Global energetic neutral atom (ENA) measurements and their association with the Dst index

We present a new global magnetospheric index that measures the intensity of the Earth\u27s ring current through energetic neutral atoms (ENAs). We have named it the Global Energetic Neutral Index (GENI), and it is derived from ENA measurements obtained by the Imaging Proton Spectrometer (IPS), part of the Comprehensive Energetic Particle and Pitch Angle Distribution (CEPPAD) experiment on the POLAR satellite. GENI provides a simple orbit-independent global sum of ENAs measured with IPS. Actual ENA measurements for the same magnetospheric state look different when seen from different points in the POLAR orbit. In addition, the instrument is sensitive to weak ion populations in the polar cap, as well as cosmic rays. We have devised a method for removing the effects of cosmic rays and weak ion fluxes, in order to produce an image of “pure” ENA counts. We then devised a method of normalizing the ENA measurements to remove the orbital bias effect. The normalized data were then used to produce the GENI. We show, both experimentally and theoretically the approximate proportionality between the GENI and the Dst index. In addition we discuss possible implications of this relation. Owing to the high sensitivity of IPS to ENAs, we can use these data to explore the ENA/Dst relationship not only during all phases of moderate geomagnetic storms, but also during quiescent ring current periods

Borderline Over-sampling for Imbalanced Data Classification

Traditional classification algorithms, in many times, perform poorly on imbalanced data sets in which some classes are heavily outnumbered by the remaining classes. For this kind of data, minority class instances, which are usually much more of interest, are often misclassified. The paper proposes a method to deal with them by changing class distribution through over-sampling at the borderline between the minority class and the majority class of the data set. A Support Vector Machines (SVMs) classifier then is trained to predict new unknown instances. Compared to other over-sampling methods, the proposed method focuses only on the minority class instances lying around the borderline due to the fact that this area is most crucial for establishing the decision boundary. Furthermore, new instances will be generated in such a manner that minority class area will be expanded further toward the side of the majority class at the places where there appear few majority class instances. Experimental results show that the proposed method can achieve better performance than some other over-sampling methods, especially with data sets having low degree of overlap due to its ability of expanding minority class area in such cases

Development of the Drive Dozing Prevention Technique Using a Sensor Installed in the Seat for Detecting the Driver’s Condition

International audienceIn this study, to propose a new data acquisition method for detecting the dozing symptom during wakeful state of a driver, magnetic and pneumatic sensors for extracting biological signals from the driver under the dynamic seated condition, a suspension with a combination of a magnetic spring and a damper to avoid cruel disturbance input from the floor are developed. To estimate emerging timing of sleep detecting signal, chaos analysis was employed which yields the largest Lyapunov exponent and the power from measured pulse waves. By making use of the information of the sleep herald phenomenon and sleep latent time, the relation of sleep latent time with medical parameters closely related to a muscle fatigue was found

A Superstabilizing log⁡(n)\log(n)-Approximation Algorithm for Dynamic Steiner Trees

In this paper we design and prove correct a fully dynamic distributed algorithm for maintaining an approximate Steiner tree that connects via a minimum-weight spanning tree a subset of nodes of a network (referred as Steiner members or Steiner group) . Steiner trees are good candidates to efficiently implement communication primitives such as publish/subscribe or multicast, essential building blocks for the new emergent networks (e.g. P2P, sensor or adhoc networks). The cost of the solution returned by our algorithm is at most $\log |S|$ times the cost of an optimal solution, where $S$ is the group of members. Our algorithm improves over existing solutions in several ways. First, it tolerates the dynamism of both the group members and the network. Next, our algorithm is self-stabilizing, that is, it copes with nodes memory corruption. Last but not least, our algorithm is \emph{superstabilizing}. That is, while converging to a correct configuration (i.e., a Steiner tree) after a modification of the network, it keeps offering the Steiner tree service during the stabilization time to all members that have not been affected by this modification

Self-stabilizing algorithms for Connected Vertex Cover and Clique decomposition problems

In many wireless networks, there is no fixed physical backbone nor centralized network management. The nodes of such a network have to self-organize in order to maintain a virtual backbone used to route messages. Moreover, any node of the network can be a priori at the origin of a malicious attack. Thus, in one hand the backbone must be fault-tolerant and in other hand it can be useful to monitor all network communications to identify an attack as soon as possible. We are interested in the minimum \emph{Connected Vertex Cover} problem, a generalization of the classical minimum Vertex Cover problem, which allows to obtain a connected backbone. Recently, Delbot et al.~\cite{DelbotLP13} proposed a new centralized algorithm with a constant approximation ratio of $2$ for this problem. In this paper, we propose a distributed and self-stabilizing version of their algorithm with the same approximation guarantee. To the best knowledge of the authors, it is the first distributed and fault-tolerant algorithm for this problem. The approach followed to solve the considered problem is based on the construction of a connected minimal clique partition. Therefore, we also design the first distributed self-stabilizing algorithm for this problem, which is of independent interest

Rendezvous of Two Robots with Constant Memory

We study the impact that persistent memory has on the classical rendezvous problem of two mobile computational entities, called robots, in the plane. It is well known that, without additional assumptions, rendezvous is impossible if the entities are oblivious (i.e., have no persistent memory) even if the system is semi-synchronous (SSynch). It has been recently shown that rendezvous is possible even if the system is asynchronous (ASynch) if each robot is endowed with O(1) bits of persistent memory, can transmit O(1) bits in each cycle, and can remember (i.e., can persistently store) the last received transmission. This setting is overly powerful. In this paper we weaken that setting in two different ways: (1) by maintaining the O(1) bits of persistent memory but removing the communication capabilities; and (2) by maintaining the O(1) transmission capability and the ability to remember the last received transmission, but removing the ability of an agent to remember its previous activities. We call the former setting finite-state (FState) and the latter finite-communication (FComm). Note that, even though its use is very different, in both settings, the amount of persistent memory of a robot is constant. We investigate the rendezvous problem in these two weaker settings. We model both settings as a system of robots endowed with visible lights: in FState, a robot can only see its own light, while in FComm a robot can only see the other robot's light. We prove, among other things, that finite-state robots can rendezvous in SSynch, and that finite-communication robots are able to rendezvous even in ASynch. All proofs are constructive: in each setting, we present a protocol that allows the two robots to rendezvous in finite time.Comment: 18 pages, 3 figure

Apparent age of deposition of meta-carbonate rocks from Sør Rondane Mountains, East Antarctica

第2回極域科学シンポジウム/第31回極域地学シンポジウム 11月17日（木） 国立極地研究所　2階大会議

EGFR is required for Wnt9a-Fzd9b signalling specificity in haematopoietic stem cells.

Wnt signalling drives many processes in development, homeostasis and disease; however, the role and mechanism of individual ligand-receptor (Wnt-Frizzled (Fzd)) interactions in specific biological processes remain poorly understood. Wnt9a is specifically required for the amplification of blood progenitor cells during development. Using genetic studies in zebrafish and human embryonic stem cells, paired with in vitro cell biology and biochemistry, we determined that Wnt9a signals specifically through Fzd9b to elicit β-catenin-dependent Wnt signalling that regulates haematopoietic stem and progenitor cell emergence. We demonstrate that the epidermal growth factor receptor (EGFR) is required as a cofactor for Wnt9a-Fzd9b signalling. EGFR-mediated phosphorylation of one tyrosine residue on the Fzd9b intracellular tail in response to Wnt9a promotes internalization of the Wnt9a-Fzd9b-LRP signalosome and subsequent signal transduction. These findings provide mechanistic insights for specific Wnt-Fzd signals, which will be crucial for specific therapeutic targeting and regenerative medicine

Enhancing the lateral-flow immunoassay for viral detection using an aqueous two-phase micellar system

Availability of a rapid, accurate, and reliable point-of-care (POC) device for detection of infectious agents and pandemic pathogens, such as swine-origin influenza A (H1N1) virus, is crucial for effective patient management and outbreak prevention. Due to its ease of use, rapid processing, and minimal power and laboratory equipment requirements, the lateral-flow (immuno)assay (LFA) has gained much attention in recent years as a possible solution. However, since the sensitivity of LFA has been shown to be inferior to that of the gold standards of pathogen detection, namely cell culture and real-time PCR, LFA remains an ineffective POC assay for preventing pandemic outbreaks. A practical solution for increasing the sensitivity of LFA is to concentrate the target agent in a solution prior to the detection step. In this study, an aqueous two-phase micellar system comprised of the nonionic surfactant Triton X-114 was investigated for concentrating a model virus, namely bacteriophage M13 (M13), prior to LFA. The volume ratio of the two coexisting micellar phases was manipulated to concentrate M13 in the top, micelle-poor phase. The concentration step effectively improved the M13 detection limit of the assay by tenfold from 5 × 108 plaque forming units (pfu)/mL to 5 × 107 pfu/mL. In the future, the volume ratio can be further manipulated to yield a greater concentration of a target virus and further decrease the detection limits of the LFA. Figure A schematic representation of concentrating viruses with an aqueous two-phase micellar system containing Triton X-114 surfactant prior to the detection of the virus through the lateral-flow immunoassa