The appearance of a compact jet in the soft-intermediate state of 4U 1543-47

Recent advancements in the understanding of jet-disc coupling in black hole candidate X-ray binaries (BHXBs) have provided close links between radio jet emission and X-ray spectral and variability behaviour. In 'soft' X-ray states the jets are suppressed, but the current picture lacks an understanding of the X-ray features associated with the quenching or recovering of these jets. Here we show that a brief, ~4 day infrared (IR) brightening during a predominantly soft X-ray state of the BHXB 4U 1543-47 is contemporaneous with a strong X-ray Type B quasi-periodic oscillation (QPO), a slight spectral hardening and an increase in the rms variability, indicating an excursion to the soft-intermediate state (SIMS). This IR 'flare' has a spectral index consistent with optically thin synchrotron emission and most likely originates from the steady, compact jet. This core jet emitting in the IR is usually only associated with the hard state, and its appearance during the SIMS places the 'jet line' between the SIMS and the soft state in the hardness-intensity diagram for this source. IR emission is produced in a small region of the jets close to where they are launched (~ 0.1 light-seconds), and the timescale of the IR flare in 4U 1543-47 is far too long to be caused by a single, discrete ejection. We also present a summary of the evolution of the jet and X-ray spectral/variability properties throughout the whole outburst, constraining the jet contribution to the X-ray flux during the decay.Comment: Accepted to MNRAS. 11 pages, 6 figure

Designing a clinical decision support system for managing and treating patients with the chief complaint of vertigo

Background: One of the challenging issues for emergency specialists is the etiology of dizziness. Using portable software installing in the mobile cell can help the clinicians to reduce the effects of confounders in emergency treatment of patients. Methods: This study was conducted in 2017 in the Department of Emergency, Rasoul-e Akram hospital, Tehran, Iran. After designing the management protocol for patients with vertigo based on the literature and standards, the validity of the protocol was approved by the expert panel. A number of 190 patients with vertigo were diagnosed using two methods for treatment and management of the disease. The first group were assessed using designed clinical decision support system, and the second group were assessed using routine method. Treatment duration, maintenance duration, and the differences between the primary and the final diagnosis were compared between the groups. Findings: Differences between the primary and the final diagnosis were significant among both groups (P < 0.050). Mean treatment duration was 3.38 and 4.96 hours in the first and second groups using support system and routine methods, respectively (P < 0.001). Mean hospitalization period was significantly shorter in support system group (9.37 hours) compared to routine method group (11.17 hours) (P < 0.001). The level of physician satisfaction with the support system was average (47.9). Conclusion: Using clinical decision support system can greatly help physicians to improve the diagnosis, decrease the hospitalization period, and manage the patients with the chief complaint of vertigo much better. © 2018, Isfahan University of Medical Sciences(IUMS). All rights reserved

Programming Protocol-Independent Packet Processors

P4 is a high-level language for programming protocol-independent packet processors. P4 works in conjunction with SDN control protocols like OpenFlow. In its current form, OpenFlow explicitly specifies protocol headers on which it operates. This set has grown from 12 to 41 fields in a few years, increasing the complexity of the specification while still not providing the flexibility to add new headers. In this paper we propose P4 as a strawman proposal for how OpenFlow should evolve in the future. We have three goals: (1) Reconfigurability in the field: Programmers should be able to change the way switches process packets once they are deployed. (2) Protocol independence: Switches should not be tied to any specific network protocols. (3) Target independence: Programmers should be able to describe packet-processing functionality independently of the specifics of the underlying hardware. As an example, we describe how to use P4 to configure a switch to add a new hierarchical label

Identification, distribution and incidence of viruses in field-grown cucurbit crops of Iran

A survey of viruses in the major cucurbit-growing areas of 17 provinces in Iran was conducted in 2005 and 2006. A total of 1699 leaf samples were collected from melon, squash, cucumber and watermelon plants showing various virus-like symptoms. Screening for 11 cucurbit viruses by double-antibody sandwich ELISA (DAS-ELISA) or RT-PCR, found that 71% of the samples were infected by at least one virus, of which Cucurbit aphid-borne yellows virus (CABYV) was the most common overall, occurring in 49, 47, 40, and 33% of cucumber, squash, melon, and watermelon samples respectively. The second most common virus on melon and watermelon was Watermelon mosaic virus (WMV) (incidence 30–33%); on cucumber, Cucumber mosaic virus (CMV)(33%); and on squash, Zucchini yellow mosaic virus (ZYMV)(38%). To our knowledge, this is the first report of Melon necrotic spot virus (MNSV) and Zucchini yellow fl eck virus (ZYFV) in Iran. Mixed infections occurred in 49% of symptomatic samples. Mixed infections were relatively frequent in squash (58%) and melon (55%). The most frequent double infections were WMV+CABYV and ZYMV+CABYV in melon, squash and cucumber, followed by WMV+ZYMV. In watermelon, the most frequent double infection was WMV+ZYMV, followed by WMV+CABYV. The high frequency of CABYV, WMV and ZYMV in the samples assayed on all four cucurbit crops and in all areas surveyed, as well as the detection of Watermelon chlorotic stunt virus (WmCSV) and Cucumber vein yellowing virus (CVYV) in northern and southern Iran, suggest that these viruses represent a potential threat to cucurbit crops in Iran

Graph Annotations in Modeling Complex Network Topologies

The coarsest approximation of the structure of a complex network, such as the Internet, is a simple undirected unweighted graph. This approximation, however, loses too much detail. In reality, objects represented by vertices and edges in such a graph possess some non-trivial internal structure that varies across and differentiates among distinct types of links or nodes. In this work, we abstract such additional information as network annotations. We introduce a network topology modeling framework that treats annotations as an extended correlation profile of a network. Assuming we have this profile measured for a given network, we present an algorithm to rescale it in order to construct networks of varying size that still reproduce the original measured annotation profile. Using this methodology, we accurately capture the network properties essential for realistic simulations of network applications and protocols, or any other simulations involving complex network topologies, including modeling and simulation of network evolution. We apply our approach to the Autonomous System (AS) topology of the Internet annotated with business relationships between ASs. This topology captures the large-scale structure of the Internet. In depth understanding of this structure and tools to model it are cornerstones of research on future Internet architectures and designs. We find that our techniques are able to accurately capture the structure of annotation correlations within this topology, thus reproducing a number of its important properties in synthetically-generated random graphs

MACEDON: methodology for automatically creating, evaluating, and designing overlay networks

Currently, researchers designing and implementing large-scale overlay services employ disparate techniques at each stage in the production cycle: design, implementation, experimentation, and evaluation. As a result, complex and tedious tasks are often duplicated leading to ineffective resource use and difficulty in fairly comparing competing algorithms. In this paper, we present MACEDON, an infrastructure that provides facilities to: i) specify distributed algorithms in a concise domain-specific language; ii) generate code that executes in popular evaluation infrastructures and in live networks; iii) leverage an overlay-generic API to simplify the interoperability of algorithm implementations and applications; and iv) enable consistent experimental evaluation. We have used MACEDON to implement and evaluate a number of algorithms, including AMMO, Bullet, Chord, NICE, Overcast, Pastry, Scribe, and SplitStream, typically with only a few hundred lines of MACEDON code. Using our infrastructure, we are able to accurately reproduce or exceed published results and behavior demonstrated by current publicly available implementation

Self-Organizing Subsets: From Each According to His Abilities, To Each According to His Needs

The key principles behind current peer-to-peer research include fully distributing service functionality among all nodes participating in the system and routing individual requests based on a small amount of locally maintained state. The goals extend much further than just improving raw system performance: such systems must survive massive concurrent failures, denial of service attacks, etc. These efforts are uncovering fundamental issues in the design and deployment of distributed services. However, the work ignores a number of practical issues with the deployment of general peer-to-peer systems, including i) the overhead of maintaining consistency among peers replicating mutable data and ii) the resource waste incurred by the replication necessary to counteract the loss in locality that results from random content distribution. This position paper argues that the key challenge in peer-to-peer research is not to distribute service functions among all participants, but rather to distribute functions to meet target levels of availability, survivability, and performance. In many cases, only a subset of participating hosts should take on server roles. The benefit of peerto- peer architectures then comes from massive diversity rather than massive decentralization: with high probability, there is always some node available to provide the required functionality should the need arise

Using Random Subsets to Build Scalable Network Services

In this paper, we argue that a broad range of large-scale network services would benefit from a scalable mechanism for delivering state about a random subset of global participants. Key to this approach is ensuring that membership in the subset changes periodically and with uniform representation over all participants. Random subsets could help overcome inherent scaling limitations to services that maintain global state and perform global network probing. It could further improve the routing performance of peer-to-peer distributed hash tables by locating topologically-close nodes. This paper presents the design, implementation, and evaluation of RanSub, a scalable protocol for delivering such state. As a first demonstration of the RanSub utility, we construct SARO, a scalable and adaptive application-layer overlay tree. SARO uses RanSub state information tolocate appropriate peers for meeting application-specific delay and bandwidth targets and to dynamically adapt to changing network conditions. A large-scale evaluation of 1000 overlay nodes participating in an emulated 20,000- node wide-area network topology demonstrate both the adaptivity and scalability (in terms of per-node state and network overhead) of both RanSub and SARO. Finally, we use an existing streaming media server to distribute content through SARO running on top of the PlanetLab Internet testbed

Hyperbolic Geometry of Complex Networks

We develop a geometric framework to study the structure and function of complex networks. We assume that hyperbolic geometry underlies these networks, and we show that with this assumption, heterogeneous degree distributions and strong clustering in complex networks emerge naturally as simple reflections of the negative curvature and metric property of the underlying hyperbolic geometry. Conversely, we show that if a network has some metric structure, and if the network degree distribution is heterogeneous, then the network has an effective hyperbolic geometry underneath. We then establish a mapping between our geometric framework and statistical mechanics of complex networks. This mapping interprets edges in a network as non-interacting fermions whose energies are hyperbolic distances between nodes, while the auxiliary fields coupled to edges are linear functions of these energies or distances. The geometric network ensemble subsumes the standard configuration model and classical random graphs as two limiting cases with degenerate geometric structures. Finally, we show that targeted transport processes without global topology knowledge, made possible by our geometric framework, are maximally efficient, according to all efficiency measures, in networks with strongest heterogeneity and clustering, and that this efficiency is remarkably robust with respect to even catastrophic disturbances and damages to the network structure

Obesity-dependent changes in interstitial ECM mechanics promote breast tumorigenesis.

Obesity and extracellular matrix (ECM) density are considered independent risk and prognostic factors for breast cancer. Whether they are functionally linked is uncertain. We investigated the hypothesis that obesity enhances local myofibroblast content in mammary adipose tissue and that these stromal changes increase malignant potential by enhancing interstitial ECM stiffness. Indeed, mammary fat of both diet- and genetically induced mouse models of obesity were enriched for myofibroblasts and stiffness-promoting ECM components. These differences were related to varied adipose stromal cell (ASC) characteristics because ASCs isolated from obese mice contained more myofibroblasts and deposited denser and stiffer ECMs relative to ASCs from lean control mice. Accordingly, decellularized matrices from obese ASCs stimulated mechanosignaling and thereby the malignant potential of breast cancer cells. Finally, the clinical relevance and translational potential of our findings were supported by analysis of patient specimens and the observation that caloric restriction in a mouse model reduces myofibroblast content in mammary fat. Collectively, these findings suggest that obesity-induced interstitial fibrosis promotes breast tumorigenesis by altering mammary ECM mechanics with important potential implications for anticancer therapies