On the necessary conditions of the regular minimum of the scale factor of the co-moving space

International Nuclear Information System (INIS)

Agakov, V.G.

1980-01-01

In the framework of homogeneous cosmologic model studied is the behaviour of the comoving space element volume filled with barotropous medium, deprived of energy fluxes. Presented are the necessary conditions at which a regular final minimum of the scale factor of the co-mowing space may take place. It is found that to carry out the above minimum at values of cosmological constant Λ <= 0 the presence of two from three anisotropy factors is necessary. Anisotropy of space deformation should be one of these factors. In case of Λ <= 0 the regular minimum is also possible if all three factors of anisotropy are equal to zero. However if none of the factors of Fsub(i), Asub(ik) anisotropy is equal to zero, the presence of deformation space anisotropy is necessary for final regular minimum appearance

Neutrino stress tensor regularization in two-dimensional space-time

International Nuclear Information System (INIS)

Davies, P.C.W.; Unruh, W.G.

1977-01-01

The method of covariant point-splitting is used to regularize the stress tensor for a massless spin 1/2 (neutrino) quantum field in an arbitrary two-dimensional space-time. A thermodynamic argument is used as a consistency check. The result shows that the physical part of the stress tensor is identical with that of the massless scalar field (in the absence of Casimir-type terms) even though the formally divergent expression is equal to the negative of the scalar case. (author)

Time-Homogeneous Parabolic Wick-Anderson Model in One Space Dimension: Regularity of Solution

OpenAIRE

Kim, Hyun-Jung; Lototsky, Sergey V

2017-01-01

Even though the heat equation with random potential is a well-studied object, the particular case of time-independent Gaussian white noise in one space dimension has yet to receive the attention it deserves. The paper investigates the stochastic heat equation with space-only Gaussian white noise on a bounded interval. The main result is that the space-time regularity of the solution is the same for additive noise and for multiplicative noise in the Wick-It\\^o-Skorokhod interpretation.

Regularization in Hilbert space under unbounded operators and general source conditions

International Nuclear Information System (INIS)

Hofmann, Bernd; Mathé, Peter; Von Weizsäcker, Heinrich

2009-01-01

The authors study ill-posed equations with unbounded operators in Hilbert space. This setup has important applications, but only a few theoretical studies are available. First, the question is addressed and answered whether every element satisfies some general source condition with respect to a given self-adjoint unbounded operator. This generalizes a previous result from Mathé and Hofmann (2008 Inverse Problems 24 015009). The analysis then proceeds to error bounds for regularization, emphasizing some specific points for regularization under unbounded operators. The study finally reviews two examples within the light of the present study, as these are fractional differentiation and some Cauchy problems for the Helmholtz equation, both studied previously and in more detail by U Tautenhahn and co-authors

A remark on partial linear spaces of girth 5 with an application to strongly regular graphs

NARCIS (Netherlands)

Brouwer, A.E.; Neumaier, A.

1988-01-01

We derive a lower bound on the number of points of a partial linear space of girth 5. As an application, certain strongly regular graphs with=2 are ruled out by observing that the first subconstituents are partial linear spaces.

A function space framework for structural total variation regularization with applications in inverse problems

Science.gov (United States)

Hintermüller, Michael; Holler, Martin; Papafitsoros, Kostas

2018-06-01

In this work, we introduce a function space setting for a wide class of structural/weighted total variation (TV) regularization methods motivated by their applications in inverse problems. In particular, we consider a regularizer that is the appropriate lower semi-continuous envelope (relaxation) of a suitable TV type functional initially defined for sufficiently smooth functions. We study examples where this relaxation can be expressed explicitly, and we also provide refinements for weighted TV for a wide range of weights. Since an integral characterization of the relaxation in function space is, in general, not always available, we show that, for a rather general linear inverse problems setting, instead of the classical Tikhonov regularization problem, one can equivalently solve a saddle-point problem where no a priori knowledge of an explicit formulation of the structural TV functional is needed. In particular, motivated by concrete applications, we deduce corresponding results for linear inverse problems with norm and Poisson log-likelihood data discrepancy terms. Finally, we provide proof-of-concept numerical examples where we solve the saddle-point problem for weighted TV denoising as well as for MR guided PET image reconstruction.

On Landweber–Kaczmarz methods for regularizing systems of ill-posed equations in Banach spaces

International Nuclear Information System (INIS)

Leitão, A; Alves, M Marques

2012-01-01

In this paper, iterative regularization methods of Landweber–Kaczmarz type are considered for solving systems of ill-posed equations modeled (finitely many) by operators acting between Banach spaces. Using assumptions of uniform convexity and smoothness on the parameter space, we are able to prove a monotony result for the proposed method, as well as to establish convergence (for exact data) and stability results (in the noisy data case). (paper)

Salt-body Inversion with Minimum Gradient Support and Sobolev Space Norm Regularizations

KAUST Repository

Kazei, Vladimir

2017-05-26

Full-waveform inversion (FWI) is a technique which solves the ill-posed seismic inversion problem of fitting our model data to the measured ones from the field. FWI is capable of providing high-resolution estimates of the model, and of handling wave propagation of arbitrary complexity (visco-elastic, anisotropic); yet, it often fails to retrieve high-contrast geological structures, such as salt. One of the reasons for the FWI failure is that the updates at earlier iterations are too smooth to capture the sharp edges of the salt boundary. We compare several regularization approaches, which promote sharpness of the edges. Minimum gradient support (MGS) regularization focuses the inversion on blocky models, even more than the total variation (TV) does. However, both approaches try to invert undesirable high wavenumbers in the model too early for a model of complex structure. Therefore, we apply the Sobolev space norm as a regularizing term in order to maintain a balance between sharp and smooth updates in FWI. We demonstrate the application of these regularizations on a Marmousi model, enriched by a chunk of salt. The model turns out to be too complex in some parts to retrieve its full velocity distribution, yet the salt shape and contrast are retrieved.

Critical phenomena of regular black holes in anti-de Sitter space-time

Energy Technology Data Exchange (ETDEWEB)

Fan, Zhong-Ying [Peking University, Center for High Energy Physics, Beijing (China)

2017-04-15

In General Relativity, addressing coupling to a non-linear electromagnetic field, together with a negative cosmological constant, we obtain the general static spherical symmetric black hole solution with magnetic charges, which is asymptotic to anti-de Sitter (AdS) space-times. In particular, for a degenerate case the solution becomes a Hayward-AdS black hole, which is regular everywhere in the full space-time. The existence of such a regular black hole solution preserves the weak energy condition, while the strong energy condition is violated. We then derive the first law and the Smarr formula of the black hole solution. We further discuss its thermodynamic properties and study the critical phenomena in the extended phase space where the cosmological constant is treated as a thermodynamic variable as well as the parameter associated with the non-linear electrodynamics. We obtain many interesting results such as: the Maxwell equal area law in the P-V (or S-T) diagram is violated and consequently the critical point (T{sub *},P{sub *}) of the first order small-large black hole transition does not coincide with the inflection point (T{sub c},P{sub c}) of the isotherms; the Clapeyron equation describing the coexistence curve of the Van der Waals (vdW) fluid is no longer valid; the heat capacity at constant pressure is finite at the critical point; the various exponents near the critical point are also different from those of the vdW fluid. (orig.)

Parameter choice in Banach space regularization under variational inequalities

International Nuclear Information System (INIS)

Hofmann, Bernd; Mathé, Peter

2012-01-01

The authors study parameter choice strategies for the Tikhonov regularization of nonlinear ill-posed problems in Banach spaces. The effectiveness of any parameter choice for obtaining convergence rates depends on the interplay of the solution smoothness and the nonlinearity structure, and it can be expressed concisely in terms of variational inequalities. Such inequalities are link conditions between the penalty term, the norm misfit and the corresponding error measure. The parameter choices under consideration include an a priori choice, the discrepancy principle as well as the Lepskii principle. For the convenience of the reader, the authors review in an appendix a few instances where the validity of a variational inequality can be established. (paper)

Supersymmetric dimensional regularization

International Nuclear Information System (INIS)

Siegel, W.; Townsend, P.K.; van Nieuwenhuizen, P.

1980-01-01

There is a simple modification of dimension regularization which preserves supersymmetry: dimensional reduction to real D < 4, followed by analytic continuation to complex D. In terms of component fields, this means fixing the ranges of all indices on the fields (and therefore the numbers of Fermi and Bose components). For superfields, it means continuing in the dimensionality of x-space while fixing the dimensionality of theta-space. This regularization procedure allows the simple manipulation of spinor derivatives in supergraph calculations. The resulting rules are: (1) First do all algebra exactly as in D = 4; (2) Then do the momentum integrals as in ordinary dimensional regularization. This regularization procedure needs extra rules before one can say that it is consistent. Such extra rules needed for superconformal anomalies are discussed. Problems associated with renormalizability and higher order loops are also discussed

Zeta-function regularization approach to finite temperature effects in Kaluza-Klein space-times

International Nuclear Information System (INIS)

Bytsenko, A.A.; Vanzo, L.; Zerbini, S.

1992-01-01

In the framework of heat-kernel approach to zeta-function regularization, in this paper the one-loop effective potential at finite temperature for scalar and spinor fields on Kaluza-Klein space-time of the form M p x M c n , where M p is p-dimensional Minkowski space-time is evaluated. In particular, when the compact manifold is M c n = H n /Γ, the Selberg tracer formula associated with discrete torsion-free group Γ of the n-dimensional Lobachevsky space H n is used. An explicit representation for the thermodynamic potential valid for arbitrary temperature is found. As a result a complete high temperature expansion is presented and the roles of zero modes and topological contributions is discussed

Effective deep brain stimulation suppresses low frequency network oscillations in the basal ganglia by regularizing neural firing patterns

Science.gov (United States)

McConnell, George C.; So, Rosa Q.; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M.

2012-01-01

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson’s disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90Hz) improve motor symptoms, while low frequencies (basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high frequency DBS reversed motor symptoms and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high frequency DBS, but not low frequency DBS, reduced pathological low frequency oscillations (~9Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low frequency band to the stimulation frequency during high frequency DBS, but not during low frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high frequency DBS is more effective than low frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low frequency network oscillations with a regularized pattern of neuronal firing. PMID:23136407

Effective deep brain stimulation suppresses low-frequency network oscillations in the basal ganglia by regularizing neural firing patterns.

Science.gov (United States)

McConnell, George C; So, Rosa Q; Hilliard, Justin D; Lopomo, Paola; Grill, Warren M

2012-11-07

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for the motor symptoms of Parkinson's disease (PD). The effects of DBS depend strongly on stimulation frequency: high frequencies (>90 Hz) improve motor symptoms, while low frequencies (basal ganglia were studied in the unilateral 6-hydroxydopamine lesioned rat model of PD. Only high-frequency DBS reversed motor symptoms, and the effectiveness of DBS depended strongly on stimulation frequency in a manner reminiscent of its clinical effects in persons with PD. Quantification of single-unit activity in the globus pallidus externa (GPe) and substantia nigra reticulata (SNr) revealed that high-frequency DBS, but not low-frequency DBS, reduced pathological low-frequency oscillations (∼9 Hz) and entrained neurons to fire at the stimulation frequency. Similarly, the coherence between simultaneously recorded pairs of neurons within and across GPe and SNr shifted from the pathological low-frequency band to the stimulation frequency during high-frequency DBS, but not during low-frequency DBS. The changes in firing patterns in basal ganglia neurons were not correlated with changes in firing rate. These results indicate that high-frequency DBS is more effective than low-frequency DBS, not as a result of changes in firing rate, but rather due to its ability to replace pathological low-frequency network oscillations with a regularized pattern of neuronal firing.

Regularization and renormalization of quantum field theory in curved space-time

International Nuclear Information System (INIS)

Bernard, C.; Duncan, A.

1977-01-01

It is proposed that field theories quantized in a curved space-time manifold can be conveniently regularized and renormalized with the aid of Pauli-Villars regulator fields. The method avoids the conceptual difficulties of covariant point-separation approaches, by starting always from a manifestly generally covariant action, and the technical limitations of the dimensional reqularization approach, which requires solution of the theory in arbitrary dimension in order to go beyond a weak-field expansion. An action is constructed which renormalizes the weak-field perturbation theory of a massive scalar field in two space-time dimensions--it is shown that the trace anomaly previously found in dimensional regularization and some point-separation calculations also arises in perturbation theory when the theory is Pauli-Villars regulated. One then studies a specific solvable two-dimensional model of a massive scalar field in a Robertson-Walker asymptotically flat universe. It is shown that the action previously considered leads, in this model, to a well defined finite expectation value for the stress-energy tensor. The particle production (less than 0 in/vertical bar/theta/sup mu nu/(x,t)/vertical bar/0 in greater than for t → + infinity) is computed explicitly. Finally, the validity of weak-field perturbation theory (in the appropriate range of parameters) is checked directly in the solvable model, and the trace anomaly computed in the asymptotic regions t→ +- infinity independently of any weak field approximation. The extension of the model to higher dimensions and the renormalization of interacting (scalar) field theories are briefly discussed

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

Science.gov (United States)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

The Accuracy of Remapping Irregularly Spaced Velocity Data onto a Regular Grid and the Computation of Vorticity

National Research Council Canada - National Science Library

Cohn, R

1998-01-01

.... This technique may be viewed as the molecular counterpart of PIV. To take advantage of standard data processing techniques, the MTV data need to be remapped onto a regular grid with a uniform spacing...

The Accuracy of Remapping Irregularly Spaced Velocity Data onto a Regular Grid and the Computation of Vorticity

National Research Council Canada - National Science Library

Cohn, Richard

1999-01-01

.... This technique may be viewed as the molecular counterpart of PIV. To take advantage of standard data processing techniques, the MTV data need to be remapped onto a regular grid with a uniform spacing...

Regularity of difference equations on Banach spaces

CERN Document Server

Agarwal, Ravi P; Lizama, Carlos

2014-01-01

This work introduces readers to the topic of maximal regularity for difference equations. The authors systematically present the method of maximal regularity, outlining basic linear difference equations along with relevant results. They address recent advances in the field, as well as basic semigroup and cosine operator theories in the discrete setting. The authors also identify some open problems that readers may wish to take up for further research. This book is intended for graduate students and researchers in the area of difference equations, particularly those with advance knowledge of and interest in functional analysis.

On RC-spaces

OpenAIRE

Bielas, Wojciech; Plewik, Szymon

2018-01-01

Following Frink's characterization of completely regular spaces, we say that a regular T_1-space is an RC-space whenever the family of all regular open sets constitutes a regular normal base. Normal spaces are RC-spaces and there exist completely regular spaces which are not RC-spaces. So the question arises, which of the known examples of completely regular and not normal spaces are RC-spaces. We show that the Niemytzki plane and the Sorgenfrey plane are RC-spaces.

Metric regularity and subdifferential calculus

International Nuclear Information System (INIS)

Ioffe, A D

2000-01-01

The theory of metric regularity is an extension of two classical results: the Lyusternik tangent space theorem and the Graves surjection theorem. Developments in non-smooth analysis in the 1980s and 1990s paved the way for a number of far-reaching extensions of these results. It was also well understood that the phenomena behind the results are of metric origin, not connected with any linear structure. At the same time it became clear that some basic hypotheses of the subdifferential calculus are closely connected with the metric regularity of certain set-valued maps. The survey is devoted to the metric theory of metric regularity and its connection with subdifferential calculus in Banach spaces

Regularity criterion for solutions to the Navier Stokes equations in the whole 3D space based on two vorticity components

Czech Academy of Sciences Publication Activity Database

Guo, Z.; Kučera, P.; Skalák, Zdeněk

2018-01-01

Roč. 458, č. 1 (2018), s. 755-766 ISSN 0022-247X R&D Projects: GA ČR GA13-00522S Institutional support: RVO:67985874 Keywords : Navier Stokes equations * conditional regularity * regularity criteria * vorticity * Besov spaces * bony decomposition Subject RIV: BA - General Mathematics OBOR OECD: Fluids and plasma physics (including surface physics) Impact factor: 1.064, year: 2016

Continuum-regularized quantum gravity

International Nuclear Information System (INIS)

Chan Huesum; Halpern, M.B.

1987-01-01

The recent continuum regularization of d-dimensional Euclidean gravity is generalized to arbitrary power-law measure and studied in some detail as a representative example of coordinate-invariant regularization. The weak-coupling expansion of the theory illustrates a generic geometrization of regularized Schwinger-Dyson rules, generalizing previous rules in flat space and flat superspace. The rules are applied in a non-trivial explicit check of Einstein invariance at one loop: the cosmological counterterm is computed and its contribution is included in a verification that the graviton mass is zero. (orig.)

Frozen-thawed embryo transfer in a natural or mildly hormonally stimulated cycle in women with regular ovulatory cycles: a RCT.

Science.gov (United States)

Peeraer, Karen; Couck, Isabelle; Debrock, Sophie; De Neubourg, Diane; De Loecker, Peter; Tomassetti, Carla; Laenen, Annouschka; Welkenhuysen, Myriam; Meeuwis, Luc; Pelckmans, Sofie; Meuleman, Christel; D'Hooghe, Thomas

2015-11-01

Can ovarian stimulation with low dose hMG improve the implantation rate (IR) per frozen-thawed embryo transferred (FET) when compared with natural cycle in an FET programme in women with a regular ovulatory cycle? Both IR and live birth rate (LBR) per FET were similar in the group with mild ovarian stimulation and the natural cycle group. Different cycle regimens for endometrial preparation are used prior to FET: spontaneous ovulatory cycles, cycles with artificial endometrial preparation using estrogen and progesterone hormones, and cycles stimulated with gonadotrophins or clomiphene citrate. At present, it is not clear which regimen results in the highest IR or LBR. More specifically, there are no RCTs in ovulatory women comparing reproductive outcome after FET during a natural cycle and during a hormonally stimulated cycle. A total of 410 women scheduled for FET during 579 cycles (December 2003-September 2013) were enrolled in an open-label RCT to natural cycle (NC FET group, n = 291) or to a cycle hormonally stimulated with s.c. gonadotrophins (hMG FET group, 37.5-75 IU per day, n = 288). A total of 672 embryos were transferred during 434 cycles (332 embryos and 213 cycles in the NC FET group; 340 embryos and 221 cycles in the hMG FET group). Assuming a = 0.05 and 80% power, it was calculated that 219 frozen-thawed embryos were required for transfer in each group to demonstrate a difference of 10% in IR. Women were eligible according to the following inclusion criteria: regular ovulatory cycle, female age ≥21 years and ≤45 years, informed consent. FET cycles with preimplantation genetic screening were excluded. The primary outcome was IR per embryo transferred. Secondary outcomes included IR with fetal heart beat (FHB), LBR per embryo transferred and endometrial thickness on the day of hCG administration. Statistical analysis was by intention to treat and controlled for the presence of multiple measures, as eligible women could be randomized in more than

Self-calibration for lab-μCT using space-time regularized projection-based DVC and model reduction

Science.gov (United States)

Jailin, C.; Buljac, A.; Bouterf, A.; Poncelet, M.; Hild, F.; Roux, S.

2018-02-01

An online calibration procedure for x-ray lab-CT is developed using projection-based digital volume correlation. An initial reconstruction of the sample is positioned in the 3D space for every angle so that its projection matches the initial one. This procedure allows a space-time displacement field to be estimated for the scanned sample, which is regularized with (i) rigid body motions in space and (ii) modal time shape functions computed using model reduction techniques (i.e. proper generalized decomposition). The result is an accurate identification of the position of the sample adapted for each angle, which may deviate from the desired perfect rotation required for standard reconstructions. An application of this procedure to a 4D in situ mechanical test is shown. The proposed correction leads to a much improved tomographic reconstruction quality.

Plasma instabilities stimulated by HF transmitters in space

International Nuclear Information System (INIS)

Benson, R.F.; Vinas, A.F.

1988-01-01

Diffuse incoherent signal returns are often observed on Alouette and ISIS topside ionograms in addition to coherent echoes of electromagnetic and electrostatic waves. These diffuse signals, which at times can be the dominant features on topside ionograms, have been attributed to sounder-induced temperature anisotropies which drive the Harris instability. Previous theoretical investigations were based on the electrostatic approximation to the dispersion equation. The present paper will present calculations indicating that when the electromagnetic terms are retained in the dispersion equation and when the sounder-stimulated perpendicular electron temperature approaches 1 keV, then the whistler mode can have a temporal growth rate larger than the electrostatic electron cyclotron harmonic wave mode central to the diffuse resonance problem. Present sounders lack the power and antenna lengths to generate whistler mode waves in this manner. In addition, such waves would have large group velocities and would quickly leave the vicinity of the sounder. Experiments to investigate the wave growth, propagation, and damping of such stimulated waves are planned for the 1990s using a highly flexible sounder on the Space Shuttle and a receiver on a subsatellite. 30 references

On the regularity of mild solutions to complete higher order differential equations on Banach spaces

Directory of Open Access Journals (Sweden)

Nezam Iraniparast

2015-09-01

Full Text Available For the complete higher order differential equation u(n(t=Σk=0n-1Aku(k(t+f(t, t∈ R (* on a Banach space E, we give a new definition of mild solutions of (*. We then characterize the regular admissibility of a translation invariant subspace al M of BUC(R, E with respect to (* in terms of solvability of the operator equation Σj=0n-1AjXal Dj-Xal Dn = C. As application, almost periodicity of mild solutions of (* is proved.

The existence and regularity of time-periodic solutions to the three-dimensional Navier–Stokes equations in the whole space

International Nuclear Information System (INIS)

Kyed, Mads

2014-01-01

The existence, uniqueness and regularity of time-periodic solutions to the Navier–Stokes equations in the three-dimensional whole space are investigated. We consider the Navier–Stokes equations with a non-zero drift term corresponding to the physical model of a fluid flow around a body that moves with a non-zero constant velocity. The existence of a strong time-periodic solution is shown for small time-periodic data. It is further shown that this solution is unique in a large class of weak solutions that can be considered physically reasonable. Finally, we establish regularity properties for any strong solution regardless of its size. (paper)

Manifold Regularized Correlation Object Tracking

OpenAIRE

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2017-01-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped fr...

Physical model of dimensional regularization

Energy Technology Data Exchange (ETDEWEB)

Schonfeld, Jonathan F.

2016-12-15

We explicitly construct fractals of dimension 4-ε on which dimensional regularization approximates scalar-field-only quantum-field theory amplitudes. The construction does not require fractals to be Lorentz-invariant in any sense, and we argue that there probably is no Lorentz-invariant fractal of dimension greater than 2. We derive dimensional regularization's power-law screening first for fractals obtained by removing voids from 3-dimensional Euclidean space. The derivation applies techniques from elementary dielectric theory. Surprisingly, fractal geometry by itself does not guarantee the appropriate power-law behavior; boundary conditions at fractal voids also play an important role. We then extend the derivation to 4-dimensional Minkowski space. We comment on generalization to non-scalar fields, and speculate about implications for quantum gravity. (orig.)

Hierarchical regular small-world networks

International Nuclear Information System (INIS)

Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

2008-01-01

Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

Graph Regularized Auto-Encoders for Image Representation.

Science.gov (United States)

Yiyi Liao; Yue Wang; Yong Liu

2017-06-01

Image representation has been intensively explored in the domain of computer vision for its significant influence on the relative tasks such as image clustering and classification. It is valuable to learn a low-dimensional representation of an image which preserves its inherent information from the original image space. At the perspective of manifold learning, this is implemented with the local invariant idea to capture the intrinsic low-dimensional manifold embedded in the high-dimensional input space. Inspired by the recent successes of deep architectures, we propose a local invariant deep nonlinear mapping algorithm, called graph regularized auto-encoder (GAE). With the graph regularization, the proposed method preserves the local connectivity from the original image space to the representation space, while the stacked auto-encoders provide explicit encoding model for fast inference and powerful expressive capacity for complex modeling. Theoretical analysis shows that the graph regularizer penalizes the weighted Frobenius norm of the Jacobian matrix of the encoder mapping, where the weight matrix captures the local property in the input space. Furthermore, the underlying effects on the hidden representation space are revealed, providing insightful explanation to the advantage of the proposed method. Finally, the experimental results on both clustering and classification tasks demonstrate the effectiveness of our GAE as well as the correctness of the proposed theoretical analysis, and it also suggests that GAE is a superior solution to the current deep representation learning techniques comparing with variant auto-encoders and existing local invariant methods.

Geometric regularizations and dual conifold transitions

International Nuclear Information System (INIS)

Landsteiner, Karl; Lazaroiu, Calin I.

2003-01-01

We consider a geometric regularization for the class of conifold transitions relating D-brane systems on noncompact Calabi-Yau spaces to certain flux backgrounds. This regularization respects the SL(2,Z) invariance of the flux superpotential, and allows for computation of the relevant periods through the method of Picard-Fuchs equations. The regularized geometry is a noncompact Calabi-Yau which can be viewed as a monodromic fibration, with the nontrivial monodromy being induced by the regulator. It reduces to the original, non-monodromic background when the regulator is removed. Using this regularization, we discuss the simple case of the local conifold, and show how the relevant field-theoretic information can be extracted in this approach. (author)

Generalization Performance of Regularized Ranking With Multiscale Kernels.

Science.gov (United States)

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Medical back belt with integrated neuromuscular electrical stimulation

NARCIS (Netherlands)

Bottenberg, E. (Eliza); Brinks, G.J. (Ger); Hesse, J. (Jenny)

2014-01-01

The medical back belt with integrated neuromuscular electrical stimulation is anorthopedic device, which has two main functions. The first function is to stimulate the backmuscles by using a neuromuscular electrical stimulation device that releases regular,electrical impulses. The second function of

Application of Fourier-wavelet regularized deconvolution for improving image quality of free space propagation x-ray phase contrast imaging.

Science.gov (United States)

Zhou, Zhongxing; Gao, Feng; Zhao, Huijuan; Zhang, Lixin

2012-11-21

New x-ray phase contrast imaging techniques without using synchrotron radiation confront a common problem from the negative effects of finite source size and limited spatial resolution. These negative effects swamp the fine phase contrast fringes and make them almost undetectable. In order to alleviate this problem, deconvolution procedures should be applied to the blurred x-ray phase contrast images. In this study, three different deconvolution techniques, including Wiener filtering, Tikhonov regularization and Fourier-wavelet regularized deconvolution (ForWaRD), were applied to the simulated and experimental free space propagation x-ray phase contrast images of simple geometric phantoms. These algorithms were evaluated in terms of phase contrast improvement and signal-to-noise ratio. The results demonstrate that the ForWaRD algorithm is most appropriate for phase contrast image restoration among above-mentioned methods; it can effectively restore the lost information of phase contrast fringes while reduce the amplified noise during Fourier regularization.

Stimulating effect of space flight factors on Artemia cysts: comparison with irradiation by gamma rays

International Nuclear Information System (INIS)

Gaubin, Y.; Pianezzi, B.; Gasset, G.; Plannel, H.; Kovalev, E.E.

1986-01-01

The Artemia cyst, a gastrula in dormant state, is a very suitable material to investigate the individual effects of HZE cosmic particles. Monolayers of Artemia cysts, sandwiched with nuclear emulsions, flew aboard the Soviet biosatellite Cosmos 1129. The space flight stimulated the developmental capacity expressed by higher percentages of emergence, hatching, and alive nauplii at day 4-5. A greater mean life span was reported in Artemias developed from Artemia cysts hit by the cosmic heavy ions. On Earth, Artemia cysts were exposed to 1, 10, 100, 200 and 400 Gy of gamma (gamma) rays. A stimulating effect on developmental capacity was observed for 10 Gy; the mean life span was significantly increased for this dose. These results are discussed in comparison with previous investigations performed on Earth and in space

Quantifying uncertainty in Transcranial Magnetic Stimulation - A high resolution simulation study in ICBM space.

Science.gov (United States)

Toschi, Nicola; Keck, Martin E; Welt, Tobias; Guerrisi, Maria

2012-01-01

Transcranial Magnetic Stimulation offers enormous potential for noninvasive brain stimulation. While it is known that brain tissue significantly "reshapes" induced field and charge distributions, most modeling investigations to-date have focused on single-subject data with limited generality. Further, the effects of the significant uncertainties which exist in the simulation (i.e. brain conductivity distributions) and stimulation (e.g. coil positioning and orientations) setup have not been quantified. In this study, we construct a high-resolution anisotropic head model in standard ICBM space, which can be used as a population-representative standard for bioelectromagnetic simulations. Further, we employ Monte-Carlo simulations in order to quantify how uncertainties in conductivity values propagate all the way to induced field and currents, demonstrating significant, regionally dependent dispersions in values which are commonly assumed "ground truth". This framework can be leveraged in order to quantify the effect of any type of uncertainty in noninvasive brain stimulation and bears relevance in all applications of TMS, both investigative and therapeutic.

Regular non-twisting S-branes

International Nuclear Information System (INIS)

Obregon, Octavio; Quevedo, Hernando; Ryan, Michael P.

2004-01-01

We construct a family of time and angular dependent, regular S-brane solutions which corresponds to a simple analytical continuation of the Zipoy-Voorhees 4-dimensional vacuum spacetime. The solutions are asymptotically flat and turn out to be free of singularities without requiring a twist in space. They can be considered as the simplest non-singular generalization of the singular S0-brane solution. We analyze the properties of a representative of this family of solutions and show that it resembles to some extent the asymptotic properties of the regular Kerr S-brane. The R-symmetry corresponds, however, to the general lorentzian symmetry. Several generalizations of this regular solution are derived which include a charged S-brane and an additional dilatonic field. (author)

Manifold Regularized Reinforcement Learning.

Science.gov (United States)

Li, Hongliang; Liu, Derong; Wang, Ding

2018-04-01

This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance.

Matrix regularization of 4-manifolds

OpenAIRE

Trzetrzelewski, M.

2012-01-01

We consider products of two 2-manifolds such as S^2 x S^2, embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)xSU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N^2 x N^2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S...

Regularity and chaos in cavity QED

International Nuclear Information System (INIS)

Bastarrachea-Magnani, Miguel Angel; López-del-Carpio, Baldemar; Chávez-Carlos, Jorge; Lerma-Hernández, Sergio; Hirsch, Jorge G

2017-01-01

The interaction of a quantized electromagnetic field in a cavity with a set of two-level atoms inside it can be described with algebraic Hamiltonians of increasing complexity, from the Rabi to the Dicke models. Their algebraic character allows, through the use of coherent states, a semiclassical description in phase space, where the non-integrable Dicke model has regions associated with regular and chaotic motion. The appearance of classical chaos can be quantified calculating the largest Lyapunov exponent over the whole available phase space for a given energy. In the quantum regime, employing efficient diagonalization techniques, we are able to perform a detailed quantitative study of the regular and chaotic regions, where the quantum participation ratio (P R ) of coherent states on the eigenenergy basis plays a role equivalent to the Lyapunov exponent. It is noted that, in the thermodynamic limit, dividing the participation ratio by the number of atoms leads to a positive value in chaotic regions, while it tends to zero in the regular ones. (paper)

Fast and compact regular expression matching

DEFF Research Database (Denmark)

Bille, Philip; Farach-Colton, Martin

2008-01-01

We study 4 problems in string matching, namely, regular expression matching, approximate regular expression matching, string edit distance, and subsequence indexing, on a standard word RAM model of computation that allows logarithmic-sized words to be manipulated in constant time. We show how...... to improve the space and/or remove a dependency on the alphabet size for each problem using either an improved tabulation technique of an existing algorithm or by combining known algorithms in a new way....

Accreting fluids onto regular black holes via Hamiltonian approach

Energy Technology Data Exchange (ETDEWEB)

Jawad, Abdul [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan); Shahzad, M.U. [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan); University of Central Punjab, CAMS, UCP Business School, Lahore (Pakistan)

2017-08-15

We investigate the accretion of test fluids onto regular black holes such as Kehagias-Sfetsos black holes and regular black holes with Dagum distribution function. We analyze the accretion process when different test fluids are falling onto these regular black holes. The accreting fluid is being classified through the equation of state according to the features of regular black holes. The behavior of fluid flow and the existence of sonic points is being checked for these regular black holes. It is noted that the three-velocity depends on critical points and the equation of state parameter on phase space. (orig.)

Defensive peripersonal space: the blink reflex evoked by hand stimulation is increased when the hand is near the face.

Science.gov (United States)

Sambo, C F; Liang, M; Cruccu, G; Iannetti, G D

2012-02-01

Electrical stimulation of the median nerve at the wrist may elicit a blink reflex [hand blink reflex (HBR)] mediated by a neural circuit at brain stem level. As, in a Sherringtonian sense, the blink reflex is a defensive response, in a series of experiments we tested, in healthy volunteers, whether and how the HBR is modulated by the proximity of the stimulated hand to the face. Electromyographic activity was recorded from the orbicularis oculi, bilaterally. We observed that the HBR is enhanced when the stimulated hand is inside the peripersonal space of the face, compared with when it is outside, irrespective of whether the proximity of the hand to the face is manipulated by changing the position of the arm (experiment 1) or by rotating the head while keeping the arm position constant (experiment 3). Experiment 2 showed that such HBR enhancement has similar magnitude when the participants have their eyes closed. Experiments 4 and 5 showed, respectively, that the blink reflex elicited by the electrical stimulation of the supraorbital nerve, as well as the N20 wave of the somatosensory evoked potentials elicited by the median nerve stimulation, are entirely unaffected by hand position. Taken together, our results provide compelling evidence that the brain stem circuits mediating the HBR in humans undergo tonic and selective top-down modulation from higher order cortical areas responsible for encoding the location of somatosensory stimuli in external space coordinates. These findings support the existence of a "defensive" peripersonal space, representing a safety margin advantageous for survival.

Manifold Regularized Correlation Object Tracking.

Science.gov (United States)

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Shao, Ling

2018-05-01

In this paper, we propose a manifold regularized correlation tracking method with augmented samples. To make better use of the unlabeled data and the manifold structure of the sample space, a manifold regularization-based correlation filter is introduced, which aims to assign similar labels to neighbor samples. Meanwhile, the regression model is learned by exploiting the block-circulant structure of matrices resulting from the augmented translated samples over multiple base samples cropped from both target and nontarget regions. Thus, the final classifier in our method is trained with positive, negative, and unlabeled base samples, which is a semisupervised learning framework. A block optimization strategy is further introduced to learn a manifold regularization-based correlation filter for efficient online tracking. Experiments on two public tracking data sets demonstrate the superior performance of our tracker compared with the state-of-the-art tracking approaches.

UNFOLDED REGULAR AND SEMI-REGULAR POLYHEDRA

Directory of Open Access Journals (Sweden)

IONIŢĂ Elena

2015-06-01

Full Text Available This paper proposes a presentation unfolding regular and semi-regular polyhedra. Regular polyhedra are convex polyhedra whose faces are regular and equal polygons, with the same number of sides, and whose polyhedral angles are also regular and equal. Semi-regular polyhedra are convex polyhedra with regular polygon faces, several types and equal solid angles of the same type. A net of a polyhedron is a collection of edges in the plane which are the unfolded edges of the solid. Modeling and unfolding Platonic and Arhimediene polyhedra will be using 3dsMAX program. This paper is intended as an example of descriptive geometry applications.

The geometric $\\beta$-function in curved space-time under operator regularization

OpenAIRE

Agarwala, Susama

2009-01-01

In this paper, I compare the generators of the renormalization group flow, or the geometric $\\beta$-functions for dimensional regularization and operator regularization. I then extend the analysis to show that the geometric $\\beta$-function for a scalar field theory on a closed compact Riemannian manifold is defined on the entire manifold. I then extend the analysis to find the generator of the renormalization group flow for a conformal scalar-field theories on the same manifolds. The geometr...

Variational analysis of regular mappings theory and applications

CERN Document Server

Ioffe, Alexander D

2017-01-01

This monograph offers the first systematic account of (metric) regularity theory in variational analysis. It presents new developments alongside classical results and demonstrates the power of the theory through applications to various problems in analysis and optimization theory. The origins of metric regularity theory can be traced back to a series of fundamental ideas and results of nonlinear functional analysis and global analysis centered around problems of existence and stability of solutions of nonlinear equations. In variational analysis, regularity theory goes far beyond the classical setting and is also concerned with non-differentiable and multi-valued operators. The present volume explores all basic aspects of the theory, from the most general problems for mappings between metric spaces to those connected with fairly concrete and important classes of operators acting in Banach and finite dimensional spaces. Written by a leading expert in the field, the book covers new and powerful techniques, whic...

Temporally Regular Musical Primes Facilitate Subsequent Syntax Processing in Children with Specific Language Impairment.

Science.gov (United States)

Bedoin, Nathalie; Brisseau, Lucie; Molinier, Pauline; Roch, Didier; Tillmann, Barbara

2016-01-01

Children with developmental language disorders have been shown to be also impaired in rhythm and meter perception. Temporal processing and its link to language processing can be understood within the dynamic attending theory. An external stimulus can stimulate internal oscillators, which orient attention over time and drive speech signal segmentation to provide benefits for syntax processing, which is impaired in various patient populations. For children with Specific Language Impairment (SLI) and dyslexia, previous research has shown the influence of an external rhythmic stimulation on subsequent language processing by comparing the influence of a temporally regular musical prime to that of a temporally irregular prime. Here we tested whether the observed rhythmic stimulation effect is indeed due to a benefit provided by the regular musical prime (rather than a cost subsequent to the temporally irregular prime). Sixteen children with SLI and 16 age-matched controls listened to either a regular musical prime sequence or an environmental sound scene (without temporal regularities in event occurrence; i.e., referred to as "baseline condition") followed by grammatically correct and incorrect sentences. They were required to perform grammaticality judgments for each auditorily presented sentence. Results revealed that performance for the grammaticality judgments was better after the regular prime sequences than after the baseline sequences. Our findings are interpreted in the theoretical framework of the dynamic attending theory (Jones, 1976) and the temporal sampling (oscillatory) framework for developmental language disorders (Goswami, 2011). Furthermore, they encourage the use of rhythmic structures (even in non-verbal materials) to boost linguistic structure processing and outline perspectives for rehabilitation.

Stimulation of Executive Functions as Part of the Language Intervention Process in Children with Autism Spectrum Disorder.

Science.gov (United States)

Sun, Ingrid Ya I; Varanda, Cristina Andrade; Fernandes, Fernanda Dreux

2017-01-01

Identifying effective methods for stimulating language and communication of children with autism spectrum disorder (ASD) is fundamental to the effective use of available resources to support these children. This pilot study was designed to explore the potential benefits of a program of stimulation of executive functions (SEF) on the functional aspects of language and communication through the assessment of the functional communicative profile and social-cognitive performance. Twenty children, aged 5-12 years, with a diagnosis of ASD participated in the study. Two stimulation programs were offered over a 10- to 12-week period as part of the regular services offered to these children through a University's speech and language therapy outpatient clinic in São Paulo, Brazil. Children either received SEF intervention in their home implemented by their parent/s, with close monitoring by the speech-language pathologist (SLP) (group 1), or they received SEF by the SLP during regular speech-language therapy individual sessions (group 2). The findings suggested that there were differences between the children's pre- and posttest performance. Significantly different performances were observed in the areas of occupation of communication space, proportion of communicative interactivity, and social-cognitive performance. The inclusion of activities to stimulate executive function abilities in language intervention for children with ASD warrants further investigation. © 2017 S. Karger AG, Basel.

Regular Exercise Enhances the Immune Response Against Microbial Antigens Through Up-Regulation of Toll-like Receptor Signaling Pathways

Directory of Open Access Journals (Sweden)

Qishi Zheng

2015-09-01

Full Text Available Background/Aims: Regular physical exercise can enhance resistance to many microbial infections. However, little is known about the mechanism underlying the changes in the immune system induced by regular exercise. Methods: We recruited members of a university badminton club as the regular exercise (RE group and healthy sedentary students as the sedentary control (SC group. We investigated the distribution of peripheral blood mononuclear cell (PBMC subsets and functions in the two groups. Results: There were no significant differences in plasma cytokine levels between the RE and SC groups in the true resting state. However, enhanced levels of IFN-γ, TNF-α, IL-6, IFN-α and IL-12 were secreted by PBMCs in the RE group following microbial antigen stimulation, when compared to the SC group. In contrast, the levels of TNF-α and IL-6 secreted by PBMC in the RE group were suppressed compared with those in SC group following non-microbial antigen stimulation (concanavalin A or α-galactosylceramide. Furthermore, PBMC expression of TLR2, TLR7 and MyD88 was significantly increased in the RE group in response to microbial antigen stimulation. Conclusion: Regular exercise enhances immune cell activation in response to pathogenic stimulation leading to enhanced cytokine production mediated via the TLR signaling pathways.

The geometric β-function in curved space-time under operator regularization

Energy Technology Data Exchange (ETDEWEB)

Agarwala, Susama [Mathematical Institute, Oxford University, Oxford OX2 6GG (United Kingdom)

2015-06-15

In this paper, I compare the generators of the renormalization group flow, or the geometric β-functions, for dimensional regularization and operator regularization. I then extend the analysis to show that the geometric β-function for a scalar field theory on a closed compact Riemannian manifold is defined on the entire manifold. I then extend the analysis to find the generator of the renormalization group flow to conformally coupled scalar-field theories on the same manifolds. The geometric β-function in this case is not defined.

The geometric β-function in curved space-time under operator regularization

International Nuclear Information System (INIS)

Agarwala, Susama

2015-01-01

In this paper, I compare the generators of the renormalization group flow, or the geometric β-functions, for dimensional regularization and operator regularization. I then extend the analysis to show that the geometric β-function for a scalar field theory on a closed compact Riemannian manifold is defined on the entire manifold. I then extend the analysis to find the generator of the renormalization group flow to conformally coupled scalar-field theories on the same manifolds. The geometric β-function in this case is not defined

Partial Regularity for Holonomic Minimisers of Quasiconvex Functionals

Science.gov (United States)

Hopper, Christopher P.

2016-10-01

We prove partial regularity for local minimisers of certain strictly quasiconvex integral functionals, over a class of Sobolev mappings into a compact Riemannian manifold, to which such mappings are said to be holonomically constrained. Our approach uses the lifting of Sobolev mappings to the universal covering space, the connectedness of the covering space, an application of Ekeland's variational principle and a certain tangential A-harmonic approximation lemma obtained directly via a Lipschitz approximation argument. This allows regularity to be established directly on the level of the gradient. Several applications to variational problems in condensed matter physics with broken symmetries are also discussed, in particular those concerning the superfluidity of liquid helium-3 and nematic liquid crystals.

Application of a rat hindlimb model: a prediction of force spaces reachable through stimulation of nerve fascicles.

Science.gov (United States)

Johnson, Will L; Jindrich, Devin L; Zhong, Hui; Roy, Roland R; Edgerton, V Reggie

2011-12-01

A device to generate standing or locomotion through chronically placed electrodes has not been fully developed due in part to limitations of clinical experimentation and the high number of muscle activation inputs of the leg. We investigated the feasibility of functional electrical stimulation paradigms that minimize the input dimensions for controlling the limbs by stimulating at nerve fascicles, utilizing a model of the rat hindlimb, which combined previously collected morphological data with muscle physiological parameters presented herein. As validation of the model, we investigated the suitability of a lumped-parameter model for the prediction of muscle activation during dynamic tasks. Using the validated model, we found that the space of forces producible through activation of muscle groups sharing common nerve fascicles was nonlinearly dependent on the number of discrete muscle groups that could be individually activated (equivalently, the neuroanatomical level of activation). Seven commonly innervated muscle groups were sufficient to produce 78% of the force space producible through individual activation of the 42 modeled hindlimb muscles. This novel, neuroanatomically derived reduction in input dimension emphasizes the potential to simplify controllers for functional electrical stimulation to improve functional recovery after a neuromuscular injury.

Consistent momentum space regularization/renormalization of supersymmetric quantum field theories: the three-loop β-function for the Wess-Zumino model

International Nuclear Information System (INIS)

Carneiro, David; Sampaio, Marcos; Nemes, Maria Carolina; Scarpelli, Antonio Paulo Baeta

2003-01-01

We compute the three loop β function of the Wess-Zumino model to motivate implicit regularization (IR) as a consistent and practical momentum-space framework to study supersymmetric quantum field theories. In this framework which works essentially in the physical dimension of the theory we show that ultraviolet are clearly disentangled from infrared divergences. We obtain consistent results which motivate the method as a good choice to study supersymmetry anomalies in quantum field theories. (author)

Matrix regularization of embedded 4-manifolds

International Nuclear Information System (INIS)

Trzetrzelewski, Maciej

2012-01-01

We consider products of two 2-manifolds such as S 2 ×S 2 , embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)⊗SU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N 2 ×N 2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S 3 also possible).

THE REGULARITIES OF THE SPACE-TEMPORAL DISTRIBUTION OF THE RADIATION BALANCE OF THE UNDERLYING SURFACE IN ARAKS BASIN ON MOUNTAINOUS TERRITORY OF THE REPUBLIC OF ARMENIA

Directory of Open Access Journals (Sweden)

V. G. Margaryan

2017-12-01

Full Text Available The regularities of the space-temporal distribution of the radiation balance of the underlying surface for the conditions of the mountainous territory of the Republic of Armenia were discussed and analyzed.

Generalized Bregman distances and convergence rates for non-convex regularization methods

International Nuclear Information System (INIS)

Grasmair, Markus

2010-01-01

We generalize the notion of Bregman distance using concepts from abstract convexity in order to derive convergence rates for Tikhonov regularization with non-convex regularization terms. In particular, we study the non-convex regularization of linear operator equations on Hilbert spaces, showing that the conditions required for the application of the convergence rates results are strongly related to the standard range conditions from the convex case. Moreover, we consider the setting of sparse regularization, where we show that a rate of order δ 1/p holds, if the regularization term has a slightly faster growth at zero than |t| p

Perceptual Spaces Induced by Cochlear Implant All-Polar Stimulation Mode

DEFF Research Database (Denmark)

Marozeau, Jeremy; McKay, Colette M

2016-01-01

sequentially or simultaneously. The dissimilarity ratings were analyzed using a multidimensional scaling technique and three-dimensional stimulus perceptual spaces were produced. For all the conditions (mode and simultaneity), the first perceptual dimension was highly correlated with the position of the most...... apical activated electrode of the electrical stimulation and the second dimension with the position of the most basal electrode. In both sequential and simultaneous conditions, the monopolar and all-polar stimuli were significantly separated by a third dimension, which may indicate that all-polar stimuli....... It was designed to activate all the electrodes simultaneously with appropriate current levels and polarities to recruit narrower regions of auditory nerves at specific intracochlear electrode positions (denoted all-polar electrodes). In this study, the all-polar mode was compared with the current commercial...

Lavrentiev regularization method for nonlinear ill-posed problems

International Nuclear Information System (INIS)

Kinh, Nguyen Van

2002-10-01

In this paper we shall be concerned with Lavientiev regularization method to reconstruct solutions x 0 of non ill-posed problems F(x)=y o , where instead of y 0 noisy data y δ is an element of X with absolut(y δ -y 0 ) ≤ δ are given and F:X→X is an accretive nonlinear operator from a real reflexive Banach space X into itself. In this regularization method solutions x α δ are obtained by solving the singularly perturbed nonlinear operator equation F(x)+α(x-x*)=y δ with some initial guess x*. Assuming certain conditions concerning the operator F and the smoothness of the element x*-x 0 we derive stability estimates which show that the accuracy of the regularized solutions is order optimal provided that the regularization parameter α has been chosen properly. (author)

Regular Gleason Measures and Generalized Effect Algebras

Science.gov (United States)

Dvurečenskij, Anatolij; Janda, Jiří

2015-12-01

We study measures, finitely additive measures, regular measures, and σ-additive measures that can attain even infinite values on the quantum logic of a Hilbert space. We show when particular classes of non-negative measures can be studied in the frame of generalized effect algebras.

A multiresolution method for solving the Poisson equation using high order regularization

DEFF Research Database (Denmark)

Hejlesen, Mads Mølholm; Walther, Jens Honore

2016-01-01

We present a novel high order multiresolution Poisson solver based on regularized Green's function solutions to obtain exact free-space boundary conditions while using fast Fourier transforms for computational efficiency. Multiresolution is a achieved through local refinement patches and regulari......We present a novel high order multiresolution Poisson solver based on regularized Green's function solutions to obtain exact free-space boundary conditions while using fast Fourier transforms for computational efficiency. Multiresolution is a achieved through local refinement patches...... and regularized Green's functions corresponding to the difference in the spatial resolution between the patches. The full solution is obtained utilizing the linearity of the Poisson equation enabling super-position of solutions. We show that the multiresolution Poisson solver produces convergence rates...

Diverse Regular Employees and Non-regular Employment (Japanese)

OpenAIRE

MORISHIMA Motohiro

2011-01-01

Currently there are high expectations for the introduction of policies related to diverse regular employees. These policies are a response to the problem of disparities between regular and non-regular employees (part-time, temporary, contract and other non-regular employees) and will make it more likely that workers can balance work and their private lives while companies benefit from the advantages of regular employment. In this paper, I look at two issues that underlie this discussion. The ...

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

Science.gov (United States)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Regularity criteria for incompressible magnetohydrodynamics equations in three dimensions

International Nuclear Information System (INIS)

Lin, Hongxia; Du, Lili

2013-01-01

In this paper, we give some new global regularity criteria for three-dimensional incompressible magnetohydrodynamics (MHD) equations. More precisely, we provide some sufficient conditions in terms of the derivatives of the velocity or pressure, for the global regularity of strong solutions to 3D incompressible MHD equations in the whole space, as well as for periodic boundary conditions. Moreover, the regularity criterion involving three of the nine components of the velocity gradient tensor is also obtained. The main results generalize the recent work by Cao and Wu (2010 Two regularity criteria for the 3D MHD equations J. Diff. Eqns 248 2263–74) and the analysis in part is based on the works by Cao C and Titi E (2008 Regularity criteria for the three-dimensional Navier–Stokes equations Indiana Univ. Math. J. 57 2643–61; 2011 Gobal regularity criterion for the 3D Navier–Stokes equations involving one entry of the velocity gradient tensor Arch. Rational Mech. Anal. 202 919–32) for 3D incompressible Navier–Stokes equations. (paper)

Regular black hole in three dimensions

OpenAIRE

Myung, Yun Soo; Yoon, Myungseok

2008-01-01

We find a new black hole in three dimensional anti-de Sitter space by introducing an anisotropic perfect fluid inspired by the noncommutative black hole. This is a regular black hole with two horizons. We compare thermodynamics of this black hole with that of non-rotating BTZ black hole. The first-law of thermodynamics is not compatible with the Bekenstein-Hawking entropy.

[Effect of axial stress stimulation on tibial and fibular open fractures healing after Taylor space stent fixation].

Science.gov (United States)

Ge, Qihang; Wan, Chunyou; Liu, Yabei; Ji, Xu; Ma, Jihai; Cao, Haikun; Yong, Wei; Liu, Zhao; Zhang, Ningning

2017-08-01

To investigate the effect of axial stress stimulation on tibial and fibular open fractures healing after Taylor space stent fixation. The data of 45 cases with tibial and fibular open fractures treated by Taylor space stent fixation who meet the selection criteria between January 2015 and June 2016 were retrospectively analysed. The patients were divided into trial group (23 cases) and control group (22 cases) according to whether the axial stress stimulation was performed after operation. There was no significant difference in gender, age, affected side, cause of injury, type of fracture, and interval time from injury to operation between 2 groups ( P >0.05). The axial stress stimulation was performed in trial group after operation. The axial load sharing ratio was tested, and when the value was less than 10%, the external fixator was removed. The fracture healing time, full weight-bearing time, and external fixator removal time were recorded and compared. After 6 months of external fixator removal, the function of the limb was assessed by Johner-Wruhs criteria for evaluation of final effectiveness of treatment of tibial shaft fractures. There were 2 and 3 cases of needle foreign body reaction in trial group and control group, respectively, and healed after symptomatic anti allergic treatment. All the patients were followed up 8-12 months with an average of 10 months. All the fractures reached clinical healing, no complication such as delayed union, nonunion, or osteomyelitis occurred. The fracture healing time, full weight-bearing time, and external fixator removal time in trial group were significantly shorter than those in control group ( P good in 6 cases, fair in 3 cases, and poor in 1 case in trial group, with an excellent and good rate of 82.6%; and was excellent in 5 cases, good in 10 cases, fair in 4 cases, and poor in 3 cases in control group, with an excellent and good rate of 68.2%, showing significant difference between 2 groups ( Z =-2.146, P =0

A low-cost multichannel wireless neural stimulation system for freely roaming animals

Science.gov (United States)

Alam, Monzurul; Chen, Xi; Fernandez, Eduardo

2013-12-01

Objectives. Electrical stimulation of nerve tissue and recording of neural activity are the basis of many therapies and neural prostheses. Conventional stimulation systems have a number of practical limitations, especially in experiments involving freely roaming subjects. Our main objective was to develop a modular, versatile and inexpensive multichannel wireless system able to overcome some of these constraints. Approach. We have designed and implemented a new multichannel wireless neural stimulator based on commercial components. The system is small (2 cm × 4 cm × 0.5 cm) and light in weight (9 g) which allows it to be easily carried in a small backpack. To test and validate the performance and reliability of the whole system we conducted several bench tests and in vivo experiments. Main results. The performance and accuracy of the stimulator were comparable to commercial threaded systems. Stimulation sequences can be constructed on-the-fly with 251 selectable current levels (from 0 to 250 µA) with 1 µA step resolution. The pulse widths and intervals can be as long as 65 ms in 2 µs time resolution. The system covers approximately 10 m of transmission range in a regular laboratory environment and 100 m in free space (line of sight). Furthermore it provides great flexibility for experiments since it allows full control of the stimulator and the stimulation parameters in real time. When there is no stimulation, the device automatically goes into low-power sleep mode to preserve battery power. Significance. We introduce the design of a powerful multichannel wireless stimulator assembled from commercial components. Key features of the system are their reliability, robustness and small size. The system has a flexible design that can be modified straightforwardly to tailor it to any specific experimental need. Furthermore it can be effortlessly adapted for use with any kind of multielectrode arrays.

Dimensional versus lattice regularization within Luescher's Yang Mills theory

International Nuclear Information System (INIS)

Diekmann, B.; Langer, M.; Schuette, D.

1993-01-01

It is pointed out that the coefficients of Luescher's effective model space Hamiltonian, which is based upon dimensional regularization techniques, can be reproduced by applying folded diagram perturbation theory to the Kogut Susskind Hamiltonian and by performing a lattice continuum limit (keeping the volume fixed). Alternative cutoff regularizations of the Hamiltonian are in general inconsistent, the critical point beeing the correct prediction for Luescher's tadpole coefficient which is formally quadratically divergent and which has to become a well defined (negative) number. (orig.)

Regularization and asymptotic expansion of certain distributions defined by divergent series

Directory of Open Access Journals (Sweden)

Ricardo Estrada

1995-01-01

Full Text Available The regularization of the distribution ∑n=−∞∞δ(x−pn. which gives a regularized value to the divergent series ∑n=−∞∞φ(pn is obtained in several spaces of test functions. The asymptotic expansion as ϵ→0+of series of the type ∑n=0∞φ(ϵ pn is also obtained.

The inclusion of pupils with special educational needs in Early Stimulation age into the regular classroom environment, at Nursery Schools, of an average municipality Vale dos Sinos

Directory of Open Access Journals (Sweden)

Luciana Cátia Loose Pereira

2012-03-01

Full Text Available Inclusive education in Brazil has been widely discussed in all areas of the educational. The inclusion of pupils with special educational needs (SEN in mainstream schools is increasingly frequent, though still many aspects need to be rethought. This work aimed at checking how the subjects with SEN in Early Stimulation age, from zero to three years and 11 months are included into the regular classroom environment, at Nursery Schools, of an average municipality - Vale dos Sinos. This work involved a cross-sectional survey of quantitative and descriptive statistics. The data collection was carried out directly from a structured questionnaire with open and closed questions, directed to all principals of the thirteen Nursery Schools in the referred municipality. From the thirteen schools of the municipality only one did not take part of the research since there was no enrollment of children with special needs there, totalizing 46 children in processes of educational inclusion. From those, twelve children (26.8% were benefited with an Early Stimulation service maintained by the Association of Parents and Friends of Exceptional Children of that referred municipality, Thirty children (65,2% enrolled in school at the initiative of his own family e four children (8% by intervention of the Wakefield council. In this sense, we believe that the professionals of the Early Stimulation have the responsibility of promoting and conveying its importance and, mainly, the benefits of Early Stimulation for the whole development of individuals, as well as its contribution to a process of inclusive education.

Simulation of Canopy CO2/H2O Fluxes for a Rubber (Hevea Brasiliensis) Plantation in Central Cambodia: The Effect of the Regular Spacing of Planted Trees

Energy Technology Data Exchange (ETDEWEB)

Kumagai, Tomo' omi; Mudd, Ryan; Miyazawa, Yoshiyuki; Liu, Wen; Giambelluca, Thomas; Kobayashi, N.; Lim, Tiva Khan; Jomura, Mayuko; Matsumoto, Kazuho; Huang, Maoyi; Chen, Qi; Ziegler, Alan; Yin, Song

2013-09-10

We developed a soil-vegetation-atmosphere transfer (SVAT) model applicable to simulating CO2 and H2O fluxes from the canopies of rubber plantations, which are characterized by distinct canopy clumping produced by regular spacing of plantation trees. Rubber (Hevea brasiliensis Müll. Arg.) plantations, which are rapidly expanding into both climatically optimal and sub-optimal environments throughout mainland Southeast Asia, potentially change the partitioning of water, energy, and carbon at multiple scales, compared with traditional land covers it is replacing. Describing the biosphere-atmosphere exchange in rubber plantations via SVAT modeling is therefore essential to understanding the impacts on environmental processes. The regular spacing of plantation trees creates a peculiar canopy structure that is not well represented in most SVAT models, which generally assumes a non-uniform spacing of vegetation. Herein we develop a SVAT model applicable to rubber plantation and an evaluation method for its canopy structure, and examine how the peculiar canopy structure of rubber plantations affects canopy CO2 and H2O exchanges. Model results are compared with measurements collected at a field site in central Cambodia. Our findings suggest that it is crucial to account for intensive canopy clumping in order to reproduce observed rubber plantation fluxes. These results suggest a potentially optimal spacing of rubber trees to produce high productivity and water use efficiency.

Regular graph construction for semi-supervised learning

International Nuclear Information System (INIS)

Vega-Oliveros, Didier A; Berton, Lilian; Eberle, Andre Mantini; Lopes, Alneu de Andrade; Zhao, Liang

2014-01-01

Semi-supervised learning (SSL) stands out for using a small amount of labeled points for data clustering and classification. In this scenario graph-based methods allow the analysis of local and global characteristics of the available data by identifying classes or groups regardless data distribution and representing submanifold in Euclidean space. Most of methods used in literature for SSL classification do not worry about graph construction. However, regular graphs can obtain better classification accuracy compared to traditional methods such as k-nearest neighbor (kNN), since kNN benefits the generation of hubs and it is not appropriate for high-dimensionality data. Nevertheless, methods commonly used for generating regular graphs have high computational cost. We tackle this problem introducing an alternative method for generation of regular graphs with better runtime performance compared to methods usually find in the area. Our technique is based on the preferential selection of vertices according some topological measures, like closeness, generating at the end of the process a regular graph. Experiments using the global and local consistency method for label propagation show that our method provides better or equal classification rate in comparison with kNN

Regularity of p(ṡ)-superharmonic functions, the Kellogg property and semiregular boundary points

Science.gov (United States)

Adamowicz, Tomasz; Björn, Anders; Björn, Jana

2014-11-01

We study various boundary and inner regularity questions for $p(\\cdot)$-(super)harmonic functions in Euclidean domains. In particular, we prove the Kellogg property and introduce a classification of boundary points for $p(\\cdot)$-harmonic functions into three disjoint classes: regular, semiregular and strongly irregular points. Regular and especially semiregular points are characterized in many ways. The discussion is illustrated by examples. Along the way, we present a removability result for bounded $p(\\cdot)$-harmonic functions and give some new characterizations of $W^{1, p(\\cdot)}_0$ spaces. We also show that $p(\\cdot)$-superharmonic functions are lower semicontinuously regularized, and characterize them in terms of lower semicontinuously regularized supersolutions.

Effects of Subthalamic and Nigral Stimulation on Gait Kinematics in Parkinson’s Disease

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Marlieke Scholten

2017-10-01

Full Text Available Conventional subthalamic deep brain stimulation for Parkinson’s disease (PD presumably modulates the spatial component of gait. However, temporal dysregulation of gait is one of the factors that is tightly associated with freezing of gait (FOG. Temporal locomotor integration may be modulated differentially at distinct levels of the basal ganglia. Owing to its specific descending brainstem projections, stimulation of the substantia nigra pars reticulata (SNr area might modulate spatial and temporal parameters of gait differentially compared to standard subthalamic nucleus (STN stimulation. Here, we aimed to characterize the differential effect of STN or SNr stimulation on kinematic gait parameters. We analyzed biomechanical parameters during unconstrained over ground walking in 12 PD patients with subthalamic deep brain stimulation and FOG. Patients performed walking in three therapeutic conditions: (i Off stimulation, (ii STN stimulation (alone, and (iii SNr stimulation (alone. SNr stimulation was achieved by stimulating the most caudal contact of the electrode. We recorded gait using three sensors (each containing a tri-axial accelerometer, gyroscope, and magnetometer attached on both left and right ankle, and to the lumbar spine. STN stimulation improved both the spatial features (stride length, stride length variability and the temporal parameters of gait. SNr stimulation improved temporal parameters of gait (swing time asymmetry. Correlation analysis suggested that patients with more medial localization of the SNr contact associated with a stronger regularization of gait. These results suggest that SNr stimulation might support temporal regularization of gait integration.

Evaluation of various somatosensory stimulations for functional MRI

International Nuclear Information System (INIS)

Hara, Kazushi; Nakasato, Nobukazu; Mizoi, Kazuo; Yoshimoto, Takashi; Shimizu, Hiroaki.

1997-01-01

The aim of this functional magnetic resonance imaging (fMRI) study was to test detectability of activated area using various somatosensory stimulations. The following stimulations were performed in normal volunteers: regular or irregular electrical median nerve stimulation (n=5, each), tactile stimulation to the palm and fingers (n=8), pain stimulation to the index finger (n=5) or to the palm and fingers (n=5). fMRI was acquired with a spoiled gradient echo sequence at 1.5 T. Detectability of activated area was the highest when the pain stimulation was applied to the palm and fingers (80%). A successful rate for the tactile stimulation was 25%, and the other stimulations failed to demonstrate any activation. When successful, the highest signal activation on fMRI was seen on a sulcus, which presumably arose from a vein. The sulcus was defined as the central sulcus by somatosensory evoked field using a median nerve stimulation. Our study indicates that the pain stimulation to the palm and fingers may be a choice for the sensory fMRI. (author)

Inter-subject and Inter-session Variability of Plasticity Induction by Non-invasive Brain Stimulation

DEFF Research Database (Denmark)

Ziemann, Ulf; Siebner, Hartwig R

2015-01-01

in human cortex well beyond the time of stimulation. These aftereffects have been termed long-term potentiation (LTP)-like and long-term depression (LTD)-like plasticity because indirect evidence supported the notion that synaptic strengthening or weakening similar to LTP/D at the cellular level underlies......Non-invasive brain stimulation (NIBS) protocols such as regular repetitive transcranial magnetic stimulation (rTMS), theta-burst stimulation (TBS), paired associative stimulation (PAS) and transcranial direct current stimulation (tDCS) can change the excitability of the stimulated neuronal network...

Selection of regularization parameter for l1-regularized damage detection

Science.gov (United States)

Hou, Rongrong; Xia, Yong; Bao, Yuequan; Zhou, Xiaoqing

2018-06-01

The l1 regularization technique has been developed for structural health monitoring and damage detection through employing the sparsity condition of structural damage. The regularization parameter, which controls the trade-off between data fidelity and solution size of the regularization problem, exerts a crucial effect on the solution. However, the l1 regularization problem has no closed-form solution, and the regularization parameter is usually selected by experience. This study proposes two strategies of selecting the regularization parameter for the l1-regularized damage detection problem. The first method utilizes the residual and solution norms of the optimization problem and ensures that they are both small. The other method is based on the discrepancy principle, which requires that the variance of the discrepancy between the calculated and measured responses is close to the variance of the measurement noise. The two methods are applied to a cantilever beam and a three-story frame. A range of the regularization parameter, rather than one single value, can be determined. When the regularization parameter in this range is selected, the damage can be accurately identified even for multiple damage scenarios. This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

International Nuclear Information System (INIS)

Olson, Gordon L.

2008-01-01

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution

Chord length distributions between hard disks and spheres in regular, semi-regular, and quasi-random structures

Energy Technology Data Exchange (ETDEWEB)

Olson, Gordon L. [Computer and Computational Sciences Division (CCS-2), Los Alamos National Laboratory, 5 Foxglove Circle, Madison, WI 53717 (United States)], E-mail: olson99@tds.net

2008-11-15

In binary stochastic media in two- and three-dimensions consisting of randomly placed impenetrable disks or spheres, the chord lengths in the background material between disks and spheres closely follow exponential distributions if the disks and spheres occupy less than 10% of the medium. This work demonstrates that for regular spatial structures of disks and spheres, the tails of the chord length distributions (CLDs) follow power laws rather than exponentials. In dilute media, when the disks and spheres are widely spaced, the slope of the power law seems to be independent of the details of the structure. When approaching a close-packed arrangement, the exact placement of the spheres can make a significant difference. When regular structures are perturbed by small random displacements, the CLDs become power laws with steeper slopes. An example CLD from a quasi-random distribution of spheres in clusters shows a modified exponential distribution.

Convergence rates in constrained Tikhonov regularization: equivalence of projected source conditions and variational inequalities

International Nuclear Information System (INIS)

Flemming, Jens; Hofmann, Bernd

2011-01-01

In this paper, we enlighten the role of variational inequalities for obtaining convergence rates in Tikhonov regularization of nonlinear ill-posed problems with convex penalty functionals under convexity constraints in Banach spaces. Variational inequalities are able to cover solution smoothness and the structure of nonlinearity in a uniform manner, not only for unconstrained but, as we indicate, also for constrained Tikhonov regularization. In this context, we extend the concept of projected source conditions already known in Hilbert spaces to Banach spaces, and we show in the main theorem that such projected source conditions are to some extent equivalent to certain variational inequalities. The derived variational inequalities immediately yield convergence rates measured by Bregman distances

Nonlocal Regularized Algebraic Reconstruction Techniques for MRI: An Experimental Study

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Xin Li

2013-01-01

Full Text Available We attempt to revitalize researchers' interest in algebraic reconstruction techniques (ART by expanding their capabilities and demonstrating their potential in speeding up the process of MRI acquisition. Using a continuous-to-discrete model, we experimentally study the application of ART into MRI reconstruction which unifies previous nonuniform-fast-Fourier-transform- (NUFFT- based and gridding-based approaches. Under the framework of ART, we advocate the use of nonlocal regularization techniques which are leveraged from our previous research on modeling photographic images. It is experimentally shown that nonlocal regularization ART (NR-ART can often outperform their local counterparts in terms of both subjective and objective qualities of reconstructed images. On one real-world k-space data set, we find that nonlocal regularization can achieve satisfactory reconstruction from as few as one-third of samples. We also address an issue related to image reconstruction from real-world k-space data but overlooked in the open literature: the consistency of reconstructed images across different resolutions. A resolution-consistent extension of NR-ART is developed and shown to effectively suppress the artifacts arising from frequency extrapolation. Both source codes and experimental results of this work are made fully reproducible.

Mathematical Modeling the Geometric Regularity in Proteus Mirabilis Colonies

Science.gov (United States)

Zhang, Bin; Jiang, Yi; Minsu Kim Collaboration

Proteus Mirabilis colony exhibits striking spatiotemporal regularity, with concentric ring patterns with alternative high and low bacteria density in space, and periodicity for repetition process of growth and swarm in time. We present a simple mathematical model to explain the spatiotemporal regularity of P. Mirabilis colonies. We study a one-dimensional system. Using a reaction-diffusion model with thresholds in cell density and nutrient concentration, we recreated periodic growth and spread patterns, suggesting that the nutrient constraint and cell density regulation might be sufficient to explain the spatiotemporal periodicity in P. Mirabilis colonies. We further verify this result using a cell based model.

Regular and stochastic particle motion in plasma dynamics

International Nuclear Information System (INIS)

Kaufman, A.N.

1979-08-01

A Hamiltonian formalism is presented for the study of charged-particle trajectories in the self-consistent field of the particles. The intention is to develop a general approach to plasma dynamics. Transformations of phase-space variables are used to separate out the regular, adiabatic motion from the irregular, stochastic trajectories. Several new techniques are included in this presentation

Stimulation of Work Integration Social Enterprises (WISES) and Combatting Social Exclusion at the Local Level

NARCIS (Netherlands)

Boesveldt, N.F.

2016-01-01

WISES are social enterprises that work with people marginalized from the regular labour market, including people with severe handicaps, with disabilities and those who suffer addiction and homelessness. WISES offer an alternative to regular social programs: they breach social exclusion and stimulate

Intrinsic Regularization in a Lorentz invariant non-orthogonal Euclidean Space

OpenAIRE

Tornow, Carmen

2006-01-01

It is shown that the Lorentz transformations can be derived for a non-orthogonal Euclidean space. In this geometry one finds the same relations of special relativity as the ones known from the orthogonal Minkowski space. In order to illustrate the advantage of a non-orthogonal Euclidean metric the two-point Green’s function at x = 0 for a self-interacting scalar field is calculated. In contrast to the Minkowski space the one loop mass correction derived from this function gives a convergent r...

Effective action for scalar fields and generalized zeta-function regularization

International Nuclear Information System (INIS)

Cognola, Guido; Zerbini, Sergio

2004-01-01

Motivated by the study of quantum fields in a Friedmann-Robertson-Walker space-time, the one-loop effective action for a scalar field defined in the ultrastatic manifold RxH 3 /Γ, H 3 /Γ being the finite volume, noncompact, hyperbolic spatial section, is investigated by a generalization of zeta-function regularization. It is shown that additional divergences may appear at the one-loop level. The one-loop renormalizability of the model is discussed and, making use of a generalization of zeta-function regularization, the one-loop renormalization group equations are derived

Mixed Total Variation and L1 Regularization Method for Optical Tomography Based on Radiative Transfer Equation

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Jinping Tang

2017-01-01

Full Text Available Optical tomography is an emerging and important molecular imaging modality. The aim of optical tomography is to reconstruct optical properties of human tissues. In this paper, we focus on reconstructing the absorption coefficient based on the radiative transfer equation (RTE. It is an ill-posed parameter identification problem. Regularization methods have been broadly applied to reconstruct the optical coefficients, such as the total variation (TV regularization and the L1 regularization. In order to better reconstruct the piecewise constant and sparse coefficient distributions, TV and L1 norms are combined as the regularization. The forward problem is discretized with the discontinuous Galerkin method on the spatial space and the finite element method on the angular space. The minimization problem is solved by a Jacobian-based Levenberg-Marquardt type method which is equipped with a split Bregman algorithms for the L1 regularization. We use the adjoint method to compute the Jacobian matrix which dramatically improves the computation efficiency. By comparing with the other imaging reconstruction methods based on TV and L1 regularizations, the simulation results show the validity and efficiency of the proposed method.

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-09-20

Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

Regularizing Feynman path integrals using the generalized Kontsevich-Vishik trace

Science.gov (United States)

Hartung, Tobias

2017-12-01

A fully regulated definition of Feynman's path integral is presented here. The proposed re-formulation of the path integral coincides with the familiar formulation whenever the path integral is well defined. In particular, it is consistent with respect to lattice formulations and Wick rotations, i.e., it can be used in Euclidean and Minkowski space-time. The path integral regularization is introduced through the generalized Kontsevich-Vishik trace, that is, the extension of the classical trace to Fourier integral operators. Physically, we are replacing the time-evolution semi-group by a holomorphic family of operators such that the corresponding path integrals are well defined in some half space of C . The regularized path integral is, thus, defined through analytic continuation. This regularization can be performed by means of stationary phase approximation or computed analytically depending only on the Hamiltonian and the observable (i.e., known a priori). In either case, the computational effort to evaluate path integrals or expectations of observables reduces to the evaluation of integrals over spheres. Furthermore, computations can be performed directly in the continuum and applications (analytic computations and their implementations) to a number of models including the non-trivial cases of the massive Schwinger model and a φ4 theory.

L1-norm locally linear representation regularization multi-source adaptation learning.

Science.gov (United States)

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of regularized inversion of data corrupted by white Gaussian noise

International Nuclear Information System (INIS)

Kekkonen, Hanne; Lassas, Matti; Siltanen, Samuli

2014-01-01

Tikhonov regularization is studied in the case of linear pseudodifferential operator as the forward map and additive white Gaussian noise as the measurement error. The measurement model for an unknown function u(x) is m(x) = Au(x) + δ ε (x), where δ > 0 is the noise magnitude. If ε was an L 2 -function, Tikhonov regularization gives an estimate T α (m) = u∈H r arg min { ||Au-m|| L 2 2 + α||u|| H r 2 } for u where α = α(δ) is the regularization parameter. Here penalization of the Sobolev norm ||u|| H r covers the cases of standard Tikhonov regularization (r = 0) and first derivative penalty (r = 1). Realizations of white Gaussian noise are almost never in L 2 , but do belong to H s with probability one if s < 0 is small enough. A modification of Tikhonov regularization theory is presented, covering the case of white Gaussian measurement noise. Furthermore, the convergence of regularized reconstructions to the correct solution as δ → 0 is proven in appropriate function spaces using microlocal analysis. The convergence of the related finite-dimensional problems to the infinite-dimensional problem is also analysed. (paper)

2-regularity and 2-normality conditions for systems with impulsive controls

Directory of Open Access Journals (Sweden)

Pavlova Natal'ya

2007-01-01

Full Text Available In this paper a controlled system with impulsive controls in the neighborhood of an abnormal point is investigated. The set of pairs (u,μ is considered as a class of admissible controls, where u is a measurable essentially bounded function and μ is a finite-dimensional Borel measure, such that for any Borel set B, μ(B is a subset of the given convex closed pointed cone. In this article the concepts of 2-regularity and 2-normality for the abstract mapping Ф, operating from the given Banach space into a finite-dimensional space, are introduced. The concepts of 2-regularity and 2-normality play a great role in the course of derivation of the first and the second order necessary conditions for the optimal control problem, consisting of the minimization of a certain functional on the set of the admissible processes. These concepts are also important for obtaining the sufficient conditions for the local controllability of the nonlinear systems. The convenient criterion for 2-regularity along the prescribed direction and necessary conditions for 2-normality of systems, linear in control, are introduced in this article as well.

Image degradation characteristics and restoration based on regularization for diffractive imaging

Science.gov (United States)

Zhi, Xiyang; Jiang, Shikai; Zhang, Wei; Wang, Dawei; Li, Yun

2017-11-01

The diffractive membrane optical imaging system is an important development trend of ultra large aperture and lightweight space camera. However, related investigations on physics-based diffractive imaging degradation characteristics and corresponding image restoration methods are less studied. In this paper, the model of image quality degradation for the diffraction imaging system is first deduced mathematically based on diffraction theory and then the degradation characteristics are analyzed. On this basis, a novel regularization model of image restoration that contains multiple prior constraints is established. After that, the solving approach of the equation with the multi-norm coexistence and multi-regularization parameters (prior's parameters) is presented. Subsequently, the space-variant PSF image restoration method for large aperture diffractive imaging system is proposed combined with block idea of isoplanatic region. Experimentally, the proposed algorithm demonstrates its capacity to achieve multi-objective improvement including MTF enhancing, dispersion correcting, noise and artifact suppressing as well as image's detail preserving, and produce satisfactory visual quality. This can provide scientific basis for applications and possesses potential application prospects on future space applications of diffractive membrane imaging technology.

Progressive image denoising through hybrid graph Laplacian regularization: a unified framework.

Science.gov (United States)

Liu, Xianming; Zhai, Deming; Zhao, Debin; Zhai, Guangtao; Gao, Wen

2014-04-01

Recovering images from corrupted observations is necessary for many real-world applications. In this paper, we propose a unified framework to perform progressive image recovery based on hybrid graph Laplacian regularized regression. We first construct a multiscale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned, which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space. In this procedure, the intrinsic manifold structure is explicitly considered using both measured and unmeasured samples, and the nonlocal self-similarity property is utilized as a fruitful resource for abstracting a priori knowledge of the images. On the other hand, between two successive scales, the proposed model is extended to a projected high-dimensional feature space through explicit kernel mapping to describe the interscale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. In this way, the proposed algorithm gradually recovers more and more image details and edges, which could not been recovered in previous scale. We test our algorithm on one typical image recovery task: impulse noise removal. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art algorithms.

FOREWORD: Tackling inverse problems in a Banach space environment: from theory to applications Tackling inverse problems in a Banach space environment: from theory to applications

Science.gov (United States)

Schuster, Thomas; Hofmann, Bernd; Kaltenbacher, Barbara

2012-10-01

Inverse problems can usually be modelled as operator equations in infinite-dimensional spaces with a forward operator acting between Hilbert or Banach spaces—a formulation which quite often also serves as the basis for defining and analyzing solution methods. The additional amount of structure and geometric interpretability provided by the concept of an inner product has rendered these methods amenable to a convergence analysis, a fact which has led to a rigorous and comprehensive study of regularization methods in Hilbert spaces over the last three decades. However, for numerous problems such as x-ray diffractometry, certain inverse scattering problems and a number of parameter identification problems in PDEs, the reasons for using a Hilbert space setting seem to be based on conventions rather than an appropriate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, non-Hilbertian regularization and data fidelity terms incorporating a priori information on solution and noise, such as general Lp-norms, TV-type norms, or the Kullback-Leibler divergence, have recently become very popular. These facts have motivated intensive investigations on regularization methods in Banach spaces, a topic which has emerged as a highly active research field within the area of inverse problems. Meanwhile some of the most well-known regularization approaches, such as Tikhonov-type methods requiring the solution of extremal problems, and iterative ones like the Landweber method, the Gauss-Newton method, as well as the approximate inverse method, have been investigated for linear and nonlinear operator equations in Banach spaces. Convergence with rates has been proven and conditions on the solution smoothness and on the structure of nonlinearity have been formulated. Still, beyond the existing results a large number of challenging open questions have arisen, due to the more involved handling of general Banach spaces and the larger variety

Multi-view clustering via multi-manifold regularized non-negative matrix factorization.

Science.gov (United States)

Zong, Linlin; Zhang, Xianchao; Zhao, Long; Yu, Hong; Zhao, Qianli

2017-04-01

Non-negative matrix factorization based multi-view clustering algorithms have shown their competitiveness among different multi-view clustering algorithms. However, non-negative matrix factorization fails to preserve the locally geometrical structure of the data space. In this paper, we propose a multi-manifold regularized non-negative matrix factorization framework (MMNMF) which can preserve the locally geometrical structure of the manifolds for multi-view clustering. MMNMF incorporates consensus manifold and consensus coefficient matrix with multi-manifold regularization to preserve the locally geometrical structure of the multi-view data space. We use two methods to construct the consensus manifold and two methods to find the consensus coefficient matrix, which leads to four instances of the framework. Experimental results show that the proposed algorithms outperform existing non-negative matrix factorization based algorithms for multi-view clustering. Copyright © 2017 Elsevier Ltd. All rights reserved.

Instabilities of the zeta-function regularization in the presence of symmetries

International Nuclear Information System (INIS)

Rasetti, M.

1980-01-01

The zeta-function regularization method requires the calculation of the spectrum-generating function zeta sub(M) of a generic real, elliptic, self-adjoint differential operator on a manifold M. An asymptotic expansion for zeta sub(M) is given for the class of all symmetric spaces of rank 1, sufficient to compute its Mellin transform and deduce the regularization of the corresponding quadratic path integrals. The summability properties of the generalized zeta-function introduce physical instabilities in the system as negative specific heat. The technique (and the instability as well) is shown to hold - under the assumed symmetry properties - in any dimension (preserving both the global and local properties of the manifold, as opposed to the dimensional regularization, where one adds extra flat dimensions only). (author)

Weighted regularized statistical shape space projection for breast 3D model reconstruction.

Science.gov (United States)

Ruiz, Guillermo; Ramon, Eduard; García, Jaime; Sukno, Federico M; Ballester, Miguel A González

2018-05-02

The use of 3D imaging has increased as a practical and useful tool for plastic and aesthetic surgery planning. Specifically, the possibility of representing the patient breast anatomy in a 3D shape and simulate aesthetic or plastic procedures is a great tool for communication between surgeon and patient during surgery planning. For the purpose of obtaining the specific 3D model of the breast of a patient, model-based reconstruction methods can be used. In particular, 3D morphable models (3DMM) are a robust and widely used method to perform 3D reconstruction. However, if additional prior information (i.e., known landmarks) is combined with the 3DMM statistical model, shape constraints can be imposed to improve the 3DMM fitting accuracy. In this paper, we present a framework to fit a 3DMM of the breast to two possible inputs: 2D photos and 3D point clouds (scans). Our method consists in a Weighted Regularized (WR) projection into the shape space. The contribution of each point in the 3DMM shape is weighted allowing to assign more relevance to those points that we want to impose as constraints. Our method is applied at multiple stages of the 3D reconstruction process. Firstly, it can be used to obtain a 3DMM initialization from a sparse set of 3D points. Additionally, we embed our method in the 3DMM fitting process in which more reliable or already known 3D points or regions of points, can be weighted in order to preserve their shape information. The proposed method has been tested in two different input settings: scans and 2D pictures assessing both reconstruction frameworks with very positive results. Copyright © 2018 Elsevier B.V. All rights reserved.

Manifold regularized multitask learning for semi-supervised multilabel image classification.

Science.gov (United States)

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Fermion-number violation in regularizations that preserve fermion-number symmetry

Science.gov (United States)

Golterman, Maarten; Shamir, Yigal

2003-01-01

There exist both continuum and lattice regularizations of gauge theories with fermions which preserve chiral U(1) invariance (“fermion number”). Such regularizations necessarily break gauge invariance but, in a covariant gauge, one recovers gauge invariance to all orders in perturbation theory by including suitable counterterms. At the nonperturbative level, an apparent conflict then arises between the chiral U(1) symmetry of the regularized theory and the existence of ’t Hooft vertices in the renormalized theory. The only possible resolution of the paradox is that the chiral U(1) symmetry is broken spontaneously in the enlarged Hilbert space of the covariantly gauge-fixed theory. The corresponding Goldstone pole is unphysical. The theory must therefore be defined by introducing a small fermion-mass term that breaks explicitly the chiral U(1) invariance and is sent to zero after the infinite-volume limit has been taken. Using this careful definition (and a lattice regularization) for the calculation of correlation functions in the one-instanton sector, we show that the ’t Hooft vertices are recovered as expected.

Asymptotic analysis of a pile-up of regular edge dislocation walls

KAUST Repository

Hall, Cameron L.

2011-12-01

The idealised problem of a pile-up of regular dislocation walls (that is, of planes each containing an infinite number of parallel, identical and equally spaced dislocations) was presented by Roy et al. [A. Roy, R.H.J. Peerlings, M.G.D. Geers, Y. Kasyanyuk, Materials Science and Engineering A 486 (2008) 653-661] as a prototype for understanding the importance of discrete dislocation interactions in dislocation-based plasticity models. They noted that analytic solutions for the dislocation wall density are available for a pile-up of regular screw dislocation walls, but that numerical methods seem to be necessary for investigating regular edge dislocation walls. In this paper, we use the techniques of discrete-to-continuum asymptotic analysis to obtain a detailed description of a pile-up of regular edge dislocation walls. To leading order, we find that the dislocation wall density is governed by a simple differential equation and that boundary layers are present at both ends of the pile-up. © 2011 Elsevier B.V.

Asymptotic analysis of a pile-up of regular edge dislocation walls

KAUST Repository

Hall, Cameron L.

2011-01-01

The idealised problem of a pile-up of regular dislocation walls (that is, of planes each containing an infinite number of parallel, identical and equally spaced dislocations) was presented by Roy et al. [A. Roy, R.H.J. Peerlings, M.G.D. Geers, Y. Kasyanyuk, Materials Science and Engineering A 486 (2008) 653-661] as a prototype for understanding the importance of discrete dislocation interactions in dislocation-based plasticity models. They noted that analytic solutions for the dislocation wall density are available for a pile-up of regular screw dislocation walls, but that numerical methods seem to be necessary for investigating regular edge dislocation walls. In this paper, we use the techniques of discrete-to-continuum asymptotic analysis to obtain a detailed description of a pile-up of regular edge dislocation walls. To leading order, we find that the dislocation wall density is governed by a simple differential equation and that boundary layers are present at both ends of the pile-up. © 2011 Elsevier B.V.

Low-cost management aspects for developing, producing and operating future space transportation systems

Science.gov (United States)

Goehlich, Robert A.; Rücker, Udo

2005-01-01

It is believed that a potential means for further significant reduction of the recurrent launch cost, which results also in a stimulation of launch rates of small satellites, is to make the launcher reusable, to increase its reliability and to make it suitable for new markets such as mass space tourism. Therefore, not only launching small satellites with expendable rockets on non-regular flights but also with reusable rockets on regular flights should be considered for the long term. However, developing, producing and operating reusable rockets require a fundamental change in the current "business as usual" philosophy. Under current conditions, it might not be possible to develop, to produce or to operate a reusable vehicle fleet economically. The favorite philosophy is based on "smart business" processes adapted by the authors using cost engineering techniques. In the following paper, major strategies for reducing costs are discussed, which are applied for a representative program proposal.

On the structure of space-time caustics

International Nuclear Information System (INIS)

Rosquist, K.

1983-01-01

Caustics formed by timelike and null geodesics in a space-time M are investigated. Care is taken to distinguish the conjugate points in the tangent space (T-conjugate points) from conjugate points in the manifold (M-conjugate points). It is shown that most nonspacelike conjugate points are regular, i.e. with all neighbouring conjugate points having the same degree of degeneracy. The regular timelike T-conjugate locus is shown to be a smooth 3-dimensional submanifold of the tangent space. Analogously, the regular null T-conjugate locus is shown to be a smooth 2-dimensional submanifold of the light cone in the tangent space. The smoothness properties of the null caustic are used to show that if an observer sees focusing in all directions, then there will necessarily be a cusp in the caustic. If, in addition, all the null conjugate points have maximal degree of degeneracy (as in the closed Friedmann-Robertson-Walker universes), then the space-time is closed. (orig.)

Double Sequences and Iterated Limits in Regular Space

Directory of Open Access Journals (Sweden)

Coghetto Roland

2016-09-01

Full Text Available First, we define in Mizar [5], the Cartesian product of two filters bases and the Cartesian product of two filters. After comparing the product of two Fréchet filters on ℕ (F1 with the Fréchet filter on ℕ × ℕ (F2, we compare limF₁ and limF₂ for all double sequences in a non empty topological space.

Extreme values, regular variation and point processes

CERN Document Server

Resnick, Sidney I

1987-01-01

Extremes Values, Regular Variation and Point Processes is a readable and efficient account of the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors It presents a coherent treatment of the distributional and sample path fundamental properties of extremes and records It emphasizes the core primacy of three topics necessary for understanding extremes the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces The book is self-contained and requires an introductory measure-theoretic course in probability as a prerequisite Almost all sections have an extensive list of exercises which extend developments in the text, offer alternate approaches, test mastery and provide for enj...

Distance-regular graphs

NARCIS (Netherlands)

van Dam, Edwin R.; Koolen, Jack H.; Tanaka, Hajime

2016-01-01

This is a survey of distance-regular graphs. We present an introduction to distance-regular graphs for the reader who is unfamiliar with the subject, and then give an overview of some developments in the area of distance-regular graphs since the monograph 'BCN'[Brouwer, A.E., Cohen, A.M., Neumaier,

Perturbative formulation of pure space-like axial gauge QED with infrared divergences regularized by residual gauge fields

International Nuclear Information System (INIS)

Nakawaki, Yuji; McCartor, Gary

2006-01-01

We construct a new perturbative formulation of pure space-like axial gauge QED in which the inherent infrared divergences are regularized by residual gauge fields. For this purpose, we carry out our calculations in the coordinates x μ =(x + , x - , x 1 , x 2 ), where x + =x 0 sinθ + x 3 cosθ and x - = x 0 cosθ - x 3 sinθ. Here, A=A 0 cosθ + A 3 sinθ = n·A=0 is taken as the gauge fixing condition. We show in detail that, in perturbation theory, infrared divergences resulting from the residual gauge fields cancel infrared divergences resulting from the physical parts of the gauge field. As a result, we obtain the gauge field propagator proposed by Mandelstam and Leibbrandt. By taking the limit θ→π/4, we are able to construct a light-cone formulation that is free from infrared divergences. With that analysis complete, we next calculate the one-loop electron self-energy, something not previously done in the light-cone quantization and light-cone gauge. (author)

Regular expressions cookbook

CERN Document Server

Goyvaerts, Jan

2009-01-01

This cookbook provides more than 100 recipes to help you crunch data and manipulate text with regular expressions. Every programmer can find uses for regular expressions, but their power doesn't come worry-free. Even seasoned users often suffer from poor performance, false positives, false negatives, or perplexing bugs. Regular Expressions Cookbook offers step-by-step instructions for some of the most common tasks involving this tool, with recipes for C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. With this book, you will: Understand the basics of regular expressions through a

Asymptotic properties of spherically symmetric, regular and static solutions to Yang-Mills equations

International Nuclear Information System (INIS)

Cronstrom, C.

1987-01-01

In this paper the author discusses the asymptotic properties of solutions to Yang-Mills equations with the gauge group SU(2), for spherically symmetric, regular and static potentials. It is known, that the pure Yang-Mills equations cannot have nontrivial regular solutions which vanish rapidly at space infinity (socalled finite energy solutions). So, if regular solutions exist, they must have non-trivial asymptotic properties. However, if the asymptotic behaviour of the solutions is non-trivial, then the fact must be explicitly taken into account in constructing the proper action (and energy) for the theory. The elucidation of the appropriate surface correction to the Yang-Mills action (and hence the energy-momentum tensor density) is one of the main motivations behind the present study. In this paper the author restricts to the asymptotic behaviour of the static solutions. It is shown that this asymptotic behaviour is such that surface corrections (at space-infinity) are needed in order to obtain a well-defined (classical) theory. This is of relevance in formulating a quantum Yang-Mills theory

Tunneling into quantum wires: regularization of the tunneling Hamiltonian and consistency between free and bosonized fermions

OpenAIRE

Filippone, Michele; Brouwer, Piet

2016-01-01

Tunneling between a point contact and a one-dimensional wire is usually described with the help of a tunneling Hamiltonian that contains a delta function in position space. Whereas the leading order contribution to the tunneling current is independent of the way this delta function is regularized, higher-order corrections with respect to the tunneling amplitude are known to depend on the regularization. Instead of regularizing the delta function in the tunneling Hamiltonian, one may also obta...

Particle trapping in stimulated scattering processes

International Nuclear Information System (INIS)

Karttunen, S.J.; Heikkinen, J.A.

1981-01-01

Particle trapping effects on stimulated Brillouin and Raman scattering are investigated. A time and space dependent model assumes a Maxwellian plasma which is taken to be homogeneous in the interaction region. Ion trapping has a rather weak effect on stimulated Brillouin scattering and large reflectivities are obtained even in strong trapping regime. Stimulated Raman scattering is considerably reduced by electron trapping. Typically 15-20 times larger laser intensities are required to obtain same reflectivity levels than without trapping. (author)

LL-regular grammars

NARCIS (Netherlands)

Nijholt, Antinus

1980-01-01

Culik II and Cogen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this paper we consider an analogous extension of the LL(k) grammars called the LL-regular grammars. The relation of this class of grammars to other classes of grammars will be shown. Any LL-regular

Sparse regularization for force identification using dictionaries

Science.gov (United States)

Qiao, Baijie; Zhang, Xingwu; Wang, Chenxi; Zhang, Hang; Chen, Xuefeng

2016-04-01

The classical function expansion method based on minimizing l2-norm of the response residual employs various basis functions to represent the unknown force. Its difficulty lies in determining the optimum number of basis functions. Considering the sparsity of force in the time domain or in other basis space, we develop a general sparse regularization method based on minimizing l1-norm of the coefficient vector of basis functions. The number of basis functions is adaptively determined by minimizing the number of nonzero components in the coefficient vector during the sparse regularization process. First, according to the profile of the unknown force, the dictionary composed of basis functions is determined. Second, a sparsity convex optimization model for force identification is constructed. Third, given the transfer function and the operational response, Sparse reconstruction by separable approximation (SpaRSA) is developed to solve the sparse regularization problem of force identification. Finally, experiments including identification of impact and harmonic forces are conducted on a cantilever thin plate structure to illustrate the effectiveness and applicability of SpaRSA. Besides the Dirac dictionary, other three sparse dictionaries including Db6 wavelets, Sym4 wavelets and cubic B-spline functions can also accurately identify both the single and double impact forces from highly noisy responses in a sparse representation frame. The discrete cosine functions can also successfully reconstruct the harmonic forces including the sinusoidal, square and triangular forces. Conversely, the traditional Tikhonov regularization method with the L-curve criterion fails to identify both the impact and harmonic forces in these cases.

Regularity criteria for the Navier–Stokes equations based on one component of velocity

Czech Academy of Sciences Publication Activity Database

Guo, Z.; Caggio, M.; Skalák, Zdeněk

2017-01-01

Roč. 35, June (2017), s. 379-396 ISSN 1468-1218 R&D Projects: GA ČR GA14-02067S Grant - others:Západočeská univerzita(CZ) SGS-2016-003; National Natural Science Foundation of China (CN) 11301394 Institutional support: RVO:67985874 Keywords : Navier–Stokes equations * regularity of solutions * regularity criteria * Anisotropic Lebesgue spaces Subject RIV: BK - Fluid Dynamics OBOR OECD: Fluids and plasma physics (including surface physics) Impact factor: 1.659, year: 2016

Regularity criteria for the Navier–Stokes equations based on one component of velocity

Czech Academy of Sciences Publication Activity Database

Guo, Z.; Caggio, M.; Skalák, Zdeněk

2017-01-01

Roč. 35, June (2017), s. 379-396 ISSN 1468-1218 R&D Projects: GA ČR GA14-02067S Grant - others:Západočeská univerzita(CZ) SGS-2016-003; National Natural Science Foundation of China(CN) 11301394 Institutional support: RVO:67985874 Keywords : Navier–Stokes equations * regularity of solutions * regularity criteria * Anisotropic Lebesgue spaces Subject RIV: BK - Fluid Dynamics OBOR OECD: Fluids and plasma physics (including surface physics) Impact factor: 1.659, year: 2016

Describing chaotic attractors: Regular and perpetual points

Science.gov (United States)

Dudkowski, Dawid; Prasad, Awadhesh; Kapitaniak, Tomasz

2018-03-01

We study the concepts of regular and perpetual points for describing the behavior of chaotic attractors in dynamical systems. The idea of these points, which have been recently introduced to theoretical investigations, is thoroughly discussed and extended into new types of models. We analyze the correlation between regular and perpetual points, as well as their relation with phase space, showing the potential usefulness of both types of points in the qualitative description of co-existing states. The ability of perpetual points in finding attractors is indicated, along with its potential cause. The location of chaotic trajectories and sets of considered points is investigated and the study on the stability of systems is shown. The statistical analysis of the observing desired states is performed. We focus on various types of dynamical systems, i.e., chaotic flows with self-excited and hidden attractors, forced mechanical models, and semiconductor superlattices, exhibiting the universality of appearance of the observed patterns and relations.

Short-Term Dosage Regimen for Stimulation-Induced Long-Lasting Desynchronization

Directory of Open Access Journals (Sweden)

Thanos Manos

2018-04-01

Full Text Available In this paper, we computationally generate hypotheses for dose-finding studies in the context of desynchronizing neuromodulation techniques. Abnormally strong neuronal synchronization is a hallmark of several brain disorders. Coordinated Reset (CR stimulation is a spatio-temporally patterned stimulation technique that specifically aims at disrupting abnormal neuronal synchrony. In networks with spike-timing-dependent plasticity CR stimulation may ultimately cause an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and neuronal synchrony. This long-lasting desynchronization was theoretically predicted and verified in several pre-clinical and clinical studies. We have shown that CR stimulation with rapidly varying sequences (RVS robustly induces an anti-kindling at low intensities e.g., if the CR stimulation frequency (i.e., stimulus pattern repetition rate is in the range of the frequency of the neuronal oscillation. In contrast, CR stimulation with slowly varying sequences (SVS turned out to induce an anti-kindling more strongly, but less robustly with respect to variations of the CR stimulation frequency. Motivated by clinical constraints and inspired by the spacing principle of learning theory, in this computational study we propose a short-term dosage regimen that enables a robust anti-kindling effect of both RVS and SVS CR stimulation, also for those parameter values where RVS and SVS CR stimulation previously turned out to be ineffective. Intriguingly, for the vast majority of parameter values tested, spaced multishot CR stimulation with demand-controlled variation of stimulation frequency and intensity caused a robust and pronounced anti-kindling. In contrast, spaced CR stimulation with fixed stimulation parameters as well as singleshot CR stimulation of equal integral duration failed to improve the stimulation outcome. In the model network under consideration, our short-term dosage regimen enables to robustly induce

Short-Term Dosage Regimen for Stimulation-Induced Long-Lasting Desynchronization.

Science.gov (United States)

Manos, Thanos; Zeitler, Magteld; Tass, Peter A

2018-01-01

In this paper, we computationally generate hypotheses for dose-finding studies in the context of desynchronizing neuromodulation techniques. Abnormally strong neuronal synchronization is a hallmark of several brain disorders. Coordinated Reset (CR) stimulation is a spatio-temporally patterned stimulation technique that specifically aims at disrupting abnormal neuronal synchrony. In networks with spike-timing-dependent plasticity CR stimulation may ultimately cause an anti-kindling, i.e., an unlearning of abnormal synaptic connectivity and neuronal synchrony. This long-lasting desynchronization was theoretically predicted and verified in several pre-clinical and clinical studies. We have shown that CR stimulation with rapidly varying sequences (RVS) robustly induces an anti-kindling at low intensities e.g., if the CR stimulation frequency (i.e., stimulus pattern repetition rate) is in the range of the frequency of the neuronal oscillation. In contrast, CR stimulation with slowly varying sequences (SVS) turned out to induce an anti-kindling more strongly, but less robustly with respect to variations of the CR stimulation frequency. Motivated by clinical constraints and inspired by the spacing principle of learning theory, in this computational study we propose a short-term dosage regimen that enables a robust anti-kindling effect of both RVS and SVS CR stimulation, also for those parameter values where RVS and SVS CR stimulation previously turned out to be ineffective. Intriguingly, for the vast majority of parameter values tested, spaced multishot CR stimulation with demand-controlled variation of stimulation frequency and intensity caused a robust and pronounced anti-kindling. In contrast, spaced CR stimulation with fixed stimulation parameters as well as singleshot CR stimulation of equal integral duration failed to improve the stimulation outcome. In the model network under consideration, our short-term dosage regimen enables to robustly induce long

Regularized quasinormal modes for plasmonic resonators and open cavities

Science.gov (United States)

Kamandar Dezfouli, Mohsen; Hughes, Stephen

2018-03-01

Optical mode theory and analysis of open cavities and plasmonic particles is an essential component of optical resonator physics, offering considerable insight and efficiency for connecting to classical and quantum optical properties such as the Purcell effect. However, obtaining the dissipative modes in normalized form for arbitrarily shaped open-cavity systems is notoriously difficult, often involving complex spatial integrations, even after performing the necessary full space solutions to Maxwell's equations. The formal solutions are termed quasinormal modes, which are known to diverge in space, and additional techniques are frequently required to obtain more accurate field representations in the far field. In this work, we introduce a finite-difference time-domain technique that can be used to obtain normalized quasinormal modes using a simple dipole-excitation source, and an inverse Green function technique, in real frequency space, without having to perform any spatial integrations. Moreover, we show how these modes are naturally regularized to ensure the correct field decay behavior in the far field, and thus can be used at any position within and outside the resonator. We term these modes "regularized quasinormal modes" and show the reliability and generality of the theory by studying the generalized Purcell factor of dipole emitters near metallic nanoresonators, hybrid devices with metal nanoparticles coupled to dielectric waveguides, as well as coupled cavity-waveguides in photonic crystals slabs. We also directly compare our results with full-dipole simulations of Maxwell's equations without any approximations, and show excellent agreement.

Reducing errors in the GRACE gravity solutions using regularization

Science.gov (United States)

Save, Himanshu; Bettadpur, Srinivas; Tapley, Byron D.

2012-09-01

solutions (RL04) from the Center for Space Research (CSR). Post-fit residual analysis shows that the regularized solutions fit the data to within the noise level of GRACE. A time series of filtered hydrological model is used to confirm that signal attenuation for basins in the Total Runoff Integrating Pathways (TRIP) database over 320 km radii is less than 1 cm equivalent water height RMS, which is within the noise level of GRACE.

An iterative method for Tikhonov regularization with a general linear regularization operator

NARCIS (Netherlands)

Hochstenbach, M.E.; Reichel, L.

2010-01-01

Tikhonov regularization is one of the most popular approaches to solve discrete ill-posed problems with error-contaminated data. A regularization operator and a suitable value of a regularization parameter have to be chosen. This paper describes an iterative method, based on Golub-Kahan

Regularization methods for ill-posed problems in multiple Hilbert scales

International Nuclear Information System (INIS)

Mazzieri, Gisela L; Spies, Ruben D

2012-01-01

Several convergence results in Hilbert scales under different source conditions are proved and orders of convergence and optimal orders of convergence are derived. Also, relations between those source conditions are proved. The concept of a multiple Hilbert scale on a product space is introduced, and regularization methods on these scales are defined, both for the case of a single observation and for the case of multiple observations. In the latter case, it is shown how vector-valued regularization functions in these multiple Hilbert scales can be used. In all cases, convergence is proved and orders and optimal orders of convergence are shown. Finally, some potential applications and open problems are discussed. (paper)

RBSURFpred: Modeling protein accessible surface area in real and binary space using regularized and optimized regression.

Science.gov (United States)

Tarafder, Sumit; Toukir Ahmed, Md; Iqbal, Sumaiya; Tamjidul Hoque, Md; Sohel Rahman, M

2018-03-14

Accessible surface area (ASA) of a protein residue is an effective feature for protein structure prediction, binding region identification, fold recognition problems etc. Improving the prediction of ASA by the application of effective feature variables is a challenging but explorable task to consider, specially in the field of machine learning. Among the existing predictors of ASA, REGAd 3 p is a highly accurate ASA predictor which is based on regularized exact regression with polynomial kernel of degree 3. In this work, we present a new predictor RBSURFpred, which extends REGAd 3 p on several dimensions by incorporating 58 physicochemical, evolutionary and structural properties into 9-tuple peptides via Chou's general PseAAC, which allowed us to obtain higher accuracies in predicting both real-valued and binary ASA. We have compared RBSURFpred for both real and binary space predictions with state-of-the-art predictors, such as REGAd 3 p and SPIDER2. We also have carried out a rigorous analysis of the performance of RBSURFpred in terms of different amino acids and their properties, and also with biologically relevant case-studies. The performance of RBSURFpred establishes itself as a useful tool for the community. Copyright © 2018 Elsevier Ltd. All rights reserved.

Regular Expression Pocket Reference

CERN Document Server

Stubblebine, Tony

2007-01-01

This handy little book offers programmers a complete overview of the syntax and semantics of regular expressions that are at the heart of every text-processing application. Ideal as a quick reference, Regular Expression Pocket Reference covers the regular expression APIs for Perl 5.8, Ruby (including some upcoming 1.9 features), Java, PHP, .NET and C#, Python, vi, JavaScript, and the PCRE regular expression libraries. This concise and easy-to-use reference puts a very powerful tool for manipulating text and data right at your fingertips. Composed of a mixture of symbols and text, regular exp

Cluster headache attack remission with sphenopalatine ganglion stimulation

DEFF Research Database (Denmark)

Barloese, Mads C J; Jürgens, Tim P; May, Arne

2016-01-01

collected at regular clinic visits. The time point “after remission” was defined as the first visit after the end of the remission period. Results: Thirty percent (10/33) of enrolled patients experienced at least one period of complete attack remission. All remission periods followed the start of SPG...... stimulation, with the first period beginning 134 ± 86 (range 21-272) days after initiation of stimulation. On average, each patient’s longest remission period lasted 149 ± 97 (range 62-322) days. The ability to treat acute attacks before and after remission was similar (37 % ± 25 % before, 49 % ± 32 % after...

Vestibular stimulation after head injury: effect on reaction times and motor speech parameters

DEFF Research Database (Denmark)

Engberg, A

1989-01-01

Earlier studies by other authors indicate that vestibular stimulation may improve attention and dysarthria in head injured patients. In the present study of five severely head injured patients and five controls, the effect of vestibular stimulation on reaction times (reflecting attention) and some...... motor speech parameters (reflecting dysarthria) was investigated. After eight weeks with regular stimulation, it was concluded that reaction time changes were individual and consistent for a given subject. Only occasionally were they shortened after stimulation. However, reaction time was lengthened...... in three cases, prohibiting further stimulation in one case. Motion sickness was prohibitive in a second case. However, after-stimulation increase of phonation time and/or vital capacity was found in one patient and four controls. Oral diadochokinetic rates were slowed in several cases. Collectively, when...

SQED two-loop beta function in the context of Implicit regularization

International Nuclear Information System (INIS)

Cherchiglia, Adriano Lana; Sampaio, Marcos; Nemes, Maria Carolina

2013-01-01

Full text: In this work we present the state-of-art for Implicit Regularization (IReg) in the context of supersymmetric theories. IReg is a four-dimensional regularization technique in momentum space which disentangles, in a consistent way at arbitrary order, the divergencies, regularization dependent and finite parts of any Feynman amplitude. Since it does not resort to modifications on the physical space-time dimensions of the underlying quantum field theoretical model, it can be consistently applied to supersymmetric theories. First we describe the technique and present previous results for supersymmetric models: the two-loop beta function for the Wess-Zumino model (both in the component and superfield formalism); the two-loop beta function for Super Yang-Mills (in the superfield formalism using the background field technique). After, we present our calculation of the two-loop beta function for massless and massive SQED using the superfield formalism with and without resorting to the background field technique. We find that only in the second case the two-loop divergence cancels out. We argue it is due to an anomalous Jacobian under the rescaling of the fields in the path-integral which is necessary for the application of the supersymmetric background field technique. We find, however, that in both cases the two-loop coefficients of beta function are non-null. Finally we briefly discuss the anomaly puzzle in the context of our technique. (author)

Effort variation regularization in sound field reproduction

DEFF Research Database (Denmark)

Stefanakis, Nick; Jacobsen, Finn; Sarris, Ioannis

2010-01-01

In this paper, active control is used in order to reproduce a given sound field in an extended spatial region. A method is proposed which minimizes the reproduction error at a number of control positions with the reproduction sources holding a certain relation within their complex strengths......), and adaptive wave field synthesis (AWFS), both under free-field conditions and in reverberant rooms. It is shown that effort variation regularization overcomes the problems associated with small spaces and with a low ratio of direct to reverberant energy, improving thus the reproduction accuracy...

Differential regularization and renormalization: a new method of calculation in quantum field theory

International Nuclear Information System (INIS)

Freedman, D.Z.; Johnson, K.; Latorre, J.I.

1992-01-01

Most primitively divergent Feynman diagrams are well defined in x-space but too singular at short distances for transformation to p-space. A new method of regularization is developed in which singular functions are written as derivatives of less singular functions which contain a logarithmic mass scale. The Fourier transform is then defined by formal integration by parts. The procedure is extended to graphs with divergent subgraphs. No explicit cutoff or counterterms are required, and the method automatically delivers renormalized amplitudes which satisfy Callan-Symanzik equations. These features are thoroughly explored in massless φ 4 theory through 3-loop order, and the method yields explicit functional forms for all amplitudes with less difficulty than conventional methods which use dimensional regularization in p-space. The procedure also appears to be compatible with gauge invariance and the chiral structure of the standard model. This aspect is tested in extensive 1-loop calculations which include the Ward identity in quantum electrodynamics, the chiral anomaly, and the background field algorithm in non-abelian gauge theories. (orig.)

Regularity of C*-algebras and central sequence algebras

DEFF Research Database (Denmark)

Christensen, Martin S.

The main topic of this thesis is regularity properties of C*-algebras and how these regularity properties are re ected in their associated central sequence algebras. The thesis consists of an introduction followed by four papers [A], [B], [C], [D]. In [A], we show that for the class of simple...... Villadsen algebra of either the rst type with seed space a nite dimensional CW complex, or the second type, tensorial absorption of the Jiang-Su algebra is characterized by the absence of characters on the central sequence algebra. Additionally, in a joint appendix with Joan Bosa, we show that the Villadsen...... algebra of the second type with innite stable rank fails the corona factorization property. In [B], we consider the class of separable C*-algebras which do not admit characters on their central sequence algebra, and show that it has nice permanence properties. We also introduce a new divisibility property...

The Validity of Dimensional Regularization Method on Fractal Spacetime

Directory of Open Access Journals (Sweden)

Yong Tao

2013-01-01

Full Text Available Svozil developed a regularization method for quantum field theory on fractal spacetime (1987. Such a method can be applied to the low-order perturbative renormalization of quantum electrodynamics but will depend on a conjectural integral formula on non-integer-dimensional topological spaces. The main purpose of this paper is to construct a fractal measure so as to guarantee the validity of the conjectural integral formula.

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia.

Science.gov (United States)

Ratnadurai-Giridharan, Shivakeshavan; Cheung, Chung C; Rubchinsky, Leonid L

2017-11-01

Conventional deep brain stimulation of basal ganglia uses high-frequency regular electrical pulses to treat Parkinsonian motor symptoms but has a series of limitations. Relatively new and not yet clinically tested, optogenetic stimulation is an effective experimental stimulation technique to affect pathological network dynamics. We compared the effects of electrical and optogenetic stimulation of the basal gangliaon the pathologicalParkinsonian rhythmic neural activity. We studied the network response to electrical stimulation and excitatory and inhibitory optogenetic stimulations. Different stimulations exhibit different interactions with pathological activity in the network. We studied these interactions for different network and stimulation parameter values. Optogenetic stimulation was found to be more efficient than electrical stimulation in suppressing pathological rhythmicity. Our findings indicate that optogenetic control of neural synchrony may be more efficacious than electrical control because of the different ways of how stimulations interact with network dynamics.

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; Huang, Jianhua Z.; Sun, Yijun; Gao, Xin

2014-01-01

by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant

The geometry of continuum regularization

International Nuclear Information System (INIS)

Halpern, M.B.

1987-03-01

This lecture is primarily an introduction to coordinate-invariant regularization, a recent advance in the continuum regularization program. In this context, the program is seen as fundamentally geometric, with all regularization contained in regularized DeWitt superstructures on field deformations

Shape-constrained regularization by statistical multiresolution for inverse problems: asymptotic analysis

International Nuclear Information System (INIS)

Frick, Klaus; Marnitz, Philipp; Munk, Axel

2012-01-01

This paper is concerned with a novel regularization technique for solving linear ill-posed operator equations in Hilbert spaces from data that are corrupted by white noise. We combine convex penalty functionals with extreme-value statistics of projections of the residuals on a given set of sub-spaces in the image space of the operator. We prove general consistency and convergence rate results in the framework of Bregman divergences which allows for a vast range of penalty functionals. Various examples that indicate the applicability of our approach will be discussed. We will illustrate in the context of signal and image processing that the presented method constitutes a locally adaptive reconstruction method. (paper)

Guangxi crustal structural evolution and the formation and distribution regularities of U-rich strata

International Nuclear Information System (INIS)

Kang Zili.

1989-01-01

Based on summing up Guangxi geotectonic features and evolutionary regularities, this paper discusses the occurrence features, formation conditions and time-space distribution regularities of various U-rich strata during the development of geosyncline, platform and diwa stages, Especially, during diwa stage all those U-rich strata might be reworked to a certain degree and resulted in the mobilization of uranium, then enriching to form polygenetic composite uranium ore deposits with stratabound features. This study will be helpful for prospecting in the region

Regular expression containment

DEFF Research Database (Denmark)

Henglein, Fritz; Nielsen, Lasse

2011-01-01

We present a new sound and complete axiomatization of regular expression containment. It consists of the conventional axiomatiza- tion of concatenation, alternation, empty set and (the singleton set containing) the empty string as an idempotent semiring, the fixed- point rule E* = 1 + E × E......* for Kleene-star, and a general coin- duction rule as the only additional rule. Our axiomatization gives rise to a natural computational inter- pretation of regular expressions as simple types that represent parse trees, and of containment proofs as coercions. This gives the axiom- atization a Curry......-Howard-style constructive interpretation: Con- tainment proofs do not only certify a language-theoretic contain- ment, but, under our computational interpretation, constructively transform a membership proof of a string in one regular expres- sion into a membership proof of the same string in another regular expression. We...

Regularization by External Variables

DEFF Research Database (Denmark)

Bossolini, Elena; Edwards, R.; Glendinning, P. A.

2016-01-01

Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind of regula......Regularization was a big topic at the 2016 CRM Intensive Research Program on Advances in Nonsmooth Dynamics. There are many open questions concerning well known kinds of regularization (e.g., by smoothing or hysteresis). Here, we propose a framework for an alternative and important kind...

Regularization scheme dependence of virtual corrections to DY and DIS

International Nuclear Information System (INIS)

Khalafi, F.; Landshoff, P.V.

1981-01-01

One loop virtual corrections to the quark photon vertex are calculated under various assumptions and their sensitivity to the manner in which infra-red and mass singularities are regularized is studied. A method based on the use of Mellin-transforms in the Feynman parametric space is developed and shown to be convenient in calculating virtual diagrams beyond the leading logarithm in perturbative QCD. (orig.)

Regular Single Valued Neutrosophic Hypergraphs

Directory of Open Access Journals (Sweden)

Muhammad Aslam Malik

2016-12-01

Full Text Available In this paper, we define the regular and totally regular single valued neutrosophic hypergraphs, and discuss the order and size along with properties of regular and totally regular single valued neutrosophic hypergraphs. We also extend work on completeness of single valued neutrosophic hypergraphs.

Regular and chaotic dynamics in time-dependent relativistic mean-field theory

International Nuclear Information System (INIS)

Vretenar, D.; Ring, P.; Lalazissis, G.A.; Poeschl, W.

1997-01-01

Isoscalar and isovector monopole oscillations that correspond to giant resonances in spherical nuclei are described in the framework of time-dependent relativistic mean-field theory. Time-dependent and self-consistent calculations that reproduce experimental data on monopole resonances in 208 Pb show that the motion of the collective coordinate is regular for isoscalar oscillations, and that it becomes chaotic when initial conditions correspond to the isovector mode. Regular collective dynamics coexists with chaotic oscillations on the microscopic level. Time histories, Fourier spectra, state-space plots, Poincare sections, autocorrelation functions, and Lyapunov exponents are used to characterize the nonlinear system and to identify chaotic oscillations. Analogous considerations apply to higher multipolarities. copyright 1997 The American Physical Society

Enhanced manifold regularization for semi-supervised classification.

Science.gov (United States)

Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong

2016-06-01

Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.

Groningen active living model (GALM) : Stimulating physical activity in sedentary older adults

NARCIS (Netherlands)

Stevens, M; Lemmink, KAPM; de Greef, NHG; Rispens, P; de Greef, M.H.G.

1999-01-01

Background A significant number of Dutch older adults can be considered sedentary when it comes to regular participation in leisure-time physical activity. Sedentariness is considered a potential public health burden-all the more reason to develop a strategy for stimulating older adults toward

Wanding Through Space: Interactive Calibration for Electric Muscle Stimulation

DEFF Research Database (Denmark)

Pohl, Henning; Hornbæk, Kasper; Knibbe, Jarrod

2018-01-01

Electric Muscle Stimulation (EMS) has emerged as an interaction paradigm for HCI. It has been used to confer object affordance, provide walking directions, and assist with sketching. However, the electrical signals used for EMS are multi-dimensional and require expert calibration before use...

Ensemble manifold regularization.

Science.gov (United States)

Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng

2012-06-01

We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.

Sparsity regularization for parameter identification problems

International Nuclear Information System (INIS)

Jin, Bangti; Maass, Peter

2012-01-01

The investigation of regularization schemes with sparsity promoting penalty terms has been one of the dominant topics in the field of inverse problems over the last years, and Tikhonov functionals with ℓ p -penalty terms for 1 ⩽ p ⩽ 2 have been studied extensively. The first investigations focused on regularization properties of the minimizers of such functionals with linear operators and on iteration schemes for approximating the minimizers. These results were quickly transferred to nonlinear operator equations, including nonsmooth operators and more general function space settings. The latest results on regularization properties additionally assume a sparse representation of the true solution as well as generalized source conditions, which yield some surprising and optimal convergence rates. The regularization theory with ℓ p sparsity constraints is relatively complete in this setting; see the first part of this review. In contrast, the development of efficient numerical schemes for approximating minimizers of Tikhonov functionals with sparsity constraints for nonlinear operators is still ongoing. The basic iterated soft shrinkage approach has been extended in several directions and semi-smooth Newton methods are becoming applicable in this field. In particular, the extension to more general non-convex, non-differentiable functionals by variational principles leads to a variety of generalized iteration schemes. We focus on such iteration schemes in the second part of this review. A major part of this survey is devoted to applying sparsity constrained regularization techniques to parameter identification problems for partial differential equations, which we regard as the prototypical setting for nonlinear inverse problems. Parameter identification problems exhibit different levels of complexity and we aim at characterizing a hierarchy of such problems. The operator defining these inverse problems is the parameter-to-state mapping. We first summarize some

Imaging sensory effects of occipital nerve stimulation: a new computer-based method in neuromodulation.

Science.gov (United States)

Göbel, Anna; Göbel, Carl H; Heinze, Axel; Heinze-Kuhn, Katja; Petersen, Inga; Meinecke, Christoph; Clasen, Svenja; Niederberger, Uwe; Rasche, Dirk; Mehdorn, Hubertus M; Göbel, Hartmut

2015-01-01

Within the last years, occipital nerve stimulation (ONS) has proven to be an important method in the treatment of severe therapy-resistant neurological pain disorders. The correspondence between lead placement as well as possible stimulation parameters and the resulting stimulation effects remains unclear. The method aims to directly relate the neuromodulatory mechanisms with the clinical treatment results, to achieve insight in the mode of action of neuromodulation, to identify the most effective stimulation sets and to optimize individual treatment effects. We describe a new computer-based imaging method for mapping the spatial, cognitive and affective sensory effects of ONS. The procedure allows a quantitative and qualitative analysis of the relationship between lead positioning, the stimulation settings as well as the sensory and clinical stimulation effects. A regular mapping of stimulation and sensory parameters allows a coordinated monitoring. The stimulation results can be reviewed and compared with regards to clinical effectiveness. Copyright © 2015 Elsevier Inc. All rights reserved.

Metric modular spaces

CERN Document Server

Chistyakov, Vyacheslav

2015-01-01

Aimed toward researchers and graduate students familiar with elements of functional analysis, linear algebra, and general topology; this book contains a general study of modulars, modular spaces, and metric modular spaces. Modulars may be thought of as generalized velocity fields and serve two important purposes: generate metric spaces in a unified manner and provide a weaker convergence, the modular convergence, whose topology is non-metrizable in general. Metric modular spaces are extensions of metric spaces, metric linear spaces, and classical modular linear spaces. The topics covered include the classification of modulars, metrizability of modular spaces, modular transforms and duality between modular spaces, metric  and modular topologies. Applications illustrated in this book include: the description of superposition operators acting in modular spaces, the existence of regular selections of set-valued mappings, new interpretations of spaces of Lipschitzian and absolutely continuous mappings, the existe...

On a correspondence between regular and non-regular operator monotone functions

DEFF Research Database (Denmark)

Gibilisco, P.; Hansen, Frank; Isola, T.

2009-01-01

We prove the existence of a bijection between the regular and the non-regular operator monotone functions satisfying a certain functional equation. As an application we give a new proof of the operator monotonicity of certain functions related to the Wigner-Yanase-Dyson skew information....

A two-way regularization method for MEG source reconstruction

KAUST Repository

Tian, Tian Siva; Huang, Jianhua Z.; Shen, Haipeng; Li, Zhimin

2012-01-01

The MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.

A two-way regularization method for MEG source reconstruction

KAUST Repository

Tian, Tian Siva

2012-09-01

The MEG inverse problem refers to the reconstruction of the neural activity of the brain from magnetoencephalography (MEG) measurements. We propose a two-way regularization (TWR) method to solve the MEG inverse problem under the assumptions that only a small number of locations in space are responsible for the measured signals (focality), and each source time course is smooth in time (smoothness). The focality and smoothness of the reconstructed signals are ensured respectively by imposing a sparsity-inducing penalty and a roughness penalty in the data fitting criterion. A two-stage algorithm is developed for fast computation, where a raw estimate of the source time course is obtained in the first stage and then refined in the second stage by the two-way regularization. The proposed method is shown to be effective on both synthetic and real-world examples. © Institute of Mathematical Statistics, 2012.

Stochastic analytic regularization

International Nuclear Information System (INIS)

Alfaro, J.

1984-07-01

Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)

Spiking irregularity and frequency modulate the behavioral report of single-neuron stimulation.

Science.gov (United States)

Doron, Guy; von Heimendahl, Moritz; Schlattmann, Peter; Houweling, Arthur R; Brecht, Michael

2014-02-05

The action potential activity of single cortical neurons can evoke measurable sensory effects, but it is not known how spiking parameters and neuronal subtypes affect the evoked sensations. Here, we examined the effects of spike train irregularity, spike frequency, and spike number on the detectability of single-neuron stimulation in rat somatosensory cortex. For regular-spiking, putative excitatory neurons, detectability increased with spike train irregularity and decreasing spike frequencies but was not affected by spike number. Stimulation of single, fast-spiking, putative inhibitory neurons led to a larger sensory effect compared to regular-spiking neurons, and the effect size depended only on spike irregularity. An ideal-observer analysis suggests that, under our experimental conditions, rats were using integration windows of a few hundred milliseconds or more. Our data imply that the behaving animal is sensitive to single neurons' spikes and even to their temporal patterning. Copyright © 2014 Elsevier Inc. All rights reserved.

Analytic semigroups and optimal regularity in parabolic problems

CERN Document Server

Lunardi, Alessandra

2012-01-01

The book shows how the abstract methods of analytic semigroups and evolution equations in Banach spaces can be fruitfully applied to the study of parabolic problems. Particular attention is paid to optimal regularity results in linear equations. Furthermore, these results are used to study several other problems, especially fully nonlinear ones. Owing to the new unified approach chosen, known theorems are presented from a novel perspective and new results are derived. The book is self-contained. It is addressed to PhD students and researchers interested in abstract evolution equations and in p

Functional differential equations with unbounded delay in extrapolation spaces

Directory of Open Access Journals (Sweden)

Mostafa Adimy

2014-08-01

Full Text Available We study the existence, regularity and stability of solutions for nonlinear partial neutral functional differential equations with unbounded delay and a Hille-Yosida operator on a Banach space X. We consider two nonlinear perturbations: the first one is a function taking its values in X and the second one is a function belonging to a space larger than X, an extrapolated space. We use the extrapolation techniques to prove the existence and regularity of solutions and we establish a linearization principle for the stability of the equilibria of our equation.

Image super-resolution reconstruction based on regularization technique and guided filter

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

2017-06-01

In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

Modern management of epilepsy: Vagus nerve stimulation.

Science.gov (United States)

Ben-Menachem, E

1996-12-01

Vagus nerve stimulation (VNS) was first tried as a treatment for seizure patients in 1988. The idea to stimulate the vagus nerve and disrupt or prevent seizures was proposed by Jacob Zabarra. He observed a consistent finding among several animal studies which indicated that stimulation of the vagus nerve could alter the brain wave patterns of the animals under study. His hypothesis formed the basis for the development of the vagus nerve stimulator, an implantable device similar to a pacemaker, which is implanted in the left chest and attached to the left vagus nerve via a stimulating lead. Once implanted, the stimulator is programmed by a physician to deliver regular stimulation 24 hours a day regardless of seizure activity. Patients can also activate extra 'on-demand' stimulation with a handheld magnet. Clinical studies have demonstrated VNS therapy to be a safe and effective mode of treatment when added to the existing regimen of severe, refractory patients with epilepsy. Efficacy ranges from seizure free to no response with the majority of patients (> 50%) reporting at least a 50% improvement in number of seizures after 1.5 years of treatment. The side-effect profile is unique and mostly includes stimulation-related sensations in the neck and throat. The mechanism of action for VNS is not clearly understood although two theories have emerged. First, the direct connection theory hypothesizes that the anticonvulsant action of VNS is caused by a threshold raising effect of the connections to the nucleus of the solitary tract and on to other structures. The second is the concept that chronic stimulation of the vagus nerve increases the amount of inhibitory neurotransmitters and decreases the amount of excitatory neurotransmitters. Additional research into the optimal use of VNS is ongoing. Animal and clinical research have produced some interesting new data suggesting there are numerous ways to improve the clinical performance of vagus nerve stimulation as a

Optokinetic stimulation modulates neglect for the number space: Evidence from mental number interval bisection

Directory of Open Access Journals (Sweden)

Konstantinos ePriftis

2012-02-01

Full Text Available Behavioral, neuropsychological, and neuroimaging data support the idea that numbers are represented along a mental number line (MNL, an analogical, visuo-spatial representation of number magnitude. The MNL is left-to-right oriented, with small numbers on the left and larger numbers on the right. Left neglect patients are impaired in processing the left side of the MNL and show a rightward deviation in the mental bisection of numerical intervals. In the present study we investigated the effects of optokinetic stimulation (OKS -a technique inducing spatial attention shifts by means of activation of the optokinetic nystagmus- on mental number interval bisection. One patient with left neglect following right hemisphere stroke (BG and four control patients with right hemisphere damage, but without neglect, performed the mental number interval bisection task in three experimental conditions of OKS: static, leftward, and rightward. In the static condition, BG misbisected to the right of the true midpoint. BG misbisected to the left following leftward OKS, but again to the right of the midpoint following rightward OKS. In contrast, the performance of controls was not significantly affected by the direction of OKS. We argue that shifts of visuospatial attention, induced by OKS, may affect the mental number interval bisection, suggesting the presence of an interaction between the processing of number magnitude and the processing of the perceptual space, in patients with neglect for the mental number space.

Regularization in global sound equalization based on effort variation

DEFF Research Database (Denmark)

Stefanakis, Nick; Sarris, John; Jacobsen, Finn

2009-01-01

. Effort variation equalization involves modifying the conventional cost function in sound equalization, which is based on minimizing least-squares reproduction errors, by adding a term that is proportional to the squared deviations between complex source strengths, calculated independently for the sources......Sound equalization in closed spaces can be significantly improved by generating propagating waves that are naturally associated with the geometry, as, for example, plane waves in rectangular enclosures. This paper presents a control approach termed effort variation regularization based on this idea...

Color correction optimization with hue regularization

Science.gov (United States)

Zhang, Heng; Liu, Huaping; Quan, Shuxue

2011-01-01

Previous work has suggested that observers are capable of judging the quality of an image without any knowledge of the original scene. When no reference is available, observers can extract the apparent objects in an image and compare them with the typical colors of similar objects recalled from their memories. Some generally agreed upon research results indicate that although perfect colorimetric rendering is not conspicuous and color errors can be well tolerated, the appropriate rendition of certain memory colors such as skin, grass, and sky is an important factor in the overall perceived image quality. These colors are appreciated in a fairly consistent manner and are memorized with slightly different hues and higher color saturation. The aim of color correction for a digital color pipeline is to transform the image data from a device dependent color space to a target color space, usually through a color correction matrix which in its most basic form is optimized through linear regressions between the two sets of data in two color spaces in the sense of minimized Euclidean color error. Unfortunately, this method could result in objectionable distortions if the color error biased certain colors undesirably. In this paper, we propose a color correction optimization method with preferred color reproduction in mind through hue regularization and present some experimental results.

Universal regularization prescription for Lovelock AdS gravity

International Nuclear Information System (INIS)

Kofinas, Georgios; Olea, Rodrigo

2007-01-01

A definite form for the boundary term that produces the finiteness of both the conserved quantities and Euclidean action for any Lovelock gravity with AdS asymptotics is presented. This prescription merely tells even from odd bulk dimensions, regardless the particular theory considered, what is valid even for Einstein-Hilbert and Einstein-Gauss-Bonnet AdS gravity. The boundary term is a given polynomial of the boundary extrinsic and intrinsic curvatures (also referred to as Kounterterms series). Only the coupling constant of the boundary term changes accordingly, such that it always preserves a well-posed variational principle for boundary conditions suitable for asymptotically AdS spaces. The background-independent conserved charges associated to asymptotic symmetries are found. In odd bulk dimensions, this regularization produces a generalized formula for the vacuum energy in Lovelock AdS gravity. The standard entropy for asymptotically AdS black holes is recovered directly from the regularization of the Euclidean action, and not only from the first law of thermodynamics associated to the conserved quantities

Existence, regularity and representation of solutions of time fractional wave equations

Directory of Open Access Journals (Sweden)

Valentin Keyantuo

2017-09-01

Full Text Available We study the solvability of the fractional order inhomogeneous Cauchy problem $$ \\mathbb{D}_t^\\alpha u(t=Au(t+f(t, \\quad t>0,\\;1<\\alpha\\le 2, $$ where A is a closed linear operator in some Banach space X and $f:[0,\\infty\\to X$ a given function. Operator families associated with this problem are defined and their regularity properties are investigated. In the case where A is a generator of a $\\beta$-times integrated cosine family $(C_\\beta(t$, we derive explicit representations of mild and classical solutions of the above problem in terms of the integrated cosine family. We include applications to elliptic operators with Dirichlet, Neumann or Robin type boundary conditions on $L^p$-spaces and on the space of continuous functions.

Multiview vector-valued manifold regularization for multilabel image classification.

Science.gov (United States)

Luo, Yong; Tao, Dacheng; Xu, Chang; Xu, Chao; Liu, Hong; Wen, Yonggang

2013-05-01

In computer vision, image datasets used for classification are naturally associated with multiple labels and comprised of multiple views, because each image may contain several objects (e.g., pedestrian, bicycle, and tree) and is properly characterized by multiple visual features (e.g., color, texture, and shape). Currently, available tools ignore either the label relationship or the view complementarily. Motivated by the success of the vector-valued function that constructs matrix-valued kernels to explore the multilabel structure in the output space, we introduce multiview vector-valued manifold regularization (MV(3)MR) to integrate multiple features. MV(3)MR exploits the complementary property of different features and discovers the intrinsic local geometry of the compact support shared by different features under the theme of manifold regularization. We conduct extensive experiments on two challenging, but popular, datasets, PASCAL VOC' 07 and MIR Flickr, and validate the effectiveness of the proposed MV(3)MR for image classification.

Effective field theory dimensional regularization

International Nuclear Information System (INIS)

Lehmann, Dirk; Prezeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed

Effective field theory dimensional regularization

Science.gov (United States)

Lehmann, Dirk; Prézeau, Gary

2002-01-01

A Lorentz-covariant regularization scheme for effective field theories with an arbitrary number of propagating heavy and light particles is given. This regularization scheme leaves the low-energy analytic structure of Greens functions intact and preserves all the symmetries of the underlying Lagrangian. The power divergences of regularized loop integrals are controlled by the low-energy kinematic variables. Simple diagrammatic rules are derived for the regularization of arbitrary one-loop graphs and the generalization to higher loops is discussed.

Electrically Stimulated Antagonist Muscle Contraction Increased Muscle Mass and Bone Mineral Density of One Astronaut - Initial Verification on the International Space Station

OpenAIRE

Shiba, Naoto; Matsuse, Hiroo; Takano, Yoshio; Yoshimitsu, Kazuhiro; Omoto, Masayuki; Hashida, Ryuki; Tagawa, Yoshihiko; Inada, Tomohisa; Yamada, Shin; Ohshima, Hiroshi

2015-01-01

Background Musculoskeletal atrophy is one of the major problems of extended periods of exposure to weightlessness such as on the International Space Station (ISS). We developed the Hybrid Training System (HTS) to maintain an astronaut?s musculoskeletal system using an electrically stimulated antagonist to resist the volitional contraction of the agonist instead of gravity. The present study assessed the system?s orbital operation capability and utility, as well as its preventative effect on a...

UNIVERSAL REGULAR AUTONOMOUS ASYNCHRONOUS SYSTEMS: ω-LIMIT SETS, INVARIANCE AND BASINS OF ATTRACTION

Directory of Open Access Journals (Sweden)

Serban Vlad

2011-07-01

Full Text Available The asynchronous systems are the non-deterministic real timebinarymodels of the asynchronous circuits from electrical engineering.Autonomy means that the circuits and their models have no input.Regularity means analogies with the dynamical systems, thus such systems may be considered to be real time dynamical systems with a’vector field’, Universality refers to the case when the state space of the system is the greatest possible in the sense of theinclusion. The purpose of this paper is that of defining, by analogy with the dynamical systems theory, the omega-limit sets, the invariance and the basins of attraction of the universal regular autonomous asynchronous systems.

Different Stimulation Frequencies Alter Synchronous Fluctuations in Motor Evoked Potential Amplitude of Intrinsic Hand Muscles—a TMS Study

Science.gov (United States)

Sale, Martin V.; Rogasch, Nigel C.; Nordstrom, Michael A.

2016-01-01

The amplitude of motor-evoked potentials (MEPs) elicited with transcranial magnetic stimulation (TMS) varies from trial-to-trial. Synchronous oscillations in cortical neuronal excitability contribute to this variability, however it is not known how different frequencies of stimulation influence MEP variability, and whether these oscillations are rhythmic or aperiodic. We stimulated the motor cortex with TMS at different regular (i.e., rhythmic) rates, and compared this with pseudo-random (aperiodic) timing. In 18 subjects, TMS was applied at three regular frequencies (0.05 Hz, 0.2 Hz, 1 Hz) and one aperiodic frequency (mean 0.2 Hz). MEPs (n = 50) were recorded from three intrinsic hand muscles of the left hand with different functional and anatomical relations. MEP amplitude correlation was highest for the functionally related muscle pair, less for the anatomically related muscle pair and least for the functionally- and anatomically-unrelated muscle pair. MEP correlations were greatest with 1 Hz, and least for stimulation at 0.05 Hz. Corticospinal neuron synchrony is higher with shorter TMS intervals. Further, corticospinal neuron synchrony is similar irrespective of whether the stimulation is periodic or aperiodic. These findings suggest TMS frequency is a crucial consideration for studies using TMS to probe correlated activity between muscle pairs. PMID:27014031

75 FR 76006 - Regular Meeting

Science.gov (United States)

2010-12-07

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. ACTION: Regular meeting. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). Date and Time: The meeting of the Board will be held...

Regular Topographic Patterning of Karst Depressions Suggests Landscape Self-Organization

Science.gov (United States)

Quintero, C.; Cohen, M. J.

2017-12-01

Thousands of wetland depressions that are commonly host to cypress domes dot the sub-tropical limestone landscape of South Florida. The origin of these depression features has been the topic of debate. Here we build upon the work of previous surveyors of this landscape to analyze the morphology and spatial distribution of depressions on the Big Cypress landscape. We took advantage of the emergence and availability of high resolution Light Direction and Ranging (LiDAR) technology and ArcMap GIS software to analyze the structure and regularity of landscape features with methods unavailable to past surveyors. Six 2.25 km2 LiDAR plots within the preserve were selected for remote analysis and one depression feature within each plot was selected for more intensive sediment and water depth surveying. Depression features on the Big Cypress landscape were found to show strong evidence of regular spatial patterning. Periodicity, a feature of regularly patterned landscapes, is apparent in both Variograms and Radial Spectrum Analyses. Size class distributions of the identified features indicate constrained feature sizes while Average Nearest Neighbor analyses support the inference of dispersed features with non-random spacing. The presence of regular patterning on this landscape strongly implies biotic reinforcement of spatial structure by way of the scale dependent feedback. In characterizing the structure of this wetland landscape we add to the growing body of work dedicated to documenting how water, life and geology may interact to shape the natural landscapes we see today.

General inverse problems for regular variation

DEFF Research Database (Denmark)

Damek, Ewa; Mikosch, Thomas Valentin; Rosinski, Jan

2014-01-01

Regular variation of distributional tails is known to be preserved by various linear transformations of some random structures. An inverse problem for regular variation aims at understanding whether the regular variation of a transformed random object is caused by regular variation of components ...

Abel transforms with low regularity with applications to x-ray tomography on spherically symmetric manifolds

Science.gov (United States)

de Hoop, Maarten V.; Ilmavirta, Joonas

2017-12-01

We study ray transforms on spherically symmetric manifolds with a piecewise C1, 1 metric. Assuming the Herglotz condition, the x-ray transform is injective on the space of L 2 functions on such manifolds. We also prove injectivity results for broken ray transforms (with and without periodicity) on such manifolds with a C1, 1 metric. To make these problems tractable in low regularity, we introduce and study a class of generalized Abel transforms and study their properties. This low regularity setting is relevant for geophysical applications.

Playful Interactions Stimulating Physical Activity in Public Spaces

DEFF Research Database (Denmark)

Sturm, Janienke; Bekker, Tilde; Vanden Abeele, Vero

In this position paper we describe our vision on designing playful interactions to persuade people to be physically active in public spaces. Social embeddedness and playful interaction are the core elements of this vision. We illustrate how our design vision is incorporated into innovative concepts...... to motivate each other to be physically active by creating challenges for each other. Designing playful solutions for public spaces asks for low-threshold solutions that support easy stepping in and stepping out solutions....

On Orthogonal Decomposition of a Sobolev Space

OpenAIRE

Lakew, Dejenie A.

2016-01-01

The theme of this short article is to investigate an orthogonal decomposition of a Sobolev space and look at some properties of the inner product therein and the distance defined from the inner product. We also determine the dimension of the orthogonal difference space and show the expansion of spaces as their regularity increases.

Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM).

Science.gov (United States)

Poddar, Sunrita; Jacob, Mathews

2016-04-01

We introduce a novel algorithm to recover real time dynamic MR images from highly under-sampled k- t space measurements. The proposed scheme models the images in the dynamic dataset as points on a smooth, low dimensional manifold in high dimensional space. We propose to exploit the non-linear and non-local redundancies in the dataset by posing its recovery as a manifold smoothness regularized optimization problem. A navigator acquisition scheme is used to determine the structure of the manifold, or equivalently the associated graph Laplacian matrix. The estimated Laplacian matrix is used to recover the dataset from undersampled measurements. The utility of the proposed scheme is demonstrated by comparisons with state of the art methods in multi-slice real-time cardiac and speech imaging applications.

Optokinetic Stimulation Modulates Neglect for the Number Space: Evidence from Mental Number Interval Bisection

Science.gov (United States)

Priftis, Konstantinos; Pitteri, Marco; Meneghello, Francesca; Umiltà, Carlo; Zorzi, Marco

2012-01-01

Behavioral, neuropsychological, and neuroimaging data support the idea that numbers are represented along a mental number line (MNL), an analogical, visuospatial representation of number magnitude. The MNL is left-to-right oriented in Western cultures, with small numbers on the left and larger numbers on the right. Left neglect patients are impaired in the mental bisection of numerical intervals, with a bias toward larger numbers that are relatively to the right on the MNL. In the present study we investigated the effects of optokinetic stimulation (OKS) – a technique inducing visuospatial attention shifts by means of activation of the optokinetic nystagmus – on number interval bisection. One patient with left neglect following right-hemisphere stroke (BG) and four control patients with right-hemisphere damage, but without neglect, performed the number interval bisection task in three conditions of OKS: static, leftward, and rightward. In the static condition, BG misbisected to the right of the true midpoint. BG misbisected to the left following leftward OKS, and again to the right of the midpoint following rightward OKS. Moreover, the variability of BG’s performance was smaller following both leftward and rightward OKS, suggesting that the attentional bias induced by OKS reduced the “indifference zone” that is thought to underlie the length effect reported in bisection tasks. We argue that shifts of visuospatial attention, induced by OKS, may affect number interval bisection, thereby revealing an interaction between the processing of the perceptual space and the processing of the number space. PMID:22363280

From Discrete Space-Time to Minkowski Space: Basic Mechanisms, Methods and Perspectives

Science.gov (United States)

Finster, Felix

This survey article reviews recent results on fermion systems in discrete space-time and corresponding systems in Minkowski space. After a basic introduction to the discrete setting, we explain a mechanism of spontaneous symmetry breaking which leads to the emergence of a discrete causal structure. As methods to study the transition between discrete space-time and Minkowski space, we describe a lattice model for a static and isotropic space-time, outline the analysis of regularization tails of vacuum Dirac sea configurations, and introduce a Lorentz invariant action for the masses of the Dirac seas. We mention the method of the continuum limit, which allows to analyze interacting systems. Open problems are discussed.

Online co-regularized algorithms

NARCIS (Netherlands)

Ruijter, T. de; Tsivtsivadze, E.; Heskes, T.

2012-01-01

We propose an online co-regularized learning algorithm for classification and regression tasks. We demonstrate that by sequentially co-regularizing prediction functions on unlabeled data points, our algorithm provides improved performance in comparison to supervised methods on several UCI benchmarks

Geometric continuum regularization of quantum field theory

International Nuclear Information System (INIS)

Halpern, M.B.

1989-01-01

An overview of the continuum regularization program is given. The program is traced from its roots in stochastic quantization, with emphasis on the examples of regularized gauge theory, the regularized general nonlinear sigma model and regularized quantum gravity. In its coordinate-invariant form, the regularization is seen as entirely geometric: only the supermetric on field deformations is regularized, and the prescription provides universal nonperturbative invariant continuum regularization across all quantum field theory. 54 refs

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

Science.gov (United States)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal

Wave dynamics of regular and chaotic rays

International Nuclear Information System (INIS)

McDonald, S.W.

1983-09-01

In order to investigate general relationships between waves and rays in chaotic systems, I study the eigenfunctions and spectrum of a simple model, the two-dimensional Helmholtz equation in a stadium boundary, for which the rays are ergodic. Statistical measurements are performed so that the apparent randomness of the stadium modes can be quantitatively contrasted with the familiar regularities observed for the modes in a circular boundary (with integrable rays). The local spatial autocorrelation of the eigenfunctions is constructed in order to indirectly test theoretical predictions for the nature of the Wigner distribution corresponding to chaotic waves. A portion of the large-eigenvalue spectrum is computed and reported in an appendix; the probability distribution of successive level spacings is analyzed and compared with theoretical predictions. The two principal conclusions are: 1) waves associated with chaotic rays may exhibit randomly situated localized regions of high intensity; 2) the Wigner function for these waves may depart significantly from being uniformly distributed over the surface of constant frequency in the ray phase space

Using Tikhonov Regularization for Spatial Projections from CSR Regularized Spherical Harmonic GRACE Solutions

Science.gov (United States)

Save, H.; Bettadpur, S. V.

2013-12-01

It has been demonstrated before that using Tikhonov regularization produces spherical harmonic solutions from GRACE that have very little residual stripes while capturing all the signal observed by GRACE within the noise level. This paper demonstrates a two-step process and uses Tikhonov regularization to remove the residual stripes in the CSR regularized spherical harmonic coefficients when computing the spatial projections. We discuss methods to produce mass anomaly grids that have no stripe features while satisfying the necessary condition of capturing all observed signal within the GRACE noise level.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yunji; Jing, Bing-Yi; Gao, Xin

2015-01-01

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Regularized maximum correntropy machine

KAUST Repository

Wang, Jim Jing-Yan

2015-02-12

In this paper we investigate the usage of regularized correntropy framework for learning of classifiers from noisy labels. The class label predictors learned by minimizing transitional loss functions are sensitive to the noisy and outlying labels of training samples, because the transitional loss functions are equally applied to all the samples. To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework. Moreover, we regularize the predictor parameter to control the complexity of the predictor. The learning problem is formulated by an objective function considering the parameter regularization and MCC simultaneously. By optimizing the objective function alternately, we develop a novel predictor learning algorithm. The experiments on two challenging pattern classification tasks show that it significantly outperforms the machines with transitional loss functions.

Different stimulation frequencies alter synchronous fluctuations in motor evoked potential amplitude of intrinsic hand muscles – a TMS study.

Directory of Open Access Journals (Sweden)

Martin Victor Sale

2016-03-01

Full Text Available The amplitude of motor-evoked potentials (MEPs elicited with transcranial magnetic stimulation (TMS varies from trial-to-trial. Synchronous oscillations in cortical neuronal excitability contribute to this variability, however it is not known how different frequencies of stimulation influence MEP variability, and whether these oscillations are rhythmic or aperiodic. We stimulated the motor cortex with TMS at different regular (i.e., rhythmic rates, and compared this with pseudo-random (aperiodic timing. In 18 subjects, TMS was applied at three regular frequencies (0.05 Hz, 0.2 Hz, 1 Hz and one aperiodic frequency (mean 0.2 Hz. MEPs (n = 50 were recorded from three intrinsic hand muscles of the left hand with different functional and anatomical relations. MEP amplitude correlation was highest for the functionally related muscle pair, less for the anatomically related muscle pair and least for the functionally- and anatomically-unrelated muscle pair. MEP correlations were greatest with 1 Hz, and least for stimulation at 0.05 Hz. Corticospinal neuron synchrony is higher with shorter TMS intervals. Further, corticospinal neuron synchrony is similar irrespective of whether the stimulation is periodic or aperiodic. These findings suggest TMS frequency is a crucial consideration for studies using TMS to probe correlated activity between muscle pairs.

Application of dimensional regularization to single chain polymer static properties: Conformational space renormalization of polymers. III

International Nuclear Information System (INIS)

Oono, Y.; Ohta, T.; Freed, K.F.

1981-01-01

A dimensional regularization approach to the renormalization group treatment of polymer excluded volume is formulated in chain conformation space where monomers are specified by their spatial positions and their positions along the chain and the polymers may be taken to be monodisperse. The method utilizes basic scale invariance considerations. First, it is recognized that long wavelength macroscopic descriptions must be well defined in the limit that the minimum atomic or molecular scale L is set to zero. Secondly, the microscopic theory is independent of the conveniently chosen macroscopic scale of length k. The freedom of choice of k is exploited along with the assumed renormalizability of the theory to provide the renormalization group equations which directly imply the universal scaling laws for macroscopic properties. The renormalizability of the model implies the existence of the general relations between the basic macroparameters, such as chain length, excluded volume, etc., and their microscopic counterparts in the microscopic model for the system. These macro--micro relations are defined through the condition that macroscopic quantities be well defined for polymer chains for any spatial dimensionality. The method is illustrated by calculating the end vector distribution function for all values of end vectors R. The evaluation of this distribution function currently requires the use of expansions in e = 4-d. In this case our distribution reduces to known limits for R→0 or infinity. Subsequent papers will present calculations of the polymer coherent scattering function, the monomer spatial distribution function, and concentration dependent properties

Stochastic dynamic modeling of regular and slow earthquakes

Science.gov (United States)

Aso, N.; Ando, R.; Ide, S.

2017-12-01

Both regular and slow earthquakes are slip phenomena on plate boundaries and are simulated by a (quasi-)dynamic modeling [Liu and Rice, 2005]. In these numerical simulations, spatial heterogeneity is usually considered not only for explaining real physical properties but also for evaluating the stability of the calculations or the sensitivity of the results on the condition. However, even though we discretize the model space with small grids, heterogeneity at smaller scales than the grid size is not considered in the models with deterministic governing equations. To evaluate the effect of heterogeneity at the smaller scales we need to consider stochastic interactions between slip and stress in a dynamic modeling. Tidal stress is known to trigger or affect both regular and slow earthquakes [Yabe et al., 2015; Ide et al., 2016], and such an external force with fluctuation can also be considered as a stochastic external force. A healing process of faults may also be stochastic, so we introduce stochastic friction law. In the present study, we propose a stochastic dynamic model to explain both regular and slow earthquakes. We solve mode III problem, which corresponds to the rupture propagation along the strike direction. We use BIEM (boundary integral equation method) scheme to simulate slip evolution, but we add stochastic perturbations in the governing equations, which is usually written in a deterministic manner. As the simplest type of perturbations, we adopt Gaussian deviations in the formulation of the slip-stress kernel, external force, and friction. By increasing the amplitude of perturbations of the slip-stress kernel, we reproduce complicated rupture process of regular earthquakes including unilateral and bilateral ruptures. By perturbing external force, we reproduce slow rupture propagation at a scale of km/day. The slow propagation generated by a combination of fast interaction at S-wave velocity is analogous to the kinetic theory of gasses: thermal

EIT image reconstruction with four dimensional regularization.

Science.gov (United States)

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

Production and action of cytokines in space

Science.gov (United States)

Chapes, Stephen K.; Morrison, Dennis R.; Guikema, James A.; Lewis, Marian L.; Spooner, Brian S.

1994-01-01

B6MP102 cells, a continuously cultured murine bone marrow macrophage cell line, were tested for secretion of tumor necrosis factor-alpha and Interleukin-1 during space flight. We found that B6MP102 cells secreted more tumor necrosis factor-alpha and interleukin-1 when stimulated in space with lipopolysaccharide than controls similarly stimulated on earth. This compared to increased secretion of interferon-beta and -gamma by lymphocytes that was measured on the same shuttle flights. Although space flight enhanced B6MP102 secretion of tumor necrosis factor-alpha, an experiment on a subsequent space flight (STS-50) found that cellular cytotoxicity, mediated by tumor necrosis factor-alpha, was inhibited.

Regularities of Multifractal Measures

Indian Academy of Sciences (India)

First, we prove the decomposition theorem for the regularities of multifractal Hausdorff measure and packing measure in R R d . This decomposition theorem enables us to split a set into regular and irregular parts, so that we can analyze each separately, and recombine them without affecting density properties. Next, we ...

3D realistic head model simulation based on transcranial magnetic stimulation.

Science.gov (United States)

Yang, Shuo; Xu, Guizhi; Wang, Lei; Chen, Yong; Wu, Huanli; Li, Ying; Yang, Qingxin

2006-01-01

Transcranial magnetic stimulation (TMS) is a powerful non-invasive tool for investigating functions in the brain. The target inside the head is stimulated with eddy currents induced in the tissue by the time-varying magnetic field. Precise spatial localization of stimulation sites is the key of efficient functional magnetic stimulations. Many researchers devote to magnetic field analysis in empty free space. In this paper, a realistic head model used in Finite Element Method has been developed. The magnetic field inducted in the head bt TMS has been analysed. This three-dimensional simulation is useful for spatial localization of stimulation.

Adaptive Regularization of Neural Classifiers

DEFF Research Database (Denmark)

Andersen, Lars Nonboe; Larsen, Jan; Hansen, Lars Kai

1997-01-01

We present a regularization scheme which iteratively adapts the regularization parameters by minimizing the validation error. It is suggested to use the adaptive regularization scheme in conjunction with optimal brain damage pruning to optimize the architecture and to avoid overfitting. Furthermo......, we propose an improved neural classification architecture eliminating an inherent redundancy in the widely used SoftMax classification network. Numerical results demonstrate the viability of the method...

Space proliferation versus space-type dissemination: from semantic issues to political issues

International Nuclear Information System (INIS)

Gaillard-Sborowsky, Florence

2015-01-01

The space and ballistic capabilities relationships are regularly revisited in forums on international security, in particular about Iran and North Korea cases. The term 'space proliferation' is commonly used by analogy with nuclear proliferation. However, is this analogy relevant? Beyond the semantic aspects, this shift raises political issues that this paper will consider. The study of the assumptions regarding the analysis of nuclear and missile proliferation and their space counterparts will highlight some approximations and presuppositions, such as the amalgam between sounding rockets, launchers and missiles technologies, in order to suggest new thinking of these sensitive issues. (author)

14 CFR 121.15 - Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. 121.15 Section 121.15 Aeronautics and Space FEDERAL AVIATION....15 Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. If a...

Aging women with polycystic ovary syndrome who achieve regular menstrual cycles have a smaller follicle cohort than those who continue to have irregular cycles

NARCIS (Netherlands)

Elting, Mariet W.; Kwee, Janet; Korsen, Ted J.M.; Rekers-Mombarg, L.T.M.; Schoemaker, Joop

2003-01-01

To examine whether follicle loss due to ovarian aging is responsible for the occurrence of regular menstrual cycles in aging women with polycystic ovary syndrome (PCOS), the size of the FSH-sensitive follicle cohort was estimated by the exogenous follicle-stimulating hormone ovarian reserve test

Condition Number Regularized Covariance Estimation.

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2013-06-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.

Multi-label learning with fuzzy hypergraph regularization for protein subcellular location prediction.

Science.gov (United States)

Chen, Jing; Tang, Yuan Yan; Chen, C L Philip; Fang, Bin; Lin, Yuewei; Shang, Zhaowei

2014-12-01

Protein subcellular location prediction aims to predict the location where a protein resides within a cell using computational methods. Considering the main limitations of the existing methods, we propose a hierarchical multi-label learning model FHML for both single-location proteins and multi-location proteins. The latent concepts are extracted through feature space decomposition and label space decomposition under the nonnegative data factorization framework. The extracted latent concepts are used as the codebook to indirectly connect the protein features to their annotations. We construct dual fuzzy hypergraphs to capture the intrinsic high-order relations embedded in not only feature space, but also label space. Finally, the subcellular location annotation information is propagated from the labeled proteins to the unlabeled proteins by performing dual fuzzy hypergraph Laplacian regularization. The experimental results on the six protein benchmark datasets demonstrate the superiority of our proposed method by comparing it with the state-of-the-art methods, and illustrate the benefit of exploiting both feature correlations and label correlations.

C1,1 regularity for degenerate elliptic obstacle problems

Science.gov (United States)

Daskalopoulos, Panagiota; Feehan, Paul M. N.

2016-03-01

The Heston stochastic volatility process is a degenerate diffusion process where the degeneracy in the diffusion coefficient is proportional to the square root of the distance to the boundary of the half-plane. The generator of this process with killing, called the elliptic Heston operator, is a second-order, degenerate-elliptic partial differential operator, where the degeneracy in the operator symbol is proportional to the distance to the boundary of the half-plane. In mathematical finance, solutions to the obstacle problem for the elliptic Heston operator correspond to value functions for perpetual American-style options on the underlying asset. With the aid of weighted Sobolev spaces and weighted Hölder spaces, we establish the optimal C 1 , 1 regularity (up to the boundary of the half-plane) for solutions to obstacle problems for the elliptic Heston operator when the obstacle functions are sufficiently smooth.

Some regularities in invertebrate succession in different microhabitats on pine stumps

OpenAIRE

Franch, Joan

1989-01-01

Sixty eight pine stumps felled on known dates from one to sixteen years before the moment of sampling have been studied in the San Juan de la Peña woodland (province of Huesca). Four microhabitats were distinguished: bark, subcortical space, sapwood and heartwood. The object of the study is to compare the invertebrate macrofauna succession of the different microhabitats in order to find regularities among them. The biocenosis has not been completely studied: ipidae, diptera and annelidae are ...

14 CFR 137.23 - Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. 137.23 Section 137.23 Aeronautics and Space FEDERAL AVIATION... drugs, marihuana, and depressant or stimulant drugs or substances. If the holder of a certificate issued...

14 CFR 133.14 - Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. 133.14 Section 133.14 Aeronautics and Space FEDERAL AVIATION... narcotic drugs, marihuana, and depressant or stimulant drugs or substances. If the holder of a certificate...

14 CFR 141.18 - Carriage of narcotic drugs, marijuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marijuana, and depressant or stimulant drugs or substances. 141.18 Section 141.18 Aeronautics and Space FEDERAL AVIATION... General § 141.18 Carriage of narcotic drugs, marijuana, and depressant or stimulant drugs or substances...

Initiating and maintaining recreational walking: a longitudinal study on the influence of neighborhood green space.

Science.gov (United States)

Sugiyama, Takemi; Giles-Corti, Billie; Summers, Jacqui; du Toit, Lorinne; Leslie, Eva; Owen, Neville

2013-09-01

This study examined prospective relationships of green space attributes with adults initiating or maintaining recreational walking. Postal surveys were completed by 1036 adults living in Adelaide, Australia, at baseline (two time points in 2003-04) and follow-up (2007-08). Initiating or maintaining recreational walking was determined using self-reported walking frequency. Green space attributes examined were perceived presence, quality, proximity, and the objectively measured area (total and largest) and number of green spaces within a 1.6 km buffer drawn from the center of each study neighborhood. Multilevel regression analyses examined the odds of initiating or maintaining walking separately for each green space attribute. At baseline, participants were categorized into non-regular (n = 395), regular (n = 286), and irregular walkers (n = 313). Among non-regular walkers, 30% had initiated walking, while 70% of regular walkers had maintained walking at follow-up. No green space attributes were associated with initiating walking. However, positive perceptions of the presence of and proximity to green spaces and the total and largest areas of green space were significantly associated with a higher likelihood of walking maintenance over four years. Neighborhood green spaces may not assist adults to initiate walking, but their presence and proximity may facilitate them to maintain recreational walking over time. Copyright © 2013 Elsevier Inc. All rights reserved.

Application of Littlewood-Paley decomposition to the regularity of Boltzmann type kinetic equations

International Nuclear Information System (INIS)

EL Safadi, M.

2007-03-01

We study the regularity of kinetic equations of Boltzmann type.We use essentially Littlewood-Paley method from harmonic analysis, consisting mainly in working with dyadics annulus. We shall mainly concern with the homogeneous case, where the solution f(t,x,v) depends only on the time t and on the velocities v, while working with realistic and singular cross-sections (non cutoff). In the first part, we study the particular case of Maxwellian molecules. Under this hypothesis, the structure of the Boltzmann operator and his Fourier transform write in a simple form. We show a global C ∞ regularity. Then, we deal with the case of general cross-sections with 'hard potential'. We are interested in the Landau equation which is limit equation to the Boltzmann equation, taking in account grazing collisions. We prove that any weak solution belongs to Schwartz space S. We demonstrate also a similar regularity for the case of Boltzmann equation. Let us note that our method applies directly for all dimensions, and proofs are often simpler compared to other previous ones. Finally, we finish with Boltzmann-Dirac equation. In particular, we adapt the result of regularity obtained in Alexandre, Desvillettes, Wennberg and Villani work, using the dissipation rate connected with Boltzmann-Dirac equation. (author)

External laryngeal nerve in thyroid surgery: is the nerve stimulator necessary?

Science.gov (United States)

Aina, E N; Hisham, A N

2001-09-01

To find out the incidence and type of external laryngeal nerves during operations on the thyroid, and to assess the role of a nerve stimulator in detecting them. Prospective, non-randomised study. Teaching hospital, Malaysia. 317 patients who had 447 dissections between early January 1998 and late November 1999. Number and type of nerves crossing the cricothyroid space, and the usefulness of the nerve stimulator in finding them. The nerve stimulator was used in 206/447 dissections (46%). 392 external laryngeal nerves were seen (88%), of which 196/206 (95%) were detected with the stimulator. However, without the stimulator 196 nerves were detected out of 241 dissections (81%). The stimulator detected 47 (23%) Type I nerves (nerve > 1 cm from the upper edge of superior pole); 86 (42%) Type IIa nerves (nerve edge of superior pole); and 63 (31%) Type IIb nerves (nerve below upper edge of superior pole). 10 nerves were not detected. When the stimulator was not used the corresponding figures were 32 (13%), 113 (47%), and 51 (21%), and 45 nerves were not seen. If the nerve cannot be found we recommend dissection of capsule close to the medial border of the upper pole of the thyroid to avoid injury to the nerve. Although the use of the nerve stimulator seems desirable, it confers no added advantage in finding the nerve. In the event of uncertainty about whether a structure is the nerve, the stimulator may help to confirm it. However, exposure of the cricothyroid space is most important for good exposure in searching for the external laryngeal nerve.

Transcranial alternating current stimulation with sawtooth waves: simultaneous stimulation and EEG recording

Directory of Open Access Journals (Sweden)

James eDowsett

2016-03-01

Full Text Available Transcranial alternating current stimulation (tACS has until now mostly been administered as an alternating sinusoidal wave. Despite modern tACS stimulators being able to deliver alternating current with any arbitrary shape there has been no systematic exploration into the relative benefits of different waveforms. As tACS is a relatively new technique there is a huge parameter space of unexplored possibilities which may prove superior or complimentary to the traditional sinusoidal waveform. Here we begin to address this with an investigation into the effects of sawtooth wave tACS on individual alpha power. Evidence from animal models suggests that the gradient and direction of an electric current should be important factors for the subsequent neural firing rate; we compared positive and negative ramp sawtooth waves to test this. An additional advantage of sawtooth waves is that the resulting artefact in the electroencephalogram (EEG recording is significantly simpler to remove than a sine wave; accordingly we were able to observe alpha oscillations both during and after stimulation.We found that positive ramp sawtooth, but not negative ramp sawtooth, significantly enhanced alpha power during stimulation relative to sham (p<0.01. In addition we tested for an after-effect of both sawtooth and sinusoidal stimulation on alpha power but in this case did not find any significant effect. This preliminary study paves the way for further investigations into the effect of the gradient and direction of the current in tACS which could significantly improve the usefulness of this technique.

Geometry on the space of geometries

International Nuclear Information System (INIS)

Christodoulakis, T.; Zanelli, J.

1988-06-01

We discuss the geometric structure of the configuration space of pure gravity. This is an infinite dimensional manifold, M, where each point represents one spatial geometry g ij (x). The metric on M is dictated by geometrodynamics, and from it, the Christoffel symbols and Riemann tensor can be found. A ''free geometry'' tracing a geodesic on the manifold describes the time evolution of space in the strong gravity limit. In a regularization previously introduced by the authors, it is found that M does not have the same dimensionality, D, everywhere, and that D is not a scalar, although it is covariantly constant. In this regularization, it is seen that the path integral measure can be absorbed in a renormalization of the cosmological constant. (author). 19 refs

Condition Number Regularized Covariance Estimation*

Science.gov (United States)

Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala

2012-01-01

Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197

Network effects of subthalamic deep brain stimulation drive a unique mixture of responses in basal ganglia output

OpenAIRE

Humphries, Mark D.; Gurney, Kevin

2012-01-01

Deep brain stimulation (DBS) is a remarkably successful treatment for the motor symptoms of Parkinson's disease. High-frequency stimulation of the subthalamic nucleus (STN) within the basal ganglia is a main clinical target, but the physiological mechanisms of therapeutic STN DBS at the cellular and network level are unclear. We set out to begin to address the hypothesis that a mixture of responses in the basal ganglia output nuclei, combining regularized firing and inhibition, is a key contr...

Diffusion of charged particles in strong large-scale random and regular magnetic fields

International Nuclear Information System (INIS)

Mel'nikov, Yu.P.

2000-01-01

The nonlinear collision integral for the Green's function averaged over a random magnetic field is transformed using an iteration procedure taking account of the strong random scattering of particles on the correlation length of the random magnetic field. Under this transformation the regular magnetic field is assumed to be uniform at distances of the order of the correlation length. The single-particle Green's functions of the scattered particles in the presence of a regular magnetic field are investigated. The transport coefficients are calculated taking account of the broadening of the cyclotron and Cherenkov resonances as a result of strong random scattering. The mean-free path lengths parallel and perpendicular to the regular magnetic field are found for a power-law spectrum of the random field. The analytical results obtained are compared with the experimental data on the transport ranges of solar and galactic cosmic rays in the interplanetary magnetic field. As a result, the conditions for the propagation of cosmic rays in the interplanetary space and a more accurate idea of the structure of the interplanetary magnetic field are determined

Regular-, irregular-, and pseudo-character processing in Chinese: The regularity effect in normal adult readers

Directory of Open Access Journals (Sweden)

Dustin Kai Yan Lau

2014-03-01

Full Text Available Background Unlike alphabetic languages, Chinese uses a logographic script. However, the pronunciation of many character’s phonetic radical has the same pronunciation as the character as a whole. These are considered regular characters and can be read through a lexical non-semantic route (Weekes & Chen, 1999. Pseudocharacters are another way to study this non-semantic route. A pseudocharacter is the combination of existing semantic and phonetic radicals in their legal positions resulting in a non-existing character (Ho, Chan, Chung, Lee, & Tsang, 2007. Pseudocharacters can be pronounced by direct derivation from the sound of its phonetic radical. Conversely, if the pronunciation of a character does not follow that of the phonetic radical, it is considered as irregular and can only be correctly read through the lexical-semantic route. The aim of the current investigation was to examine reading aloud in normal adults. We hypothesized that the regularity effect, previously described for alphabetical scripts and acquired dyslexic patients of Chinese (Weekes & Chen, 1999; Wu, Liu, Sun, Chromik, & Zhang, 2014, would also be present in normal adult Chinese readers. Method Participants. Thirty (50% female native Hong Kong Cantonese speakers with a mean age of 19.6 years and a mean education of 12.9 years. Stimuli. Sixty regular-, 60 irregular-, and 60 pseudo-characters (with at least 75% of name agreement in Chinese were matched by initial phoneme, number of strokes and family size. Additionally, regular- and irregular-characters were matched by frequency (low and consistency. Procedure. Each participant was asked to read aloud the stimuli presented on a laptop using the DMDX software. The order of stimuli presentation was randomized. Data analysis. ANOVAs were carried out by participants and items with RTs and errors as dependent variables and type of stimuli (regular-, irregular- and pseudo-character as repeated measures (F1 or between subject�

Regularity effect in prospective memory during aging

Directory of Open Access Journals (Sweden)

Geoffrey Blondelle

2016-10-01

Full Text Available Background: Regularity effect can affect performance in prospective memory (PM, but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults. Objective and design: Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30, 16 intermediate adults (40–55, and 25 older adults (65–80. The task, adapted from the Virtual Week, was designed to manipulate the regularity of the various activities of daily life that were to be recalled (regular repeated activities vs. irregular non-repeated activities. We examine the role of several cognitive functions including certain dimensions of executive functions (planning, inhibition, shifting, and binding, short-term memory, and retrospective episodic memory to identify those involved in PM, according to regularity and age. Results: A mixed-design ANOVA showed a main effect of task regularity and an interaction between age and regularity: an age-related difference in PM performances was found for irregular activities (older < young, but not for regular activities. All participants recalled more regular activities than irregular ones with no age effect. It appeared that recalling of regular activities only involved planning for both intermediate and older adults, while recalling of irregular ones were linked to planning, inhibition, short-term memory, binding, and retrospective episodic memory. Conclusion: Taken together, our data suggest that planning capacities seem to play a major role in remembering to perform intended actions with advancing age. Furthermore, the age-PM-paradox may be attenuated when the experimental design is adapted by implementing a familiar context through the use of activities of daily living. The clinical

J-regular rings with injectivities

OpenAIRE

Shen, Liang

2010-01-01

A ring $R$ is called a J-regular ring if R/J(R) is von Neumann regular, where J(R) is the Jacobson radical of R. It is proved that if R is J-regular, then (i) R is right n-injective if and only if every homomorphism from an $n$-generated small right ideal of $R$ to $R_{R}$ can be extended to one from $R_{R}$ to $R_{R}$; (ii) R is right FP-injective if and only if R is right (J, R)-FP-injective. Some known results are improved.

Chiral Thirring–Wess model with Faddeevian regularization

International Nuclear Information System (INIS)

Rahaman, Anisur

2015-01-01

Replacing vector type of interaction of the Thirring–Wess model by the chiral type a new model is presented which is termed here as chiral Thirring–Wess model. Ambiguity parameters of regularization are so chosen that the model falls into the Faddeevian class. The resulting Faddeevian class of model in general does not possess Lorentz invariance. However we can exploit the arbitrariness admissible in the ambiguity parameters to relate the quantum mechanically generated ambiguity parameters with the classical parameter involved in the masslike term of the gauge field which helps to maintain physical Lorentz invariance instead of the absence of manifestly Lorentz covariance of the model. The phase space structure and the theoretical spectrum of this class of model have been determined through Dirac’s method of quantization of constraint system

Discriminative Elastic-Net Regularized Linear Regression.

Science.gov (United States)

Zhang, Zheng; Lai, Zhihui; Xu, Yong; Shao, Ling; Wu, Jian; Xie, Guo-Sen

2017-03-01

In this paper, we aim at learning compact and discriminative linear regression models. Linear regression has been widely used in different problems. However, most of the existing linear regression methods exploit the conventional zero-one matrix as the regression targets, which greatly narrows the flexibility of the regression model. Another major limitation of these methods is that the learned projection matrix fails to precisely project the image features to the target space due to their weak discriminative capability. To this end, we present an elastic-net regularized linear regression (ENLR) framework, and develop two robust linear regression models which possess the following special characteristics. First, our methods exploit two particular strategies to enlarge the margins of different classes by relaxing the strict binary targets into a more feasible variable matrix. Second, a robust elastic-net regularization of singular values is introduced to enhance the compactness and effectiveness of the learned projection matrix. Third, the resulting optimization problem of ENLR has a closed-form solution in each iteration, which can be solved efficiently. Finally, rather than directly exploiting the projection matrix for recognition, our methods employ the transformed features as the new discriminate representations to make final image classification. Compared with the traditional linear regression model and some of its variants, our method is much more accurate in image classification. Extensive experiments conducted on publicly available data sets well demonstrate that the proposed framework can outperform the state-of-the-art methods. The MATLAB codes of our methods can be available at http://www.yongxu.org/lunwen.html.

Iterative Regularization with Minimum-Residual Methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2007-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

Iterative regularization with minimum-residual methods

DEFF Research Database (Denmark)

Jensen, Toke Koldborg; Hansen, Per Christian

2006-01-01

subspaces. We provide a combination of theory and numerical examples, and our analysis confirms the experience that MINRES and MR-II can work as general regularization methods. We also demonstrate theoretically and experimentally that the same is not true, in general, for GMRES and RRGMRES - their success......We study the regularization properties of iterative minimum-residual methods applied to discrete ill-posed problems. In these methods, the projection onto the underlying Krylov subspace acts as a regularizer, and the emphasis of this work is on the role played by the basis vectors of these Krylov...... as regularization methods is highly problem dependent....

MagPy: A Python toolbox for controlling Magstim transcranial magnetic stimulators.

Science.gov (United States)

McNair, Nicolas A

2017-01-30

To date, transcranial magnetic stimulation (TMS) studies manipulating stimulation parameters have largely used blocked paradigms. However, altering these parameters on a trial-by-trial basis in Magstim stimulators is complicated by the need to send regular (1Hz) commands to the stimulator. Additionally, effecting such control interferes with the ability to send TMS pulses or simultaneously present stimuli with high-temporal precision. This manuscript presents the MagPy toolbox, a Python software package that provides full control over Magstim stimulators via the serial port. It is able to maintain this control with no impact on concurrent processing, such as stimulus delivery. In addition, a specially-designed "QuickFire" serial cable is specified that allows MagPy to trigger TMS pulses with very low-latency. In a series of experimental simulations, MagPy was able to maintain uninterrupted remote control over the connected Magstim stimulator across all testing sessions. In addition, having MagPy enabled had no effect on stimulus timing - all stimuli were presented for precisely the duration specified. Finally, using the QuickFire cable, MagPy was able to elicit TMS pulses with sub-millisecond latencies. The MagPy toolbox allows for experiments that require manipulating stimulation parameters from trial to trial. Furthermore, it can achieve this in contexts that require tight control over timing, such as those seeking to combine TMS with fMRI or EEG. Together, the MagPy toolbox and QuickFire serial cable provide an effective means for controlling Magstim stimulators during experiments while ensuring high-precision timing. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Neural dynamics during repetitive visual stimulation

Science.gov (United States)

Tsoneva, Tsvetomira; Garcia-Molina, Gary; Desain, Peter

2015-12-01

Objective. Steady-state visual evoked potentials (SSVEPs), the brain responses to repetitive visual stimulation (RVS), are widely utilized in neuroscience. Their high signal-to-noise ratio and ability to entrain oscillatory brain activity are beneficial for their applications in brain-computer interfaces, investigation of neural processes underlying brain rhythmic activity (steady-state topography) and probing the causal role of brain rhythms in cognition and emotion. This paper aims at analyzing the space and time EEG dynamics in response to RVS at the frequency of stimulation and ongoing rhythms in the delta, theta, alpha, beta, and gamma bands. Approach.We used electroencephalography (EEG) to study the oscillatory brain dynamics during RVS at 10 frequencies in the gamma band (40-60 Hz). We collected an extensive EEG data set from 32 participants and analyzed the RVS evoked and induced responses in the time-frequency domain. Main results. Stable SSVEP over parieto-occipital sites was observed at each of the fundamental frequencies and their harmonics and sub-harmonics. Both the strength and the spatial propagation of the SSVEP response seem sensitive to stimulus frequency. The SSVEP was more localized around the parieto-occipital sites for higher frequencies (>54 Hz) and spread to fronto-central locations for lower frequencies. We observed a strong negative correlation between stimulation frequency and relative power change at that frequency, the first harmonic and the sub-harmonic components over occipital sites. Interestingly, over parietal sites for sub-harmonics a positive correlation of relative power change and stimulation frequency was found. A number of distinct patterns in delta (1-4 Hz), theta (4-8 Hz), alpha (8-12 Hz) and beta (15-30 Hz) bands were also observed. The transient response, from 0 to about 300 ms after stimulation onset, was accompanied by increase in delta and theta power over fronto-central and occipital sites, which returned to baseline

Quantum magnification of classical sub-Planck phase space features

International Nuclear Information System (INIS)

Hensinger, W.K.; Heckenberg, N.; Rubinsztein-Dunlop, H.; Delande, D.

2002-01-01

Full text: To understand the relationship between quantum mechanics and classical physics a crucial question to be answered is how distinct classical dynamical phase space features translate into the quantum picture. This problem becomes even more interesting if these phase space features occupy a much smaller volume than ℎ in a phase space spanned by two non-commuting variables such as position and momentum. The question whether phase space structures in quantum mechanics associated with sub-Planck scales have physical signatures has recently evoked a lot of discussion. Here we will show that sub-Planck classical dynamical phase space structures, for example regions of regular motion, can give rise to states whose phase space representation is of size ℎ or larger. This is illustrated using period-1 regions of regular motion (modes of oscillatory motion of a particle in a modulated well) whose volume is distinctly smaller than Planck's constant. They are magnified in the quantum picture and appear as states whose phase space representation is of size h or larger. Cold atoms provide an ideal test bed to probe such fundamental aspects of quantum and classical dynamics. In the experiment a Bose-Einstein condensate is loaded into a far detuned optical lattice. The lattice depth is modulated resulting in the emergence of regions of regular motion surrounded by chaotic motion in the phase space spanned by position and momentum of the atoms along the standing wave. Sub-Planck scaled phase space features in the classical phase space are magnified and appear as distinct broad peaks in the atomic momentum distribution. The corresponding quantum analysis shows states of size Ti which can be associated with much smaller classical dynamical phase space features. This effect may considered as the dynamical equivalent of the Goldstone and Jaffe theorem which predicts the existence of at least one bound state at a bend in a two or three dimensional spatial potential

Higher derivative regularization and chiral anomaly

International Nuclear Information System (INIS)

Nagahama, Yoshinori.

1985-02-01

A higher derivative regularization which automatically leads to the consistent chiral anomaly is analyzed in detail. It explicitly breaks all the local gauge symmetry but preserves global chiral symmetry and leads to the chirally symmetric consistent anomaly. This regularization thus clarifies the physics content contained in the consistent anomaly. We also briefly comment on the application of this higher derivative regularization to massless QED. (author)

Modeling extracellular electrical stimulation: I. Derivation and interpretation of neurite equations.

Science.gov (United States)

Meffin, Hamish; Tahayori, Bahman; Grayden, David B; Burkitt, Anthony N

2012-12-01

Neuroprosthetic devices, such as cochlear and retinal implants, work by directly stimulating neurons with extracellular electrodes. This is commonly modeled using the cable equation with an applied extracellular voltage. In this paper a framework for modeling extracellular electrical stimulation is presented. To this end, a cylindrical neurite with confined extracellular space in the subthreshold regime is modeled in three-dimensional space. Through cylindrical harmonic expansion of Laplace's equation, we derive the spatio-temporal equations governing different modes of stimulation, referred to as longitudinal and transverse modes, under types of boundary conditions. The longitudinal mode is described by the well-known cable equation, however, the transverse modes are described by a novel ordinary differential equation. For the longitudinal mode, we find that different electrotonic length constants apply under the two different boundary conditions. Equations connecting current density to voltage boundary conditions are derived that are used to calculate the trans-impedance of the neurite-plus-thin-extracellular-sheath. A detailed explanation on depolarization mechanisms and the dominant current pathway under different modes of stimulation is provided. The analytic results derived here enable the estimation of a neurite's membrane potential under extracellular stimulation, hence bypassing the heavy computational cost of using numerical methods.

Generalisation for regular black holes on general relativity to f(R) gravity

Energy Technology Data Exchange (ETDEWEB)

Rodrigues, Manuel E. [Universidade Federal do Para Campus Universitario de Abaetetuba, Faculdade de Ciencias Exatas e Tecnologia, Abaetetuba, Para (Brazil); Universidade Federal do Para, Faculdade de Fisica, PPGF, Belem, Para (Brazil); Fabris, Julio C. [Universidade Federal do Espirito Santo, Vitoria, ES (Brazil); National Research Nuclear University MEPhI, Moscow (Russian Federation); Junior, Ednaldo L.B. [Universidade Federal do Para, Faculdade de Fisica, PPGF, Belem, Para (Brazil); Universidade Federal do Para, Campus Universitario de Tucurui, Faculdade de Engenharia da Computacao, Tucurui, Para (Brazil); Marques, Glauber T. [Universidade Federal Rural da Amazonia ICIBE - LASIC, Belem, PA (Brazil)

2016-05-15

IIn this paper, we determine regular black hole solutions using a very general f(R) theory, coupled to a nonlinear electromagnetic field given by a Lagrangian L{sub NED}. The functions f(R) and L{sub NED} are in principle left unspecified. Instead, the model is constructed through a choice of the mass function M(r) presented in the metric coefficients. Solutions which have a regular behaviour of the geometric invariants are found. These solutions have two horizons, the event horizon and the Cauchy horizon. All energy conditions are satisfied in the whole space-time, except the strong energy condition (SEC), which is violated near the Cauchy horizon.We present also a new theorem related to the energy conditions in f(R) gravity, re-obtaining the well-known conditions in the context of general relativity when the geometry of the solution is the same. (orig.)

Ito's formula in UMD Banach spaces and regularity of solution of the Zakai equation

NARCIS (Netherlands)

Brzezniak, Z.; Van Neerven, J.M.A.M.; Veraar, M.C.; Weis, L.

2008-01-01

Using the theory of stochastic integration for processes with values in a UMD Banach space developed recently by the authors, an Itô formula is proved which is applied to prove the existence of strong solutions for a class of stochastic evolution equations in UMD Banach spaces. The abstract results

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

75 FR 53966 - Regular Meeting

Science.gov (United States)

2010-09-02

... FARM CREDIT SYSTEM INSURANCE CORPORATION Regular Meeting AGENCY: Farm Credit System Insurance Corporation Board. SUMMARY: Notice is hereby given of the regular meeting of the Farm Credit System Insurance Corporation Board (Board). DATE AND TIME: The meeting of the Board will be held at the offices of the Farm...

Work and family life of childrearing women workers in Japan: comparison of non-regular employees with short working hours, non-regular employees with long working hours, and regular employees.

Science.gov (United States)

Seto, Masako; Morimoto, Kanehisa; Maruyama, Soichiro

2006-05-01

This study assessed the working and family life characteristics, and the degree of domestic and work strain of female workers with different employment statuses and weekly working hours who are rearing children. Participants were the mothers of preschoolers in a large Japanese city. We classified the women into three groups according to the hours they worked and their employment conditions. The three groups were: non-regular employees working less than 30 h a week (n=136); non-regular employees working 30 h or more per week (n=141); and regular employees working 30 h or more a week (n=184). We compared among the groups the subjective values of work, financial difficulties, childcare and housework burdens, psychological effects, and strains such as work and family strain, work-family conflict, and work dissatisfaction. Regular employees were more likely to report job pressures and inflexible work schedules and to experience more strain related to work and family than non-regular employees. Non-regular employees were more likely to be facing financial difficulties. In particular, non-regular employees working longer hours tended to encounter socioeconomic difficulties and often lacked support from family and friends. Female workers with children may have different social backgrounds and different stressors according to their working hours and work status.

Dose domain regularization of MLC leaf patterns for highly complex IMRT plans

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Dan; Yu, Victoria Y.; Ruan, Dan; Cao, Minsong; Low, Daniel A.; Sheng, Ke, E-mail: ksheng@mednet.ucla.edu [Department of Radiation Oncology, University of California Los Angeles, Los Angeles, California 90095 (United States); O’Connor, Daniel [Department of Mathematics, University of California Los Angeles, Los Angeles, California 90095 (United States)

2015-04-15

Purpose: The advent of automated beam orientation and fluence optimization enables more complex intensity modulated radiation therapy (IMRT) planning using an increasing number of fields to exploit the expanded solution space. This has created a challenge in converting complex fluences to robust multileaf collimator (MLC) segments for delivery. A novel method to regularize the fluence map and simplify MLC segments is introduced to maximize delivery efficiency, accuracy, and plan quality. Methods: In this work, we implemented a novel approach to regularize optimized fluences in the dose domain. The treatment planning problem was formulated in an optimization framework to minimize the segmentation-induced dose distribution degradation subject to a total variation regularization to encourage piecewise smoothness in fluence maps. The optimization problem was solved using a first-order primal-dual algorithm known as the Chambolle-Pock algorithm. Plans for 2 GBM, 2 head and neck, and 2 lung patients were created using 20 automatically selected and optimized noncoplanar beams. The fluence was first regularized using Chambolle-Pock and then stratified into equal steps, and the MLC segments were calculated using a previously described level reducing method. Isolated apertures with sizes smaller than preset thresholds of 1–3 bixels, which are square units of an IMRT fluence map from MLC discretization, were removed from the MLC segments. Performance of the dose domain regularized (DDR) fluences was compared to direct stratification and direct MLC segmentation (DMS) of the fluences using level reduction without dose domain fluence regularization. Results: For all six cases, the DDR method increased the average planning target volume dose homogeneity (D95/D5) from 0.814 to 0.878 while maintaining equivalent dose to organs at risk (OARs). Regularized fluences were more robust to MLC sequencing, particularly to the stratification and small aperture removal. The maximum and

Stimulating the demand for dental care: An application of Ajzen and Fishbein's theory of reasoned action.

NARCIS (Netherlands)

Hoogstraten, J.; de Haan, W.; ter Horst, G.

1985-01-01

Applied I. Ajzen and M. Fishbein's (1980) attitude-behavior model to the problem of stimulating the demand for dental care with 329 members (aged 21-50 yrs) of health insurance companies who had not received regular dental treatment and/or certificate of dental fitness for at least 2 1/2 yrs.

Incremental projection approach of regularization for inverse problems

Energy Technology Data Exchange (ETDEWEB)

Souopgui, Innocent, E-mail: innocent.souopgui@usm.edu [The University of Southern Mississippi, Department of Marine Science (United States); Ngodock, Hans E., E-mail: hans.ngodock@nrlssc.navy.mil [Naval Research Laboratory (United States); Vidard, Arthur, E-mail: arthur.vidard@imag.fr; Le Dimet, François-Xavier, E-mail: ledimet@imag.fr [Laboratoire Jean Kuntzmann (France)

2016-10-15

This paper presents an alternative approach to the regularized least squares solution of ill-posed inverse problems. Instead of solving a minimization problem with an objective function composed of a data term and a regularization term, the regularization information is used to define a projection onto a convex subspace of regularized candidate solutions. The objective function is modified to include the projection of each iterate in the place of the regularization. Numerical experiments based on the problem of motion estimation for geophysical fluid images, show the improvement of the proposed method compared with regularization methods. For the presented test case, the incremental projection method uses 7 times less computation time than the regularization method, to reach the same error target. Moreover, at convergence, the incremental projection is two order of magnitude more accurate than the regularization method.

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

Regularization by Functions of Bounded Variation and Applications to Image Enhancement

International Nuclear Information System (INIS)

Casas, E.; Kunisch, K.; Pola, C.

1999-01-01

Optimization problems regularized by bounded variation seminorms are analyzed. The optimality system is obtained and finite-dimensional approximations of bounded variation function spaces as well as of the optimization problems are studied. It is demonstrated that the choice of the vector norm in the definition of the bounded variation seminorm is of special importance for approximating subspaces consisting of piecewise constant functions. Algorithms based on a primal-dual framework that exploit the structure of these nondifferentiable optimization problems are proposed. Numerical examples are given for denoising of blocky images with very high noise

Adaptive regularization

DEFF Research Database (Denmark)

Hansen, Lars Kai; Rasmussen, Carl Edward; Svarer, C.

1994-01-01

Regularization, e.g., in the form of weight decay, is important for training and optimization of neural network architectures. In this work the authors provide a tool based on asymptotic sampling theory, for iterative estimation of weight decay parameters. The basic idea is to do a gradient desce...

Space physiology and medicine, 2nd ed

International Nuclear Information System (INIS)

Nicogossian, A.E.; Huntoon, C.L.; Pool, S.L.; Johnson, P.C.

1988-01-01

The contents of this book are: Physiological Adaptation to Space Flight: Overall Adaptation to Space Flight and Implications; The Neurovestibular System; Performance; The Cardiopulmonary System; Nutrition; Bone and Mineral Metabolism; Hematology, Immunology, Endocrinology, and Biochemistry; Microgravity: Stimulations and Analogs; Health Maintenance of Space Crewmemebers: Medical Evaluation for Astronaut Selection and Longitudinal Studies; Biomedical Training of Space Crews; Ground-Based Medical Programs; Countermeasures to Space Deconditioning; Medical Problems of Space Flight: Toxic Hazards in Space Operations; Radiation Exposure Issues and Medical Care and Health Maintenance in Flight

Regularizing portfolio optimization

International Nuclear Information System (INIS)

Still, Susanne; Kondor, Imre

2010-01-01

The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.

Regularizing portfolio optimization

Science.gov (United States)

Still, Susanne; Kondor, Imre

2010-07-01

The optimization of large portfolios displays an inherent instability due to estimation error. This poses a fundamental problem, because solutions that are not stable under sample fluctuations may look optimal for a given sample, but are, in effect, very far from optimal with respect to the average risk. In this paper, we approach the problem from the point of view of statistical learning theory. The occurrence of the instability is intimately related to over-fitting, which can be avoided using known regularization methods. We show how regularized portfolio optimization with the expected shortfall as a risk measure is related to support vector regression. The budget constraint dictates a modification. We present the resulting optimization problem and discuss the solution. The L2 norm of the weight vector is used as a regularizer, which corresponds to a diversification 'pressure'. This means that diversification, besides counteracting downward fluctuations in some assets by upward fluctuations in others, is also crucial because it improves the stability of the solution. The approach we provide here allows for the simultaneous treatment of optimization and diversification in one framework that enables the investor to trade off between the two, depending on the size of the available dataset.

Space Mathematics, A Resource for Teachers Outlining Supplementary Space-Related Problems in Mathematics.

Science.gov (United States)

Reynolds, Thomas D.; And Others

This compilation of 138 problems illustrating applications of high school mathematics to various aspects of space science is intended as a resource from which the teacher may select questions to supplement his regular course. None of the problems require a knowledge of calculus or physics, and solutions are presented along with the problem…

Tessellating the Sphere with Regular Polygons

Science.gov (United States)

Soto-Johnson, Hortensia; Bechthold, Dawn

2004-01-01

Tessellations in the Euclidean plane and regular polygons that tessellate the sphere are reviewed. The regular polygons that can possibly tesellate the sphere are spherical triangles, squares and pentagons.

A multi-channel stimulator and electrode array providing a rotating current whirlpool for electrical stimulation of wounds.

Science.gov (United States)

Petrofsky, J; Suh, H J; Fish, A; Hernandez, V; Abdo, A; Collins, K; Mendoza, E; Yang, T-N

2008-01-01

When electrical stimulation is used on wounds, the electrical current has difficulty penetrating areas where there is necrotic tissue. Further, for an irregularly shaped wound, current distribution is poor in some areas of the wound since conventional two-electrode delivery systems provide the greatest current in a line directly between the electrodes. A new stimulator and electrode system is described which uses three electrodes spaced around a wound to disperse current more evenly. The stimulator senses tissue impedance and then redirects current by altering its Thevenin's output impedance for each electrode; each of the three electrodes becomes the active one in sequence while the remaining are the sink electrodes. Eight subjects were examined to test the stimulator. Electrical stimulation was applied to the skin above the quadriceps muscle at currents of 15 mA in six subjects without wounds and in two subjects with wounds. The relationship between electrode position and current dispersion on the skin was examined with a two-electrode vs. a three-electrode system to set stimulation parameters for the computer. The results showed that the three-electrode system could (1) detect areas of the skin with high impedance; (2) compensate by altering the Thevenin's output impedance at each of the three electrodes to shift current to high impedance areas; (3) provide uniform current across the skin as assessed by skin current and blood flow measurements with a laser Doppler flow imager.

Causal Measurement Models: Can Criticism Stimulate Clarification?

Science.gov (United States)

Markus, Keith A.

2016-01-01

In their 2016 work, Aguirre-Urreta et al. provided a contribution to the literature on causal measurement models that enhances clarity and stimulates further thinking. Aguirre-Urreta et al. presented a form of statistical identity involving mapping onto the portion of the parameter space involving the nomological net, relationships between the…

Accretion onto some well-known regular black holes

International Nuclear Information System (INIS)

Jawad, Abdul; Shahzad, M.U.

2016-01-01

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes. (orig.)

Accretion onto some well-known regular black holes

Energy Technology Data Exchange (ETDEWEB)

Jawad, Abdul; Shahzad, M.U. [COMSATS Institute of Information Technology, Department of Mathematics, Lahore (Pakistan)

2016-03-15

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes. (orig.)

Accretion onto some well-known regular black holes

Science.gov (United States)

Jawad, Abdul; Shahzad, M. Umair

2016-03-01

In this work, we discuss the accretion onto static spherically symmetric regular black holes for specific choices of the equation of state parameter. The underlying regular black holes are charged regular black holes using the Fermi-Dirac distribution, logistic distribution, nonlinear electrodynamics, respectively, and Kehagias-Sftesos asymptotically flat regular black holes. We obtain the critical radius, critical speed, and squared sound speed during the accretion process near the regular black holes. We also study the behavior of radial velocity, energy density, and the rate of change of the mass for each of the regular black holes.

The patterning of retinal horizontal cells: normalizing the regularity index enhances the detection of genomic linkage

Directory of Open Access Journals (Sweden)

Patrick W. Keeley

2014-10-01

Full Text Available Retinal neurons are often arranged as non-random distributions called mosaics, as their somata minimize proximity to neighboring cells of the same type. The horizontal cells serve as an example of such a mosaic, but little is known about the developmental mechanisms that underlie their patterning. To identify genes involved in this process, we have used three different spatial statistics to assess the patterning of the horizontal cell mosaic across a panel of genetically distinct recombinant inbred strains. To avoid the confounding effect cell density, which varies two-fold across these different strains, we computed the real/random regularity ratio, expressing the regularity of a mosaic relative to a randomly distributed simulation of similarly sized cells. To test whether this latter statistic better reflects the variation in biological processes that contribute to horizontal cell spacing, we subsequently compared the genetic linkage for each of these two traits, the regularity index and the real/random regularity ratio, each computed from the distribution of nearest neighbor (NN distances and from the Voronoi domain (VD areas. Finally, we compared each of these analyses with another index of patterning, the packing factor. Variation in the regularity indexes, as well as their real/random regularity ratios, and the packing factor, mapped quantitative trait loci (QTL to the distal ends of Chromosomes 1 and 14. For the NN and VD analyses, we found that the degree of linkage was greater when using the real/random regularity ratio rather than the respective regularity index. Using informatic resources, we narrow the list of prospective genes positioned at these two intervals to a small collection of six genes that warrant further investigation to determine their potential role in shaping the patterning of the horizontal cell mosaic.

A variational regularization of Abel transform for GPS radio occultation

Directory of Open Access Journals (Sweden)

T.-K. Wee

2018-04-01

Full Text Available In the Global Positioning System (GPS radio occultation (RO technique, the inverse Abel transform of measured bending angle (Abel inversion, hereafter AI is the standard means of deriving the refractivity. While concise and straightforward to apply, the AI accumulates and propagates the measurement error downward. The measurement error propagation is detrimental to the refractivity in lower altitudes. In particular, it builds up negative refractivity bias in the tropical lower troposphere. An alternative to AI is the numerical inversion of the forward Abel transform, which does not incur the integration of error-possessing measurement and thus precludes the error propagation. The variational regularization (VR proposed in this study approximates the inversion of the forward Abel transform by an optimization problem in which the regularized solution describes the measurement as closely as possible within the measurement's considered accuracy. The optimization problem is then solved iteratively by means of the adjoint technique. VR is formulated with error covariance matrices, which permit a rigorous incorporation of prior information on measurement error characteristics and the solution's desired behavior into the regularization. VR holds the control variable in the measurement space to take advantage of the posterior height determination and to negate the measurement error due to the mismodeling of the refractional radius. The advantages of having the solution and the measurement in the same space are elaborated using a purposely corrupted synthetic sounding with a known true solution. The competency of VR relative to AI is validated with a large number of actual RO soundings. The comparison to nearby radiosonde observations shows that VR attains considerably smaller random and systematic errors compared to AI. A noteworthy finding is that in the heights and areas that the measurement bias is supposedly small, VR follows AI very closely in the

A variational regularization of Abel transform for GPS radio occultation

Science.gov (United States)

Wee, Tae-Kwon

2018-04-01

In the Global Positioning System (GPS) radio occultation (RO) technique, the inverse Abel transform of measured bending angle (Abel inversion, hereafter AI) is the standard means of deriving the refractivity. While concise and straightforward to apply, the AI accumulates and propagates the measurement error downward. The measurement error propagation is detrimental to the refractivity in lower altitudes. In particular, it builds up negative refractivity bias in the tropical lower troposphere. An alternative to AI is the numerical inversion of the forward Abel transform, which does not incur the integration of error-possessing measurement and thus precludes the error propagation. The variational regularization (VR) proposed in this study approximates the inversion of the forward Abel transform by an optimization problem in which the regularized solution describes the measurement as closely as possible within the measurement's considered accuracy. The optimization problem is then solved iteratively by means of the adjoint technique. VR is formulated with error covariance matrices, which permit a rigorous incorporation of prior information on measurement error characteristics and the solution's desired behavior into the regularization. VR holds the control variable in the measurement space to take advantage of the posterior height determination and to negate the measurement error due to the mismodeling of the refractional radius. The advantages of having the solution and the measurement in the same space are elaborated using a purposely corrupted synthetic sounding with a known true solution. The competency of VR relative to AI is validated with a large number of actual RO soundings. The comparison to nearby radiosonde observations shows that VR attains considerably smaller random and systematic errors compared to AI. A noteworthy finding is that in the heights and areas that the measurement bias is supposedly small, VR follows AI very closely in the mean refractivity

Spinal cord stimulation for FBSS and CRPS: A review of 80 cases with on-table trial of stimulation.

Science.gov (United States)

Gopal, Hari; Fitzgerald, Joseph; McCrory, Connail

2016-01-01

Spinal cord stimulation (SCS) is used for the treatment of chronic neuropathic pain, a notoriously difficult condition to treat. Failed Back Surgery Syndrome (FBSS) and Complex Regional Pain syndrome (CRPS) remain the strongest indications. Funding remains a difficult issue and the use of trial of stimulation is the traditional method of ensuring best outcomes from implantation. A retrospective and consecutive review of 80 cases of spinal cord stimulation for patients with a diagnosis of FBSS and CRPS having undergone prior comprehensive medical management and interventional treatment with no sustained benefit. Trial of stimulation was performed on-table and if acceptable coverage was achieved, the case proceeded to full implantation. The mean patient age was 50.08 years (range 28-80 years). At 12 months follow-up, thirty two patients (40%) no longer required analgesic medication. Thirty patients (37.5%) reported their pain was manageable with first line analgesics. Fourteen (17.5%) reported their pain was manageable first line analgesic and occasional tramadol or codeine. Four (5%) reported that their pain was manageable with NSAID's, paracetamol, amitriptyline, and regular codeine or tramadol. Seventeen out of eighty patients (21.25%) were unemployed before SCS implant, and at 12 months follow up eight of these patients (47.05%) had returned to work. There was no infective complications or explants. Two patients (2.53%) required one lead revision, which was successful. SCS is the most effective treatment for FBSS and CRPS, which is proven resistant to medical management. On-table trial and implantation is easy to perform with good success rate and low morbidity and if successful will reduce complication rates, especially infection.

A regularized approach for geodesic-based semisupervised multimanifold learning.

Science.gov (United States)

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

Temporal regularity of the environment drives time perception

OpenAIRE

van Rijn, H; Rhodes, D; Di Luca, M

2016-01-01

It’s reasonable to assume that a regularly paced sequence should be perceived as regular, but here we show that perceived regularity depends on the context in which the sequence is embedded. We presented one group of participants with perceptually regularly paced sequences, and another group of participants with mostly irregularly paced sequences (75% irregular, 25% regular). The timing of the final stimulus in each sequence could be var- ied. In one experiment, we asked whether the last stim...

Approximate message passing for nonconvex sparse regularization with stability and asymptotic analysis

Science.gov (United States)

Sakata, Ayaka; Xu, Yingying

2018-03-01

We analyse a linear regression problem with nonconvex regularization called smoothly clipped absolute deviation (SCAD) under an overcomplete Gaussian basis for Gaussian random data. We propose an approximate message passing (AMP) algorithm considering nonconvex regularization, namely SCAD-AMP, and analytically show that the stability condition corresponds to the de Almeida-Thouless condition in spin glass literature. Through asymptotic analysis, we show the correspondence between the density evolution of SCAD-AMP and the replica symmetric (RS) solution. Numerical experiments confirm that for a sufficiently large system size, SCAD-AMP achieves the optimal performance predicted by the replica method. Through replica analysis, a phase transition between replica symmetric and replica symmetry breaking (RSB) region is found in the parameter space of SCAD. The appearance of the RS region for a nonconvex penalty is a significant advantage that indicates the region of smooth landscape of the optimization problem. Furthermore, we analytically show that the statistical representation performance of the SCAD penalty is better than that of \

The uniqueness of the regularization procedure

International Nuclear Information System (INIS)

Brzezowski, S.

1981-01-01

On the grounds of the BPHZ procedure, the criteria of correct regularization in perturbation calculations of QFT are given, together with the prescription for dividing the regularized formulas into the finite and infinite parts. (author)

Strong self-coupling expansion in the lattice-regularized standard SU(2) Higgs model

International Nuclear Information System (INIS)

Decker, K.; Weisz, P.; Montvay, I.

1985-11-01

Expectation values at an arbitrary point of the 3-dimensional coupling parameter space in the lattice-regularized SU(2) Higgs-model with a doublet scalar field are expressed by a series of expectation values at infinite self-coupling (lambda=infinite). Questions of convergence of this 'strong self-coupling expansion' (SSCE) are investigated. The SSCE is a potentially useful tool for the study of the lambda-dependence at any value (zero or non-zero) of the bare gauge coupling. (orig.)

Strong self-coupling expansion in the lattice-regularized standard SU(2) Higgs model

International Nuclear Information System (INIS)

Decker, K.; Weisz, P.

1986-01-01

Expectation values at an arbitrary point of the 3-dimensional coupling parameter space in the lattice-regularized SU(2) Higgs model with a doublet scalar field are expressed by a series of expectation values at infinite self-coupling (lambda=infinite). Questions of convergence of this ''strong self-coupling expansion'' (SSCE) are investigated. The SSCE is a potentially useful tool for the study of the lambda-dependence at any value (zero or non-zero) of the bare gauge coupling. (orig.)

Joint Segmentation and Shape Regularization with a Generalized Forward Backward Algorithm.

Science.gov (United States)

Stefanoiu, Anca; Weinmann, Andreas; Storath, Martin; Navab, Nassir; Baust, Maximilian

2016-05-11

This paper presents a method for the simultaneous segmentation and regularization of a series of shapes from a corresponding sequence of images. Such series arise as time series of 2D images when considering video data, or as stacks of 2D images obtained by slicewise tomographic reconstruction. We first derive a model where the regularization of the shape signal is achieved by a total variation prior on the shape manifold. The method employs a modified Kendall shape space to facilitate explicit computations together with the concept of Sobolev gradients. For the proposed model, we derive an efficient and computationally accessible splitting scheme. Using a generalized forward-backward approach, our algorithm treats the total variation atoms of the splitting via proximal mappings, whereas the data terms are dealt with by gradient descent. The potential of the proposed method is demonstrated on various application examples dealing with 3D data. We explain how to extend the proposed combined approach to shape fields which, for instance, arise in the context of 3D+t imaging modalities, and show an application in this setup as well.

Strategy for implementing research in hydrology to promote space science among school children in Nigeria

Science.gov (United States)

Alabi, Omowumi O.

2015-04-01

This paper describes a proposed activity to introduce school children in Nigeria to research in hydrology through the public outreach coordinated by the United Nations affiliated African Regional Centre for Space Science and Technology Education in English (ARCSSTE-E). Over the years, ARCSSTE-E has established a vibrant relationship with Nigerian schools through periodic zonal and national space educational workshops organized for students and teachers. The enthusiasm displayed by the students, coupled with the brilliant performance in the evaluation tests, indicated that this method of informal education is suitable for stimulating the interest of Nigerian pre-collegiate youths in space science and technology, and also to inspire the young learners and develop their interest in the Sciences, Technology, Engineering and Mathematics (STEM). Because only few representatives from each school can participate in these public outreach programs, it became expedient for the Centre to inaugurate space clubs in schools as a forum for students and teachers to meet regularly to discuss space related issues. Since the first space club was officially launched in 2007, the Centre has inaugurated over 300 space clubs in primary, secondary and tertiary institutions, strategically distributed over the six geopolitical zones of Nigeria. The presentation highlights a space club activity designed to introduce the students to precipitation data collection, with locally fabricated rain gauges. The paper also documents the proposed post-data collection activities in which ARCSSTE-E, acting as the coordinating Centre will collaborate with other national and international organizations to standardize and utilize the rainfall data collected by the students for ground validation of satellite data from the Global Precipitation Measurement. Key words: Public Outreach, Space Club, Human Capacity Development, Hydrologic Research, Global Precipitation Measurement.

Coupling regularizes individual units in noisy populations

International Nuclear Information System (INIS)

Ly Cheng; Ermentrout, G. Bard

2010-01-01

The regularity of a noisy system can modulate in various ways. It is well known that coupling in a population can lower the variability of the entire network; the collective activity is more regular. Here, we show that diffusive (reciprocal) coupling of two simple Ornstein-Uhlenbeck (O-U) processes can regularize the individual, even when it is coupled to a noisier process. In cellular networks, the regularity of individual cells is important when a select few play a significant role. The regularizing effect of coupling surprisingly applies also to general nonlinear noisy oscillators. However, unlike with the O-U process, coupling-induced regularity is robust to different kinds of coupling. With two coupled noisy oscillators, we derive an asymptotic formula assuming weak noise and coupling for the variance of the period (i.e., spike times) that accurately captures this effect. Moreover, we find that reciprocal coupling can regularize the individual period of higher dimensional oscillators such as the Morris-Lecar and Brusselator models, even when coupled to noisier oscillators. Coupling can have a counterintuitive and beneficial effect on noisy systems. These results have implications for the role of connectivity with noisy oscillators and the modulation of variability of individual oscillators.

Learning regularization parameters for general-form Tikhonov

International Nuclear Information System (INIS)

Chung, Julianne; Español, Malena I

2017-01-01

Computing regularization parameters for general-form Tikhonov regularization can be an expensive and difficult task, especially if multiple parameters or many solutions need to be computed in real time. In this work, we assume training data is available and describe an efficient learning approach for computing regularization parameters that can be used for a large set of problems. We consider an empirical Bayes risk minimization framework for finding regularization parameters that minimize average errors for the training data. We first extend methods from Chung et al (2011 SIAM J. Sci. Comput. 33 3132–52) to the general-form Tikhonov problem. Then we develop a learning approach for multi-parameter Tikhonov problems, for the case where all involved matrices are simultaneously diagonalizable. For problems where this is not the case, we describe an approach to compute near-optimal regularization parameters by using operator approximations for the original problem. Finally, we propose a new class of regularizing filters, where solutions correspond to multi-parameter Tikhonov solutions, that requires less data than previously proposed optimal error filters, avoids the generalized SVD, and allows flexibility and novelty in the choice of regularization matrices. Numerical results for 1D and 2D examples using different norms on the errors show the effectiveness of our methods. (paper)

5 CFR 551.421 - Regular working hours.

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Regular working hours. 551.421 Section... Activities § 551.421 Regular working hours. (a) Under the Act there is no requirement that a Federal employee... distinction based on whether the activity is performed by an employee during regular working hours or outside...

Regular extensions of some classes of grammars

NARCIS (Netherlands)

Nijholt, Antinus

Culik and Cohen introduced the class of LR-regular grammars, an extension of the LR(k) grammars. In this report we consider the analogous extension of the LL(k) grammers, called the LL-regular grammars. The relations of this class of grammars to other classes of grammars are shown. Every LL-regular

Differential regularization of a non-relativistic anyon model

International Nuclear Information System (INIS)

Freedman, D.Z.; Rius, N.

1993-07-01

Differential regularization is applied to a field theory of a non-relativistic charged boson field φ with λ(φ * φ) 2 self-interaction and coupling to a statistics-changing 0(1) Chern-Simons gauge field. Renormalized configuration-space amplitudes for all diagrams contributing to the φ * φ * φφ 4-point function, which is the only primitively divergent Green's function, are obtained up to 3-loop order. The renormalization group equations are explicitly checked, and the scheme dependence of the β-function is investigated. If the renormalization scheme is fixed to agree with a previous 1-loop calculation, the 2- and 3-loop contributions to β(λ, e) vanish, and β(λ, ε) itself vanishes when the ''self-dual'' condition relating λ to the gauge coupling e is imposed. (author). 12 refs, 1 fig

Quantum mechanics on Laakso spaces

Science.gov (United States)

Kauffman, Christopher J.; Kesler, Robert M.; Parshall, Amanda G.; Stamey, Evelyn A.; Steinhurst, Benjamin A.

2012-04-01

We first review the spectrum of the Laplacian operator on a general Laakso space before considering modified Hamiltonians for the infinite square well, parabola, and Coulomb potentials. Additionally, we compute the spectrum for the Laplacian and its multiplicities when certain regions of a Laakso space are compressed or stretched and calculate the Casimir force experienced by two uncharged conducting plates by imposing physically relevant boundary conditions and then analytically regularizing the resulting zeta function. Lastly, we derive a general formula for the spectral zeta function and its derivative for Laakso spaces with strict self-similar structure before listing explicit spectral values for some special cases

Near-Regular Structure Discovery Using Linear Programming

KAUST Repository

Huang, Qixing

2014-06-02

Near-regular structures are common in manmade and natural objects. Algorithmic detection of such regularity greatly facilitates our understanding of shape structures, leads to compact encoding of input geometries, and enables efficient generation and manipulation of complex patterns on both acquired and synthesized objects. Such regularity manifests itself both in the repetition of certain geometric elements, as well as in the structured arrangement of the elements. We cast the regularity detection problem as an optimization and efficiently solve it using linear programming techniques. Our optimization has a discrete aspect, that is, the connectivity relationships among the elements, as well as a continuous aspect, namely the locations of the elements of interest. Both these aspects are captured by our near-regular structure extraction framework, which alternates between discrete and continuous optimizations. We demonstrate the effectiveness of our framework on a variety of problems including near-regular structure extraction, structure-preserving pattern manipulation, and markerless correspondence detection. Robustness results with respect to geometric and topological noise are presented on synthesized, real-world, and also benchmark datasets. © 2014 ACM.

Regularized κ-distributions with non-diverging moments

Science.gov (United States)

Scherer, K.; Fichtner, H.; Lazar, M.

2017-12-01

For various plasma applications the so-called (non-relativistic) κ-distribution is widely used to reproduce and interpret the suprathermal particle populations exhibiting a power-law distribution in velocity or energy. Despite its reputation the standard κ-distribution as a concept is still disputable, mainly due to the velocity moments M l which make a macroscopic characterization possible, but whose existence is restricted only to low orders l definition of the κ-distribution itself is conditioned by the existence of the moment of order l = 2 (i.e., kinetic temperature) satisfied only for κ > 3/2 . In order to resolve these critical limitations we introduce the regularized κ-distribution with non-diverging moments. For the evaluation of all velocity moments a general analytical expression is provided enabling a significant step towards a macroscopic (fluid-like) description of space plasmas, and, in general, any system of κ-distributed particles.

Technology transfer from the space exploration initiative

International Nuclear Information System (INIS)

Buden, D.

1991-01-01

Space exploration has demonstrated that it stimulates the national economy by creating new and improved products, increased employment, and provides a stimulus to education. The exploration of the Moon and Mars under the Space Exploration Initiative has the potential of accelerating this stimulates to the economy. It is difficult to identify all of the concrete ways this will be accomplished. However, many areas can be identified. The space exploration building blocks of power, propulsion, spacecraft, robotics, rovers, mining and manufacturing, communications, navigation, habitats, life support and infrastructures are reviewed to identify possible technology areas. For example, better means for working in hazardous areas and handling hazardous waste are potential outcomes of this initiative. Methods to produce higher quality goods and improve America's competitiveness in manufacturing will undoubtedly evolve from the need to produce products that must last many years in the harsh environments of space and planetary surfaces. Some ideas for technology transfer are covered in this paper

Regular Expression Matching and Operational Semantics

Directory of Open Access Journals (Sweden)

Asiri Rathnayake

2011-08-01

Full Text Available Many programming languages and tools, ranging from grep to the Java String library, contain regular expression matchers. Rather than first translating a regular expression into a deterministic finite automaton, such implementations typically match the regular expression on the fly. Thus they can be seen as virtual machines interpreting the regular expression much as if it were a program with some non-deterministic constructs such as the Kleene star. We formalize this implementation technique for regular expression matching using operational semantics. Specifically, we derive a series of abstract machines, moving from the abstract definition of matching to increasingly realistic machines. First a continuation is added to the operational semantics to describe what remains to be matched after the current expression. Next, we represent the expression as a data structure using pointers, which enables redundant searches to be eliminated via testing for pointer equality. From there, we arrive both at Thompson's lockstep construction and a machine that performs some operations in parallel, suitable for implementation on a large number of cores, such as a GPU. We formalize the parallel machine using process algebra and report some preliminary experiments with an implementation on a graphics processor using CUDA.

Tetravalent one-regular graphs of order 4p2

DEFF Research Database (Denmark)

Feng, Yan-Quan; Kutnar, Klavdija; Marusic, Dragan

2014-01-01

A graph is one-regular if its automorphism group acts regularly on the set of its arcs. In this paper tetravalent one-regular graphs of order 4p2, where p is a prime, are classified.......A graph is one-regular if its automorphism group acts regularly on the set of its arcs. In this paper tetravalent one-regular graphs of order 4p2, where p is a prime, are classified....

Regularization and error assignment to unfolded distributions

CERN Document Server

Zech, Gunter

2011-01-01

The commonly used approach to present unfolded data only in graphical formwith the diagonal error depending on the regularization strength is unsatisfac-tory. It does not permit the adjustment of parameters of theories, the exclusionof theories that are admitted by the observed data and does not allow the com-bination of data from different experiments. We propose fixing the regulariza-tion strength by a p-value criterion, indicating the experimental uncertaintiesindependent of the regularization and publishing the unfolded data in additionwithout regularization. These considerations are illustrated with three differentunfolding and smoothing approaches applied to a toy example.

Graph Regularized Meta-path Based Transductive Regression in Heterogeneous Information Network.

Science.gov (United States)

Wan, Mengting; Ouyang, Yunbo; Kaplan, Lance; Han, Jiawei

2015-01-01

A number of real-world networks are heterogeneous information networks, which are composed of different types of nodes and links. Numerical prediction in heterogeneous information networks is a challenging but significant area because network based information for unlabeled objects is usually limited to make precise estimations. In this paper, we consider a graph regularized meta-path based transductive regression model ( Grempt ), which combines the principal philosophies of typical graph-based transductive classification methods and transductive regression models designed for homogeneous networks. The computation of our method is time and space efficient and the precision of our model can be verified by numerical experiments.

On the interplay of basis smoothness and specific range conditions occurring in sparsity regularization

International Nuclear Information System (INIS)

Anzengruber, Stephan W; Hofmann, Bernd; Ramlau, Ronny

2013-01-01

The convergence rates results in ℓ 1 -regularization when the sparsity assumption is narrowly missed, presented by Burger et al (2013 Inverse Problems 29 025013), are based on a crucial condition which requires that all basis elements belong to the range of the adjoint of the forward operator. Partly it was conjectured that such a condition is very restrictive. In this context, we study sparsity-promoting varieties of Tikhonov regularization for linear ill-posed problems with respect to an orthonormal basis in a separable Hilbert space using ℓ 1 and sublinear penalty terms. In particular, we show that the corresponding range condition is always satisfied for all basis elements if the problems are well-posed in a certain weaker topology and the basis elements are chosen appropriately related to an associated Gelfand triple. The Radon transform, Symm’s integral equation and linear integral operators of Volterra type are examples for such behaviour, which allows us to apply convergence rates results for non-sparse solutions, and we further extend these results also to the case of non-convex ℓ q -regularization with 0 < q < 1. (paper)

Higher order total variation regularization for EIT reconstruction.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Zhang, Fan; Mueller-Lisse, Ullrich; Moeller, Knut

2018-01-08

Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.

Application of Turchin's method of statistical regularization

Science.gov (United States)

Zelenyi, Mikhail; Poliakova, Mariia; Nozik, Alexander; Khudyakov, Alexey

2018-04-01

During analysis of experimental data, one usually needs to restore a signal after it has been convoluted with some kind of apparatus function. According to Hadamard's definition this problem is ill-posed and requires regularization to provide sensible results. In this article we describe an implementation of the Turchin's method of statistical regularization based on the Bayesian approach to the regularization strategy.

LumaFluid: a responsive environment to stimulate social interaction in public spaces

NARCIS (Netherlands)

Monaci, G.; Gritti, T.; Van Beers, M.; Vermeulen, A.J.W.A.; Nab, B.; Thomassen, I.; Heijboer, M.; Suijkerbuijk, S.; Walmink, W.; Hendriks, M.

2012-01-01

LumaFluid is an interactive environment that explores new ways to stimulate emotional and social engagement through immersive light effects. A computer vision system detects and tracks persons present inthe LumaFluid square. Using this location information, colored spotlights highlight each person

Regularization based on steering parameterized Gaussian filters and a Bhattacharyya distance functional

Science.gov (United States)

Lopes, Emerson P.

2001-08-01

Template regularization embeds the problem of class separability. In the machine vision perspective, this problem is critical when a textural classification procedure is applied to non-stationary pattern mosaic images. These applications often present low accuracy performance due to disturbance of the classifiers produced by exogenous or endogenous signal regularity perturbations. Natural scene imaging, where the images present certain degree of homogeneity in terms of texture element size or shape (primitives) shows a variety of behaviors, especially varying the preferential spatial directionality. The space-time image pattern characterization is only solved if classification procedures are designed considering the most robust tools within a parallel and hardware perspective. The results to be compared in this paper are obtained using a framework based on multi-resolution, frame and hypothesis approach. Two strategies for the bank of Gabor filters applications are considered: adaptive strategy using the KL transform and fix configuration strategy. The regularization under discussion is accomplished in the pyramid building system instance. The filterings are steering Gaussians controlled by free parameters which are adjusted in accordance with a feedback process driven by hints obtained from sequence of frames interaction functionals pos-processed in the training process and including classification of training set samples as examples. Besides these adjustments there is continuous input data sensitive adaptiveness. The experimental result assessments are focused on two basic issues: Bhattacharyya distance as pattern characterization feature and the combination of KL transform as feature selection and adaptive criterion with the regularization of the pattern Bhattacharyya distance functional (BDF) behavior, using the BDF state separability and symmetry as the main indicators of an optimum framework parameter configuration.

On the regularized fermionic projector of the vacuum

Science.gov (United States)

Finster, Felix

2008-03-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed.

On the regularized fermionic projector of the vacuum

International Nuclear Information System (INIS)

Finster, Felix

2008-01-01

We construct families of fermionic projectors with spherically symmetric regularization, which satisfy the condition of a distributional MP-product. The method is to analyze regularization tails with a power law or logarithmic scaling in composite expressions in the fermionic projector. The resulting regularizations break the Lorentz symmetry and give rise to a multilayer structure of the fermionic projector near the light cone. Furthermore, we construct regularizations which go beyond the distributional MP-product in that they yield additional distributional contributions supported at the origin. The remaining freedom for the regularization parameters and the consequences for the normalization of the fermionic states are discussed

Quantum effects in non-maximally symmetric spaces

International Nuclear Information System (INIS)

Shen, T.C.

1985-01-01

Non-Maximally symmetric spaces provide a more general background to explore the relation between the geometry of the manifold and the quantum fields defined in the manifold than those with maximally symmetric spaces. A static Taub universe is used to study the effect of curvature anisotropy on the spontaneous symmetry breaking of a self-interacting scalar field. The one-loop effective potential on a λphi 4 field with arbitrary coupling xi is computed by zeta function regularization. For massless minimal coupled scalar fields, first order phase transitions can occur. Keeping the shape invariant but decreasing the curvature radius of the universe induces symmetry breaking. If the curvature radius is held constant, increasing deformation can restore the symmetry. Studies on the higher-dimensional Kaluza-Klein theories are also focused on the deformation effect. Using the dimensional regularization, the effective potential of the free scalar fields in M 4 x T/sup N/ and M 4 x (Taub) 3 spaces are obtained. The stability criterions for the static solutions of the self-consistent Einstein equations are derived. Stable solutions of the M 4 x S/sup N/ topology do not exist. With the Taub space as the internal space, the gauge coupling constants of SU(2), and U(1) can be determined geometrically. The weak angle is therefore predicted by geometry in this model

Behavioral analysis of preterm neonates included in a tactile and kinesthetic stimulation program during hospitalization.

Science.gov (United States)

Ferreira, Andréia M; Bergamasco, Niélsy H P

2010-01-01

To evaluate the effect of tactile and kinesthetic stimulation on behavioral and clinical development in preterm neonates while still in the hospital. Thirty-two clinically stable preterm infants weighing kinesthetic stimulation (n=16). Data on the infants' clinical progress were collected from medical charts and behavioral evaluations by means of a series of weekly, eight-minute films recorded from the time of inclusion into the study until hospital discharge. There was a trend towards a shorter duration of hospital stay, increased daily weight gain and a predominance of self-regulated behavior (regular breathing, state of alertness, balanced tonus, a range of postures, coordinated movements, hand-to-face movement control, suction, grip, support) in infants in the SG. With respect to motor control, comparative analysis of postconceptional ages according to age-bracket (I - 31-33 weeks 6/7; II - 34-36 weeks 6/7; and III - 37-39 weeks 6/7) revealed balanced tonus and coordinated voluntary movements in all three periods, a longer time spent in a range of postures (age bracket I) or in flexion (age bracket II) and more regular breathing in age bracket I in the SG. In the hospital, tactile and kinesthetic stimulation was shown to have a positive effect, contributing towards adjustment and self-regulation of behavior in the preterm newborn infant. Article registered in the Australian New Zealand Clinical Trials Registry (ANZCTR) under the number ACTRN12610000133033.

Reversibility and the structure of the local state space

International Nuclear Information System (INIS)

Al-Safi, Sabri W; Richens, Jonathan

2015-01-01

The richness of quantum theory’s reversible dynamics is one of its unique operational characteristics, with recent results suggesting deep links between the theory’s reversible dynamics, its local state space and the degree of non-locality it permits. We explore the delicate interplay between these features, demonstrating that reversibility places strong constraints on both the local and global state space. Firstly, we show that all reversible dynamics are trivial (composed of local transformations and permutations of subsytems) in maximally non-local theories whose local state spaces satisfy a dichotomy criterion; this applies to a range of operational models that have previously been studied, such as d-dimensional ‘hyperballs’ and almost all regular polytope systems. By separately deriving a similar result for odd-sided polygons, we show that classical systems are the only regular polytope state spaces whose maximally non-local composites allow for non-trivial reversible dynamics. Secondly, we show that non-trivial reversible dynamics do exist in maximally non-local theories whose state spaces are reducible into two or more smaller spaces. We conjecture that this is a necessary condition for the existence of such dynamics, but that reversible entanglement generation remains impossible even in this scenario. (paper)

Regularization modeling for large-eddy simulation

NARCIS (Netherlands)

Geurts, Bernardus J.; Holm, D.D.

2003-01-01

A new modeling approach for large-eddy simulation (LES) is obtained by combining a "regularization principle" with an explicit filter and its inversion. This regularization approach allows a systematic derivation of the implied subgrid model, which resolves the closure problem. The central role of

Spatially-Variant Tikhonov Regularization for Double-Difference Waveform Inversion

Energy Technology Data Exchange (ETDEWEB)

Lin, Youzuo [Los Alamos National Laboratory; Huang, Lianjie [Los Alamos National Laboratory; Zhang, Zhigang [Los Alamos National Laboratory

2011-01-01

Double-difference waveform inversion is a potential tool for quantitative monitoring for geologic carbon storage. It jointly inverts time-lapse seismic data for changes in reservoir geophysical properties. Due to the ill-posedness of waveform inversion, it is a great challenge to obtain reservoir changes accurately and efficiently, particularly when using time-lapse seismic reflection data. Regularization techniques can be utilized to address the issue of ill-posedness. The regularization parameter controls the smoothness of inversion results. A constant regularization parameter is normally used in waveform inversion, and an optimal regularization parameter has to be selected. The resulting inversion results are a trade off among regions with different smoothness or noise levels; therefore the images are either over regularized in some regions while under regularized in the others. In this paper, we employ a spatially-variant parameter in the Tikhonov regularization scheme used in double-difference waveform tomography to improve the inversion accuracy and robustness. We compare the results obtained using a spatially-variant parameter with those obtained using a constant regularization parameter and those produced without any regularization. We observe that, utilizing a spatially-variant regularization scheme, the target regions are well reconstructed while the noise is reduced in the other regions. We show that the spatially-variant regularization scheme provides the flexibility to regularize local regions based on the a priori information without increasing computational costs and the computer memory requirement.

From recreational to regular drug use

DEFF Research Database (Denmark)

Järvinen, Margaretha; Ravn, Signe

2011-01-01

This article analyses the process of going from recreational use to regular and problematic use of illegal drugs. We present a model containing six career contingencies relevant for young people’s progress from recreational to regular drug use: the closing of social networks, changes in forms...

A wavelet-based regularized reconstruction algorithm for SENSE parallel MRI with applications to neuroimaging

International Nuclear Information System (INIS)

Chaari, L.; Pesquet, J.Ch.; Chaari, L.; Ciuciu, Ph.; Benazza-Benyahia, A.

2011-01-01

To reduce scanning time and/or improve spatial/temporal resolution in some Magnetic Resonance Imaging (MRI) applications, parallel MRI acquisition techniques with multiple coils acquisition have emerged since the early 1990's as powerful imaging methods that allow a faster acquisition process. In these techniques, the full FOV image has to be reconstructed from the resulting acquired under sampled k-space data. To this end, several reconstruction techniques have been proposed such as the widely-used Sensitivity Encoding (SENSE) method. However, the reconstructed image generally presents artifacts when perturbations occur in both the measured data and the estimated coil sensitivity profiles. In this paper, we aim at achieving accurate image reconstruction under degraded experimental conditions (low magnetic field and high reduction factor), in which neither the SENSE method nor the Tikhonov regularization in the image domain give convincing results. To this end, we present a novel method for SENSE-based reconstruction which proceeds with regularization in the complex wavelet domain by promoting sparsity. The proposed approach relies on a fast algorithm that enables the minimization of regularized non-differentiable criteria including more general penalties than a classical l 1 term. To further enhance the reconstructed image quality, local convex constraints are added to the regularization process. In vivo human brain experiments carried out on Gradient-Echo (GRE) anatomical and Echo Planar Imaging (EPI) functional MRI data at 1.5 T indicate that our algorithm provides reconstructed images with reduced artifacts for high reduction factors. (authors)

A 2-center Comparative Study on Tonic Versus Burst Spinal Cord Stimulation: Amount of Responders and Amount of Pain Suppression

NARCIS (Netherlands)

Ridder, D.M.D.; Lenders, M.W.P.M.; de Vos, Cecilia Cecilia Clementine; Dijkstra-Scholten, C.R.N.; Wolters, R.R.N.; Vancamp, T.P.T.; Van Looy, P.R.N.; Van Havenbergh, T.M.D.; Vanneste, S.

2015-01-01

Introduction: Spinal cord stimulation is a safe and effective procedure applied for medically intractable neuropathic pain and failed back surgery syndrome. Recently, a novel stimulation paradigm was developed, called burst stimulation consisting of intermittent packets of closely spaced

Regular variation on measure chains

Czech Academy of Sciences Publication Activity Database

Řehák, Pavel; Vitovec, J.

2010-01-01

Roč. 72, č. 1 (2010), s. 439-448 ISSN 0362-546X R&D Projects: GA AV ČR KJB100190701 Institutional research plan: CEZ:AV0Z10190503 Keywords : regularly varying function * regularly varying sequence * measure chain * time scale * embedding theorem * representation theorem * second order dynamic equation * asymptotic properties Subject RIV: BA - General Mathematics Impact factor: 1.279, year: 2010 http://www.sciencedirect.com/science/article/pii/S0362546X09008475

New regular black hole solutions

International Nuclear Information System (INIS)

Lemos, Jose P. S.; Zanchin, Vilson T.

2011-01-01

In the present work we consider general relativity coupled to Maxwell's electromagnetism and charged matter. Under the assumption of spherical symmetry, there is a particular class of solutions that correspond to regular charged black holes whose interior region is de Sitter, the exterior region is Reissner-Nordstroem and there is a charged thin-layer in-between the two. The main physical and geometrical properties of such charged regular black holes are analyzed.

On geodesics in low regularity

Science.gov (United States)

Sämann, Clemens; Steinbauer, Roland

2018-02-01

We consider geodesics in both Riemannian and Lorentzian manifolds with metrics of low regularity. We discuss existence of extremal curves for continuous metrics and present several old and new examples that highlight their subtle interrelation with solutions of the geodesic equations. Then we turn to the initial value problem for geodesics for locally Lipschitz continuous metrics and generalize recent results on existence, regularity and uniqueness of solutions in the sense of Filippov.

The paradox of systemic vasodilatation and sympathetic nervous stimulation in space

DEFF Research Database (Denmark)

Norsk, Peter; Christensen, Niels Juel

2009-01-01

decreased by 5mmHg. This is in accordance with observations that very acute weightlessness during parabolic airplane flights and a week of weightlessness in space leads to a decrease in systemic vascular resistance. That the arterial resistance vessels are dilated in space is in contrast to the augmented...

Supersymmetric black holes with lens-space topology.

Science.gov (United States)

Kunduri, Hari K; Lucietti, James

2014-11-21

We present a new supersymmetric, asymptotically flat, black hole solution to five-dimensional supergravity. It is regular on and outside an event horizon of lens-space topology L(2,1). It is the first example of an asymptotically flat black hole with lens-space topology. The solution is characterized by a charge, two angular momenta, and a magnetic flux through a noncontractible disk region ending on the horizon, with one constraint relating these.

Neuromuscular Electrical Stimulation for Mobility Support of Elderly.

Science.gov (United States)

Mayr, Winfried

2015-08-24

The stimulator for neuromuscular electrical stimulation for mobility support of elderly is not very complicated, but for application within "MOBIL" we have some additional demands to fulfill. First we have specific safety issues for this user group. A powerful compliance management system is crucial not only to guide daily application, but for creating hard data for the scientific outcome. We also need to assure easy handling of the stimulator, because the subjects are generally not able to cope with too difficult and complex motor skills. So, we developed five generations of stimulators and optimizing solutions after field tests. We are already planning the sixth generation with wireless control of the stimulation units by the central main handheld control unit. In a prototype, we have implemented a newly available high capacity memory, a breakthrough in "compliance data storage" as they offer the necessary high storage capacity and fast data handling for an affordable prize. The circuit also contains a 3D accelerometer sensor which acts as a further important safety features: if the control unit drops, this event is detected automatically by the sensor and activates an emergency switch-off that disables the stimulation to avoid associated risks. Further, we have implemented a hardware emergence shutdown and other safety measures. Finally, in the last example muscle torque measurements are referenced with compliance data. In the study normalized maximum voluntary contraction (MVC) and maximum stimulation induced contraction (MSC) were assessed in regular check-ups along the training period. With additional consideration of adjusted stimulation intensity for training out of the compliance data records we are able to estimate the induced contraction strength, which turned out to amount in average 11% of MVC. This value may seem on a first sight rather low, and ought to be considered in relation to the results at the end of the training period. Therefore the

Neuromuscular electrical stimulation for mobility support of elderly

Directory of Open Access Journals (Sweden)

Winfried Mayr

2015-10-01

Full Text Available The stimulator for neuromuscular electrical stimulation for mobility support of elderly is not very complicated, but for application within "MOBIL" we have some additional demands to fulfill. First we have specific safety issues for this user group. A powerful compliance management system is crucial not only to guide daily application, but for creating hard data for the scientific outcome. We also need to assure easy handling of the stimulator, because the subjects are generally not able to cope with too difficult and complex motor skills. So, we developed five generations of stimulators and optimizing solutions after field tests. We are already planning the sixth generation with wireless control of the stimulation units by the central main handheld control unit. In a prototype, we have implemented a newly available high capacity memory, a breakthrough in “compliance data storage” as they offer the necessary high storage capacity and fast data handling for an affordable prize. The circuit also contains a 3D accelerometer sensor which acts as a further important safety features: if the control unit drops, this event is detected automatically by the sensor and activates an emergency switch-off that disables the stimulation to avoid associated risks. Further, we have implemented a hardware emergence shutdown and other safety measures. Finally, in the last example muscle torque measurements are referenced with compliance data. In the study normalized maximum voluntary contraction (MVC and maximum stimulation induced contraction (MSC were assessed in regular check-ups along the training period. With additional consideration of adjusted stimulation intensity for training out of the compliance data records we are able to estimate the induced contraction strength, which turned out to amount in average 11% of MVC. This value may seem on a first sight rather low, and ought to be considered in relation to the results at the end of the training period

Laplacian manifold regularization method for fluorescence molecular tomography

Science.gov (United States)

He, Xuelei; Wang, Xiaodong; Yi, Huangjian; Chen, Yanrong; Zhang, Xu; Yu, Jingjing; He, Xiaowei

2017-04-01

Sparse regularization methods have been widely used in fluorescence molecular tomography (FMT) for stable three-dimensional reconstruction. Generally, ℓ1-regularization-based methods allow for utilizing the sparsity nature of the target distribution. However, in addition to sparsity, the spatial structure information should be exploited as well. A joint ℓ1 and Laplacian manifold regularization model is proposed to improve the reconstruction performance, and two algorithms (with and without Barzilai-Borwein strategy) are presented to solve the regularization model. Numerical studies and in vivo experiment demonstrate that the proposed Gradient projection-resolved Laplacian manifold regularization method for the joint model performed better than the comparative algorithm for ℓ1 minimization method in both spatial aggregation and location accuracy.

Learning Sparse Visual Representations with Leaky Capped Norm Regularizers

OpenAIRE

Wangni, Jianqiao; Lin, Dahua

2017-01-01

Sparsity inducing regularization is an important part for learning over-complete visual representations. Despite the popularity of $\\ell_1$ regularization, in this paper, we investigate the usage of non-convex regularizations in this problem. Our contribution consists of three parts. First, we propose the leaky capped norm regularization (LCNR), which allows model weights below a certain threshold to be regularized more strongly as opposed to those above, therefore imposes strong sparsity and...

Adaptive regularization of noisy linear inverse problems

DEFF Research Database (Denmark)

Hansen, Lars Kai; Madsen, Kristoffer Hougaard; Lehn-Schiøler, Tue

2006-01-01

In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyper-parameter, i.e., the optimal strength of regularization, satisfies a simple relation: T......: The expectation of the regularization function, i.e., takes the same value in the posterior and prior distribution. We present three examples: two simulations, and application in fMRI neuroimaging....

Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan; AbdulJabbar, Mustafa Abdulmajeed

2012-01-01

Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

Exclusion of children with intellectual disabilities from regular ...

African Journals Online (AJOL)

Study investigated why teachers exclude children with intellectual disability from the regular classrooms in Nigeria. Participants were, 169 regular teachers randomly selected from Oyo and Ogun states. Questionnaire was used to collect data result revealed that 57.4% regular teachers could not cope with children with ID ...

On infinite regular and chiral maps

OpenAIRE

Arredondo, John A.; Valdez, Camilo Ramírez y Ferrán

2015-01-01

We prove that infinite regular and chiral maps take place on surfaces with at most one end. Moreover, we prove that an infinite regular or chiral map on an orientable surface with genus can only be realized on the Loch Ness monster, that is, the topological surface of infinite genus with one end.

29 CFR 779.18 - Regular rate.

Science.gov (United States)

2010-07-01

... employee under subsection (a) or in excess of the employee's normal working hours or regular working hours... Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR STATEMENTS OF GENERAL POLICY OR... not less than one and one-half times their regular rates of pay. Section 7(e) of the Act defines...

Continuum regularized Yang-Mills theory

International Nuclear Information System (INIS)

Sadun, L.A.

1987-01-01

Using the machinery of stochastic quantization, Z. Bern, M. B. Halpern, C. Taubes and I recently proposed a continuum regularization technique for quantum field theory. This regularization may be implemented by applying a regulator to either the (d + 1)-dimensional Parisi-Wu Langevin equation or, equivalently, to the d-dimensional second order Schwinger-Dyson (SD) equations. This technique is non-perturbative, respects all gauge and Lorentz symmetries, and is consistent with a ghost-free gauge fixing (Zwanziger's). This thesis is a detailed study of this regulator, and of regularized Yang-Mills theory, using both perturbative and non-perturbative techniques. The perturbative analysis comes first. The mechanism of stochastic quantization is reviewed, and a perturbative expansion based on second-order SD equations is developed. A diagrammatic method (SD diagrams) for evaluating terms of this expansion is developed. We apply the continuum regulator to a scalar field theory. Using SD diagrams, we show that all Green functions can be rendered finite to all orders in perturbation theory. Even non-renormalizable theories can be regularized. The continuum regulator is then applied to Yang-Mills theory, in conjunction with Zwanziger's gauge fixing. A perturbative expansion of the regulator is incorporated into the diagrammatic method. It is hoped that the techniques discussed in this thesis will contribute to the construction of a renormalized Yang-Mills theory is 3 and 4 dimensions

Critical spaces for quasilinear parabolic evolution equations and applications

Science.gov (United States)

Prüss, Jan; Simonett, Gieri; Wilke, Mathias

2018-02-01

We present a comprehensive theory of critical spaces for the broad class of quasilinear parabolic evolution equations. The approach is based on maximal Lp-regularity in time-weighted function spaces. It is shown that our notion of critical spaces coincides with the concept of scaling invariant spaces in case that the underlying partial differential equation enjoys a scaling invariance. Applications to the vorticity equations for the Navier-Stokes problem, convection-diffusion equations, the Nernst-Planck-Poisson equations in electro-chemistry, chemotaxis equations, the MHD equations, and some other well-known parabolic equations are given.

Regularity for 3D Navier-Stokes equations in terms of two components of the vorticity

Directory of Open Access Journals (Sweden)

Sadek Gala

2010-10-01

Full Text Available We establish regularity conditions for the 3D Navier-Stokes equation via two components of the vorticity vector. It is known that if a Leray-Hopf weak solution $u$ satisfies $$ ilde{omega}in L^{2/(2-r}(0,T;L^{3/r}(mathbb{R}^3quad hbox{with }0regularity of Leray-Hopf weak solution $u$ under each of the following two (weaker conditions: $$displaylines{ ilde{omega}in L^{2/(2-r}(0,T;dot {mathcal{M}}_{2, 3/r}(mathbb{R}^3quad hbox{for }0space. Since $L^{3/r}(mathbb{R}^3$ is a proper subspace of $dot {mathcal{M}}_{2,3/r}(mathbb{R}^3$, our regularity criterion improves the results in Chae-Choe [5].

Astrocytic mechanisms explaining neural-activity-induced shrinkage of extraneuronal space

DEFF Research Database (Denmark)

Østby, Ivar; Øyehaug, Leiv; Einevoll, Gaute T

2009-01-01

Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance and astr......Neuronal stimulation causes approximately 30% shrinkage of the extracellular space (ECS) between neurons and surrounding astrocytes in grey and white matter under experimental conditions. Despite its possible implications for a proper understanding of basic aspects of potassium clearance...... concentrations observed in connection with neuronal stimulation, the actions of the Na(+)/K(+)/Cl(-) (NKCC1) and the Na(+)/HCO(3) (-) (NBC) cotransporters appear to be critical determinants for achieving observed quantitative levels of ECS shrinkage. Considering the current state of knowledge, the model...

Regularity effect in prospective memory during aging

OpenAIRE

Blondelle, Geoffrey; Hainselin, Mathieu; Gounden, Yannick; Heurley, Laurent; Voisin, Hélène; Megalakaki, Olga; Bressous, Estelle; Quaglino, Véronique

2016-01-01

Background: Regularity effect can affect performance in prospective memory (PM), but little is known on the cognitive processes linked to this effect. Moreover, its impacts with regard to aging remain unknown. To our knowledge, this study is the first to examine regularity effect in PM in a lifespan perspective, with a sample of young, intermediate, and older adults.Objective and design: Our study examined the regularity effect in PM in three groups of participants: 28 young adults (18–30), 1...

20 CFR 226.14 - Employee regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Employee regular annuity rate. 226.14 Section... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing an Employee Annuity § 226.14 Employee regular annuity rate. The regular annuity rate payable to the employee is the total of the employee tier I...

Soft X-ray imaging by optically stimulated luminescence from color centers in lithium fluoride

Energy Technology Data Exchange (ETDEWEB)

Bonfigli, F. [ENEA, C.R. Frascati, Via E. Fermi, 45, 00044 Frascati (Rome) (Italy)], E-mail: bonfigli@frascati.enea.it; Almaviva, S.; Baldacchini, G.; Bollanti, S.; Flora, F.; Lai, A.; Montereali, R.M. [ENEA, C.R. Frascati, Via E. Fermi, 45, 00044 Frascati (Rome) (Italy); Nichelatti, E. [ENEA, C.R. Casaccia, Via Anguillarese 301, 00060 S.Maria di Galeria (Rome) (Italy); Tomassetti, G.; Ritucci, A.; Reale, L. [Universita de L' Aquila e INFN, Dip. di Fisica, Coppito, L' Aquila (Italy); Faenov, A. Ya.; Pikuz, T.A. [MISDC of VNIIFTRI Mendeleevo, Moscow region, 141570 (Russian Federation); Larciprete, R. [ISC-CNR, Sezione Montelibretti, Via Salaria, Km. 29.3, 00016 Monterotondo Scalo (Rome) (Italy); Gregoratti, L.; Kiskinova, M. [Sincrotrone Trieste, S. S. 14, Km. 163.5, 34012 Basovizza (TS) (Italy)

2007-07-15

An innovative X-ray imaging detector based on Optically Stimulated Luminescence from color centers in lithium fluoride is presented. Regular photoluminescent patterns produced on LiF samples by different intense X-ray sources, like synchrotrons, laser plasma sources and a capillary discharge laser have been investigated by a Confocal Laser Scanning Microscope. The use of a LiF-based imaging plate for X-ray microscopy is also discussed showing microradiographies of small animals.

Point interactions of the dipole type defined through a three-parametric power regularization

International Nuclear Information System (INIS)

Zolotaryuk, A V

2010-01-01

A family of point interactions of the dipole type is studied in one dimension using a regularization by rectangles in the form of a barrier and a well separated by a finite distance. The rectangles and the distance are parametrized by a squeezing parameter ε → 0 with three powers μ, ν and τ describing the squeezing rates for the barrier, the well and the distance, respectively. This parametrization allows us to construct a whole family of point potentials of the dipole type including some other point interactions, such as e.g. δ-potentials. Varying the power τ, it is possible to obtain in the zero-range limit the following two cases: (i) the limiting δ'-potential is opaque (the conventional result obtained earlier by some authors) or (ii) this potential admits a resonant tunneling (the opposite result obtained recently by other authors). The structure of resonances (if any) also depends on a regularizing sequence. The sets of the {μ, ν, τ}-space where a non-zero (resonant or non-resonant) transmission occurs are found. For all these cases in the zero-range limit the transfer matrix is shown to be with real parameters χ and g depending on a regularizing sequence. Those cases when χ ≠ 1 and g ≠ 0 mean that the corresponding δ'-potential is accompanied by an effective δ-potential.

Galvanic Vestibular Stimulation (GVS) as an Analogue of Post-flight Sensorimotor Dysfunction

Data.gov (United States)

National Aeronautics and Space Administration — Aim 1A (complete): Tolerance to GVS. Dilda, V, MacDougall HG, Moore, ST. Tolerance to extended Galvanic vestibular stimulation: optimal exposure for astronaut...

Urea and ammonia excretion into gastric juice in regularly dialyzed patients and patients after renal transplantation. I. Dialyzed patients.

Science.gov (United States)

Skála, I; Marecková, O; Růzicková, J; Bláha, J; Straková, M; Reneltová, I; Jirka, J; Kocandrle, V; Zvolánková, K

1978-01-01

In regularly dialyzed patients in basal gastric juice and after stimulation with pentagastrin the volume of titrable acidity, urea and ammonia were assessed. It was revealed that in relation to the plasma urea concentration in basal juice the mean urea and ammonia concentration is roughly half and in stimulation juice roughly one third. The urea concentration in gastric juice is negatively correlated to the ammonia concentration. Urea excretion into the stomach depends on the plasma urea level and on the secretory gastric activity. The decisive factor of gastric secretion is probably parietal cell secretion. From the results ensues that gastric juice of dialyzed patients contains a quantitatively significant amount of urea and ammonia. Ammonia due to its neutralizing action distorts the examination of gastric acidity assessed by titration. The findings call for a revision of hitherto known data concerning gastric secretion of uraemic patients.

An optimal design of cluster spacing intervals for staged fracturing in horizontal shale gas wells based on the optimal SRVs

Directory of Open Access Journals (Sweden)

Lan Ren

2017-09-01

Full Text Available When horizontal well staged cluster fracturing is applied in shale gas reservoirs, the cluster spacing is essential to fracturing performance. If the cluster spacing is too small, the stimulated area between major fractures will be overlapped, and the efficiency of fracturing stimulation will be decreased. If the cluster spacing is too large, the area between major fractures cannot be stimulated completely and reservoir recovery extent will be adversely impacted. At present, cluster spacing design is mainly based on the static model with the potential reservoir stimulation area as the target, and there is no cluster spacing design method in accordance with the actual fracturing process and targets dynamic stimulated reservoir volume (SRV. In this paper, a dynamic SRV calculation model for cluster fracture propagation was established by analyzing the coupling mechanisms among fracture propagation, fracturing fluid loss and stress. Then, the cluster spacing was optimized to reach the target of the optimal SRVs. This model was applied for validation on site in the Jiaoshiba shale gasfield in the Fuling area of the Sichuan Basin. The key geological engineering parameters influencing the optimal cluster spacing intervals were analyzed. The reference charts for the optimal cluster spacing design were prepared based on the geological characteristics of south and north blocks in the Jiaoshiba shale gasfield. It is concluded that the cluster spacing optimal design method proposed in this paper is of great significance in overcoming the blindness in current cluster perforation design and guiding the optimal design of volume fracturing in shale gas reservoirs. Keywords: Shale gas, Horizontal well, Staged fracturing, Cluster spacing, Reservoir, Stimulated reservoir volume (SRV, Mathematical model, Optimal method, Sichuan basin, Jiaoshiba shale gasfield

Decay property of regularity-loss type of solutions in elastic solids with voids

KAUST Repository

Said-Houari, Belkacem; Messaoudi, Salim A.

2013-01-01

In this article, we consider two porous systems of nonclassical thermoelasticity in the whole real line. We discuss the long-time behaviour of the solutions in the presence of a strong damping acting, together with the heat effect, on the elastic equation and establish several decay results. Those decay results are shown to be very slow and of regularity-loss type. Some improvements of the decay rates have also been given, provided that the initial data belong to some weighted spaces. © 2013 Copyright Taylor and Francis Group, LLC.

Decay property of regularity-loss type of solutions in elastic solids with voids

KAUST Repository

Said-Houari, Belkacem

2013-12-01

In this article, we consider two porous systems of nonclassical thermoelasticity in the whole real line. We discuss the long-time behaviour of the solutions in the presence of a strong damping acting, together with the heat effect, on the elastic equation and establish several decay results. Those decay results are shown to be very slow and of regularity-loss type. Some improvements of the decay rates have also been given, provided that the initial data belong to some weighted spaces. © 2013 Copyright Taylor and Francis Group, LLC.

Regular algebra and finite machines

CERN Document Server

Conway, John Horton

2012-01-01

World-famous mathematician John H. Conway based this classic text on a 1966 course he taught at Cambridge University. Geared toward graduate students of mathematics, it will also prove a valuable guide to researchers and professional mathematicians.His topics cover Moore's theory of experiments, Kleene's theory of regular events and expressions, Kleene algebras, the differential calculus of events, factors and the factor matrix, and the theory of operators. Additional subjects include event classes and operator classes, some regulator algebras, context-free languages, communicative regular alg

Stickiness in Hamiltonian systems: From sharply divided to hierarchical phase space

Science.gov (United States)

Altmann, Eduardo G.; Motter, Adilson E.; Kantz, Holger

2006-02-01

We investigate the dynamics of chaotic trajectories in simple yet physically important Hamiltonian systems with nonhierarchical borders between regular and chaotic regions with positive measures. We show that the stickiness to the border of the regular regions in systems with such a sharply divided phase space occurs through one-parameter families of marginally unstable periodic orbits and is characterized by an exponent γ=2 for the asymptotic power-law decay of the distribution of recurrence times. Generic perturbations lead to systems with hierarchical phase space, where the stickiness is apparently enhanced due to the presence of infinitely many regular islands and Cantori. In this case, we show that the distribution of recurrence times can be composed of a sum of exponentials or a sum of power laws, depending on the relative contribution of the primary and secondary structures of the hierarchy. Numerical verification of our main results are provided for area-preserving maps, mushroom billiards, and the newly defined magnetic mushroom billiards.

ℓ1/2-norm regularized nonnegative low-rank and sparse affinity graph for remote sensing image segmentation

Science.gov (United States)

Tian, Shu; Zhang, Ye; Yan, Yiming; Su, Nan

2016-10-01

Segmentation of real-world remote sensing images is a challenge due to the complex texture information with high heterogeneity. Thus, graph-based image segmentation methods have been attracting great attention in the field of remote sensing. However, most of the traditional graph-based approaches fail to capture the intrinsic structure of the feature space and are sensitive to noises. A ℓ-norm regularization-based graph segmentation method is proposed to segment remote sensing images. First, we use the occlusion of the random texture model (ORTM) to extract the local histogram features. Then, a ℓ-norm regularized low-rank and sparse representation (LNNLRS) is implemented to construct a ℓ-regularized nonnegative low-rank and sparse graph (LNNLRS-graph), by the union of feature subspaces. Moreover, the LNNLRS-graph has a high ability to discriminate the manifold intrinsic structure of highly homogeneous texture information. Meanwhile, the LNNLRS representation takes advantage of the low-rank and sparse characteristics to remove the noises and corrupted data. Last, we introduce the LNNLRS-graph into the graph regularization nonnegative matrix factorization to enhance the segmentation accuracy. The experimental results using remote sensing images show that when compared to five state-of-the-art image segmentation methods, the proposed method achieves more accurate segmentation results.

39 CFR 6.1 - Regular meetings, annual meeting.

Science.gov (United States)

2010-07-01

... 39 Postal Service 1 2010-07-01 2010-07-01 false Regular meetings, annual meeting. 6.1 Section 6.1 Postal Service UNITED STATES POSTAL SERVICE THE BOARD OF GOVERNORS OF THE U.S. POSTAL SERVICE MEETINGS (ARTICLE VI) § 6.1 Regular meetings, annual meeting. The Board shall meet regularly on a schedule...

Analysis in Banach spaces

CERN Document Server

Hytönen, Tuomas; Veraar, Mark; Weis, Lutz

The present volume develops the theory of integration in Banach spaces, martingales and UMD spaces, and culminates in a treatment of the Hilbert transform, Littlewood-Paley theory and the vector-valued Mihlin multiplier theorem. Over the past fifteen years, motivated by regularity problems in evolution equations, there has been tremendous progress in the analysis of Banach space-valued functions and processes. The contents of this extensive and powerful toolbox have been mostly scattered around in research papers and lecture notes. Collecting this diverse body of material into a unified and accessible presentation fills a gap in the existing literature. The principal audience that we have in mind consists of researchers who need and use Analysis in Banach Spaces as a tool for studying problems in partial differential equations, harmonic analysis, and stochastic analysis. Self-contained and offering complete proofs, this work is accessible to graduate students and researchers with a background in functional an...

Ombud's corner: space invaders

CERN Multimedia

Sudeshna Datta-Cockerill

2015-01-01

When normal communication breaks down and there is no sharing anymore, office-mates can become ‘space invaders’. Very often, the situation can be resolved effectively by taking just a few simple steps...   The lack of office space at CERN is a permanent issue that the various departments regularly have to address. As a result, very often this precious space where we spend the entire day has to be shared with other colleagues. Office-mates may come from different backgrounds and cultures and may have very different habits and behaviours; they may also have different activities during the day, sometimes requiring unusual, (perhaps even strange?) interactions with the space they occupy; finally, their presence might be irregular, making it very difficult for us to establish a stable relationship. Mark and Claire share an office as well as some professional activities. In the beginning, the relationship seems to work normally but, over time, the communication between them ste...

Group-level variations in motor representation areas of thenar and anterior tibial muscles: Navigated Transcranial Magnetic Stimulation Study.

Science.gov (United States)

Niskanen, Eini; Julkunen, Petro; Säisänen, Laura; Vanninen, Ritva; Karjalainen, Pasi; Könönen, Mervi

2010-08-01

Navigated transcranial magnetic stimulation (TMS) can be used to stimulate functional cortical areas at precise anatomical location to induce measurable responses. The stimulation has commonly been focused on anatomically predefined motor areas: TMS of that area elicits a measurable muscle response, the motor evoked potential. In clinical pathologies, however, the well-known homunculus somatotopy theory may not be straightforward, and the representation area of the muscle is not fixed. Traditionally, the anatomical locations of TMS stimulations have not been reported at the group level in standard space. This study describes a methodology for group-level analysis by investigating the normal representation areas of thenar and anterior tibial muscle in the primary motor cortex. The optimal representation area for these muscles was mapped in 59 healthy right-handed subjects using navigated TMS. The coordinates of the optimal stimulation sites were then normalized into standard space to determine the representation areas of these muscles at the group-level in healthy subjects. Furthermore, 95% confidence interval ellipsoids were fitted into the optimal stimulation site clusters to define the variation between subjects in optimal stimulation sites. The variation was found to be highest in the anteroposterior direction along the superior margin of the precentral gyrus. These results provide important normative information for clinical studies assessing changes in the functional cortical areas because of plasticity of the brain. Furthermore, it is proposed that the presented methodology to study TMS locations at the group level on standard space will be a suitable tool for research purposes in population studies. 2010 Wiley-Liss, Inc.

Space-Time Discrete KPZ Equation

Science.gov (United States)

Cannizzaro, G.; Matetski, K.

2018-03-01

We study a general family of space-time discretizations of the KPZ equation and show that they converge to its solution. The approach we follow makes use of basic elements of the theory of regularity structures (Hairer in Invent Math 198(2):269-504, 2014) as well as its discrete counterpart (Hairer and Matetski in Discretizations of rough stochastic PDEs, 2015. arXiv:1511.06937). Since the discretization is in both space and time and we allow non-standard discretization for the product, the methods mentioned above have to be suitably modified in order to accommodate the structure of the models under study.

A regularized stationary mean-field game

KAUST Repository

Yang, Xianjin

2016-01-01

In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.

A regularized stationary mean-field game

KAUST Repository

Yang, Xianjin

2016-04-19

In the thesis, we discuss the existence and numerical approximations of solutions of a regularized mean-field game with a low-order regularization. In the first part, we prove a priori estimates and use the continuation method to obtain the existence of a solution with a positive density. Finally, we introduce the monotone flow method and solve the system numerically.

Automating InDesign with Regular Expressions

CERN Document Server

Kahrel, Peter

2006-01-01

If you need to make automated changes to InDesign documents beyond what basic search and replace can handle, you need regular expressions, and a bit of scripting to make them work. This Short Cut explains both how to write regular expressions, so you can find and replace the right things, and how to use them in InDesign specifically.

Cyclic programmed cell death stimulates hormone signaling and root development in Arabidopsis

NARCIS (Netherlands)

Xuan, Wei; Band, Leah R.; Kumpf, Robert P.; Rybel, De Bert

2016-01-01

The plant root cap, surrounding the very tip of the growing root, perceives and transmits environmental signals to the inner root tissues. In Arabidopsis thaliana, auxin released by the root cap contributes to the regular spacing of lateral organs along the primary root axis. Here, we show that

Optimal behaviour can violate the principle of regularity.

Science.gov (United States)

Trimmer, Pete C

2013-07-22

Understanding decisions is a fundamental aim of behavioural ecology, psychology and economics. The regularity axiom of utility theory holds that a preference between options should be maintained when other options are made available. Empirical studies have shown that animals violate regularity but this has not been understood from a theoretical perspective, such decisions have therefore been labelled as irrational. Here, I use models of state-dependent behaviour to demonstrate that choices can violate regularity even when behavioural strategies are optimal. I also show that the range of conditions over which regularity should be violated can be larger when options do not always persist into the future. Consequently, utility theory--based on axioms, including transitivity, regularity and the independence of irrelevant alternatives--is undermined, because even alternatives that are never chosen by an animal (in its current state) can be relevant to a decision.

Regular Breakfast and Blood Lead Levels among Preschool Children

Directory of Open Access Journals (Sweden)

Needleman Herbert

2011-04-01

Full Text Available Abstract Background Previous studies have shown that fasting increases lead absorption in the gastrointestinal tract of adults. Regular meals/snacks are recommended as a nutritional intervention for lead poisoning in children, but epidemiological evidence of links between fasting and blood lead levels (B-Pb is rare. The purpose of this study was to examine the association between eating a regular breakfast and B-Pb among children using data from the China Jintan Child Cohort Study. Methods Parents completed a questionnaire regarding children's breakfast-eating habit (regular or not, demographics, and food frequency. Whole blood samples were collected from 1,344 children for the measurements of B-Pb and micronutrients (iron, copper, zinc, calcium, and magnesium. B-Pb and other measures were compared between children with and without regular breakfast. Linear regression modeling was used to evaluate the association between regular breakfast and log-transformed B-Pb. The association between regular breakfast and risk of lead poisoning (B-Pb≥10 μg/dL was examined using logistic regression modeling. Results Median B-Pb among children who ate breakfast regularly and those who did not eat breakfast regularly were 6.1 μg/dL and 7.2 μg/dL, respectively. Eating breakfast was also associated with greater zinc blood levels. Adjusting for other relevant factors, the linear regression model revealed that eating breakfast regularly was significantly associated with lower B-Pb (beta = -0.10 units of log-transformed B-Pb compared with children who did not eat breakfast regularly, p = 0.02. Conclusion The present study provides some initial human data supporting the notion that eating a regular breakfast might reduce B-Pb in young children. To our knowledge, this is the first human study exploring the association between breakfast frequency and B-Pb in young children.

On the equivalence of different regularization methods

International Nuclear Information System (INIS)

Brzezowski, S.

1985-01-01

The R-circunflex-operation preceded by the regularization procedure is discussed. Some arguments are given, according to which the results may depend on the method of regularization, introduced in order to avoid divergences in perturbation calculations. 10 refs. (author)

Young PHD's in Human Space Flight

Science.gov (United States)

Wilson, Eleanor

2002-01-01

The Cooperating Hampton Roads Organizations for Minorities in Engineering (CHROME) in cooperation with the NASA Office of Space Flight, Human Exploration and Development of Space Enterprise sponsored a summer institute, Young PHD#s (Persons Having Dreams) in Human Space Flight. This 3-day institute used the curriculum of a workshop designed for space professionals, 'Human Space Flight-Analysis and Design: An Integrated, Systematic Approach.' The content was tailored to a high school audience. This institute seeks to stimulate the interest of pre-college students in space flight and motivate them to pursue further experiences in this field. Additionally, this institute will serve as a pilot model for a pre- collegiate training program that can be replicated throughout the country. The institute was complemented with a trip to the Goddard Space Flight Center.

Regularity for a clamped grid equation $u_{xxxx}+u_{yyyy}=f $ on a domain with a corner

Directory of Open Access Journals (Sweden)

Tymofiy Gerasimov

2009-04-01

Full Text Available The operator $L=frac{partial ^{4}}{partial x^{4}} +frac{partial ^{4}}{partial y^{4}}$ appears in a model for the vertical displacement of a two-dimensional grid that consists of two perpendicular sets of elastic fibers or rods. We are interested in the behaviour of such a grid that is clamped at the boundary and more specifically near a corner of the domain. Kondratiev supplied the appropriate setting in the sense of Sobolev type spaces tailored to find the optimal regularity. Inspired by the Laplacian and the Bilaplacian models one expect, except maybe for some special angles that the optimal regularity improves when angle decreases. For the homogeneous Dirichlet problem with this special non-isotropic fourth order operator such a result does not hold true. We will show the existence of an interval $( frac{1}{2}pi ,omega _{star }$, $omega _{star }/pi approx 0.528dots$ (in degrees $omega _{star }approx 95.1dots^{circ} $, in which the optimal regularity improves with increasing opening angle.

Regular-chaos transition of the energy spectrum and electromagnetic transition intensities in 44V nucleus using the framework of the nuclear shell model

International Nuclear Information System (INIS)

Hamoudi, A.K.; Abdul Majeed Al-Rahmani, A.

2012-01-01

The spectral fluctuations and the statistics of electromagnetic transition intensities and electromagnetic moments in 44 V nucleus are studied by the framework of the interacting shell model, using the FPD6 as a realistic effective interaction in the isospin formalism for 4 particles move in the fp-model space with a 40 Ca core. To look for a regular-chaos transition in 44 V nucleus, we perform shell model calculations using various interaction strengths β to the off-diagonal matrix elements of the FPD6. The nearest-neighbors level spacing distribution P(s) and the distribution of electromagnetic transition intensities [such as, B(M1) and B(E2) transitions] are found to have a regular dynamic at β=0, a chaotic dynamic at β⩾0.3 and an intermediate situation at 0 3 statistic we have found a regular dynamic at β=0, a chaotic dynamic at β⩾0.4 and an intermediate situation at 0<β<0.4. It is also found that the statistics of the squares of M1 and E2 moments, which are consistent with a Porter-Thomas distribution, have no dependence on the interaction strength β.

Bounded Perturbation Regularization for Linear Least Squares Estimation

KAUST Repository

Ballal, Tarig

2017-10-18

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded norm is allowed into the linear transformation matrix to improve the singular-value structure. Following this, the problem is formulated as a min-max optimization problem. Next, the min-max problem is converted to an equivalent minimization problem to estimate the unknown vector quantity. The solution of the minimization problem is shown to converge to that of the ℓ2 -regularized least squares problem, with the unknown regularizer related to the norm bound of the introduced perturbation through a nonlinear constraint. A procedure is proposed that combines the constraint equation with the mean squared error (MSE) criterion to develop an approximately optimal regularization parameter selection algorithm. Both direct and indirect applications of the proposed method are considered. Comparisons with different Tikhonov regularization parameter selection methods, as well as with other relevant methods, are carried out. Numerical results demonstrate that the proposed method provides significant improvement over state-of-the-art methods.

Ad Hoc Physical Hilbert Spaces in Quantum Mechanics

Czech Academy of Sciences Publication Activity Database

Fernandez, F. M.; Garcia, J.; Semorádová, Iveta; Znojil, Miloslav

2015-01-01

Roč. 54, č. 12 (2015), s. 4187-4203 ISSN 0020-7748 Institutional support: RVO:61389005 Keywords : quantum mechanics * physical Hilbert spaces * ad hoc inner product * singular potentials regularized * low lying energies Subject RIV: BE - Theoretical Physics Impact factor: 1.041, year: 2015

MRI reconstruction with joint global regularization and transform learning.

Science.gov (United States)

Tanc, A Korhan; Eksioglu, Ender M

2016-10-01

Sparsity based regularization has been a popular approach to remedy the measurement scarcity in image reconstruction. Recently, sparsifying transforms learned from image patches have been utilized as an effective regularizer for the Magnetic Resonance Imaging (MRI) reconstruction. Here, we infuse additional global regularization terms to the patch-based transform learning. We develop an algorithm to solve the resulting novel cost function, which includes both patchwise and global regularization terms. Extensive simulation results indicate that the introduced mixed approach has improved MRI reconstruction performance, when compared to the algorithms which use either of the patchwise transform learning or global regularization terms alone. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dynamical tunneling in systems with a mixed phase space

International Nuclear Information System (INIS)

Loeck, Steffen

2010-01-01

Tunneling is one of the most prominent features of quantum mechanics. While the tunneling process in one-dimensional integrable systems is well understood, its quantitative prediction for systems with a mixed phase space is a long-standing open challenge. In such systems regions of regular and chaotic dynamics coexist in phase space, which are classically separated but quantum mechanically coupled by the process of dynamical tunneling. We derive a prediction of dynamical tunneling rates which describe the decay of states localized inside the regular region towards the so-called chaotic sea. This approach uses a fictitious integrable system which mimics the dynamics inside the regular domain and extends it into the chaotic region. Excellent agreement with numerical data is found for kicked systems, billiards, and optical microcavities, if nonlinear resonances are negligible. Semiclassically, however, such nonlinear resonance chains dominate the tunneling process. Hence, we combine our approach with an improved resonance-assisted tunneling theory and derive a unified prediction which is valid from the quantum to the semiclassical regime. We obtain results which show a drastically improved accuracy of several orders of magnitude compared to previous studies. (orig.)

Dynamical tunneling in systems with a mixed phase space

Energy Technology Data Exchange (ETDEWEB)

Loeck, Steffen

2010-04-22

Tunneling is one of the most prominent features of quantum mechanics. While the tunneling process in one-dimensional integrable systems is well understood, its quantitative prediction for systems with a mixed phase space is a long-standing open challenge. In such systems regions of regular and chaotic dynamics coexist in phase space, which are classically separated but quantum mechanically coupled by the process of dynamical tunneling. We derive a prediction of dynamical tunneling rates which describe the decay of states localized inside the regular region towards the so-called chaotic sea. This approach uses a fictitious integrable system which mimics the dynamics inside the regular domain and extends it into the chaotic region. Excellent agreement with numerical data is found for kicked systems, billiards, and optical microcavities, if nonlinear resonances are negligible. Semiclassically, however, such nonlinear resonance chains dominate the tunneling process. Hence, we combine our approach with an improved resonance-assisted tunneling theory and derive a unified prediction which is valid from the quantum to the semiclassical regime. We obtain results which show a drastically improved accuracy of several orders of magnitude compared to previous studies. (orig.)

Strictly-regular number system and data structures

DEFF Research Database (Denmark)

Elmasry, Amr Ahmed Abd Elmoneim; Jensen, Claus; Katajainen, Jyrki

2010-01-01

We introduce a new number system that we call the strictly-regular system, which efficiently supports the operations: digit-increment, digit-decrement, cut, concatenate, and add. Compared to other number systems, the strictly-regular system has distinguishable properties. It is superior to the re...

Analysis of regularized Navier-Stokes equations, 2

Science.gov (United States)

Ou, Yuh-Roung; Sritharan, S. S.

1989-01-01

A practically important regularization of the Navier-Stokes equations was analyzed. As a continuation of the previous work, the structure of the attractors characterizing the solutins was studied. Local as well as global invariant manifolds were found. Regularity properties of these manifolds are analyzed.

Regularities, Natural Patterns and Laws of Nature

Directory of Open Access Journals (Sweden)

Stathis Psillos

2014-02-01

Full Text Available  The goal of this paper is to sketch an empiricist metaphysics of laws of nature. The key idea is that there are regularities without regularity-enforcers. Differently put, there are natural laws without law-makers of a distinct metaphysical kind. This sketch will rely on the concept of a natural pattern and more significantly on the existence of a network of natural patterns in nature. The relation between a regularity and a pattern will be analysed in terms of mereology.  Here is the road map. In section 2, I will briefly discuss the relation between empiricism and metaphysics, aiming to show that an empiricist metaphysics is possible. In section 3, I will offer arguments against stronger metaphysical views of laws. Then, in section 4 I will motivate nomic objectivism. In section 5, I will address the question ‘what is a regularity?’ and will develop a novel answer to it, based on the notion of a natural pattern. In section 6, I will raise the question: ‘what is a law of nature?’, the answer to which will be: a law of nature is a regularity that is characterised by the unity of a natural pattern.

Consistent Partial Least Squares Path Modeling via Regularization.

Science.gov (United States)

Jung, Sunho; Park, JaeHong

2018-01-01

Partial least squares (PLS) path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc), designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

Consistent Partial Least Squares Path Modeling via Regularization

Directory of Open Access Journals (Sweden)

Sunho Jung

2018-02-01

Full Text Available Partial least squares (PLS path modeling is a component-based structural equation modeling that has been adopted in social and psychological research due to its data-analytic capability and flexibility. A recent methodological advance is consistent PLS (PLSc, designed to produce consistent estimates of path coefficients in structural models involving common factors. In practice, however, PLSc may frequently encounter multicollinearity in part because it takes a strategy of estimating path coefficients based on consistent correlations among independent latent variables. PLSc has yet no remedy for this multicollinearity problem, which can cause loss of statistical power and accuracy in parameter estimation. Thus, a ridge type of regularization is incorporated into PLSc, creating a new technique called regularized PLSc. A comprehensive simulation study is conducted to evaluate the performance of regularized PLSc as compared to its non-regularized counterpart in terms of power and accuracy. The results show that our regularized PLSc is recommended for use when serious multicollinearity is present.

On Some General Regularities of Formation of the Planetary Systems

Directory of Open Access Journals (Sweden)

Belyakov A. V.

2014-01-01

Full Text Available J.Wheeler’s geometrodynamic concept has been used, in which space continuum is considered as a topologically non-unitary coherent surface admitting the existence of transitions of the input-output kind between distant regions of the space in an additional dimension. This model assumes the existence of closed structures (micro- and macro- contours formed due to the balance between main interactions: gravitational, electric, magnetic, and inertial forces. It is such macrocontours that have been demonstrated to form — independently of their material basis — the essential structure of objects at various levels of organization of matter. On the basis of this concept in this paper basic regularities acting during formation planetary systems have been obtained. The existence of two sharply different types of planetary systems has been determined. The dependencies linking the masses of the planets, the diameters of the planets, the orbital radii of the planet, and the mass of the central body have been deduced. The possibility of formation of Earth-like planets near brown dwarfs has been grounded. The minimum mass of the planet, which may arise in the planetary system, has been defined.

Comparison of the ballistic contractile responses generated during microstimulation of single human motor axons with brief irregular and regular stimuli.

Science.gov (United States)

Leitch, Michael; Macefield, Vaughan G

2017-08-01

Ballistic contractions are induced by brief, high-frequency (60-100 Hz) trains of action potentials in motor axons. During ramp voluntary contractions, human motoneurons exhibit significant discharge variability of ∼20% and have been shown to be advantageous to the neuromuscular system. We hypothesized that ballistic contractions incorporating discharge variability would generate greater isometric forces than regular trains with zero variability. High-impedance tungsten microelectrodes were inserted into human fibular nerve, and single motor axons were stimulated with both irregular and constant-frequency stimuli at mean frequencies ranging from 57.8 to 68.9 Hz. Irregular trains generated significantly greater isometric peak forces than regular trains over identical mean frequencies. The high forces generated by ballistic contractions are not based solely on high frequencies, but rather a combination of high firing rates and discharge irregularity. It appears that irregular ballistic trains take advantage of the "catchlike property" of muscle, allowing augmentation of force. Muscle Nerve 56: 292-297, 2017. © 2016 Wiley Periodicals, Inc.

Bilinear Regularized Locality Preserving Learning on Riemannian Graph for Motor Imagery BCI.

Science.gov (United States)

Xie, Xiaofeng; Yu, Zhu Liang; Gu, Zhenghui; Zhang, Jun; Cen, Ling; Li, Yuanqing

2018-03-01

In off-line training of motor imagery-based brain-computer interfaces (BCIs), to enhance the generalization performance of the learned classifier, the local information contained in test data could be used to improve the performance of motor imagery as well. Further considering that the covariance matrices of electroencephalogram (EEG) signal lie on Riemannian manifold, in this paper, we construct a Riemannian graph to incorporate the information of training and test data into processing. The adjacency and weight in Riemannian graph are determined by the geodesic distance of Riemannian manifold. Then, a new graph embedding algorithm, called bilinear regularized locality preserving (BRLP), is derived upon the Riemannian graph for addressing the problems of high dimensionality frequently arising in BCIs. With a proposed regularization term encoding prior information of EEG channels, the BRLP could obtain more robust performance. Finally, an efficient classification algorithm based on extreme learning machine is proposed to perform on the tangent space of learned embedding. Experimental evaluations on the BCI competition and in-house data sets reveal that the proposed algorithms could obtain significantly higher performance than many competition algorithms after using same filter process.

Regularization of the Boundary-Saddle-Node Bifurcation

Directory of Open Access Journals (Sweden)

Xia Liu

2018-01-01

Full Text Available In this paper we treat a particular class of planar Filippov systems which consist of two smooth systems that are separated by a discontinuity boundary. In such systems one vector field undergoes a saddle-node bifurcation while the other vector field is transversal to the boundary. The boundary-saddle-node (BSN bifurcation occurs at a critical value when the saddle-node point is located on the discontinuity boundary. We derive a local topological normal form for the BSN bifurcation and study its local dynamics by applying the classical Filippov’s convex method and a novel regularization approach. In fact, by the regularization approach a given Filippov system is approximated by a piecewise-smooth continuous system. Moreover, the regularization process produces a singular perturbation problem where the original discontinuous set becomes a center manifold. Thus, the regularization enables us to make use of the established theories for continuous systems and slow-fast systems to study the local behavior around the BSN bifurcation.

Creating a Space for Creativity

DEFF Research Database (Denmark)

Bøjer, Bodil

2017-01-01

and creativity. But the relational dependence between the physical space, pedagogics and organisation is widely overlooked when designing these new learning environments as a new spatial design in itself is expected to change the way we teach and learn. Simply changing the space is not enough (Imms & Byers, 2017......) and the intentions of the space can only be fully realised if the inhabitants of the schools completely understand and support the pedagogical principles informing the provision of these spaces (Burke, 2016). This is why three things should be aligned in order for an ILE to work intendedly: creative teaching (the...... teacher), space (the designer) and organisation (management). With my research, I would like to contribute to the understanding of the relationship between the physical learning environment and creative learning processes and the potential of the space as a tool to stimulate creativity. In my poster...

Low-Complexity Regularization Algorithms for Image Deblurring

KAUST Repository

Alanazi, Abdulrahman

2016-11-01

Image restoration problems deal with images in which information has been degraded by blur or noise. In practice, the blur is usually caused by atmospheric turbulence, motion, camera shake, and several other mechanical or physical processes. In this study, we present two regularization algorithms for the image deblurring problem. We first present a new method based on solving a regularized least-squares (RLS) problem. This method is proposed to find a near-optimal value of the regularization parameter in the RLS problems. Experimental results on the non-blind image deblurring problem are presented. In all experiments, comparisons are made with three benchmark methods. The results demonstrate that the proposed method clearly outperforms the other methods in terms of both the output PSNR and structural similarity, as well as the visual quality of the deblurred images. To reduce the complexity of the proposed algorithm, we propose a technique based on the bootstrap method to estimate the regularization parameter in low and high-resolution images. Numerical results show that the proposed technique can effectively reduce the computational complexity of the proposed algorithms. In addition, for some cases where the point spread function (PSF) is separable, we propose using a Kronecker product so as to reduce the computations. Furthermore, in the case where the image is smooth, it is always desirable to replace the regularization term in the RLS problems by a total variation term. Therefore, we propose a novel method for adaptively selecting the regularization parameter in a so-called square root regularized total variation (SRTV). Experimental results demonstrate that our proposed method outperforms the other benchmark methods when applied to smooth images in terms of PSNR, SSIM and the restored image quality. In this thesis, we focus on the non-blind image deblurring problem, where the blur kernel is assumed to be known. However, we developed algorithms that also work

Improvements in GRACE Gravity Fields Using Regularization

Science.gov (United States)

Save, H.; Bettadpur, S.; Tapley, B. D.

2008-12-01

The unconstrained global gravity field models derived from GRACE are susceptible to systematic errors that show up as broad "stripes" aligned in a North-South direction on the global maps of mass flux. These errors are believed to be a consequence of both systematic and random errors in the data that are amplified by the nature of the gravity field inverse problem. These errors impede scientific exploitation of the GRACE data products, and limit the realizable spatial resolution of the GRACE global gravity fields in certain regions. We use regularization techniques to reduce these "stripe" errors in the gravity field products. The regularization criteria are designed such that there is no attenuation of the signal and that the solutions fit the observations as well as an unconstrained solution. We have used a computationally inexpensive method, normally referred to as "L-ribbon", to find the regularization parameter. This paper discusses the characteristics and statistics of a 5-year time-series of regularized gravity field solutions. The solutions show markedly reduced stripes, are of uniformly good quality over time, and leave little or no systematic observation residuals, which is a frequent consequence of signal suppression from regularization. Up to degree 14, the signal in regularized solution shows correlation greater than 0.8 with the un-regularized CSR Release-04 solutions. Signals from large-amplitude and small-spatial extent events - such as the Great Sumatra Andaman Earthquake of 2004 - are visible in the global solutions without using special post-facto error reduction techniques employed previously in the literature. Hydrological signals as small as 5 cm water-layer equivalent in the small river basins, like Indus and Nile for example, are clearly evident, in contrast to noisy estimates from RL04. The residual variability over the oceans relative to a seasonal fit is small except at higher latitudes, and is evident without the need for de-striping or

Loop-space quantum formulation of free electromagnetism

International Nuclear Information System (INIS)

Di Bartolo, C.; Nori, F.; Gambini, R.; Trias, A.

1983-01-01

A procedure for direct quantization of free electromagnetism in the loop-space is proposed. Explicit solutions for the loop-dependent vacuum and the Wilson loop-average are given. It is shown that elementary lines of magnetic field appear as extremals in the vacuum state as a result of the regularization procedure

Deterministic automata for extended regular expressions

Directory of Open Access Journals (Sweden)

Syzdykov Mirzakhmet

2017-12-01

Full Text Available In this work we present the algorithms to produce deterministic finite automaton (DFA for extended operators in regular expressions like intersection, subtraction and complement. The method like “overriding” of the source NFA(NFA not defined with subset construction rules is used. The past work described only the algorithm for AND-operator (or intersection of regular languages; in this paper the construction for the MINUS-operator (and complement is shown.

Regularities of intermediate adsorption complex relaxation

International Nuclear Information System (INIS)

Manukova, L.A.

1982-01-01

The experimental data, characterizing the regularities of intermediate adsorption complex relaxation in the polycrystalline Mo-N 2 system at 77 K are given. The method of molecular beam has been used in the investigation. The analytical expressions of change regularity in the relaxation process of full and specific rates - of transition from intermediate state into ''non-reversible'', of desorption into the gas phase and accumUlation of the particles in the intermediate state are obtained

Systematic implementation of implicit regularization for multi-loop Feynman Diagrams

International Nuclear Information System (INIS)

Cherchiglia, Adriano Lana; Sampaio, Marcos; Nemes, Maria Carolina

2011-01-01

Full text: Implicit Regularization (IR) is a candidate to become an invariant framework in momentum space to perform Feynman diagram calculations to arbitrary loop order. The essence of the method is to write the divergences in terms of loop integrals in one internal momentum which do not need to be explicitly evaluated. Moreover it acts in the physical dimension of the theory and gauge invariance is controlled by regularization dependent surface terms which when set to zero define a constrained version of IR (CIR) and deliver gauge invariant amplitudes automatically. Therefore it is in principle applicable to all physical relevant quantum field theories, supersymmetric gauge theories included. A non trivial question is whether we can generalize this program to arbitrary loop order in consonance with locality, unitarity and Lorentz invariance, especially when overlapping divergences occur. In this work we present a systematic implementation of our method that automatically displays the terms to be subtracted by Bogoliubov's recursion formula. Therefore, we achieve a twofold objective: we show that the IR program respects unitarity, locality and Lorentz invariance and we show that our method is consistent since we are able to display the divergent content of a multi-loop amplitude in a well defined set of basic divergent integrals in one internal momentum. We present several examples (from 1-loop to n-loops) using scalar φ 6 3 theory in order to help the reader understand and visualize the essence of the IR program. The choice of a scalar theory does not reduce the generality of the method presented since all other physical theories can be treated within the same strategy after space time and internal algebra are performed. Another result of this contribution is to show that if the surface terms are not set to zero they will contaminate the renormalization group coefficients. Thus, we are forced to adopt CIR which is equivalent to demand momentum routing invariance

Space - A unique environment for process modeling R&D

Science.gov (United States)

Overfelt, Tony

1991-01-01

Process modeling, the application of advanced computational techniques to simulate real processes as they occur in regular use, e.g., welding, casting and semiconductor crystal growth, is discussed. Using the low-gravity environment of space will accelerate the technical validation of the procedures and enable extremely accurate determinations of the many necessary thermophysical properties. Attention is given to NASA's centers for the commercial development of space; joint ventures of universities, industries, and goverment agencies to study the unique attributes of space that offer potential for applied R&D and eventual commercial exploitation.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

Phaseless tomographic inverse scattering in Banach spaces

International Nuclear Information System (INIS)

Estatico, C.; Fedeli, A.; Pastorino, M.; Randazzo, A.; Tavanti, E.

2016-01-01

In conventional microwave imaging, a hidden dielectric object under test is illuminated by microwave incident waves and the field it scatters is measured in magnitude and phase in order to retrieve the dielectric properties by solving the related non-homogenous Helmholtz equation or its Lippmann-Schwinger integral formulation. Since the measurement of the phase of electromagnetic waves can be still considered expensive in real applications, in this paper only the magnitude of the scattering wave fields is measured in order to allow a reduction of the cost of the measurement apparatus. In this respect, we firstly analyse the properties of the phaseless scattering nonlinear forward modelling operator in its integral form and we provide an analytical expression for computing its Fréchet derivative. Then, we propose an inexact Newton method to solve the associated nonlinear inverse problems, where any linearized step is solved by a L p Banach space iterative regularization method which acts on the dual space L p* . Indeed, it is well known that regularization in special Banach spaces, such us L p with 1 < p < 2, allows to promote sparsity and to reduce Gibbs phenomena and over-smoothness. Preliminary results concerning numerically computed field data are shown. (paper)

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

20 CFR 226.35 - Deductions from regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Deductions from regular annuity rate. 226.35... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing a Spouse or Divorced Spouse Annuity § 226.35 Deductions from regular annuity rate. The regular annuity rate of the spouse and divorced...

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

Science.gov (United States)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2013-01-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

Artificial intelligence - NASA. [robotics for Space Station

Science.gov (United States)

Erickson, J. D.

1985-01-01

Artificial Intelligence (AI) represents a vital common space support element needed to enable the civil space program and commercial space program to perform their missions successfully. It is pointed out that advances in AI stimulated by the Space Station Program could benefit the U.S. in many ways. A fundamental challenge for the civil space program is to meet the needs of the customers and users of space with facilities enabling maximum productivity and having low start-up costs, and low annual operating costs. An effective way to meet this challenge may involve a man-machine system in which artificial intelligence, robotics, and advanced automation are integrated into high reliability organizations. Attention is given to the benefits, NASA strategy for AI, candidate space station systems, the Space Station as a stepping stone, and the commercialization of space.

Targeted transtracheal stimulation for vocal fold closure.

Science.gov (United States)

Hadley, Aaron J; Thompson, Paul; Kolb, Ilya; Hahn, Elizabeth C; Tyler, Dustin J

2014-06-01

Paralysis of the structures in the head and neck due to stroke or other neurological disorder often causes dysphagia (difficulty in swallowing). Patients with dysphagia have a significantly higher incidence of aspiration pneumonia and death. The recurrent laryngeal nerve (RLN), which innervates the intrinsic laryngeal muscles that control the vocal folds, travels superiorly in parallel to the trachea in the tracheoesophageal groove. This study tests the hypothesis that functional electrical stimulation (FES) applied via transtracheal electrodes can produce controlled vocal fold adduction. Bipolar electrodes were placed at 15° intervals around the interior mucosal surface of the canine trachea, and current was applied to the tissue while electromyography (EMG) from the intrinsic laryngeal muscles and vocal fold movement visualization via laryngoscopy were recorded. The lowest EMG thresholds were found at an average location of 100° to the left of the ventral midsagittal line and 128° to the right. A rotatable pair of bipolar electrodes spaced 230° apart were able to stimulate bilaterally both RLNs in every subject. Laryngoscopy showed complete glottal closure with transtracheal stimulation in six of the eight subjects, and this closure was maintained under simultaneous FES-induced laryngeal elevation. Transtracheal stimulation is an effective tool for minimally invasive application of FES to induce vocal fold adduction, providing an alternative mechanism to study airway protection.

Regularization theory for ill-posed problems selected topics

CERN Document Server

Lu, Shuai

2013-01-01

Thismonograph is a valuable contribution to thehighly topical and extremly productive field ofregularisationmethods for inverse and ill-posed problems. The author is an internationally outstanding and acceptedmathematicianin this field. In his book he offers a well-balanced mixtureof basic and innovative aspects.He demonstrates new,differentiatedviewpoints, and important examples for applications. The bookdemontrates thecurrent developments inthe field of regularization theory,such as multiparameter regularization and regularization in learning theory. The book is written for graduate and PhDs

Finite Metric Spaces of Strictly Negative Type

DEFF Research Database (Denmark)

Hjorth, Poul; Lisonek, P.; Markvorsen, Steen

1998-01-01

of Euclidean spaces. We prove that, if the distance matrix is both hypermetric and regular, then it is of strictly negative type. We show that the strictly negative type finite subspaces of spheres are precisely those which do not contain two pairs of antipodal points. In connection with an open problem raised...

20 CFR 226.34 - Divorced spouse regular annuity rate.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 1 2010-04-01 2010-04-01 false Divorced spouse regular annuity rate. 226.34... COMPUTING EMPLOYEE, SPOUSE, AND DIVORCED SPOUSE ANNUITIES Computing a Spouse or Divorced Spouse Annuity § 226.34 Divorced spouse regular annuity rate. The regular annuity rate of a divorced spouse is equal to...

Chimeric mitochondrial peptides from contiguous regular and swinger RNA.

Science.gov (United States)

Seligmann, Hervé

2016-01-01

Previous mass spectrometry analyses described human mitochondrial peptides entirely translated from swinger RNAs, RNAs where polymerization systematically exchanged nucleotides. Exchanges follow one among 23 bijective transformation rules, nine symmetric exchanges (X ↔ Y, e.g. A ↔ C) and fourteen asymmetric exchanges (X → Y → Z → X, e.g. A → C → G → A), multiplying by 24 DNA's protein coding potential. Abrupt switches from regular to swinger polymerization produce chimeric RNAs. Here, human mitochondrial proteomic analyses assuming abrupt switches between regular and swinger transcriptions, detect chimeric peptides, encoded by part regular, part swinger RNA. Contiguous regular- and swinger-encoded residues within single peptides are stronger evidence for translation of swinger RNA than previously detected, entirely swinger-encoded peptides: regular parts are positive controls matched with contiguous swinger parts, increasing confidence in results. Chimeric peptides are 200 × rarer than swinger peptides (3/100,000 versus 6/1000). Among 186 peptides with > 8 residues for each regular and swinger parts, regular parts of eleven chimeric peptides correspond to six among the thirteen recognized, mitochondrial protein-coding genes. Chimeric peptides matching partly regular proteins are rarer and less expressed than chimeric peptides matching non-coding sequences, suggesting targeted degradation of misfolded proteins. Present results strengthen hypotheses that the short mitogenome encodes far more proteins than hitherto assumed. Entirely swinger-encoded proteins could exist.

On the minimizers of calculus of variations problems in Hilbert spaces

KAUST Repository

Gomes, Diogo A.

2014-01-19

The objective of this paper is to discuss existence, uniqueness and regularity issues of minimizers of one dimensional calculus of variations problem in Hilbert spaces. © 2014 Springer-Verlag Berlin Heidelberg.

On the minimizers of calculus of variations problems in Hilbert spaces

KAUST Repository

Gomes, Diogo A.; Nurbekyan, Levon

2014-01-01

The objective of this paper is to discuss existence, uniqueness and regularity issues of minimizers of one dimensional calculus of variations problem in Hilbert spaces. © 2014 Springer-Verlag Berlin Heidelberg.

Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Jaewook Jung

2017-03-01

Full Text Available With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL combined with Hypothesize and Test (HAT. The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International

Implicit Regularization for Reconstructing 3D Building Rooftop Models Using Airborne LiDAR Data.

Science.gov (United States)

Jung, Jaewook; Jwa, Yoonseok; Sohn, Gunho

2017-03-19

With rapid urbanization, highly accurate and semantically rich virtualization of building assets in 3D become more critical for supporting various applications, including urban planning, emergency response and location-based services. Many research efforts have been conducted to automatically reconstruct building models at city-scale from remotely sensed data. However, developing a fully-automated photogrammetric computer vision system enabling the massive generation of highly accurate building models still remains a challenging task. One the most challenging task for 3D building model reconstruction is to regularize the noises introduced in the boundary of building object retrieved from a raw data with lack of knowledge on its true shape. This paper proposes a data-driven modeling approach to reconstruct 3D rooftop models at city-scale from airborne laser scanning (ALS) data. The focus of the proposed method is to implicitly derive the shape regularity of 3D building rooftops from given noisy information of building boundary in a progressive manner. This study covers a full chain of 3D building modeling from low level processing to realistic 3D building rooftop modeling. In the element clustering step, building-labeled point clouds are clustered into homogeneous groups by applying height similarity and plane similarity. Based on segmented clusters, linear modeling cues including outer boundaries, intersection lines, and step lines are extracted. Topology elements among the modeling cues are recovered by the Binary Space Partitioning (BSP) technique. The regularity of the building rooftop model is achieved by an implicit regularization process in the framework of Minimum Description Length (MDL) combined with Hypothesize and Test (HAT). The parameters governing the MDL optimization are automatically estimated based on Min-Max optimization and Entropy-based weighting method. The performance of the proposed method is tested over the International Society for

Dimensional regularization and analytical continuation at finite temperature

International Nuclear Information System (INIS)

Chen Xiangjun; Liu Lianshou

1998-01-01

The relationship between dimensional regularization and analytical continuation of infrared divergent integrals at finite temperature is discussed and a method of regularization of infrared divergent integrals and infrared divergent sums is given

Galvanic Vestibular Stimulation in Hemi-Spatial Neglect

Directory of Open Access Journals (Sweden)

David eWilkinson

2014-01-01

Full Text Available Hemi-spatial neglect is an attentional disorder in which the sufferer fails to acknowledge or respond to stimuli appearing in contralesional space. In recent years, it has become clear that a measurable reduction in contralesional neglect can occur during galvanic vestibular stimulation, a technique by which transmastoid, small amplitude current induces lateral, attentional shifts via asymmetric modulation of the left and right vestibular nerves. However, it remains unclear whether this reduction persists after stimulation is stopped. To estimate longevity of effect, we therefore conducted a double-blind, randomized, dose-response trial involving a group of stroke patients suffering from left-sided neglect (n=52, mean age=66 years. To determine whether repeated sessions of galvanic vestibular stimulation more effectively induce lasting relief than a single session, participants received 1, 5, or 10 sessions, each lasting 25mins, of sub-sensory, left-anodal right-cathodal noisy direct current (mean amplitude=1mA. Ninety five percent confidence intervals indicated that all three treatment arms showed a statistically significant improvement between the pre-stimulation baseline and the final day of stimulation on the primary outcome measure, the conventional tests of the Behavioural Inattention Test. More remarkably, this change (mean change=28%, SD=18 was still evident 1month later. Secondary analyses indicated an allied increase of 20% in median Barthel Index score, a measure of functional capacity, in the absence of any adverse events or instances of participant non-compliance. Together these data suggest that galvanic vestibular stimulation, a simple, cheap technique suitable for home-based administration, may produce lasting reductions in neglect that are clinically important. Further protocol optimization is now needed ahead of a larger effectiveness study.

Burst stimulation improves hemodynamics during resuscitation after prolonged ventricular fibrillation.

Science.gov (United States)

Walcott, Gregory; Melnick, Sharon; Killingsworth, Cheryl; Ideker, Raymond

2009-02-01

Although return of spontaneous circulation (ROSC) is frequently achieved during resuscitation for sudden cardiac arrest, systolic blood pressure can then decrease, requiring additional myocardial support. Previous studies have shown that a series of 1-ms electrical pulses delivered through the defibrillation patches during ventricular fibrillation (VF) can stimulate the autonomic nervous system to increase myocardial function following defibrillation. We hypothesized that a similar series of electrical pulses could increase myocardial function and blood pressure during the early post-resuscitation period. Six swine were studied that underwent 6-7 min. Each animal received 5, 10, 15, or 20 pulse packets consisting of 6 10 A, 1-ms pulses every 3-4 s in random order whenever systolic blood pressure became less than 50 mmHg. All four sets of pulse packets were delivered to each animal. Systolic blood pressure and cardiac function (left ventricular +dP/dt) were increased to pre-stimulation levels or above by all four sets of pulse packets. The increases were significantly greater for the longer than the shorter number of pulse packets. The mean+/-SD duration of the time that the systolic pressure remained above 50 mmHg following pulse delivery was 4.2+/-2.5 min. Electrical stimulation during regular rhythm following prolonged VF and resuscitation can increase blood pressure and cardiac function to above prestimulation levels.

Space Life Sciences Research and Education Program

Science.gov (United States)

Coats, Alfred C.

2001-01-01

Since 1969, the Universities Space Research Association (USRA), a private, nonprofit corporation, has worked closely with the National Aeronautics and Space Administration (NASA) to advance space science and technology and to promote education in those areas. USRA's Division of Space Life Sciences (DSLS) has been NASA's life sciences research partner for the past 18 years. For the last six years, our Cooperative Agreement NCC9-41 for the 'Space Life Sciences Research and Education Program' has stimulated and assisted life sciences research and education at NASA's Johnson Space Center (JSC) - both at the Center and in collaboration with outside academic institutions. To accomplish our objectives, the DSLS has facilitated extramural research, developed and managed educational programs, recruited and employed visiting and staff scientists, and managed scientific meetings.

Regular and conformal regular cores for static and rotating solutions

Energy Technology Data Exchange (ETDEWEB)

Azreg-Aïnou, Mustapha

2014-03-07

Using a new metric for generating rotating solutions, we derive in a general fashion the solution of an imperfect fluid and that of its conformal homolog. We discuss the conditions that the stress–energy tensors and invariant scalars be regular. On classical physical grounds, it is stressed that conformal fluids used as cores for static or rotating solutions are exempt from any malicious behavior in that they are finite and defined everywhere.

Regular and conformal regular cores for static and rotating solutions

International Nuclear Information System (INIS)

Azreg-Aïnou, Mustapha

2014-01-01

Using a new metric for generating rotating solutions, we derive in a general fashion the solution of an imperfect fluid and that of its conformal homolog. We discuss the conditions that the stress–energy tensors and invariant scalars be regular. On classical physical grounds, it is stressed that conformal fluids used as cores for static or rotating solutions are exempt from any malicious behavior in that they are finite and defined everywhere.

Flexible multichannel vagus nerve electrode for stimulation and recording for heart failure treatment.

Science.gov (United States)

Xue, Ning; Martinez, Ignacio Delgado; Sun, Jianhai; Cheng, Yuhua; Liu, Chunxiu

2018-07-30

Vagus nerve stimulation is an emerging bioelectronic medicine to modulate cardiac function, as the nerve provides parasympathetic innervation to the heart. In this study, we developed a polyimide based 2D cuff electrode to wrap around on the vagus nerve. Thanks to the tiny size and bendable protruding structure of the contact tips of the device, the electrode sites are able to flexibly bend to touch the nerve, selectively record and stimulate the vagus nerve. Gold, platinum and platinum black materials were chosen to compose the electrodes for nerve stimulation and recording, respectively. Since the platinum black has ~30 times larger charge delivery capacity (CDC) than gold, Pt black electrode is used for nerve stimulation. The electrochemical impedance spectroscopy and cyclic voltammetry measurement of the three materials were conducted in vitro, revealing the results of 405 kΩ, 41 kΩ, 10.5 kΩ, @1 kHz and 0.81 mC/cm 2 , 4.26 mC/cm 2 , 25.5 mC/cm 2 , respectively (n = 3). The cuff electrodes were implanted into the right-sided vagus nerve of rats for in vivo experiment. Biphasic current configuration was implemented for nerve stimulation with frequency of 10 Hz, pulse during of 300 μs and various currents stimulus. The result shows the heart beat frequency drops up to 36% during the stimulation and was able to return the regular frequency as stimulation was removed. Subsequently, the vagus nerve signals were recorded with the four channel cuff electrodes. The magnitude of the compound nerve action potentials (CNAPs) is ~10 μV and the signal to noise ratio (SNR) is ~20. Copyright © 2018 Elsevier B.V. All rights reserved.

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

Studies on gene expressions analyses for Arabidopsis thaliana plants stimulated by space flight condition

Science.gov (United States)

Lu, Jinying; Liu, Min; Pan, Yi; Li, Huasheng

We carried out whole-genome microarray to screen the transcript profile of Arabidopsis thaliana seedlings after three treatment: space microgravity condition( Seedlings grown in microgravity state of space flight of SIMBOX on Shenzhou-8), 1g centrifugal force in space(Seedlings grown in 1g centrifugal force state of space flight of SIMBOX on Shenzhou-8) and ground control. The result of microarray analysis is as followed: There were 368 genes significantly differentially expressed in space microgravity condition compared with that in 1g centrifuge space condition. Space radiation caused 246 genes significantly differentially expressed between seedlings in 1g centrifuge space condition and ground control. Space conditions (including microgravity and radiation) caused 621 genes significantly differentially expressed between seedlings in space microgravity condition and ground control. Microgravity and radiation as a single factor can cause plant gene expression change, but two factors synergism can produce some new effects on plant gene expression. The function of differential expression genes were analyst by bioinformatics, and we found the expression of genes related with stress were more different, such as the dehydration of protein (dehydrin Xero2) expression is up-regulated 57 times; low-temperature-induced protein expression is up-regulated in 49 times; heat shock protein expression is up-regulated 20 times; transcription factor DREB2A expression increase 25 times; protein phosphatase 2C expression is up-regulated 14 times; transcription factor NAM-like protein expression is up-regulated 13 times; cell wall metabolism related genes (xyloglucan, endo-1, 4-beta-D-glucanase) expression is down-regulated in 15 times. The results provide scientific data for the mechanism of space mutation.

Regular-fat dairy and human health

DEFF Research Database (Denmark)

Astrup, Arne; Bradley, Beth H Rice; Brenna, J Thomas

2016-01-01

In recent history, some dietary recommendations have treated dairy fat as an unnecessary source of calories and saturated fat in the human diet. These assumptions, however, have recently been brought into question by current research on regular fat dairy products and human health. In an effort to......, cheese and yogurt, can be important components of an overall healthy dietary pattern. Systematic examination of the effects of dietary patterns that include regular-fat milk, cheese and yogurt on human health is warranted....

Bounded Perturbation Regularization for Linear Least Squares Estimation

KAUST Repository

Ballal, Tarig; Suliman, Mohamed Abdalla Elhag; Al-Naffouri, Tareq Y.

2017-01-01

This paper addresses the problem of selecting the regularization parameter for linear least-squares estimation. We propose a new technique called bounded perturbation regularization (BPR). In the proposed BPR method, a perturbation with a bounded

Beneficial effects of multisensory and cognitive stimulation on age-related cognitive decline in long-term-care institutions

Science.gov (United States)

De Oliveira, Thaís Cristina Galdino; Soares, Fernanda Cabral; De Macedo, Liliane Dias E Dias; Diniz, Domingos Luiz Wanderley Picanço; Bento-Torres, Natáli Valim Oliver; Picanço-Diniz, Cristovam Wanderley

2014-01-01

The aim of the present report was to evaluate the effectiveness and impact of multisensory and cognitive stimulation on improving cognition in elderly persons living in long-term-care institutions (institutionalized [I]) or in communities with their families (noninstitutionalized [NI]). We compared neuropsychological performance using language and Mini-Mental State Examination (MMSE) test scores before and after 24 and 48 stimulation sessions. The two groups were matched by age and years of schooling. Small groups of ten or fewer volunteers underwent the stimulation program, twice a week, over 6 months (48 sessions in total). Sessions were based on language and memory exercises, as well as visual, olfactory, auditory, and ludic stimulation, including music, singing, and dance. Both groups were assessed at the beginning (before stimulation), in the middle (after 24 sessions), and at the end (after 48 sessions) of the stimulation program. Although the NI group showed higher performance in all tasks in all time windows compared with I subjects, both groups improved their performance after stimulation. In addition, the improvement was significantly higher in the I group than the NI group. Language tests seem to be more efficient than the MMSE to detect early changes in cognitive status. The results suggest the impoverished environment of long-term-care institutions may contribute to lower cognitive scores before stimulation and the higher improvement rate of this group after stimulation. In conclusion, language tests should be routinely adopted in the neuropsychological assessment of elderly subjects, and long-term-care institutions need to include regular sensorimotor, social, and cognitive stimulation as a public health policy for elderly persons. PMID:24600211

Beneficial effects of multisensory and cognitive stimulation on age-related cognitive decline in long-term-care institutions.

Science.gov (United States)

De Oliveira, Thaís Cristina Galdino; Soares, Fernanda Cabral; De Macedo, Liliane Dias E Dias; Diniz, Domingos Luiz Wanderley Picanço; Bento-Torres, Natáli Valim Oliver; Picanço-Diniz, Cristovam Wanderley

2014-01-01

The aim of the present report was to evaluate the effectiveness and impact of multisensory and cognitive stimulation on improving cognition in elderly persons living in long-term-care institutions (institutionalized [I]) or in communities with their families (noninstitutionalized [NI]). We compared neuropsychological performance using language and Mini-Mental State Examination (MMSE) test scores before and after 24 and 48 stimulation sessions. The two groups were matched by age and years of schooling. Small groups of ten or fewer volunteers underwent the stimulation program, twice a week, over 6 months (48 sessions in total). Sessions were based on language and memory exercises, as well as visual, olfactory, auditory, and ludic stimulation, including music, singing, and dance. Both groups were assessed at the beginning (before stimulation), in the middle (after 24 sessions), and at the end (after 48 sessions) of the stimulation program. Although the NI group showed higher performance in all tasks in all time windows compared with I subjects, both groups improved their performance after stimulation. In addition, the improvement was significantly higher in the I group than the NI group. Language tests seem to be more efficient than the MMSE to detect early changes in cognitive status. The results suggest the impoverished environment of long-term-care institutions may contribute to lower cognitive scores before stimulation and the higher improvement rate of this group after stimulation. In conclusion, language tests should be routinely adopted in the neuropsychological assessment of elderly subjects, and long-term-care institutions need to include regular sensorimotor, social, and cognitive stimulation as a public health policy for elderly persons.

Clustering, randomness, and regularity in cloud fields: 2. Cumulus cloud fields

Science.gov (United States)

Zhu, T.; Lee, J.; Weger, R. C.; Welch, R. M.

1992-12-01

During the last decade a major controversy has been brewing concerning the proper characterization of cumulus convection. The prevailing view has been that cumulus clouds form in clusters, in which cloud spacing is closer than that found for the overall cloud field and which maintains its identity over many cloud lifetimes. This "mutual protection hypothesis" of Randall and Huffman (1980) has been challenged by the "inhibition hypothesis" of Ramirez et al. (1990) which strongly suggests that the spatial distribution of cumuli must tend toward a regular distribution. A dilemma has resulted because observations have been reported to support both hypotheses. The present work reports a detailed analysis of cumulus cloud field spatial distributions based upon Landsat, Advanced Very High Resolution Radiometer, and Skylab data. Both nearest-neighbor and point-to-cloud cumulative distribution function statistics are investigated. The results show unequivocally that when both large and small clouds are included in the cloud field distribution, the cloud field always has a strong clustering signal. The strength of clustering is largest at cloud diameters of about 200-300 m, diminishing with increasing cloud diameter. In many cases, clusters of small clouds are found which are not closely associated with large clouds. As the small clouds are eliminated from consideration, the cloud field typically tends towards regularity. Thus it would appear that the "inhibition hypothesis" of Ramirez and Bras (1990) has been verified for the large clouds. However, these results are based upon the analysis of point processes. A more exact analysis also is made which takes into account the cloud size distributions. Since distinct clouds are by definition nonoverlapping, cloud size effects place a restriction upon the possible locations of clouds in the cloud field. The net effect of this analysis is that the large clouds appear to be randomly distributed, with only weak tendencies towards

International Conference on Function Spaces and Inequalities

CERN Document Server

Schmeisser, Hans-Jürgen

2017-01-01

This book features original research and survey articles on the topics of function spaces and inequalities. It focuses on (variable/grand/small) Lebesgue spaces, Orlicz spaces, Lorentz spaces, and Morrey spaces and deals with mapping properties of operators, (weighted) inequalities, pointwise multipliers and interpolation. Moreover, it considers Sobolev–Besov and Triebel–Lizorkin type smoothness spaces. The book includes papers by leading international researchers, presented at the International Conference on Function Spaces and Inequalities, held at the South Asian University, New Delhi, India, on 11–15 December 2015, which focused on recent developments in the theory of spaces with variable exponents. It also offers further investigations concerning Sobolev-type embeddings, discrete inequalities and harmonic analysis. Each chapter is dedicated to a specific topic and written by leading experts, providing an overview of the subject and stimulating future research.

Investigating Irregularly Patterned Deep Brain Stimulation Signal Design Using Biophysical Models

Directory of Open Access Journals (Sweden)

Samantha Rose Summerson

2015-06-01

Full Text Available Parkinson’s disease (PD is a neurodegenerative disorder which follows from cell loss of dopaminergic neurons in the substantia nigra pars compacta (SNc, a nucleus in the basal ganglia (BG. Deep brain stimulation (DBS is an electrical therapy that modulates the pathological activity to treat the motor symptoms of PD. Although this therapy is currently used in clinical practice, the sufficient conditions for therapeutic efficacy are unknown. In this work we develop a model of critical motor circuit structures in the brain using biophysical cell models as the base components and then evaluate performance of different DBS signals in this model to perform comparative studies of their efficacy. Biological models are an important tool for gaining insights into neural function and, in this case, serve as effective tools for investigating innovative new DBS paradigms. Experiments were performed using the hemi-parkinsonian rodent model to test the same set of signals, verifying the obedience of the model to physiological trends. We show that antidromic spiking from DBS of the subthalamic nucleus (STN has a significant impact on cortical neural activity, which is frequency dependent and additionally modulated by the regularity of the stimulus pulse train used. Irregular spacing between stimulus pulses, where the amount of variability added is bounded, is shown to increase diversification of response of basal ganglia neurons and reduce entropic noise in cortical neurons, which may be fundamentally important to restoration of information flow in the motor circuit.

Recognition Memory for Novel Stimuli: The Structural Regularity Hypothesis

Science.gov (United States)

Cleary, Anne M.; Morris, Alison L.; Langley, Moses M.

2007-01-01

Early studies of human memory suggest that adherence to a known structural regularity (e.g., orthographic regularity) benefits memory for an otherwise novel stimulus (e.g., G. A. Miller, 1958). However, a more recent study suggests that structural regularity can lead to an increase in false-positive responses on recognition memory tests (B. W. A.…

Brain Stimulation Therapies

Science.gov (United States)

... Magnetic Seizure Therapy Deep Brain Stimulation Additional Resources Brain Stimulation Therapies Overview Brain stimulation therapies can play ... for a shorter recovery time than ECT Deep Brain Stimulation Deep brain stimulation (DBS) was first developed ...

Disturbances in lipid second messengers generation by stimulated blood lymphocytes in breast cancer

Directory of Open Access Journals (Sweden)

Galstyan H. M.

2011-10-01

Full Text Available Aim. The main objective of this study was the comparative investigation of diverse lipid second messenger (LSM generation by human peripheral blood lymphocytes (HPBL at different (5, 10, 30 and 60 s time points of cell co-stimulation by anti-CD3 and anti-CD28 monoclonal antibodies in norm and breast cancer (BC. Methods. Ficoll-Hypaque gradient centrifugation. Results. The data obtained indicate that some mechanisms of LSM generation/utilization in stimulated crude HPBL were significantly altered in BC compared to norm. Particularly, the reliable generation of arachidonyl-1,2-diacylglycerol (1,2-DAG at the initial step (5 s of cell stimulation observed in norm was depressed in BC and reached the value below the basal level in unstimulated cells. It is important that the disturbances in 1,2-DAG formation in HPBL obtained from patients with BC were identical with those observed earlier in other forms of cancer. Conclusions. We conclude that the regularities revealed are common characteristics for all the types of malignancy studied and can be used as additional testing parameters for cancer definition and individual correction of the chemotherapy programs for disease treatment

Regularization Techniques for Linear Least-Squares Problems

KAUST Repository

Suliman, Mohamed

2016-04-01

Linear estimation is a fundamental branch of signal processing that deals with estimating the values of parameters from a corrupted measured data. Throughout the years, several optimization criteria have been used to achieve this task. The most astonishing attempt among theses is the linear least-squares. Although this criterion enjoyed a wide popularity in many areas due to its attractive properties, it appeared to suffer from some shortcomings. Alternative optimization criteria, as a result, have been proposed. These new criteria allowed, in one way or another, the incorporation of further prior information to the desired problem. Among theses alternative criteria is the regularized least-squares (RLS). In this thesis, we propose two new algorithms to find the regularization parameter for linear least-squares problems. In the constrained perturbation regularization algorithm (COPRA) for random matrices and COPRA for linear discrete ill-posed problems, an artificial perturbation matrix with a bounded norm is forced into the model matrix. This perturbation is introduced to enhance the singular value structure of the matrix. As a result, the new modified model is expected to provide a better stabilize substantial solution when used to estimate the original signal through minimizing the worst-case residual error function. Unlike many other regularization algorithms that go in search of minimizing the estimated data error, the two new proposed algorithms are developed mainly to select the artifcial perturbation bound and the regularization parameter in a way that approximately minimizes the mean-squared error (MSE) between the original signal and its estimate under various conditions. The first proposed COPRA method is developed mainly to estimate the regularization parameter when the measurement matrix is complex Gaussian, with centered unit variance (standard), and independent and identically distributed (i.i.d.) entries. Furthermore, the second proposed COPRA

Regularized Regression and Density Estimation based on Optimal Transport

KAUST Repository

Burger, M.

2012-03-11

The aim of this paper is to investigate a novel nonparametric approach for estimating and smoothing density functions as well as probability densities from discrete samples based on a variational regularization method with the Wasserstein metric as a data fidelity. The approach allows a unified treatment of discrete and continuous probability measures and is hence attractive for various tasks. In particular, the variational model for special regularization functionals yields a natural method for estimating densities and for preserving edges in the case of total variation regularization. In order to compute solutions of the variational problems, a regularized optimal transport problem needs to be solved, for which we discuss several formulations and provide a detailed analysis. Moreover, we compute special self-similar solutions for standard regularization functionals and we discuss several computational approaches and results. © 2012 The Author(s).

The Analysis of Two-Way Functional Data Using Two-Way Regularized Singular Value Decompositions

KAUST Repository

Huang, Jianhua Z.

2009-12-01

Two-way functional data consist of a data matrix whose row and column domains are both structured, for example, temporally or spatially, as when the data are time series collected at different locations in space. We extend one-way functional principal component analysis (PCA) to two-way functional data by introducing regularization of both left and right singular vectors in the singular value decomposition (SVD) of the data matrix. We focus on a penalization approach and solve the nontrivial problem of constructing proper two-way penalties from oneway regression penalties. We introduce conditional cross-validated smoothing parameter selection whereby left-singular vectors are cross- validated conditional on right-singular vectors, and vice versa. The concept can be realized as part of an alternating optimization algorithm. In addition to the penalization approach, we briefly consider two-way regularization with basis expansion. The proposed methods are illustrated with one simulated and two real data examples. Supplemental materials available online show that several "natural" approaches to penalized SVDs are flawed and explain why so. © 2009 American Statistical Association.

Energy functions for regularization algorithms

Science.gov (United States)

Delingette, H.; Hebert, M.; Ikeuchi, K.

1991-01-01

Regularization techniques are widely used for inverse problem solving in computer vision such as surface reconstruction, edge detection, or optical flow estimation. Energy functions used for regularization algorithms measure how smooth a curve or surface is, and to render acceptable solutions these energies must verify certain properties such as invariance with Euclidean transformations or invariance with parameterization. The notion of smoothness energy is extended here to the notion of a differential stabilizer, and it is shown that to void the systematic underestimation of undercurvature for planar curve fitting, it is necessary that circles be the curves of maximum smoothness. A set of stabilizers is proposed that meet this condition as well as invariance with rotation and parameterization.

Computationally Developed Sham Stimulation Protocol for Multichannel Desynchronizing Stimulation

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Magteld Zeitler

2018-05-01

Full Text Available A characteristic pattern of abnormal brain activity is abnormally strong neuronal synchronization, as found in several brain disorders, such as tinnitus, Parkinson's disease, and epilepsy. As observed in several diseases, different therapeutic interventions may induce a placebo effect that may be strong and hinder reliable clinical evaluations. Hence, to distinguish between specific, neuromodulation-induced effects and unspecific, placebo effects, it is important to mimic the therapeutic procedure as precisely as possibly, thereby providing controls that actually lack specific effects. Coordinated Reset (CR stimulation has been developed to specifically counteract abnormally strong synchronization by desynchronization. CR is a spatio-temporally patterned multichannel stimulation which reduces the extent of coincident neuronal activity and aims at an anti-kindling, i.e., an unlearning of both synaptic connectivity and neuronal synchrony. Apart from acute desynchronizing effects, CR may cause sustained, long-lasting desynchronizing effects, as already demonstrated in pre-clinical and clinical proof of concept studies. In this computational study, we set out to computationally develop a sham stimulation protocol for multichannel desynchronizing stimulation. To this end, we compare acute effects and long-lasting effects of six different spatio-temporally patterned stimulation protocols, including three variants of CR, using a no-stimulation condition as additional control. This is to provide an inventory of different stimulation algorithms with similar fundamental stimulation parameters (e.g., mean stimulation rates but qualitatively different acute and/or long-lasting effects. Stimulation protocols sharing basic parameters, but inducing nevertheless completely different or even no acute effects and/or after-effects, might serve as controls to validate the specific effects of particular desynchronizing protocols such as CR. In particular, based on

Three regularities of recognition memory: the role of bias.

Science.gov (United States)

Hilford, Andrew; Maloney, Laurence T; Glanzer, Murray; Kim, Kisok

2015-12-01

A basic assumption of Signal Detection Theory is that decisions are made on the basis of likelihood ratios. In a preceding paper, Glanzer, Hilford, and Maloney (Psychonomic Bulletin & Review, 16, 431-455, 2009) showed that the likelihood ratio assumption implies that three regularities will occur in recognition memory: (1) the Mirror Effect, (2) the Variance Effect, (3) the normalized Receiver Operating Characteristic (z-ROC) Length Effect. The paper offered formal proofs and computational demonstrations that decisions based on likelihood ratios produce the three regularities. A survey of data based on group ROCs from 36 studies validated the likelihood ratio assumption by showing that its three implied regularities are ubiquitous. The study noted, however, that bias, another basic factor in Signal Detection Theory, can obscure the Mirror Effect. In this paper we examine how bias affects the regularities at the theoretical level. The theoretical analysis shows: (1) how bias obscures the Mirror Effect, not the other two regularities, and (2) four ways to counter that obscuring. We then report the results of five experiments that support the theoretical analysis. The analyses and the experimental results also demonstrate: (1) that the three regularities govern individual, as well as group, performance, (2) alternative explanations of the regularities are ruled out, and (3) that Signal Detection Theory, correctly applied, gives a simple and unified explanation of recognition memory data.

14 CFR 125.39 - Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. 125.39 Section 125.39 Aeronautics and Space FEDERAL AVIATION... AIRCRAFT Certification Rules and Miscellaneous Requirements § 125.39 Carriage of narcotic drugs, marihuana...

Stimulation of the peripheral nervous system for pain control.

Science.gov (United States)

Long, D M

1983-01-01

Transcutaneous stimulation is a proven effective way to relieve pain. Its optimal use requires an accurate patient diagnosis. Treatment of pain as a symptom only is likely to fail. There must be a careful psychosocial evaluation, for the majority of patients who come to the doctor complaining of pain have major psychological, social, or behavioral factors that are most important in the genesis of the complaint. Drug abuse must be corrected. Related symptoms, such as anxiety and depression, must be treated. Then, a thorough trail of transcutaneous stimulation is mandatory. A desultory use will undoubtedly lead to failure. This trial must begin with patient education by experienced personnel. Then the electrodes must be properly applied, and there must be a regular follow-up of stimulation to be certain the patient is utilizing it correctly. The patient must be supported through an adequate trial which should extend over 2-4 weeks before purchase of the device is contemplated. Furthermore, all related nursing and physician personnel must be educated in the proper use of the technique. The uninformed professional who denigrates the therapy is a very effective deterrent to appropriate use. In this situation, transcutaneous electrical stimulation will be of great value in the treatment of acute musculoskeletal injury and acute postoperative pain. It will be effective in the treatment of peripheral nerve injury pain, chronic musculoskeletal abnormalities, chronic pain in the patient who has undergone multiple operations upon the low back and neck, visceral pain, some of the reflex sympathetic dystrophies, and postherpetic neuralgia. Stimulation will not help a complaint which is psychosomatic in origin. It will not influence drug addiction. It is not likely to be useful in any situation where secondary gain is important. The metabolic neuropathies, pain of spinal cord injury, and pain from cerebrovascular accident will not respond frequently enough to warrant more than

Mechanisms of magnetic stimulation of central nervous system neurons.

Directory of Open Access Journals (Sweden)

Tamar Pashut

2011-03-01

Full Text Available Transcranial magnetic stimulation (TMS is a stimulation method in which a magnetic coil generates a magnetic field in an area of interest in the brain. This magnetic field induces an electric field that modulates neuronal activity. The spatial distribution of the induced electric field is determined by the geometry and location of the coil relative to the brain. Although TMS has been used for several decades, the biophysical basis underlying the stimulation of neurons in the central nervous system (CNS is still unknown. To address this problem we developed a numerical scheme enabling us to combine realistic magnetic stimulation (MS with compartmental modeling of neurons with arbitrary morphology. The induced electric field for each location in space was combined with standard compartmental modeling software to calculate the membrane current generated by the electromagnetic field for each segment of the neuron. In agreement with previous studies, the simulations suggested that peripheral axons were excited by the spatial gradients of the induced electric field. In both peripheral and central neurons, MS amplitude required for action potential generation was inversely proportional to the square of the diameter of the stimulated compartment. Due to the importance of the fiber's diameter, magnetic stimulation of CNS neurons depolarized the soma followed by initiation of an action potential in the initial segment of the axon. Passive dendrites affect this process primarily as current sinks, not sources. The simulations predict that neurons with low current threshold are more susceptible to magnetic stimulation. Moreover, they suggest that MS does not directly trigger dendritic regenerative mechanisms. These insights into the mechanism of MS may be relevant for the design of multi-intensity TMS protocols, may facilitate the construction of magnetic stimulators, and may aid the interpretation of results of TMS of the CNS.

Mechanisms of magnetic stimulation of central nervous system neurons.

Science.gov (United States)

Pashut, Tamar; Wolfus, Shuki; Friedman, Alex; Lavidor, Michal; Bar-Gad, Izhar; Yeshurun, Yosef; Korngreen, Alon

2011-03-01

Transcranial magnetic stimulation (TMS) is a stimulation method in which a magnetic coil generates a magnetic field in an area of interest in the brain. This magnetic field induces an electric field that modulates neuronal activity. The spatial distribution of the induced electric field is determined by the geometry and location of the coil relative to the brain. Although TMS has been used for several decades, the biophysical basis underlying the stimulation of neurons in the central nervous system (CNS) is still unknown. To address this problem we developed a numerical scheme enabling us to combine realistic magnetic stimulation (MS) with compartmental modeling of neurons with arbitrary morphology. The induced electric field for each location in space was combined with standard compartmental modeling software to calculate the membrane current generated by the electromagnetic field for each segment of the neuron. In agreement with previous studies, the simulations suggested that peripheral axons were excited by the spatial gradients of the induced electric field. In both peripheral and central neurons, MS amplitude required for action potential generation was inversely proportional to the square of the diameter of the stimulated compartment. Due to the importance of the fiber's diameter, magnetic stimulation of CNS neurons depolarized the soma followed by initiation of an action potential in the initial segment of the axon. Passive dendrites affect this process primarily as current sinks, not sources. The simulations predict that neurons with low current threshold are more susceptible to magnetic stimulation. Moreover, they suggest that MS does not directly trigger dendritic regenerative mechanisms. These insights into the mechanism of MS may be relevant for the design of multi-intensity TMS protocols, may facilitate the construction of magnetic stimulators, and may aid the interpretation of results of TMS of the CNS.

Hydrogen atom in the phase-space formulation of quantum mechanics

International Nuclear Information System (INIS)

Gracia-Bondia, J.M.

1984-01-01

Using a coordinate transformation which regularizes the classical Kepler problem, we show that the hydrogen-atom case may be analytically solved via the phase-space formulation of nonrelativistic quantum mechanics. The problem is essentially reduced to that of a four-dimensional oscillator whose treatment in the phase-space formulation is developed. Furthermore, the method allows us to calculate the Green's function for the H atom in a surprisingly simple way

Method of transferring regular shaped vessel into cell

International Nuclear Information System (INIS)

Murai, Tsunehiko.

1997-01-01

The present invention concerns a method of transferring regular shaped vessels from a non-contaminated area to a contaminated cell. A passage hole for allowing the regular shaped vessels to pass in the longitudinal direction is formed to a partitioning wall at the bottom of the contaminated cell. A plurality of regular shaped vessel are stacked in multiple stages in a vertical direction from the non-contaminated area present below the passage hole, allowed to pass while being urged and transferred successively into the contaminated cell. As a result, since they are transferred while substantially closing the passage hole by the regular shaped vessels, radiation rays or contaminated materials are prevented from discharging from the contaminated cell to the non-contaminated area. Since there is no requirement to open/close an isolation door frequently, the workability upon transfer can be improved remarkably. In addition, the sealing member for sealing the gap between the regular shaped vessel passing through the passage hole and the partitioning wall of the bottom is disposed to the passage hole, the contaminated materials in the contaminated cells can be prevented from discharging from the gap to the non-contaminated area. (N.H.)

Automatic Constraint Detection for 2D Layout Regularization.

Science.gov (United States)

Jiang, Haiyong; Nan, Liangliang; Yan, Dong-Ming; Dong, Weiming; Zhang, Xiaopeng; Wonka, Peter

2016-08-01

In this paper, we address the problem of constraint detection for layout regularization. The layout we consider is a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important in digitizing plans or images, such as floor plans and facade images, and in the improvement of user-created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm that automatically detects constraints. We evaluate the proposed framework using a variety of input layouts from different applications. Our results demonstrate that our method has superior performance to the state of the art.

Automatic Constraint Detection for 2D Layout Regularization

KAUST Repository

Jiang, Haiyong

2015-09-18

In this paper, we address the problem of constraint detection for layout regularization. As layout we consider a set of two-dimensional elements where each element is represented by its bounding box. Layout regularization is important for digitizing plans or images, such as floor plans and facade images, and for the improvement of user created contents, such as architectural drawings and slide layouts. To regularize a layout, we aim to improve the input by detecting and subsequently enforcing alignment, size, and distance constraints between layout elements. Similar to previous work, we formulate the layout regularization as a quadratic programming problem. In addition, we propose a novel optimization algorithm to automatically detect constraints. In our results, we evaluate the proposed framework on a variety of input layouts from different applications, which demonstrates our method has superior performance to the state of the art.

Online Manifold Regularization by Dual Ascending Procedure

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Boliang Sun

2013-01-01

Full Text Available We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approaches. An important conclusion is that our online MR algorithms can handle the settings where the target hypothesis is not fixed but drifts with the sequence of examples. We also recap and draw connections to earlier works. This paper paves a way to the design and analysis of online manifold regularization algorithms.

Parameter identification in ODE models with oscillatory dynamics: a Fourier regularization approach

Science.gov (United States)

Chiara D'Autilia, Maria; Sgura, Ivonne; Bozzini, Benedetto

2017-12-01

In this paper we consider a parameter identification problem (PIP) for data oscillating in time, that can be described in terms of the dynamics of some ordinary differential equation (ODE) model, resulting in an optimization problem constrained by the ODEs. In problems with this type of data structure, simple application of the direct method of control theory (discretize-then-optimize) yields a least-squares cost function exhibiting multiple ‘low’ minima. Since in this situation any optimization algorithm is liable to fail in the approximation of a good solution, here we propose a Fourier regularization approach that is able to identify an iso-frequency manifold {{ S}} of codimension-one in the parameter space \

Alternation of regular and chaotic dynamics in a simple two-degree-of-freedom system with nonlinear inertial coupling.

Science.gov (United States)

Sigalov, G; Gendelman, O V; AL-Shudeifat, M A; Manevitch, L I; Vakakis, A F; Bergman, L A

2012-03-01

We show that nonlinear inertial coupling between a linear oscillator and an eccentric rotator can lead to very interesting interchanges between regular and chaotic dynamical behavior. Indeed, we show that this model demonstrates rather unusual behavior from the viewpoint of nonlinear dynamics. Specifically, at a discrete set of values of the total energy, the Hamiltonian system exhibits non-conventional nonlinear normal modes, whose shape is determined by phase locking of rotatory and oscillatory motions of the rotator at integer ratios of characteristic frequencies. Considering the weakly damped system, resonance capture of the dynamics into the vicinity of these modes brings about regular motion of the system. For energy levels far from these discrete values, the motion of the system is chaotic. Thus, the succession of resonance captures and escapes by a discrete set of the normal modes causes a sequence of transitions between regular and chaotic behavior, provided that the damping is sufficiently small. We begin from the Hamiltonian system and present a series of Poincaré sections manifesting the complex structure of the phase space of the considered system with inertial nonlinear coupling. Then an approximate analytical description is presented for the non-conventional nonlinear normal modes. We confirm the analytical results by numerical simulation and demonstrate the alternate transitions between regular and chaotic dynamics mentioned above. The origin of the chaotic behavior is also discussed.

Limit Formulae and Jump Relations of Potential Theory in Sobolev Spaces

OpenAIRE

Raskop, Thomas; Grothaus, Martin

2009-01-01

In this article we combine the modern theory of Sobolev spaces with the classical theory of limit formulae and jump relations of potential theory. Also other authors proved the convergence in Lebesgue spaces for integrable functions. The achievement of this paper is the L2 convergence for the weak derivatives of higher orders. Also the layer functions F are elements of Sobolev spaces and a two dimensional suitable smooth submanifold in R3, called regular Cm-surface. We are considering the pot...

Regularized principal covariates regression and its application to finding coupled patterns in climate fields

Science.gov (United States)

Fischer, M. J.

2014-02-01

There are many different methods for investigating the coupling between two climate fields, which are all based on the multivariate regression model. Each different method of solving the multivariate model has its own attractive characteristics, but often the suitability of a particular method for a particular problem is not clear. Continuum regression methods search the solution space between the conventional methods and thus can find regression model subspaces that mix the attractive characteristics of the end-member subspaces. Principal covariates regression is a continuum regression method that is easily applied to climate fields and makes use of two end-members: principal components regression and redundancy analysis. In this study, principal covariates regression is extended to additionally span a third end-member (partial least squares or maximum covariance analysis). The new method, regularized principal covariates regression, has several attractive features including the following: it easily applies to problems in which the response field has missing values or is temporally sparse, it explores a wide range of model spaces, and it seeks a model subspace that will, for a set number of components, have a predictive skill that is the same or better than conventional regression methods. The new method is illustrated by applying it to the problem of predicting the southern Australian winter rainfall anomaly field using the regional atmospheric pressure anomaly field. Regularized principal covariates regression identifies four major coupled patterns in these two fields. The two leading patterns, which explain over half the variance in the rainfall field, are related to the subtropical ridge and features of the zonally asymmetric circulation.

Compressing the hidden variable space of a qubit

International Nuclear Information System (INIS)

Montina, Alberto

2011-01-01

In previously exhibited hidden variable models of quantum state preparation and measurement, the number of continuous hidden variables describing the actual state of single realizations is never smaller than the quantum state manifold dimension. We introduce a simple model for a qubit whose hidden variable space is one-dimensional, i.e., smaller than the two-dimensional Bloch sphere. The hidden variable probability distributions associated with quantum states satisfy reasonable criteria of regularity. Possible generalizations of this shrinking to an N-dimensional Hilbert space are discussed.

Regularities of magnetic field penetration into half-space in type-II superconductors

International Nuclear Information System (INIS)

Medvedev, Yu.V.; Krasnyuk, I.B.

2003-01-01

The equations, modeling the distributions of the magnetic field induction and current density in the half-space with an account of the exponential volt-ampere characteristics, are obtained. The velocity of the magnetization front propagation by the assigned average rate of the change by the time of the external magnetic field at the sample boundary is determined. The integral condition for the electric resistance, nonlinearly dependent on the magnetic field, by accomplishing whereof the magnetic flux penetrates into the sample with the finite velocity is indicated. The analytical representation of the equation with the exponential boundary mode, which models the change in the magnetic field at the area boundary, is pointed out [ru

14 CFR 135.41 - Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Carriage of narcotic drugs, marihuana, and depressant or stimulant drugs or substances. 135.41 Section 135.41 Aeronautics and Space FEDERAL AVIATION... PERSONS ON BOARD SUCH AIRCRAFT General § 135.41 Carriage of narcotic drugs, marihuana, and depressant or...

A Galerkin Finite Element Method for Numerical Solutions of the Modified Regularized Long Wave Equation

Directory of Open Access Journals (Sweden)

Liquan Mei

2014-01-01

Full Text Available A Galerkin method for a modified regularized long wave equation is studied using finite elements in space, the Crank-Nicolson scheme, and the Runge-Kutta scheme in time. In addition, an extrapolation technique is used to transform a nonlinear system into a linear system in order to improve the time accuracy of this method. A Fourier stability analysis for the method is shown to be marginally stable. Three invariants of motion are investigated. Numerical experiments are presented to check the theoretical study of this method.

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational ℓ1-Norm Regularization in the Derivative Domain

Science.gov (United States)

Foufoula-Georgiou, E.; Ebtehaj, A. M.; Zhang, S. Q.; Hou, A. Y.

2014-05-01

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall), and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients (called ℓ1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a data base of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case

Classical and quantum investigations of four-dimensional maps with a mixed phase space

International Nuclear Information System (INIS)

Richter, Martin

2012-01-01

Systems with more than two degrees of freedom are of fundamental importance for the understanding of problems ranging from celestial mechanics to molecules. Due to the dimensionality the classical phase-space structure of such systems is more difficult to understand than for systems with two or fewer degrees of freedom. This thesis aims for a better insight into the classical as well as the quantum mechanics of 4D mappings representing driven systems with two degrees of freedom. In order to analyze such systems, we introduce 3D sections through the 4D phase space which reveal the regular and chaotic structures. We introduce these concepts by means of three example mappings of increasing complexity. After a classical analysis the systems are investigated quantum mechanically. We focus especially on two important aspects: First, we address quantum mechanical consequences of the classical Arnold web and demonstrate how quantum mechanics can resolve this web in the semiclassical limit. Second, we investigate the quantum mechanical tunneling couplings between regular and chaotic regions in phase space. We determine regular-to-chaotic tunneling rates numerically and extend the fictitious integrable system approach to higher dimensions for their prediction. Finally, we study resonance-assisted tunneling in 4D maps.

Gene selection for microarray data classification via subspace learning and manifold regularization.

Science.gov (United States)

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

The effect of stimulation interval on plasticity following repeated blocks of intermittent theta burst stimulation.

Science.gov (United States)

Tse, Nga Yan; Goldsworthy, Mitchell R; Ridding, Michael C; Coxon, James P; Fitzgerald, Paul B; Fornito, Alex; Rogasch, Nigel C

2018-06-04

This study assessed the effect of interval duration on the direction and magnitude of changes in cortical excitability and inhibition when applying repeated blocks of intermittent theta burst stimulation (iTBS) over motor cortex. 15 participants received three different iTBS conditions on separate days: single iTBS; repeated iTBS with a 5 minute interval (iTBS-5-iTBS); and with a 15 minute interval (iTBS-15-iTBS). Changes in cortical excitability and short-interval cortical inhibition (SICI) were assessed via motor-evoked potentials (MEPs) before and up to 60 mins following stimulation. iTBS-15-iTBS increased MEP amplitude for up to 60 mins post stimulation, whereas iTBS-5-iTBS decreased MEP amplitude. In contrast, MEP amplitude was not altered by single iTBS. Despite the group level findings, only 53% of individuals showed facilitated MEPs following iTBS-15-iTBS, and only 40% inhibited MEPs following iTBS-5-iTBS. Modulation of SICI did not differ between conditions. These results suggest interval duration between spaced iTBS plays an important role in determining the direction of plasticity on excitatory, but not inhibitory circuits in human motor cortex. While repeated iTBS can increase the magnitude of MEP facilitation/inhibition in some individuals compared to single iTBS, the response to repeated iTBS appears variable between individuals in this small sample.

Optokinetic and vestibular stimulation determines the spatial orientation of negative optokinetic afternystagmus in the rabbit.

Science.gov (United States)

Pettorossi, V E; Errico, P; Ferraresi, A; Barmack, N H

1999-02-15

Prolonged binocular optokinetic stimulation (OKS) in the rabbit induces a high-velocity negative optokinetic afternystagmus (OKAN II) that persists for several hours. We have taken advantage of this uniform nystagmus to study how changes in static head orientation in the pitch plane might influence the orientation of the nystagmus. After horizontal OKS, the rotation axis of the OKAN II remained almost constant in space as it was kept aligned with the gravity vector when the head was pitched by as much as 80 degrees up and 35 degrees down. Moreover, during reorientation, slow-phase eye velocity decreased according to the head pitch angle. Thereafter, we analyzed the space orientation of OKAN II after optokinetic stimulation during which the head and/or the OKS were pitched upward and downward. The rotation axis of OKAN II did not remain aligned with an earth vertical axis nor a head vertical axis, but it tended to be aligned with that of the OKS respace. The slow-phase eye velocity of OKAN II was also affected by the head pitch angle during OKS, because maximal OKAN II velocity occurred at the same head pitch angle as that during optokinetic stimulation. We suggest that OKAN II is coded in gravity-centered rather than in head-centered coordinates, but that this coordinate system may be influenced by optokinetic and vestibular stimulation. Moreover, the velocity attenuation of OKAN II seems to depend on the mismatch between the space-centered nystagmus rotation axis orientation and that of the "remembered" head-centered optokinetic pathway activated by OKS.

Recreational stimulants, herbal, and spice cannabis: The core psychobiological processes that underlie their damaging effects.

Science.gov (United States)

Parrott, Andrew C; Hayley, Amie C; Downey, Luke A

2017-05-01

Recreational drugs are taken for their positive mood effects, yet their regular usage damages well-being. The psychobiological mechanisms underlying these damaging effects will be debated. The empirical literature on recreational cannabinoids and stimulant drugs is reviewed. A theoretical explanation for how they cause similar types of damage is outlined. All psychoactive drugs cause moods and psychological states to fluctuate. The acute mood gains underlie their recreational usage, while the mood deficits on withdrawal explain their addictiveness. Cyclical mood changes are found with every central nervous system stimulant and also occur with cannabis. These mood state changes provide a surface index for more profound psychobiological fluctuations. Homeostatic balance is altered, with repetitive disturbances of the hypothalamic-pituitary-adrenal axis, and disrupted cortisol-neurohormonal secretions. Hence, these drugs cause increased stress, disturbed sleep, neurocognitive impairments, altered brain activity, and psychiatric vulnerability. Equivalent deficits occur with novel psychoactive stimulants such as mephedrone and artificial "spice" cannabinoids. These psychobiological fluctuations underlie drug dependency and make cessation difficult. Psychobiological stability and homeostatic balance are optimally restored by quitting psychoactive drugs. Recreational stimulants such as cocaine or MDMA (3.4-methylenedioxymethamphetamine) and sedative drugs such as cannabis damage human homeostasis and well-being through similar core psychobiological mechanisms. Copyright © 2017 John Wiley & Sons, Ltd.

Information-theoretic semi-supervised metric learning via entropy regularization.

Science.gov (United States)

Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi

2014-08-01

We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.

Fluctuations of quantum fields via zeta function regularization

International Nuclear Information System (INIS)

Cognola, Guido; Zerbini, Sergio; Elizalde, Emilio

2002-01-01

Explicit expressions for the expectation values and the variances of some observables, which are bilinear quantities in the quantum fields on a D-dimensional manifold, are derived making use of zeta function regularization. It is found that the variance, related to the second functional variation of the effective action, requires a further regularization and that the relative regularized variance turns out to be 2/N, where N is the number of the fields, thus being independent of the dimension D. Some illustrating examples are worked through. The issue of the stress tensor is also briefly addressed

X-ray computed tomography using curvelet sparse regularization.

Science.gov (United States)

Wieczorek, Matthias; Frikel, Jürgen; Vogel, Jakob; Eggl, Elena; Kopp, Felix; Noël, Peter B; Pfeiffer, Franz; Demaret, Laurent; Lasser, Tobias

2015-04-01

Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method's strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directional features.

Stability of the Regular Hayward Thin-Shell Wormholes

Directory of Open Access Journals (Sweden)

M. Sharif

2016-01-01

Full Text Available The aim of this paper is to construct regular Hayward thin-shell wormholes and analyze their stability. We adopt Israel formalism to calculate surface stresses of the shell and check the null and weak energy conditions for the constructed wormholes. It is found that the stress-energy tensor components violate the null and weak energy conditions leading to the presence of exotic matter at the throat. We analyze the attractive and repulsive characteristics of wormholes corresponding to ar>0 and ar<0, respectively. We also explore stability conditions for the existence of traversable thin-shell wormholes with arbitrarily small amount of fluid describing cosmic expansion. We find that the space-time has nonphysical regions which give rise to event horizon for 0

Second order elastic metrics on the shape space of curves

DEFF Research Database (Denmark)

Bauer, Martin; Bruveris, Martins; Harms, Philipp

2015-01-01

Second order Sobolev metrics on the space of regular unparametrized planar curves have several desirable completeness properties not present in lower order metrics, but numerics are still largely missing. In this paper, we present algorithms to numerically solve the initial and boundary value......, due to its generality, it could be applied to more general spaces of mapping. We demonstrate the effectiveness of our approach by analyzing a collection of shapes representing physical objects....

Towards a Switched-Capacitor Based Stimulator for Efficient Deep-Brain Stimulation

Science.gov (United States)

Vidal, Jose; Ghovanloo, Maysam

2013-01-01

We have developed a novel 4-channel prototype stimulation circuit for implantable neurological stimulators (INS). This Switched-Capacitor based Stimulator (SCS) aims to utilize charge storage and charge injection techniques to take advantage of both the efficiency of conventional voltage-controlled stimulators (VCS) and the safety and controllability of current-controlled stimulators (CCS). The discrete SCS prototype offers fine control over stimulation parameters such as voltage, current, pulse width, frequency, and active electrode channel via a LabVIEW graphical user interface (GUI) when connected to a PC through USB. Furthermore, the prototype utilizes a floating current sensor to provide charge-balanced biphasic stimulation and ensure safety. The stimulator was analyzed using an electrode-electrolyte interface (EEI) model as well as with a pair of pacing electrodes in saline. The primary motivation of this research is to test the feasibility and functionality of a safe, effective, and power-efficient switched-capacitor based stimulator for use in Deep Brain Stimulation. PMID:21095987

The effect of dietary intervention on paraffin-stimulated saliva and dental health of children participating in a randomized controlled trial.

Science.gov (United States)

Laine, M A; Tolvanen, M; Pienihäkkinen, K; Söderling, E; Niinikoski, H; Simell, O; Karjalainen, S

2014-02-01

The aim was to study the impact of dietary intervention on the properties of paraffin-stimulated saliva, and on dental caries. At 7 months of age 1062 infants (540 intervention; 522 controls) started in the prospective, randomized Special Turku Intervention Project (STRIP) aimed at restricting the child's saturated fat and cholesterol intake to prevent atherosclerosis of adult age (www.clinicaltrials.gov NCT 00223600). At 3 years of age, every fifth child was invited to an oral sub-study, and 148 (78 boys) children attended. At 6, 9, 12 and 16 years of age 135, 127, 114 and 88 children were restudied, respectively. Dietary intakes of carbohydrates, protein, saturated fat, calcium, phosphate, and fibre were regularly recorded using 4-day food records. Height and weight were regularly monitored. Paraffin-stimulated saliva samples were collected at 6, 9, 12 and 16 years of age, and analyzed for flow rate, buffer capacity, calcium, phosphate and proteins. Dental health was recorded and expressed as d3mft/D3MFT, and as time of caries onset. Dietary intakes of calcium, phosphate and fibre, and salivary flow rate increased with time in both groups (pparaffin-stimulated salivary flow rate. The concentration of salivary calcium was directly correlated to dental health. Higher salivary flow rate in the intervention group is believed to be due to higher fibre intake in the intervention group. Copyright © 2013 Elsevier Ltd. All rights reserved.

Blue Marble Space Institute essay contest

Science.gov (United States)

Wendel, JoAnna

2014-04-01

The Blue Marble Space Institute of Science, based in Seattle, Wash., is inviting college students to participate in its essay contest. Essays need to address the question, "In the next 100 years, how can human civilization prepare for the long-term changes to the Earth system that will occur over the coming millennium?" According to the institute, the purpose of the contest is "to stimulate creative thinking relating to space exploration and global issues by exploring how changes in the Earth system will affect humanity's future."

Ultrasound stimulation on bone healing. The optimization of stimulation time

International Nuclear Information System (INIS)

Rosim, R.C.; Paulin, J.B.P.; Goncalves, R.P.

1990-01-01

Previous works in ultrasonic simulation of bone healing dealt with parameters optimization. Albertin (1983) studied the stimulation time and found forty minutes as ideal. However, this stimulation time was the largest one employed and remained some doubt about the most appropriated value. 30, 40, 50 and 60 minutes of stimulation time were selected, while others parameters were held constant with: pulse width in 200 μs, repetition rate in 1000 pulses per second and amplitude in 30 V. Partial incomplete transverse osteotomies were done in the middle third of radio in the right forearm of rabbits. Twenty four animals divided in four subgroups, with 6 animals each were stimulated. The daily stimulation time for each subgroup was 30, 40, 50 and minutes respectively, during 15 consecutive days. The stimulation procedure started 24 hours after surgery. After the stimulation period, radiological, histological and morphometric evaluations were done and greater bone healing was found for the 50 minutes stimulation subgroup, in them new bone was also prominent. (author)

Cognitive Aspects of Regularity Exhibit When Neighborhood Disappears

Science.gov (United States)

Chen, Sau-Chin; Hu, Jon-Fan

2015-01-01

Although regularity refers to the compatibility between pronunciation of character and sound of phonetic component, it has been suggested as being part of consistency, which is defined by neighborhood characteristics. Two experiments demonstrate how regularity effect is amplified or reduced by neighborhood characteristics and reveals the…

DOD Space Systems: Additional Knowledge Would Better Support Decisions about Disaggregating Large Satellites

Science.gov (United States)

2014-10-01

considering new approaches. According to Air Force Space Command, U.S. space systems face intentional and unintentional threats , which have increased...life cycle costs • Demand for more satellites may stimulate new entrants and competition to lower acquisition costs. • Smaller, less complex...Fiscal constraints and growing threats to space systems have led DOD to consider alternatives for acquiring space-based capabilities, including

Imaging of the internal structure of comet 67P/Churyumov-Gerasimenko from radiotomography CONSERT Data (Rosetta Mission) through a full 3D regularized inversion of the Helmholtz equations on functional spaces

Science.gov (United States)

Barriot, Jean-Pierre; Serafini, Jonathan; Sichoix, Lydie; Benna, Mehdi; Kofman, Wlodek; Herique, Alain

We investigate the inverse problem of imaging the internal structure of comet 67P/ Churyumov-Gerasimenko from radiotomography CONSERT data by using a coupled regularized inversion of the Helmholtz equations. A first set of Helmholtz equations, written w.r.t a basis of 3D Hankel functions describes the wave propagation outside the comet at large distances, a second set of Helmholtz equations, written w.r.t. a basis of 3D Zernike functions describes the wave propagation throughout the comet with avariable permittivity. Both sets are connected by continuity equations over a sphere that surrounds the comet. This approach, derived from GPS water vapor tomography of the atmosphere,will permit a full 3D inversion of the internal structure of the comet, contrary to traditional approaches that use a discretization of space at a fraction of the radiowave wavelength.

Conformally flat spaces and solutions to Yang-Mills equations

International Nuclear Information System (INIS)

Chaohao, G.

1980-01-01

Using the conformal invariance of Yang-Mills equations in four-dimensional manifolds, it is proved that in a simply connected space of negative constant curvature Yang-Mills equations admit solutions with any real number as their Pontryagin number. It is also shown that the space S 3 x S 1 which is the regular counterpart of the meron solution is one example of a class of solutions to Yang-Mills equations on compact manifolds that are neither self-dual nor anti-self-dual

An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography

Energy Technology Data Exchange (ETDEWEB)

Feng Jinchao; Qin Chenghu; Jia Kebin; Han Dong; Liu Kai; Zhu Shouping; Yang Xin; Tian Jie [Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China); Medical Image Processing Group, Institute of Automation, Chinese Academy of Sciences, P. O. Box 2728, Beijing 100190 (China) and School of Life Sciences and Technology, Xidian University, Xi' an 710071 (China)

2011-11-15

Purpose: Bioluminescence tomography (BLT) provides an effective tool for monitoring physiological and pathological activities in vivo. However, the measured data in bioluminescence imaging are corrupted by noise. Therefore, regularization methods are commonly used to find a regularized solution. Nevertheless, for the quality of the reconstructed bioluminescent source obtained by regularization methods, the choice of the regularization parameters is crucial. To date, the selection of regularization parameters remains challenging. With regards to the above problems, the authors proposed a BLT reconstruction algorithm with an adaptive parameter choice rule. Methods: The proposed reconstruction algorithm uses a diffusion equation for modeling the bioluminescent photon transport. The diffusion equation is solved with a finite element method. Computed tomography (CT) images provide anatomical information regarding the geometry of the small animal and its internal organs. To reduce the ill-posedness of BLT, spectral information and the optimal permissible source region are employed. Then, the relationship between the unknown source distribution and multiview and multispectral boundary measurements is established based on the finite element method and the optimal permissible source region. Since the measured data are noisy, the BLT reconstruction is formulated as l{sub 2} data fidelity and a general regularization term. When choosing the regularization parameters for BLT, an efficient model function approach is proposed, which does not require knowledge of the noise level. This approach only requests the computation of the residual and regularized solution norm. With this knowledge, we construct the model function to approximate the objective function, and the regularization parameter is updated iteratively. Results: First, the micro-CT based mouse phantom was used for simulation verification. Simulation experiments were used to illustrate why multispectral data were used

Scaling Non-Regular Shared-Memory Codes by Reusing Custom Loop Schedules

Directory of Open Access Journals (Sweden)

Dimitrios S. Nikolopoulos

2003-01-01

Full Text Available In this paper we explore the idea of customizing and reusing loop schedules to improve the scalability of non-regular numerical codes in shared-memory architectures with non-uniform memory access latency. The main objective is to implicitly setup affinity links between threads and data, by devising loop schedules that achieve balanced work distribution within irregular data spaces and reusing them as much as possible along the execution of the program for better memory access locality. This transformation provides a great deal of flexibility in optimizing locality, without compromising the simplicity of the shared-memory programming paradigm. In particular, the programmer does not need to explicitly distribute data between processors. The paper presents practical examples from real applications and experiments showing the efficiency of the approach.

Tactile-Foot Stimulation Can Assist the Navigation of People with Visual Impairment

Directory of Open Access Journals (Sweden)

Ramiro Velázquez

2015-01-01

Full Text Available Background. Tactile interfaces that stimulate the plantar surface with vibrations could represent a step forward toward the development of wearable, inconspicuous, unobtrusive, and inexpensive assistive devices for people with visual impairments. Objective. To study how people understand information through their feet and to maximize the capabilities of tactile-foot perception for assisting human navigation. Methods. Based on the physiology of the plantar surface, three prototypes of electronic tactile interfaces for the foot have been developed. With important technological improvements between them, all three prototypes essentially consist of a set of vibrating actuators embedded in a foam shoe-insole. Perceptual experiments involving direction recognition and real-time navigation in space were conducted with a total of 60 voluntary subjects. Results. The developed prototypes demonstrated that they are capable of transmitting tactile information that is easy and fast to understand. Average direction recognition rates were 76%, 88.3%, and 94.2% for subjects wearing the first, second, and third prototype, respectively. Exhibiting significant advances in tactile-foot stimulation, the third prototype was evaluated in navigation tasks. Results show that subjects were capable of following directional instructions useful for navigating spaces. Conclusion. Footwear providing tactile stimulation can be considered for assisting the navigation of people with visual impairments.

Optimal Tikhonov Regularization in Finite-Frequency Tomography

Science.gov (United States)

Fang, Y.; Yao, Z.; Zhou, Y.

2017-12-01

The last decade has witnessed a progressive transition in seismic tomography from ray theory to finite-frequency theory which overcomes the resolution limit of the high-frequency approximation in ray theory. In addition to approximations in wave propagation physics, a main difference between ray-theoretical tomography and finite-frequency tomography is the sparseness of the associated sensitivity matrix. It is well known that seismic tomographic problems are ill-posed and regularizations such as damping and smoothing are often applied to analyze the tradeoff between data misfit and model uncertainty. The regularizations depend on the structure of the matrix as well as noise level of the data. Cross-validation has been used to constrain data uncertainties in body-wave finite-frequency inversions when measurements at multiple frequencies are available to invert for a common structure. In this study, we explore an optimal Tikhonov regularization in surface-wave phase-velocity tomography based on minimization of an empirical Bayes risk function using theoretical training datasets. We exploit the structure of the sensitivity matrix in the framework of singular value decomposition (SVD) which also allows for the calculation of complete resolution matrix. We compare the optimal Tikhonov regularization in finite-frequency tomography with traditional tradeo-off analysis using surface wave dispersion measurements from global as well as regional studies.

Fractional Regularization Term for Variational Image Registration

Directory of Open Access Journals (Sweden)

Rafael Verdú-Monedero

2009-01-01

Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

Likelihood ratio decisions in memory: three implied regularities.

Science.gov (United States)

Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T

2009-06-01

We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.

Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

Science.gov (United States)

Lu, Gui-Fu; Wang, Yong; Zou, Jian

2016-05-01

In this paper, we present a novel low-rank matrix factorization algorithm with adaptive graph regularizer (LMFAGR). We extend the recently proposed low-rank matrix with manifold regularization (MMF) method with an adaptive regularizer. Different from MMF, which constructs an affinity graph in advance, LMFAGR can simultaneously seek graph weight matrix and low-dimensional representations of data. That is, graph construction and low-rank matrix factorization are incorporated into a unified framework, which results in an automatically updated graph rather than a predefined one. The experimental results on some data sets demonstrate that the proposed algorithm outperforms the state-of-the-art low-rank matrix factorization methods.

Online Manifold Regularization by Dual Ascending Procedure

OpenAIRE

Sun, Boliang; Li, Guohui; Jia, Li; Zhang, Hui

2013-01-01

We propose a novel online manifold regularization framework based on the notion of duality in constrained optimization. The Fenchel conjugate of hinge functions is a key to transfer manifold regularization from offline to online in this paper. Our algorithms are derived by gradient ascent in the dual function. For practical purpose, we propose two buffering strategies and two sparse approximations to reduce the computational complexity. Detailed experiments verify the utility of our approache...

Degree-regular triangulations of torus and Klein bottle

Indian Academy of Sciences (India)

Home; Journals; Proceedings – Mathematical Sciences; Volume 115; Issue 3 ... A triangulation of a connected closed surface is called degree-regular if each of its vertices have the same degree. ... In [5], Datta and Nilakantan have classified all the degree-regular triangulations of closed surfaces on at most 11 vertices.

Phase-space exploration in nuclear giant resonance decay

International Nuclear Information System (INIS)

Drozdz, S.; Nishizaki, S.; Wambach, J.; Speth, J.

1995-01-01

The rate of phase-space exploration in the decay of isovector and isoscalar giant quadrupole resonances in 40 Ca is analyzed. The study is based on the time dependence of the survival probability and of the spectrum of generalized entropies evaluated in the space of one-particle--one-hole (1p-1h) and 2p-2h states. Three different cases for the level distribution of 2p-2h background states, corresponding to (a) high degeneracy, (b) classically regular motion, and (c) classically chaotic motion, are studied. In the latter case the isovector excitation evolves almost statistically while the isoscalar excitation remains largely localized, even though it penetrates the whole available phase space

Does quantum mechanics select out regularity and local mode behaviour in nonlinearly coupled vibrational systems?

International Nuclear Information System (INIS)

Yurtsever, E.; Brickmann, J.

1990-01-01

A two dimensional strongly nonharmonic vibrational system with nonlinear intermode coupling is studied both classically and quantum mechanically. The system was chosen such that there is a low lying transition (in energy) from a region where almost all trajectories move regularly to a region where chaotic dynamics strongly dominates. The corresponding quantum system is far away from the semiclassical limit. The eigenfunctions are calculated with high precision according to a linear variational scheme using conveniently chosen basis functions. It is the aim of this paper to check whether the prediction from semiclassical theory, namely that the measure of classically chaotic trajectories in phase space approaches the measure of irregular states in corresponding energy ranges, holds when the system is not close to the classical limit. It is also the aim to identify individual eigenfunctions with respect to regularity and to differentiate between local and normal vibrational states. It is found that there are quantitative and also qualitative differences between the quantum results and the semiclassical predictions. (orig./HK)

Stochastic Nonlinear Evolutional Model of the Large-Scaled Neuronal Population and Dynamic Neural Coding Subject to Stimulation

International Nuclear Information System (INIS)

Wang Rubin; Yu Wei

2005-01-01

In this paper, we investigate how the population of neuronal oscillators deals with information and the dynamic evolution of neural coding when the external stimulation acts on it. Numerically computing method is used to describe the evolution process of neural coding in three-dimensioned space. The numerical result proves that only the suitable stimulation can change the coupling structure and plasticity of neurons

Co-ingestion of energy drinks with alcohol and other substances among a sample of people who regularly use ecstasy.

Science.gov (United States)

Peacock, Amy; Sindicich, Natasha; Dunn, Matthew; Whittaker, Elizabeth; Sutherland, Rachel; Entwistle, Gavin; Burns, Lucinda; Bruno, Raimondo

2016-05-01

Despite the potential harms of mixing unregulated drugs with energy drinks (ED), research to date has primarily been focused on EDs co-ingested with alcohol. Consequently, the aim of the present study was to explore the rate of use, harms and correlates of EDs co-ingested with alcohol and other drugs among a sample of people who regularly use illicit stimulant drugs. In 2010, 693 Australians who regularly used ecstasy completed a 1-h interview about their past six-month ED and drug use. Three-quarters of the sample (77%) had recently consumed EDs with other substances, primarily alcohol (70%) and ecstasy (57%). People who consumed ED with alcohol versus those who had consumed ED with ecstasy and with alcohol (only 8% reported only consuming ED with ecstasy) had similar profiles in regards to demographics, drug use, mental health and drug-related problems. Primary motives for consuming ED with alcohol included increased alertness (59%), the taste (25%), to party for longer (23%) and to combat fatigue (16%). One-half (52%) and one-quarter (27%) of participants who consumed EDs with alcohol and with ecstasy respectively had recently experienced adverse outcomes post-consumption, primarily headaches (24% and 11%) and heart palpitations (21% and 14%). Co-ingestion of EDs with licit and illicit drugs is common among people who regularly use ecstasy and related drugs. Adverse outcomes of co-ingestion suggest that targeted education regarding negative interactive drug effects is crucial for harm reduction. [Peacock A, Sindicich N, Dunn M, Whittaker E, Sutherland R, Entwistle G, Burns L, Bruno R. Co-Ingestion of Energy Drinks with Alcohol and Other Substances among a Sample of People Who Regularly Use Ecstasy. Drug Alcohol Rev 2016;35:352-358]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

Stimulating at the right time: phase-specific deep brain stimulation.

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Cagnan, Hayriye; Pedrosa, David; Little, Simon; Pogosyan, Alek; Cheeran, Binith; Aziz, Tipu; Green, Alexander; Fitzgerald, James; Foltynie, Thomas; Limousin, Patricia; Zrinzo, Ludvic; Hariz, Marwan; Friston, Karl J; Denison, Timothy; Brown, Peter

2017-01-01

SEE MOLL AND ENGEL DOI101093/AWW308 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Brain regions dynamically engage and disengage with one another to execute everyday actions from movement to decision making. Pathologies such as Parkinson's disease and tremor emerge when brain regions controlling movement cannot readily decouple, compromising motor function. Here, we propose a novel stimulation strategy that selectively regulates neural synchrony through phase-specific stimulation. We demonstrate for the first time the therapeutic potential of such a stimulation strategy for the treatment of patients with pathological tremor. Symptom suppression is achieved by delivering stimulation to the ventrolateral thalamus, timed according to the patient's tremor rhythm. Sustained locking of deep brain stimulation to a particular phase of tremor afforded clinically significant tremor relief (up to 87% tremor suppression) in selected patients with essential tremor despite delivering less than half the energy of conventional high frequency stimulation. Phase-specific stimulation efficacy depended on the resonant characteristics of the underlying tremor network. Selective regulation of neural synchrony through phase-locked stimulation has the potential to both increase the efficiency of therapy and to minimize stimulation-induced side effects. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain.

The relationship between lifestyle regularity and subjective sleep quality

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Monk, Timothy H.; Reynolds, Charles F 3rd; Buysse, Daniel J.; DeGrazia, Jean M.; Kupfer, David J.

2003-01-01

In previous work we have developed a diary instrument-the Social Rhythm Metric (SRM), which allows the assessment of lifestyle regularity-and a questionnaire instrument--the Pittsburgh Sleep Quality Index (PSQI), which allows the assessment of subjective sleep quality. The aim of the present study was to explore the relationship between lifestyle regularity and subjective sleep quality. Lifestyle regularity was assessed by both standard (SRM-17) and shortened (SRM-5) metrics; subjective sleep quality was assessed by the PSQI. We hypothesized that high lifestyle regularity would be conducive to better sleep. Both instruments were given to a sample of 100 healthy subjects who were studied as part of a variety of different experiments spanning a 9-yr time frame. Ages ranged from 19 to 49 yr (mean age: 31.2 yr, s.d.: 7.8 yr); there were 48 women and 52 men. SRM scores were derived from a two-week diary. The hypothesis was confirmed. There was a significant (rho = -0.4, p subjects with higher levels of lifestyle regularity reported fewer sleep problems. This relationship was also supported by a categorical analysis, where the proportion of "poor sleepers" was doubled in the "irregular types" group as compared with the "non-irregular types" group. Thus, there appears to be an association between lifestyle regularity and good sleep, though the direction of causality remains to be tested.

Quantum volume and length fluctuations in a midi-superspace model of Minkowski space

International Nuclear Information System (INIS)

Adelman, Jeremy; Hinterleitner, Franz; Major, Seth

2015-01-01

In a (1+1)-dimensional midi-superspace model for gravitational plane waves, a flat space–time condition is imposed with constraints derived from null Killing vectors. Solutions to a straightforward regularization of these constraints have diverging length and volume expectation values. Physically acceptable solutions in the kinematic Hilbert space are obtained from the original constraint by multiplying with a power of the volume operator and by a similar modification of the Hamiltonian constraint, which is used in a regularization of the constraints. The solutions of the modified Killing constraint have finite expectation values of geometric quantities. Further, the expectation value of the original Killing constraint vanishes, but its moment is non-vanishing. As the power of the volume grows, the moment of the original constraint grows, while the moments of volume and length both decrease. Thus, these states provide possible kinematic states for flat space, with fluctuations. As a consequence of the regularization of operators, the quantum uncertainty relations between geometric quantities such as length and its conjugate momentum do not reflect naive expectations from the classical Poisson bracket relations. (paper)

The Spatial Extent of Epiretinal Electrical Stimulation in the Healthy Mouse Retina

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Zohreh Hosseinazdeh

2017-07-01

Full Text Available Background/Aims: Retinal prostheses use electrical stimulation to restore functional vision to patients blinded by retinitis pigmentosa. A key detail is the spatial pattern of ganglion cells activated by stimulation. Therefore, we characterized the spatial extent of network-mediated electrical activation of retinal ganglion cells (RGCs in the epiretinal monopolar electrode configuration. Methods: Healthy mouse RGC activities were recorded with a micro-electrode array (MEA. The stimuli consisted of monophasic rectangular cathodic voltage pulses and cycling full-field light flashes. Results: Voltage tuning curves exhibited significant hysteresis, reflecting adaptation to electrical stimulation on the time scale of seconds. Responses decreased from 0 to 300 µm, and were also dependent on the strength of stimulation. Applying the Rayleigh criterion to the half-width at half-maximum of the electrical point spread function suggests a visual acuity limit of no better than 20/946. Threshold voltage showed only a modest increase across these distances. Conclusion: The existence of significant hysteresis requires that future investigations of electrical retinal stimulation control for such long-memory adaptation. The spread of electrical activation beyond 200 µm suggests that neighbouring electrodes in epiretinal implants based on indirect stimulation of RGCs may be indiscriminable at interelectrode spacings as large as 400 µm.

Optimal analysis of structures by concepts of symmetry and regularity

CERN Document Server

Kaveh, Ali

2013-01-01

Optimal analysis is defined as an analysis that creates and uses sparse, well-structured and well-conditioned matrices. The focus is on efficient methods for eigensolution of matrices involved in static, dynamic and stability analyses of symmetric and regular structures, or those general structures containing such components. Powerful tools are also developed for configuration processing, which is an important issue in the analysis and design of space structures and finite element models. Different mathematical concepts are combined to make the optimal analysis of structures feasible. Canonical forms from matrix algebra, product graphs from graph theory and symmetry groups from group theory are some of the concepts involved in the variety of efficient methods and algorithms presented. The algorithms elucidated in this book enable analysts to handle large-scale structural systems by lowering their computational cost, thus fulfilling the requirement for faster analysis and design of future complex systems. The ...

Borderline personality disorder and regularly drinking alcohol before sex.

Science.gov (United States)

Thompson, Ronald G; Eaton, Nicholas R; Hu, Mei-Chen; Hasin, Deborah S

2017-07-01

Drinking alcohol before sex increases the likelihood of engaging in unprotected intercourse, having multiple sexual partners and becoming infected with sexually transmitted infections. Borderline personality disorder (BPD), a complex psychiatric disorder characterised by pervasive instability in emotional regulation, self-image, interpersonal relationships and impulse control, is associated with substance use disorders and sexual risk behaviours. However, no study has examined the relationship between BPD and drinking alcohol before sex in the USA. This study examined the association between BPD and regularly drinking before sex in a nationally representative adult sample. Participants were 17 491 sexually active drinkers from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions. Logistic regression models estimated effects of BPD diagnosis, specific borderline diagnostic criteria and BPD criterion count on the likelihood of regularly (mostly or always) drinking alcohol before sex, adjusted for controls. Borderline personality disorder diagnosis doubled the odds of regularly drinking before sex [adjusted odds ratio (AOR) = 2.26; confidence interval (CI) = 1.63, 3.14]. Of nine diagnostic criteria, impulsivity in areas that are self-damaging remained a significant predictor of regularly drinking before sex (AOR = 1.82; CI = 1.42, 2.35). The odds of regularly drinking before sex increased by 20% for each endorsed criterion (AOR = 1.20; CI = 1.14, 1.27) DISCUSSION AND CONCLUSIONS: This is the first study to examine the relationship between BPD and regularly drinking alcohol before sex in the USA. Substance misuse treatment should assess regularly drinking before sex, particularly among patients with BPD, and BPD treatment should assess risk at the intersection of impulsivity, sexual behaviour and substance use. [Thompson Jr RG, Eaton NR, Hu M-C, Hasin DS Borderline personality disorder and regularly drinking alcohol

In-Space Inspection Technologies Vision

Science.gov (United States)

Studor, George

2012-01-01

Purpose: Assess In-Space NDE technologies and needs - current & future spacecraft. Discover & build on needs, R&D & NDE products in other industries and agencies. Stimulate partnerships in & outside NASA to move technologies forward cooperatively. Facilitate group discussion on challenges and opportunities of mutual benefit. Focus Areas: Miniaturized 3D Penetrating Imagers Controllable Snake-arm Inspection systems Miniature Free-flying Micro-satellite Inspectors

Commercial Space with Technology Maturation

Science.gov (United States)

McCleskey, Carey M.; Rhodes, Russell E.; Robinson, John W.

2013-01-01

To provide affordable space transportation we must be capable of using common fixed assets and the infrastructure for multiple purposes simultaneously. The Space Shuttle was operated for thirty years, but was not able to establish an effective continuous improvement program because of the high risk to the crew on every mission. An unmanned capability is needed to provide an acceptable risk to the primary mission. This paper is intended to present a case where a commercial space venture could share the large fixed cost of operating the infrastructure with the government while the government provides new advanced technology that is focused on reduced operating cost to the common launch transportation system. A conceivable commercial space venture could provide educational entertainment for the country's youth that would stimulate their interest in the science, technology, engineering, and mathematics (STEM) through access at entertainment parks or the existing Space Visitor Centers. The paper uses this example to demonstrate how growing public-private space market demand will re-orient space transportation industry priorities in flight and ground system design and technology development, and how the infrastructure is used and shared.

[Transcranial magnetic stimulation and motor cortex stimulation in neuropathic pain].

Science.gov (United States)

Mylius, V; Ayache, S S; Teepker, M; Kappus, C; Kolodziej, M; Rosenow, F; Nimsky, C; Oertel, W H; Lefaucheur, J P

2012-12-01

Non-invasive and invasive cortical stimulation allows the modulation of therapy-refractory neuropathic pain. High-frequency repetitive transcranial magnetic stimulation (rTMS) of the contralateral motor cortex yields therapeutic effects at short-term and predicts the benefits of epidural motor cortex stimulation (MCS). The present article summarizes the findings on application, mechanisms and therapeutic effects of cortical stimulation in neuropathic pain.

STAKEHOLDERS PARTICIPATION FOR URBAN CLIMATE RESILIENCE: A CASE OF INFORMAL SETTLEMENTS REGULARIZATION IN KHULNA CITY, BANGLADESH

Directory of Open Access Journals (Sweden)

Sujit Kumar SIKDER

2015-06-01

Full Text Available This study focuses on stakeholders’ participation, perceptions and local contextualization in the Informal Settlement (IS regularization processes in Khulna City. These processes are undertaken to address livelihood challenges of IS dwellers and to operationalize development initiatives in informal regularization projects. Adopting both a qualitative and quantitative approach, the research results show that IS formation in Khulna City started slowly with rural immigration. These immigrants remain vulnerable to climate change although some initiatives were undertaken since the last 20 years to improve their living conditions. The IS dwellers and local leaders initially participated in these settlement-upgrading initiatives due to accompanied incentives but they became adamant after the project period ended. It was also found that the city local government and NGOs do not have any permanent arrangement to sustain the IS regularization processes. The analysis of the interrelationships among the stakeholders revealed that the relevant public agencies are in conflict, and the role of the private sector is less recognized. The initiatives undertaken so far have limited success especially in granting tenure security, and the private landowners or local authorities that trespassed public spaces resort to forceful eviction. Amidst all these, there is the need for the formulation and implementation of climate resilience policies that address stakeholder participations in mitigating climate change consequences and enhance livelihood development.

Breast ultrasound tomography with total-variation regularization

Energy Technology Data Exchange (ETDEWEB)

Huang, Lianjie [Los Alamos National Laboratory; Li, Cuiping [KARMANOS CANCER INSTIT.; Duric, Neb [KARMANOS CANCER INSTIT

2009-01-01

Breast ultrasound tomography is a rapidly developing imaging modality that has the potential to impact breast cancer screening and diagnosis. A new ultrasound breast imaging device (CURE) with a ring array of transducers has been designed and built at Karmanos Cancer Institute, which acquires both reflection and transmission ultrasound signals. To extract the sound-speed information from the breast data acquired by CURE, we have developed an iterative sound-speed image reconstruction algorithm for breast ultrasound transmission tomography based on total-variation (TV) minimization. We investigate applicability of the TV tomography algorithm using in vivo ultrasound breast data from 61 patients, and compare the results with those obtained using the Tikhonov regularization method. We demonstrate that, compared to the Tikhonov regularization scheme, the TV regularization method significantly improves image quality, resulting in sound-speed tomography images with sharp (preserved) edges of abnormalities and few artifacts.

Manufacture of Regularly Shaped Sol-Gel Pellets

Science.gov (United States)

Leventis, Nicholas; Johnston, James C.; Kinder, James D.

2006-01-01

An extrusion batch process for manufacturing regularly shaped sol-gel pellets has been devised as an improved alternative to a spray process that yields irregularly shaped pellets. The aspect ratio of regularly shaped pellets can be controlled more easily, while regularly shaped pellets pack more efficiently. In the extrusion process, a wet gel is pushed out of a mold and chopped repetitively into short, cylindrical pieces as it emerges from the mold. The pieces are collected and can be either (1) dried at ambient pressure to xerogel, (2) solvent exchanged and dried under ambient pressure to ambigels, or (3) supercritically dried to aerogel. Advantageously, the extruded pellets can be dropped directly in a cross-linking bath, where they develop a conformal polymer coating around the skeletal framework of the wet gel via reaction with the cross linker. These pellets can be dried to mechanically robust X-Aerogel.

Study of localized photon source in space of measures