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly.

Perspectives of nursing and midwifery students regarding the role of the hidden curriculum in patient education: A qualitative study

PubMed Central

Azadi, Zohreh; Ravanipour, Maryam; Yazdankhahfard, Mohammadreza; Motamed, Niloofar; Pouladi, Shahnaz

2017-01-01

BACKGROUND: Although education is one of the most substantial needs of patients that should be taught by nurses and midwives, it is not clearly defined through the hidden curriculum in students’ teaching programs. The aim of this study was to explore the patient education through the hidden curriculum in the perspectives of nursing and midwifery students. MATERIALS AND METHODS: A qualitative, content analysis study was performed and twenty nursing and midwifery students were interviewed. Data were collected using face-to-face semi-structured interviews and analyzed using conventional content analysis approach. RESULTS: Students’ perception of the hidden curriculum in patient education emerged in three main themes concerning: (1) interactions, (2) teaching and learning opportunities, and (3) reflective evaluation. CONCLUSIONS: The hidden curriculum in patient education can be transferred as interactions between professors, students, nurses, doctors, and also patients who are rooted from paying attention to the human dimension of the patient, avoiding the materialistic treatment of the patient and treating the patient with dignity. Educational policies and students’ assignments should be designed based on the patient's educational goals and the goal of evaluation has to be presented to the students clearly. PMID:29296609

Dissipative hidden sector dark matter

NASA Astrophysics Data System (ADS)

Foot, R.; Vagnozzi, S.

2015-01-01

A simple way of explaining dark matter without modifying known Standard Model physics is to require the existence of a hidden (dark) sector, which interacts with the visible one predominantly via gravity. We consider a hidden sector containing two stable particles charged under an unbroken U (1 )' gauge symmetry, hence featuring dissipative interactions. The massless gauge field associated with this symmetry, the dark photon, can interact via kinetic mixing with the ordinary photon. In fact, such an interaction of strength ε ˜10-9 appears to be necessary in order to explain galactic structure. We calculate the effect of this new physics on big bang nucleosynthesis and its contribution to the relativistic energy density at hydrogen recombination. We then examine the process of dark recombination, during which neutral dark states are formed, which is important for large-scale structure formation. Galactic structure is considered next, focusing on spiral and irregular galaxies. For these galaxies we modeled the dark matter halo (at the current epoch) as a dissipative plasma of dark matter particles, where the energy lost due to dissipation is compensated by the energy produced from ordinary supernovae (the core-collapse energy is transferred to the hidden sector via kinetic mixing induced processes in the supernova core). We find that such a dynamical halo model can reproduce several observed features of disk galaxies, including the cored density profile and the Tully-Fisher relation. We also discuss how elliptical and dwarf spheroidal galaxies could fit into this picture. Finally, these analyses are combined to set bounds on the parameter space of our model, which can serve as a guideline for future experimental searches.

The Search for Hidden Structure

ERIC Educational Resources Information Center

Matsuura, Ryota; Sword, Sarah; Finkelstein, Tatyana

2017-01-01

How does one look for mathematical structure? Finding structure is a challenging yet accessible activity for all students. This article describes a lesson in which seventh graders engaged with mathematical structure. The setting was a seventh-grade prealgebra classroom in a suburban school. The classroom teacher was co-author Tatyana Finkelstein.…

Material content of the universe - Introductory survey

NASA Astrophysics Data System (ADS)

Tayler, R. J.

1986-12-01

Matter in the universe can be detected either by the radiation it emits or by its gravitational influence. There is a strong suggestion that the universe contains substantial hidden matter, mass without corresponding light. There are also arguments from elementary particle physics that the universe should have closure density, which would also imply hidden mass. Observations of the chemical composition of the universe interpreted in terms of the hot Big Bang cosmological theory suggest that this hidden matter cannot all be of baryonic form but must consist of weakly interacting elementary particles. A combination of observations and theoretical ideas about the origin of large-scale structure may demand that these particles are of a type which is not yet definitely known to exist.

Structure and Randomness of Continuous-Time, Discrete-Event Processes

NASA Astrophysics Data System (ADS)

Marzen, Sarah E.; Crutchfield, James P.

2017-10-01

Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calculate, for the first time, the entropy rate and statistical complexity of stochastic processes generated by finite unifilar hidden semi-Markov models—memoryful, state-dependent versions of renewal processes. Calculating these quantities requires introducing novel mathematical objects (ɛ -machines of hidden semi-Markov processes) and new information-theoretic methods to stochastic processes.

Hidden Dangers.

ERIC Educational Resources Information Center

Greven, Erik D. W.; Knox, Winthrop S.

1999-01-01

Discusses each of the major system components of a maintenance survey that can provide pool facilities with the information needed to properly maintain aging pools. Components examined include mechanical and structural systems; pool structure; and the filtration, circulation, and chemical treatment systems. (GR)

Damage evaluation by a guided wave-hidden Markov model based method

NASA Astrophysics Data System (ADS)

Mei, Hanfei; Yuan, Shenfang; Qiu, Lei; Zhang, Jinjin

2016-02-01

Guided wave based structural health monitoring has shown great potential in aerospace applications. However, one of the key challenges of practical engineering applications is the accurate interpretation of the guided wave signals under time-varying environmental and operational conditions. This paper presents a guided wave-hidden Markov model based method to improve the damage evaluation reliability of real aircraft structures under time-varying conditions. In the proposed approach, an HMM based unweighted moving average trend estimation method, which can capture the trend of damage propagation from the posterior probability obtained by HMM modeling is used to achieve a probabilistic evaluation of the structural damage. To validate the developed method, experiments are performed on a hole-edge crack specimen under fatigue loading condition and a real aircraft wing spar under changing structural boundary conditions. Experimental results show the advantage of the proposed method.

Resummed tree heptagon

NASA Astrophysics Data System (ADS)

Belitsky, A. V.

2018-04-01

The form factor program for the regularized space-time S-matrix in planar maximally supersymmetric gauge theory, known as the pentagon operator product expansion, is formulated in terms of flux-tube excitations propagating on a dual two-dimensional world-sheet, whose dynamics is known exactly as a function of 't Hooft coupling. Both MHV and non-MHV amplitudes are described in a uniform, systematic fashion within this framework, with the difference between the two encoded in coupling-dependent helicity form factors expressed via Zhukowski variables. The nontrivial SU(4) tensor structure of flux-tube transitions is coupling independent and is known for any number of charged excitations from solutions of a system of Watson and Mirror equations. This description allows one to resum the infinite series of form factors and recover the space-time S-matrix exactly in kinematical variables at a given order of perturbation series. Recently, this was done for the hexagon. Presently, we successfully perform resummation for the seven-leg tree NMHV amplitude. To this end, we construct the flux-tube integrands of the fifteen independent Grassmann component of the heptagon with an infinite number of small fermion-antifermion pairs accounted for in NMHV two-channel conformal blocks.

New infinite-dimensional hidden symmetries for heterotic string theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao Yajun

The symmetry structures of two-dimensional heterotic string theory are studied further. A (2d+n)x(2d+n) matrix complex H-potential is constructed and the field equations are extended into a complex matrix formulation. A pair of Hauser-Ernst-type linear systems are established. Based on these linear systems, explicit formulations of new hidden symmetry transformations for the considered theory are given and then these symmetry transformations are verified to constitute infinite-dimensional Lie algebras: the semidirect product of the Kac-Moody o(d,d+n-circumflex) and Virasoro algebras (without center charges). These results demonstrate that the heterotic string theory under consideration possesses more and richer symmetry structures than previously expected.

Invariant glycines and prolines flanking in loops the strand beta 2 of various (alpha/beta)8-barrel enzymes: a hidden homology?

PubMed Central

Janecek, S.

1996-01-01

The question of parallel (alpha/beta)8-barrel fold evolution remains unclear, owing mainly to the lack of sequence homology throughout the amino acid sequences of (alpha/beta)8-barrel enzymes. The "classical" approaches used in the search for homologies among (alpha/beta)8-barrels (e.g., production of structurally based alignments) have yielded alignments perfect from the structural point of view, but the approaches have been unable to reveal the homologies. These are proposed to be "hidden" in (alpha/beta)8-barrel enzymes. The term "hidden homology" means that the alignment of sequence stretches proposed to be homologous need not be structurally fully satisfactory. This is due to the very long evolutionary history of all (alpha/beta)8-barrels. This work identifies so-called hidden homology around the strand beta 2 that is flanked by loops containing invariant glycines and prolines in 17 different (alpha/beta)8-barrel enzymes, i.e., roughly in half of all currently known (alpha/beta)8-barrel proteins. The search was based on the idea that a conserved sequence region of an (alpha/beta)8-barrel enzyme should be more or less conserved also in the equivalent part of the structure of the other enzymes with this folding motif, given their mutual evolutionary relatedness. For this purpose, the sequence region around the well-conserved second beta-strand of alpha-amylase flanked by the invariant glycine and proline (56_GFTAIWITP, Aspergillus oryzae alpha-amylase numbering), was used as the sequence-structural template. The proposal that the second beta-strand of (alpha/beta)8-barrel fold is important from the evolutionary point of view is strongly supported by the increasing trend of the observed beta 2-strand structural similarity for the pairs of (alpha/beta)8-barrel enzymes: alpha-amylase and the alpha-subunit of tryptophan synthase, alpha-amylase and mandelate racemase, and alpha-amylase and cyclodextrin glycosyltransferase. This trend is also in agreement with the existing evolutionary division of the entire family of (alpha/beta)8-barrel proteins. PMID:8762144

Invariant glycines and prolines flanking in loops the strand beta 2 of various (alpha/beta)8-barrel enzymes: a hidden homology?

PubMed

Janecek, S

1996-06-01

The question of parallel (alpha/beta)8-barrel fold evolution remains unclear, owing mainly to the lack of sequence homology throughout the amino acid sequences of (alpha/beta)8-barrel enzymes. The "classical" approaches used in the search for homologies among (alpha/beta)8-barrels (e.g., production of structurally based alignments) have yielded alignments perfect from the structural point of view, but the approaches have been unable to reveal the homologies. These are proposed to be "hidden" in (alpha/beta)8-barrel enzymes. The term "hidden homology" means that the alignment of sequence stretches proposed to be homologous need not be structurally fully satisfactory. This is due to the very long evolutionary history of all (alpha/beta)8-barrels. This work identifies so-called hidden homology around the strand beta 2 that is flanked by loops containing invariant glycines and prolines in 17 different (alpha/beta)8-barrel enzymes, i.e., roughly in half of all currently known (alpha/beta)8-barrel proteins. The search was based on the idea that a conserved sequence region of an (alpha/beta)8-barrel enzyme should be more or less conserved also in the equivalent part of the structure of the other enzymes with this folding motif, given their mutual evolutionary relatedness. For this purpose, the sequence region around the well-conserved second beta-strand of alpha-amylase flanked by the invariant glycine and proline (56_GFTAIWITP, Aspergillus oryzae alpha-amylase numbering), was used as the sequence-structural template. The proposal that the second beta-strand of (alpha/beta)8-barrel fold is important from the evolutionary point of view is strongly supported by the increasing trend of the observed beta 2-strand structural similarity for the pairs of (alpha/beta)8-barrel enzymes: alpha-amylase and the alpha-subunit of tryptophan synthase, alpha-amylase and mandelate racemase, and alpha-amylase and cyclodextrin glycosyltransferase. This trend is also in agreement with the existing evolutionary division of the entire family of (alpha/beta)8-barrel proteins.

Analysing the hidden curriculum: use of a cultural web

PubMed Central

Mossop, Liz; Dennick, Reg; Hammond, Richard; Robbé, Iain

2013-01-01

CONTEXT Major influences on learning about medical professionalism come from the hidden curriculum. These influences can contribute positively or negatively towards the professional enculturation of clinical students. The fact that there is no validated method for identifying the components of the hidden curriculum poses problems for educators considering professionalism. The aim of this study was to analyse whether a cultural web, adapted from a business context, might assist in the identification of elements of the hidden curriculum at a UK veterinary school. METHODS A qualitative approach was used. Seven focus groups consisting of three staff groups and four student groups were organised. Questioning was framed using the cultural web, which is a model used by business owners to assess their environment and consider how it affects their employees and customers. The focus group discussions were recorded, transcribed and analysed thematically using a combination of a priori and emergent themes. RESULTS The cultural web identified elements of the hidden curriculum for both students and staff. These included: core assumptions; routines; rituals; control systems; organisational factors; power structures, and symbols. Discussions occurred about how and where these issues may affect students’ professional identity development. CONCLUSIONS The cultural web framework functioned well to help participants identify elements of the hidden curriculum. These aspects aligned broadly with previously described factors such as role models and institutional slang. The influence of these issues on a student’s development of a professional identity requires discussion amongst faculty staff, and could be used to develop learning opportunities for students. The framework is promising for the analysis of the hidden curriculum and could be developed as an instrument for implementation in other clinical teaching environments. PMID:23323652

Intuitive optics: what great apes infer from mirrors and shadows.

PubMed

Völter, Christoph J; Call, Josep

2018-05-02

There is ongoing debate about the extent to which nonhuman animals, like humans, can go beyond first-order perceptual information to abstract structural information from their environment. To provide more empirical evidence regarding this question, we examined what type of information great apes (chimpanzees, bonobos, and orangutans) gain from optical effects such as shadows and mirror images. In an initial experiment, we investigated whether apes would use mirror images and shadows to locate hidden food. We found that all examined ape species used these cues to find the food. Follow-up experiments showed that apes neither confused these optical effects with the food rewards nor did they merely associate cues with food. First, naïve chimpanzees used the shadow of the hidden food to locate it but they did not learn within the same number of trials to use a perceptually similar rubber patch as indicator of the hidden food reward. Second, apes made use of the mirror images to estimate the distance of the hidden food from their own body. Depending on the distance, apes either pointed into the direction of the food or tried to access the hidden food directly. Third, apes showed some sensitivity to the geometrical relation between mirror orientation and mirrored objects when searching hidden food. Fourth, apes tended to interpret mirror images and pictures of these mirror images differently depending on their prior knowledge. Together, these findings suggest that apes are sensitive to the optical relation between mirror images and shadows and their physical referents.

Detection of latent fingerprint hidden beneath adhesive tape by optical coherence tomography.

PubMed

Zhang, Ning; Wang, Chengming; Sun, Zhenwen; Li, Zhigang; Xie, Lanchi; Yan, Yuwen; Xu, Lei; Guo, Jingjing; Huang, Wei; Li, Zhihui; Xue, Jing; Liu, Huan; Xu, Xiaojing

2018-06-01

Adhesive tape is one type of common item which can be encountered in criminal cases involving rape, murder, kidnapping and explosives. It is often the case that a suspect deposits latent fingerprints on the sticky side of adhesive tape material when tying up victims, manufacturing improvised explosive devices or packaging illegal goods. However, the adhesive tapes found at crime scenes are usually stuck together or attached to a certain substrate, and thus the latent fingerprints may be hidden beneath the tapes. Current methods to detect latent fingerprint hidden beneath adhesive tape need to peel it off first and then apply physical or chemical methods to develop the fingerprint, which undergo complicated procedures and would affect the original condition of latent print. Optical coherence tomography (OCT) is a novel applied techniques in forensics which enables obtaining cross-sectional structure with the advantages of non-invasive, in-situ, high resolution and high speed. In this paper, a custom-built spectral-domain OCT (SD-OCT) system with a hand-held probe was employed to detect fingerprints hidden beneath different types of adhesive tapes. Three-dimensional (3D) OCT reconstructions were performed and the en face images were presented to reveal the hidden fingerprints. The results demonstrate that OCT is a promising tool for rapidly detecting and recovering high quality image of latent fingerprint hidden beneath adhesive tape without any changes to the original state and preserve the integrity of the evidence. Copyright © 2018 Elsevier B.V. All rights reserved.

Precision grid survey apparatus and method for the mapping of hidden ferromagnetic structures

DOEpatents

von Wimmerspeg, Udo

2004-11-16

The present invention is for a precision grid surveyor having a stationary unit and a roving unit. The stationary unit has a light source unit that emits a light beam and a rotator to project the light beam toward detectors on a roving unit. The roving unit moves over an area to be surveyed. Further the invention is for a method of mapping details of hidden underground iron pipelines, and more particularly the location of bell joints.

κ-deformed Dirac oscillator in an external magnetic field

NASA Astrophysics Data System (ADS)

Chargui, Y.; Dhahbi, A.; Cherif, B.

2018-04-01

We study the solutions of the (2 + 1)-dimensional κ-deformed Dirac oscillator in the presence of a constant transverse magnetic field. We demonstrate how the deformation parameter affects the energy eigenvalues of the system and the corresponding eigenfunctions. Our findings suggest that this system could be used to detect experimentally the effect of the deformation. We also show that the hidden supersymmetry of the non-deformed system reduces to a hidden pseudo-supersymmetry having the same algebraic structure as a result of the κ-deformation.

You've got to know the rules to play the game: how medical students negotiate the hidden curriculum of surgical careers.

PubMed

Hill, Elspeth; Bowman, Katherine; Stalmeijer, Renée; Hart, Jo

2014-09-01

The hidden curriculum may be framed as the culture, beliefs and behaviours of a community that are passed to students outside formal course offerings. Medical careers involve diverse specialties, each with a different culture, yet how medical students negotiate these cultures has not been fully explored. Using surgery as a case study, we aimed to establish, first, whether a specialty-specific hidden curriculum existed for students, and second, how students encountered and negotiated surgical career options. Using a constructivist grounded theory approach, we explored students' thoughts, beliefs and experiences regarding career decisions and surgery. An exploratory questionnaire informed the discussion schedule for semi-structured individual interviews. Medical students were purposively sampled by year group, gender and career intentions in surgery. Data collection and analysis were iterative: analysis followed each interview and guided the adaptation of our discussion schedule to further our evolving model. Students held a clear sense of a hidden curriculum in surgery. To successfully negotiate a surgical career, students perceived that they must first build networks because careers information flows through relationships. They subsequently enacted what they learned by accruing the accolades ('ticking the boxes') and appropriating the dispositions ('walking the talk') of 'future surgeons'. This allowed them to identify themselves and to be identified by others as 'future surgeons' and to gain access to participation in the surgical world. Participation then enabled further network building and access to careers information in a positive feedback loop. For some, negotiating the hidden curriculum was more difficult, which, for them, rendered a surgical career unattractive or unattainable. Students perceive a clear surgery-specific hidden curriculum. Using a constructivist grounded theory approach, we have developed a model of how students encounter, uncover and enact this hidden curriculum to succeed. Drawing on concepts of Bourdieu, we discuss unequal access to the hidden curriculum, which was found to exclude many from the possibility of a surgical career. © 2014 John Wiley & Sons Ltd.

Hidden scale invariance of metals

NASA Astrophysics Data System (ADS)

Hummel, Felix; Kresse, Georg; Dyre, Jeppe C.; Pedersen, Ulf R.

2015-11-01

Density functional theory (DFT) calculations of 58 liquid elements at their triple point show that most metals exhibit near proportionality between the thermal fluctuations of the virial and the potential energy in the isochoric ensemble. This demonstrates a general "hidden" scale invariance of metals making the condensed part of the thermodynamic phase diagram effectively one dimensional with respect to structure and dynamics. DFT computed density scaling exponents, related to the Grüneisen parameter, are in good agreement with experimental values for the 16 elements where reliable data were available. Hidden scale invariance is demonstrated in detail for magnesium by showing invariance of structure and dynamics. Computed melting curves of period three metals follow curves with invariance (isomorphs). The experimental structure factor of magnesium is predicted by assuming scale invariant inverse power-law (IPL) pair interactions. However, crystal packings of several transition metals (V, Cr, Mn, Fe, Nb, Mo, Ta, W, and Hg), most post-transition metals (Ga, In, Sn, and Tl), and the metalloids Si and Ge cannot be explained by the IPL assumption. The virial-energy correlation coefficients of iron and phosphorous are shown to increase at elevated pressures. Finally, we discuss how scale invariance explains the Grüneisen equation of state and a number of well-known empirical melting and freezing rules.

A Spatial View of the Interpersonal Structure of Family Interviews: Similarities and Differences Across Counselors.

ERIC Educational Resources Information Center

Friedlander, Myrna L.; Highlen, Pamela S.

1984-01-01

Examined the interpersonal structures of interviews by Ackerman, Bowen, Jackson, and Whitaker with the same family to identify common features across counselors. Multidimensional scaling provided a spatial representation of the hidden structure in the communication patterns of these interviews. Correlations indicated counselors' interactions were…

Antisymmetric Spin-Orbit Coupling in a d-p Model on a Zigzag Chain

DOE PAGES

Sugita, Yusuke; Hayami, Satoru; Motome, Yukitoshi

2015-12-29

In this paper, we theoretically investigate how an antisymmetric spin-orbit coupling emerges in electrons moving on lattice structures which are centrosymmetric but break the spatial inversion symme- try at atomic positions. We construct an effective d-p model on the simplest lattice structure, a zigzag chain of edge-sharing octahedra, with taking into account the crystalline electric field, the spin-orbit coupling, and on-site and inter-site d-p hybridizations. We show that an effective antisymmetric spin-orbit coupling arises in the sublattice-dependent form, which results in a hidden spin polarization in the band structure. Finally, we explicitly derive the effective antisymmetric spin-orbit coupling for dmore » electrons, which not only explains the hidden spin polarization but also indicates how to enhance it.« less

Antisymmetric Spin-Orbit Coupling in a d-p Model on a Zigzag Chain

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sugita, Yusuke; Hayami, Satoru; Motome, Yukitoshi

In this paper, we theoretically investigate how an antisymmetric spin-orbit coupling emerges in electrons moving on lattice structures which are centrosymmetric but break the spatial inversion symme- try at atomic positions. We construct an effective d-p model on the simplest lattice structure, a zigzag chain of edge-sharing octahedra, with taking into account the crystalline electric field, the spin-orbit coupling, and on-site and inter-site d-p hybridizations. We show that an effective antisymmetric spin-orbit coupling arises in the sublattice-dependent form, which results in a hidden spin polarization in the band structure. Finally, we explicitly derive the effective antisymmetric spin-orbit coupling for dmore » electrons, which not only explains the hidden spin polarization but also indicates how to enhance it.« less

11. DETAIL VIEW OF DAM 87, SHOWING STOPLOG STRUCTURE (PARTIALLY ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

11. DETAIL VIEW OF DAM 87, SHOWING STOPLOG STRUCTURE (PARTIALLY HIDDEN BY MARSH GRASSES IN LOWER PART OF PHOTO) AT RIGHT (WEST) END OF SPILLWAY - Upper Souris National Wildlife Refuge, Dam 87, Souris River Basin, Foxholm, Surrey (England), ND

Hidden Costs of Hospital Based Delivery from Two Tertiary Hospitals in Western Nepal.

PubMed

Acharya, Jeevan; Kaehler, Nils; Marahatta, Sujan Babu; Mishra, Shiva Raj; Subedi, Sudarshan; Adhikari, Bipin

2016-01-01

Hospital based delivery has been an expensive experience for poor households because of hidden costs which are usually unaccounted in hospital costs. The main aim of this study was to estimate the hidden costs of hospital based delivery and determine the factors associated with the hidden costs. A hospital based cross-sectional study was conducted among 384 post-partum mothers with their husbands/house heads during the discharge time in Manipal Teaching Hospital and Western Regional Hospital, Pokhara, Nepal. A face to face interview with each respondent was conducted using a structured questionnaire. Hidden costs were calculated based on the price rate of the market during the time of the study. The total hidden costs for normal delivery and C-section delivery were 243.4 USD (US Dollar) and 321.6 USD respectively. Of the total maternity care expenditures; higher mean expenditures were found for food & drinking (53.07%), clothes (9.8%) and transport (7.3%). For postpartum women with their husband or house head, the total mean opportunity cost of "days of work loss" were 84.1 USD and 81.9 USD for normal delivery and C-section respectively. Factors such as literate mother (p = 0.007), employed house head (p = 0.011), monthly family income more than 25,000 NRs (Nepalese Rupees) (p = 0.014), private hospital as a place of delivery (p = 0.0001), C-section as a mode of delivery (p = 0.0001), longer duration (>5days) of stay in hospital (p = 0.0001), longer distance (>15km) from house to hospital (p = 0.0001) and longer travel time (>240 minutes) from house to hospital (p = 0.007) showed a significant association with the higher hidden costs (>25000 NRs). Experiences of hidden costs on hospital based delivery and opportunity costs of days of work loss were found high. Several socio-demographic factors, delivery related factors (place and mode of delivery, length of stay, distance from hospital and travel time) were associated with hidden costs. Hidden costs can be a critical factor for many poor and remote households who attend the hospital for delivery. Current remuneration (10-15 USD for normal delivery, 30 USD for complicated delivery and 70 USD for caesarean section delivery) for maternity incentive needs to account the hidden costs by increasing it to 250 USD for normal delivery and 350 USD for C-section. Decentralization of the obstetric care to remote and under-privileged population might reduce the economic burden of pregnant women and can facilitate their attendance at the health care centers.

On some dynamical chameleon systems

NASA Astrophysics Data System (ADS)

Burkin, I. M.; Kuznetsova, O. I.

2018-03-01

It is now well known that dynamical systems can be categorized into systems with self-excited attractors and systems with hidden attractors. A self-excited attractor has a basin of attraction that is associated with an unstable equilibrium, while a hidden attractor has a basin of attraction that does not intersect with small neighborhoods of any equilibrium points. Hidden attractors play the important role in engineering applications because they allow unexpected and potentially disastrous responses to perturbations in a structure like a bridge or an airplane wing. In addition, complex behaviors of chaotic systems have been applied in various areas from image watermarking, audio encryption scheme, asymmetric color pathological image encryption, chaotic masking communication to random number generator. Recently, researchers have discovered the so-called “chameleon systems”. These systems were so named because they demonstrate self-excited or hidden oscillations depending on the value of parameters. The present paper offers a simple algorithm of synthesizing one-parameter chameleon systems. The authors trace the evolution of Lyapunov exponents and the Kaplan-Yorke dimension of such systems which occur when parameters change.

Miracles in Scattering Amplitudes: from QCD to Gravity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Volovich, Anastasia

2016-10-09

The goal of my research project "Miracles in Scattering Amplitudes: from QCD to Gravity" involves deepening our understanding of gauge and gravity theories by exploring hidden structures in scattering amplitudes and using these rich structures as much as possible to aid practical calculations.

The Hidden Rule: A Critical Discussion of Harvard University's Governing Structure. [A Harvard Watch Report].

ERIC Educational Resources Information Center

Weissman, Robert

The governing structure of Harvard University is reviewed, and the findings include the following: (1) Harvard's present administrative and governance structure utilize corporate techniques of management that allow the president to diffuse administrative tasks without diffusing power--the difficulty of locating responsibility in the decentralized…

Hidden symmetries for ellipsoid-solitonic deformations of Kerr-Sen black holes and quantum anomalies

NASA Astrophysics Data System (ADS)

Vacaru, Sergiu I.

2013-02-01

We prove the existence of hidden symmetries in the general relativity theory defined by exact solutions with generic off-diagonal metrics, nonholonomic (non-integrable) constraints, and deformations of the frame and linear connection structure. A special role in characterization of such spacetimes is played by the corresponding nonholonomic generalizations of Stackel-Killing and Killing-Yano tensors. There are constructed new classes of black hole solutions and we study hidden symmetries for ellipsoidal and/or solitonic deformations of "prime" Kerr-Sen black holes into "target" off-diagonal metrics. In general, the classical conserved quantities (integrable and not-integrable) do not transfer to the quantized systems and produce quantum gravitational anomalies. We prove that such anomalies can be eliminated via corresponding nonholonomic deformations of fundamental geometric objects (connections and corresponding Riemannian and Ricci tensors) and by frame transforms.

Hidden negative linear compressibility in lithium l-tartrate.

PubMed

Yeung, Hamish H-M; Kilmurray, Rebecca; Hobday, Claire L; McKellar, Scott C; Cheetham, Anthony K; Allan, David R; Moggach, Stephen A

2017-02-01

By decoupling the mechanical behaviour of building units for the first time in a wine-rack framework containing two different strut types, we show that lithium l-tartrate exhibits NLC with a maximum value, K max = -21 TPa -1 , and an overall NLC capacity, χ NLC = 5.1%, that are comparable to the most exceptional materials to date. Furthermore, the contributions from molecular strut compression and angle opening interplay to give rise to so-called "hidden" negative linear compressibility, in which NLC is absent at ambient pressure, switched on at 2 GPa and sustained up to the limit of our experiment, 5.5 GPa. Analysis of the changes in crystal structure using variable-pressure synchrotron X-ray diffraction reveals new chemical and geometrical design rules to assist the discovery of other materials with exciting hidden anomalous mechanical properties.

Test results of smart aircraft fastener for KC-135 structural integrity

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1998-07-01

Hidden and inaccessible corrosion in aircraft structures is the number one logistics problem for the US Air Force, with an estimated maintenance cost in excess of $LR 1.0B per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system was developed to provide early warning detection of corrosion-related symptoms in hidden locations of aircraft structures. The SAFE system incorporates an in situ measurement approach that measures and autonomously records several environmental conditions within a Hi-Lok aircraft fastener that could cause corrosion. The SAFE system integrates a miniature electrochemical microsensor array and a time-of-wetness sensor with an ultra low power 8-bit microcontroller and 4- Mbyte solid-state FLASH archival memory to measure evidence of active corrosion. A summary of the technical approach and a detailed analysis of the KC-135 lap joint test coupon results are presented.

Smart fastener for KC-135 structural integrity monitoring

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg

1997-06-01

Hidden and inaccessible corrosion in aircraft structures is the number-one logistics problem for the U.S. Air Force, with an estimated maintenance cost in excess of $DOL1.0 billion per year in 1990-equivalent dollars. The Smart Aircraft Fastener Evaluation (SAFE) system is being developed to provide early warning detection of corrosion- related symptoms in hidden locations of aircraft structures. The SAFE incorporates an in situ measurement approach that measures and autonomously records several environmental conditions (i.e., pH, temperature, chloride, free potential, time-of-wetness) within a Hi-Lok aircraft fastener that could cause corrosion to occur. The SAFE system integrates a miniature electrochemical microsensor array and a time-of- wetness sensor with an ultra-low-power 8-bit microcontroller and 5-Mbyte solid-state FLASH archival memory to measure the evidence of active corrosion. A summary of the technical approach, system design definition, software architecture, and future field test plans will be presented.

View-Dependent Streamline Deformation and Exploration

PubMed Central

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R.; Wong, Pak Chung

2016-01-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely. PMID:26600061

Peculiar bonding associated with atomic doping and hidden honeycombs in borophene

NASA Astrophysics Data System (ADS)

Lee, Chi-Cheng; Feng, Baojie; D'angelo, Marie; Yukawa, Ryu; Liu, Ro-Ya; Kondo, Takahiro; Kumigashira, Hiroshi; Matsuda, Iwao; Ozaki, Taisuke

2018-02-01

Engineering atomic-scale structures allows great manipulation of physical properties and chemical processes for advanced technology. We show that the B atoms deployed at the centers of honeycombs in boron sheets, borophene, behave as nearly perfect electron donors for filling the graphitic σ bonding states without forming additional in-plane bonds by first-principles calculations. The dilute electron density distribution owing to the weak bonding surrounding the center atoms provides easier atomic-scale engineering and is highly tunable via in-plane strain, promising for practical applications, such as modulating the extraordinarily high thermal conductance that exceeds the reported value in graphene. The hidden honeycomb bonding structure suggests an unusual energy sequence of core electrons that has been verified by our high-resolution core-level photoelectron spectroscopy measurements. With the experimental and theoretical evidence, we demonstrate that borophene exhibits a peculiar bonding structure and is distinctive among two-dimensional materials.

View-Dependent Streamline Deformation and Exploration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tong, Xin; Edwards, John; Chen, Chun-Ming

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual cluttering for visualizing 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures.more » Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.« less

The way to uncover community structure with core and diversity

NASA Astrophysics Data System (ADS)

Chang, Y. F.; Han, S. K.; Wang, X. D.

2018-07-01

Communities are ubiquitous in nature and society. Individuals that share common properties often self-organize to form communities. Avoiding the shortages of computation complexity, pre-given information and unstable results in different run, in this paper, we propose a simple and efficient method to deepen our understanding of the emergence and diversity of communities in complex systems. By introducing the rational random selection, our method reveals the hidden deterministic and normal diverse community states of community structure. To demonstrate this method, we test it with real-world systems. The results show that our method could not only detect community structure with high sensitivity and reliability, but also provide instructional information about the hidden deterministic community world and the real normal diverse community world by giving out the core-community, the real-community, the tide and the diversity. Thizs is of paramount importance in understanding, predicting, and controlling a variety of collective behaviors in complex systems.

View-Dependent Streamline Deformation and Exploration.

PubMed

Tong, Xin; Edwards, John; Chen, Chun-Ming; Shen, Han-Wei; Johnson, Chris R; Wong, Pak Chung

2016-07-01

Occlusion presents a major challenge in visualizing 3D flow and tensor fields using streamlines. Displaying too many streamlines creates a dense visualization filled with occluded structures, but displaying too few streams risks losing important features. We propose a new streamline exploration approach by visually manipulating the cluttered streamlines by pulling visible layers apart and revealing the hidden structures underneath. This paper presents a customized view-dependent deformation algorithm and an interactive visualization tool to minimize visual clutter in 3D vector and tensor fields. The algorithm is able to maintain the overall integrity of the fields and expose previously hidden structures. Our system supports both mouse and direct-touch interactions to manipulate the viewing perspectives and visualize the streamlines in depth. By using a lens metaphor of different shapes to select the transition zone of the targeted area interactively, the users can move their focus and examine the vector or tensor field freely.

Hidden corrosion detection in aircraft aluminum structures using laser ultrasonics and wavelet transform signal analysis.

PubMed

Silva, M Z; Gouyon, R; Lepoutre, F

2003-06-01

Preliminary results of hidden corrosion detection in aircraft aluminum structures using a noncontact laser based ultrasonic technique are presented. A short laser pulse focused to a line spot is used as a broadband source of ultrasonic guided waves in an aluminum 2024 sample cut from an aircraft structure and prepared with artificially corroded circular areas on its back surface. The out of plane surface displacements produced by the propagating ultrasonic waves were detected with a heterodyne Mach-Zehnder interferometer. Time-frequency analysis of the signals using a continuous wavelet transform allowed the identification of the generated Lamb modes by comparison with the calculated dispersion curves. The presence of back surface corrosion was detected by noting the loss of the S(1) mode near its cutoff frequency. This method is applicable to fast scanning inspection techniques and it is particularly suited for early corrosion detection.

The Cognitive Dimensions of Information Structures.

ERIC Educational Resources Information Center

Green, T. R. G.

1994-01-01

Describes a set of terms (viscosity, hidden dependencies, imposes guess-ahead, abstraction level, and secondary notation) intended as a set of discussion tools for nonspecialists to converse about the structural features of a range of information artifacts. Explains the terms using spreadsheets as an example. (SR)

The "LARSE" Project - Working Toward a Safer Future for Los Angeles

USGS Publications Warehouse

Henyey, Thomas L.; Fuis, Gary S.; Benthien, Mark L.; Burdette, Thomas R.; Christofferson, Shari A.; Clayton, Robert W.; Davis, Paul M.; Hendley, James W.; Kohler, Monica D.; Lutter, William J.; McRaney, John K.; Murphy, Janice M.; Okaya, David A.; Ryberg, Trond; Similia, Gerald W.; Stauffer, Peter H.

1999-01-01

The Los Angeles region is underlain by a network of active faults, including many that are deep and do not break the Earth's surface. These hidden faults include the previously unknown one responsible for the devastating January 1994 Northridge earthquake, the costliest quake in U.S. history. So that structures can be built or strengthened to withstand the quakes that are certain in the future, the Los Angeles Region Seismic Experiment (LARSE) is locating hidden earthquake hazards beneath the region to help scientists determine where the strongest shaking will occur.

Student portfolios and the hidden curriculum on gender: mapping exclusion.

PubMed

Phillips, Christine B

2009-09-01

The hidden curriculum - the norms, values and practices that are transmitted to students through modelling by preceptors and teachers, and decisions about curricular exclusions and inclusions - can be profoundly important in the socialising of trainee doctors. However, tracking the hidden curriculum as it evolves can be challenging for medical schools. This study aimed to explore the content of student e-portfolios on gender issues, a key perspective often taught through a hidden curriculum. Online posts for a gender and medicine e-portfolio task completed by two cohorts of students in Year 3 of a 4-year medical course (n = 167, 66% female) were analysed using a grounded theory approach. A process of gendered 'othering' was applied to both men and women in the medical school using different pedagogical strategies. Curricular emphases on women's health and lack of support for male students to acquire gynaecological examination skills were seen as explicit ways of excluding males. For female medical students, exclusion tended to be implicit, operating through modelling and aphoristic comments about so-called 'female-friendly' career choices and the negative impact of motherhood on career. E-portfolios can be a useful way of tracking the hidden curriculum as it evolves. Responses to gendered exclusion may be developed more readily for the explicit processes impacting on male students than for the implicit processes impacting on female students, which often reflect structural issues related to training and employment.

Detecting structure of haplotypes and local ancestry

USDA-ARS?s Scientific Manuscript database

We present a two-layer hidden Markov model to detect the structure of haplotypes for unrelated individuals. This allows us to model two scales of linkage disequilibrium (one within a group of haplotypes and one between groups), thereby taking advantage of rich haplotype information to infer local an...

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

PubMed Central

Shah, Abhik; Woolf, Peter

2009-01-01

Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

A comparative study of Laplacians and Schroedinger- Lichnerowicz-Weitzenboeck identities in Riemannian and antisymplectic geometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Batalin, Igor A.; I.E. Tamm Theory Division, P.N. Lebedev Physics Institute, Russian Academy of Sciences, 53 Leninsky Prospect, Moscow 119991; Bering, Klaus

2009-07-15

We introduce an antisymplectic Dirac operator and antisymplectic gamma matrices. We explore similarities between, on one hand, the Schroedinger-Lichnerowicz formula for spinor bundles in Riemannian spin geometry, which contains a zeroth-order term proportional to the Levi-Civita scalar curvature, and, on the other hand, the nilpotent, Grassmann-odd, second-order {delta} operator in antisymplectic geometry, which, in general, has a zeroth-order term proportional to the odd scalar curvature of an arbitrary antisymplectic and torsion-free connection that is compatible with the measure density. Finally, we discuss the close relationship with the two-loop scalar curvature term in the quantum Hamiltonian for a particle in amore » curved Riemannian space.« less

Z2×Z2 generalizations of 𝒩 =2 super Schrödinger algebras and their representations

NASA Astrophysics Data System (ADS)

Aizawa, N.; Segar, J.

2017-11-01

We generalize the real and chiral N =2 super Schrödinger algebras to Z2×Z2-graded Lie superalgebras. This is done by D-module presentation, and as a consequence, the D-module presentations of Z2×Z2-graded superalgebras are identical to the ones of super Schrödinger algebras. We then generalize the calculus over the Grassmann number to Z2×Z2 setting. Using it and the standard technique of Lie theory, we obtain a vector field realization of Z2×Z2-graded superalgebras. A vector field realization of the Z2×Z2 generalization of N =1 super Schrödinger algebra is also presented.

Deformation quantization of fermi fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Galaviz, I.; Garcia-Compean, H.; Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN, P.O. Box 14-740, 07000 Mexico, D.F.

2008-04-15

Deformation quantization for any Grassmann scalar free field is described via the Weyl-Wigner-Moyal formalism. The Stratonovich-Weyl quantizer, the Moyal *-product and the Wigner functional are obtained by extending the formalism proposed recently in [I. Galaviz, H. Garcia-Compean, M. Przanowski, F.J. Turrubiates, Weyl-Wigner-Moyal Formalism for Fermi Classical Systems, arXiv:hep-th/0612245] to the fermionic systems of infinite number of degrees of freedom. In particular, this formalism is applied to quantize the Dirac free field. It is observed that the use of suitable oscillator variables facilitates considerably the procedure. The Stratonovich-Weyl quantizer, the Moyal *-product, the Wigner functional, the normal ordering operator, and finally,more » the Dirac propagator have been found with the use of these variables.« less

Universal SU(2/1) and the Higgs and fermion masses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ne`eman, Y.

1992-12-31

We review the SU(2/1) internal supersymmetry suggested by D. Fairlie and the author in 1979. The initial apparent difficulties were resolved when, with J. Thierry-Mieg, we understood that the gauging of a supergroup implies taking the usual Yang-Mills-like Principal (Double) Fibre Bundle as a ``scaffold`` and using its Grassmann algebra as parameter manifold for the supergauge. SU(2/1) Universality fixes the masses of the Higgs scalar field and the ``top`` quark around 100--200 GeV, in the same region as the W and Z masses. A ``unified``` supergauge, enclosing SU(3)colour x SU(2) x U(l), predicts a fourth lepton generation in which themore » neutrino mass is of the same order.« less

Electronic band structure and charge density wave transition in quasi-2D KMo6O17 purple bronze

NASA Astrophysics Data System (ADS)

Valbuena, M. A.; Avila, J.; Vyalikh, D. V.; Guyot, H.; Laubschat, C.; Molodtsov, S. L.; Asensio, M. C.

2008-03-01

High resolution angle-resolved photoemission of quasi-2D KMo6O17 purple bronze has been performed in the range from room temperature to 130 K, slightly above the charge density wave (CDW) transition (Tc = 110 K), and down to 35 K (well below Tc). In this paper we report a detailed study of how electronic band structure is affected by this transition driven by the hidden nesting scenario. The expected spectroscopic fingerprints of the CDW phase transition have been found and discussed according to the hidden one dimension and the development of a quasi-commensurate CDW. The excellent agreement between theory and our experimental results makes of potassium purple bronze a reference system for studying this type of instabilities.

Adults with Autism Tend to Undermine the Hidden Environmental Structure: Evidence from a Visual Associative Learning Task.

PubMed

Sapey-Triomphe, Laurie-Anne; Sonié, Sandrine; Hénaff, Marie-Anne; Mattout, Jérémie; Schmitz, Christina

2018-04-13

The learning-style theory of Autism Spectrum Disorders (ASD) (Qian, Lipkin, Frontiers in Human Neuroscience 5:77, 2011) states that ASD individuals differ from neurotypics in the way they learn and store information about the environment and its structure. ASD would rather adopt a lookup-table strategy (LUT: memorizing each experience), while neurotypics would favor an interpolation style (INT: extracting regularities to generalize). In a series of visual behavioral tasks, we tested this hypothesis in 20 neurotypical and 20 ASD adults. ASD participants had difficulties using the INT style when instructions were hidden but not when instructions were revealed. Rather than an inability to use rules, ASD would be characterized by a disinclination to generalize and infer such rules.

Hidden Structural Codes in Protein Intrinsic Disorder.

PubMed

Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo

2017-10-17

Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.

[Assessment of hidden curriculum components by medical students].

PubMed

Ortega B, Javiera; Fasce H, Eduardo; Pérez V, Cristhian; Ibáñez G, Pilar; Márquez U, Carolina; Parra P, Paula

2014-11-01

Hidden curriculum refers to the unwritten, unofficial, and often unintended lessons, values, and perspectives that students learn at the university, which influences the acquisition of professional skills. To analyze the perception about the influence of the hidden curriculum in the education of medical students at the Universidad de Concepción, Chile. Qualitative investigation with case study approach. Seventeen graduated medical students were selected by probability sampling. A semi-structured interview was used to collect the information and a content analysis was applied. Forty seven percent of participants recognized having fulfilled their academic expectations. As favorable factors for academic achievement the students underlined clinical practice, access to patients and to clinical fields. As negative factors, they identified the lack of commitment, educational support and over-specialization of their mentors. The results show the strengths and weaknesses of the educational environment of undergraduated medical students. This information should be used to modify teaching environments.

Von Neumann's impossibility proof: Mathematics in the service of rhetorics

NASA Astrophysics Data System (ADS)

Dieks, Dennis

2017-11-01

According to what has become a standard history of quantum mechanics, in 1932 von Neumann persuaded the physics community that hidden variables are impossible as a matter of principle, after which leading proponents of the Copenhagen interpretation put the situation to good use by arguing that the completeness of quantum mechanics was undeniable. This state of affairs lasted, so the story continues, until Bell in 1966 exposed von Neumann's proof as obviously wrong. The realization that von Neumann's proof was fallacious then rehabilitated hidden variables and made serious foundational research possible again. It is often added in recent accounts that von Neumann's error had been spotted almost immediately by Grete Hermann, but that her discovery was of no effect due to the dominant Copenhagen Zeitgeist. We shall attempt to tell a story that is more historically accurate and less ideologically charged. Most importantly, von Neumann never claimed to have shown the impossibility of hidden variables tout court, but argued that hidden-variable theories must possess a structure that deviates fundamentally from that of quantum mechanics. Both Hermann and Bell appear to have missed this point; moreover, both raised unjustified technical objections to the proof. Von Neumann's argument was basically that hidden-variables schemes must violate the ;quantum principle; that physical quantities are to be represented by operators in a Hilbert space. As a consequence, hidden-variables schemes, though possible in principle, necessarily exhibit a certain kind of contextuality. As we shall illustrate, early reactions to Bohm's theory are in agreement with this account. Leading physicists pointed out that Bohm's theory has the strange feature that pre-existing particle properties do not generally reveal themselves in measurements, in accordance with von Neumann's result. They did not conclude that the ;impossible was done; and that von Neumann had been shown wrong.

“Invisible” Conformers of an Antifungal Disulfide Protein Revealed by Constrained Cold and Heat Unfolding, CEST-NMR Experiments, and Molecular Dynamics Calculations

PubMed Central

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-01-01

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20–40 % at 298 K in a disulfide-rich protein. In addition, sensitive 15N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR “dark matter”. Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. PMID:25676351

Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties

NASA Astrophysics Data System (ADS)

Yang, Shuangming; Deng, Bin; Wang, Jiang; Li, Huiyan; Liu, Chen; Fietkiewicz, Chris; Loparo, Kenneth A.

2017-01-01

Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization. In the proposed system, the FPGA-based unscented Kalman filter is implemented into a conductance-based TC neuron model. Since the complexity of TC neuron model restrains its hardware implementation in parallel structure, a cost efficient model is proposed to reduce the resource cost while retaining the relevant ionic dynamics. Experimental results demonstrate the real-time capability to estimate thalamocortical hidden properties with high precision under both normal and Parkinsonian states. While it is applied to estimate the hidden properties of the thalamus and explore the mechanism of the Parkinsonian state, the proposed method can be useful in the dynamic clamp technique of the electrophysiological experiments, the neural control engineering and brain-machine interface studies.

A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

Hidden order and flux attachment in symmetry-protected topological phases: A Laughlin-like approach

NASA Astrophysics Data System (ADS)

Ringel, Zohar; Simon, Steven H.

2015-05-01

Topological phases of matter are distinct from conventional ones by their lack of a local order parameter. Still in the quantum Hall effect, hidden order parameters exist and constitute the basis for the celebrated composite-particle approach. Whether similar hidden orders exist in 2D and 3D symmetry protected topological phases (SPTs) is a largely open question. Here, we introduce a new approach for generating SPT ground states, based on a generalization of the Laughlin wave function. This approach gives a simple and unifying picture of some classes of SPTs in 1D and 2D, and reveals their hidden order and flux attachment structures. For the 1D case, we derive exact relations between the wave functions obtained in this manner and group cohomology wave functions, as well as matrix product state classification. For the 2D Ising SPT, strong analytical and numerical evidence is given to show that the wave function obtained indeed describes the desired SPT. The Ising SPT then appears as a state with quasi-long-range order in composite degrees of freedom consisting of Ising-symmetry charges attached to Ising-symmetry fluxes.

Cognitive Control over Learning: Creating, Clustering, and Generalizing Task-Set Structure

ERIC Educational Resources Information Center

Collins, Anne G. E.; Frank, Michael J.

2013-01-01

Learning and executive functions such as task-switching share common neural substrates, notably prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for…

Hidden Myth: Structure & Symbolism in Advertising.

ERIC Educational Resources Information Center

Leymore, Varda Langholz

This discussion of advertising treats it as a communication system analyzable in structuralist terms. Building on the approaches of Levi-Strauss and others, the discussion begins with a general introduction to structuralism and goes on to outline the specific methodology adopted in this study. The approach is illustrated in two contexts: static…

Embodied memory allows accurate and stable perception of hidden objects despite orientation change.

PubMed

Pan, Jing Samantha; Bingham, Ned; Bingham, Geoffrey P

2017-07-01

Rotating a scene in a frontoparallel plane (rolling) yields a change in orientation of constituent images. When using only information provided by static images to perceive a scene after orientation change, identification performance typically decreases (Rock & Heimer, 1957). However, rolling generates optic flow information that relates the discrete, static images (before and after the change) and forms an embodied memory that aids recognition. The embodied memory hypothesis predicts that upon detecting a continuous spatial transformation of image structure, or in other words, seeing the continuous rolling process and objects undergoing rolling observers should accurately perceive objects during and after motion. Thus, in this case, orientation change should not affect performance. We tested this hypothesis in three experiments and found that (a) using combined optic flow and image structure, participants identified locations of previously perceived but currently occluded targets with great accuracy and stability (Experiment 1); (b) using combined optic flow and image structure information, participants identified hidden targets equally well with or without 30° orientation changes (Experiment 2); and (c) when the rolling was unseen, identification of hidden targets after orientation change became worse (Experiment 3). Furthermore, when rolling was unseen, although target identification was better when participants were told about the orientation change than when they were not told, performance was still worse than when there was no orientation change. Therefore, combined optic flow and image structure information, not mere knowledge about the rolling, enables accurate and stable perception despite orientation change. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A semi-supervised learning framework for biomedical event extraction based on hidden topics.

PubMed

Zhou, Deyu; Zhong, Dayou

2015-05-01

Scientists have devoted decades of efforts to understanding the interaction between proteins or RNA production. The information might empower the current knowledge on drug reactions or the development of certain diseases. Nevertheless, due to the lack of explicit structure, literature in life science, one of the most important sources of this information, prevents computer-based systems from accessing. Therefore, biomedical event extraction, automatically acquiring knowledge of molecular events in research articles, has attracted community-wide efforts recently. Most approaches are based on statistical models, requiring large-scale annotated corpora to precisely estimate models' parameters. However, it is usually difficult to obtain in practice. Therefore, employing un-annotated data based on semi-supervised learning for biomedical event extraction is a feasible solution and attracts more interests. In this paper, a semi-supervised learning framework based on hidden topics for biomedical event extraction is presented. In this framework, sentences in the un-annotated corpus are elaborately and automatically assigned with event annotations based on their distances to these sentences in the annotated corpus. More specifically, not only the structures of the sentences, but also the hidden topics embedded in the sentences are used for describing the distance. The sentences and newly assigned event annotations, together with the annotated corpus, are employed for training. Experiments were conducted on the multi-level event extraction corpus, a golden standard corpus. Experimental results show that more than 2.2% improvement on F-score on biomedical event extraction is achieved by the proposed framework when compared to the state-of-the-art approach. The results suggest that by incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely described by hidden topics and structures of the sentences. Copyright © 2015 Elsevier B.V. All rights reserved.

Investigation of hidden periodic structures on SEM images of opal-like materials using FFT and IFFT.

PubMed

Stephant, Nicolas; Rondeau, Benjamin; Gauthier, Jean-Pierre; Cody, Jason A; Fritsch, Emmanuel

2014-01-01

We have developed a method to use fast Fourier transformation (FFT) and inverse fast Fourier transformation (IFFT) to investigate hidden periodic structures on SEM images. We focused on samples of natural, play-of-color opals that diffract visible light and hence are periodically structured. Conventional sample preparation by hydrofluoric acid etch was not used; untreated, freshly broken surfaces were examined at low magnification relative to the expected period of the structural features, and, the SEM was adjusted to get a very high number of pixels in the images. These SEM images were treated by software to calculate autocorrelation, FFT, and IFFT. We present how we adjusted SEM acquisition parameters for best results. We first applied our procedure on an SEM image on which the structure was obvious. Then, we applied the same procedure on a sample that must contain a periodic structure because it diffracts visible light, but on which no structure was visible on the SEM image. In both cases, we obtained clearly periodic patterns that allowed measurements of structural parameters. We also investigated how the irregularly broken surface interfered with the periodic structure to produce additional periodicity. We tested the limits of our methodology with the help of simulated images. © 2014 Wiley Periodicals, Inc.

Physiological optics and physical geometry.

PubMed

Hyder, D J

2001-09-01

Hermann von Helmholtz's distinction between "pure intuitive" and "physical" geometry must be counted as the most influential of his many contributions to the philosophy of science. In a series of papers from the 1860s and 70s, Helmholtz argued against Kant's claim that our knowledge of Euclidean geometry was an a priori condition for empirical knowledge. He claimed that geometrical propositions could be meaningful only if they were taken to concern the behaviors of physical bodies used in measurement, from which it followed that it was posterior to our acquaintance with this behavior. This paper argues that Helmholtz's understanding of geometry was fundamentally shaped by his work in sense-physiology, above all on the continuum of colors. For in the course of that research, Helmholtz was forced to realize that the color-space had no inherent metrical structure. The latter was a product of axiomatic definitions of color-addition and the empirical results of such additions. Helmholtz's development of these views is explained with detailed reference to the competing work of the mathematician Hermann Grassmann and that of the young James Clerk Maxwell. It is this separation between 1) essential properties of a continuum, 2) supplementary axioms concerning distance-measurement, and 3) the behaviors of the physical apparatus used to realize the axioms, which is definitive of Helmholtz's arguments concerning geometry.

Design Overview of the DM Radio Pathfinder Experiment

NASA Technical Reports Server (NTRS)

Silva-Feaver, Maximiliano; Chaudhuri, Saptarshi; Cho, Hsaio-Mei; Dawson, Carl; Graham, Peter; Irwin, Kent; Kuenstner, Stephen; Li, Dale; Mardon, Jeremy; Moseley, Harvey;

HIPPI: highly accurate protein family classification with ensembles of HMMs.

PubMed

Nguyen, Nam-Phuong; Nute, Michael; Mirarab, Siavash; Warnow, Tandy

2016-11-11

Given a new biological sequence, detecting membership in a known family is a basic step in many bioinformatics analyses, with applications to protein structure and function prediction and metagenomic taxon identification and abundance profiling, among others. Yet family identification of sequences that are distantly related to sequences in public databases or that are fragmentary remains one of the more difficult analytical problems in bioinformatics. We present a new technique for family identification called HIPPI (Hierarchical Profile Hidden Markov Models for Protein family Identification). HIPPI uses a novel technique to represent a multiple sequence alignment for a given protein family or superfamily by an ensemble of profile hidden Markov models computed using HMMER. An evaluation of HIPPI on the Pfam database shows that HIPPI has better overall precision and recall than blastp, HMMER, and pipelines based on HHsearch, and maintains good accuracy even for fragmentary query sequences and for protein families with low average pairwise sequence identity, both conditions where other methods degrade in accuracy. HIPPI provides accurate protein family identification and is robust to difficult model conditions. Our results, combined with observations from previous studies, show that ensembles of profile Hidden Markov models can better represent multiple sequence alignments than a single profile Hidden Markov model, and thus can improve downstream analyses for various bioinformatic tasks. Further research is needed to determine the best practices for building the ensemble of profile Hidden Markov models. HIPPI is available on GitHub at https://github.com/smirarab/sepp .

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Resources of learning through hidden curriculum: Iranian nursing students’ perspective

PubMed Central

Karimi, Zohreh; Ashktorab, Tahereh; Mohammadi, Eesa; Abedi, Heidarali; Zarea, Kourosh

2015-01-01

Background: Students tend to internalize and perpetuate the patterns of behavior and the values surrounding them. Review of literature showed that there are several student learning sources through the hidden curriculum, but they have not been identified in nursing yet. Hence, the purpose of this study is explanation of learning resources in the hidden curriculum in the view of baccalaureate nursing students. Materials and Methods: This qualitative study was carried out in 2012 with the participation of 32 baccalaureate nursing students in Nursing and Midwifery College of Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran by purposeful sampling strategies. Data were collected by semi-structured interviews and continued to the level of data saturation and themes’ emergence. Data analysis was performed through inductive content analysis method. Result: “Instructor as the unique learning element,” “various learning resources in the clinical setting,” and “instructive nature of the education environment” were extracted as the main themes, each of which incorporated some categories. Conclusion: Baccalaureate undergraduate nursing students learnt the hidden curriculum by the resources such as instructors, resources existing in the clinical setting, and the university campus. Therefore, more research is recommended for the identification of other resources. In order to promote positive messages and reduce the negative messages of the hidden curricula running at academic and clinical settings, nursing educators and nurses need to learn more about this issue in the nursing profession. PMID:26430684

Modeling Protein Expression and Protein Signaling Pathways

PubMed Central

Telesca, Donatello; Müller, Peter; Kornblau, Steven M.; Suchard, Marc A.; Ji, Yuan

2015-01-01

High-throughput functional proteomic technologies provide a way to quantify the expression of proteins of interest. Statistical inference centers on identifying the activation state of proteins and their patterns of molecular interaction formalized as dependence structure. Inference on dependence structure is particularly important when proteins are selected because they are part of a common molecular pathway. In that case, inference on dependence structure reveals properties of the underlying pathway. We propose a probability model that represents molecular interactions at the level of hidden binary latent variables that can be interpreted as indicators for active versus inactive states of the proteins. The proposed approach exploits available expert knowledge about the target pathway to define an informative prior on the hidden conditional dependence structure. An important feature of this prior is that it provides an instrument to explicitly anchor the model space to a set of interactions of interest, favoring a local search approach to model determination. We apply our model to reverse-phase protein array data from a study on acute myeloid leukemia. Our inference identifies relevant subpathways in relation to the unfolding of the biological process under study. PMID:26246646

Numerical predictions and experiments for optimizing hidden corrosion detection in aircraft structures using Lamb modes.

PubMed

Terrien, N; Royer, D; Lepoutre, F; Déom, A

2007-06-01

To increase the sensitivity of Lamb waves to hidden corrosion in aircraft structures, a preliminary step is to understand the phenomena governing this interaction. A hybrid model combining a finite element approach and a modal decomposition method is used to investigate the interaction of Lamb modes with corrosion pits. The finite element mesh is used to describe the region surrounding the corrosion pits while the modal decomposition method permits to determine the waves reflected and transmitted by the damaged area. Simulations make easier the interpretation of some parts of the measured waveform corresponding to superposition of waves diffracted by the corroded area. Numerical results permit to extract significant information from the transmitted waveform and thus to optimize the signal processing for the detection of corrosion at an early stage. Now, we are able to detect corrosion pits down to 80-mum depth distributed randomly on a square centimeter of an aluminum plate. Moreover, thickness variations present on aircraft structures can be discriminated from a slightly corroded area. Finally, using this experimental setup, aircraft structures have been tested.

Propeller Churns the A Ring

NASA Image and Video Library

2010-07-08

This image is part of a set of images obtained by NASA Cassini spacecraft showing a propeller-shaped structure created by a hidden, embedded moon moving through one of Saturn rings. An animation is available at the Photojournal.

Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

PubMed

Nitta, Tohru

2017-10-01

We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

Number and measure: Hermann von Helmholtz at the crossroads of mathematics, physics, and psychology.

PubMed

Darrigol, Olivier

2003-09-01

In 1887 Helmholtz discussed the foundations of measurement in science as a last contribution to his philosophy of knowledge. This essay borrowed from earlier debates on the foundations of mathematics (Grassmann/Du Bois), on the possibility of quantitative psychology (Fechner/Kries, Wundt/Zeller), and on the meaning of temperature measurement (Maxwell,Mach.). Late nineteenth-century scrutinisers of the foundations of mathematics (Dedekind, Cantor, Frege, Russell) made little of Helmholtz's essay. Yet it inspired two mathematicians with an eye on physics (Poincaré and Hölder), and a few philosopher-physicists (Mach, Duhem,Campbell). The aim of the present paper is to situate Helmholtz's contribution in this complex array of nineteenth-century philosophies of number, quantity, and measurement. 2003 Published by Elsevier Ltd.

Geometric Lie algebra in matter, arts and mathematics with incubation of the periodic systems of the elements

NASA Astrophysics Data System (ADS)

Trell, Erik; Edeagu, Samuel; Animalu, Alexander

2017-01-01

From a brief recapitulation of the foundational works of Marius Sophus Lie and Herrmann Günther Grassmann, and including missing African links, a rhapsodic survey is made of the straight line of extension and existence that runs as the very fibre of generation and creation throughout Nature's all utterances, which must therefore ultimately be the web of Reality itself of which the Arts and Sciences are interpreters on equal explorer terms. Assuming their direct approach, the straight line and its archaic and algebraic and artistic bearings and convolutions have been followed towards their inner reaches, which earlier resulted in a retrieval of the baryon and meson elementary particles and now equally straightforward the electron geodesics and the organic build of the periodic system of the elements.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Comparison of statistical algorithms for detecting homogeneous river reaches along a longitudinal continuum

NASA Astrophysics Data System (ADS)

Leviandier, Thierry; Alber, A.; Le Ber, F.; Piégay, H.

2012-02-01

Seven methods designed to delineate homogeneous river segments, belonging to four families, namely — tests of homogeneity, contrast enhancing, spatially constrained classification, and hidden Markov models — are compared, firstly on their principles, then on a case study, and on theoretical templates. These templates contain patterns found in the case study but not considered in the standard assumptions of statistical methods, such as gradients and curvilinear structures. The influence of data resolution, noise and weak satisfaction of the assumptions underlying the methods is investigated. The control of the number of reaches obtained in order to achieve meaningful comparisons is discussed. No method is found that outperforms all the others on all trials. However, the methods with sequential algorithms (keeping at order n + 1 all breakpoints found at order n) fail more often than those running complete optimisation at any order. The Hubert-Kehagias method and Hidden Markov Models are the most successful at identifying subpatterns encapsulated within the templates. Ergodic Hidden Markov Models are, moreover, liable to exhibit transition areas.

New ARCH: Future Generation Internet Architecture

DTIC Science & Technology

2004-08-01

a vocabulary to talk about a system . This provides a framework ( a “reference model ...layered model Modularity and abstraction are central tenets of Computer Science thinking. Modularity breaks a system into parts, normally to permit...this complexity is hidden. Abstraction suggests a structure for the system . A popular and simple structure is a layered model : lower layer

Acoustic tomography for decay detection in red oak trees

Treesearch

Xiping Wang; R. Bruce Allison; Lihai Wang; Robert J. Ross

2007-01-01

The science of tree stability analysis uses both biological and engineering principles in attempting to rate a tree’s structural soundness and make reasonable predictions of potential for failure. In such analysis, arborists are often challenged by internal structural defects hidden from view within the trunks. This paper reports the results of an investigation using...

Experimentally observed conformation-dependent geometry and hidden strain in proteins.

PubMed Central

Karplus, P. A.

1996-01-01

A database has been compiled documenting the peptide conformations and geometries from 70 diverse proteins refined at 1.75 A or better. Analysis of the well-ordered residues within the database shows phi, psi-distributions that have more fine structure than is generally observed. Also, clear evidence is presented that the peptide covalent geometry depends on conformation, with the interpeptide N-C alpha-C bond angle varying by nearly +/-5 degrees from its standard value. The observed deviations from standard peptide geometry are greatest near the edges of well-populated regions, consistent with strain occurring in these conformations. Minimization of such hidden strain could be an important factor in thermostability of proteins. These empirical data describing how equilibrium peptide geometry varies as a function of conformation confirm and extend quantum mechanics calculations, and have predictive value that will aid both theoretical and experimental analyses of protein structure. PMID:8819173

A projective reconstruction method of underground or hidden structures using atmospheric muon absorption data

NASA Astrophysics Data System (ADS)

Bonechi, L.; D'Alessandro, R.; Mori, N.; Viliani, L.

2015-02-01

Muon absorption radiography is an imaging technique based on the analysis of the attenuation of the cosmic-ray muon flux after traversing an object under examination. While this technique is now reaching maturity in the field of volcanology for the imaging of the innermost parts of the volcanic cones, its applicability to other fields of research has not yet been proved. In this paper we present a study concerning the application of the muon absorption radiography technique to the field of archaeology, and we propose a method for the search of underground cavities and structures hidden a few metres deep in the soil (patent [1]). An original geometric treatment of the reconstructed muon tracks, based on the comparison of the measured flux with a reference simulated flux, and the preliminary results of specific simulations are discussed in details.

Uncovering the "Hidden Dimension": Proxemic Research Techniques Applied to Teacher Preparation.

ERIC Educational Resources Information Center

Levis-Pilz, Gladys

1982-01-01

Classroom observation assignments for preservice teachers allow them to observe detailed relationships among classroom space and teacher student interaction. Through structured observation, preservice teachers become aware of classroom interactions in a vivid and instructive manner. (CJ)

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine

PubMed Central

Liu, Yongxiang; Huo, Kai; Zhang, Zhongshuai

2018-01-01

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available. PMID:29320453

Radar HRRP Target Recognition Based on Stacked Autoencoder and Extreme Learning Machine.

PubMed

Zhao, Feixiang; Liu, Yongxiang; Huo, Kai; Zhang, Shuanghui; Zhang, Zhongshuai

2018-01-10

A novel radar high-resolution range profile (HRRP) target recognition method based on a stacked autoencoder (SAE) and extreme learning machine (ELM) is presented in this paper. As a key component of deep structure, the SAE does not only learn features by making use of data, it also obtains feature expressions at different levels of data. However, with the deep structure, it is hard to achieve good generalization performance with a fast learning speed. ELM, as a new learning algorithm for single hidden layer feedforward neural networks (SLFNs), has attracted great interest from various fields for its fast learning speed and good generalization performance. However, ELM needs more hidden nodes than conventional tuning-based learning algorithms due to the random set of input weights and hidden biases. In addition, the existing ELM methods cannot utilize the class information of targets well. To solve this problem, a regularized ELM method based on the class information of the target is proposed. In this paper, SAE and the regularized ELM are combined to make full use of their advantages and make up for each of their shortcomings. The effectiveness of the proposed method is demonstrated by experiments with measured radar HRRP data. The experimental results show that the proposed method can achieve good performance in the two aspects of real-time and accuracy, especially when only a few training samples are available.

A Multiscale Vision Model applied to analyze EIT images of the solar corona

NASA Astrophysics Data System (ADS)

Portier-Fozzani, F.; Vandame, B.; Bijaoui, A.; Maucherat, A. J.; EIT Team

2001-07-01

The large dynamic range provided by the SOHO/EIT CCD (1 : 5000) is needed to observe the large EUV zoom of coronal structures from coronal homes up to flares. Histograms show that often a wide dynamic range is present in each image. Extracting hidden structures in the background level requires specific techniques such as the use of the Multiscale Vision Model (MVM, Bijaoui et al., 1998). This method, based on wavelet transformations optimizes detection of various size objects, however complex they may be. Bijaoui et al. built the Multiscale Vision Model to extract small dynamical structures from noise, mainly for studying galaxies. In this paper, we describe requirements for the use of this method with SOHO/EIT images (calibration, size of the image, dynamics of the subimage, etc.). Two different areas were studied revealing hidden structures: (1) classical coronal mass ejection (CME) formation and (2) a complex group of active regions with its evolution. The aim of this paper is to define carefully the constraints for this new method of imaging the solar corona with SOHO/EIT. Physical analysis derived from multi-wavelength observations will later complete these first results.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Hidden momentum of electrons, nuclei, atoms, and molecules

NASA Astrophysics Data System (ADS)

Cameron, Robert P.; Cotter, J. P.

2018-04-01

We consider the positions and velocities of electrons and spinning nuclei and demonstrate that these particles harbour hidden momentum when located in an electromagnetic field. This hidden momentum is present in all atoms and molecules, however it is ultimately canceled by the momentum of the electromagnetic field. We point out that an electron vortex in an electric field might harbour a comparatively large hidden momentum and recognize the phenomenon of hidden hidden momentum.

Hidden Markov models for estimating animal mortality from anthropogenic hazards

EPA Science Inventory

Carcasses searches are a common method for studying the risk of anthropogenic hazards to wildlife, including non-target poisoning and collisions with anthropogenic structures. Typically, numbers of carcasses found must be corrected for scavenging rates and imperfect detection. ...

The perception of the hidden curriculum on medical education: an exploratory study

PubMed Central

2009-01-01

Background Major curriculum reform of undergraduate medical education occurred during the past decades in the United Kingdom (UK); however, the effects of the hidden curriculum, which influence the choice of primary care as a career, have not been sufficiently recognized. While Japan, where traditionally few institutions systematically foster primary care physicians and very few have truly embraced family medicine as their guiding discipline, has also experienced meaningful curriculum reform, the effect of the hidden curriculum is not well known. The aim of this study is to identify themes pertaining to the students' perceptions of the hidden curriculum affecting undergraduate medical education in bedside learning in Japan. Methods Semi-structured interviews with thematic content analysis were implemented. Undergraduate year-5 students from a Japanese medical school at a Japanese teaching hospital were recruited. Interview were planned to last between 30 to 60 minutes each, over an 8-month period in 2007. The interviewees' perceptions concerning the quality of teaching in their bedside learning and related experiences were collected and analysed thematically. Results Twenty five medical students (18 males and 7 females, mean age 25 years old) consented to participate in the interviews, and seven main themes emerged: "the perception of education as having a low priority," "the prevalence of positive/negative role models," "the persistence of hierarchy and exclusivity," "the existence of gender issues," "an overburdened medical knowledge," "human relationships with colleagues and medical team members," and "first experience from the practical wards and their patients." Conclusions Both similarities and differences were found when comparing the results to those of previous studies in the UK. Some effects of the hidden curriculum in medical education likely exist in common between the UK and Japan, despite the differences in their demographic backgrounds, cultures and philosophies. PMID:20003462

zipHMMlib: a highly optimised HMM library exploiting repetitions in the input to speed up the forward algorithm.

PubMed

Sand, Andreas; Kristiansen, Martin; Pedersen, Christian N S; Mailund, Thomas

2013-11-22

Hidden Markov models are widely used for genome analysis as they combine ease of modelling with efficient analysis algorithms. Calculating the likelihood of a model using the forward algorithm has worst case time complexity linear in the length of the sequence and quadratic in the number of states in the model. For genome analysis, however, the length runs to millions or billions of observations, and when maximising the likelihood hundreds of evaluations are often needed. A time efficient forward algorithm is therefore a key ingredient in an efficient hidden Markov model library. We have built a software library for efficiently computing the likelihood of a hidden Markov model. The library exploits commonly occurring substrings in the input to reuse computations in the forward algorithm. In a pre-processing step our library identifies common substrings and builds a structure over the computations in the forward algorithm which can be reused. This analysis can be saved between uses of the library and is independent of concrete hidden Markov models so one preprocessing can be used to run a number of different models.Using this library, we achieve up to 78 times shorter wall-clock time for realistic whole-genome analyses with a real and reasonably complex hidden Markov model. In one particular case the analysis was performed in less than 8 minutes compared to 9.6 hours for the previously fastest library. We have implemented the preprocessing procedure and forward algorithm as a C++ library, zipHMM, with Python bindings for use in scripts. The library is available at http://birc.au.dk/software/ziphmm/.

Tsirelson's bound and supersymmetric entangled states

PubMed Central

Borsten, L.; Brádler, K.; Duff, M. J.

2014-01-01

A superqubit, belonging to a (2|1)-dimensional super-Hilbert space, constitutes the minimal supersymmetric extension of the conventional qubit. In order to see whether superqubits are more non-local than ordinary qubits, we construct a class of two-superqubit entangled states as a non-local resource in the CHSH game. Since super Hilbert space amplitudes are Grassmann numbers, the result depends on how we extract real probabilities and we examine three choices of map: (1) DeWitt (2) Trigonometric and (3) Modified Rogers. In cases (1) and (2), the winning probability reaches the Tsirelson bound pwin=cos2π/8≃0.8536 of standard quantum mechanics. Case (3) crosses Tsirelson's bound with pwin≃0.9265. Although all states used in the game involve probabilities lying between 0 and 1, case (3) permits other changes of basis inducing negative transition probabilities. PMID:25294964

Supermanifolds from Feynman graphs

NASA Astrophysics Data System (ADS)

Marcolli, Matilde; Rej, Abhijnan

2008-08-01

We generalize the computation of Feynman integrals of log divergent graphs in terms of the Kirchhoff polynomial to the case of graphs with both fermionic and bosonic edges, to which we assign a set of ordinary and Grassmann variables. This procedure gives a computation of the Feynman integrals in terms of a period on a supermanifold, for graphs admitting a basis of the first homology satisfying a condition generalizing the log divergence in this context. The analog in this setting of the graph hypersurfaces is a graph supermanifold given by the divisor of zeros and poles of the Berezinian of a matrix associated with the graph, inside a superprojective space. We introduce a Grothendieck group for supermanifolds and identify the subgroup generated by the graph supermanifolds. This can be seen as a general procedure for constructing interesting classes of supermanifolds with associated periods.

"Invisible" conformers of an antifungal disulfide protein revealed by constrained cold and heat unfolding, CEST-NMR experiments, and molecular dynamics calculations.

PubMed

Fizil, Ádám; Gáspári, Zoltán; Barna, Terézia; Marx, Florentine; Batta, Gyula

2015-03-23

Transition between conformational states in proteins is being recognized as a possible key factor of function. In support of this, hidden dynamic NMR structures were detected in several cases up to populations of a few percent. Here, we show by two- and three-state analysis of thermal unfolding, that the population of hidden states may weight 20-40 % at 298 K in a disulfide-rich protein. In addition, sensitive (15) N-CEST NMR experiments identified a low populated (0.15 %) state that was in slow exchange with the folded PAF protein. Remarkably, other techniques failed to identify the rest of the NMR "dark matter". Comparison of the temperature dependence of chemical shifts from experiments and molecular dynamics calculations suggests that hidden conformers of PAF differ in the loop and terminal regions and are most similar in the evolutionary conserved core. Our observations point to the existence of a complex conformational landscape with multiple conformational states in dynamic equilibrium, with diverse exchange rates presumably responsible for the completely hidden nature of a considerable fraction. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Algebras Generated by Geometric Scalar Forms and their Applications in Physics and Social Sciences

DOE Office of Scientific and Technical Information (OSTI.GOV)

Keller, Jaime

2008-09-17

The present paper analyzes the consequences of defining that the geometric scalar form is not necessarily quadratic, but in general K-atic, that is obtained from the K{sup th} power of the linear form, requiring {l_brace}e{sub i};i = 1,...,N;(e{sub i}){sup K} = 1{r_brace} and d-vector {sigma}{sub i}x{sub i}e{sub i}. We consider the algebras which are thus generated, for positive integer K, a generalization of the geometric algebras we know under the names of Clifford or Grassmann algebras. We then obtain a set of geometric K-algebras. We also consider the generalization of special functions of geometry which corresponds to the K-order scalarmore » forms (as trigonometric functions and other related geometric functions which are based on the use of quadratic forms). We present an overview of the use of quadratic forms in physics as in our general theory, we have called START. And, in order to give an introduction to the use of the more general K-algebras and to the possible application to sciences other than physics, the application to social sciences is considered.For the applications to physics we show that quadratic spaces are a fundamental clue to understand the structure of theoretical physics (see, for example, Keller in ICNAAM 2005 and 2006)« less

Hidden Markov model approach for identifying the modular framework of the protein backbone.

PubMed

Camproux, A C; Tuffery, P; Chevrolat, J P; Boisvieux, J F; Hazout, S

1999-12-01

The hidden Markov model (HMM) was used to identify recurrent short 3D structural building blocks (SBBs) describing protein backbones, independently of any a priori knowledge. Polypeptide chains are decomposed into a series of short segments defined by their inter-alpha-carbon distances. Basically, the model takes into account the sequentiality of the observed segments and assumes that each one corresponds to one of several possible SBBs. Fitting the model to a database of non-redundant proteins allowed us to decode proteins in terms of 12 distinct SBBs with different roles in protein structure. Some SBBs correspond to classical regular secondary structures. Others correspond to a significant subdivision of their bounding regions previously considered to be a single pattern. The major contribution of the HMM is that this model implicitly takes into account the sequential connections between SBBs and thus describes the most probable pathways by which the blocks are connected to form the framework of the protein structures. Validation of the SBBs code was performed by extracting SBB series repeated in recoding proteins and examining their structural similarities. Preliminary results on the sequence specificity of SBBs suggest promising perspectives for the prediction of SBBs or series of SBBs from the protein sequences.

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks

PubMed Central

Jang, Hojin; Plis, Sergey M.; Calhoun, Vince D.; Lee, Jong-Hwan

2016-01-01

Feedforward deep neural networks (DNN), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean ± standard deviation; %) of 6.9 (± 3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4 ± 4.6) and the two-layer network (7.4 ± 4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. PMID:27079534

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks.

PubMed

Jang, Hojin; Plis, Sergey M; Calhoun, Vince D; Lee, Jong-Hwan

2017-01-15

Feedforward deep neural networks (DNNs), artificial neural networks with multiple hidden layers, have recently demonstrated a record-breaking performance in multiple areas of applications in computer vision and speech processing. Following the success, DNNs have been applied to neuroimaging modalities including functional/structural magnetic resonance imaging (MRI) and positron-emission tomography data. However, no study has explicitly applied DNNs to 3D whole-brain fMRI volumes and thereby extracted hidden volumetric representations of fMRI that are discriminative for a task performed as the fMRI volume was acquired. Our study applied fully connected feedforward DNN to fMRI volumes collected in four sensorimotor tasks (i.e., left-hand clenching, right-hand clenching, auditory attention, and visual stimulus) undertaken by 12 healthy participants. Using a leave-one-subject-out cross-validation scheme, a restricted Boltzmann machine-based deep belief network was pretrained and used to initialize weights of the DNN. The pretrained DNN was fine-tuned while systematically controlling weight-sparsity levels across hidden layers. Optimal weight-sparsity levels were determined from a minimum validation error rate of fMRI volume classification. Minimum error rates (mean±standard deviation; %) of 6.9 (±3.8) were obtained from the three-layer DNN with the sparsest condition of weights across the three hidden layers. These error rates were even lower than the error rates from the single-layer network (9.4±4.6) and the two-layer network (7.4±4.1). The estimated DNN weights showed spatial patterns that are remarkably task-specific, particularly in the higher layers. The output values of the third hidden layer represented distinct patterns/codes of the 3D whole-brain fMRI volume and encoded the information of the tasks as evaluated from representational similarity analysis. Our reported findings show the ability of the DNN to classify a single fMRI volume based on the extraction of hidden representations of fMRI volumes associated with tasks across multiple hidden layers. Our study may be beneficial to the automatic classification/diagnosis of neuropsychiatric and neurological diseases and prediction of disease severity and recovery in (pre-) clinical settings using fMRI volumes without requiring an estimation of activation patterns or ad hoc statistical evaluation. Copyright © 2016 Elsevier Inc. All rights reserved.

Normal Science Education and Its Dangers: The Case of School Chemistry.

ERIC Educational Resources Information Center

Van Berkel, Berry; De Vos, Wobbe; Verdonk, Adri H.; Pilot, Albert

2000-01-01

Attempts to solve the problem of hidden structure in school chemistry. Argues that normal chemistry education is isolated from common sense, everyday life and society, the history and philosophy of science, technology, school physics, and chemical research. (Author/CCM)

Photoproduction of hidden-charm states in the reaction near threshold

NASA Astrophysics Data System (ADS)

Huang, Yin; Xie, Ju-Jun; He, Jun; Chen, Xurong; Zhang, Hong-Fei

2016-12-01

We report on a theoretical study of the hidden charm states in the reaction near threshold within an effective Lagrangian approach. In addition to the contributions from the s-channel nucleon pole, the t-channel D0 exchange, the u-channel exchange and the contact term, we study the contributions from the states with spin-parity JP = 1/2- and 3/2-. The total and differential cross sections of the reaction are predicted. It is found that the contributions of these states give clear peak structures in the total cross sections. Thus, this reaction is another new platform to study the hidden-charm states. It is expected that our model calculation may be tested by future experiments. Supported by Major State Basic Research Development Program in China (2014CB845400), National Natural Science Foundation of China (11475227, 11275235, 11035006) and Chinese Academy of Sciences (Knowledge Innovation Project (KJCX2-EW-N01), Youth Innovation Promotion Association CAS (2016367), Open Project Program of State Key Laboratory of Theoretical Physics, Institute of Theoretical Physics, Chinese Academy of Sciences, China (Y5KF151CJ1)

Neutrino mixing in SO(10) GUTs with a non-Abelian flavor symmetry in the hidden sector

NASA Astrophysics Data System (ADS)

Smirnov, Alexei Yu.; Xu, Xun-Jie

2018-05-01

The relation between the mixing matrices of leptons and quarks, UPMNS≈VCKM†U0 , where U0 is a matrix of special forms [e.g., bimaximal (BM) and tribimaximal], can be a clue for understanding the lepton mixing and neutrino masses. It may imply the grand unification and the existence of a hidden sector with certain symmetry that generates U0 and leads to the smallness of neutrino masses. We apply the residual symmetry approach to obtain U0. The residual symmetries of both the visible and hidden sectors are Z2×Z2 . Their embedding in a unified flavor group is considered. We find that there are only several possible structures of U0, including the BM mixing and matrices with elements determined by the golden ratio. Realization of the BM scenario based on the SO(10) grand unified theory with the S4 flavor group is presented. Generic features of this scenario are discussed, in particular, the prediction of C P phase 14 4 ° ≲δCP≲21 0 ° in the minimal version.

Structural colours of nickel bioreplicas of butterfly wings

NASA Astrophysics Data System (ADS)

Tolenis, Tomas; Swiontek, Stephen E.; Lakhtakia, Akhlesh

2017-04-01

The two-angle conformally evaporated-film-by-rotation technique (TA-CEFR) was devised to coat the wings of the monarch butterfly with nickel in order to form a 500-nm thick bioreplica thereof. The bioreplica exhibits structural colours that are completely obscured in actual wings by pigmental colours. Thus, the TA-CEFR technique provides a way to replicate, study and exploit hidden morphologies of biological surfaces.

Learning the Hidden Structure of Speech.

DTIC Science & Technology

1987-02-01

STRUCTURE OF SPEECH J. L. Elman and D. Zipser February 1987 ICS Report 8701 COGNITIVE SCIENCE ,a - ~QIt b’eez INSTITUTE FOR COGNITIVE SCIENCE...Zipser February 1987 ICS Report 8701 *0:-.:-! ,%. ., Jeffrey L. Elman David Zipser Department of Linguistics Institute for Cognitive Science...any purpose of the United States Government. Requests for reprints should be sent to the Institute for Cognitive Science, C-015; University of

Smart aircraft fastener evaluation (SAFE) system: a condition-based corrosion detection system for aging aircraft

NASA Astrophysics Data System (ADS)

Schoess, Jeffrey N.; Seifert, Greg; Paul, Clare A.

1996-05-01

The smart aircraft fastener evaluation (SAFE) system is an advanced structural health monitoring effort to detect and characterize corrosion in hidden and inaccessible locations of aircraft structures. Hidden corrosion is the number one logistics problem for the U.S. Air Force, with an estimated maintenance cost of $700M per year in 1990 dollars. The SAFE system incorporates a solid-state electrochemical microsensor and smart sensor electronics in the body of a Hi-Lok aircraft fastener to process and autonomously report corrosion status to aircraft maintenance personnel. The long-term payoff for using SAFE technology will be in predictive maintenance for aging aircraft and rotorcraft systems, fugitive emissions applications such as control valves, chemical pipeline vessels, and industrial boilers. Predictive maintenance capability, service, and repair will replace the current practice of scheduled maintenance to substantially reduce operational costs. A summary of the SAFE concept, laboratory test results, and future field test plans is presented.

Conserved patterns hidden within group A Streptococcus M protein hypervariability recognize human C4b-binding protein

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buffalo, Cosmo Z.; Bahn-Suh, Adrian J.; Hirakis, Sophia P.

No vaccine exists against group A Streptococcus (GAS), a leading cause of worldwide morbidity and mortality. A severe hurdle is the hypervariability of its major antigen, the M protein, with >200 different M types known. Neutralizing antibodies typically recognize M protein hypervariable regions (HVRs) and confer narrow protection. In stark contrast, human C4b-binding protein (C4BP), which is recruited to the GAS surface to block phagocytic killing, interacts with a remarkably large number of M protein HVRs (apparently ~90%). Such broad recognition is rare, and we discovered a unique mechanism for this through the structure determination of four sequence-diverse M proteinsmore » in complexes with C4BP. The structures revealed a uniform and tolerant ‘reading head’ in C4BP, which detected conserved sequence patterns hidden within hypervariability. Our results open up possibilities for rational therapies that target the M–C4BP interaction, and also inform a path towards vaccine design.« less

Hidden Attractors in Dynamical Systems. From Hidden Oscillations in Hilbert-Kolmogorov Aizerman, and Kalman Problems to Hidden Chaotic Attractor in Chua Circuits

NASA Astrophysics Data System (ADS)

Leonov, G. A.; Kuznetsov, N. V.

From a computational point of view, in nonlinear dynamical systems, attractors can be regarded as self-excited and hidden attractors. Self-excited attractors can be localized numerically by a standard computational procedure, in which after a transient process a trajectory, starting from a point of unstable manifold in a neighborhood of equilibrium, reaches a state of oscillation, therefore one can easily identify it. In contrast, for a hidden attractor, a basin of attraction does not intersect with small neighborhoods of equilibria. While classical attractors are self-excited, attractors can therefore be obtained numerically by the standard computational procedure. For localization of hidden attractors it is necessary to develop special procedures, since there are no similar transient processes leading to such attractors. At first, the problem of investigating hidden oscillations arose in the second part of Hilbert's 16th problem (1900). The first nontrivial results were obtained in Bautin's works, which were devoted to constructing nested limit cycles in quadratic systems, that showed the necessity of studying hidden oscillations for solving this problem. Later, the problem of analyzing hidden oscillations arose from engineering problems in automatic control. In the 50-60s of the last century, the investigations of widely known Markus-Yamabe's, Aizerman's, and Kalman's conjectures on absolute stability have led to the finding of hidden oscillations in automatic control systems with a unique stable stationary point. In 1961, Gubar revealed a gap in Kapranov's work on phase locked-loops (PLL) and showed the possibility of the existence of hidden oscillations in PLL. At the end of the last century, the difficulties in analyzing hidden oscillations arose in simulations of drilling systems and aircraft's control systems (anti-windup) which caused crashes. Further investigations on hidden oscillations were greatly encouraged by the present authors' discovery, in 2010 (for the first time), of chaotic hidden attractor in Chua's circuit. This survey is dedicated to efficient analytical-numerical methods for the study of hidden oscillations. Here, an attempt is made to reflect the current trends in the synthesis of analytical and numerical methods.

"Hidden" bone metastasis from thyroid carcinoma: a clinical note.

PubMed

Sioka, C; Skarulis, M C; Tulloch-Reid, M K; Heiss, J D; Reynolds, J C

2014-01-01

The (131)I-iodide ((131)I) whole-body scan, for thyroid carcinoma is at times difficult to interpret. In a diagnostic whole body (131)I scan of a patient with follicular carcinoma, a posterior skull lesion was partially hidden by overlapping facial structures. On lateral head view, the abnormality was clearly evident. SPECT/CT and MRI showed the lesion originated in the occipital bone and had enlarged into the posterior fossa. The mass was surgically removed and the patient received (131)I therapy for residual tissue. The study demonstrates a pitfall in the reading of two dimensional radioiodine images which can be overcome by SPECT or lateral imaging. Copyright © 2013 Elsevier España, S.L. and SEMNIM. All rights reserved.

A hidden markov model derived structural alphabet for proteins.

PubMed

Camproux, A C; Gautier, R; Tufféry, P

2004-06-04

Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction.

Investigation of an HMM/ANN hybrid structure in pattern recognition application using cepstral analysis of dysarthric (distorted) speech signals.

PubMed

Polur, Prasad D; Miller, Gerald E

2006-10-01

Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech (isolated word) recognition system, intended to act as an assistive tool, was investigated. A small size vocabulary spoken by three cerebral palsy subjects was chosen. The effect of such a structure on the recognition rate of the system was investigated by comparing it with an ergodic hidden Markov model as a control tool. This was done in order to determine if this modified technique contributed to enhanced recognition of dysarthric speech. The speech was sampled at 11 kHz. Mel frequency cepstral coefficients were extracted from them using 15 ms frames and served as training input to the hybrid model setup. The subsequent results demonstrated that the hybrid model structure was quite robust in its ability to handle the large variability and non-conformity of dysarthric speech. The level of variability in input dysarthric speech patterns sometimes limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor impaired individuals holds sufficient promise.

A Gradient-Field Pulsed Eddy Current Probe for Evaluation of Hidden Material Degradation in Conductive Structures Based on Lift-Off Invariance

PubMed Central

Li, Yong; Jing, Haoqing; Zainal Abidin, Ilham Mukriz; Yan, Bei

2017-01-01

Coated conductive structures are widely adopted in such engineering fields as aerospace, nuclear energy, etc. The hostile and corrosive environment leaves in-service coated conductive structures vulnerable to Hidden Material Degradation (HMD) occurring under the protection coating. It is highly demanded that HMD can be non-intrusively assessed using non-destructive evaluation techniques. In light of the advantages of Gradient-field Pulsed Eddy Current technique (GPEC) over other non-destructive evaluation methods in corrosion evaluation, in this paper the GPEC probe for quantitative evaluation of HMD is intensively investigated. Closed-form expressions of GPEC responses to HMD are formulated via analytical modeling. The Lift-off Invariance (LOI) in GPEC signals, which makes the HMD evaluation immune to the variation in thickness of the protection coating, is introduced and analyzed through simulations involving HMD with variable depths and conductivities. A fast inverse method employing magnitude and time of the LOI point in GPEC signals for simultaneously evaluating the conductivity and thickness of HMD region is proposed, and subsequently verified by finite element modeling and experiments. It has been found from the results that along with the proposed inverse method the GPEC probe is applicable to evaluation of HMD in coated conductive structures without much loss in accuracy. PMID:28441328

Marvels of enzyme catalysis at true atomic resolution: distortions, bond elongations, hidden flips, protonation states and atom identities.

PubMed

Neumann, Piotr; Tittmann, Kai

2014-12-01

Although general principles of enzyme catalysis are fairly well understood nowadays, many important details of how exactly the substrate is bound and processed in an enzyme remain often invisible and as such elusive. In fortunate cases, structural analysis of enzymes can be accomplished at true atomic resolution thus making possible to shed light on otherwise concealed fine-structural traits of bound substrates, intermediates, cofactors and protein groups. We highlight recent structural studies of enzymes using ultrahigh-resolution X-ray protein crystallography showcasing its enormous potential as a tool in the elucidation of enzymatic mechanisms and in unveiling fundamental principles of enzyme catalysis. We discuss the observation of seemingly hyper-reactive, physically distorted cofactors and intermediates with elongated scissile substrate bonds, the detection of 'hidden' conformational and chemical equilibria and the analysis of protonation states with surprising findings. In delicate cases, atomic resolution is required to unambiguously disclose the identity of atoms as demonstrated for the metal cluster in nitrogenase. In addition to the pivotal structural findings and the implications for our understanding of enzyme catalysis, we further provide a practical framework for resolution enhancement through optimized data acquisition and processing. Copyright © 2014 Elsevier Ltd. All rights reserved.

A Gradient-Field Pulsed Eddy Current Probe for Evaluation of Hidden Material Degradation in Conductive Structures Based on Lift-Off Invariance.

PubMed

Li, Yong; Jing, Haoqing; Zainal Abidin, Ilham Mukriz; Yan, Bei

2017-04-25

Coated conductive structures are widely adopted in such engineering fields as aerospace, nuclear energy, etc. The hostile and corrosive environment leaves in-service coated conductive structures vulnerable to Hidden Material Degradation (HMD) occurring under the protection coating. It is highly demanded that HMD can be non-intrusively assessed using non-destructive evaluation techniques. In light of the advantages of Gradient-field Pulsed Eddy Current technique (GPEC) over other non-destructive evaluation methods in corrosion evaluation, in this paper the GPEC probe for quantitative evaluation of HMD is intensively investigated. Closed-form expressions of GPEC responses to HMD are formulated via analytical modeling. The Lift-off Invariance (LOI) in GPEC signals, which makes the HMD evaluation immune to the variation in thickness of the protection coating, is introduced and analyzed through simulations involving HMD with variable depths and conductivities. A fast inverse method employing magnitude and time of the LOI point in GPEC signals for simultaneously evaluating the conductivity and thickness of HMD region is proposed, and subsequently verified by finite element modeling and experiments. It has been found from the results that along with the proposed inverse method the GPEC probe is applicable to evaluation of HMD in coated conductive structures without much loss in accuracy.

Coherent states for quantum compact groups

NASA Astrophysics Data System (ADS)

Jurĉo, B.; Ŝťovíĉek, P.

1996-12-01

Coherent states are introduced and their properties are discussed for simple quantum compact groups A l, Bl, Cl and D l. The multiplicative form of the canonical element for the quantum double is used to introduce the holomorphic coordinates on a general quantum dressing orbit. The coherent state is interpreted as a holomorphic function on this orbit with values in the carrier Hilbert space of an irreducible representation of the corresponding quantized enveloping algebra. Using Gauss decomposition, the commutation relations for the holomorphic coordinates on the dressing orbit are derived explicitly and given in a compact R-matrix formulation (generalizing this way the q-deformed Grassmann and flag manifolds). The antiholomorphic realization of the irreducible representations of a compact quantum group (the analogue of the Borel-Weil construction) is described using the concept of coherent state. The relation between representation theory and non-commutative differential geometry is suggested.

Thermodynamic analyses of a biomass-coal co-gasification power generation system.

PubMed

Yan, Linbo; Yue, Guangxi; He, Boshu

2016-04-01

A novel chemical looping power generation system is presented based on the biomass-coal co-gasification with steam. The effects of different key operation parameters including biomass mass fraction (Rb), steam to carbon mole ratio (Rsc), gasification temperature (Tg) and iron to fuel mole ratio (Rif) on the system performances like energy efficiency (ηe), total energy efficiency (ηte), exergy efficiency (ηex), total exergy efficiency (ηtex) and carbon capture rate (ηcc) are analyzed. A benchmark condition is set, under which ηte, ηtex and ηcc are found to be 39.9%, 37.6% and 96.0%, respectively. Furthermore, detailed energy Sankey diagram and exergy Grassmann diagram are drawn for the entire system operating under the benchmark condition. The energy and exergy efficiencies of the units composing the system are also predicted. Copyright © 2016 Elsevier Ltd. All rights reserved.

The First Fundamental Theorem of Invariant Theory for the Orthosymplectic Supergroup

NASA Astrophysics Data System (ADS)

Lehrer, G. I.; Zhang, R. B.

2017-01-01

We give an elementary and explicit proof of the first fundamental theorem of invariant theory for the orthosymplectic supergroup by generalising the geometric method of Atiyah, Bott and Patodi to the supergroup context. We use methods from super-algebraic geometry to convert invariants of the orthosymplectic supergroup into invariants of the corresponding general linear supergroup on a different space. In this way, super Schur-Weyl-Brauer duality is established between the orthosymplectic supergroup of superdimension ( m|2 n) and the Brauer algebra with parameter m - 2 n. The result may be interpreted either in terms of the group scheme OSp( V) over C, where V is a finite dimensional super space, or as a statement about the orthosymplectic Lie supergroup over the infinite dimensional Grassmann algebra {Λ}. We take the latter point of view here, and also state a corresponding theorem for the orthosymplectic Lie superalgebra, which involves an extra invariant generator, the super-Pfaffian.

Conceptual design and kinematic analysis of a novel parallel robot for high-speed pick-and-place operations

NASA Astrophysics Data System (ADS)

Meng, Qizhi; Xie, Fugui; Liu, Xin-Jun

2018-06-01

This paper deals with the conceptual design, kinematic analysis and workspace identification of a novel four degrees-of-freedom (DOFs) high-speed spatial parallel robot for pick-and-place operations. The proposed spatial parallel robot consists of a base, four arms and a 1½ mobile platform. The mobile platform is a major innovation that avoids output singularity and offers the advantages of both single and double platforms. To investigate the characteristics of the robot's DOFs, a line graph method based on Grassmann line geometry is adopted in mobility analysis. In addition, the inverse kinematics is derived, and the constraint conditions to identify the correct solution are also provided. On the basis of the proposed concept, the workspace of the robot is identified using a set of presupposed parameters by taking input and output transmission index as the performance evaluation criteria.

Three-dimensional fractional-spin gravity

NASA Astrophysics Data System (ADS)

Boulanger, Nicolas; Sundell, Per; Valenzuela, Mauricio

2014-02-01

Using Wigner-deformed Heisenberg oscillators, we construct 3D Chern-Simons models consisting of fractional-spin fields coupled to higher-spin gravity and internal nonabelian gauge fields. The gauge algebras consist of Lorentz-tensorial Blencowe-Vasiliev higher-spin algebras and compact internal algebras intertwined by infinite-dimensional generators in lowest-weight representations of the Lorentz algebra with fractional spin. In integer or half-integer non-unitary cases, there exist truncations to gl(ℓ , ℓ ± 1) or gl(ℓ|ℓ ± 1) models. In all non-unitary cases, the internal gauge fields can be set to zero. At the semi-classical level, the fractional-spin fields are either Grassmann even or odd. The action requires the enveloping-algebra representation of the deformed oscillators, while their Fock-space representation suffices on-shell. The project was funded in part by F.R.S.-FNRS " Ulysse" Incentive Grant for Mobility in Scientific Research.

The secret art of managing healthcare expenses: investigating implicit rationing and autonomy in public healthcare systems.

PubMed

Lauridsen, S M R; Norup, M S; Rossel, P J H

2007-12-01

Rationing healthcare is a difficult task, which includes preventing patients from accessing potentially beneficial treatments. Proponents of implicit rationing argue that politicians cannot resist pressure from strong patient groups for treatments and conclude that physicians should ration without informing patients or the public. The authors subdivide this specific programme of implicit rationing, or "hidden rationing", into local hidden rationing, unsophisticated global hidden rationing and sophisticated global hidden rationing. They evaluate the appropriateness of these methods of rationing from the perspectives of individual and political autonomy and conclude that local hidden rationing and unsophisticated global hidden rationing clearly violate patients' individual autonomy, that is, their right to participate in medical decision-making. While sophisticated global hidden rationing avoids this charge, the authors point out that it nonetheless violates the political autonomy of patients, that is, their right to engage in public affairs as citizens. A defence of any of the forms of hidden rationing is therefore considered to be incompatible with a defence of autonomy.

Discriminative latent models for recognizing contextual group activities.

PubMed

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N; Mori, Greg

2012-08-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities.

Discriminative Latent Models for Recognizing Contextual Group Activities

PubMed Central

Lan, Tian; Wang, Yang; Yang, Weilong; Robinovitch, Stephen N.; Mori, Greg

2012-01-01

In this paper, we go beyond recognizing the actions of individuals and focus on group activities. This is motivated from the observation that human actions are rarely performed in isolation; the contextual information of what other people in the scene are doing provides a useful cue for understanding high-level activities. We propose a novel framework for recognizing group activities which jointly captures the group activity, the individual person actions, and the interactions among them. Two types of contextual information, group-person interaction and person-person interaction, are explored in a latent variable framework. In particular, we propose three different approaches to model the person-person interaction. One approach is to explore the structures of person-person interaction. Differently from most of the previous latent structured models, which assume a predefined structure for the hidden layer, e.g., a tree structure, we treat the structure of the hidden layer as a latent variable and implicitly infer it during learning and inference. The second approach explores person-person interaction in the feature level. We introduce a new feature representation called the action context (AC) descriptor. The AC descriptor encodes information about not only the action of an individual person in the video, but also the behavior of other people nearby. The third approach combines the above two. Our experimental results demonstrate the benefit of using contextual information for disambiguating group activities. PMID:22144516

Three-dimensional reconstruction with x-ray shape-from-silhouette

NASA Astrophysics Data System (ADS)

Simioni, E.; Ratti, F.; Calliari, I.; Poletto, L.

2010-09-01

In the field of restoration of ancient handworks, X-ray tomography is a powerful method to reconstruct the internal structure of the object in non-invasive way. In some cases, such as small objects fully realized with hard metals and completely hidden by clay or products of oxidation, the tomography, although necessary to obtain the 3D appearance of the object, does not give any additional information on its internal monolithic structure. We present here the application of the shape-from-silhouette technique on X-ray images to reconstruct the 3D profile of handworks. The acquisition technique is similar to tomography, since several X-ray images are taken while the object is rotated. Some reference points are placed on a structure co-rotating with the object and are acquired on the images for calibration and registration. The shape-from-silhouette algorithm gives finally the 3D appearance of the handwork. We present the analysis of a tin pendant of VI-VIII century b.C. (Venetian area) completely hidden by solid ground. The 3D reconstruction shows surprisingly that the pendant is a very elaborated piece, with two embraced figures that were completely invisible before restoration.

The Hidden Curriculum as Emancipatory and Non-Emancipatory Tools.

ERIC Educational Resources Information Center

Kanpol, Barry

Moral values implied in school practices and policies constitute the "hidden curriculum." Because the hidden curriculum may promote certain moral values to students, teachers are partially responsible for the moral education of students. A component of the hidden curriculum, institutional political resistance, concerns teacher opposition to…

Subsurface Mapping: A Question of Position and Interpretation

ERIC Educational Resources Information Center

Kellie, Andrew C.

2009-01-01

This paper discusses the character and challenges inherent in the graphical portrayal of features in subsurface mapping. Subsurface structures are, by their nature, hidden and must be mapped based on drilling and/or geophysical data. Efficient use of graphical techniques is central to effectively communicating the results of expensive exploration…

Discovering the Sequential Structure of Thought

ERIC Educational Resources Information Center

Anderson, John R.; Fincham, Jon M.

2014-01-01

Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel…

Uncovering the "Hidden" Multilingualism of Europe: An Italian Case Study

ERIC Educational Resources Information Center

Tamburelli, Marco

2014-01-01

Dominant notions of what constitutes a "language" and what a "dialect" within a continuum are entirely based on sociopolitical factors (i.e. the "languages by 'Ausbau'" of Kloss), totally disregarding structural and communicative aspects. This paper argues that such stance is no longer tenable in view of the modern…

Technology and English Language Teaching (ELT)

ERIC Educational Resources Information Center

Kazzemi, Akram; Narafshan, Mehry Haddad

2014-01-01

This paper is a try to investigate the attitudes of English language university teachers in Kerman (Iran) toward computer technology and find the hidden factors that make university teachers avoid using technology in English language teaching. 30 university teachers participated in this study. A questionnaire and semi-structured interview were…

Knock at Any School.

ERIC Educational Resources Information Center

Parish, Ralph; And Others

1989-01-01

In poor, urban schools, so much time is spent controlling and disciplining children to obey authority (or to learn the hidden curriculum), that scant time is left for "real" teaching and learning. This article shows how school culture (conditions, norms, relationships, and structures) can be changed to educate all children adequately. Includes 10…

Photoacoustic imaging of hidden dental caries by using a fiber-based probing system

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2017-04-01

Photoacoustic method to detect hidden dental caries is proposed. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating laser light to occlusal surface of model tooth. By making a map of intensity of these high frequency components, photoacoustic images of hidden caries were successfully obtained. A photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for using clinical application, and clear photoacoustic image of hidden caries was also obtained by this system.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alfaro, Ruben

An application of high energy physics instrumentation is to look for structure or different densities (materials) hidden in a matrix (tons) of material. By tracing muons produced by primary Cosmic Rays, it has been possible to generate a kind of radiographs which shows the inner structure of dense containers, monuments or mountains. In this paper I review the basics principles of such techniques with emphasis in the Sun Pyramid project, carried out by IFUNAM in collaboration with Instituto Nacioanal de Antropologia e Historia.

--No Title--

Science.gov Websites

;height:auto;overflow:hidden}.poc_table .top_row{background-color:#eee;height:auto;overflow:hidden}.poc_table ;background-color:#FFF;height:auto;overflow:hidden;border-top:1px solid #ccc}.poc_table .main_row .name :200px;padding:5px;height:auto;overflow:hidden}.tli_grey_box{background-color:#eaeaea;text-align:center

Natural hidden antibodies reacting with DNA or cardiolipin bind to thymocytes and evoke their death.

PubMed

Zamulaeva, I A; Lekakh, I V; Kiseleva, V I; Gabai, V L; Saenko, A S; Shevchenko, A S; Poverenny, A M

1997-08-18

Both free and hidden natural antibodies to DNA or cardiolipin were obtained from immunoglobulins of a normal donor. The free antibodies reacting with DNA or cardiolipin were isolated by means of affinity chromatography. Antibodies occurring in an hidden state were disengaged from the depleted immunoglobulins by ion-exchange chromatography and were then affinity-isolated on DNA or cardiolipin sorbents. We used flow cytometry to study the ability of free and hidden antibodies to bind to rat thymocytes. Simultaneously, plasma membrane integrity was tested by propidium iodide (PI) exclusion. The hidden antibodies reacted with 65.2 +/- 10.9% of the thymocytes and caused a fast plasma membrane disruption. Cells (28.7 +/- 7.1%) were stained with PI after incubation with the hidden antibodies for 1 h. The free antibodies bound to a very small fraction of the thymocytes and did not evoke death as compared to control without antibodies. The possible reason for the observed effects is difference in reactivity of the free and hidden antibodies to phospholipids. While free antibodies reacted preferentially with phosphotidylcholine, hidden antibodies reacted with cardiolipin and phosphotidylserine.

Analyzing hidden populations online: topic, emotion, and social network of HIV-related users in the largest Chinese online community.

PubMed

Liu, Chuchu; Lu, Xin

2018-01-05

Traditional survey methods are limited in the study of hidden populations due to the hard to access properties, including lack of a sampling frame, sensitivity issue, reporting error, small sample size, etc. The rapid increase of online communities, of which members interact with others via the Internet, have generated large amounts of data, offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. In this study, we try to understand the multidimensional characteristics of a hidden population by analyzing the massive data generated in the online community. By elaborately designing crawlers, we retrieved a complete dataset from the "HIV bar," the largest bar related to HIV on the Baidu Tieba platform, for all records from January 2005 to August 2016. Through natural language processing and social network analysis, we explored the psychology, behavior and demand of online HIV population and examined the network community structure. In HIV communities, the average topic similarity among members is positively correlated to network efficiency (r = 0.70, p < 0.001), indicating that the closer the social distance between members of the community, the more similar their topics. The proportion of negative users in each community is around 60%, weakly correlated with community size (r = 0.25, p = 0.002). It is found that users suspecting initial HIV infection or first in contact with high-risk behaviors tend to seek help and advice on the social networking platform, rather than immediately going to a hospital for blood tests. Online communities have generated copious amounts of data offering new opportunities for understanding hidden populations with unprecedented sample sizes and richness of information. It is recommended that support through online services for HIV/AIDS consultation and diagnosis be improved to avoid privacy concerns and social discrimination in China.

Raising awareness of the hidden curriculum in veterinary medical education: a review and call for research.

PubMed

Whitcomb, Tiffany L

2014-01-01

The hidden curriculum is characterized by information that is tacitly conveyed to and among students about the cultural and moral environment in which they find themselves. Although the hidden curriculum is often defined as a distinct entity, tacit information is conveyed to students throughout all aspects of formal and informal curricula. This unconsciously communicated knowledge has been identified across a wide spectrum of educational environments and is known to have lasting and powerful impacts, both positive and negative. Recently, medical education research on the hidden curriculum of becoming a doctor has come to the forefront as institutions struggle with inconsistencies between formal and hidden curricula that hinder the practice of patient-centered medicine. Similarly, the complex ethical questions that arise during the practice and teaching of veterinary medicine have the potential to cause disagreement between what the institution sets out to teach and what is actually learned. However, the hidden curriculum remains largely unexplored for this field. Because the hidden curriculum is retained effectively by students, elucidating its underlying messages can be a key component of program refinement. A review of recent literature about the hidden curriculum in a variety of fields, including medical education, will be used to explore potential hidden curricula in veterinary medicine and draw attention to the need for further investigation.

The saturation of monochromatic lights obliquely incident on the retina.

PubMed Central

Alpern, M; Tamaki, R

1983-01-01

Foveal dark-adaptation undertaken to test the hypothesis that the excitation of rods causes the desaturation of 'yellow' lights in a 1 degree field traversing the margin of the pupil, fails to exclude that possibility. The desaturation is largest for a 1 degree outside diameter annular test, is still measurable with a 0.5 degree circular disk, but disappears for a 0.29 degree disk. The supersaturation of obliquely incident 501.2 nm test light follows the opposite pattern; it disappears with an annulus and is largest for a 0.29 degree circular field. It is unlikely that rods replace short-wave sensitive cones in the trichromatic match of an obliquely incident test with normally incident primaries. If rods as well as all three cones species are involved, the matches might not be trichromatic in the strong sense. Grassmann's law of scalar multiplication was tested and shown not to hold for the match of an obliquely incident test with normally incident primaries, though it remains valid whenever, both primaries and test strike the retina at the same angle of incidence (independent of that angle). The result in section 3 (above) cannot be due to rod intrusion. It persists (and becomes more conspicuous) on backgrounds (4.0 log scotopic td) which saturate rods. Moreover obliquely incident 'yellow' lights remain desaturated in intervals in the dark after a full bleach, whilst the test field is below rod threshold. The amount of desaturation does not differ appreciably from that normally found. The assumption of the unified theory of Alpern, Kitahara & Tamaki (1983) that the outer segments of only a single set of three cone species (with acceptance angles wide enough to include the entire exit pupil) contain the visual pigments absorbing both the normally incident primaries and the obliquely incident test is disproved by these results. Failure of Grassmann's law is most conspicuous under the conditions for which the changes in saturation upon changing from normal to oblique incidence are greatest and least when the saturation changes are the smallest. Either all unified theories of the Stiles-Crawford effects are wrong or all the effects of oblique incidence operate at a stage in the visual process at which the effects of radiation of different wave-lengths are no longer compounded by the simple linear laws. PMID:6875976

Hidden topological constellations and polyvalent charges in chiral nematic droplets

NASA Astrophysics Data System (ADS)

Posnjak, Gregor; Čopar, Simon; Muševič, Igor

2017-02-01

Topology has an increasingly important role in the physics of condensed matter, quantum systems, material science, photonics and biology, with spectacular realizations of topological concepts in liquid crystals. Here we report on long-lived hidden topological states in thermally quenched, chiral nematic droplets, formed from string-like, triangular and polyhedral constellations of monovalent and polyvalent singular point defects. These topological defects are regularly packed into a spherical liquid volume and stabilized by the elastic energy barrier due to the helical structure and confinement of the liquid crystal in the micro-sphere. We observe, for the first time, topological three-dimensional point defects of the quantized hedgehog charge q=-2, -3. These higher-charge defects act as ideal polyvalent artificial atoms, binding the defects into polyhedral constellations representing topological molecules.

Galaxies Detected by the Dwingeloo Obscured Galaxies Survey

NASA Astrophysics Data System (ADS)

Rivers, A. J.; Henning, P. A.; Kraan-Korteweg, R. C.

1999-04-01

The Dwingeloo Obscured Galaxies Survey (DOGS) is a 21-cm blind survey for galaxies hidden in the northern `Zone of Avoidance' (ZOA): the portion of the optical extragalactic sky which is obscured by dust in the Milky Way. Like the Parkes southern hemisphere ZOA survey, the DOGS project is designed to reveal hidden dynamically important nearby galaxies and to help `fill in the blanks' in the local large scale structure. To date, 36 galaxies have been detected by the Dwingeloo survey; 23 of these were previously unknown [no corresponding sources recorded in the NASA Extragalactic Database (NED)]. Among the interesting detections are three nearby galaxies in the vicinity of NGC 6946 and 11 detections in the Supergalactic plane crossing region. VLA follow-up observations have been conducted for several of the DOGS detections.

Hidden topological constellations and polyvalent charges in chiral nematic droplets

PubMed Central

Posnjak, Gregor; Čopar, Simon; Muševič, Igor

2017-01-01

Topology has an increasingly important role in the physics of condensed matter, quantum systems, material science, photonics and biology, with spectacular realizations of topological concepts in liquid crystals. Here we report on long-lived hidden topological states in thermally quenched, chiral nematic droplets, formed from string-like, triangular and polyhedral constellations of monovalent and polyvalent singular point defects. These topological defects are regularly packed into a spherical liquid volume and stabilized by the elastic energy barrier due to the helical structure and confinement of the liquid crystal in the micro-sphere. We observe, for the first time, topological three-dimensional point defects of the quantized hedgehog charge q=−2, −3. These higher-charge defects act as ideal polyvalent artificial atoms, binding the defects into polyhedral constellations representing topological molecules. PMID:28220770

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

Heating up the Galaxy with hidden photons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubovsky, Sergei; Hernández-Chifflet, Guzmán, E-mail: dubovsky@nyu.edu, E-mail: ghc236@nyu.edu

2015-12-01

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Heating up the Galaxy with hidden photons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dubovsky, Sergei; Hernández-Chifflet, Guzmán; Instituto de Física, Facultad de Ingeniería, Universidad de la República,Montevideo, 11300

2015-12-29

We elaborate on the dynamics of ionized interstellar medium in the presence of hidden photon dark matter. Our main focus is the ultra-light regime, where the hidden photon mass is smaller than the plasma frequency in the Milky Way. We point out that as a result of the Galactic plasma shielding direct detection of ultra-light photons in this mass range is especially challenging. However, we demonstrate that ultra-light hidden photon dark matter provides a powerful heating source for the ionized interstellar medium. This results in a strong bound on the kinetic mixing between hidden and regular photons all the waymore » down to the hidden photon masses of order 10{sup −20} eV.« less

Site-specific electronic structure analysis by channeling EELS and first-principles calculations.

PubMed

Tatsumi, Kazuyoshi; Muto, Shunsuke; Yamamoto, Yu; Ikeno, Hirokazu; Yoshioka, Satoru; Tanaka, Isao

2006-01-01

Site-specific electronic structures were investigated by electron energy loss spectroscopy (EELS) under electron channeling conditions. The Al-K and Mn-L(2,3) electron energy loss near-edge structure (ELNES) of, respectively, NiAl2O4 and Mn3O4 were measured. Deconvolution of the raw spectra with the instrumental resolution function restored the blunt and hidden fine features, which allowed us to interpret the experimental spectral features by comparing with theoretical spectra obtained by first-principles calculations. The present method successfully revealed the electronic structures specific to the differently coordinated cationic sites.

High pressure air compressor valve fault diagnosis using feedforward neural networks

NASA Astrophysics Data System (ADS)

James Li, C.; Yu, Xueli

1995-09-01

Feedforward neural networks (FNNs) are developed and implemented to classify a four-stage high pressure air compressor into one of the following conditions: baseline, suction or exhaust valve faults. These FNNs are used for the compressor's automatic condition monitoring and fault diagnosis. Measurements of 39 variables are obtained under different baseline conditions and third-stage suction and exhaust valve faults. These variables include pressures and temperatures at all stages, voltage between phase aand phase b, voltage between phase band phase c, total three-phase real power, cooling water flow rate, etc. To reduce the number of variables, the amount of their discriminatory information is quantified by scattering matrices to identify statistical significant ones. Measurements of the selected variables are then used by a fully automatic structural and weight learning algorithm to construct three-layer FNNs to classify the compressor's condition. This learning algorithm requires neither guesses of initial weight values nor number of neurons in the hidden layer of an FNN. It takes an incremental approach in which a hidden neuron is trained by exemplars and then augmented to the existing network. These exemplars are then made orthogonal to the newly identified hidden neuron. They are subsequently used for the training of the next hidden neuron. The betterment continues until a desired accuracy is reached. After the neural networks are established, novel measurements from various conditions that haven't been previously seen by the FNNs are then used to evaluate their ability in fault diagnosis. The trained neural networks provide very accurate diagnosis for suction and discharge valve defects.

Artificial Intelligence in Prediction of Secondary Protein Structure Using CB513 Database

PubMed Central

Avdagic, Zikrija; Purisevic, Elvir; Omanovic, Samir; Coralic, Zlatan

2009-01-01

In this paper we describe CB513 a non-redundant dataset, suitable for development of algorithms for prediction of secondary protein structure. A program was made in Borland Delphi for transforming data from our dataset to make it suitable for learning of neural network for prediction of secondary protein structure implemented in MATLAB Neural-Network Toolbox. Learning (training and testing) of neural network is researched with different sizes of windows, different number of neurons in the hidden layer and different number of training epochs, while using dataset CB513. PMID:21347158

Foot anthropometry and morphology phenomena.

PubMed

Agić, Ante; Nikolić, Vasilije; Mijović, Budimir

2006-12-01

Foot structure description is important for many reasons. The foot anthropometric morphology phenomena are analyzed together with hidden biomechanical functionality in order to fully characterize foot structure and function. For younger Croatian population the scatter data of the individual foot variables were interpolated by multivariate statistics. Foot structure descriptors are influenced by many factors, as a style of life, race, climate, and things of the great importance in human society. Dominant descriptors are determined by principal component analysis. Some practical recommendation and conclusion for medical, sportswear and footwear practice are highlighted.

Experimental Design for the Evaluation of Detection Techniques of Hidden Corrosion Beneath the Thermal Protective System of the Space Shuttle Orbiter

NASA Technical Reports Server (NTRS)

Kammerer, Catherine C.; Jacoby, Joseph A.; Lomness, Janice K.; Hintze, Paul E.; Russell, Richard W.

2007-01-01

The United States Space Operational Space Shuttle Fleet Consists of three shuttles with an average age of 19.7 years. Shuttles are exposed to corrosive conditions while undergoing final closeout for missions at the launch pad and extreme conditions during ascent, orbit, and descent that may accelerate the corrosion process. Structural corrosion under TPS could progress undetected (without tile removal) and eventually result in reduction in structural capability sufficient to create negative margins of . safety and ultimate loss of local structural capability.

Dimensions of Learning: Community College Students and Their Perceptions of Learning Spaces

ERIC Educational Resources Information Center

Bowers, Hugh Hawes, III

2016-01-01

Classrooms, both by design and by accident, have been used to teach and reinforce certain ethics and ideologies. Examining the actual structures of a classroom one can recognize forces often hidden or considered background revealing how students and instructors together are culturally bound by educational spaces. Considerable research exists that…

Extracting Hidden Trails and Roads Under Canopy Using LIDAR

DTIC Science & Technology

2008-12-01

structure of a tree canopy in the early 1990s. The LIDAR system developed for Mars (Mars Observer Laser Altimeter, or MOLA , 1996-2000) was limited by...bandwidth, and hence was only a discrete return system. The MOLA technology design was subsequently flown as the Shuttle Laser Altimeter on the space

The hidden life of truffles

Treesearch

James M. Trappe; Andrew W. Claridge

2010-01-01

Truffles, like mushrooms, are the fruit of fungi. These fleshy organs are temporary reproductive structures that produce spores, which eventually germinate and give rise to new offspring. What sets truffles apart from mushrooms is that their spore-laden fruit forms below ground rather than above. Technically, true truffles are those fungi that belong to the Ascomycota...

Efficiently Exploring Multilevel Data with Recursive Partitioning

ERIC Educational Resources Information Center

Martin, Daniel P.; von Oertzen, Timo; Rimm-Kaufman, Sara E.

2015-01-01

There is an increasing number of datasets with many participants, variables, or both, in education and other fields that often deal with large, multilevel data structures. Once initial confirmatory hypotheses are exhausted, it can be difficult to determine how best to explore the dataset to discover hidden relationships that could help to inform…

The Curriculum Prerequisite Network: Modeling the Curriculum as a Complex System

ERIC Educational Resources Information Center

Aldrich, Preston R.

2015-01-01

This article advances the prerequisite network as a means to visualize the hidden structure in an academic curriculum. Networks have been used to represent a variety of complex systems ranging from social systems to biochemical pathways and protein interactions. Here, I treat the academic curriculum as a complex system with nodes representing…

Investigating a Case of Hidden Misinterpretations of an Additive Word Problem: Structural Substitution

ERIC Educational Resources Information Center

Polotskaia, Elena; Savard, Annie; Freiman, Viktor

2016-01-01

According to numerous studies (Barrouillet & Camos 2002; Brousseau 1988; Chevallard 1988; Riley et al. 1984; Schubauer-Leoni & Ntamakiliro, "Revue Des Sciences de L'éducation," 20(1): 87-113, 1994; Vergnaud 1982; Xin, "The Journal of Educational Research," 100(6):347-360, 2007), a combination of many factors, including…

Xylose utilization in recombinant Zymomonas

DOEpatents

Kahsay, Robel Y; Qi, Min; Tao, Luan; Viitanen, Paul V; Yang, Jianjun

2013-01-07

Zymomonas expressing xylose isomerase from A. missouriensis was found to have improved xylose utilization, growth, and ethanol production when grown in media containing xylose. Xylose isomerases related to that of A. missouriensis were identified structurally through molecular phylogenetic and Profile Hidden Markov Model analyses, providing xylose isomerases that may be used to improve xylose utilization.

Investigating the Relationship between Dialogue Structure and Tutoring Effectiveness: A Hidden Markov Modeling Approach

ERIC Educational Resources Information Center

Boyer, Kristy Elizabeth; Phillips, Robert; Ingram, Amy; Ha, Eun Young; Wallis, Michael; Vouk, Mladen; Lester, James

2011-01-01

Identifying effective tutorial dialogue strategies is a key issue for intelligent tutoring systems research. Human-human tutoring offers a valuable model for identifying effective tutorial strategies, but extracting them is a challenge because of the richness of human dialogue. This article addresses that challenge through a machine learning…

In the Minds of OSCE Examiners: Uncovering Hidden Assumptions

ERIC Educational Resources Information Center

Chahine, Saad; Holmes, Bruce; Kowalewski, Zbigniew

2016-01-01

The Objective Structured Clinical Exam (OSCE) is a widely used method of assessment in medical education. Rater cognition has become an important area of inquiry in the medical education assessment literature generally, and in the OSCE literature specifically, because of concerns about potential compromises of validity. In this study, a novel…

Emotion and Emotionality as a Hidden Dimension of Lexicon and Discourse

ERIC Educational Resources Information Center

Viberg, Ake

2008-01-01

In her thought-provoking article, Aneta Pavlenko approaches emotion and emotion-laden words in the bilingual lexicon from an impressive number of different perspectives. This is particularly welcome, since most models of linguistic structure do not account for emotional meanings in a systematic way. One exception worth mentioning, however, is…

A Multimedia English Learning System Using HMMs to Improve Phonemic Awareness for English Learning

ERIC Educational Resources Information Center

Lai, Yen-Shou; Tsai, Hung-Hsu; Yu, Pao-Ta

2009-01-01

This paper proposes a multimedia English learning (MEL) system, based on Hidden Markov Models (HMMs) and mastery theory strategy, for teaching students with the aim of enhancing their English phonetic awareness and pronunciation. It can analyze phonetic structures, identify and capture pronunciation errors to provide students with targeted advice…

Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

Hidden cross-correlation patterns in stock markets based on permutation cross-sample entropy and PCA

NASA Astrophysics Data System (ADS)

Lin, Aijing; Shang, Pengjian; Zhong, Bo

2014-12-01

In this article, we investigate the hidden cross-correlation structures in Chinese stock markets and US stock markets by performing PCSE combined with PCA approach. It is suggested that PCSE can provide a more faithful and more interpretable description of the dynamic mechanism between time series than cross-correlation matrix. We show that this new technique can be adapted to observe stock markets especially during financial crisis. In order to identify and compare the interactions and structures of stock markets during financial crisis, as well as in normal periods, all the samples are divided into four sub-periods. The results imply that the cross-correlations between Chinese group are stronger than the US group in the most sub-periods. In particular, it is likely that the US stock markets are more integrated with each other during global financial crisis than during Asian financial crisis. However, our results illustrate that Chinese stock markets are not immune from the global financial crisis, although less integrated with other markets if they are compared with US stock markets.

Short-term prediction of chaotic time series by using RBF network with regression weights.

PubMed

Rojas, I; Gonzalez, J; Cañas, A; Diaz, A F; Rojas, F J; Rodriguez, M

2000-10-01

We propose a framework for constructing and training a radial basis function (RBF) neural network. The structure of the gaussian functions is modified using a pseudo-gaussian function (PG) in which two scaling parameters sigma are introduced, which eliminates the symmetry restriction and provides the neurons in the hidden layer with greater flexibility with respect to function approximation. We propose a modified PG-BF (pseudo-gaussian basis function) network in which the regression weights are used to replace the constant weights in the output layer. For this purpose, a sequential learning algorithm is presented to adapt the structure of the network, in which it is possible to create a new hidden unit and also to detect and remove inactive units. A salient feature of the network systems is that the method used for calculating the overall output is the weighted average of the output associated with each receptive field. The superior performance of the proposed PG-BF system over the standard RBF are illustrated using the problem of short-term prediction of chaotic time series.

"It's Not Always What It Seems": Exploring the Hidden Curriculum within a Doctoral Program

ERIC Educational Resources Information Center

Foot, Rachel Elizabeth

2017-01-01

The purpose of this qualitative, naturalistic study was to explore the ways in which hidden curriculum might influence doctoral student success. Two questions guided the study: (a) How do doctoral students experience the hidden curriculum? (b) What forms of hidden curricula can be identified in a PhD program? Data were collected from twelve…

3D-Printed Ultratough Hydrogel Structures with Titin-like Domains.

PubMed

Zhu, Fengbo; Cheng, Libo; Wang, Zhi Jian; Hong, Wei; Wu, Zi Liang; Yin, Jun; Qian, Jin; Zheng, Qiang

2017-04-05

Titin is composed of repeated modular domains which unfold and dissipate energy upon loading. Here we employed such molecular-level paradigm to fabricate macroscopic ultratough hydrogel structures with titin-like domains, enabled by three-dimensional printing with multiple nozzles. Under stretch, the relatively thin and weak gel fibers in the printed structures break first and the hidden lengths postpone the failure of the main structures, mimicking the toughening principle in titin. These titin-like folded domains have been incorporated into a synthetic spider-web, which shows significantly enhanced extensibility and toughness. This work provides a new avenue of topological design for materials/structures with desired properties.

Net Shape Technology in Aerospace Structures. Volume 1.

DTIC Science & Technology

1986-11-01

ofI nIo n- destructive evaluation methods, such a s ult rasonic inspection, in detecting otherwise hidden defects in parts made of the material. Pratt...SCHEDULE 4. PERFORMING ORGANIZATION REPORT NUMBER( S ) 5. MONITORING ORGANIZATION REPORT NUMBER( S ) n/a n/a 6a. NAME OF PERFORMING ORGANIZATION 6b...a n/a n/a 11 TITLE (Include Security Classification) Net Shape Technology in Aerospace Structures, Vol. I (U) 12. PERSONAL AUTHOR( S ) 13a. TYPE OF

A Viable Paradigm for Quantum Reality

NASA Astrophysics Data System (ADS)

Srivastava, Jagdish

2010-10-01

After a brief discussion of the EPR paradox, Bell's inequality, and Aspect's experiment, arguments will be presented in favor of the following statements: ``As it stands, Quantum mechanics is incomplete. There is further hidden structure, which would involve variables. No influence can move faster than light. The wave function is one whole thing and any change in its structure instantly influences its outcomes. Bell's theorem has not been applied correctly. There is a better paradigm.'' The said paradigm will be presented.

Secrets of the Chinese magic mirror replica

NASA Astrophysics Data System (ADS)

Mak, Se-yuen; Yip, Din-yan

2001-03-01

We examine the structure of five Chinese magic mirror replicas using a special imaging technique developed by the authors. All mirrors are found to have a two-layered structure. The reflecting surface that gives rise to a projected magic pattern on the screen is hidden under a polished half-reflecting top layer. An alternative method of making the magic mirror using ancient technology has been proposed. Finally, we suggest a simple method of reconstructing a mirror replica in the laboratory.

Hidden Markov models-based system (HMMSPECTR) for detecting structural homologies on the basis of sequential information.

PubMed

Tsigelny, Igor; Sharikov, Yuriy; Ten Eyck, Lynn F

2002-05-01

HMMSPECTR is a tool for finding putative structural homologs for proteins with known primary sequences. HMMSPECTR contains four major components: a data warehouse with the hidden Markov models (HMM) and alignment libraries; a search program which compares the initial protein sequences with the libraries of HMMs; a secondary structure prediction and comparison program; and a dominant protein selection program that prepares the set of 10-15 "best" proteins from the chosen HMMs. The data warehouse contains four libraries of HMMs. The first two libraries were constructed using different HHM preparation options of the HAMMER program. The third library contains parts ("partial HMM") of initial alignments. The fourth library contains trained HMMs. We tested our program against all of the protein targets proposed in the CASP4 competition. The data warehouse included libraries of structural alignments and HMMs constructed on the basis of proteins publicly available in the Protein Data Bank before the CASP4 meeting. The newest fully automated versions of HMMSPECTR 1.02 and 1.02ss produced better results than the best result reported at CASP4 either by r.m.s.d. or by length (or both) in 64% (HMMSPECTR 1.02) and 79% (HMMSPECTR 1.02ss) of the cases. The improvement is most notable for the targets with complexity 4 (difficult fold recognition cases).

Zipf exponent of trajectory distribution in the hidden Markov model

NASA Astrophysics Data System (ADS)

Bochkarev, V. V.; Lerner, E. Yu

2014-03-01

This paper is the first step of generalization of the previously obtained full classification of the asymptotic behavior of the probability for Markov chain trajectories for the case of hidden Markov models. The main goal is to study the power (Zipf) and nonpower asymptotics of the frequency list of trajectories of hidden Markov frequencys and to obtain explicit formulae for the exponent of the power asymptotics. We consider several simple classes of hidden Markov models. We prove that the asymptotics for a hidden Markov model and for the corresponding Markov chain can be essentially different.

MD simulation of the Tat/Cyclin T1/CDK9 complex revealing the hidden catalytic cavity within the CDK9 molecule upon Tat binding.

PubMed

Asamitsu, Kaori; Hirokawa, Takatsugu; Okamoto, Takashi

2017-01-01

In this study, we applied molecular dynamics (MD) simulation to analyze the dynamic behavior of the Tat/CycT1/CDK9 tri-molecular complex and revealed the structural changes of P-TEFb upon Tat binding. We found that Tat could deliberately change the local flexibility of CycT1. Although the structural coordinates of the H1 and H2 helices did not substantially change, H1', H2', and H3' exhibited significant changes en masse. Consequently, the CycT1 residues involved in Tat binding, namely Tat-recognition residues (TRRs), lost their flexibility with the addition of Tat to P-TEFb. In addition, we clarified the structural variation of CDK9 in complex with CycT1 in the presence or absence of Tat. Interestingly, Tat addition significantly reduced the structural variability of the T-loop, thus consolidating the structural integrity of P-TEFb. Finally, we deciphered the formation of the hidden catalytic cavity of CDK9 upon Tat binding. MD simulation revealed that the PITALRE signature sequence of CDK9 flips the inactive kinase cavity of CDK9 into the active form by connecting with Thr186, which is crucial for its activity, thus presumably recruiting the substrate peptide such as the C-terminal domain of RNA pol II. These findings provide vital information for the development of effective novel anti-HIV drugs with CDK9 catalytic activity as the target.

Cognitive control over learning: Creating, clustering and generalizing task-set structure

PubMed Central

Collins, Anne G.E.; Frank, Michael J.

2013-01-01

Executive functions and learning share common neural substrates essential for their expression, notably in prefrontal cortex and basal ganglia. Understanding how they interact requires studying how cognitive control facilitates learning, but also how learning provides the (potentially hidden) structure, such as abstract rules or task-sets, needed for cognitive control. We investigate this question from three complementary angles. First, we develop a new computational “C-TS” (context-task-set) model inspired by non-parametric Bayesian methods, specifying how the learner might infer hidden structure and decide whether to re-use that structure in new situations, or to create new structure. Second, we develop a neurobiologically explicit model to assess potential mechanisms of such interactive structured learning in multiple circuits linking frontal cortex and basal ganglia. We systematically explore the link betweens these levels of modeling across multiple task demands. We find that the network provides an approximate implementation of high level C-TS computations, where manipulations of specific neural mechanisms are well captured by variations in distinct C-TS parameters. Third, this synergism across models yields strong predictions about the nature of human optimal and suboptimal choices and response times during learning. In particular, the models suggest that participants spontaneously build task-set structure into a learning problem when not cued to do so, which predicts positive and negative transfer in subsequent generalization tests. We provide evidence for these predictions in two experiments and show that the C-TS model provides a good quantitative fit to human sequences of choices in this task. These findings implicate a strong tendency to interactively engage cognitive control and learning, resulting in structured abstract representations that afford generalization opportunities, and thus potentially long-term rather than short-term optimality. PMID:23356780

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

NASA Astrophysics Data System (ADS)

Zheng, Yipeng; Tan, Wenjiang; Si, Jinhai; Ren, YuHu; Xu, Shichao; Tong, Junyi; Hou, Xun

2016-09-01

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. This imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.

Selection of Hidden Layer Neurons and Best Training Method for FFNN in Application of Long Term Load Forecasting

NASA Astrophysics Data System (ADS)

Singh, Navneet K.; Singh, Asheesh K.; Tripathy, Manoj

2012-05-01

For power industries electricity load forecast plays an important role for real-time control, security, optimal unit commitment, economic scheduling, maintenance, energy management, and plant structure planning etc. A new technique for long term load forecasting (LTLF) using optimized feed forward artificial neural network (FFNN) architecture is presented in this paper, which selects optimal number of neurons in the hidden layer as well as the best training method for the case study. The prediction performance of proposed technique is evaluated using mean absolute percentage error (MAPE) of Thailand private electricity consumption and forecasted data. The results obtained are compared with the results of classical auto-regressive (AR) and moving average (MA) methods. It is, in general, observed that the proposed method is prediction wise more accurate.

Depth-resolved ballistic imaging in a low-depth-of-field optical Kerr gated imaging system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zheng, Yipeng; Tan, Wenjiang, E-mail: tanwenjiang@mail.xjtu.edu.cn; Si, Jinhai

2016-09-07

We demonstrate depth-resolved imaging in a ballistic imaging system, in which a heterodyned femtosecond optical Kerr gate is introduced to extract useful imaging photons for detecting an object hidden in turbid media and a compound lens is proposed to ensure both the depth-resolved imaging capability and the long working distance. Two objects of about 15-μm widths hidden in a polystyrene-sphere suspension have been successfully imaged with approximately 600-μm depth resolution. Modulation-transfer-function curves with the object in and away from the object plane have also been measured to confirm the depth-resolved imaging capability of the low-depth-of-field (low-DOF) ballistic imaging system. Thismore » imaging approach shows potential for application in research of the internal structure of highly scattering fuel spray.« less

Radio for hidden-photon dark matter detection

DOE PAGES

Chaudhuri, Saptarshi; Graham, Peter W.; Irwin, Kent; ...

2015-10-08

We propose a resonant electromagnetic detector to search for hidden-photon dark matter over an extensive range of masses. Hidden-photon dark matter can be described as a weakly coupled “hidden electric field,” oscillating at a frequency fixed by the mass, and able to penetrate any shielding. At low frequencies (compared to the inverse size of the shielding), we find that the observable effect of the hidden photon inside any shielding is a real, oscillating magnetic field. We outline experimental setups designed to search for hidden-photon dark matter, using a tunable, resonant LC circuit designed to couple to this magnetic field. Ourmore » “straw man” setups take into consideration resonator design, readout architecture and noise estimates. At high frequencies, there is an upper limit to the useful size of a single resonator set by 1/ν. However, many resonators may be multiplexed within a hidden-photon coherence length to increase the sensitivity in this regime. Hidden-photon dark matter has an enormous range of possible frequencies, but current experiments search only over a few narrow pieces of that range. As a result, we find the potential sensitivity of our proposal is many orders of magnitude beyond current limits over an extensive range of frequencies, from 100 Hz up to 700 GHz and potentially higher.« less

G-protein-coupled receptor structures were not built in a day.

PubMed

Blois, Tracy M; Bowie, James U

2009-07-01

Among the most exciting recent developments in structural biology is the structure determination of G-protein-coupled receptors (GPCRs), which comprise the largest class of membrane proteins in mammalian cells and have enormous importance for disease and drug development. The GPCR structures are perhaps the most visible examples of a nascent revolution in membrane protein structure determination. Like other major milestones in science, however, such as the sequencing of the human genome, these achievements were built on a hidden foundation of technological developments. Here, we describe some of the methods that are fueling the membrane protein structure revolution and have enabled the determination of the current GPCR structures, along with new techniques that may lead to future structures.

PCSYS: The optimal design integration system picture drawing system with hidden line algorithm capability for aerospace vehicle configurations

NASA Technical Reports Server (NTRS)

Hague, D. S.; Vanderburg, J. D.

1977-01-01

A vehicle geometric definition based upon quadrilateral surface elements to produce realistic pictures of an aerospace vehicle. The PCSYS programs can be used to visually check geometric data input, monitor geometric perturbations, and to visualize the complex spatial inter-relationships between the internal and external vehicle components. PCSYS has two major component programs. The between program, IMAGE, draws a complex aerospace vehicle pictorial representation based on either an approximate but rapid hidden line algorithm or without any hidden line algorithm. The second program, HIDDEN, draws a vehicle representation using an accurate but time consuming hidden line algorithm.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Phases of cannibal dark matter

NASA Astrophysics Data System (ADS)

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; Trevisan, Gabriele

2016-12-01

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector is cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.

Phases of cannibal dark matter

DOE PAGES

Farina, Marco; Pappadopulo, Duccio; Ruderman, Joshua T.; ...

2016-12-13

A hidden sector with a mass gap undergoes an epoch of cannibalism if number changing interactions are active when the temperature drops below the mass of the lightest hidden particle. During cannibalism, the hidden sector temperature decreases only logarithmically with the scale factor. We consider the possibility that dark matter resides in a hidden sector that underwent cannibalism, and has relic density set by the freeze-out of two-to-two annihilations. We identify three novel phases, depending on the behavior of the hidden sector when dark matter freezes out. During the cannibal phase, dark matter annihilations decouple while the hidden sector ismore » cannibalizing. During the chemical phase, only two-to-two interactions are active and the total number of hidden particles is conserved. During the one way phase, the dark matter annihilation products decay out of equilibrium, suppressing the production of dark matter from inverse annihilations. We map out the distinct phenomenology of each phase, which includes a boosted dark matter annihilation rate, new relativistic degrees of freedom, warm dark matter, and observable distortions to the spectrum of the cosmic microwave background.« less

Generalization and capacity of extensively large two-layered perceptrons.

PubMed

Rosen-Zvi, Michal; Engel, Andreas; Kanter, Ido

2002-09-01

The generalization ability and storage capacity of a treelike two-layered neural network with a number of hidden units scaling as the input dimension is examined. The mapping from the input to the hidden layer is via Boolean functions; the mapping from the hidden layer to the output is done by a perceptron. The analysis is within the replica framework where an order parameter characterizing the overlap between two networks in the combined space of Boolean functions and hidden-to-output couplings is introduced. The maximal capacity of such networks is found to scale linearly with the logarithm of the number of Boolean functions per hidden unit. The generalization process exhibits a first-order phase transition from poor to perfect learning for the case of discrete hidden-to-output couplings. The critical number of examples per input dimension, alpha(c), at which the transition occurs, again scales linearly with the logarithm of the number of Boolean functions. In the case of continuous hidden-to-output couplings, the generalization error decreases according to the same power law as for the perceptron, with the prefactor being different.

Ultrasonic guided wave bondline evaluation of thick metallic structures with viscoelastic coatings and the demonstration of a novel mode sweep technique

NASA Astrophysics Data System (ADS)

Bostron, Jason

Ultrasonic guided waves are becoming more widely used in nondestructive evaluation applications due to their efficiency in defect detection, ability to inspect hidden areas, and other reasons. This dissertation addresses two main topics: ultrasonic guided wave bond evaluation of thin and thick coatings on thick metallic structures, and the use of a novel phased array technique for optimal guided wave mode and frequency selection. (Abstract shortened by UMI.).

The Dinosaur in the Classroom: What We Stand to Lose through Ability-Grouping in the Primary School

ERIC Educational Resources Information Center

Marks, Rachel

2014-01-01

Embedding setting (subject-based ability-grouping) into the primary school environment creates structural conflict--physically and culturally--fundamentally changing the nature of primary schools through the imposition of secondary practices and cultures and the loss of pastoral care. This article examines the hidden implications for teachers and…

Transcription-induced DNA supercoiling: New roles of intranucleosomal DNA loops in DNA repair and transcription.

PubMed

Gerasimova, N S; Pestov, N A; Kulaeva, O I; Clark, D J; Studitsky, V M

2016-05-26

RNA polymerase II (Pol II) transcription through chromatin is accompanied by formation of small intranucleosomal DNA loops. Pol II captured within a small loop drives accumulation of DNA supercoiling, facilitating further transcription. DNA breaks relieve supercoiling and induce Pol II arrest, allowing detection of DNA damage hidden in chromatin structure.

The Concept of Profound Boredom: Learning from Moments of Vision

ERIC Educational Resources Information Center

Gibbs, Paul

2011-01-01

This paper recognizes that we become bored in our post-modern, consumerist Western world and that boredom is related to this existence and hidden within it. Through Heidegger, it seeks to provide a way to structure our understanding of boredom and suggest ways of acknowledging its cause, and then to allow it to liberate our authentic appreciation…

Mountain Plains Learning Experience Guide: Electrical Wiring. Course: Electrical Wiring Rough-In.

ERIC Educational Resources Information Center

Arneson, R.; And Others

One of two individualized courses included in an electrical wiring curriculum, this course covers electrical installations that are generally hidden within the structure. The course is comprised of four units: (1) Outlet and Switch Boxes, (2) Wiring, (3) Service Entrance, and (4) Signal and Low Voltage Systems. Each unit begins with a Unit…

The Use of Tetrads in the Analysis of Arts-Based Media

ERIC Educational Resources Information Center

Gouzouasis, Peter; LaMonde, Anne-Marie

2005-01-01

In this article, we chose the musical form of a sonata to examine tetrads, a simple four-fold structure that Marshall McLuhan coined and employed to describe various technologies. Tetrads, as cognitive models, are used to refine, focus, or discover entities in cultures and technologies, which are hidden from view in the psyche. Tetradic logic…

Polychronicity: Review of the Literature and a New Configuration for the Study of This Hidden Dimension of Online Learning

ERIC Educational Resources Information Center

Capdeferro, Neus; Romero, Margarida; Barberà, Elena

2014-01-01

Polychronicity is the natural tendency or preference for structuring time that has an influence on people's behaviors. Highly polychronic individuals are involved in everything, doing many things at once because they value human relationships and interactions over arbitrary schedules and appointments. In contrast, highly monochronic…

Out of Reach, Out of Mind? Infants' Comprehension of References to Hidden Inaccessible Objects.

PubMed

Osina, Maria A; Saylor, Megan M; Ganea, Patricia A

2017-09-01

This study investigated the nature of infants' difficulty understanding references to hidden inaccessible objects. Twelve-month-old infants (N = 32) responded to the mention of objects by looking at, pointing at, or approaching them when the referents were visible or accessible, but not when they were hidden and inaccessible (Experiment I). Twelve-month-olds (N = 16) responded robustly when a container with the hidden referent was moved from a previously inaccessible position to an accessible position before the request, but failed to respond when the reverse occurred (Experiment II). This suggests that infants might be able to track the hidden object's dislocations and update its accessibility as it changes. Knowing the hidden object is currently inaccessible inhibits their responding. Older, 16-month-old (N = 17) infants' performance was not affected by object accessibility. © 2016 The Authors. Child Development © 2016 Society for Research in Child Development, Inc.

Hidden role of Maxwell superalgebras in the free differential algebras of D = 4 and D = 11 supergravity

NASA Astrophysics Data System (ADS)

Ravera, Lucrezia

2018-03-01

The purpose of this paper is to show that the so-called Maxwell superalgebra in four dimensions, which naturally involves the presence of a nilpotent fermionic generator, can be interpreted as a hidden superalgebra underlying N=1, {D}=4 supergravity extended to include a 2-form gauge potential associated to a 2-index antisymmetric tensor. In this scenario, the theory is appropriately discussed in the context of Free Differential Algebras (an extension of the Maurer-Cartan equations to involve higher-degree differential forms). The study is then extended to the Free Differential Algebra describing D = 11 supergravity, showing that, also in this case, there exists a super-Maxwell algebra underlying the theory. The same extra spinors dual to the nilpotent fermionic generators whose presence is crucial for writing a supersymmetric extension of the Maxwell algebras, both in the D = 4 and in the D = 11 case, turn out to be fundamental ingredients also to reproduce the D = 4 and D = 11 Free Differential Algebras on ordinary superspace, whose basis is given by the supervielbein. The analysis of the gauge structure of the supersymmetric Free Differential Algebras is carried on taking into account the gauge transformations from the hidden supergroup-manifold associated with the Maxwell superalgebras.

Accurate step-hold tracking of smoothly varying periodic and aperiodic probability.

PubMed

Ricci, Matthew; Gallistel, Randy

2017-07-01

Subjects observing many samples from a Bernoulli distribution are able to perceive an estimate of the generating parameter. A question of fundamental importance is how the current percept-what we think the probability now is-depends on the sequence of observed samples. Answers to this question are strongly constrained by the manner in which the current percept changes in response to changes in the hidden parameter. Subjects do not update their percept trial-by-trial when the hidden probability undergoes unpredictable and unsignaled step changes; instead, they update it only intermittently in a step-hold pattern. It could be that the step-hold pattern is not essential to the perception of probability and is only an artifact of step changes in the hidden parameter. However, we now report that the step-hold pattern obtains even when the parameter varies slowly and smoothly. It obtains even when the smooth variation is periodic (sinusoidal) and perceived as such. We elaborate on a previously published theory that accounts for: (i) the quantitative properties of the step-hold update pattern; (ii) subjects' quick and accurate reporting of changes; (iii) subjects' second thoughts about previously reported changes; (iv) subjects' detection of higher-order structure in patterns of change. We also call attention to the challenges these results pose for trial-by-trial updating theories.

Orienting to Medicine: Scripting Professionalism, Hierarchy, and Social Difference at the Start of Medical School.

PubMed

Craig, Sienna R; Scott, Rebekah; Blackwood, Kristy

2018-04-23

Nascent medical students' first view into medical school orients them toward what is considered important in medicine. Based on ethnography conducted over 18 months at a New England medical school, this article explores themes which emerged during a first-year student orientation and examines how these scripts resurface across a four-year curriculum, revealing dynamics of enculturation into an institution and the broader profession. We analyze orientation activities as discursive and embodied fields which serve "practical" purposes of making new social geographies familiar, but which also frame institutional values surrounding "soft" aspects of medicine: professionalism; dynamics of hierarchy and vulnerability; and social difference. By examining orientation and connecting these insights to later, discerning educational moments, we argue that orientation reveals tensions between the overt and hidden curricula within medical education, including what being a good doctor means. Our findings are based on data from semi-structured interviews, focus groups, and participant-observation in didactic and clinical settings. This article answers calls within medical anthropology and medical education literature to recognize implicit values at play in producing physicians, unearthing ethnographically how these values are learned longitudinally via persisting gaps between formal and hidden curricula. Assumptions hidden in plain sight call for ongoing medical education reform.

Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

NASA Astrophysics Data System (ADS)

Zhu, Shijia; Wang, Yadong

2015-12-01

Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

The hidden challenges in role transitions and how leadership coaching can help new leaders find solid ground.

PubMed

Weinstock, Beth

2011-01-01

Leadership coaching is becoming an increasingly important intervention that helps individual nurse executives and managers develop and use the best of their strengths, gifts, and talents. As the need for leadership in nursing becomes urgent and brave souls move into the positions of greater authority and potential impact, they will face challenges as they move up in rank. This article identifies the hidden and often-overlooked challenges that are faced by new leaders as they transition into roles of increased responsibility, and it demonstrates how leadership coaching can help new leaders make successful transitions. As the current health care crisis creates opportunity for new leaders, those who opt for promotions and lateral shifts encounter both expected and surprising challenges. The expected challenges include mastering new content skills, learning new organizational structures, and getting to know new teams. The less obvious stressors include issues of self-esteem, assertiveness, self-consciousness, self-criticism, perfectionism, new boundaries, changing identities, and finding one's own leadership style. These important issues are often kept out of conscious awareness and overlooked at great cost to the individual leader and her institution. Leadership coaching can provide support and practical strategies for managing and overcoming these hidden challenges.

Asymmetric author-topic model for knowledge discovering of big data in toxicogenomics.

PubMed

Chung, Ming-Hua; Wang, Yuping; Tang, Hailin; Zou, Wen; Basinger, John; Xu, Xiaowei; Tong, Weida

2015-01-01

The advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on keyword search and/or literature review to navigate the databases and analyses are often done in rather small-scale. As a result, the rich information of a database has not been fully utilized, particularly for the information embedded in the interactive nature between data points that are largely ignored and buried. For the past 10 years, probabilistic topic modeling has been recognized as an effective machine learning algorithm to annotate the hidden thematic structure of massive collection of documents. The analogy between text corpus and large-scale genomic data enables the application of text mining tools, like probabilistic topic models, to explore hidden patterns of genomic data and to the extension of altered biological functions. In this paper, we developed a generalized probabilistic topic model to analyze a toxicogenomics dataset that consists of a large number of gene expression data from the rat livers treated with drugs in multiple dose and time-points. We discovered the hidden patterns in gene expression associated with the effect of doses and time-points of treatment. Finally, we illustrated the ability of our model to identify the evidence of potential reduction of animal use.

Earthquake relocation near the Leech River Fault, southern Vancouver Island

NASA Astrophysics Data System (ADS)

Li, G.; Liu, Y.; Regalla, C.

2015-12-01

The Leech River Fault (LRF), a northeast dipping thrust, extends across the southern tip of Vancouver Island in Southwest British Columbia, where local tectonic regime is dominated by the subduction of the Juan de Fuca plate beneath the North American plate at the present rate of 40-50 mm/year. British Columbia geologic map (Geoscience Map 2009-1A) shows that this area also consists of many crosscutting minor faults in addition to the San Juan Fault north of the LRF. To investigate the seismic evidence of the subsurface structures of these minor faults and of possible hidden active structures in this area, precise earthquake locations are required. In this study, we relocate 941 earthquakes reported by Canadian National Seismograph Network (CNSN) catalog from 2000 to 2015 within a 100km x 55km study area surrounding the LRF. We use HypoDD [Waldhauser, F., 2001] double-difference relocation method by combining P/S phase arrivals provided by the CNSN at 169 stations and waveform data with correlation coefficient values greater than 0.7 at 50 common stations and event separation less than 10km. A total of 900 out of the 931 events satisfy the above relocation criteria. Velocity model used is a 1-D model extracted from the Ramachandran et al. (2005) model. Average relative location errors estimated by the bootstrap method are 546.5m (horizontal) and 1128.6m (in depth). Absolute errors reported by SVD method for individual clusters are ~100m in both dimensions. We select 5 clusters visually according to their epicenters (see figure). Cluster 1 is parallel to the LRF and a thrust FID #60. Clusters 2 and 3 are bounded by two faults: FID #75, a northeast dipping thrust marking the southwestern boundary of the Wrangellia terrane, and FID #2 marking the northern boundary. Clusters 4 and 5, to the northeast and northwest of Victoria respectively, however, do not represent the surface traces of any mapped faults. The depth profile of Cluster 5 depicts a hidden northeast dipping structure, while other clusters illustrate near-vertical structures. Seismicity of Clusters 1 and 3 suggests vertically dipping patterns for FID #60 and FID #2, while Cluster 4 may reveal a hidden vertically dipping structure. It is noteworthy that most events in this area are deeper than 20km, but the explanation for such deep earthquakes is still unclear.

Double-stranded DNA breaks hidden in the neutral Comet assay suggest a role of the sperm nuclear matrix in DNA integrity maintenance

PubMed Central

Ribas-Maynou, J.; Gawecka, J.E.; Benet, J.; Ward, W.S.

2014-01-01

We used a mouse model in which sperm DNA damage was induced to understand the relationship of double-stranded DNA (dsDNA) breaks to sperm chromatin structure and to the Comet assay. Sperm chromatin fragmentation (SCF) produces dsDNA breaks located on the matrix attachment regions, between protamine toroids. In this model, epididymal sperm induced to undergo SCF can religate dsDNA breaks while vas deferens sperm cannot. Here, we demonstrated that the conventional neutral Comet assay underestimates the epididymal SCF breaks because the broken DNA ends remain attached to the nuclear matrix, causing the DNA to remain associated with the dispersion halo, and the Comet tails to be weak. Therefore, we term these hidden dsDNA breaks. When the Comet assay was modified to include an additional incubation with sodium dodecyl sulfate (SDS) and dithiothreitol (DTT) after the conventional lysis, thereby solubilizing the nuclear matrix, the broken DNA was released from the matrix, which resulted in a reduction of the sperm head halo and an increase in the Comet tail length, exposing the hidden dsDNA breaks. Conversely, SCF-induced vas deferens sperm had small halos and long tails with the conventional neutral Comet assay, suggesting that the broken DNA ends were not tethered to the nuclear matrix. These results suggest that the attachment to the nuclear matrix is crucial for the religation of SCF-induced DNA breaks in sperm. Our data suggest that the neutral Comet assay identifies only dsDNA breaks that are released from the nuclear matrix and that the addition of an SDS treatment can reveal these hidden dsDNA breaks. PMID:24282283

Double-stranded DNA breaks hidden in the neutral Comet assay suggest a role of the sperm nuclear matrix in DNA integrity maintenance.

PubMed

Ribas-Maynou, J; Gawecka, J E; Benet, J; Ward, W S

2014-04-01

We used a mouse model in which sperm DNA damage was induced to understand the relationship of double-stranded DNA (dsDNA) breaks to sperm chromatin structure and to the Comet assay. Sperm chromatin fragmentation (SCF) produces dsDNA breaks located on the matrix attachment regions, between protamine toroids. In this model, epididymal sperm induced to undergo SCF can religate dsDNA breaks while vas deferens sperm cannot. Here, we demonstrated that the conventional neutral Comet assay underestimates the epididymal SCF breaks because the broken DNA ends remain attached to the nuclear matrix, causing the DNA to remain associated with the dispersion halo, and the Comet tails to be weak. Therefore, we term these hidden dsDNA breaks. When the Comet assay was modified to include an additional incubation with sodium dodecyl sulfate (SDS) and dithiothreitol (DTT) after the conventional lysis, thereby solubilizing the nuclear matrix, the broken DNA was released from the matrix, which resulted in a reduction of the sperm head halo and an increase in the Comet tail length, exposing the hidden dsDNA breaks. Conversely, SCF-induced vas deferens sperm had small halos and long tails with the conventional neutral Comet assay, suggesting that the broken DNA ends were not tethered to the nuclear matrix. These results suggest that the attachment to the nuclear matrix is crucial for the religation of SCF-induced DNA breaks in sperm. Our data suggest that the neutral Comet assay identifies only dsDNA breaks that are released from the nuclear matrix and that the addition of an SDS treatment can reveal these hidden dsDNA breaks.

Identification of hidden relationships from the coupling of hydrophobic cluster analysis and domain architecture information.

PubMed

Faure, Guilhem; Callebaut, Isabelle

2013-07-15

Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze. We present here an original novel approach, called TREMOLO-HCA, for the analysis of orphan domain sequences and inspired from our experience in the use of Hydrophobic Cluster Analysis (HCA). Hidden relationships between protein sequences can be more easily identified from the PSI-BLAST results, using information on domain architecture, HCA plots and the conservation degree of amino acids that may participate in the protein core. This can lead to reveal remote relationships with known families of domains, as illustrated here with the identification of a hidden Tudor tandem in the human BAHCC1 protein and a hidden ET domain in the Saccharomyces cerevisiae Taf14p and human AF9 proteins. The results obtained in such a way are consistent with those provided by HHPRED, based on pairwise comparisons of HHMs. Our approach can, however, be applied even in absence of domain profiles or known 3D structures for the identification of novel families of domains. It can also be used in a reverse way for refining domain profiles, by starting from known protein domain families and identifying highly divergent members, hitherto considered as orphan. We provide a possible integration of this approach in an open TREMOLO-HCA package, which is fully implemented in python v2.7 and is available on request. Instructions are available at http://www.impmc.upmc.fr/∼callebau/tremolohca.html. isabelle.callebaut@impmc.upmc.fr Supplementary Data are available at Bioinformatics online.

The hidden costs of coastal hazards: Implications for risk assessment and mitigation

USGS Publications Warehouse

Kunreuther, H.; Platt, R.; Baruch, S.; Bernknopf, R.L.; Buckley, M.; Burkett, V.; Conrad, D.; Davidson, T.; Deutsch, K.; Geis, D.; Jannereth, M.; Knap, A.; Lane, H.; Ljung, G.; McCauley, M.; Mileti, D.; Miller, T.; Morrow, B.; Meyers, J.; Pielke, R.; Pratt, A.; Tripp, J.

2000-01-01

Society has limited hazard mitigation dollars to invest. Which actions will be most cost effective, considering the true range of impacts and costs incurred? In 1997, the H. John Heinz III Center for Science, Economics and the Environment began a two-year study with a panel of experts to help develop new strategies to identify and reduce the costs of weather-related hazards associated with rapidly increasing coastal development activities.The Hidden Costs of Coastal Hazards presents the panel's findings, offering the first in-depth study that considers the costs of coastal hazards to natural resources, social institutions, business, and the built environment. Using Hurricane Hugo, which struck South Carolina in 1989, as a case study, it provides for the first time information on the full range of economic costs caused by a major coastal hazard event. The book:describes and examines unreported, undocumented, and hidden costs such as losses due to business interruption, reduction in property values, interruption of social services, psychological trauma, damage to natural systems, and othersexamines the concepts of risk and vulnerability, and discusses conventional approaches to risk assessment and the emerging area of vulnerability assessmentrecommends a comprehensive framework for developing and implementing mitigation strategiesdocuments the human impact of Hurricane Hugo and provides insight from those who lived through it.The Hidden Costs of Coastal Hazards takes a structured approach to the problem of coastal hazards, offering a new framework for community-based hazard mitigation along with specific recommendations for implementation. Decisionmakers -- both policymakers and planners -- who are interested in coastal hazard issues will find the book a unique source of new information and insight, as will private-sector decisionmakers including lenders, investors, developers, and insurers of coastal property.

Learning and inference in a nonequilibrium Ising model with hidden nodes.

PubMed

Dunn, Benjamin; Roudi, Yasser

2013-02-01

We study inference and reconstruction of couplings in a partially observed kinetic Ising model. With hidden spins, calculating the likelihood of a sequence of observed spin configurations requires performing a trace over the configurations of the hidden ones. This, as we show, can be represented as a path integral. Using this representation, we demonstrate that systematic approximate inference and learning rules can be derived using dynamical mean-field theory. Although naive mean-field theory leads to an unstable learning rule, taking into account Gaussian corrections allows learning the couplings involving hidden nodes. It also improves learning of the couplings between the observed nodes compared to when hidden nodes are ignored.

A modulation wave approach to the order hidden in disorder

PubMed Central

Withers, Ray

2015-01-01

The usefulness of a modulation wave approach to understanding and interpreting the highly structured continuous diffuse intensity distributions characteristic of the reciprocal spaces of the very large family of inherently flexible materials which exhibit ordered ‘disorder’ is pointed out. It is shown that both longer range order and truly short-range order are simultaneously encoded in highly structured diffuse intensity distributions. The long-range ordered crystal chemical rules giving rise to such diffuse distributions are highlighted, along with the existence and usefulness of systematic extinction conditions in these types of structured diffuse distributions. PMID:25610629

Hidden multidimensional social structure modeling applied to biased social perception

NASA Astrophysics Data System (ADS)

Maletić, Slobodan; Zhao, Yi

2018-02-01

Intricacies of the structure of social relations are realized by representing a collection of overlapping opinions as a simplicial complex, thus building latent multidimensional structures, through which agents are, virtually, moving as they exchange opinions. The influence of opinion space structure on the distribution of opinions is demonstrated by modeling consensus phenomena when the opinion exchange between individuals may be affected by the false consensus effect. The results indicate that in the cases with and without bias, the road toward consensus is influenced by the structure of multidimensional space of opinions, and in the biased case, complete consensus is achieved. The applications of proposed modeling framework can easily be generalized, as they transcend opinion formation modeling.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study

PubMed Central

Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-01-01

Background Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Objective Our Medical Research Council–funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Methods Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. Results This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. Conclusions This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. PMID:29523503

Life imitating art: depictions of the hidden curriculum in medical television programs.

PubMed

Stanek, Agatha; Clarkin, Chantalle; Bould, M Dylan; Writer, Hilary; Doja, Asif

2015-09-26

The hidden curriculum represents influences occurring within the culture of medicine that indirectly alter medical professionals' interactions, beliefs and clinical practices throughout their training. One approach to increase medical student awareness of the hidden curriculum is to provide them with readily available examples of how it is enacted in medicine; as such the purpose of this study was to examine depictions of the hidden curriculum in popular medical television programs. One full season of ER, Grey's Anatomy and Scrubs were selected for review. A summative content analysis was performed to ascertain the presence of depictions of the hidden curriculum, as well as to record the type, frequency and quality of examples. A second reviewer also viewed a random selection of episodes from each series to establish coding reliability. The most prevalent themes across all television programs were: the hierarchical nature of medicine; challenges during transitional stages in medicine; the importance of role modeling; patient dehumanization; faking or overstating one's capabilities; unprofessionalism; the loss of idealism; and difficulties with work-life balance. The hidden curriculum is frequently depicted in popular medical television shows. These examples of the hidden curriculum could serve as a valuable teaching resource in undergraduate medical programs.

Uncovering hidden nodes in complex networks in the presence of noise

PubMed Central

Su, Ri-Qi; Lai, Ying-Cheng; Wang, Xiao; Do, Younghae

2014-01-01

Ascertaining the existence of hidden objects in a complex system, objects that cannot be observed from the external world, not only is curiosity-driven but also has significant practical applications. Generally, uncovering a hidden node in a complex network requires successful identification of its neighboring nodes, but a challenge is to differentiate its effects from those of noise. We develop a completely data-driven, compressive-sensing based method to address this issue by utilizing complex weighted networks with continuous-time oscillatory or discrete-time evolutionary-game dynamics. For any node, compressive sensing enables accurate reconstruction of the dynamical equations and coupling functions, provided that time series from this node and all its neighbors are available. For a neighboring node of the hidden node, this condition cannot be met, resulting in abnormally large prediction errors that, counterintuitively, can be used to infer the existence of the hidden node. Based on the principle of differential signal, we demonstrate that, when strong noise is present, insofar as at least two neighboring nodes of the hidden node are subject to weak background noise only, unequivocal identification of the hidden node can be achieved. PMID:24487720

Quons, an interpolation between Bose and Fermi oscillators

NASA Technical Reports Server (NTRS)

Greenberg, O. W.

1993-01-01

After a brief mention of Bose and Fermi oscillators and of particles which obey other types of statistics, including intermediate statistics, parastatistics, paronic statistics, anyon statistics, and infinite statistics, I discuss the statistics of 'quons' (pronounced to rhyme with muons), particles whose annihilation and creation operators obey the q-deformed commutation relation (the quon algebra or q-mutator) which interpolates between fermions and bosons. I emphasize that the operator for interaction with an external source must be an effective Bose operator in all cases. To accomplish this for parabose, parafermi and quon operators, I introduce parabose, parafermi, and quon Grassmann numbers, respectively. I also discuss interactions of non-relativistic quons, quantization of quon fields with antiparticles, calculation of vacuum matrix elements of relativistic quon fields, demonstration of the TCP theorem, cluster decomposition, and Wick's theorem for relativistic quon fields, and the failure of local commutativity of observables for relativistic quon fields. I conclude with the bound on the parameter q for electrons due to the Ramberg-Snow experiment.

Fermionic topological quantum states as tensor networks

NASA Astrophysics Data System (ADS)

Wille, C.; Buerschaper, O.; Eisert, J.

2017-06-01

Tensor network states, and in particular projected entangled pair states, play an important role in the description of strongly correlated quantum lattice systems. They do not only serve as variational states in numerical simulation methods, but also provide a framework for classifying phases of quantum matter and capture notions of topological order in a stringent and rigorous language. The rapid development in this field for spin models and bosonic systems has not yet been mirrored by an analogous development for fermionic models. In this work, we introduce a tensor network formalism capable of capturing notions of topological order for quantum systems with fermionic components. At the heart of the formalism are axioms of fermionic matrix-product operator injectivity, stable under concatenation. Building upon that, we formulate a Grassmann number tensor network ansatz for the ground state of fermionic twisted quantum double models. A specific focus is put on the paradigmatic example of the fermionic toric code. This work shows that the program of describing topologically ordered systems using tensor networks carries over to fermionic models.

An Introduction to Geometric Algebra with some Preliminary Thoughts on the Geometric Meaning of Quantum Mechanics

NASA Astrophysics Data System (ADS)

Horn, Martin Erik

2014-10-01

It is still a great riddle to me why Wolfgang Pauli and P.A.M. Dirac had not fully grasped the meaning of their own mathematical constructions. They invented magnificent, fantastic and very important mathematical features of modern physics, but they only delivered half of the interpretations of their own inventions. Of course, Pauli matrices and Dirac matrices represent operators, which Pauli and Dirac discussed in length. But this is only part of the true meaning behind them, as the non-commutative ideas of Grassmann, Clifford, Hamilton and Cartan allow a second, very far reaching interpretation of Pauli and Dirac matrices. An introduction to this alternative interpretation will be discussed. Some applications of this view on Pauli and Dirac matrices are given, e.g. a geometric algebra picture of the plane wave solution of the Maxwell equation, a geometric algebra picture of special relativity, a toy model of SU(3) symmetry, and some only very preliminary thoughts about a possible geometric meaning of quantum mechanics.

A Unified Model of Phantom Energy and Dark Matter

NASA Astrophysics Data System (ADS)

Chaves, Max; Singleton, Douglas

2008-01-01

To explain the acceleration of the cosmological expansion researchers have considered an unusual form of mass-energy generically called dark energy. Dark energy has a ratio of pressure over mass density which obeys w = p/ρ < -1/3. This form of mass-energy leads to accelerated expansion. An extreme form of dark energy, called phantom energy, has been proposed which has w = p/ρ < -1. This possibility is favored by the observational data. The simplest model for phantom energy involves the introduction of a scalar field with a negative kinetic energy term. Here we show that theories based on graded Lie algebras naturally have such a negative kinetic energy and thus give a model for phantom energy in a less ad hoc manner. We find that the model also contains ordinary scalar fields and anti-commuting (Grassmann) vector fields which act as a form of two component dark matter. Thus from a gauge theory based o! n a graded algebra we naturally obtained both phantom energy and dark matter.

Birefringence and hidden photons

NASA Astrophysics Data System (ADS)

Arza, Ariel; Gamboa, J.

2018-05-01

We study a model where photons interact with hidden photons and millicharged particles through a kinetic mixing term. Particularly, we focus on vacuum birefringence effects and we find a bound for the millicharged parameter assuming that hidden photons are a piece of the local dark matter density.

Nondestructive surface profiling of hidden MEMS using an infrared low-coherence interferometric microscope

NASA Astrophysics Data System (ADS)

Krauter, Johann; Osten, Wolfgang

2018-03-01

There are a wide range of applications for micro-electro-mechanical systems (MEMS). The automotive and consumer market is the strongest driver for the growing MEMS industry. A 100 % test of MEMS is particularly necessary since these are often used for safety-related purposes such as the ESP (Electronic Stability Program) system. The production of MEMS is a fully automated process that generates 90 % of the costs during the packaging and dicing steps. Nowadays, an electrical test is carried out on each individual MEMS component before these steps. However, after encapsulation, MEMS are opaque to visible light and other defects cannot be detected. Therefore, we apply an infrared low-coherence interferometer for the topography measurement of those hidden structures. A lock-in algorithm-based method is shown to calculate the object height and to reduce ghost steps due to the 2π -unambiguity. Finally, measurements of different MEMS-based sensors are presented.

Origami structures with a critical transition to bistability arising from hidden degrees of freedom

NASA Astrophysics Data System (ADS)

Silverberg, Jesse L.; Na, Jun-Hee; Evans, Arthur A.; Liu, Bin; Hull, Thomas C.; Santangelo, Christian D.; Lang, Robert J.; Hayward, Ryan C.; Cohen, Itai

2015-04-01

Origami is used beyond purely aesthetic pursuits to design responsive and customizable mechanical metamaterials. However, a generalized physical understanding of origami remains elusive, owing to the challenge of determining whether local kinematic constraints are globally compatible and to an incomplete understanding of how the folded sheet’s material properties contribute to the overall mechanical response. Here, we show that the traditional square twist, whose crease pattern has zero degrees of freedom (DOF) and therefore should not be foldable, can nevertheless be folded by accessing bending deformations that are not explicit in the crease pattern. These hidden bending DOF are separated from the crease DOF by an energy gap that gives rise to a geometrically driven critical bifurcation between mono- and bistability. Noting its potential utility for fabricating mechanical switches, we use a temperature-responsive polymer-gel version of the square twist to demonstrate hysteretic folding dynamics at the sub-millimetre scale.

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment.

PubMed

Bidargaddi, Niranjan P; Chetty, Madhu; Kamruzzaman, Joarder

2008-06-01

Profile hidden Markov models (HMMs) based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.

Multi-category micro-milling tool wear monitoring with continuous hidden Markov models

NASA Astrophysics Data System (ADS)

Zhu, Kunpeng; Wong, Yoke San; Hong, Geok Soon

2009-02-01

In-process monitoring of tool conditions is important in micro-machining due to the high precision requirement and high tool wear rate. Tool condition monitoring in micro-machining poses new challenges compared to conventional machining. In this paper, a multi-category classification approach is proposed for tool flank wear state identification in micro-milling. Continuous Hidden Markov models (HMMs) are adapted for modeling of the tool wear process in micro-milling, and estimation of the tool wear state given the cutting force features. For a noise-robust approach, the HMM outputs are connected via a medium filter to minimize the tool state before entry into the next state due to high noise level. A detailed study on the selection of HMM structures for tool condition monitoring (TCM) is presented. Case studies on the tool state estimation in the micro-milling of pure copper and steel demonstrate the effectiveness and potential of these methods.

[Application of an artificial neural network in the design of sustained-release dosage forms].

PubMed

Wei, X H; Wu, J J; Liang, W Q

2001-09-01

To use the artificial neural network (ANN) in Matlab 5.1 tool-boxes to predict the formulations of sustained-release tablets. The solubilities of nine drugs and various ratios of HPMC: Dextrin for 63 tablet formulations were used as the ANN model input, and in vitro accumulation released at 6 sampling times were used as output. The ANN model was constructed by selecting the optimal number of iterations (25) and model structure in which there are one hidden layer and five hidden layer nodes. The optimized ANN model was used for prediction of formulation based on desired target in vitro dissolution-time profiles. ANN predicted profiles based on ANN predicted formulations were closely similar to the target profiles. The ANN could be used for predicting the dissolution profiles of sustained release dosage form and for the design of optimal formulation.

Distinct magnetic spectra in the hidden order and antiferromagnetic phases in URu 2 - x Fe x Si 2

DOE PAGES

Butch, Nicholas P.; Ran, Sheng; Jeon, Inho; ...

2016-11-07

We use neutron scattering to compare the magnetic excitations in the hidden order (HO) and antiferromagnetic (AFM) phases in URu 2-xFe xSi 2 as a function of Fe concentration. The magnetic excitation spectra change significantly between x = 0.05 and x = 0.10, following the enhancement of the AFM ordered moment, in good analogy to the behavior of the parent compound under applied pressure. Prominent lattice-commensurate low-energy excitations characteristic of the HO phase vanish in the AFM phase. The magnetic scattering is dominated by strong excitations along the Brillouin zone edges, underscoring the important role of electron hybridization to bothmore » HO and AFM phases, and the similarity of the underlying electronic structure. The stability of the AFM phase is correlated with enhanced local-itinerant electron hybridization.« less

Monitoring Farmland Loss Caused by Urbanization in Beijing from Modis Time Series Using Hierarchical Hidden Markov Model

NASA Astrophysics Data System (ADS)

Yuan, Y.; Meng, Y.; Chen, Y. X.; Jiang, C.; Yue, A. Z.

2018-04-01

In this study, we proposed a method to map urban encroachment onto farmland using satellite image time series (SITS) based on the hierarchical hidden Markov model (HHMM). In this method, the farmland change process is decomposed into three hierarchical levels, i.e., the land cover level, the vegetation phenology level, and the SITS level. Then a three-level HHMM is constructed to model the multi-level semantic structure of farmland change process. Once the HHMM is established, a change from farmland to built-up could be detected by inferring the underlying state sequence that is most likely to generate the input time series. The performance of the method is evaluated on MODIS time series in Beijing. Results on both simulated and real datasets demonstrate that our method improves the change detection accuracy compared with the HMM-based method.

Implications of the measured angular anisotropy at the hidden order transition of URu2Si2

NASA Astrophysics Data System (ADS)

Chandra, P.; Coleman, P.; Flint, R.; Trinh, J.; Ramirez, A. P.

2018-05-01

The heavy fermion compound URu2Si2 continues to attract great interest due to the long-unidentified nature of the hidden order that develops below 17.5 K. Here we discuss the implications of an angular survey of the linear and nonlinear susceptibility of URu2Si2 in the vicinity of the hidden order transition [1]. While the anisotropic nature of spin fluctuations and low-temperature quasiparticles was previously established, our recent results suggest that the order parameter itself has intrinsic Ising anisotropy, and that moreover this anisotropy extends far above the hidden order transition. Consistency checks and subsequent questions for future experimental and theoretical studies of hidden order are discussed.

A Self-Organizing Incremental Spatiotemporal Associative Memory Networks Model for Problems with Hidden State

PubMed Central

2016-01-01

Identifying the hidden state is important for solving problems with hidden state. We prove any deterministic partially observable Markov decision processes (POMDP) can be represented by a minimal, looping hidden state transition model and propose a heuristic state transition model constructing algorithm. A new spatiotemporal associative memory network (STAMN) is proposed to realize the minimal, looping hidden state transition model. STAMN utilizes the neuroactivity decay to realize the short-term memory, connection weights between different nodes to represent long-term memory, presynaptic potentials, and synchronized activation mechanism to complete identifying and recalling simultaneously. Finally, we give the empirical illustrations of the STAMN and compare the performance of the STAMN model with that of other methods. PMID:27891146

Image segmentation using hidden Markov Gauss mixture models.

PubMed

Pyun, Kyungsuk; Lim, Johan; Won, Chee Sun; Gray, Robert M

2007-07-01

Image segmentation is an important tool in image processing and can serve as an efficient front end to sophisticated algorithms and thereby simplify subsequent processing. We develop a multiclass image segmentation method using hidden Markov Gauss mixture models (HMGMMs) and provide examples of segmentation of aerial images and textures. HMGMMs incorporate supervised learning, fitting the observation probability distribution given each class by a Gauss mixture estimated using vector quantization with a minimum discrimination information (MDI) distortion. We formulate the image segmentation problem using a maximum a posteriori criteria and find the hidden states that maximize the posterior density given the observation. We estimate both the hidden Markov parameter and hidden states using a stochastic expectation-maximization algorithm. Our results demonstrate that HMGMM provides better classification in terms of Bayes risk and spatial homogeneity of the classified objects than do several popular methods, including classification and regression trees, learning vector quantization, causal hidden Markov models (HMMs), and multiresolution HMMs. The computational load of HMGMM is similar to that of the causal HMM.

Higher Stakes--The Hidden Risks of School Security Fences for Children's Learning Environments

ERIC Educational Resources Information Center

Rooney, Tonya

2015-01-01

In a move away from the open or low-fenced grounds that have traditionally been a feature of Australian school design, the last decade has seen a growth in the installation of high-security fences around schools. These structures, far from being passive and neutral, act to redefine the possibilities for movement and connectivity in the local…

Transcription-induced DNA supercoiling: New roles of intranucleosomal DNA loops in DNA repair and transcription

PubMed Central

Gerasimova, N. S.; Pestov, N. A.; Kulaeva, O. I.; Clark, D. J.; Studitsky, V. M.

2016-01-01

ABSTRACT RNA polymerase II (Pol II) transcription through chromatin is accompanied by formation of small intranucleosomal DNA loops. Pol II captured within a small loop drives accumulation of DNA supercoiling, facilitating further transcription. DNA breaks relieve supercoiling and induce Pol II arrest, allowing detection of DNA damage hidden in chromatin structure. PMID:27115204

Exploring the Hidden Structure of Astronomical Images: A "Pixelated" View of Solar System and Deep Space Features!

ERIC Educational Resources Information Center

Ward, R. Bruce; Sienkiewicz, Frank; Sadler, Philip; Antonucci, Paul; Miller, Jaimie

2013-01-01

We describe activities created to help student participants in Project ITEAMS (Innovative Technology-Enabled Astronomy for Middle Schools) develop a deeper understanding of picture elements (pixels), image creation, and analysis of the recorded data. ITEAMS is an out-of-school time (OST) program funded by the National Science Foundation (NSF) with…

Decay detection in red oak trees using a combination of visual inspection, acoustic testing, and resistance microdrilling

Treesearch

Xiping Wang; R. Bruce Allison

2008-01-01

Arborists are often challenged to identify internal structural defects hidden from view within tree trunks. This article reports the results of a study using a trunk inspection protocol combining visual observation, single-path stress wave testing, acoustic tomography, and resistance microdrilling to detect internal defects. Two century-old red oak (Quercus rubra)...

The Hidden Lives of Galaxies: An Information & Activity Booklet, Grades 9-12, 2000-2001. Imagine the Universe! Probing the Structure & Evolution of the Cosmos.

ERIC Educational Resources Information Center

Lochner, James C.; Williamson, Lisa; Fitzhugh, Ethel

This National Aeronautics and Space Administration (NASA) document presents activities on the properties of galaxies for additional curriculum support. The activities presented in this document include: (1) "How Big Is the Universe"; (2) "Identifying Galaxies"; (3) "Classifying Galaxies Using Hubble's Fork Diagram"; (4) "Identifying Unusual…

Dynamic Latent Trait Models with Mixed Hidden Markov Structure for Mixed Longitudinal Outcomes.

PubMed

Zhang, Yue; Berhane, Kiros

2016-01-01

We propose a general Bayesian joint modeling approach to model mixed longitudinal outcomes from the exponential family for taking into account any differential misclassification that may exist among categorical outcomes. Under this framework, outcomes observed without measurement error are related to latent trait variables through generalized linear mixed effect models. The misclassified outcomes are related to the latent class variables, which represent unobserved real states, using mixed hidden Markov models (MHMM). In addition to enabling the estimation of parameters in prevalence, transition and misclassification probabilities, MHMMs capture cluster level heterogeneity. A transition modeling structure allows the latent trait and latent class variables to depend on observed predictors at the same time period and also on latent trait and latent class variables at previous time periods for each individual. Simulation studies are conducted to make comparisons with traditional models in order to illustrate the gains from the proposed approach. The new approach is applied to data from the Southern California Children Health Study (CHS) to jointly model questionnaire based asthma state and multiple lung function measurements in order to gain better insight about the underlying biological mechanism that governs the inter-relationship between asthma state and lung function development.

Application of hidden Markov models to biological data mining: a case study

NASA Astrophysics Data System (ADS)

Yin, Michael M.; Wang, Jason T.

2000-04-01

In this paper we present an example of biological data mining: the detection of splicing junction acceptors in eukaryotic genes. Identification or prediction of transcribed sequences from within genomic DNA has been a major rate-limiting step in the pursuit of genes. Programs currently available are far from being powerful enough to elucidate the gene structure completely. Here we develop a hidden Markov model (HMM) to represent the degeneracy features of splicing junction acceptor sites in eukaryotic genes. The HMM system is fully trained using an expectation maximization (EM) algorithm and the system performance is evaluated using the 10-way cross- validation method. Experimental results show that our HMM system can correctly classify more than 94% of the candidate sequences (including true and false acceptor sites) into right categories. About 90% of the true acceptor sites and 96% of the false acceptor sites in the test data are classified correctly. These results are very promising considering that only the local information in DNA is used. The proposed model will be a very important component of an effective and accurate gene structure detection system currently being developed in our lab.

Hidden phase in parent Fe-pnictide superconductors

NASA Astrophysics Data System (ADS)

Ali, Khadiza; Adhikary, Ganesh; Thakur, Sangeeta; Patil, Swapnil; Mahatha, Sanjoy K.; Thamizhavel, A.; De Ninno, Giovanni; Moras, Paolo; Sheverdyaeva, Polina M.; Carbone, Carlo; Petaccia, Luca; Maiti, Kalobaran

2018-02-01

We investigate the origin of exoticity in Fe-based systems via studying the fermiology of CaFe2As2 employing angle-resolved photoemission spectroscopy. While the Fermi surfaces (FSs) at 200 K and 31 K are observed to exhibit two-dimensional and three-dimensional (3D) topology, respectively, the FSs at intermediate temperatures reveal the emergence of the 3D topology at a temperature much lower than the structural and magnetic phase transition temperature (170 K, for the sample under scrutiny). This leads to the conclusion that the evolution of FS topology is not directly driven by the structural transition. In addition, we discover the existence in ambient conditions of energy bands related to the cT phase. These bands are distinctly resolved in the high-photon energy spectra exhibiting strong Fe 3 d character. They gradually move to higher binding energies due to thermal compression with cooling, leading to the emergence of 3D topology in the Fermi surface. These results reveal the so-far hidden existence of a cT phase under ambient conditions, which is argued to lead to quantum fluctuations responsible for the exotic electronic properties in Fe-pnictide superconductors.

Detecting network communities beyond assortativity-related attributes

NASA Astrophysics Data System (ADS)

Liu, Xin; Murata, Tsuyoshi; Wakita, Ken

2014-07-01

In network science, assortativity refers to the tendency of links to exist between nodes with similar attributes. In social networks, for example, links tend to exist between individuals of similar age, nationality, location, race, income, educational level, religious belief, and language. Thus, various attributes jointly affect the network topology. An interesting problem is to detect community structure beyond some specific assortativity-related attributes ρ, i.e., to take out the effect of ρ on network topology and reveal the hidden community structures which are due to other attributes. An approach to this problem is to redefine the null model of the modularity measure, so as to simulate the effect of ρ on network topology. However, a challenge is that we do not know to what extent the network topology is affected by ρ and by other attributes. In this paper, we propose a distance modularity, which allows us to freely choose any suitable function to simulate the effect of ρ. Such freedom can help us probe the effect of ρ and detect the hidden communities which are due to other attributes. We test the effectiveness of distance modularity on synthetic benchmarks and two real-world networks.

Topological properties of flat electroencephalography's state space

NASA Astrophysics Data System (ADS)

Ken, Tan Lit; Ahmad, Tahir bin; Mohd, Mohd Sham bin; Ngien, Su Kong; Suwa, Tohru; Meng, Ong Sie

2016-02-01

Neuroinverse problem are often associated with complex neuronal activity. It involves locating problematic cell which is highly challenging. While epileptic foci localization is possible with the aid of EEG signals, it relies greatly on the ability to extract hidden information or pattern within EEG signals. Flat EEG being an enhancement of EEG is a way of viewing electroencephalograph on the real plane. In the perspective of dynamical systems, Flat EEG is equivalent to epileptic seizure hence, making it a great platform to study epileptic seizure. Throughout the years, various mathematical tools have been applied on Flat EEG to extract hidden information that is hardly noticeable by traditional visual inspection. While these tools have given worthy results, the journey towards understanding seizure process completely is yet to be succeeded. Since the underlying structure of Flat EEG is dynamic and is deemed to contain wealthy information regarding brainstorm, it would certainly be appealing to explore in depth its structures. To better understand the complex seizure process, this paper studies the event of epileptic seizure via Flat EEG in a more general framework by means of topology, particularly, on the state space where the event of Flat EEG lies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Costigliola, Lorenzo; Schrøder, Thomas B.; Dyre, Jeppe C.

The recent theoretical prediction by Maimbourg and Kurchan [e-print http://arxiv.org/abs/1603.05023 (2016)] that for regular pair-potential systems the virial potential-energy correlation coefficient increases towards unity as the dimension d goes to infinity is investigated for the standard 12-6 Lennard-Jones fluid. This is done by computer simulations for d = 2, 3, 4 going from the critical point along the critical isotherm/isochore to higher density/temperature. In both cases the virial potential-energy correlation coefficient increases significantly. For a given density and temperature relative to the critical point, with increasing number of dimension the Lennard-Jones system conforms better to the hidden-scale-invariance property characterized bymore » high virial potential-energy correlations (a property that leads to the existence of isomorphs in the thermodynamic phase diagram, implying that it becomes effectively one-dimensional in regard to structure and dynamics). The present paper also gives the first numerical demonstration of isomorph invariance of structure and dynamics in four dimensions. Our findings emphasize the need for a universally applicable 1/d expansion in liquid-state theory; we conjecture that the systems known to obey hidden scale invariance in three dimensions are those for which the yet-to-be-developed 1/d expansion converges rapidly.« less

Bell's theorem and the problem of decidability between the views of Einstein and Bohr.

PubMed

Hess, K; Philipp, W

2001-12-04

Einstein, Podolsky, and Rosen (EPR) have designed a gedanken experiment that suggested a theory that was more complete than quantum mechanics. The EPR design was later realized in various forms, with experimental results close to the quantum mechanical prediction. The experimental results by themselves have no bearing on the EPR claim that quantum mechanics must be incomplete nor on the existence of hidden parameters. However, the well known inequalities of Bell are based on the assumption that local hidden parameters exist and, when combined with conflicting experimental results, do appear to prove that local hidden parameters cannot exist. This fact leaves only instantaneous actions at a distance (called "spooky" by Einstein) to explain the experiments. The Bell inequalities are based on a mathematical model of the EPR experiments. They have no experimental confirmation, because they contradict the results of all EPR experiments. In addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions; for instance, he assumes that the hidden parameters are governed by a single probability measure independent of the analyzer settings. We argue that the mathematical model of Bell excludes a large set of local hidden variables and a large variety of probability densities. Our set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does permit derivation of the quantum result and is consistent with all known experiments.

Hidden attractors in dynamical systems

NASA Astrophysics Data System (ADS)

Dudkowski, Dawid; Jafari, Sajad; Kapitaniak, Tomasz; Kuznetsov, Nikolay V.; Leonov, Gennady A.; Prasad, Awadhesh

2016-06-01

Complex dynamical systems, ranging from the climate, ecosystems to financial markets and engineering applications typically have many coexisting attractors. This property of the system is called multistability. The final state, i.e., the attractor on which the multistable system evolves strongly depends on the initial conditions. Additionally, such systems are very sensitive towards noise and system parameters so a sudden shift to a contrasting regime may occur. To understand the dynamics of these systems one has to identify all possible attractors and their basins of attraction. Recently, it has been shown that multistability is connected with the occurrence of unpredictable attractors which have been called hidden attractors. The basins of attraction of the hidden attractors do not touch unstable fixed points (if exists) and are located far away from such points. Numerical localization of the hidden attractors is not straightforward since there are no transient processes leading to them from the neighborhoods of unstable fixed points and one has to use the special analytical-numerical procedures. From the viewpoint of applications, the identification of hidden attractors is the major issue. The knowledge about the emergence and properties of hidden attractors can increase the likelihood that the system will remain on the most desirable attractor and reduce the risk of the sudden jump to undesired behavior. We review the most representative examples of hidden attractors, discuss their theoretical properties and experimental observations. We also describe numerical methods which allow identification of the hidden attractors.

Structural barriers to HIV prevention among men who have sex with men (MSM) in Vietnam: Diversity, stigma, and healthcare access.

PubMed

Philbin, Morgan M; Hirsch, Jennifer S; Wilson, Patrick A; Ly, An Thanh; Giang, Le Minh; Parker, Richard G

2018-01-01

Men who have sex with men (MSM) in Vietnam experience disproportionate rates of HIV infection. To advance understanding of how structural barriers may shape their engagement with HIV prevention services, we draw on 32 in-depth interviews and four focus groups (n = 31) conducted with MSM in Hanoi between October 2015- March 2016. Three primary factors emerged: (1) Diversity, both in relation to identity and income; Vietnamese MSM described themselves as segregated into Bóng kín (hidden, often heterosexually-identified MSM) and Bóng lộ ('out,' transgender, or effeminate MSM). Lower-income, 'hidden' MSM from rural areas were reluctant to access MSM-targeted services; (2) Stigma: MSM reported being stigmatized by the healthcare system, family, and other MSM; and (3) Healthcare access: this was limited due to economic barriers and lack of MSM-friendly services. Our research suggests the need for multiple strategies to reach diverse types of MSM as well as to address barriers in access to health services such as stigma and costs. While a great deal has been written about the diversity of MSM in relation to gender performance and sexual identities, our research points to the substantial structural-level barriers that must be addressed in order to achieve meaningful and effective HIV prevention for MSM worldwide.

The Hidden Curriculum in Distance Education: An Updated View.

ERIC Educational Resources Information Center

Anderson, Terry

2001-01-01

Addressing recent criticism of distance education, explores the distinctive hidden curriculum (supposed "real" agenda) of distance education, focusing on both its positive and negative expressions. Also offers an updated view of the hidden curriculum of traditional, campus-based education, grounded in an emerging worldwide context of broadening…

77 FR 8253 - Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-14

... ENVIRONMENTAL PROTECTION AGENCY [FRL-9631-3] Notice of Proposed Settlement Agreement and Opportunity for Public Comment: Hidden Lane Landfill Superfund Site ACTION: Notice. SUMMARY: In accordance... (``DOJ'') on behalf of EPA, in connection with the Hidden Lane Landfill Superfund Site, Sterling, Loudoun...

Hidden Curriculum as One of Current Issue of Curriculum

ERIC Educational Resources Information Center

Alsubaie, Merfat Ayesh

2015-01-01

There are several issues in the education system, especially in the curriculum field that affect education. Hidden curriculum is one of current controversial curriculum issues. Many hidden curricular issues are the result of assumptions and expectations that are not formally communicated, established, or conveyed within the learning environment.…

Hidden Variable Theories and Quantum Nonlocality

ERIC Educational Resources Information Center

Boozer, A. D.

2009-01-01

We clarify the meaning of Bell's theorem and its implications for the construction of hidden variable theories by considering an example system consisting of two entangled spin-1/2 particles. Using this example, we present a simplified version of Bell's theorem and describe several hidden variable theories that agree with the predictions of…

Building Simple Hidden Markov Models. Classroom Notes

ERIC Educational Resources Information Center

Ching, Wai-Ki; Ng, Michael K.

2004-01-01

Hidden Markov models (HMMs) are widely used in bioinformatics, speech recognition and many other areas. This note presents HMMs via the framework of classical Markov chain models. A simple example is given to illustrate the model. An estimation method for the transition probabilities of the hidden states is also discussed.

Seuss's Butter Battle Book: Is There Hidden Harm?

ERIC Educational Resources Information Center

Van Cleaf, David W.; Martin, Rita J.

1986-01-01

Examines whether elementary school children relate to the "harmful hidden message" about nuclear war in Dr. Seuss's THE BUTTER BATTLE BOOK. After ascertaining the children's cognitive level, they participated in activities to find hidden meanings in stories, including Seuss's book. Students failed to identify the nuclear war message in…

Comment on 'All quantum observables in a hidden-variable model must commute simultaneously'

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagata, Koji

Malley discussed [Phys. Rev. A 69, 022118 (2004)] that all quantum observables in a hidden-variable model for quantum events must commute simultaneously. In this comment, we discuss that Malley's theorem is indeed valid for the hidden-variable theoretical assumptions, which were introduced by Kochen and Specker. However, we give an example that the local hidden-variable (LHV) model for quantum events preserves noncommutativity of quantum observables. It turns out that Malley's theorem is not related to the LHV model for quantum events, in general.

Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

We consider the problem of a subnetwork of observed nodes embedded into a larger bulk of unknown (i.e. hidden) nodes, where the aim is to infer these hidden states given information about the subnetwork dynamics. The biochemical networks underlying many cellular and metabolic processes are important realizations of such a scenario as typically one is interested in reconstructing the time evolution of unobserved chemical concentrations starting from the experimentally more accessible ones. We present an application to this problem of a novel dynamical mean field approximation, the extended Plefka expansion, which is based on a path integral description of the stochastic dynamics. As a paradigmatic model we study the stochastic linear dynamics of continuous degrees of freedom interacting via random Gaussian couplings. The resulting joint distribution is known to be Gaussian and this allows us to fully characterize the posterior statistics of the hidden nodes. In particular the equal-time hidden-to-hidden variance—conditioned on observations—gives the expected error at each node when the hidden time courses are predicted based on the observations. We assess the accuracy of the extended Plefka expansion in predicting these single node variances as well as error correlations over time, focussing on the role of the system size and the number of observed nodes.

Target space pseudoduality in supersymmetric sigma models on symmetric spaces

NASA Astrophysics Data System (ADS)

Sarisaman, Mustafa

We discuss the target space pseudoduality in supersymmetric sigma models on symmetric spaces. We first consider the case where sigma models based on real compact connected Lie groups of the same dimensionality and give examples using three dimensional models on target spaces. We show explicit construction of nonlocal conserved currents on the pseudodual manifold. We then switch the Lie group valued pseudoduality equations to Lie algebra valued ones, which leads to an infinite number of pseudoduality equations. We obtain an infinite number of conserved currents on the tangent bundle of the pseudo-dual manifold. Since pseudoduality imposes the condition that sigma models pseudodual to each other are based on symmetric spaces with opposite curvatures (i.e. dual symmetric spaces), we investigate pseudoduality transformation on the symmetric space sigma models in the third chapter. We see that there can be mixing of decomposed spaces with each other, which leads to mixings of the following expressions. We obtain the pseudodual conserved currents which are viewed as the orthonormal frame on the pullback bundle of the tangent space of G˜ which is the Lie group on which the pseudodual model based. Hence we obtain the mixing forms of curvature relations and one loop renormalization group beta function by means of these currents. In chapter four, we generalize the classical construction of pseudoduality transformation to supersymmetric case. We perform this both by component expansion method on manifold M and by orthonormal coframe method on manifold SO( M). The component method produces the result that pseudoduality transformation is not invertible at all points and occurs from all points on one manifold to only one point where riemann normal coordinates valid on the second manifold. Torsion of the sigma model on M must vanish while it is nonvanishing on M˜, and curvatures of the manifolds must be constant and the same because of anticommuting grassmann numbers. We obtain the similar results with the classical case in orthonormal coframe method. In case of super WZW sigma models pseudoduality equations result in three different pseudoduality conditions; flat space, chiral and antichiral pseudoduality. Finally we study the pseudoduality transformations on symmetric spaces using two different methods again. These two methods yield similar results to the classical cases with the exception that commuting bracket relations in classical case turns out to be anticommuting ones because of the appearance of grassmann numbers. It is understood that constraint relations in case of non-mixing pseudoduality are the remnants of mixing pseudoduality. Once mixing terms are included in the pseudoduality the constraint relations disappear.

Symmorphic Intersecting Nodal Rings in Semiconducting Layers

NASA Astrophysics Data System (ADS)

Gong, Cheng; Xie, Yuee; Chen, Yuanping; Kim, Heung-Sik; Vanderbilt, David

2018-03-01

The unique properties of topological semimetals have strongly driven efforts to seek for new topological phases and related materials. Here, we identify a critical condition for the existence of intersecting nodal rings (INRs) in symmorphic crystals, and further classify all possible kinds of INRs which can be obtained in the layered semiconductors with Amm2 and Cmmm space group symmetries. Several honeycomb structures are suggested to be topological INR semimetals, including layered and "hidden" layered structures. Transitions between the three types of INRs, named as α , β , and γ type, can be driven by external strains in these structures. The resulting surface states and Landau-level structures, more complicated than those resulting from a simple nodal loop, are also discussed.

Hierarchically Structured Non-Intrusive Sign Language Recognition. Chapter 2

NASA Technical Reports Server (NTRS)

Zieren, Jorg; Zieren, Jorg; Kraiss, Karl-Friedrich

2007-01-01

This work presents a hierarchically structured approach at the nonintrusive recognition of sign language from a monocular frontal view. Robustness is achieved through sophisticated localization and tracking methods, including a combined EM/CAMSHIFT overlap resolution procedure and the parallel pursuit of multiple hypotheses about hands position and movement. This allows handling of ambiguities and automatically corrects tracking errors. A biomechanical skeleton model and dynamic motion prediction using Kalman filters represents high level knowledge. Classification is performed by Hidden Markov Models. 152 signs from German sign language were recognized with an accuracy of 97.6%.

Uncovering the Hidden Structure of Platoons: Formal and Emergent Leaders’ Perceptions of Organizational Networks

DTIC Science & Technology

2008-12-01

perceptions of formal and emergent leaders differ from those of non-leaders, and if so, how. We approach this topic through the lens of social network...analysis. 1.1 Social Networks The term “ social network” refers to a set of actors who are connected by a set of ties. Actors, often referred to as...the structure of any social system can be defined as a set of relations between all pairs of individuals who are members of the network (Krackhardt

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models

PubMed Central

Murray-Watters, Alexander; Glymour, Clark

2016-01-01

Using Gebharter's (2014) representation, we consider aspects of the problem of discovering the structure of unmeasured sub-mechanisms when the variables in those sub-mechanisms have not been measured. Exploiting an early insight of Sober's (1998), we provide a correct algorithm for identifying latent, endogenous structure—sub-mechanisms—for a restricted class of structures. The algorithm can be merged with other methods for discovering causal relations among unmeasured variables, and feedback relations between measured variables and unobserved causes can sometimes be learned. PMID:27313331

Increased taxon sampling reveals thousands of hidden orthologs in flatworms

PubMed Central

2017-01-01

Gains and losses shape the gene complement of animal lineages and are a fundamental aspect of genomic evolution. Acquiring a comprehensive view of the evolution of gene repertoires is limited by the intrinsic limitations of common sequence similarity searches and available databases. Thus, a subset of the gene complement of an organism consists of hidden orthologs, i.e., those with no apparent homology to sequenced animal lineages—mistakenly considered new genes—but actually representing rapidly evolving orthologs or undetected paralogs. Here, we describe Leapfrog, a simple automated BLAST pipeline that leverages increased taxon sampling to overcome long evolutionary distances and identify putative hidden orthologs in large transcriptomic databases by transitive homology. As a case study, we used 35 transcriptomes of 29 flatworm lineages to recover 3427 putative hidden orthologs, some unidentified by OrthoFinder and HaMStR, two common orthogroup inference algorithms. Unexpectedly, we do not observe a correlation between the number of putative hidden orthologs in a lineage and its “average” evolutionary rate. Hidden orthologs do not show unusual sequence composition biases that might account for systematic errors in sequence similarity searches. Instead, gene duplication with divergence of one paralog and weak positive selection appear to underlie hidden orthology in Platyhelminthes. By using Leapfrog, we identify key centrosome-related genes and homeodomain classes previously reported as absent in free-living flatworms, e.g., planarians. Altogether, our findings demonstrate that hidden orthologs comprise a significant proportion of the gene repertoire in flatworms, qualifying the impact of gene losses and gains in gene complement evolution. PMID:28400424

A Rose By Other Names: Some General Musings on Lawrence and Colleagues' Hidden Curriculum Scoping Review.

PubMed

Hafferty, Frederic W; Martimianakis, Maria Athina

2017-11-07

In this Commentary, the authors explore the scoping review by Lawrence and colleagues by challenging their conclusion that with over 25 years' worth of "ambiguous and seemingly ubiquitous use" of the hidden curriculum construct in health professions education scholarship, it is time to either move to a more uniform definitional foundation or abandon the term altogether. The commentary authors counter these remedial propositions by foregrounding the importance of theoretical diversity and the conceptual richness afforded when the hidden curriculum construct is used as an entry point for studying the interstitial space between the formal and a range of other-than-formal domains of learning. Further, they document how tightly-delimited scoping strategies fail to capture the wealth of educational scholarship that operates within a hidden curriculum framework, including "hidden" hidden curriculum articles, studies that employ alternative constructs, and investigations that target important tacit socio-cultural influences on learners and faculty without formally deploying the term. They offer examples of how the hidden curriculum construct, while undergoing significant transformation in its application within the field of health professions education, has created the conceptual foundation for the application of a number of critical perspectives that make visible the field's political investments in particular forms of knowing and associated practices. Finally, the commentary authors invite readers to consider the methodological promise afforded by conceptual heterogeneity, particularly strands of scholarship that resituate the hidden curriculum concept within the magically expansive dance of social relationships, social learning, and social life that form the learning environments of health professions education.

FIMP dark matter freeze-in gauge mediation and hidden sector

NASA Astrophysics Data System (ADS)

Tsao, Kuo-Hsing

2018-07-01

We explore the dark matter freeze-in mechanism within the gauge mediation framework, which involves a hidden feebly interacting massive particle (FIMP) coupling feebly with the messenger fields while the messengers are still in the thermal bath. The FIMP is the fermionic component of the pseudo-moduli in a generic metastable supersymmetry (SUSY) breaking model and resides in the hidden sector. The relic abundance and the mass of the FIMP are determined by the SUSY breaking scale and the feeble coupling. The gravitino, which is the canonical dark matter candidate in the gauge mediation framework, contributes to the dark matter relic abundance along with the freeze-in of the FIMP. The hidden sector thus becomes two-component with both the FIMP and gravitino lodging in the SUSY breaking hidden sector. We point out that the ratio between the FIMP and the gravitino is determined by how SUSY breaking is communicated to the messengers. In particular when the FIMP dominates the hidden sector, the gravitino becomes the minor contributor in the hidden sector. Meanwhile, the neutralino is assumed to be both the weakly interacting massive particle dark matter candidate in the freeze-out mechanism and the lightest observable SUSY particle. We further find out the neutralino has the sub-leading contribution to the current dark matter relic density in the parameter space of our freeze-in gauge mediation model. Our result links the SUSY breaking scale in the gauge mediation framework with the FIMP freeze-in production rate leading to a natural and predicting scenario for the studies of the dark matter in the hidden sector.

Noise-induced cochlear synaptopathy: Past findings and future studies.

PubMed

Kobel, Megan; Le Prell, Colleen G; Liu, Jennifer; Hawks, John W; Bao, Jianxin

2017-06-01

For decades, we have presumed the death of hair cells and spiral ganglion neurons are the main cause of hearing loss and difficulties understanding speech in noise, but new findings suggest synapse loss may be the key contributor. Specifically, recent preclinical studies suggest that the synapses between inner hair cells and spiral ganglion neurons with low spontaneous rates and high thresholds are the most vulnerable subcellular structures, with respect to insults during aging and noise exposure. This cochlear synaptopathy can be "hidden" because this synaptic loss can occur without permanent hearing threshold shifts. This new discovery of synaptic loss opens doors to new research directions. Here, we review a number of recent studies and make suggestions in two critical future research directions. First, based on solid evidence of cochlear synaptopathy in animal models, it is time to apply molecular approaches to identify the underlying molecular mechanisms; improved understanding is necessary for developing rational, effective therapies against this cochlear synaptopathy. Second, in human studies, the data supporting cochlear synaptopathy are indirect although rapid progress has been made. To fully identify changes in function that are directly related this hidden synaptic damage, we argue that a battery of tests including both electrophysiological and behavior tests should be combined for diagnosis of "hidden hearing loss" in clinical studies. This new approach may provide a direct link between cochlear synaptopathy and perceptual difficulties. Copyright © 2016 Elsevier B.V. All rights reserved.

An alternative approach for neural network evolution with a genetic algorithm: crossover by combinatorial optimization.

PubMed

García-Pedrajas, Nicolás; Ortiz-Boyer, Domingo; Hervás-Martínez, César

2006-05-01

In this work we present a new approach to crossover operator in the genetic evolution of neural networks. The most widely used evolutionary computation paradigm for neural network evolution is evolutionary programming. This paradigm is usually preferred due to the problems caused by the application of crossover to neural network evolution. However, crossover is the most innovative operator within the field of evolutionary computation. One of the most notorious problems with the application of crossover to neural networks is known as the permutation problem. This problem occurs due to the fact that the same network can be represented in a genetic coding by many different codifications. Our approach modifies the standard crossover operator taking into account the special features of the individuals to be mated. We present a new model for mating individuals that considers the structure of the hidden layer and redefines the crossover operator. As each hidden node represents a non-linear projection of the input variables, we approach the crossover as a problem on combinatorial optimization. We can formulate the problem as the extraction of a subset of near-optimal projections to create the hidden layer of the new network. This new approach is compared to a classical crossover in 25 real-world problems with an excellent performance. Moreover, the networks obtained are much smaller than those obtained with classical crossover operator.

The ``Folk Theorem'' on effective field theory: How does it fare in nuclear physics?

NASA Astrophysics Data System (ADS)

Rho, Mannque

2017-10-01

This is a brief history of what I consider as very important, some of which truly seminal, contributions made by young Korean nuclear theorists, mostly graduate students working on PhD thesis in 1990s and early 2000s, to nuclear effective field theory, nowadays heralded as the first-principle approach to nuclear physics. The theoretical framework employed is an effective field theory anchored on a single scale-invariant hidden local symmetric Lagrangian constructed in the spirit of Weinberg's "Folk Theorem" on effective field theory. The problems addressed are the high-precision calculations on the thermal np capture, the solar pp fusion process, the solar hep process — John Bahcall's challenge to nuclear theorists — and the quenching of g A in giant Gamow-Teller resonances and the whopping enhancement of first-forbidden beta transitions relevant in astrophysical processes. Extending adventurously the strategy to a wild uncharted domain in which a systematic implementation of the "theorem" is far from obvious, the same effective Lagrangian is applied to the structure of compact stars. A surprising, unexpected, result on the properties of massive stars, totally different from what has been obtained up to day in the literature, is predicted, such as the precocious onset of conformal sound velocity together with a hint for the possible emergence in dense matter of hidden symmetries such as scale symmetry and hidden local symmetry.

Simultaneous escaping of explicit and hidden free energy barriers: application of the orthogonal space random walk strategy in generalized ensemble based conformational sampling.

PubMed

Zheng, Lianqing; Chen, Mengen; Yang, Wei

2009-06-21

To overcome the pseudoergodicity problem, conformational sampling can be accelerated via generalized ensemble methods, e.g., through the realization of random walks along prechosen collective variables, such as spatial order parameters, energy scaling parameters, or even system temperatures or pressures, etc. As usually observed, in generalized ensemble simulations, hidden barriers are likely to exist in the space perpendicular to the collective variable direction and these residual free energy barriers could greatly abolish the sampling efficiency. This sampling issue is particularly severe when the collective variable is defined in a low-dimension subset of the target system; then the "Hamiltonian lagging" problem, which reveals the fact that necessary structural relaxation falls behind the move of the collective variable, may be likely to occur. To overcome this problem in equilibrium conformational sampling, we adopted the orthogonal space random walk (OSRW) strategy, which was originally developed in the context of free energy simulation [L. Zheng, M. Chen, and W. Yang, Proc. Natl. Acad. Sci. U.S.A. 105, 20227 (2008)]. Thereby, generalized ensemble simulations can simultaneously escape both the explicit barriers along the collective variable direction and the hidden barriers that are strongly coupled with the collective variable move. As demonstrated in our model studies, the present OSRW based generalized ensemble treatments show improved sampling capability over the corresponding classical generalized ensemble treatments.

Hidden symmetries and supergravity solutions

NASA Astrophysics Data System (ADS)

Santillan, Osvaldo P.

2012-04-01

The role of Killing and Killing-Yano tensors for studying the geodesic motion of the particle and the superparticle in a curved background is reviewed. Additionally, the Papadopoulos list [G. Papadopoulos, Class. Quantum Grav. 25, 105016 (2008)], 10.1088/0264-9381/25/10/105016 for Killing-Yano tensors in G structures is reproduced by studying the torsion types these structures admit. The Papadopoulos list deals with groups G appearing in the Berger classification, and we enlarge the list by considering additional G structures which are not of the Berger type. Possible applications of these results in the study of supersymmetric particle actions and in the AdS/CFT correspondence are outlined.

What Should We Do With a Hidden Curriculum When We Fine One?

ERIC Educational Resources Information Center

Martin, Jane R.

1976-01-01

A hidden curriculum consists of those learning states of a setting that are either unintended or intended but not openly acknowledged to the learners in the setting unless the learners are aware of them. Consciousness-raising may be the best weapon of individuals who are subject to hidden curricula. (Author/MLF)

Manifestations of Hidden Curriculum in a Community College Online Opticianry Program: An Ecological Approach

ERIC Educational Resources Information Center

Hubbard, Barry

2010-01-01

Understanding the influential factors at work within an online learning environment is a growing area of interest. Hidden or implicit expectations, skill sets, knowledge, and social process can help or hinder student achievement, belief systems, and persistence. This qualitative study investigated how hidden curricular issues transpired in an…

The Hidden Reason Behind Children's Misbehavior.

ERIC Educational Resources Information Center

Nystul, Michael S.

1986-01-01

Discusses hidden reason theory based on the assumptions that: (1) the nature of people is positive; (2) a child's most basic psychological need is involvement; and (3) a child has four possible choices in life (good somebody, good nobody, bad somebody, or severely mentally ill.) A three step approach for implementing hidden reason theory is…

Student Teaching: A Hidden Wholeness

ERIC Educational Resources Information Center

Bowman, Richard F.

2007-01-01

Productive student teachers lead learning by emergently sensing and honoring the hidden wholeness of life in classrooms. That hidden wholeness mirrors seven contextual concerns which learners reflect upon in the everydayness of classroom life: What are we going to do in class today? What am I going to have to do in class? What counts in today's…

Environmental Assessment for the Expansion of Permitted Land and Operations at the 9940 Complex and Thunder Range at Sandia National Laboratories/New Mexico

DTIC Science & Technology

2008-03-01

vivipara Hidden flower Cryptantha crassisepala Hidden flower Cryptantha fulvocanescens James’s hidden flower Cryptantha jamesii Buffalo gourd...pumila Bigbract verbena ta Verbena bractea Banana yucca ta Yucca bacca Soapweed yucca Yucca glauca Rocky Mountain zinnia Zinnia grandiflora A-9

Hidden Agendas in Marriage: Affective and Longitudinal Dimensions.

ERIC Educational Resources Information Center

Krokoff, Lowell J.

1990-01-01

Examines how couples' discussions of troublesome problems reveal hidden agendas (issues not directly discussed or explored). Finds disgust and contempt are at the core of both love and respect agendas for husbands and wives. Finds that wives' more than husbands' hidden agendas are directly predictive of how negatively they argue at home. (SR)

Driving style recognition method using braking characteristics based on hidden Markov model

PubMed Central

Wu, Chaozhong; Lyu, Nengchao; Huang, Zhen

2017-01-01

Since the advantage of hidden Markov model in dealing with time series data and for the sake of identifying driving style, three driving style (aggressive, moderate and mild) are modeled reasonably through hidden Markov model based on driver braking characteristics to achieve efficient driving style. Firstly, braking impulse and the maximum braking unit area of vacuum booster within a certain time are collected from braking operation, and then general braking and emergency braking characteristics are extracted to code the braking characteristics. Secondly, the braking behavior observation sequence is used to describe the initial parameters of hidden Markov model, and the generation of the hidden Markov model for differentiating and an observation sequence which is trained and judged by the driving style is introduced. Thirdly, the maximum likelihood logarithm could be implied from the observable parameters. The recognition accuracy of algorithm is verified through experiments and two common pattern recognition algorithms. The results showed that the driving style discrimination based on hidden Markov model algorithm could realize effective discriminant of driving style. PMID:28837580

A possible loophole in the theorem of Bell.

PubMed

Hess, K; Philipp, W

2001-12-04

The celebrated inequalities of Bell are based on the assumption that local hidden parameters exist. When combined with conflicting experimental results, these inequalities appear to prove that local hidden parameters cannot exist. This contradiction suggests to many that only instantaneous action at a distance can explain the Einstein, Podolsky, and Rosen type of experiments. We show that, in addition to the assumption that hidden parameters exist, Bell tacitly makes a variety of other assumptions that contribute to his being able to obtain the desired contradiction. For instance, Bell assumes that the hidden parameters do not depend on time and are governed by a single probability measure independent of the analyzer settings. We argue that the exclusion of time has neither a physical nor a mathematical basis but is based on Bell's translation of the concept of Einstein locality into the language of probability theory. Our additional set of local hidden variables includes time-like correlated parameters and a generalized probability density. We prove that our extended space of local hidden variables does not permit Bell-type proofs to go forward.

Reputation and Competition in a Hidden Action Model

PubMed Central

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium. PMID:25329387

Reputation and competition in a hidden action model.

PubMed

Fedele, Alessandro; Tedeschi, Piero

2014-01-01

The economics models of reputation and quality in markets can be classified in three categories. (i) Pure hidden action, where only one type of seller is present who can provide goods of different quality. (ii) Pure hidden information, where sellers of different types have no control over product quality. (iii) Mixed frameworks, which include both hidden action and hidden information. In this paper we develop a pure hidden action model of reputation and Bertrand competition, where consumers and firms interact repeatedly in a market with free entry. The price of the good produced by the firms is contractible, whilst the quality is noncontractible, hence it is promised by the firms when a contract is signed. Consumers infer future quality from all available information, i.e., both from what they know about past quality and from current prices. According to early contributions, competition should make reputation unable to induce the production of high-quality goods. We provide a simple solution to this problem by showing that high quality levels are sustained as an outcome of a stationary symmetric equilibrium.

Photoacoustic imaging of hidden dental caries by using a bundle of hollow optical fibers

NASA Astrophysics Data System (ADS)

Koyama, Takuya; Kakino, Satoko; Matsuura, Yuji

2018-02-01

Photoacoustic imaging system using a bundle of hollow-optical fibers to detect hidden dental caries is proposed. Firstly, we fabricated a hidden caries model with a brown pigment simulating a common color of caries lesion. It was found that high frequency ultrasonic waves are generated from hidden carious part when radiating Nd:YAG laser light with a 532 nm wavelength to occlusal surface of model tooth. We calculated by Fourier transform and found that the waveform from the carious part provides frequency components of approximately from 0.5 to 1.2 MHz. Then a photoacoustic imaging system using a bundle of hollow optical fiber was fabricated for clinical applications. From intensity map of frequency components in 0.5-1.2 MHz, photoacoustic images of hidden caries in the simulated samples were successfully obtained.

On the LHC sensitivity for non-thermalised hidden sectors

NASA Astrophysics Data System (ADS)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Optimization of Artificial Neural Network using Evolutionary Programming for Prediction of Cascading Collapse Occurrence due to the Hidden Failure Effect

NASA Astrophysics Data System (ADS)

Idris, N. H.; Salim, N. A.; Othman, M. M.; Yasin, Z. M.

2018-03-01

This paper presents the Evolutionary Programming (EP) which proposed to optimize the training parameters for Artificial Neural Network (ANN) in predicting cascading collapse occurrence due to the effect of protection system hidden failure. The data has been collected from the probability of hidden failure model simulation from the historical data. The training parameters of multilayer-feedforward with backpropagation has been optimized with objective function to minimize the Mean Square Error (MSE). The optimal training parameters consists of the momentum rate, learning rate and number of neurons in first hidden layer and second hidden layer is selected in EP-ANN. The IEEE 14 bus system has been tested as a case study to validate the propose technique. The results show the reliable prediction of performance validated through MSE and Correlation Coefficient (R).

Hidden Rift Structure Beneath a Thick Sedimentary Basin in the Niigata Region, Japan

NASA Astrophysics Data System (ADS)

Takeda, T.; Enescu, B.; Asano, Y.; Obara, K.; Sekiguchi, S.

2010-12-01

Niigata region is located in a high-strain-rate zone, along the easternmost margin of the back-arc basin of the Sea of Japan (Sagiya et al., 2000, Okamura et al., 1995). In this region, two M6.8 inland earthquakes with reverse fault type focal mechanism, having NW-SE compression, occurred in 2004 and 2007. The reverse fault system may indicate present reactivation of the rift structure formed as a result of normal faulting when the Sea of Japan opened in the Miocene (Sato, 1994). Therefore, imaging the spatial extent of the rift structure is important to reveal the seismotectonics and occurrence mechanism of inland earthquakes. To resolve the fine structure beneath the Niigata region, we have installed a dense temporary network of 300 seismic stations and performed a regional tomography analysis. The temporary seismic network was designed with a multi-scale station spacing of 3 to 5 km in and around the aftershock areas of the two large earthquakes, and of ~10 km for the surrounding region. The 3D velocity tomography analysis and relocation of earthquakes were performed using the tomoDD software (Zhang and Thurber, 2003). We used 777 events that occurred after the installation of the temporary network and 703 events that were recorded only by the permanent seismic network (Hi-net) before the temporary network deployment. The initial 3D velocity model was constructed by using the 3D shallow velocity structure provided by the “Japan Seismic Hazard Information Station” (J-SHIS; Fujiwara et al., 2009) of NIED. The horizontal and vertical grid spacing were of 5 ~ 10 km and 2 ~ 4 km, respectively. The tomography analysis enabled us to delineate the fine subsurface structure. The high and low velocity pattern corresponds well to the Bouguer gravity anomalies mapped in the region. The velocity model shows a wide and relatively low velocity (< 5 km/sec for the P-wave velocity) band extending in a NE-SW direction. The band widens and narrows along its extent. The thickness of the low-velocity region varies from place to place and exceeds 7 km in some parts. The surface of the basement rock below the low velocity band is fairly undulated, showing in some places a stair-like structure. Most of the earthquakes occurred in the basement rocks. The aftershocks of the 2004 and 2007 Niigata earthquakes occurred on the flanks of the lower velocity band. Kato et al. (2009) suggested that in the two aftershock areas the undulation of the basement rock surface was formed from multiple rift structures. According to our tomography results, the undulation structure is extensively found below the low-velocity band, which indicates that ancient, hidden rift structures are widely distributed. Some of these structures show micro-earthquake activity, however they do not correspond to the recognized active fault traces. The reactivation of deep rift structures covered with thick sediments may have not been fully detected. Therefore, mapping of the hidden rift structure helps mitigating the earthquake hazards in this high strain-rate and high seismic activity region.

Proceedings of the Annual Meeting of the Association for Education in Journalism and Mass Communication (76th, Kansas City, Missouri, August 11-14, 1993). Part XIII: Miscellaneous Studies.

ERIC Educational Resources Information Center

Association for Education in Journalism and Mass Communication.

The Miscellaneous Studies section of this collection of conference presentations contains the following 12 papers: "Revelatory Silences: A Critical Analysis of the Structuring Absences in Sydney Pollack's 'Out of Africa'" (Brenda Cooper and David Descutner); "The Cox Fight with the FCC: Gamesmanship, Hidden Agendas, and Personal…

Are Models Easier to Understand than Code? An Empirical Study on Comprehension of Entity-Relationship (ER) Models vs. Structured Query Language (SQL) Code

ERIC Educational Resources Information Center

Sanchez, Pablo; Zorrilla, Marta; Duque, Rafael; Nieto-Reyes, Alicia

2011-01-01

Models in Software Engineering are considered as abstract representations of software systems. Models highlight relevant details for a certain purpose, whereas irrelevant ones are hidden. Models are supposed to make system comprehension easier by reducing complexity. Therefore, models should play a key role in education, since they would ease the…

ABC: Aging-Based IC Configuration

DTIC Science & Technology

2014-04-01

Benign Hardware Trojan on FPGA-based Embedded Systems Hardware Trojan Horses (HTHs) are hidden structural and functional alterations of an integrated...or highly damaging hardware Trojans [66] [67] [68]. However, while all these efforts created Trojan horses with the intention to demonstrate their...practical importance and/or to facilitate development of the detection techniques, in our case the purpose of the Trojan horse is to directly enable

Thinking Through Egyptian Tradition: The Potential of Pre-Colonial Craft Working Methods in Art Education

ERIC Educational Resources Information Center

Shafer, Ann

2013-01-01

The January 25th 2011 Revolution in Egypt brought the eyes of the world to the "cradle of civilization" once more, as existing power structures toppled and hidden voices surfaced to forge a unified vision for the future. In many parts of the Middle East, and indeed all over the world, the visual arts embody cultural values and remain a…

Nonparametric model validations for hidden Markov models with applications in financial econometrics.

PubMed

Zhao, Zhibiao

2011-06-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise.

State Space Model with hidden variables for reconstruction of gene regulatory networks.

PubMed

Wu, Xi; Li, Peng; Wang, Nan; Gong, Ping; Perkins, Edward J; Deng, Youping; Zhang, Chaoyang

2011-01-01

State Space Model (SSM) is a relatively new approach to inferring gene regulatory networks. It requires less computational time than Dynamic Bayesian Networks (DBN). There are two types of variables in the linear SSM, observed variables and hidden variables. SSM uses an iterative method, namely Expectation-Maximization, to infer regulatory relationships from microarray datasets. The hidden variables cannot be directly observed from experiments. How to determine the number of hidden variables has a significant impact on the accuracy of network inference. In this study, we used SSM to infer Gene regulatory networks (GRNs) from synthetic time series datasets, investigated Bayesian Information Criterion (BIC) and Principle Component Analysis (PCA) approaches to determining the number of hidden variables in SSM, and evaluated the performance of SSM in comparison with DBN. True GRNs and synthetic gene expression datasets were generated using GeneNetWeaver. Both DBN and linear SSM were used to infer GRNs from the synthetic datasets. The inferred networks were compared with the true networks. Our results show that inference precision varied with the number of hidden variables. For some regulatory networks, the inference precision of DBN was higher but SSM performed better in other cases. Although the overall performance of the two approaches is compatible, SSM is much faster and capable of inferring much larger networks than DBN. This study provides useful information in handling the hidden variables and improving the inference precision.

The Hidden Curriculum of Youth Policy: A Dutch Example

ERIC Educational Resources Information Center

Hopman, Marit; de Winter, Micha; Koops, Willem

2014-01-01

Youth policy is more than a mere response to the actual behavior of children, but it is equally influenced by values and beliefs of policy makers. These values are however rarely made explicit and, therefore, the authors refer to them as "the hidden curriculum" of youth policy. The study investigation explicates this hidden curriculum by…

Hidden School Dropout among Immigrant Students: A Cross-Sectional Study

ERIC Educational Resources Information Center

Makarova, Elena; Herzog, Walter

2013-01-01

Actual school dropout among immigrant youth has been addressed in a number of studies, but research on hidden school dropout among immigrant students is rare. Thus, the objective of this paper is to analyze hidden school dropout among primary school students with an immigrant background. The analyses were performed using survey data of 1186…

Secret Codes: The Hidden Curriculum of Semantic Web Technologies

ERIC Educational Resources Information Center

Edwards, Richard; Carmichael, Patrick

2012-01-01

There is a long tradition in education of examination of the hidden curriculum, those elements which are implicit or tacit to the formal goals of education. This article draws upon that tradition to open up for investigation the hidden curriculum and assumptions about students and knowledge that are embedded in the coding undertaken to facilitate…

Dopamine reward prediction errors reflect hidden state inference across time

PubMed Central

Starkweather, Clara Kwon; Babayan, Benedicte M.; Uchida, Naoshige; Gershman, Samuel J.

2017-01-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a ‘belief state’). In this work, we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling exhibited a striking difference between two tasks that differed only with respect to whether reward was delivered deterministically. Our results favor an associative learning rule that combines cached values with hidden state inference. PMID:28263301

Cosmological abundance of the QCD axion coupled to hidden photons

NASA Astrophysics Data System (ADS)

Kitajima, Naoya; Sekiguchi, Toyokazu; Takahashi, Fuminobu

2018-06-01

We study the cosmological evolution of the QCD axion coupled to hidden photons. For a moderately strong coupling, the motion of the axion field leads to an explosive production of hidden photons by tachyonic instability. We use lattice simulations to evaluate the cosmological abundance of the QCD axion. In doing so, we incorporate the backreaction of the produced hidden photons on the axion dynamics, which becomes significant in the non-linear regime. We find that the axion abundance is suppressed by at most O (102) for the decay constant fa =1016GeV, compared to the case without the coupling. For a sufficiently large coupling, the motion of the QCD axion becomes strongly damped, and as a result, the axion abundance is enhanced. Our results show that the cosmological upper bound on the axion decay constant can be relaxed by a few hundred for a certain range of the coupling to hidden photons.

Perspective: Disclosing hidden sources of funding.

PubMed

Resnik, David B

2009-09-01

In this article, the author discusses ethical and policy issues related to the disclosure of hidden sources of funding in research. The author argues that authors have an ethical obligation to disclose hidden sources of funding and that journals should adopt policies to enforce this obligation. Journal policies should require disclosure of hidden sources of funding that authors know about and that have a direct relation to their research. To stimulate this discussion, the author describes a recent case: investigators who conducted a lung cancer screening study had received funding from a private foundation that was supported by a tobacco company, but they did not disclose this relationship to the journal. Investigators and journal editors must be prepared to deal with these issues in a manner that promotes honesty, transparency, fairness, and accountability in research. The development of well-defined, reasonable policies pertaining to hidden sources of funding can be a step in this direction.

Dopamine reward prediction errors reflect hidden-state inference across time.

PubMed

Starkweather, Clara Kwon; Babayan, Benedicte M; Uchida, Naoshige; Gershman, Samuel J

2017-04-01

Midbrain dopamine neurons signal reward prediction error (RPE), or actual minus expected reward. The temporal difference (TD) learning model has been a cornerstone in understanding how dopamine RPEs could drive associative learning. Classically, TD learning imparts value to features that serially track elapsed time relative to observable stimuli. In the real world, however, sensory stimuli provide ambiguous information about the hidden state of the environment, leading to the proposal that TD learning might instead compute a value signal based on an inferred distribution of hidden states (a 'belief state'). Here we asked whether dopaminergic signaling supports a TD learning framework that operates over hidden states. We found that dopamine signaling showed a notable difference between two tasks that differed only with respect to whether reward was delivered in a deterministic manner. Our results favor an associative learning rule that combines cached values with hidden-state inference.

Nurture Hidden Talents: Transform School Culture into One That Values Teacher Expertise

ERIC Educational Resources Information Center

Zimmerman, Diane P.

2014-01-01

This article looks into the school culture where teacher expertise is often hidden and underused. While the media-rich culture places a high value on talent, the irony is that talent is underrated in most schools, and educators often remain silent about their hidden talents. Many school cultures are not conducive to dialogue that supports displays…

Nonparametric model validations for hidden Markov models with applications in financial econometrics

PubMed Central

Zhao, Zhibiao

2011-01-01

We address the nonparametric model validation problem for hidden Markov models with partially observable variables and hidden states. We achieve this goal by constructing a nonparametric simultaneous confidence envelope for transition density function of the observable variables and checking whether the parametric density estimate is contained within such an envelope. Our specification test procedure is motivated by a functional connection between the transition density of the observable variables and the Markov transition kernel of the hidden states. Our approach is applicable for continuous time diffusion models, stochastic volatility models, nonlinear time series models, and models with market microstructure noise. PMID:21750601

Hidden Area and Mechanical Nonlinearities in Freestanding Graphene.

PubMed

Nicholl, Ryan J T; Lavrik, Nickolay V; Vlassiouk, Ivan; Srijanto, Bernadeta R; Bolotin, Kirill I

2017-06-30

We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ∼0% obeyed linear mechanics with biaxial stiffness 428±10  N/m, specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ∼0.1.

Hidden Area and Mechanical Nonlinearities in Freestanding Graphene

NASA Astrophysics Data System (ADS)

Nicholl, Ryan J. T.; Lavrik, Nickolay V.; Vlassiouk, Ivan; Srijanto, Bernadeta R.; Bolotin, Kirill I.

2017-06-01

We investigated the effect of out-of-plane crumpling on the mechanical response of graphene membranes. In our experiments, stress was applied to graphene membranes using pressurized gas while the strain state was monitored through two complementary techniques: interferometric profilometry and Raman spectroscopy. By comparing the data obtained through these two techniques, we determined the geometric hidden area which quantifies the crumpling strength. While the devices with hidden area ˜0 % obeyed linear mechanics with biaxial stiffness 428 ±10 N /m , specimens with hidden area in the range 0.5%-1.0% were found to obey an anomalous nonlinear Hooke's law with an exponent ˜0.1 .

Multilayer neural networks with extensively many hidden units.

PubMed

Rosen-Zvi, M; Engel, A; Kanter, I

2001-08-13

The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones.

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Moroz, Irene; Sprott, J. C.; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, the 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

Hidden hyperchaos and electronic circuit application in a 5D self-exciting homopolar disc dynamo.

PubMed

Wei, Zhouchao; Moroz, Irene; Sprott, J C; Akgul, Akif; Zhang, Wei

2017-03-01

We report on the finding of hidden hyperchaos in a 5D extension to a known 3D self-exciting homopolar disc dynamo. The hidden hyperchaos is identified through three positive Lyapunov exponents under the condition that the proposed model has just two stable equilibrium states in certain regions of parameter space. The new 5D hyperchaotic self-exciting homopolar disc dynamo has multiple attractors including point attractors, limit cycles, quasi-periodic dynamics, hidden chaos or hyperchaos, as well as coexisting attractors. We use numerical integrations to create the phase plane trajectories, produce bifurcation diagram, and compute Lyapunov exponents to verify the hidden attractors. Because no unstable equilibria exist in two parameter regions, the system has a multistability and six kinds of complex dynamic behaviors. To the best of our knowledge, this feature has not been previously reported in any other high-dimensional system. Moreover, the 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integrations. Both Matlab and the oscilloscope outputs produce similar phase portraits. Such implementations in real time represent a new type of hidden attractor with important consequences for engineering applications.

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study.

PubMed

Dewey, Rebecca Susan; Hall, Deborah A; Guest, Hannah; Prendergast, Garreth; Plack, Christopher J; Francis, Susan T

2018-03-09

Rodent studies indicate that noise exposure can cause permanent damage to synapses between inner hair cells and high-threshold auditory nerve fibers, without permanently altering threshold sensitivity. These demonstrations of what is commonly known as hidden hearing loss have been confirmed in several rodent species, but the implications for human hearing are unclear. Our Medical Research Council-funded program aims to address this unanswered question, by investigating functional consequences of the damage to the human peripheral and central auditory nervous system that results from cumulative lifetime noise exposure. Behavioral and neuroimaging techniques are being used in a series of parallel studies aimed at detecting hidden hearing loss in humans. The planned neuroimaging study aims to (1) identify central auditory biomarkers associated with hidden hearing loss; (2) investigate whether there are any additive contributions from tinnitus or diminished sound tolerance, which are often comorbid with hearing problems; and (3) explore the relation between subcortical functional magnetic resonance imaging (fMRI) measures and the auditory brainstem response (ABR). Individuals aged 25 to 40 years with pure tone hearing thresholds ≤20 dB hearing level over the range 500 Hz to 8 kHz and no contraindications for MRI or signs of ear disease will be recruited into the study. Lifetime noise exposure will be estimated using an in-depth structured interview. Auditory responses throughout the central auditory system will be recorded using ABR and fMRI. Analyses will focus predominantly on correlations between lifetime noise exposure and auditory response characteristics. This paper reports the study protocol. The funding was awarded in July 2013. Enrollment for the study described in this protocol commenced in February 2017 and was completed in December 2017. Results are expected in 2018. This challenging and comprehensive study will have the potential to impact diagnostic procedures for hidden hearing loss, enabling early identification of noise-induced auditory damage via the detection of changes in central auditory processing. Consequently, this will generate the opportunity to give personalized advice regarding provision of ear defense and monitoring of further damage, thus reducing the incidence of noise-induced hearing loss. ©Rebecca Susan Dewey, Deborah A Hall, Hannah Guest, Garreth Prendergast, Christopher J Plack, Susan T Francis. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 09.03.2018.

Experimental and Computational Studies on the Scattering of an Edge-Guided Wave by a Hidden Crack on a Racecourse Shaped Hole.

PubMed

Vien, Benjamin Steven; Rose, Louis Raymond Francis; Chiu, Wing Kong

2017-07-01

Reliable and quantitative non-destructive evaluation for small fatigue cracks, in particular those in hard-to-inspect locations, is a challenging problem. Guided waves are advantageous for structural health monitoring due to their slow geometrical decay of amplitude with propagating distance, which is ideal for rapid wide-area inspection. This paper presents a 3D laser vibrometry experimental and finite element analysis of the interaction between an edge-guided wave and a small through-thickness hidden edge crack on a racecourse shaped hole that occurs, in practice, as a fuel vent hole. A piezoelectric transducer is bonded on the straight edge of the hole to generate the incident wave. The excitation signal consists of a 5.5 cycle Hann-windowed tone burst of centre frequency 220 kHz, which is below the cut-off frequency for the first order Lamb wave modes (SH1). Two-dimensional fast Fourier transformation (2D FFT) is applied to the incident and scattered wave field along radial lines emanating from the crack mouth, so as to identify the wave modes and determine their angular variation and amplitude. It is shown experimentally and computationally that mid-plane symmetric edge waves can travel around the hole's edge to detect a hidden crack. Furthermore, the scattered wave field due to a small crack length, a , (compared to the wavelength λ of the incident wave) is shown to be equivalent to a point source consisting of a particular combination of body-force doublets. It is found that the amplitude of the scattered field increases quadratically as a function of a/λ , whereas the scattered wave pattern is independent of crack length for small cracks a < λ . This study of the forward scattering problem from a known crack size provides a useful guide for the inverse problem of hidden crack detection and sizing.

Geophysical Investigations at Hidden Dam, Raymond, California Flow Simulations

USGS Publications Warehouse

Minsley, Burke J.; Ikard, Scott

2010-01-01

Numerical flow modeling and analysis of observation-well data at Hidden Dam are carried out to supplement recent geophysical field investigations at the site (Minsley and others, 2010). This work also is complementary to earlier seepage-related studies at Hidden Dam documented by Cedergren (1980a, b). Known seepage areas on the northwest right abutment area of the downstream side of the dam was documented by Cedergren (1980a, b). Subsequent to the 1980 seepage study, a drainage blanket with a sub-drain system was installed to mitigate downstream seepage. Flow net analysis provided by Cedergren (1980a, b) suggests that the primary seepage mechanism involves flow through the dam foundation due to normal reservoir pool elevations, which results in upflow that intersects the ground surface in several areas on the downstream side of the dam. In addition to the reservoir pool elevations and downstream surface topography, flow is also controlled by the existing foundation geology as well as the presence or absence of a horizontal drain in the downstream portion of the dam. The current modeling study is aimed at quantifying how variability in dam and foundation hydrologic properties influences seepage as a function of reservoir stage. Flow modeling is implemented using the COMSOL Multiphysics software package, which solves the partially saturated flow equations in a two-dimensional (2D) cross-section of Hidden Dam that also incorporates true downstream topography. Use of the COMSOL software package provides a more quantitative approach than the flow net analysis by Cedergren (1980a, b), and allows for rapid evaluation of the influence of various parameters such as reservoir level, dam structure and geometry, and hydrogeologic properties of the dam and foundation materials. Historical observation-well data are used to help validate the flow simulations by comparing observed and predicted water levels for a range of reservoir elevations. The flow models are guided by, and discussed in the context of, the geophysical work (Minsley and others, 2010) where appropriate.

SA-Search: a web tool for protein structure mining based on a Structural Alphabet

PubMed Central

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-01-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search. PMID:15215446

SA-Search: a web tool for protein structure mining based on a Structural Alphabet.

PubMed

Guyon, Frédéric; Camproux, Anne-Claude; Hochez, Joëlle; Tufféry, Pierre

2004-07-01

SA-Search is a web tool that can be used to mine for protein structures and extract structural similarities. It is based on a hidden Markov model derived Structural Alphabet (SA) that allows the compression of three-dimensional (3D) protein conformations into a one-dimensional (1D) representation using a limited number of prototype conformations. Using such a representation, classical methods developed for amino acid sequences can be employed. Currently, SA-Search permits the performance of fast 3D similarity searches such as the extraction of exact words using a suffix tree approach, and the search for fuzzy words viewed as a simple 1D sequence alignment problem. SA-Search is available at http://bioserv.rpbs.jussieu.fr/cgi-bin/SA-Search.

Real-Time Adaptive Color Segmentation by Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2004-01-01

Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural network and algorithm is that each update of synaptic weights takes place in conjunction with the addition of another hidden unit, which then remains in place as still other hidden units are added on subsequent iterations. For a given training pattern, the synaptic weight between (1) the inputs and the previously added hidden units and (2) the newly added hidden unit is updated by an amount proportional to the partial derivative of a quadratic error function with respect to the synaptic weight. The synaptic weight between the newly added hidden unit and each output unit is given by a more complex function that involves the errors between the outputs and their target values, the transfer functions (hyperbolic tangents) of the neural units, and the derivatives of the transfer functions.

Repair, Evaluation, Maintenance, and Rehabilitation Research Program. Inspection of the Engineering Condition of Underwater Concrete Structures.

DTIC Science & Technology

1989-04-01

corrosion of rebar Spalling of concrete surface IIl Detect hidden and beginning Location of rebar damage Beginning corrosion of rebar ...honeycombs MD Moderate defects: spalling of concrete minor corrosion of exposed rebar rust stains along rebar with or without visible cracking softening of...velocity. . Replenishment of the attacking chemical hgents. h. Higher temperatures. i. Corrosion of reinforcing steel. 46. Note that concrete which

Data Stream Mining

NASA Astrophysics Data System (ADS)

Gaber, Mohamed Medhat; Zaslavsky, Arkady; Krishnaswamy, Shonali

Data mining is concerned with the process of computationally extracting hidden knowledge structures represented in models and patterns from large data repositories. It is an interdisciplinary field of study that has its roots in databases, statistics, machine learning, and data visualization. Data mining has emerged as a direct outcome of the data explosion that resulted from the success in database and data warehousing technologies over the past two decades (Fayyad, 1997,Fayyad, 1998,Kantardzic, 2003).

Communication: Studies of the Lennard-Jones fluid in 2, 3, and 4 dimensions highlight the need for a liquid-state 1/d expansion.

PubMed

Costigliola, Lorenzo; Schrøder, Thomas B; Dyre, Jeppe C

2016-06-21

The recent theoretical prediction by Maimbourg and Kurchan [e-print arXiv:1603.05023 (2016)] that for regular pair-potential systems the virial potential-energy correlation coefficient increases towards unity as the dimension d goes to infinity is investigated for the standard 12-6 Lennard-Jones fluid. This is done by computer simulations for d = 2, 3, 4 going from the critical point along the critical isotherm/isochore to higher density/temperature. In both cases the virial potential-energy correlation coefficient increases significantly. For a given density and temperature relative to the critical point, with increasing number of dimension the Lennard-Jones system conforms better to the hidden-scale-invariance property characterized by high virial potential-energy correlations (a property that leads to the existence of isomorphs in the thermodynamic phase diagram, implying that it becomes effectively one-dimensional in regard to structure and dynamics). The present paper also gives the first numerical demonstration of isomorph invariance of structure and dynamics in four dimensions. Our findings emphasize the need for a universally applicable 1/d expansion in liquid-state theory; we conjecture that the systems known to obey hidden scale invariance in three dimensions are those for which the yet-to-be-developed 1/d expansion converges rapidly.

DYNA3D, INGRID, and TAURUS: an integrated, interactive software system for crashworthiness engineering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benson, D.J.; Hallquist, J.O.; Stillman, D.W.

1985-04-01

Crashworthiness engineering has always been a high priority at Lawrence Livermore National Laboratory because of its role in the safe transport of radioactive material for the nuclear power industry and military. As a result, the authors have developed an integrated, interactive set of finite element programs for crashworthiness analysis. The heart of the system is DYNA3D, an explicit, fully vectorized, large deformation structural dynamics code. DYNA3D has the following four capabilities that are critical for the efficient and accurate analysis of crashes: (1) fully nonlinear solid, shell, and beam elements for representing a structure, (2) a broad range of constitutivemore » models for representing the materials, (3) sophisticated contact algorithms for the impact interactions, and (4) a rigid body capability to represent the bodies away from the impact zones at a greatly reduced cost without sacrificing any accuracy in the momentum calculations. To generate the large and complex data files for DYNA3D, INGRID, a general purpose mesh generator, is used. It runs on everything from IBM PCs to CRAYS, and can generate 1000 nodes/minute on a PC. With its efficient hidden line algorithms and many options for specifying geometry, INGRID also doubles as a geometric modeller. TAURUS, an interactive post processor, is used to display DYNA3D output. In addition to the standard monochrome hidden line display, time history plotting, and contouring, TAURUS generates interactive color displays on 8 color video screens by plotting color bands superimposed on the mesh which indicate the value of the state variables. For higher quality color output, graphic output files may be sent to the DICOMED film recorders. We have found that color is every bit as important as hidden line removal in aiding the analyst in understanding his results. In this paper the basic methodologies of the programs are presented along with several crashworthiness calculations.« less

Assessing population genetic structure via the maximisation of genetic distance

PubMed Central

2009-01-01

Background The inference of the hidden structure of a population is an essential issue in population genetics. Recently, several methods have been proposed to infer population structure in population genetics. Methods In this study, a new method to infer the number of clusters and to assign individuals to the inferred populations is proposed. This approach does not make any assumption on Hardy-Weinberg and linkage equilibrium. The implemented criterion is the maximisation (via a simulated annealing algorithm) of the averaged genetic distance between a predefined number of clusters. The performance of this method is compared with two Bayesian approaches: STRUCTURE and BAPS, using simulated data and also a real human data set. Results The simulations show that with a reduced number of markers, BAPS overestimates the number of clusters and presents a reduced proportion of correct groupings. The accuracy of the new method is approximately the same as for STRUCTURE. Also, in Hardy-Weinberg and linkage disequilibrium cases, BAPS performs incorrectly. In these situations, STRUCTURE and the new method show an equivalent behaviour with respect to the number of inferred clusters, although the proportion of correct groupings is slightly better with the new method. Re-establishing equilibrium with the randomisation procedures improves the precision of the Bayesian approaches. All methods have a good precision for FST ≥ 0.03, but only STRUCTURE estimates the correct number of clusters for FST as low as 0.01. In situations with a high number of clusters or a more complex population structure, MGD performs better than STRUCTURE and BAPS. The results for a human data set analysed with the new method are congruent with the geographical regions previously found. Conclusion This new method used to infer the hidden structure in a population, based on the maximisation of the genetic distance and not taking into consideration any assumption about Hardy-Weinberg and linkage equilibrium, performs well under different simulated scenarios and with real data. Therefore, it could be a useful tool to determine genetically homogeneous groups, especially in those situations where the number of clusters is high, with complex population structure and where Hardy-Weinberg and/or linkage equilibrium are present. PMID:19900278

Combining 3D seismic tomography and ground-penetrating radar to reveal the structure of a megalithic burial tomb

NASA Astrophysics Data System (ADS)

Mendes, Manuela; Caldeira, Bento; Borges, José

2017-04-01

This work describes a case study concerning a prehistoric buried tomb (around 3000 years B.C.) located near Évora (Portugal). This monument is a tomb completely buried with only five visible irregular small stones distributed in a circle of 3 meter in diameter. A multi-approach combining 3D seismic tomography and ground-penetrating radar (GPR) have been applied to identify hidden elements and arrangement of the stones, required prior to any excavation work. The methodology for the 3D seismic data acquisition involves a total of 24 shots recorded by four lines, with twelve fixed receivers each one. For the GPR survey was used a 400 MHz antenna which moves along parallel lines with 50 cm separation, over a 30x30 m2 area that contains the buried tomb; the GPR unit was configured to a horizontal rate of 50 scans per meter (1024 samples/scan) and a time window of 60 ns. This multi-approach procedure allowed defining: (i) the housing of the tomb in the basement structure; (ii) the presence of a hidden corridor; (iii) the description of the internal structure of the walls of the tomb; (iv) the state of preservation of the monument. Acknowledgements: This work is co-financed by the European Union through the European Regional Development Fund under COMPETE 2020 (Operational Program for Competitiveness and Internationalization) through the ICT project (UID / GEO / 04683/2013) under the reference POCI-01-0145 -FEDER-007690.

Mechanics without mechanisms

NASA Astrophysics Data System (ADS)

Eisenthal, Joshua

2018-05-01

At the time of Heinrich Hertz's premature death in 1894, he was regarded as one of the leading scientists of his generation. However, the posthumous publication of his treatise in the foundations of physics, Principles of Mechanics, presents a curious historical situation. Although Hertz's book was widely praised and admired, it was also met with a general sense of dissatisfaction. Almost all of Hertz's contemporaries criticized Principles for the lack of any plausible way to construct a mechanism from the "hidden masses" that are particularly characteristic of Hertz's framework. This issue seemed especially glaring given the expectation that Hertz's work might lead to a model of the underlying workings of the ether. In this paper I seek an explanation for why Hertz seemed so unperturbed by the difficulties of constructing such a mechanism. In arriving at this explanation, I explore how the development of Hertz's image-theory of representation framed the project of Principles. The image-theory brings with it an austere view of the "essential content" of mechanics, only requiring a kind of structural isomorphism between symbolic representations and target phenomena. I argue that bringing this into view makes clear why Hertz felt no need to work out the kinds of mechanisms that many of his readers looked for. Furthermore, I argue that a crucial role of Hertz's hypothesis of hidden masses has been widely overlooked. Far from acting as a proposal for the underlying structure of the ether, I show that Hertz's hypothesis ruled out knowledge of such underlying structure.

Hidden amorphous phase and reentrant supercooled liquid in Pd-Ni-P metallic glasses

DOE PAGES

Lan, S.; Ren, Y.; Wei, X. Y.; ...

2017-03-17

An anomaly in differential scanning calorimetry has been reported in a number of metallic glass materials in which a broad exothermal peak was observed between the glass and crystallization temperatures. The mystery surrounding this calorimetric anomaly is epitomized by four decades long studies of Pd-Ni-P metallic glasses, arguably the best glass-forming alloys. Here we show, using a suite of in-situ experimental techniques, that Pd-Ni-P alloys have a hidden amorphous phase in the supercooled liquid region. The anomalous exothermal peak is the consequence of a polyamorphous phase transition between two supercooled liquids, involving a change in the packing of atomic clustersmore » over medium-range length scales as large as 18 Å. With further temperature increase, the alloy reenters the supercooled liquid phase which forms the room-temperature glass phase upon quenching. Finally, the outcome of this study raises a possibility to manipulate the structure and hence the stability of metallic glasses through heat-treatment.« less

Revealing Stellar Surface Structure Behind Transiting Exoplanets

NASA Astrophysics Data System (ADS)

Dravins, Dainis

2018-04-01

During exoplanet transits, successive stellar surface portions become hidden and differential spectroscopy between various transit phases provide spectra of small surface segments temporarily hidden behind the planet. Line profile changes across the stellar disk offer diagnostics for hydrodynamic modeling, while exoplanet analyses require stellar background spectra to be known along the transit path. Since even giant planets cover only a small fraction of any main-sequence star, very precise observations are required, as well as averaging over numerous spectral lines with similar parameters. Spatially resolved Fe I line profiles across stellar disks have now been retrieved for HD209458 (G0V) and HD189733A (K1V), using data from the UVES and HARPS spectrometers. Free from rotational broadening, spatially resolved profiles are narrower and deeper than in integrated starlight. During transit, the profiles shift towards longer wavelengths, illustrating both stellar rotation at the latitude of transit and the prograde orbital motion of the exoplanets. This method will soon become applicable to more stars, once additional bright exoplanet hosts have been found.

Autoantibodies against the inner aspect of erythrocyte membranes in NZB mice.

PubMed Central

Linder, E

1977-01-01

Erythrocyte autoantibodies in NZB mice react by hemagglutination methods with exposed and hidden red cell antigens. The hidden antigens can be exposed by treatment with proteolytic enzymes. By indirect immunofluorescence one antibody population can be shown to react with modified red cells. In the present study the location of the corresponding autoantigen within the membrane was studied. Mechanical or hypotonic lysis of the red cells exposed the antigen. Proteolytic digestion known to expose other erythrocyte autoantigens had no effect. The autoantigen was exposed on 'inside out' erythrocyte membrane vesicles, but not on 'right-side out' vesicles, prepared from isolated erythrocyte ghosts. Frezzing and thawing as well as mechanical disintergration of red cells liberated antigenically active material as saline-insuluble fibrillar material. The observations indicate that the autoantigen studied is located at the inner aspect of the erythrocyte membrane and suggest that it is associated with fibril-forming structural components. The observed reactivity distinguishes the described antibodies from previously identified erythrocyte autoantibodies. PMID:862240

Multi-scale chromatin state annotation using a hierarchical hidden Markov model

NASA Astrophysics Data System (ADS)

Marco, Eugenio; Meuleman, Wouter; Huang, Jialiang; Glass, Kimberly; Pinello, Luca; Wang, Jianrong; Kellis, Manolis; Yuan, Guo-Cheng

2017-04-01

Chromatin-state analysis is widely applied in the studies of development and diseases. However, existing methods operate at a single length scale, and therefore cannot distinguish large domains from isolated elements of the same type. To overcome this limitation, we present a hierarchical hidden Markov model, diHMM, to systematically annotate chromatin states at multiple length scales. We apply diHMM to analyse a public ChIP-seq data set. diHMM not only accurately captures nucleosome-level information, but identifies domain-level states that vary in nucleosome-level state composition, spatial distribution and functionality. The domain-level states recapitulate known patterns such as super-enhancers, bivalent promoters and Polycomb repressed regions, and identify additional patterns whose biological functions are not yet characterized. By integrating chromatin-state information with gene expression and Hi-C data, we identify context-dependent functions of nucleosome-level states. Thus, diHMM provides a powerful tool for investigating the role of higher-order chromatin structure in gene regulation.

Analysis of world terror networks from the reduced Google matrix of Wikipedia

NASA Astrophysics Data System (ADS)

El Zant, Samer; Frahm, Klaus M.; Jaffrès-Runser, Katia; Shepelyansky, Dima L.

2018-01-01

We apply the reduced Google matrix method to analyze interactions between 95 terrorist groups and determine their relationships and influence on 64 world countries. This is done on the basis of the Google matrix of the English Wikipedia (2017) composed of 5 416 537 articles which accumulate a great part of global human knowledge. The reduced Google matrix takes into account the direct and hidden links between a selection of 159 nodes (articles) appearing due to all paths of a random surfer moving over the whole network. As a result we obtain the network structure of terrorist groups and their relations with selected countries including hidden indirect links. Using the sensitivity of PageRank to a weight variation of specific links we determine the geopolitical sensitivity and influence of specific terrorist groups on world countries. The world maps of the sensitivity of various countries to influence of specific terrorist groups are obtained. We argue that this approach can find useful application for more extensive and detailed data bases analysis.

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.

PubMed

Yamazaki, Keisuke

2012-07-01

Parametric models for sequential data, such as hidden Markov models, stochastic context-free grammars, and linear dynamical systems, are widely used in time-series analysis and structural data analysis. Computation of the likelihood function is one of primary considerations in many learning methods. Iterative calculation of the likelihood such as the model selection is still time-consuming though there are effective algorithms based on dynamic programming. The present paper studies parameter learning in a simplified feature space to reduce the computational cost. Simplifying data is a common technique seen in feature selection and dimension reduction though an oversimplified space causes adverse learning results. Therefore, we mathematically investigate a condition of the feature map to have an asymptotically equivalent convergence point of estimated parameters, referred to as the vicarious map. As a demonstration to find vicarious maps, we consider the feature space, which limits the length of data, and derive a necessary length for parameter learning in hidden Markov models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using Bayesian Nonparametric Hidden Semi-Markov Models to Disentangle Affect Processes during Marital Interaction

PubMed Central

Griffin, William A.; Li, Xun

2016-01-01

Sequential affect dynamics generated during the interaction of intimate dyads, such as married couples, are associated with a cascade of effects—some good and some bad—on each partner, close family members, and other social contacts. Although the effects are well documented, the probabilistic structures associated with micro-social processes connected to the varied outcomes remain enigmatic. Using extant data we developed a method of classifying and subsequently generating couple dynamics using a Hierarchical Dirichlet Process Hidden semi-Markov Model (HDP-HSMM). Our findings indicate that several key aspects of existing models of marital interaction are inadequate: affect state emissions and their durations, along with the expected variability differences between distressed and nondistressed couples are present but highly nuanced; and most surprisingly, heterogeneity among highly satisfied couples necessitate that they be divided into subgroups. We review how this unsupervised learning technique generates plausible dyadic sequences that are sensitive to relationship quality and provide a natural mechanism for computational models of behavioral and affective micro-social processes. PMID:27187319

Data Envelopment Analysis for steel production with the use of Total Material Requirement

NASA Astrophysics Data System (ADS)

Oyaizu, Akira; Cravioto, Jordi; Yamasue, Eiji; Daigo, Ichiro

2018-06-01

High properties of stainless steels can be achieved by adding alloying elements and/or by structure control through complex heat treatments. Evaluations of such processes have so far been made in terms of the carbon dioxide emissions emitted or the energy consumption, but less attention has been given to resource intensity and "hidden flows". Using Data Envelopment Analysis (DEA), this study evaluates the efficiency of the environmental impact, characterised through Total Material Requirement (TMR), a measurement of hidden flows, and three properties (two mechanical and one chemical) of the materials obtained after manufacturing. Out of sample of 72 stainless steels it was found that seven (SUS312L, SUS836L, SUS447J1, SUSXM27, SUS410, SUS420F2, and SUS329J4L) showed the highest comparative efficiency, and that, when classifying the sample into four groups, the production of martensitic steels showed the highest efficiency (88%), followed by ferritic and duplex (82.6% each) and lastly austenitic (43.3%).

The importance of situation-specific encodings: analysis of a simple connectionist model of letter transposition effects

NASA Astrophysics Data System (ADS)

Fang, Shin-Yi; Smith, Garrett; Tabor, Whitney

2018-04-01

This paper analyses a three-layer connectionist network that solves a translation-invariance problem, offering a novel explanation for transposed letter effects in word reading. Analysis of the hidden unit encodings provides insight into two central issues in cognitive science: (1) What is the novelty of claims of "modality-specific" encodings? and (2) How can a learning system establish a complex internal structure needed to solve a problem? Although these topics (embodied cognition and learnability) are often treated separately, we find a close relationship between them: modality-specific features help the network discover an abstract encoding by causing it to break the initial symmetries of the hidden units in an effective way. While this neural model is extremely simple compared to the human brain, our results suggest that neural networks need not be black boxes and that carefully examining their encoding behaviours may reveal how they differ from classical ideas about the mind-world relationship.

Cross-modal learning to rank via latent joint representation.

PubMed

Wu, Fei; Jiang, Xinyang; Li, Xi; Tang, Siliang; Lu, Weiming; Zhang, Zhongfei; Zhuang, Yueting

2015-05-01

Cross-modal ranking is a research topic that is imperative to many applications involving multimodal data. Discovering a joint representation for multimodal data and learning a ranking function are essential in order to boost the cross-media retrieval (i.e., image-query-text or text-query-image). In this paper, we propose an approach to discover the latent joint representation of pairs of multimodal data (e.g., pairs of an image query and a text document) via a conditional random field and structural learning in a listwise ranking manner. We call this approach cross-modal learning to rank via latent joint representation (CML²R). In CML²R, the correlations between multimodal data are captured in terms of their sharing hidden variables (e.g., topics), and a hidden-topic-driven discriminative ranking function is learned in a listwise ranking manner. The experiments show that the proposed approach achieves a good performance in cross-media retrieval and meanwhile has the capability to learn the discriminative representation of multimodal data.

Identifying influential user communities on the social network

NASA Astrophysics Data System (ADS)

Hu, Weishu; Gong, Zhiguo; Hou U, Leong; Guo, Jingzhi

2015-10-01

Nowadays social network services have been popularly used in electronic commerce systems. Users on the social network can develop different relationships based on their common interests and activities. In order to promote the business, it is interesting to explore hidden relationships among users developed on the social network. Such knowledge can be used to locate target users for different advertisements and to provide effective product recommendations. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a data set from Epinions, which demonstrates that our method achieves 4-11.8% accuracy improvement over the state-of-the-art method.

Behavioral and Temporal Pattern Detection Within Financial Data With Hidden Information

DTIC Science & Technology

2012-02-01

probabilistic pattern detector to monitor the pattern. 15. SUBJECT TERMS Runtime verification, Hidden data, Hidden Markov models, Formal specifications...sequences in many other fields besides financial systems [L, TV, LC, LZ ]. Rather, the technique suggested in this paper is positioned as a hybrid...operation of the pattern detector . Section 7 describes the operation of the probabilistic pattern-matching monitor, and section 8 describes three

Image Steganography for Hidden Communication

DTIC Science & Technology

2000-04-01

ARMY RESEARCH LABORATORY Image Steganography for Hidden Communication by Lisa M. Marvel sx:8 lÄPSilll msmmmmsi IH :’:-:’X^:-:-:-:o-x...2000 Image Steganography for Hidden Communication Lisa M. Marvel Information Science and Technology Directorate, ARL Approved for public release...Capacity for Image Steganography 14 3.4 Summary 1’ 4. Spread Spectrum Image Steganography (SSIS) 19 4.1 Modulation 21 4.1.1 Sign-Detector System

2015 Cataloging Hidden Special Collections and Archives Unconference and Symposium: Innovation, Collaboration, and Models. Proceedings of the CLIR Cataloging Hidden Special Collections and Archives Symposium (Philadelphia, Pennsylvania, March 12-13, 2015)

ERIC Educational Resources Information Center

Oestreicher, Cheryl, Ed.

2015-01-01

The 2015 CLIR Unconference & Symposium was the capstone event to seven years of grant funding through CLIR's Cataloging Hidden Special Collections and Archives program. These proceedings group presentations by theme. Collaborations provides examples of multi-institutional projects, including one international collaboration; Student and Faculty…

Hidden Statistics of Schroedinger Equation

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

Work was carried out in determination of the mathematical origin of randomness in quantum mechanics and creating a hidden statistics of Schr dinger equation; i.e., to expose the transitional stochastic process as a "bridge" to the quantum world. The governing equations of hidden statistics would preserve such properties of quantum physics as superposition, entanglement, and direct-product decomposability while allowing one to measure its state variables using classical methods.

The Hidden Messages of Secondary Reading Programs: What Students Learn vs. What Teachers Teach.

ERIC Educational Resources Information Center

Battraw, Judith L.

Hidden messages are part of the culture of reading at any school, particularly at the secondary level. In many schools, the overt message that reading is essential to success on state-mandated tests and in society is jeopardized due to hidden messages about the nature of the reading process and the place of reading in everyday life. A qualitative…

[Becoming doctor: Highlight the hidden curriculum. Medical error as an example].

PubMed

Galam, Eric

2014-04-01

Medical culture is both individual and collective. It is also implicit, hidden (hidden curriculum) and binding.It spreads and builds from the beginning of the training.It strongly impacts the personalities and professional care practices. Awareness of its existence and identification of its main lines are the first steps for fruitful research. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Online Farsi digit recognition using their upper half structure

NASA Astrophysics Data System (ADS)

Ghods, Vahid; Sohrabi, Mohammad Karim

2015-03-01

In this paper, we investigated the efficiency of upper half Farsi numerical digit structure. In other words, half of data (upper half of the digit shapes) was exploited for the recognition of Farsi numerical digits. This method can be used for both offline and online recognition. Half of data is more effective in speed process, data transfer and in this application accuracy. Hidden Markov model (HMM) was used to classify online Farsi digits. Evaluation was performed by TMU dataset. This dataset contains more than 1200 samples of online handwritten Farsi digits. The proposed method yielded more accuracy in recognition rate.

Modeling online social signed networks

NASA Astrophysics Data System (ADS)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

Gauge mediation scenario with hidden sector renormalization in MSSM

NASA Astrophysics Data System (ADS)

Arai, Masato; Kawai, Shinsuke; Okada, Nobuchika

2010-02-01

We study the hidden sector effects on the mass renormalization of a simplest gauge-mediated supersymmetry breaking scenario. We point out that possible hidden sector contributions render the soft scalar masses smaller, resulting in drastically different sparticle mass spectrum at low energy. In particular, in the 5+5¯ minimal gauge-mediated supersymmetry breaking with high messenger scale (that is favored by the gravitino cold dark matter scenario), we show that a stau can be the next lightest superparticle for moderate values of hidden sector self-coupling. This provides a very simple theoretical model of long-lived charged next lightest superparticles, which imply distinctive signals in ongoing and upcoming collider experiments.

Resonant conversions of QCD axions into hidden axions and suppressed isocurvature perturbations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kitajima, Naoya; Takahashi, Fuminobu, E-mail: kitajima@tuhep.phys.tohoku.ac.jp, E-mail: fumi@tuhep.phys.tohoku.ac.jp

2015-01-01

We study in detail MSW-like resonant conversions of QCD axions into hidden axions, including cases where the adiabaticity condition is only marginally satisfied, and where anharmonic effects are non-negligible. When the resonant conversion is efficient, the QCD axion abundance is suppressed by the hidden and QCD axion mass ratio. We find that, when the resonant conversion is incomplete due to a weak violation of the adiabaticity, the CDM isocurvature perturbations can be significantly suppressed, while non-Gaussianity of the isocurvature perturbations generically remain unsuppressed. The isocurvature bounds on the inflation scale can therefore be relaxed by the partial resonant conversion ofmore » the QCD axions into hidden axions.« less

Hidden Genetic Variation in LCA9-Associated Congenital Blindness Explained by 5'UTR Mutations and Copy-Number Variations of NMNAT1.

PubMed

Coppieters, Frauke; Todeschini, Anne Laure; Fujimaki, Takuro; Baert, Annelot; De Bruyne, Marieke; Van Cauwenbergh, Caroline; Verdin, Hannah; Bauwens, Miriam; Ongenaert, Maté; Kondo, Mineo; Meire, Françoise; Murakami, Akira; Veitia, Reiner A; Leroy, Bart P; De Baere, Elfride

2015-12-01

Leber congenital amaurosis (LCA) is a severe autosomal-recessive retinal dystrophy leading to congenital blindness. A recently identified LCA gene is NMNAT1, located in the LCA9 locus. Although most mutations in blindness genes are coding variations, there is accumulating evidence for hidden noncoding defects or structural variations (SVs). The starting point of this study was an LCA9-associated consanguineous family in which no coding mutations were found in the LCA9 region. Exploring the untranslated regions of NMNAT1 revealed a novel homozygous 5'UTR variant, c.-70A>T. Moreover, an adjacent 5'UTR variant, c.-69C>T, was identified in a second consanguineous family displaying a similar phenotype. Both 5'UTR variants resulted in decreased NMNAT1 mRNA abundance in patients' lymphocytes, and caused decreased luciferase activity in human retinal pigment epithelial RPE-1 cells. Second, we unraveled pseudohomozygosity of a coding NMNAT1 mutation in two unrelated LCA patients by the identification of two distinct heterozygous partial NMNAT1 deletions. Molecular characterization of the breakpoint junctions revealed a complex Alu-rich genomic architecture. Our study uncovered hidden genetic variation in NMNAT1-associated LCA and emphasized a shift from coding to noncoding regulatory mutations and repeat-mediated SVs in the molecular pathogenesis of heterogeneous recessive disorders such as hereditary blindness. © 2015 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

DOE PAGES

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-24

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

A TWO-STATE MIXED HIDDEN MARKOV MODEL FOR RISKY TEENAGE DRIVING BEHAVIOR

PubMed Central

Jackson, John C.; Albert, Paul S.; Zhang, Zhiwei

2016-01-01

This paper proposes a joint model for longitudinal binary and count outcomes. We apply the model to a unique longitudinal study of teen driving where risky driving behavior and the occurrence of crashes or near crashes are measured prospectively over the first 18 months of licensure. Of scientific interest is relating the two processes and predicting crash and near crash outcomes. We propose a two-state mixed hidden Markov model whereby the hidden state characterizes the mean for the joint longitudinal crash/near crash outcomes and elevated g-force events which are a proxy for risky driving. Heterogeneity is introduced in both the conditional model for the count outcomes and the hidden process using a shared random effect. An estimation procedure is presented using the forward–backward algorithm along with adaptive Gaussian quadrature to perform numerical integration. The estimation procedure readily yields hidden state probabilities as well as providing for a broad class of predictors. PMID:27766124

Characteristics of Hidden Status Among Users of Crack, Powder Cocaine, and Heroin in Central Harlem

PubMed Central

Davis, W. Rees; Johnson, Bruce D.; Liberty, Hilary James; Randolph, Doris D.

2007-01-01

This article analyzes hidden status among crack, powder cocaine, and heroin users and setters, in contrast to more accessible users/sellers. Several sampling strategies acquired 657 users (N=559) and sellers (N=98). Indicators of hidden status were those who (1) paid rent in full in the last 30 days, (2) used nonstreet drug procurement. (3) had legal jobs, and (4) earned $1,000 or more in legal income in the last 30 days. Nearly half had at least one indicator: approximately 16% of users/sellers had two to four indicators. In logistic regression analyses, those who had not panhandled in the last 30 days, those who had used powder cocaine in the last 30 days, and those never arrested were the most likely to have hidden status, whether the analysis predicted those having any indicators or those having two to four indicators. The four indicators begin to operationally define hidden status among users of cocaine and heroin. PMID:17710217

Clustering coefficients of protein-protein interaction networks

NASA Astrophysics Data System (ADS)

Miller, Gerald A.; Shi, Yi Y.; Qian, Hong; Bomsztyk, Karol

2007-05-01

The properties of certain networks are determined by hidden variables that are not explicitly measured. The conditional probability (propagator) that a vertex with a given value of the hidden variable is connected to k other vertices determines all measurable properties. We study hidden variable models and find an averaging approximation that enables us to obtain a general analytical result for the propagator. Analytic results showing the validity of the approximation are obtained. We apply hidden variable models to protein-protein interaction networks (PINs) in which the hidden variable is the association free energy, determined by distributions that depend on biochemistry and evolution. We compute degree distributions as well as clustering coefficients of several PINs of different species; good agreement with measured data is obtained. For the human interactome two different parameter sets give the same degree distributions, but the computed clustering coefficients differ by a factor of about 2. This shows that degree distributions are not sufficient to determine the properties of PINs.

Singlet scalar top partners from accidental supersymmetry

NASA Astrophysics Data System (ADS)

Cheng, Hsin-Chia; Li, Lingfeng; Salvioni, Ennio; Verhaaren, Christopher B.

2018-05-01

We present a model wherein the Higgs mass is protected from the quadratic one-loop top quark corrections by scalar particles that are complete singlets under the Standard Model (SM) gauge group. While bearing some similarity to Folded Supersymmetry, the construction is purely four dimensional and enjoys more parametric freedom, allowing electroweak symmetry breaking to occur easily. The cancelation of the top loop quadratic divergence is ensured by a Z 3 symmetry that relates the SM top sector and two hidden top sectors, each charged under its own hidden color group. In addition to the singlet scalars, the hidden sectors contain electroweak-charged supermultiplets below the TeV scale, which provide the main access to this model at colliders. The phenomenology presents both differences and similarities with respect to other realizations of neutral naturalness. Generally, the glueballs of hidden color have longer decay lengths. The production of hidden sector particles results in quirk or squirk bound states, which later annihilate. We survey the possible signatures and corresponding experimental constraints.

Hidden Sector Dark Matter and the Galactic Center Gamma-Ray Excess: A Closer Look

DOE Office of Scientific and Technical Information (OSTI.GOV)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-09-20

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

NASA Astrophysics Data System (ADS)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-01

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case, we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

DOE Office of Scientific and Technical Information (OSTI.GOV)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Single-hidden-layer feed-forward quantum neural network based on Grover learning.

PubMed

Liu, Cheng-Yi; Chen, Chein; Chang, Ching-Ter; Shih, Lun-Min

2013-09-01

In this paper, a novel single-hidden-layer feed-forward quantum neural network model is proposed based on some concepts and principles in the quantum theory. By combining the quantum mechanism with the feed-forward neural network, we defined quantum hidden neurons and connected quantum weights, and used them as the fundamental information processing unit in a single-hidden-layer feed-forward neural network. The quantum neurons make a wide range of nonlinear functions serve as the activation functions in the hidden layer of the network, and the Grover searching algorithm outstands the optimal parameter setting iteratively and thus makes very efficient neural network learning possible. The quantum neuron and weights, along with a Grover searching algorithm based learning, result in a novel and efficient neural network characteristic of reduced network, high efficient training and prospect application in future. Some simulations are taken to investigate the performance of the proposed quantum network and the result show that it can achieve accurate learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chimpanzees (Pan troglodytes) use markers to monitor the movement of a hidden item.

PubMed

Beran, Michael J; Beran, Mary M; Menzel, Charles R

2005-10-01

Four chimpanzees (Pan troglodytes) monitored the movement of hidden items in arrays of opaque cups. A chocolate candy was hidden in an array of four cups and temporarily presented paper markers indicated the location of the candy (which otherwise was not visible). These markers were either non-symbolic or symbolic (lexigram) stimuli that in other contexts acted as a label for the hidden candy, and the array was either rotated 180 degrees after the marker was removed or the array remained in the same location. For three of four chimpanzees, performance was better than chance in all conditions and there was no effect of the type of marker. These experiments indicate that chimpanzees can track the movement of a hidden item in an array of identical cups even when they never see the item itself, but only see a temporarily presented marker for the location of that item. However, there was no benefit to the use of symbolic as opposed to non-symbolic stimuli in this performance.

A two particle hidden sector and the oscillations with photons

NASA Astrophysics Data System (ADS)

Alvarez, Pedro D.; Arias, Paola; Maldonado, Carlos

2018-01-01

We present a detailed study of the oscillations and optical properties for vacuum, in a model for the dark sector that contains axion-like particles and hidden photons. We provide bounds for the couplings versus the mass, using current results from ALPS-I and PVLAS. We also discuss the challenges for the detection of models with more than one hidden particle in light shining trough wall-like experiments.

Hidden symmetries of Eisenhart-Duval lift metrics and the Dirac equation with flux

NASA Astrophysics Data System (ADS)

Cariglia, Marco

2012-10-01

The Eisenhart-Duval lift allows embedding nonrelativistic theories into a Lorentzian geometrical setting. In this paper we study the lift from the point of view of the Dirac equation and its hidden symmetries. We show that dimensional reduction of the Dirac equation for the Eisenhart-Duval metric in general gives rise to the nonrelativistic Lévy-Leblond equation in lower dimension. We study in detail in which specific cases the lower dimensional limit is given by the Dirac equation, with scalar and vector flux, and the relation between lift, reduction, and the hidden symmetries of the Dirac equation. While there is a precise correspondence in the case of the lower dimensional massive Dirac equation with no flux, we find that for generic fluxes it is not possible to lift or reduce all solutions and hidden symmetries. As a by-product of this analysis, we construct new Lorentzian metrics with special tensors by lifting Killing-Yano and closed conformal Killing-Yano tensors and describe the general conformal Killing-Yano tensor of the Eisenhart-Duval lift metrics in terms of lower dimensional forms. Last, we show how, by dimensionally reducing the higher dimensional operators of the massless Dirac equation that are associated with shared hidden symmetries, it is possible to recover hidden symmetry operators for the Dirac equation with flux.

A market on both "sides" of the law: The use of the hidden web for the sale of new psychoactive substances.

PubMed

Wadsworth, Elle; Drummond, Colin; Kimergård, Andreas; Deluca, Paolo

2017-05-01

The hidden Web is used for the anonymous sale of drugs, and with the UK Psychoactive Substances Act, 2016, implemented on May 26th 2016; it could increase as a platform for obtaining new psychoactive substances (NPS). This study aims to describe the NPS market on the visible and hidden Web preban, and assess whether the hidden Web is a likely place for the sale of NPS postban. Data collection of 113 online shops took place in October 2015. Data collection of 22 cryptomarkets took place every 2 months from October 2015 to 2016 as part of the CASSANDRA project. All online shops with a UK domain location sold NPS that were uncontrolled by the UK Misuse of Drugs Act, 1971, and closed after the ban. Of the cryptomarkets analysed, the total number of vendors selling NPS, number of substances, and listings advertised, all increased over the year. The majority of the NPS advertised on the hidden Web were phenethylamines and cathinones, yet the majority of uncontrolled NPS were synthetic cannabinoids. Vendors selling and availability of NPS increased over the 12 months of data collection. Potential displacement from the visible Web to hidden Web should be taken into consideration. Copyright © 2017 John Wiley & Sons, Ltd.

Hidden treasures - 50 km points of interests

NASA Astrophysics Data System (ADS)

Lommi, Matias; Kortelainen, Jaana

2015-04-01

Tampere is third largest city in Finland and a regional centre. During 70's there occurred several communal mergers. Nowadays this local area has both strong and diversed identity - from wilderness and agricultural fields to high density city living. Outside the city center there are interesting geological points unknown for modern city settlers. There is even a local proverb, "Go abroad to Teisko!". That is the area the Hidden Treasures -student project is focused on. Our school Tammerkoski Upper Secondary School (or Gymnasium) has emphasis on visual arts. We are going to offer our art students scientific and artistic experiences and knowledge about the hidden treasures of Teisko area and involve the Teisko inhabitants into this project. Hidden treasures - Precambrian subduction zone and a volcanism belt with dense bed of gold (Au) and arsenic (As), operating goldmines and quarries of minerals and metamorphic slates. - North of subduction zone a homogenic precambrian magmastone area with quarries, products known as Kuru Grey. - Former ashores of post-glasial Lake Näsijärvi and it's sediments enabled the developing agriculture and sustained settlement. Nowadays these ashores have both scenery and biodiversity values. - Old cattle sheds and dairy buildings made of local granite stones related to cultural stonebuilding inheritance. - Local active community of Kapee, about 100 inhabitants. Students will discover information of these "hidden" phenomena, and rendering this information trough Enviromental Art Method. Final form of this project will be published in several artistic and informative geocaches. These caches are achieved by a GPS-based special Hidden Treasures Cycling Route and by a website guiding people to find these hidden points of interests.

Hidden in plain sight: the formal, informal, and hidden curricula of a psychiatry clerkship.

PubMed

Wear, Delese; Skillicorn, Jodie

2009-04-01

To examine perceptions of the formal, informal, and hidden curricula in psychiatry as they are observed and experienced by (1) attending physicians who have teaching responsibilities for residents and medical students, (2) residents who are taught by those same physicians and who have teaching responsibilities for medical students, and (3) medical students who are taught by attendings and residents during their psychiatry rotation. From June to November 2007, the authors conducted focus groups with attendings, residents, and students in one midwestern academic setting. The sessions were audiotaped, transcribed, and analyzed for themes surrounding the formal, informal, and hidden curricula. All three groups offered a similar belief that the knowledge, skills, and values of the formal curriculum focused on building relationships. Similarly, all three suggested that elements of the informal and hidden curricula were expressed primarily as the values arising from attendings' role modeling, as the nature and amount of time attendings spend with patients, and as attendings' advice arising from experience and intuition versus "textbook learning." Whereas students and residents offered negative values arising from the informal and hidden curricula, attendings did not, offering instead the more positive values they intended to encourage through the informal and hidden curricula. The process described here has great potential in local settings across all disciplines. Asking teachers and learners in any setting to think about how they experience the educational environment and what sense they make of all curricular efforts can provide a reality check for educators and a values check for learners as they critically reflect on the meanings of what they are learning.

Empowering students with the hidden curriculum.

PubMed

Neve, Hilary; Collett, Tracey

2017-11-27

The hidden curriculum (HC) refers to unscripted, ad hoc learning that occurs outside the formal, taught curriculum and can have a powerful influence on the professional development of students. While this learning may be positive, it may conflict with that taught in the formal curriculum. Medical schools take a range of steps to address these negative effects; however, the existence and nature of the concept tends to be hidden from students. Since 2007, our medical school has incorporated into its small group programme an educational activity exploring the concept of the hidden curriculum. We undertook a qualitative evaluation of our intervention, conducting a thematic analysis of students' wiki reflections about the HC. We also analysed students' responses to a short questionnaire about the educational approach used. The majority of students felt that the HC session was important and relevant. Most appeared able to identify positive and negative HC experiences and consider how these might influence their learning and development, although a few students found the concept of the HC hard to grasp. Revealing and naming the hidden curriculum can make students aware of its existence and understand its potential impact. The hidden curriculum may also be a useful tool for triggering debate about issues such as power, patient centredness, personal resilience and career stereotypes in medicine. Supporting students to think critically about HC experiences may empower them to make active choices about which messages to take on board. The hidden curriculum can have a powerful influence on the professional development of students. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

On a clean power generation system with the co-gasification of biomass and coal in a quadruple fluidized bed gasifier.

PubMed

Yan, Linbo; He, Boshu

2017-07-01

A clean power generation system was built based on the steam co-gasification of biomass and coal in a quadruple fluidized bed gasifier. The chemical looping with oxygen uncoupling technology was used to supply oxygen for the calciner. The solid oxide fuel cell and the steam turbine were combined to generate power. The calcium looping and mineral carbonation were used for CO 2 capture and sequestration. The aim of this work was to study the characteristics of this system. The effects of key operation parameters on the system total energy efficiency (ŋ ten ), total exergy efficiency (ŋ tex ) and carbon sequestration rate (R cs ) were detected. The energy and exergy balance calculations were implemented and the corresponding Sankey and Grassmann diagrams were drawn. It was found that the maximum energy and exergy losses occurred in the steam turbine. The system ŋ ten and ŋ tex could be ∼50% and ∼47%, and R cs could be over unit. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a brain MRI-based hidden Markov model for dementia recognition.

PubMed

Chen, Ying; Pham, Tuan D

2013-01-01

Dementia is an age-related cognitive decline which is indicated by an early degeneration of cortical and sub-cortical structures. Characterizing those morphological changes can help to understand the disease development and contribute to disease early prediction and prevention. But modeling that can best capture brain structural variability and can be valid in both disease classification and interpretation is extremely challenging. The current study aimed to establish a computational approach for modeling the magnetic resonance imaging (MRI)-based structural complexity of the brain using the framework of hidden Markov models (HMMs) for dementia recognition. Regularity dimension and semi-variogram were used to extract structural features of the brains, and vector quantization method was applied to convert extracted feature vectors to prototype vectors. The output VQ indices were then utilized to estimate parameters for HMMs. To validate its accuracy and robustness, experiments were carried out on individuals who were characterized as non-demented and mild Alzheimer's diseased. Four HMMs were constructed based on the cohort of non-demented young, middle-aged, elder and demented elder subjects separately. Classification was carried out using a data set including both non-demented and demented individuals with a wide age range. The proposed HMMs have succeeded in recognition of individual who has mild Alzheimer's disease and achieved a better classification accuracy compared to other related works using different classifiers. Results have shown the ability of the proposed modeling for recognition of early dementia. The findings from this research will allow individual classification to support the early diagnosis and prediction of dementia. By using the brain MRI-based HMMs developed in our proposed research, it will be more efficient, robust and can be easily used by clinicians as a computer-aid tool for validating imaging bio-markers for early prediction of dementia.

Machine learning in sentiment reconstruction of the simulated stock market

NASA Astrophysics Data System (ADS)

Goykhman, Mikhail; Teimouri, Ali

2018-02-01

In this paper we continue the study of the simulated stock market framework defined by the driving sentiment processes. We focus on the market environment driven by the buy/sell trading sentiment process of the Markov chain type. We apply the methodology of the Hidden Markov Models and the Recurrent Neural Networks to reconstruct the transition probabilities matrix of the Markov sentiment process and recover the underlying sentiment states from the observed stock price behavior. We demonstrate that the Hidden Markov Model can successfully recover the transition probabilities matrix for the hidden sentiment process of the Markov Chain type. We also demonstrate that the Recurrent Neural Network can successfully recover the hidden sentiment states from the observed simulated stock price time series.

Revealing hidden antiferromagnetic correlations in doped Hubbard chains via string correlators

NASA Astrophysics Data System (ADS)

Hilker, Timon A.; Salomon, Guillaume; Grusdt, Fabian; Omran, Ahmed; Boll, Martin; Demler, Eugene; Bloch, Immanuel; Gross, Christian

2017-08-01

Topological phases, like the Haldane phase in spin-1 chains, defy characterization through local order parameters. Instead, nonlocal string order parameters can be employed to reveal their hidden order. Similar diluted magnetic correlations appear in doped one-dimensional lattice systems owing to the phenomenon of spin-charge separation. Here we report on the direct observation of such hidden magnetic correlations via quantum gas microscopy of hole-doped ultracold Fermi-Hubbard chains. The measurement of nonlocal spin-density correlation functions reveals a hidden finite-range antiferromagnetic order, a direct consequence of spin-charge separation. Our technique, which measures nonlocal order directly, can be readily extended to higher dimensions to study the complex interplay between magnetic order and density fluctuations.

Optimal no-go theorem on hidden-variable predictions of effect expectations

NASA Astrophysics Data System (ADS)

Blass, Andreas; Gurevich, Yuri

2018-03-01

No-go theorems prove that, under reasonable assumptions, classical hidden-variable theories cannot reproduce the predictions of quantum mechanics. Traditional no-go theorems proved that hidden-variable theories cannot predict correctly the values of observables. Recent expectation no-go theorems prove that hidden-variable theories cannot predict the expectations of observables. We prove the strongest expectation-focused no-go theorem to date. It is optimal in the sense that the natural weakenings of the assumptions and the natural strengthenings of the conclusion make the theorem fail. The literature on expectation no-go theorems strongly suggests that the expectation-focused approach is more general than the value-focused one. We establish that the expectation approach is not more general.

Hidden-Symmetry-Protected Topological Semimetals on a Square Lattice

NASA Astrophysics Data System (ADS)

Hou, Jing-Min

2013-09-01

We study a two-dimensional fermionic square lattice, which supports the existence of a two-dimensional Weyl semimetal, quantum anomalous Hall effect, and 2π-flux topological semimetal in different parameter ranges. We show that the band degenerate points of the two-dimensional Weyl semimetal and 2π-flux topological semimetal are protected by two distinct novel hidden symmetries, which both correspond to antiunitary composite operations. When these hidden symmetries are broken, a gap opens between the conduction and valence bands, turning the system into a insulator. With appropriate parameters, a quantum anomalous Hall effect emerges. The degenerate point at the boundary between the quantum anomalous Hall insulator and trivial band insulator is also protected by the hidden symmetry.

Hidden symmetries and Lie algebra structures from geometric and supergravity Killing spinors

NASA Astrophysics Data System (ADS)

Açık, Özgür; Ertem, Ümit

2016-08-01

We consider geometric and supergravity Killing spinors and the spinor bilinears constructed out of them. The spinor bilinears of geometric Killing spinors correspond to the antisymmetric generalizations of Killing vector fields which are called Killing-Yano forms. They constitute a Lie superalgebra structure in constant curvature spacetimes. We show that the Dirac currents of geometric Killing spinors satisfy a Lie algebra structure up to a condition on 2-form spinor bilinears. We propose that the spinor bilinears of supergravity Killing spinors give way to different generalizations of Killing vector fields to higher degree forms. It is also shown that those supergravity Killing forms constitute a Lie algebra structure in six- and ten-dimensional cases. For five- and eleven-dimensional cases, the Lie algebra structure depends on an extra condition on supergravity Killing forms.

A deep structural ridge beneath central India

NASA Astrophysics Data System (ADS)

Agrawal, P. K.; Thakur, N. K.; Negi, J. G.

A joint-inversion of magnetic satellite (MAGSAT) and free air gravity data has been conducted to quantitatively investigate the cause for Bouguer gravity anomaly over Central Indian plateaus and possible fold consequences beside Himalayan zone in the Indian sub-continent due to collision between Indian and Eurasian plates. The appropriate inversion with 40 km crustal depth model has delineated after discriminating high density and magnetisation models, for the first time, about 1500 km long hidden ridge structure trending NW-SE. The structure is parallel to Himalayan fold axis and the Indian Ocean ridge in the Arabian Sea. A quantitative relief model across a representative anomaly profile confirms the ridge structure with its highest point nearly 6 km higher than the surrounding crustal level in peninsular India. The ridge structure finds visible support from the astro-geoidal contours.

Knot soliton in DNA and geometric structure of its free-energy density.

PubMed

Wang, Ying; Shi, Xuguang

2018-03-01

In general, the geometric structure of DNA is characterized using an elastic rod model. The Landau model provides us a new theory to study the geometric structure of DNA. By using the decomposition of the arc unit in the helical axis of DNA, we find that the free-energy density of DNA is similar to the free-energy density of a two-condensate superconductor. By using the φ-mapping topological current theory, the torus knot soliton hidden in DNA is demonstrated. We show the relation between the geometric structure and free-energy density of DNA and the Frenet equations in differential geometry theory are considered. Therefore, the free-energy density of DNA can be expressed by the curvature and torsion of the helical axis.

Structural Diversification of Lyngbyatoxin A by Host-Dependent Heterologous Expression of the tleABC Biosynthetic Gene Cluster.

PubMed

Zhang, Lihan; Hoshino, Shotaro; Awakawa, Takayoshi; Wakimoto, Toshiyuki; Abe, Ikuro

2016-08-03

Natural products have enormous structural diversity, yet little is known about how such diversity is achieved in nature. Here we report the structural diversification of a cyanotoxin-lyngbyatoxin A-and its biosynthetic intermediates by heterologous expression of the Streptomyces-derived tleABC biosynthetic gene cluster in three different Streptomyces hosts: S. lividans, S. albus, and S. avermitilis. Notably, the isolated lyngbyatoxin derivatives, including four new natural products, were biosynthesized by crosstalk between the heterologous tleABC gene cluster and the endogenous host enzymes. The simple strategy described here has expanded the structural diversity of lyngbyatoxin A and its biosynthetic intermediates, and provides opportunities for investigation of the currently underestimated hidden biosynthetic crosstalk. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia

PubMed Central

Kim, Junghoe; Calhoun, Vince D.; Shim, Eunsoo; Lee, Jong-Hwan

2015-01-01

Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was quantified by using kurtosis/modularity measures and features from the higher hidden layer showed holistic/global FC patterns differentiating SZ from HC. Our proposed schemes and reported findings attained by using the DNN classifier and whole-brain FC data suggest that such approaches show improved ability to learn hidden patterns in brain imaging data, which may be useful for developing diagnostic tools for SZ and other neuropsychiatric disorders and identifying associated aberrant FC patterns. PMID:25987366

Alerts and Advisories

MedlinePlus

... Elimidrol ‘Opiate Withdrawal’ Product (FTC 09/28/17 ) Physic Candy – Define contains hidden drug ingredients ( FDA 09/11/17 ) Physic Candy – Curve contains hidden drug ingredients ( FDA 08/ ...

Rare Z boson decays to a hidden sector

DOE PAGES

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

2018-01-18

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Rare Z boson decays to a hidden sector

DOE PAGES

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

2018-01-01

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Experimental search for hidden photon CDM in the eV mass range with a dish antenna

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suzuki, J.; Horie, T.; Inoue, Y.

2015-09-15

A search for hidden photon cold dark matter (HP CDM) using a new technique with a dish antenna is reported. From the result of the measurement, we found no evidence for the existence of HP CDM and set an upper limit on the photon-HP mixing parameter χ of ∼6×10{sup −12} for the hidden photon mass m{sub γ}=3.1±1.2 eV.

Rare Z boson decays to a hidden sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blinov, Nikita; Izaguirre, Eder; Shuve, Brian

We demonstrate that rare decays of the Standard Model Z boson can be used to discover and characterize the nature of new hidden-sector particles. We propose new searches for these particles in soft, high-multiplicity leptonic final states at the Large Hadron Collider. The proposed searches are sensitive to low-mass particles produced in Z decays, and we argue that these striking signatures can shed light on the hidden-sector couplings and mechanism for mass generation.

Hidden-sector Spectroscopy with Gravitational Waves from Binary Neutron Stars

NASA Astrophysics Data System (ADS)

Croon, Djuna; Nelson, Ann E.; Sun, Chen; Walker, Devin G. E.; Xianyu, Zhong-Zhi

2018-05-01

We show that neutron star (NS) binaries can be ideal laboratories to probe hidden sectors with a long-range force. In particular, it is possible for gravitational wave (GW) detectors such as LIGO and Virgo to resolve the correction of waveforms from ultralight dark gauge bosons coupled to NSs. We observe that the interaction of the hidden sector affects both the GW frequency and amplitude in a way that cannot be fitted by pure gravity.

Veiled EGM Jackpots: The Effects of Hidden and Mystery Jackpots on Gambling Intensity.

PubMed

Donaldson, Phillip; Langham, Erika; Rockloff, Matthew J; Browne, Matthew

2016-06-01

Understanding the impact of EGM Jackpots on gambling intensity may allow targeted strategies to be implemented that facilitate harm minimisation by acting to reduce losses of gamblers who play frequently, while maintaining the enjoyment and excitement of potential jackpots. The current study investigated the influences of Hidden and Mystery Jackpots on EGM gambling intensity. In a Hidden Jackpot, the prize value is not shown to the player, although the existence of a jackpot prize is advertised. In a Mystery Jackpot, the jackpot triggering state of the machine is unknown to players. One hundred and seven volunteers (males = 49, females = 58) played a laptop-simulated EGM with a starting $20 real-money stake and a chance to win a Jackpot ($500). Participants played for either a Hidden or Known Jackpot Value, with either a Mystery or Known winning symbol combination in a crossed design. Lastly, a control condition with no jackpot was included. Gambling intensity (speed of bets, persistence) was greater when the Jackpot value was unknown, especially when a winning-symbol combination suggested that a win was possible. While there is no evidence in the present investigation to suggest that Hidden or Mystery jackpots contribute to greater player enjoyment, there is some evidence to suggest a marginal positive contribution of hidden jackpots to risky playing behaviour.

Detecting targets hidden in random forests

NASA Astrophysics Data System (ADS)

Kouritzin, Michael A.; Luo, Dandan; Newton, Fraser; Wu, Biao

2009-05-01

Military tanks, cargo or troop carriers, missile carriers or rocket launchers often hide themselves from detection in the forests. This plagues the detection problem of locating these hidden targets. An electro-optic camera mounted on a surveillance aircraft or unmanned aerial vehicle is used to capture the images of the forests with possible hidden targets, e.g., rocket launchers. We consider random forests of longitudinal and latitudinal correlations. Specifically, foliage coverage is encoded with a binary representation (i.e., foliage or no foliage), and is correlated in adjacent regions. We address the detection problem of camouflaged targets hidden in random forests by building memory into the observations. In particular, we propose an efficient algorithm to generate random forests, ground, and camouflage of hidden targets with two dimensional correlations. The observations are a sequence of snapshots consisting of foliage-obscured ground or target. Theoretically, detection is possible because there are subtle differences in the correlations of the ground and camouflage of the rocket launcher. However, these differences are well beyond human perception. To detect the presence of hidden targets automatically, we develop a Markov representation for these sequences and modify the classical filtering equations to allow the Markov chain observation. Particle filters are used to estimate the position of the targets in combination with a novel random weighting technique. Furthermore, we give positive proof-of-concept simulations.

Experimental test of state-independent quantum contextuality of an indivisible quantum system

NASA Astrophysics Data System (ADS)

Li, Meng; Huang, Yun-Feng; Cao, Dong-Yang; Zhang, Chao; Zhang, Yong-Sheng; Liu, Bi-Heng; Li, Chuan-Feng; Guo, Guang-Can

2014-05-01

Since the quantum mechanics was born, quantum mechanics was argued among scientists because the differences between quantum mechanics and the classical physics. Because of this, some people give hidden variable theory. One of the hidden variable theory is non-contextual hidden variable theory, and KS inequalities are famous in non-contextual hidden variable theory. But the original KS inequalities have 117 directions to measure, so it is almost impossible to test the KS inequalities in experiment. However bout two years ago, Sixia Yu and C.H. Oh point out that for a single qutrit, we only need to measure 13 directions, then we can test the KS inequalities. This makes it possible to test the KS inequalities in experiment. We use the polarization and the path of single photon to construct a qutrit, and we use the half-wave plates, the beam displacers and polar beam splitters to prepare the quantum state and finish the measurement. And the result prove that quantum mechanics is right and non-contextual hidden variable theory is wrong.

How hidden are hidden processes? A primer on crypticity and entropy convergence

NASA Astrophysics Data System (ADS)

Mahoney, John R.; Ellison, Christopher J.; James, Ryan G.; Crutchfield, James P.

2011-09-01

We investigate a stationary process's crypticity—a measure of the difference between its hidden state information and its observed information—using the causal states of computational mechanics. Here, we motivate crypticity and cryptic order as physically meaningful quantities that monitor how hidden a hidden process is. This is done by recasting previous results on the convergence of block entropy and block-state entropy in a geometric setting, one that is more intuitive and that leads to a number of new results. For example, we connect crypticity to how an observer synchronizes to a process. We show that the block-causal-state entropy is a convex function of block length. We give a complete analysis of spin chains. We present a classification scheme that surveys stationary processes in terms of their possible cryptic and Markov orders. We illustrate related entropy convergence behaviors using a new form of foliated information diagram. Finally, along the way, we provide a variety of interpretations of crypticity and cryptic order to establish their naturalness and pervasiveness. This is also a first step in developing applications in spatially extended and network dynamical systems.

Central Compact Objects in Kes 79 and RCW 103 as `Hidden' Magnetars with Crustal Activity

NASA Astrophysics Data System (ADS)

Popov, S. B.; Kaurov, A. A.; Kaminker, A. D.

2015-05-01

We propose that observations of `hidden' magnetars in central compact objects can be used to probe crustal activity of neutron stars with large internal magnetic fields. Estimates based on calculations by Perna & Pons, Pons & Rea and Kaminker et al. suggest that central compact objects, which are proposed to be `hidden' magnetars, must demonstrate flux variations on the time scale of months-years. However, the most prominent candidate for the `hidden' magnetars - CXO J1852.6+0040 in Kes 79 - shows constant (within error bars) flux. This can be interpreted by lower variable crustal activity than in typical magnetars. Alternatively, CXO J1852.6+0040 can be in a high state of variable activity during the whole period of observations. Then we consider the source 1E161348 - 5055 in RCW103 as another candidate. Employing a simple 2D-modelling we argue that properties of the source can be explained by the crustal activity of the magnetar type. Thus, this object may be supplemented for the three known candidates for the `hidden' magnetars among central compact objects discussed in literature.

StegoWall: blind statistical detection of hidden data

NASA Astrophysics Data System (ADS)

Voloshynovskiy, Sviatoslav V.; Herrigel, Alexander; Rytsar, Yuri B.; Pun, Thierry

2002-04-01

Novel functional possibilities, provided by recent data hiding technologies, carry out the danger of uncontrolled (unauthorized) and unlimited information exchange that might be used by people with unfriendly interests. The multimedia industry as well as the research community recognize the urgent necessity for network security and copyright protection, or rather the lack of adequate law for digital multimedia protection. This paper advocates the need for detecting hidden data in digital and analog media as well as in electronic transmissions, and for attempting to identify the underlying hidden data. Solving this problem calls for the development of an architecture for blind stochastic hidden data detection in order to prevent unauthorized data exchange. The proposed architecture is called StegoWall; its key aspects are the solid investigation, the deep understanding, and the prediction of possible tendencies in the development of advanced data hiding technologies. The basic idea of our complex approach is to exploit all information about hidden data statistics to perform its detection based on a stochastic framework. The StegoWall system will be used for four main applications: robust watermarking, secret communications, integrity control and tamper proofing, and internet/network security.

Hidden axion dark matter decaying through mixing with QCD axion and the 3.5 keV X-ray line

DOE Office of Scientific and Technical Information (OSTI.GOV)

Higaki, Tetsutaro; Kitajima, Naoya; Takahashi, Fuminobu, E-mail: thigaki@post.kek.jp, E-mail: kitajima@tuhep.phys.tohoku.ac.jp, E-mail: fumi@tuhep.phys.tohoku.ac.jp

2014-12-01

Hidden axions may be coupled to the standard model particles through a kinetic or mass mixing with QCD axion. We study a scenario in which a hidden axion constitutes a part of or the whole of dark matter and decays into photons through the mixing, explaining the 3.5 keV X-ray line signal. Interestingly, the required long lifetime of the hidden axion dark matter can be realized for the QCD axion decay constant at an intermediate scale, if the mixing is sufficiently small. In such a two component dark matter scenario, the primordial density perturbations of the hidden axion can bemore » highly non-Gaussian, leading to a possible dispersion in the X-ray line strength from various galaxy clusters and near-by galaxies. We also discuss how the parallel and orthogonal alignment of two axions affects their couplings to gauge fields. In particular, the QCD axion decay constant can be much larger than the actual Peccei-Quinn symmetry breaking.« less

Generalizing the Network Scale-Up Method: A New Estimator for the Size of Hidden Populations*

PubMed Central

Feehan, Dennis M.; Salganik, Matthew J.

2018-01-01

The network scale-up method enables researchers to estimate the size of hidden populations, such as drug injectors and sex workers, using sampled social network data. The basic scale-up estimator offers advantages over other size estimation techniques, but it depends on problematic modeling assumptions. We propose a new generalized scale-up estimator that can be used in settings with non-random social mixing and imperfect awareness about membership in the hidden population. Further, the new estimator can be used when data are collected via complex sample designs and from incomplete sampling frames. However, the generalized scale-up estimator also requires data from two samples: one from the frame population and one from the hidden population. In some situations these data from the hidden population can be collected by adding a small number of questions to already planned studies. For other situations, we develop interpretable adjustment factors that can be applied to the basic scale-up estimator. We conclude with practical recommendations for the design and analysis of future studies. PMID:29375167

Factors influencing infants’ ability to update object representations in memory

PubMed Central

Moher, Mariko; Feigenson, Lisa

2013-01-01

Remembering persisting objects over occlusion is critical to representing a stable environment. Infants remember hidden objects at multiple locations and can update their representation of a hidden array when an object is added or subtracted. However, the factors influencing these updating abilities have received little systematic exploration. Here we examined the flexibility of infants’ ability to update object representations. We tested 11-month-olds in a looking-time task in which objects were added to or subtracted from two hidden arrays. Across five experiments, infants successfully updated their representations of hidden arrays when the updating occurred successively at one array before beginning at the other. But when updating required alternating between two arrays, infants failed. However, simply connecting the two arrays with a thin strip of foam-core led infants to succeed. Our results suggest that infants’ construal of an event strongly affects their ability to update memory representations of hidden objects. When construing an event as containing multiple updates to the same array, infants succeed, but when construing the event as requiring the revisiting and updating of previously attended arrays, infants fail. PMID:24049245

Developing JSequitur to Study the Hierarchical Structure of Biological Sequences in a Grammatical Inference Framework of String Compression Algorithms.

PubMed

Galbadrakh, Bulgan; Lee, Kyung-Eun; Park, Hyun-Seok

2012-12-01

Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.

A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

PubMed Central

2017-01-01

The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them. PMID:28497059

Supporting undergraduate nursing students through structured personal tutoring: Some reflections.

PubMed

Watts, Tessa E

2011-02-01

Support is imperative for nursing students worldwide as they face the many challenges associated with learning and working. Moreover enhancing student retention is an increasing concern for institutions across the globe. The personal tutor is a frequently hidden yet potentially significant figure in many students' experience of higher education. This paper offers some critical reflections on a structured approach to personal tutoring within an undergraduate nursing programme in a research focused Welsh university. Structured personal tutoring can provide an organised, coherent and proactive support system throughout students' educational programmes. However the approach changes the shape of personal tutoring and has the potential to increase academics' workloads and with it costs. Copyright © 2010 Elsevier Ltd. All rights reserved.

First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aguilar-Arevalo, A.; Amidei, D.; Bertou, X.

We present direct detection constraints on the absorption of hidden-photon dark matter with particle masses in the range 1.2-30 eVmore » $$c^{-2}$$ with the DAMIC experiment at SNOLAB. Under the assumption that the local dark matter is entirely constituted of hidden photons, the sensitivity to the kinetic mixing parameter $$\\kappa$$ is competitive with constraints from solar emission, reaching a minimum value of 2.2$$\\times$$$10^{-14}$$ at 17 eV$$c^{-2}$$. These results are the most stringent direct detection constraints on hidden-photon dark matter with masses 3-12 eV$$c^{-2}$$ and the first demonstration of direct experimental sensitivity to ionization signals $<$12 eV from dark matter interactions.« less

NPLOT: an Interactive Plotting Program for NASTRAN Finite Element Models

NASA Technical Reports Server (NTRS)

Jones, G. K.; Mcentire, K. J.

1985-01-01

The NPLOT (NASTRAN Plot) is an interactive computer graphics program for plotting undeformed and deformed NASTRAN finite element models. Developed at NASA's Goddard Space Flight Center, the program provides flexible element selection and grid point, ASET and SPC degree of freedom labelling. It is easy to use and provides a combination menu and command driven user interface. NPLOT also provides very fast hidden line and haloed line algorithms. The hidden line algorithm in NPLOT proved to be both very accurate and several times faster than other existing hidden line algorithms. A fast spatial bucket sort and horizon edge computation are used to achieve this high level of performance. The hidden line and the haloed line algorithms are the primary features that make NPLOT different from other plotting programs.

The composition and structure of planetary rings

NASA Technical Reports Server (NTRS)

Burns, J. A.

1985-01-01

The properties of planetary ring systems are summarized herein; emphasis is given to the available evidence on their compositions and to their dynamical attributes. Somewhat contaminated water ice makes up the vast expanse of Saturn's rings. Modified methane ice may comprise Uranus' rings while silicates are the likely material of the Jovian ring. Saturn's rings form an elaborate system whose characteristics are still being documented and whose nature is being unravelled following the Voyager flybys. Uranus' nine narrow bands display an intriguing dynamical structure thought to be caused by unseen shephard satellites. Jupiter's ring system is a mere wisp, probably derived as ejecta off hidden parent bodies.

A recurrent self-organizing neural fuzzy inference network.

PubMed

Juang, C F; Lin, C T

1999-01-01

A recurrent self-organizing neural fuzzy inference network (RSONFIN) is proposed in this paper. The RSONFIN is inherently a recurrent multilayered connectionist network for realizing the basic elements and functions of dynamic fuzzy inference, and may be considered to be constructed from a series of dynamic fuzzy rules. The temporal relations embedded in the network are built by adding some feedback connections representing the memory elements to a feedforward neural fuzzy network. Each weight as well as node in the RSONFIN has its own meaning and represents a special element in a fuzzy rule. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially in the RSONFIN. They are created on-line via concurrent structure identification (the construction of dynamic fuzzy if-then rules) and parameter identification (the tuning of the free parameters of membership functions). The structure learning together with the parameter learning forms a fast learning algorithm for building a small, yet powerful, dynamic neural fuzzy network. Two major characteristics of the RSONFIN can thus be seen: 1) the recurrent property of the RSONFIN makes it suitable for dealing with temporal problems and 2) no predetermination, like the number of hidden nodes, must be given, since the RSONFIN can find its optimal structure and parameters automatically and quickly. Moreover, to reduce the number of fuzzy rules generated, a flexible input partition method, the aligned clustering-based algorithm, is proposed. Various simulations on temporal problems are done and performance comparisons with some existing recurrent networks are also made. Efficiency of the RSONFIN is verified from these results.

Peptide crystal simulations reveal hidden dynamics

PubMed Central

Janowski, Pawel A.; Cerutti, David S.; Holton, James; Case, David A.

2013-01-01

Molecular dynamics simulations of biomolecular crystals at atomic resolution have the potential to recover information on dynamics and heterogeneity hidden in the X-ray diffraction data. We present here 9.6 microseconds of dynamics in a small helical peptide crystal with 36 independent copies of the unit cell. The average simulation structure agrees with experiment to within 0.28 Å backbone and 0.42 Å all-atom rmsd; a model refined against the average simulation density agrees with the experimental structure to within 0.20 Å backbone and 0.33 Å all-atom rmsd. The R-factor between the experimental structure factors and those derived from this unrestrained simulation is 23% to 1.0 Å resolution. The B-factors for most heavy atoms agree well with experiment (Pearson correlation of 0.90), but B-factors obtained by refinement against the average simulation density underestimate the coordinate fluctuations in the underlying simulation where the simulation samples alternate conformations. A dynamic flow of water molecules through channels within the crystal lattice is observed, yet the average water density is in remarkable agreement with experiment. A minor population of unit cells is characterized by reduced water content, 310 helical propensity and a gauche(−) side-chain rotamer for one of the valine residues. Careful examination of the experimental data suggests that transitions of the helices are a simulation artifact, although there is indeed evidence for alternate valine conformers and variable water content. This study highlights the potential for crystal simulations to detect dynamics and heterogeneity in experimental diffraction data, as well as to validate computational chemistry methods. PMID:23631449

Flu Widget

MedlinePlus

... 0" width="300" title="Flu I.Q. Widget" style="overflow: hidden;"> Flu ... 0" width="280" title="CDC Flu Vaccine Finder" style="overflow: hidden;"> FluView Widget < ...

Mean-field message-passing equations in the Hopfield model and its generalizations

NASA Astrophysics Data System (ADS)

Mézard, Marc

2017-02-01

Motivated by recent progress in using restricted Boltzmann machines as preprocessing algorithms for deep neural network, we revisit the mean-field equations [belief-propagation and Thouless-Anderson Palmer (TAP) equations] in the best understood of such machines, namely the Hopfield model of neural networks, and we explicit how they can be used as iterative message-passing algorithms, providing a fast method to compute the local polarizations of neurons. In the "retrieval phase", where neurons polarize in the direction of one memorized pattern, we point out a major difference between the belief propagation and TAP equations: The set of belief propagation equations depends on the pattern which is retrieved, while one can use a unique set of TAP equations. This makes the latter method much better suited for applications in the learning process of restricted Boltzmann machines. In the case where the patterns memorized in the Hopfield model are not independent, but are correlated through a combinatorial structure, we show that the TAP equations have to be modified. This modification can be seen either as an alteration of the reaction term in TAP equations or, more interestingly, as the consequence of message passing on a graphical model with several hidden layers, where the number of hidden layers depends on the depth of the correlations in the memorized patterns. This layered structure is actually necessary when one deals with more general restricted Boltzmann machines.

Novel methods for aircraft corrosion monitoring

NASA Astrophysics Data System (ADS)

Bossi, Richard H.; Criswell, Thomas L.; Ikegami, Roy; Nelson, James; Normand, Eugene; Rutherford, Paul S.; Shrader, John E.

1995-07-01

Monitoring aging aircraft for hidden corrosion is a significant problem for both military and civilian aircraft. Under a Wright Laboratory sponsored program, Boeing Defense & Space Group is investigating three novel methods for detecting and monitoring hidden corrosion: (1) atmospheric neutron radiography, (2) 14 MeV neutron activation analysis and (3) fiber optic corrosion sensors. Atmospheric neutron radiography utilizes the presence of neutrons in the upper atmosphere as a source for interrogation of the aircraft structure. Passive track-etch neutron detectors, which have been previously placed on the aircraft, are evaluated during maintenance checks to assess the presence of corrosion. Neutrons generated by an accelerator are used via activation analysis to assess the presence of distinctive elements in corrosion products, particularly oxygen. By using fast (14 MeV) neutrons for the activation, portable, high intensity sources can be employed for field testing of aircraft. The third novel method uses fiber optics as part of a smart structure technology for corrosion detection and monitoring. Fiber optic corrosion sensors are placed in the aircraft at locations known to be susceptible to corrosion. Periodic monitoring of the sensors is used to alert maintenance personnel to the presence and degree of corrosion at specific locations on the aircraft. During the atmospheric neutron experimentation, we identified a fourth method referred to as secondary emission radiography (SER). This paper discusses the development of these methods.

Optical character recognition of handwritten Arabic using hidden Markov models

NASA Astrophysics Data System (ADS)

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

2011-04-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

Abnormal hippocampal functioning and impaired spatial navigation in depressed individuals: evidence from whole-head magnetoencephalography.

PubMed

Cornwell, Brian R; Salvadore, Giacomo; Colon-Rosario, Veronica; Latov, David R; Holroyd, Tom; Carver, Frederick W; Coppola, Richard; Manji, Husseini K; Zarate, Carlos A; Grillon, Christian

2010-07-01

Dysfunction of the hippocampus has long been suspected to be a key component of the pathophysiology of major depressive disorder. Despite evidence of hippocampal structural abnormalities in depressed patients, abnormal hippocampal functioning has not been demonstrated. The authors aimed to link spatial navigation deficits previously documented in depressed patients to abnormal hippocampal functioning using a virtual reality navigation task. Whole-head magnetoencephalography (MEG) recordings were collected while participants (19 patients diagnosed with major depressive disorder and 19 healthy subjects matched by gender and age) navigated a virtual Morris water maze to find a hidden platform; navigation to a visible platform served as a control condition. Behavioral measures were obtained to assess navigation performance. Theta oscillatory activity (4-8 Hz) was mapped across the brain on a voxel-wise basis using a spatial-filtering MEG source analysis technique. Depressed patients performed worse than healthy subjects in navigating to the hidden platform. Robust group differences in theta activity were observed in right medial temporal cortices during navigation, with patients exhibiting less engagement of the anterior hippocampus and parahippocampal cortices relative to comparison subjects. Left posterior hippocampal theta activity was positively correlated with individual performance within each group. Consistent with previous findings, depressed patients showed impaired spatial navigation. Dysfunction of right anterior hippocampus and parahippocampal cortices may underlie this deficit and stem from structural abnormalities commonly found in depressed patients.

Optical character recognition of handwritten Arabic using hidden Markov models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.

2011-01-01

The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language ismore » initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.« less

Estimating parameters of hidden Markov models based on marked individuals: use of robust design data

USGS Publications Warehouse

Kendall, William L.; White, Gary C.; Hines, James E.; Langtimm, Catherine A.; Yoshizaki, Jun

2012-01-01

Development and use of multistate mark-recapture models, which provide estimates of parameters of Markov processes in the face of imperfect detection, have become common over the last twenty years. Recently, estimating parameters of hidden Markov models, where the state of an individual can be uncertain even when it is detected, has received attention. Previous work has shown that ignoring state uncertainty biases estimates of survival and state transition probabilities, thereby reducing the power to detect effects. Efforts to adjust for state uncertainty have included special cases and a general framework for a single sample per period of interest. We provide a flexible framework for adjusting for state uncertainty in multistate models, while utilizing multiple sampling occasions per period of interest to increase precision and remove parameter redundancy. These models also produce direct estimates of state structure for each primary period, even for the case where there is just one sampling occasion. We apply our model to expected value data, and to data from a study of Florida manatees, to provide examples of the improvement in precision due to secondary capture occasions. We also provide user-friendly software to implement these models. This general framework could also be used by practitioners to consider constrained models of particular interest, or model the relationship between within-primary period parameters (e.g., state structure) and between-primary period parameters (e.g., state transition probabilities).

Eavesdropping on insects hidden in soil and interior structures of plants.

PubMed

Mankin, R W; Brandhorst-Hubbard, J; Flanders, K L; Zhang, M; Crocker, R L; Lapointe, S L; McCoy, C W; Fisher, J R; Weaver, D K

2000-08-01

Accelerometer, electret microphone, and piezoelectric disk acoustic systems were evaluated for their potential to detect hidden insect infestations in soil and interior structures of plants. Coleopteran grubs (the scarabaeids Phyllophaga spp. and Cyclocephala spp.) and the curculionids Diaprepes abbreviatus (L.) and Otiorhynchus sulcatus (F.) weighing 50-300 mg were detected easily in the laboratory and in the field except under extremely windy or noisy conditions. Cephus cinctus Norton (Hymenoptera: Cephidae) larvae weighing 1-12 mg could be detected in small pots of wheat in the laboratory by taking moderate precautions to eliminate background noise. Insect sounds could be distinguished from background noises by differences in frequency and temporal patterns, but insects of similarly sized species could not be distinguished easily from each other. Insect activity was highly variable among individuals and species, although D. abbreviatus grubs tended to be more active than those of O. sulcatus. Tests were done to compare acoustically predicted infestations with the contents of soil samples taken at recording sites. Under laboratory or ideal field conditions, active insects within approximately 30 cm were identified with nearly 100% reliability. In field tests under adverse conditions, the reliability decreased to approximately 75%. These results indicate that acoustic systems with vibration sensors have considerable potential as activity monitors in the laboratory and as field tools for rapid, nondestructive scouting and mapping of soil insect populations.

Experimental search for hidden photon CDM in the eV mass range with a dish antenna

DOE Office of Scientific and Technical Information (OSTI.GOV)

Suzuki, J.; Horie, T.; Minowa, M.

2015-09-01

A search for hidden photon cold dark matter (HP CDM) using a new technique with a dish antenna is reported. From the result of the measurement, we found no evidence for the existence of HP CDM and set an upper limit on the photon-HP mixing parameter χ of ∼ 6× 10{sup −12} for the hidden photon mass m{sub γ} = 3.1 ± 1.2 eV.

The hidden universe

DOE Office of Scientific and Technical Information (OSTI.GOV)

Disney, M.

1985-01-01

Astronomer Disney has followed a somewhat different tack than that of most popular books on cosmology by concentrating on the notion of hidden (as in not directly observable by its own radiation) matter in the universe.

Estimating wheat and maize daily evapotranspiration using artificial neural network

NASA Astrophysics Data System (ADS)

Abrishami, Nazanin; Sepaskhah, Ali Reza; Shahrokhnia, Mohammad Hossein

2018-02-01

In this research, artificial neural network (ANN) is used for estimating wheat and maize daily standard evapotranspiration. Ten ANN models with different structures were designed for each crop. Daily climatic data [maximum temperature (T max), minimum temperature (T min), average temperature (T ave), maximum relative humidity (RHmax), minimum relative humidity (RHmin), average relative humidity (RHave), wind speed (U 2), sunshine hours (n), net radiation (Rn)], leaf area index (LAI), and plant height (h) were used as inputs. For five structures of ten, the evapotranspiration (ETC) values calculated by ETC = ET0 × K C equation (ET0 from Penman-Monteith equation and K C from FAO-56, ANNC) were used as outputs, and for the other five structures, the ETC values measured by weighing lysimeter (ANNM) were used as outputs. In all structures, a feed forward multiple-layer network with one or two hidden layers and sigmoid transfer function and BR or LM training algorithm was used. Favorite network was selected based on various statistical criteria. The results showed the suitable capability and acceptable accuracy of ANNs, particularly those having two hidden layers in their structure in estimating the daily evapotranspiration. Best model for estimation of maize daily evapotranspiration is «M»ANN1 C (8-4-2-1), with T max, T min, RHmax, RHmin, U 2, n, LAI, and h as input data and LM training rule and its statistical parameters (NRMSE, d, and R2) are 0.178, 0.980, and 0.982, respectively. Best model for estimation of wheat daily evapotranspiration is «W»ANN5 C (5-2-3-1), with T max, T min, Rn, LAI, and h as input data and LM training rule, its statistical parameters (NRMSE, d, and R 2) are 0.108, 0.987, and 0.981 respectively. In addition, if the calculated ETC used as the output of the network for both wheat and maize, higher accurate estimation was obtained. Therefore, ANN is suitable method for estimating evapotranspiration of wheat and maize.

"On Second Thoughts…": Changes of Mind as an Indication of Competing Knowledge Structures

NASA Astrophysics Data System (ADS)

Wilson, Kate F.; Low, David J.

2015-09-01

A review of student answers to diagnostic questions concerned with Newton's Laws showed a tendency for some students to change their answer to a question when the following question caused them to think more about the situation. We investigate this behavior and interpret it in the framework of the resource model; in particular, a weak Newton's Third Law structure being dominated by an inconsistent Newton's Second Law (or "Net Force") structure, in the absence of a strong, consistent Newtonian structure. This observation highlights the hidden problem in instruction where the implicit use of Newton's Third Law is dominated by the explicit conceptual and mathematical application of Newton's Second Law, both within individual courses and across a degree program. To facilitate students' development of a consistent Newtonian knowledge structure, it is important that instructors highlight the interrelated nature of Newton's Laws in problem solving.

It Twins! Spitzer Finds Hidden Jet

NASA Image and Video Library

2011-04-04

NASA Spitzer Space Telescope took this image of a baby star sprouting two identical jets green lines emanating from fuzzy star. The left jet was hidden behind a dark cloud, which Spitzer can see through.

SECTION L FROM FLAGPOLE TOWARD SOLDIERS AND SAILORS MONUMENT (HIDDEN ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

SECTION L FROM FLAGPOLE TOWARD SOLDIERS AND SAILORS MONUMENT (HIDDEN BY TREES). VIEW TO SOUTHEAST. - Bath National Cemetery, Department of Veterans Affairs Medical Center, San Juan Avenue, Bath, Steuben County, NY

A neural network based computational model to predict the output power of different types of photovoltaic cells.

PubMed

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Hidden Nanobubbles in Undersaturated Liquids.

PubMed

Guo, Zhenjiang; Liu, Yawei; Xiao, Qianxiang; Zhang, Xianren

2016-11-01

Here, we propose theoretically the existence of a new type of nanobubble in undersaturated liquids. These nanobubbles have a concave vapor-liquid interface featured with a negative curvature rather than a positive curvature for nanobubbles in supersaturated liquids, so that they often hide inside of the substrate textures and it might not be easy to characterize them through atomic force microscopy (AFM) measurements. However, these hidden nanobubbles are still stabilized by the contact line pinning effect and stay at the thermodynamically metastable state. We further demonstrate that similar to the nanobubbles in supersaturated liquids the contact angle of the hidden nanobubbles is more sensitive to the nanobubble size rather than the substrate chemistry, and their curvature radius is dependent on the chemical potential but independent of the base radius. Finally, we show several potential situations for the appearance of the hidden nanobubbles.

First Direct-Detection Constraints on eV-Scale Hidden-Photon Dark Matter with DAMIC at SNOLAB.

PubMed

Aguilar-Arevalo, A; Amidei, D; Bertou, X; Butner, M; Cancelo, G; Castañeda Vázquez, A; Cervantes Vergara, B A; Chavarria, A E; Chavez, C R; de Mello Neto, J R T; D'Olivo, J C; Estrada, J; Fernandez Moroni, G; Gaïor, R; Guardincerri, Y; Hernández Torres, K P; Izraelevitch, F; Kavner, A; Kilminster, B; Lawson, I; Letessier-Selvon, A; Liao, J; Matalon, A; Mello, V B B; Molina, J; Privitera, P; Ramanathan, K; Sarkis, Y; Schwarz, T; Settimo, M; Sofo Haro, M; Thomas, R; Tiffenberg, J; Tiouchichine, E; Torres Machado, D; Trillaud, F; You, X; Zhou, J

2017-04-07

We present direct detection constraints on the absorption of hidden-photon dark matter with particle masses in the range 1.2-30  eV c^{-2} with the DAMIC experiment at SNOLAB. Under the assumption that the local dark matter is entirely constituted of hidden photons, the sensitivity to the kinetic mixing parameter κ is competitive with constraints from solar emission, reaching a minimum value of 2.2×10^{-14} at 17  eV c^{-2}. These results are the most stringent direct detection constraints on hidden-photon dark matter in the galactic halo with masses 3-12  eV c^{-2} and the first demonstration of direct experimental sensitivity to ionization signals <12  eV from dark matter interactions.

Hidden-Symmetry-Protected Topological Semimetals on a Square Lattice

NASA Astrophysics Data System (ADS)

Hou, Jing-Min

2014-03-01

We study a two-dimensional fermionic square lattice, which supports the existence of two-dimensional Weyl semimetal, quantum anomalous Hall effect, and 2 π -flux topological semimetal in different parameter ranges. We show that the band degenerate points of the two-dimensional Weyl semimetal and 2 π -flux topological semimetal are protected by two distinct novel hidden symmetries, which both corresponds to antiunitary composite operations. When these hidden symmetries are broken, a gap opens between the conduction and valence bands, turning the system into a insulator. With appropriate parameters, a quantum anomalous Hall effect emerges. The degenerate point at the boundary between the quantum anomalous Hall insulator and trivial band insulator is also protected by the hidden symmetry. [PRL 111, 130403(2013)] This work was supported by the National Natural Science Foundation of China under Grants No. 11004028 and No. 11274061.

Complex Sequencing Rules of Birdsong Can be Explained by Simple Hidden Markov Processes

PubMed Central

Katahira, Kentaro; Suzuki, Kenta; Okanoya, Kazuo; Okada, Masato

2011-01-01

Complex sequencing rules observed in birdsongs provide an opportunity to investigate the neural mechanism for generating complex sequential behaviors. To relate the findings from studying birdsongs to other sequential behaviors such as human speech and musical performance, it is crucial to characterize the statistical properties of the sequencing rules in birdsongs. However, the properties of the sequencing rules in birdsongs have not yet been fully addressed. In this study, we investigate the statistical properties of the complex birdsong of the Bengalese finch (Lonchura striata var. domestica). Based on manual-annotated syllable labeles, we first show that there are significant higher-order context dependencies in Bengalese finch songs, that is, which syllable appears next depends on more than one previous syllable. We then analyze acoustic features of the song and show that higher-order context dependencies can be explained using first-order hidden state transition dynamics with redundant hidden states. This model corresponds to hidden Markov models (HMMs), well known statistical models with a large range of application for time series modeling. The song annotation with these models with first-order hidden state dynamics agreed well with manual annotation, the score was comparable to that of a second-order HMM, and surpassed the zeroth-order model (the Gaussian mixture model; GMM), which does not use context information. Our results imply that the hierarchical representation with hidden state dynamics may underlie the neural implementation for generating complex behavioral sequences with higher-order dependencies. PMID:21915345

Data Mining of NASA Boeing 737 Flight Data: Frequency Analysis of In-Flight Recorded Data

NASA Technical Reports Server (NTRS)

Butterfield, Ansel J.

2001-01-01

Data recorded during flights of the NASA Trailblazer Boeing 737 have been analyzed to ascertain the presence of aircraft structural responses from various excitations such as the engine, aerodynamic effects, wind gusts, and control system operations. The NASA Trailblazer Boeing 737 was chosen as a focus of the study because of a large quantity of its flight data records. The goal of this study was to determine if any aircraft structural characteristics could be identified from flight data collected for measuring non-structural phenomena. A number of such data were examined for spatial and frequency correlation as a means of discovering hidden knowledge of the dynamic behavior of the aircraft. Data recorded from on-board dynamic sensors over a range of flight conditions showed consistently appearing frequencies. Those frequencies were attributed to aircraft structural vibrations.

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

NASA Astrophysics Data System (ADS)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.

A Taxonomy-Based Approach to Shed Light on the Babel of Mathematical Models for Rice Simulation

NASA Technical Reports Server (NTRS)

Confalonieri, Roberto; Bregaglio, Simone; Adam, Myriam; Ruget, Francoise; Li, Tao; Hasegawa, Toshihiro; Yin, Xinyou; Zhu, Yan; Boote, Kenneth; Buis, Samuel;

Improving Forecasts Through Realistic Uncertainty Estimates: A Novel Data Driven Method for Model Uncertainty Quantification in Data Assimilation

NASA Astrophysics Data System (ADS)

Pathiraja, S. D.; Moradkhani, H.; Marshall, L. A.; Sharma, A.; Geenens, G.

2016-12-01

Effective combination of model simulations and observations through Data Assimilation (DA) depends heavily on uncertainty characterisation. Many traditional methods for quantifying model uncertainty in DA require some level of subjectivity (by way of tuning parameters or by assuming Gaussian statistics). Furthermore, the focus is typically on only estimating the first and second moments. We propose a data-driven methodology to estimate the full distributional form of model uncertainty, i.e. the transition density p(xt|xt-1). All sources of uncertainty associated with the model simulations are considered collectively, without needing to devise stochastic perturbations for individual components (such as model input, parameter and structural uncertainty). A training period is used to derive the distribution of errors in observed variables conditioned on hidden states. Errors in hidden states are estimated from the conditional distribution of observed variables using non-linear optimization. The theory behind the framework and case study applications are discussed in detail. Results demonstrate improved predictions and more realistic uncertainty bounds compared to a standard perturbation approach.

Guided wave energy trapping to detect hidden multilayer delamination damage

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Seebo, Jeffrey P.

2015-03-01

Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) simulation tools capable of modeling three-dimensional (3D) realistic energy-damage interactions are needed for aerospace composites. Current practice in NDE/SHM simulation for composites commonly involves over-simplification of the material parameters and/or a simplified two-dimensional (2D) approach. The unique damage types that occur in composite materials (delamination, microcracking, etc) develop as complex 3D geometry features. This paper discusses the application of 3D custom ultrasonic simulation tools to study wave interaction with multilayer delamination damage in carbon-fiber reinforced polymer (CFRP) composites. In particular, simulation based studies of ultrasonic guided wave energy trapping due to multilayer delamination damage were performed. The simulation results show changes in energy trapping at the composite surface as additional delaminations are added through the composite thickness. The results demonstrate a potential approach for identifying the presence of hidden multilayer delamination damage in applications where only single-sided access to a component is available. The paper also describes recent advancements in optimizing the custom ultrasonic simulation code for increases in computation speed.

A proposed OB-fold with a protein-interaction surface in Candida albicans telomerase protein Est3

PubMed Central

Yu, Eun Young; Wang, Feng; Lei, Ming; Lue, Neal F

2008-01-01

Ever shorter telomeres 3 (Est3) is an essential telomerase regulatory subunit thought to be unique to budding yeasts. Here we use multiple sequence alignment and hidden Markov model–hidden Markov model (HMM-HMM) comparison to uncover potential similarities between Est3 and the mammalian telomeric protein Tpp1. Analysis of site-specific mutants of Candida albicans Est3 revealed functional distinctions between residues that are conserved between Est3 and Tpp1 and those that are unique to Est3. Although both types of residues are important for telomere maintenance in vivo, only the former contributes to telomerase activity in vitro and facilitates the association of Est3 with telomerase core components. Consistent with a function in protein-protein interaction, the residues common to Est3 and Tpp1 map to one face of an OB-fold model structure, away from the canonical nucleic acid binding surface. We propose that Est3 and the OB-fold domain of Tpp1 mediate a conserved function in telomerase regulation. PMID:19172753

Clustered mixed nonhomogeneous Poisson process spline models for the analysis of recurrent event panel data.

PubMed

Nielsen, J D; Dean, C B

2008-09-01

A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.