Accumulation and bunching of positrons

Results from a positron accumulator that operates efficiently over a range of repetition rates from 100 to 1000 Hz are presented. Moderated β‐decay positrons from a radioactive source are accumulated in a Penning‐style trap. At a repetition rate of 250 Hz an accumulation efficiency of ∼25% has been achieved. Two techniques for reducing the time spread of the positron pulses have been investigated. The most successful method reduces the pulse width from 120 ns to 20 ns.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/87600/2/487_1.pd

Functional-Friction Networks: New Insights on the Laboratory Earthquakes

We report some new applications of functional complex networks on acoustic emission waveforms from frictional interfaces. Our results show that laboratory faults undergo a sequence of generic phases as well as strengthening, weakening or fast-slip and slow-slip leading to healing. Also, using functional networks, we extend the dissipated energy due to acoustic emission signals in terms of short-term and long-term features of events. We show that the transition from regular to slow ruptures can have an additional production from the critical rupture class similar to the direct observations of this phenomenon in the transparent samples. Furthermore, we demonstrate detailed sub-micron evolution of the interface due to the short-term evolution of rupture tip, which is represented by phenomenological description of the modularity rates. In addition, we found nucleation phase of each single event for most amplified events follows a nearly constant time scale, corresponding to initial strengthening of interfaces

Noise-aided gradient descent bit-flipping decoders approaching maximum likelihood decoding

International audienceIn the recent literature, the study of iterative LDPC decoders implemented on faulty-hardware has led to the counter-intuitive conclusion that noisy decoders could perform better than their noiseless version. This peculiar behavior has been observed in the finite codeword length regime, where the noise perturbating the decoder dynamics help to escape the attraction of fixed points such as trapping sets. In this paper, we will study two recently introduced LDPC decoders derived from noisy versions of the gradient descent bit-flipping decoder (GDBF). Although the GDBF is known to be a simple decoder with limited error correction capability compared to more powerful soft-decision decoders, it has been shown that the introduction of a random perturbation in the decoder could greatly improve the performance results, approaching and even surpassing belief propagation or min-sum based decoders. For both decoders, we evaluate the probability of escaping from a Trapping set, and relate this probability to the parameters of the injected noise distribution, using a Markovian model of the decoder transitions in the state space of errors localized on isolated trapping sets. In a second part of the paper, we present a modified scheduling of our algorithms for the binary symmetric channel, which allows to approach maximum likelihood decoding (MLD) at the cost of a very large number of iterations

Information-based view initialization in visual SLAM with a single omnidirectional camera

© 2015 Elsevier B.V. All rights reserved. This paper presents a novel mechanism to initiate new views within the map building process for an EKF-based visual SLAM (Simultaneous Localization and Mapping) approach using omnidirectional images. In presence of non-linearities, the EKF is very likely to compromise the final estimation. Particularly, the omnidirectional observation model induces non-linear errors, thus it becomes a potential source of uncertainty. To deal with this issue we propose a novel mechanism for view initialization which accounts for information gain and losses more efficiently. The main outcome of this contribution is the reduction of the map uncertainty and thus the higher consistency of the final estimation. Its basis relies on a Gaussian Process to infer an information distribution model from sensor data. This model represents feature points existence probabilities and their information content analysis leads to the proposed view initialization scheme. To demonstrate the suitability and effectiveness of the approach we present a series of real data experiments conducted with a robot equipped with a camera sensor and map model solely based on omnidirectional views. The results reveal a beneficial reduction on the uncertainty but also on the error in the pose and the map estimate

Bioinformatics analysis of calcium-dependent protein kinase 4 (CDPK4) as Toxoplasma gondii vaccine target

Objectives Toxoplasma gondii (T. gondii), an obligate intracellular apicomplexan parasite, could affect numerous warm-blooded animals, such as humans. Calcium-dependent protein kinases (CDPKs) are essential Ca2+ signaling mediators and participate in parasite host cell egress, outer membrane motility, invasion, and cell division. Results Several bioinformatics online servers were employed to analyze and predict the important properties of CDPK4 protein. The findings revealed that CDPK4 peptide has 1158 amino acid residues with average molecular weight (MW) of 126.331 KDa. The aliphatic index and GRAVY for this protein were estimated at 66.82 and - 0.650, respectively. The findings revealed that the CDPK4 protein comprised 30.14 and 34.97 alpha-helix, 59.84 and 53.54 random coils, and 10.02 and 11.49 extended strand with SOPMA and GOR4 tools, respectively. Ramachandran plot output showed 87.87, 8.40, and 3.73 of amino acid residues in the favored, allowed, and outlier regions, respectively. Also, several potential B and T-cell epitopes were predicted for CDPK4 protein through different bioinformatics tools. Also, antigenicity and allergenicity evaluation demonstrated that this protein has immunogenic and non-allergenic nature. This paper presents a basis for further studies, thereby provides a fundamental basis for the development of an effective vaccine against T. gondii infection

Almost-Tight Distributed Minimum Cut Algorithms

We study the problem of computing the minimum cut in a weighted distributed message-passing networks (the CONGEST model). Let $\lambda$ be the minimum cut, $n$ be the number of nodes in the network, and $D$ be the network diameter. Our algorithm can compute $\lambda$ exactly in $O((\sqrt{n} \log^{*} n+D)\lambda^4 \log^2 n)$ time. To the best of our knowledge, this is the first paper that explicitly studies computing the exact minimum cut in the distributed setting. Previously, non-trivial sublinear time algorithms for this problem are known only for unweighted graphs when $\lambda\leq 3$ due to Pritchard and Thurimella's $O(D)$-time and $O(D+n^{1/2}\log^* n)$-time algorithms for computing $2$-edge-connected and $3$-edge-connected components. By using the edge sampling technique of Karger's, we can convert this algorithm into a $(1+\epsilon)$-approximation $O((\sqrt{n}\log^{*} n+D)\epsilon^{-5}\log^3 n)$-time algorithm for any $\epsilon>0$. This improves over the previous $(2+\epsilon)$-approximation $O((\sqrt{n}\log^{*} n+D)\epsilon^{-5}\log^2 n\log\log n)$-time algorithm and $O(\epsilon^{-1})$-approximation $O(D+n^{\frac{1}{2}+\epsilon} \mathrm{poly}\log n)$-time algorithm of Ghaffari and Kuhn. Due to the lower bound of $\Omega(D+n^{1/2}/\log n)$ by Das Sarma et al. which holds for any approximation algorithm, this running time is tight up to a $\mathrm{poly}\log n$ factor. To get the stated running time, we developed an approximation algorithm which combines the ideas of Thorup's algorithm and Matula's contraction algorithm. It saves an $\epsilon^{-9}\log^{7} n$ factor as compared to applying Thorup's tree packing theorem directly. Then, we combine Kutten and Peleg's tree partitioning algorithm and Karger's dynamic programming to achieve an efficient distributed algorithm that finds the minimum cut when we are given a spanning tree that crosses the minimum cut exactly once

Non conservative Abelian sandpile model with BTW toppling rule

A non conservative Abelian sandpile model with BTW toppling rule introduced in [Tsuchiya and Katori, Phys. Rev. E {\bf 61}, 1183 (2000)] is studied. Using a scaling analysis of the different energy scales involved in the model and numerical simulations it is shown that this model belong to a universality class different from that of previous models considered in the literature.Comment: RevTex, 5 pages, 6 ps figs, Minor change

Anthracnose: The sophisticated rot

The mold fungus Colletotrichum graminicola causes anthracnose, one of the most economically damaging corn diseases worldwide. Anthracnose can occur either as a stalk rot (ASR), or a leaf blight (ALB) (4; 27). The leaf blight phase is generally insignificant in North America as a cause of yield loss, although in the tropics and subtropics it is much more important. Resistance to ASR is usually not correlated with resistance to ALB, complicating efforts to breed resistant corn varieties (2; 4). Resistance to ASR and ALB is mostly quantitative, although sources of major gene resistance have been described (10; 29). Hybrids containing some of these major-gene resistance sources are likely to become available for management of ASR in the near future