Brief Announcement: Node Sampling Using Centrifugal Random Walks.

We propose distributed algorithms for sampling networks based on a new class of random walks that we call Centrifugal Random Walks (CRW). A CRW is a random walk that starts at a source and always moves away from it. We propose CRW algorithms for connected networks with arbitrary probability distributions, and for grids and networks with regular concentric connectivity with distance based distributions. All CRW sampling algorithms select a node with the exact probability distribution, do not need warm-up, and end in a number of hops bounded by the network diameter.

Node sampling using random centrifugal walks

Sampling a network with a given probability distribution has been identified as a useful operation. In this paper we propose distributed algorithms for sampling networks, so that nodes are selected by a special node, called the source, with a given probability distribution. All these algorithms are based on a new class of random walks, that we call Random Centrifugal Walks (RCW). A RCW is a random walk that starts at the source and always moves away from it. Firstly, an algorithm to sample any connected network using RCW is proposed. The algorithm assumes that each node has a weight, so that the sampling process must select a node with a probability proportional to its weight. This algorithm requires a preprocessing phase before the sampling of nodes. In particular, a minimum diameter spanning tree (MDST) is created in the network, and then nodes weights are efficiently aggregated using the tree. The good news are that the preprocessing is done only once, regardless of the number of sources and the number of samples taken from the network. After that, every sample is done with a RCW whose length is bounded by the network diameter. Secondly, RCW algorithms that do not require preprocessing are proposed for grids and networks with regular concentric connectivity, for the case when the probability of selecting a node is a function of its distance to the source. The key features of the RCW algorithms (unlike previous Markovian approaches) are that (1) they do not need to warm-up (stabilize), (2) the sampling always finishes in a number of hops bounded by the network diameter, and (3) it selects a node with the exact probability distribution.

Novel fast random search clustering approach for mixing matrix identification in MIMO linear blind inverse problems with sparse inputs

In this paper we propose a novel fast random search clustering (RSC) algorithm for mixing matrix identification in multiple input multiple output (MIMO) linear blind inverse problems with sparse inputs. The proposed approach is based on the clustering of the observations around the directions given by the columns of the mixing matrix that occurs typically for sparse inputs. Exploiting this fact, the RSC algorithm proceeds by parameterizing the mixing matrix using hyperspherical coordinates, randomly selecting candidate basis vectors (i.e. clustering directions) from the observations, and accepting or rejecting them according to a binary hypothesis test based on the Neyman–Pearson criterion. The RSC algorithm is not tailored to any specific distribution for the sources, can deal with an arbitrary number of inputs and outputs (thus solving the difficult under-determined problem), and is applicable to both instantaneous and convolutive mixtures. Extensive simulations for synthetic and real data with different number of inputs and outputs, data size, sparsity factors of the inputs and signal to noise ratios confirm the good performance of the proposed approach under moderate/high signal to noise ratios. RESUMEN. Método de separación ciega de fuentes para señales dispersas basado en la identificación de la matriz de mezcla mediante técnicas de "clustering" aleatorio.

Efficient random variable generation: ratio of uniforms and polar rejection sampling

Monte Carlo techniques, which require the generation of samples from some target density, are often the only alternative for performing Bayesian inference. Two classic sampling techniques to draw independent samples are the ratio of uniforms (RoU) and rejection sampling (RS). An efficient sampling algorithm is proposed combining the RoU and polar RS (i.e. RS inside a sector of a circle using polar coordinates). Its efficiency is shown in drawing samples from truncated Cauchy and Gaussian random variables, which have many important applications in signal processing and communications. RESUMEN. Método eficiente para generar algunas variables aleatorias de uso común en procesado de señal y comunicaciones (por ejemplo, Gaussianas o Cauchy truncadas) mediante la combinación de dos técnicas: "ratio of uniforms" y "rejection sampling".

Methodology for assessing regional economic impacts of charging HGVs in Spain: an integrated approach through a random utility based multiregional input-output and a road transportation network model

An integrated approach composed of a random utility-based multiregional input-output model and a road transport network model was developed for evaluating the application of a fee to heavy-goods vehicles (HGVs) in Spain. For this purpose, a distance-based charge scenario (in euros per vehicle kilometer) for HGVs was evaluated for a selected motorway network in Spain. Although the aim of this charging policy was to increase the efficiency of transport, the approach strongly identified direct and indirect impacts on the regional economy. Estimates of the magnitude and extent of indirect effects on aggregated macroeconomic indicators (employment and gross domestic product) are provided. The macroeconomic effects of the charging policy were found to be positive for some regions and negative for other regions.

A random utility based multiregional input-output approach to estimate the impact of a new highway on the regional distribution of jobs

This paper addresses the economic impact assessment of the construction of a new road on the regional distribution of jobs. The paper summarizes different existing model approaches considered to assess economic impacts through a literature review. Afterwards, we present the development of a comprehensive approach for analyzing the interaction of new transport infrastructure and the economic impact through an integrated model. This model has been applied to the construction of the motorway A-40 in Spain (497 Km.) which runs across three regions without passing though Madrid City. This may in turn lead to the relocation of labor and capital due to the improvement of accessibility of markets or inputs. The result suggests the existence of direct and indirect effects in other regions derived from the improvement of the transportation infrastructure, and confirms the relevance of road freight transport in some regions. We found that the changes in regional employment are substantial for some regions (increasing or decreasing jobs), but a t the same time negligible in other regions. As a result,the approach provides broad guidance to national governments and other transport-related parties about the impacts of this transport policy.

Random positions of dendritic spines in human cerebral cortex

Dendritic spines establish most excitatory synapses in the brain and are located in Purkinje cell’s dendrites along helical paths, perhaps maximizing the probability to contact different axons. To test whether spine helixes also occur in neocortex, we reconstructed >500 dendritic segments from adult human cortex obtained from autopsies. With Fourier analysis and spatial statistics, we analyzed spine position along apical and basal dendrites of layer 3 pyramidal neurons from frontal, temporal, and cingulate cortex. Although we occasionally detected helical positioning, for the great majority of dendrites we could not reject the null hypothesis of spatial randomness in spine locations, either in apical or basal dendrites, in neurons of different cortical areas or among spines of different volumes and lengths. We conclude that in adult human neocortex spine positions are mostly random. We discuss the relevance of these results for spine formation and plasticity and their functional impact for cortical circuits.

Random positioning of dendritic spines in the human cerebral cortex

Dendritic spines establish most excitatory synapses in the brain and are located in Purkinje cell?s dendrites along helical paths, perhaps maximizing the probability to contact different axons. To test whether spine helixes also occur in neocortex, we reconstructed ?500 dendritic segments from adult human cortex obtained from autopsies. With Fourier analysis and spatial statistics, we analyzed spine position along apical and basal dendrites of layer 3 pyramidal neurons from frontal, temporal, and cingulate cortex. Although we occasionally detected helical positioning, for the great majority of dendrites we could not reject the null hypothesis of spatial randomness in spine locations, either in apical or basal dendrites, in neurons of different cortical areas or among spines of different volumes and lengths. We conclude that in adult human neocortex spine positions are mostly random. We discuss the relevance of these results for spine formation and plasticity and their functional impact for cortical circuits.

Computer simulation of random parckings for self-similar particle size distributions in soil and granular materials: porosity and pore size distribution

A 2D computer simulation method of random packings is applied to sets of particles generated by a self-similar uniparametric model for particle size distributions (PSDs) in granular media. The parameter p which controls the model is the proportion of mass of particles corresponding to the left half of the normalized size interval [0,1]. First the influence on the total porosity of the parameter p is analyzed and interpreted. It is shown that such parameter, and the fractal exponent of the associated power scaling, are efficient packing parameters, but this last one is not in the way predicted in a former published work addressing an analogous research in artificial granular materials. The total porosity reaches the minimum value for p = 0.6. Limited information on the pore size distribution is obtained from the packing simulations and by means of morphological analysis methods. Results show that the range of pore sizes increases for decreasing values of p showing also different shape in the volume pore size distribution. Further research including simulations with a greater number of particles and image resolution are required to obtain finer results on the hierarchical structure of pore space.

Pseudo-random single photon counting for space-borne atmospheric sensing applications

The ability to accurately observe the Earth's carbon cycles from space gives scientists an important tool to analyze climate change. Current space-borne Integrated-Path Differential Absorption (IPDA) Iidar concepts have the potential to meet this need. They are mainly based on the pulsed time-offlight principle, in which two high energy pulses of different wavelengths interrogate the atmosphere for its transmission properties and are backscattered by the ground. In this paper, feasibility study results of a Pseudo-Random Single Photon Counting (PRSPC) IPDA lidar are reported. The proposed approach replaces the high energy pulsed source (e.g. a solidstate laser), with a semiconductor laser in CW operation with a similar average power of a few Watts, benefiting from better efficiency and reliability. The auto-correlation property of Pseudo-Random Binary Sequence (PRBS) and temporal shifting of the codes can be utilized to transmit both wavelengths simultaneously, avoiding the beam misalignment problem experienced by pulsed techniques. The envelope signal to noise ratio has been analyzed, and various system parameters have been selected. By restricting the telescopes field-of-view, the dominant noise source of ambient light can be suppressed, and in addition with a low noise single photon counting detector, a retrieval precision of 1.5 ppm over 50 km along-track averaging could be attained. We also describe preliminary experimental results involving a negative feedback Indium Gallium Arsenide (InGaAs) single photon avalanche photodiode and a low power Distributed Feedback laser diode modulated with PRBS driven acoustic optical modulator. The results demonstrate that higher detector saturation count rates will be needed for use in future spacebourne missions but measurement linearity and precision should meet the stringent requirements set out by future Earthobserving missions.

Random-modulation cw lidar system for space-borne carbon dioxide remote sensing based on a high-brightness semiconductor laser

In this paper, we report on the progresses of the BRITESPACE Consortium in order to achieve space-borne LIDAR measurements of atmospheric carbon dioxide concentration based on an all semiconductor laser source at 1.57 ?m. The complete design of the proposed RM-CW IPDA LIDAR has been presented and described in detail. Complete descriptions of the laser module and the FSU have been presented. Two bended MOPAs, emitting at the sounding frequency of the on- and off- IPDA channels, have been proposed as the transmitter optical sources with the required high brightness. Experimental results on the bended MOPAs have been presented showing a high spectral purity and promising expectations on the high output power requirements. Finally, the RM-CW approach has been modelled and an estimation of the expected SNR for the entire system is presented. Preliminary results indicate that a CO2 retrieval precision of 1.5 ppm could be achieved with an average output power of 2 W for each channel.

Multistability, chaos, and random signal generation in semiconductor superlattices

Peer reviewed

Broken symmetry and critical transport properties of random metals

Recent experimental data on the conductivity σ+(T), T → 0, on the metallic side of the metal–insulator transition in ideally random (neutron transmutation-doped) 70Ge:Ga have shown that σ+(0) ∝ (N − Nc)μ with μ = ½, confirming earlier ultra-low-temperature results for Si:P. This value is inconsistent with theoretical predictions based on diffusive classical scaling models, but it can be understood by a quantum-directed percolative filamentary amplitude model in which electronic basis states exist which have a well-defined momentum parallel but not normal to the applied electric field. The model, which is based on a new kind of broken symmetry, also explains the anomalous sign reversal of the derivative of the temperature dependence in the critical regime.

Critical transport properties of random metals in large magnetic fields

The threshold behavior of the transport properties of a random metal in the critical region near a metal–insulator transition is strongly affected by the measuring electromagnetic fields. In spite of the randomness, the electrical conductivity exhibits striking phase-coherent effects due to broken symmetry, which greatly sharpen the transition compared with the predictions of effective medium theories, as previously explained for electrical conductivities. Here broken symmetry explains the sign reversal of the T → 0 magnetoconductance of the metal–insulator transition in Si(B,P), also previously not understood by effective medium theories. Finally, the symmetry-breaking features of quantum percolation theory explain the unexpectedly very small electrical conductivity temperature exponent α = 0.22(2) recently observed in Ni(S,Se)2 alloys at the antiferromagnetic metal–insulator transition below T = 0.8 K.

Random locomotion and chemotaxis of human blood polymorphonuclear leukocytes (PMN) in the presence of EDTA: PMN in close quarters require neither leukocyte integrins nor external divalent cations

Divalent cations are thought essential for motile function of leukocytes in general, and for the function of critical adhesion molecules in particular. In the current study, under direct microscopic observation with concomitant time-lapse video recording, we examined the effects of 10 mM EDTA on locomotion of human blood polymorphonuclear leukocytes (PMN). In very thin slide preparations, EDTA did not impair either random locomotion or chemotaxis; motile behavior appeared to benefit from the close approximation of slide and coverslip (“chimneying”). In preparations twice as thick, PMN in EDTA first exhibited active deformability with little or no displacement, then rounded up and became motionless. However, on creation of a chemotactic gradient, the same cells were able to orient and make their way to the target, often, however, losing momentarily their purchase on the substrate. In either of these preparations without EDTA, specific antibodies to β2 integrins did not prevent random locomotion or chemotaxis, even when we added antibodies to β1 and αvβ3 integrins and to integrin-associated protein, and none of these antibodies added anything to the effects of EDTA. In the more turbulent environment of even more media, effects of anti-β2 integrins became evident: PMN still could locomote but adhered to substrate largely by their uropods and by uropod-associated filaments. We relate these findings to the reported independence from integrins of PMN in certain experimental and disease states. Moreover, we suggest that PMN locomotion in close quarters is not only integrin-independent, but independent of external divalent cations as well.