Creating and modulating rhythms by controlling the physics of the body

The motion behaviors of vertebrates require the correct coordination of the muscles and of the body limbs even for the most stereotyped ones like the rhythmical patterns. It means that the neural circuits have to share some part of the control with the material properties and the body morphology in order to rise any of these motor synergies. To this respect, the chemical downward neuromodulators that supervise the pattern generators in the spinal cord create the conditions to merge (or to disrupt) them by matching the phase of the neural controllers to the body dynamics. In this paper, we replicate this control based on phase synchronization to implement neuromodulators and investigate the interplay between control, morphology and material. We employ this mechanism to control three robotic setups of gradual complexity and actuated by McKibben type air muscles: a single air muscle, an elbow-like system and a leg-like articulation. We show that for specific values, the control parameters modulate the internal dynamics to match those of the body and of the material physics to either the rhythmical and non-rhythmical gait patterns.     

Coordinating Mobile Agents by the XML-Based Tuple Space

This paper presents Xspace,a programmable coordination paradigm for Internet applications based on mobile agents.The Xspace system fully exploits the advantages of the XML language and Linda-like coordination.It supports XML documents as tuple fields and multiple matching routines implementing different relations among XML documents,including those given by XML query languages,The Xspace uses Java as the implementation language;it is based on object-oriented XMLized tuple spaces to implement a portable and programmable coordination paradigm for mobile agents.The dsign and implementation procedures of Xspace are described in this paper,Experiment and performance evaluation are also made.Finally,some conclusinos and remarks are given.     

Realizing the Typical Gas Burning System''''s Control by PLC

ShanxiAluminaPlanthasfourcalcinersnow.Threeofthosearegassuspensioncalcinersandtherefuelwascomefromthegasgenerationfurnishorthecokeoven,operatedundernegativepress,andtheywerebuildupandprocessedin1992,1994and2002onebyone;theotheronewasthefluidflashcalciner,itwasbuildforepart,itsprimefuelwasheavyoil,operatedunderpositivepress,itsproducecostwashigherandhigherforthereasonofheavyoilsource'swentshortofrecently.Aconstitutionofchangingthelatter'sfueltobegas,whichhaslowercoststhanoil,haspasseddemonstrat…     

Accelerating the Computation of PageRank by λ2 Extrapolation

In order to improve the running performance of standard PageRank algorithm, a new extrapolation algorithm is proposed, which exploits the second eigenvalue λ2 of web page hyperlink probabilistic matrix. Experiments indicate that the new algorithm with , λ2-extrapolation can significantly outperform the standard PageRank. Compared with the standard PageRank algorithm, both the number of iterations up to the desired tolerances and the clock time used by computing importance scores of pages in the new algorithm are reduced effectively.     

Is the k-NN classifier in high dimensions affected by the curse of dimensionality?

There is an increasing body of evidence suggesting that exact nearest neighbour search in high-dimensional spaces is affected by the curse of dimensionality at a fundamental level. Does it necessarily mean that the same is true for $k$ nearest neighbours based learning algorithms such as the $k$-NN classifier? We analyse this question at a number of levels and show that the answer is different at each of them. As our first main observation, we show the consistency of a $k$ approximate nearest neighbour classifier. However, the performance of the classifier in very high dimensions is provably unstable. As our second main observation, we point out that the existing model for statistical learning is oblivious of dimension of the domain and so every learning problem admits a universally consistent deterministic reduction to the one-dimensional case by means of a Borel isomorphism.     

Identification of Experimental Trends by the L χ-Transformation Methods

Identification of experimental trends by the integral L -transformation (the generalization of Carson transformation) methods is investigated. Identification algorithms for determining the analytical expression of trend are designed. Examples are given.     

Translating by post-editing: is it the way forward?

Translation memory tools now offer the translator to insert post-edited machine translation segments for which no match is found in the databases. The Google Translator Toolkit does this by default, advising in its Settings window: “Most users should not modify this”. Post-editing of no matches appears to work on engines trained with specific bilingual data on a source written under controlled language constraints. Would this, however, work for any type of task as Google’s advice implies? We have tested this by carrying out experiments with English–Chinese trainees, using the Toolkit to translate from the source text (the control group) and by post-editing (the experimental group). Results show that post-editing gains in productivity are marginal. With regard to quality, however, post-editing produces significantly better statistical results compared to translating manually. These gains in quality are observed independently of language direction, text difficulty or translator’s level of performance. In light of these findings, we discuss whether translators should consider post-editing as a viable alternative to conventional translation.     

Solitary-wave solutions of the Degasperis–Procesi equation by means of the homotopy analysis method

The homotopy analysis method (HAM) is applied to the Degasperis–Procesi equation in order to find analytic approximations to the known exact solitary-wave solutions for the solitary peakon wave and the family of solitary smooth-hump waves. It is demonstrated that the approximate solutions agree well with the exact solutions. This provides further evidence that the HAM is a powerful tool for finding excellent approximations to nonlinear solitary waves.     

Operation speed limited by the electric properties of?the?photorefractive spatial light modulator

With excellent photo-electric and electro-optical effects, the photorefractive spatial light modulators can work as optically addressed modulators in optical information processing systems and parallel optical computing systems. The photo-induced current pulses of the photorefractive spatial light modulator observed in the experiments are analyzed to conclude the characteristics, and to find the relationship between the properties of the current pulse and the structural parameters. Furthermore, the origin of the photo-induced current pulse is analyzed, and the methods to improve the operation speed of the spatial light modulators are proposed. The research results will be significant for extending the applications of the photorefractive spatial light modulators, and pushing ahead the research of all-optical modulation materials and devices for optical supercomputing.     

Numerical simulation of the three dimensional Allen–Cahn equation by the high-order compact ADI method

In this paper, a new linearized high-order compact difference method is presented for numerical simulation of three dimensional (3D) Allen–Cahn equation with three kinds of boundary conditions. The method, which is based on the Crank–Nicholson/Adams–Bashforth scheme combined with the Douglas–Gunn ADI method, is second order accurate in time and fourth order accurate in space and energy degradation. The main advantages of this method is that the nonlinear penalty term f(u)$f\left(u\right)$ is linear and an extra stabilizing term is added to alleviate the stability constraint while maintaining accuracy and simplicity. Numerical experiments are given to demonstrate the validity and applicability of the new method.     

Two filter smoothing formulae by diagonalization of the Hamiltonian equations†

We present a new approach to two filter smoothing formulae via diagonalization of the general time variant hamiltonian equations of the linear estimation problem. This approach shows the special role of the famous Mayno-Fraser two filter formulae and also provides insight into certaini nvariance properties of backwards Kalman filter estimates.     

Improving the parallelism of iterative methods by aggressive loop fusion

Traditionally, loop nests are fused only when the data dependences in the loop nests are not violated. This paper presents a new loop fusion algorithm that is capable of fusing loop nests in the presence of fusion-preventing anti-dependences. All the violated anti-dependences are removed by automatic array copying. As a case study, this aggressive loop fusion strategy is applied to a Jacobi solver. The performance of iterative methods is typically limited by the speed of the memory system. Fusing the two loop nests in the Jacobi solver into one reduces data cache misses, and consequently, improves the performance results of both sequential and parallel versions of the Jacobi program, as validated by our experimental results on an HP AlphaServer SC45 supercomputer.     

Blind Deconvolution Models Regularized by Fractional Powers of the Laplacian

We present a method for deconvolution of images by means of an inversion of fractional powers of the Gaussian. The main feature of our model is the introduction of a regularizing term which is also a fractional power of the Laplacian. This term allows us to recover higher frequencies. The model is particularly useful to devise an algorithm for blind deconvolution. We will show, analyze and illustrate through examples the performance of this algorithm.

Spectral: Solving Schroedinger and Wheeler–DeWitt equations in the positive semi-axis by the spectral method

The Galerkin spectral method can be used for approximate calculation of eigenvalues and eigenfunctions of unidimensional Schroedinger-like equations such as the Wheeler–DeWitt equation. The criteria most commonly employed for checking the accuracy of results is the conservation of norm of the wave function, but some other criteria might be used, such as the orthogonality of eigenfunctions and the variation of the spectrum with varying computational parameters, e.g. the number of basis functions used in the approximation. The package Spectra, which implements the spectral method in Maple language together with a number of testing tools, is presented. Alternatively, Maple may interact with the Octave numerical system without the need of Octave programming by the user.     

A commentary and correction on the article “Pansharpening by exploiting sharpness of the spatial structure”

This study clarifies the implicit potential deficiency caused by the sparse cardinality parameter k in Rong et al. (2014). In addition, k = β × W × M × N (0.9 ≤ β < 1) is suggested to avert this potential deficiency, where β is a ratio controlling the amount of sparse cardinality, W is the number of multispectral bands and M × N is the size of panchromatic image. With the choice of k suggested in this study, the low rank matrix L and sparse matrix S obtained by Go Decomposition (Zhou and Tao 2011) can be iteratively optimized and solved. Thus, instead of choosing k as W × M × N in Rong et al. (2014), the potential deficiency that L is directly obtained as an analytic solution can be averted.     

Spectral analysis of quadrupolar NMR signals by the Padé-Laplace method

A new spectral analysis method, referred to as the Padé-Laplace method (PLM), is used for the first time to analyse NMR signals. For this analysis it introduces Laplace transform of the free induction decay (FID) and represents this transform through Padé approximants. When suitably applied this method allows retrieval of the spectral parameters (frequency, amplitude and linewidth) of each NMR line, without any a priori assumption concerning the number of exponential components involved in the FID. Mathematical analysis and numerical tricks of the PLM are discussed in the frame of this important class of signals. Numerical simulations, including two well resolved component FID, free of noise and with various levels of noise, have been performed in order to test the efficiency of the method. Finally, NMR signals from N-methyl imidazole in DMSO have been analysed; agreement with the results of the FT procedure is within experimental accuracy.     

Solutions to the generalized Sylvester matrix equations by a singular value decomposition

In this paper,solutions to the generalized Sylvester matrix equations AX-XF=BY and MXN-X=TY with A,M∈Rn×n,B,T∈Rn×n,F,N∈Rp×p and the matrices N,F being in companion form,are established by a singular value decomposition of a matrix with dimensions n×(n pr).The algorithm proposed in this paper for the euqation AX-XF=BY does not require the controllability of matrix pair(A,B)andthe restriction that A,F do not have common eigenvalues.Since singular value decomposition is adopted,the algorithm is numerically stable and may provide great convenience to the computation of the solution to these equations,and can perform important functions in many design problems in control systems theory.     

Prediction of the PPARα agonism of fibrates by combined MM-docking approaches

Fibrates are peroxisome proliferator-activated alpha receptor (PPARα) activators derived from fibric acid and are the most clinically used therapeutics in the treatment of hypertriglyceridemia. Long standing studies on these drugs have accumulated a large body of experimental data about their biological activity and, more recently, on the molecular mechanism mediating their PPARα agonism. An immense interest for the discovery of new fibrates with improved potency and PPARα selectivity has stimulated many investigations toward a deeper understanding of structure-activity relationships controlling their activity. The present study aimed at investigating the binding properties of a set of 23 fibrates, characterized by similar carboxylic heads but differing in the size and orientation of the hydrophobic portion, using computational approaches. We combined standard docking and molecular mechanics approaches to better describe the adaptation of the protein target to the bound ligand. The agonist potencies were then regressed against the calculated binding energies to elaborate predictive model equations. The obtained models were characterized by good performances realizing a fair trade-off between accuracy and computational costs. The best model was obtained with a regression procedure allowing automatic generation of a training subset from the whole set of trials and filtering out outliers, thus highlighting the importance of regression strategies.     

Thermodynamic modeling of the V–Si system supported by key experiments

The V–Si system is reassessed based on a critical literature review involving recently reported data and the present experimental data. These new data include the thermodynamic stability of V ₆Si₅ and the enthalpies of formation for the compounds calculated by first-principles method. Two alloys were prepared in the region of (Si)+V Si₂ and annealed at 1273 K for 14 days. After X-ray diffraction (XRD) and chemical analysis of these alloys were performed, the eutectic reaction (L⇔(Si)+V Si₂) temperature was determined by differential thermal analysis (DTA). Self-consistent thermodynamic parameters for the V–Si system were obtained by optimization of the selected experimental values. The calculated phase diagram and thermodynamic properties agree well with the experimental ones. Noticeable improvements have been made, compared with the previous assessments.