Adaptive Partitioning for Large-Scale Dynamic Graphs

Abstract—In the last years, large-scale graph processing has gained increasing attention, with most recent systems placing particular emphasis on latency. One possible technique to improve runtime performance in a distributed graph processing system is to reduce network communication. The most notable way to achieve this goal is to partition the graph by minimizing the num-ber of edges that connect vertices assigned to different machines, while keeping the load balanced. However, real-world graphs are highly dynamic, with vertices and edges being constantly added and removed. Carefully updating the partitioning of the graph to reflect these changes is necessary to avoid the introduction of an extensive number of cut edges, which would gradually worsen computation performance. In this paper we show that performance degradation in dynamic graph processing systems can be avoided by adapting continuously the graph partitions as the graph changes. We present a novel highly scalable adaptive partitioning strategy, and show a number of refinements that make it work under the constraints of a large-scale distributed system. The partitioning strategy is based on iterative vertex migrations, relying only on local information. We have implemented the technique in a graph processing system, and we show through three real-world scenarios how adapting graph partitioning reduces execution time by over 50 % when compared to commonly used hash-partitioning. I

Free-form Light Actuators - Fabrication and Control of Actuation in Microscopic Scale

Liquid crystalline elastomers (LCEs) are smart materials capable of reversible shape-change in response to external stimuli, and have attracted researchers' attention in many fields. Most of the studies focused on macroscopic LCE structures (films, fibers) and their miniaturization is still in its infancy. Recently developed lithography techniques, e.g., mask exposure and replica molding, only allow for creating 2D structures on LCE thin films. Direct laser writing (DLW) opens access to truly 3D fabrication in the microscopic scale. However, controlling the actuation topology and dynamics at the same length scale remains a challenge. In this paper we report on a method to control the liquid crystal (LC) molecular alignment in the LCE microstructures of arbitrary three-dimensional shape. This was made possible by a combination of direct laser writing for both the LCE structures as well as for micrograting patterns inducing local LC alignment. Several types of grating patterns were used to introduce different LC alignments, which can be subsequently patterned into the LCE structures. This protocol allows one to obtain LCE microstructures with engineered alignments able to perform multiple opto-mechanical actuation, thus being capable of multiple functionalities. Applications can be foreseen in the fields of tunable photonics, micro-robotics, lab-on-chip technology and others

A software-based self test of CUDA Fermi GPUs

Nowadays, Graphical Processing Units (GPUs) have become increasingly popular due to their high computational power and low prices. This makes them particularly suitable for high-performance computing applications, like data elaboration and financial computation. In these fields, high efficient test methodologies are mandatory. One of the most effective ways to detect and localize hardware faults in GPUs is a Software-Based-Self-Test methodology (SBST). In this paper a fully comprehensive SBST and fault localization methodology for GPUs is presented. This novel approach exploits different custom test strategies for each component inside the GPU architecture. Such strategies guarantee both permanent fault detection and accurate fault localization

Increasing the robustness of CUDA Fermi GPU-based systems

Nowadays Graphical processing Units (GPUs) have become increasingly popular due to their high computational power and low prices. This makes them particularly suitable for high-performance computing applications, like data elaboration and image processing. In these fields, the capability of properly work even in presence of faults is mandatory. This paper presents an innovative approach, that combines a Software Based Self Test & Diagnosis (SBSTD) methodology with a fault mitigation strategy, to increase the robustness of a CUDA Fermi GPU-based system

The endocannabinoid 2-AG controls skeletal muscle cell differentiation via CB1 receptor-dependent inhibition of Kv7 channels.

Little is known of the involvement of endocannabinoids and cannabinoid receptors in skeletal muscle cell differentiation. We report that, due to changes in the expression of genes involved in its metabolism, the levels of the endocannabinoid 2-arachidonoylglycerol (2-AG) are decreased both during myotube formation in vitro from murine C2C12 myoblasts and during mouse muscle growth in vivo. The endocannabinoid, as well as the CB1 agonist arachidonoyl-2-chloroethylamide, prevent myotube formation in a manner antagonized by CB1 knockdown and by CB1 antagonists, which, per se, instead stimulate differentiation. Importantly, 2-AG also inhibits differentiation of primary human satellite cells. Muscle fascicles from CB1 knockout embryos contain more muscle fibers, and postnatal mice show muscle fibers of an increased diameter relative to wild-type littermates. Inhibition of Kv7.4 channel activity, which plays a permissive role in myogenesis and depends on phosphatidylinositol 4,5-bisphosphate (PIP2), underlies the effects of 2-AG. We find that CB1 stimulation reduces both total and Kv7.4-bound PIP2 levels in C2C12 cells and inhibits Kv7.4 currents in transfected CHO cells. We suggest that 2-AG is an endogenous repressor of myoblast differentiation via CB1-mediated inhibition of Kv7.4 channels

Wildlife Reservoirs of Canine Distemper Virus Resulted in a Major Outbreak in Danish Farmed Mink (<em>Neovison vison</em>)

A major outbreak of canine distemper virus (CDV) in Danish farmed mink (Neovison vison) started in the late summer period of 2012. At the same time, a high number of diseased and dead wildlife species such as foxes, raccoon dogs, and ferrets were observed. To track the origin of the outbreak virus full-length sequencing of the receptor binding surface protein hemagglutinin (H) was performed on 26 CDV's collected from mink and 10 CDV's collected from wildlife species. Subsequent phylogenetic analyses showed that the virus circulating in the mink farms and wildlife were highly identical with an identity at the nucleotide level of 99.45% to 100%. The sequences could be grouped by single nucleotide polymorphisms according to geographical distribution of mink farms and wildlife. The signaling lymphocytic activation molecule (SLAM) receptor binding region in most viruses from both mink and wildlife contained G at position 530 and Y at position 549; however, three mink viruses had an Y549H substitution. The outbreak viruses clustered phylogenetically in the European lineage and were highly identical to wildlife viruses from Germany and Hungary (99.29% – 99.62%). The study furthermore revealed that fleas (Ceratophyllus sciurorum) contained CDV and that vertical transmission of CDV occurred in a wild ferret. The study provides evidence that wildlife species, such as foxes, play an important role in the transmission of CDV to farmed mink and that the virus may be maintained in the wild animal reservoir between outbreaks

xDGP: A Dynamic Graph Processing System with Adaptive Partitioning

13 pagesMany real-world systems, such as social networks, rely on mining efficiently large graphs, with hundreds of millions of vertices and edges. This volume of information requires partitioning the graph across multiple nodes in a distributed system. This has a deep effect on performance, as traversing edges cut between partitions incurs a significant performance penalty due to the cost of communication. Thus, several systems in the literature have attempted to improve computational performance by enhancing graph partitioning, but they do not support another characteristic of real-world graphs: graphs are inherently dynamic, their topology evolves continuously, and subsequently the optimum partitioning also changes over time. In this work, we present the first system that dynamically repartitions massive graphs to adapt to structural changes. The system optimises graph partitioning to prevent performance degradation without using data replication. The system adopts an iterative vertex migration algorithm that relies on local information only, making complex coordination unnecessary. We show how the improvement in graph partitioning reduces execution time by over 50%, while adapting the partitioning to a large number of changes to the graph in three real-world scenarios

The impact of bilingualism on executive functions in children and adolescents: a systematic review based on the PRISMA method

Approximately half of the world's population is bilingual or multilingual. The bilingual advantage theory claims that the constant need to control both known languages, that are always active in the brain, to use the one suitable for each specific context improves cognitive functions and specifically executive functions. However, some authors do not agree on the bilingual effect, given the controversial results of studies on this topic. This systematic review aims to summarize the results of studies on the relationship between bilingualism and executive functions. The review was conducted according to PRISMA-statement through searches in the scientific database PsychINFO, PsycARTICLES, MEDLINE, and PUBMED. Studies included in this review had at least one bilingual and monolingual group, participants aged between 5 and 17 years, and at least one executive function measure. Studies on second language learners, multilingual people, and the clinical population were excluded. Fifty-three studies were included in the systematic review. Evidence supporting the bilingual effect seems to appear when assessing inhibition and cognitive flexibility, but to disappear when working memory is considered. The inconsistent results of the studies do not allow drawing definite conclusions on the bilingual effect. Further studies are needed; they should consider the role of some modulators (e.g., language history and context, methodological differences) on the observed results

Rabies and canine distemper virus epidemics in the red fox population of Northern Italy (2006–2010)

Since 2006 the red fox (Vulpes vulpes) population in north-eastern Italy has experienced an epidemic of canine distemper virus (CDV). Additionally, in 2008, after a thirteen-year absence from Italy, fox rabies was re-introduced in the Udine province at the national border with Slovenia. Disease intervention strategies are being developed and implemented to control rabies in this area and minimise risk to human health. Here we present empirical data and the epidemiological picture relating to these epidemics in the period 2006-2010. Of important significance for epidemiological studies of wild animals, basic mathematical models are developed to exploit information collected from the surveillance program on dead and/or living animals in order to assess the incidence of infection. These models are also used to estimate the rate of transmission of both diseases and the rate of vaccination, while correcting for a bias in early collection of CDV samples. We found that the rate of rabies transmission was roughly twice that of CDV, with an estimated effective contact between infected and susceptible fox leading to a new infection occurring once every 3 days for rabies, and once a week for CDV. We also inferred that during the early stage of the CDV epidemic, a bias in the monitoring protocol resulted in a positive sample being almost 10 times more likely to be collected than a negative sample. We estimated the rate of intake of oral vaccine at 0.006 per day, allowing us to estimate that roughly 68% of the foxes would be immunised. This was confirmed by field observations. Finally we discuss the implications for the eco-epidemiological dynamics of both epidemics in relation to control measures