Psi: A Silicon Compiler for Very Fast Protocol Processing

Conventional protocols implementations typically fall short, by a few orders of magnitude, of supporting the speeds afforded by high-speed optical transmission media. This protocol processing bottleneck is a key hurdle in taking advantage of the opportunities presented by high-speed communications. This paper describes PSi, a silicon compiler that transforms formal protocol specifications into efficient VLSI implementations. PSi takes advantage of the parallelisms intrinsic to a given protocol to accomplish very high-speed implementations. Initial application of PSi to the IEEE 802.2 (logical link control) leads to processing rates in the order of 106 packets per second (p/s). The 802.2 was selected as a benchmark of complexity; light-weight protocols can accomplish even higher processing rates, reaching the limits set by chip clock rates (i.e., a packet per cycle). These speeds significantly exceed typical of software implementations (up to a few hundred p/s) or special hardware-assisted implementations (up to a few thousands p/s). More importantly, at these rates when the packet size is 103-4 bits the protocol throughput of 109-10 bits/sec reaches the limiting throughput afforded by memory technology. Thus, the protocol processing bottleneck is pushed to the ultimate bounds set by VLSI technologies

Developing a multiple-document-processing performance assessment for epistemic literacy

The LAK15 theme “shifts the focus from data to impact”, noting the potential for Learning Analytics based on existing technologies to have scalable impact on learning for people of all ages. For such demand and potential in scalability to be met the challenges of addressing higher-order thinking skills should be addressed. This paper discuses one such approach – the creation of an analytic and task model to probe epistemic cognition in complex literacy tasks. The research uses existing technologies in novel ways to build a conceptually grounded model of trace-indicators for epistemic-commitments in information seeking behaviors. We argue that such an evidence centered approach is fundamental to realizing the potential of analytics, which should maintain a strong association with learning theory

The AFLOW Fleet for Materials Discovery

The traditional paradigm for materials discovery has been recently expanded to incorporate substantial data driven research. With the intent to accelerate the development and the deployment of new technologies, the AFLOW Fleet for computational materials design automates high-throughput first principles calculations, and provides tools for data verification and dissemination for a broad community of users. AFLOW incorporates different computational modules to robustly determine thermodynamic stability, electronic band structures, vibrational dispersions, thermo-mechanical properties and more. The AFLOW data repository is publicly accessible online at aflow.org, with more than 1.7 million materials entries and a panoply of queryable computed properties. Tools to programmatically search and process the data, as well as to perform online machine learning predictions, are also available.Comment: 14 pages, 8 figure

Leukocytes Breach Endothelial Barriers by Insertion of Nuclear Lobes and Disassembly of Endothelial Actin Filaments

Israel Science Foundation (grant 87/12) Flight Attendant Medical Research Institute Foundation (FAMRI) (grant FAMRI032001_CoE), USA Minerva Foundation, Germany Wellcome Trust (grant 098291/Z/12/Z to S.N.

Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization

We present a practical implementation of an optimal first-order method, due to Nesterov, for large-scale total variation regularization in tomographic reconstruction, image deblurring, etc. The algorithm applies to $\mu$-strongly convex objective functions with $L$-Lipschitz continuous gradient. In the framework of Nesterov both $\mu$ and $L$ are assumed known -- an assumption that is seldom satisfied in practice. We propose to incorporate mechanisms to estimate locally sufficient $\mu$ and $L$ during the iterations. The mechanisms also allow for the application to non-strongly convex functions. We discuss the iteration complexity of several first-order methods, including the proposed algorithm, and we use a 3D tomography problem to compare the performance of these methods. The results show that for ill-conditioned problems solved to high accuracy, the proposed method significantly outperforms state-of-the-art first-order methods, as also suggested by theoretical results.Comment: 23 pages, 4 figure

Statin Therapy and Risk of Developing Type 2 Diabetes: A Meta-Analysis

OBJECTIVE: Although statin therapy reduces cardiovascular risk, its relationship with the development of diabetes is controversial. The first study (West of Scotland Coronary Prevention Study [WOSCOPS]) that evaluated this association reported a small protective effect but used nonstandardized criteria for diabetes diagnosis. However, results from subsequent hypothesis-testing trials have been inconsistent. The aim of this meta-analysis is to evaluate the possible effect of statin therapy on incident diabetes. RESEARCH DESIGN AND METHODS: A systematic literature search for randomized statin trials that reported data on diabetes through February 2009 was conducted using specific search terms. In addition to the hypothesis-generating data from WOSCOPS, hypothesis-testing data were available from the Heart Protection Study (HPS), the Long-Term Intervention with Pravastatin in Ischemic Disease (LIPID) Study, the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT), the Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER), and the Controlled Rosuvastatin Multinational Study in Heart Failure (CORONA), together including 57,593 patients with mean follow-up of 3.9 years during which 2,082 incident diabetes cases accrued. Weighted averages were reported as risk ratios (RRs) with 95% CIs using a random-effects model. Statistical heterogeneity scores were assessed with the Q and I2 statistic.RESULTS In the meta-analysis of the hypothesis-testing trials, we observed a small increase in diabetes risk (RR 1.13 [95% CI 1.03–1.23]) with no evidence of heterogeneity across trials. However, this estimate was attenuated and no longer significant when the hypothesis-generating trial WOSCOPS was included (1.06 [0.93–1.25]) and also resulted in significant heterogeneity (Q 11.8 [5 d.f.], P = 0.03, I2 = 57.7%). CONCLUSIONS: Although statin therapy greatly lowers vascular risk, including among those with and at risk for diabetes, the relationship of statin therapy to incident diabetes remains uncertain. Future statin trials should be designed to formally address this issue

Successful removal of a telephone cable, a foreign body through the urethra into the bladder: a case report

The variety of foreign bodies inserted into or externally attached to the genitourinary tract defies imagination and includes all types of objects. The frequency of such cases renders these an important addition to the diseases of the genitourinary organs. The most common motive associated with the insertion of foreign bodies into the genitourinary tract is sexual or erotic in nature. In adults this is commonly caused by the insertion of objects used for masturbation and is frequently associated with mental health disorders. We report a case of insertion of telephone cable wire into the urethra. Our case highlights the importance of good history, clinical examination, relevant radiological investigation and simple measures to solve the problem

Aggregating Centrality Rankings: A Novel Approach to Detect Critical Infrastructure Vulnerabilities

Assessing critical infrastructure vulnerabilities is paramount to arrange efficient plans for their protection. Critical infrastructures are network-based systems hence, they are composed of nodes and edges. The literature shows that node criticality, which is the focus of this paper, can be addressed from different metric-based perspectives (e.g., degree, maximal flow, shortest path). However, each metric provides a specific insight while neglecting others. This paper attempts to overcome this pitfall through a methodology based on ranking aggregation. Specifically, we consider several numerical topological descriptors of the nodes’ importance (e.g., degree, betweenness, closeness, etc.) and we convert such descriptors into ratio matrices; then, we extend the Analytic Hierarchy Process problem to the case of multiple ratio matrices and we resort to a Logarithmic Least Squares formulation to identify an aggregated metric that represents a good tradeoff among the different topological descriptors. The procedure is validated considering the Central London Tube network as a case study

Genome-wide data from medieval German Jews show that the Ashkenazi founder event pre-dated the 14th century

We report genome-wide data for 33 Ashkenazi Jews (AJ), dated to the 14th century, following a salvageexcavation at the medieval Jewish cemetery of Erfurt, Germany. The Erfurt individuals are geneticallysimilar to modern AJ and have substantial Southern European ancestry, but they show more variabilityin Eastern European-related ancestry than modern AJ. A third of the Erfurt individuals carried the samenearly-AJ-specific mitochondrial haplogroup and eight carried pathogenic variants known to affect AJtoday. These observations, together with high levels of runs of homozygosity, suggest that the Erfurtcommunity had already experienced the major reduction in size that affected modern AJ. However, theErfurt bottleneck was more severe, implying substructure in medieval AJ. Together, our results suggestthat the AJ founder event and the acquisition of the main sources of ancestry pre-dated the 14th centuryand highlight late medieval genetic heterogeneity no longer present in modern AJ