Energy Model of Networks-on-Chip and a Bus

A Network-on-Chip (NoC) is an energy-efficient onchip communication architecture for Multi-Processor Systemon-Chip (MPSoC) architectures. In earlier papers we proposed two Network-on-Chip architectures based on packet-switching and circuit-switching. In this paper we derive an energy model for both NoC architectures to predict their energy consumption per transported bit. Both architectures are also compared with a traditional bus architecture. The energy model is primarily needed to find a near optimal run-time mapping (from an energy point of view) of inter-process communication to NoC link

Energy-Efficient NoC for Best-Effort Communication

A Network-on-Chip (NoC) is an energy-efficient on-chip communication architecture forMulti-Processor System-on-Chip (MPSoC) architectures. In an earlier paper we proposed a energy-efficient reconfigurable circuit-switched NoC to reduce the energy consumption compared to a packetswitched NoC. In this paper we investigate a chordal slotted ring and a bus architecture that can be used to handle the best-effort traffic in the system and configure the circuitswitched network. Both architectures are compared on their latency behavior and power consumption. At the same clock frequency, the chordal ring has the major benefit of a lower latency and higher throughput. But the bus has a lower overall power consumption at the same frequency. However, if we tune the frequency of the network to meet the throughput requirements of control network, we see that the ring consumes less energy per transported bit

Review article: A European perspective on wind and storm damage – from the meteorological background to index-based approaches to assess impacts

Wind and windstorms cause severe damage to natural and human-made environments. Thus, wind-related risk assessment is vital for the preparation and mitigation of calamities. However, the cascade of events leading to damage depends on many factors that are environment-specific and the available methods to address wind-related damage often require sophisticated analysis and specialization. Fortunately, simple indices and thresholds are as effective as complex mechanistic models for many applications. Nonetheless, the multitude of indices and thresholds available requires a careful selection process according to the target sector. Here, we first provide a basic background on wind and storm formation and characteristics, followed by a comprehensive collection of both indices and thresholds that can be used to predict the occurrence and magnitude of wind and storm damage. We focused on five key sectors: forests, urban areas, transport, agriculture and wind-based energy production. For each sector we described indices and thresholds relating to physical properties such as topography and land cover but also to economic aspects (e.g. disruptions in transportation or energy production). In the face of increased climatic variability, the promotion of more effective analysis of wind and storm damage could reduce the impact on society and the environment

Proposal for a revised taxonomy of the family Filoviridae: classification, names of taxa and viruses, and virus abbreviations

The taxonomy of the family Filoviridae (marburgviruses and ebolaviruses) has changed several times since the discovery of its members, resulting in a plethora of species and virus names and abbreviations. The current taxonomy has only been partially accepted by most laboratory virologists. Confusion likely arose for several reasons: species names that consist of several words or which (should) contain diacritical marks, the current orthographic identity of species and virus names, and the similar pronunciation of several virus abbreviations in the absence of guidance for the correct use of vernacular names. To rectify this problem, we suggest (1) to retain the current species names Reston ebolavirus, Sudan ebolavirus, and Zaire ebolavirus, but to replace the name Cote d'Ivoire ebolavirus [sic] with Taï Forest ebolavirus and Lake Victoria marburgvirus with Marburg marburgvirus; (2) to revert the virus names of the type marburgviruses and ebolaviruses to those used for decades in the field (Marburg virus instead of Lake Victoria marburgvirus and Ebola virus instead of Zaire ebolavirus); (3) to introduce names for the remaining viruses reminiscent of jargon used by laboratory virologists but nevertheless different from species names (Reston virus, Sudan virus, Taï Forest virus), and (4) to introduce distinct abbreviations for the individual viruses (RESTV for Reston virus, SUDV for Sudan virus, and TAFV for Taï Forest virus), while retaining that for Marburg virus (MARV) and reintroducing that used over decades for Ebola virus (EBOV). Paying tribute to developments in the field, we propose (a) to create a new ebolavirus species (Bundibugyo ebolavirus) for one member virus (Bundibugyo virus, BDBV); (b) to assign a second virus to the species Marburg marburgvirus (Ravn virus, RAVV) for better reflection of now available high-resolution phylogeny; and (c) to create a new tentative genus (Cuevavirus) with one tentative species (Lloviu cuevavirus) for the recently discovered Lloviu virus (LLOV). Furthermore, we explain the etymological derivation of individual names, their pronunciation, and their correct use, and we elaborate on demarcation criteria for each taxon and virus.S

Distinct Patterns of IFITM-Mediated Restriction of Filoviruses, SARS Coronavirus, and Influenza A Virus

Interferon-inducible transmembrane proteins 1, 2, and 3 (IFITM1, 2, and 3) are recently identified viral restriction factors that inhibit infection mediated by the influenza A virus (IAV) hemagglutinin (HA) protein. Here we show that IFITM proteins restricted infection mediated by the entry glycoproteins (GP1,2) of Marburg and Ebola filoviruses (MARV, EBOV). Consistent with these observations, interferon-β specifically restricted filovirus and IAV entry processes. IFITM proteins also inhibited replication of infectious MARV and EBOV. We observed distinct patterns of IFITM-mediated restriction: compared with IAV, the entry processes of MARV and EBOV were less restricted by IFITM3, but more restricted by IFITM1. Moreover, murine Ifitm5 and 6 did not restrict IAV, but efficiently inhibited filovirus entry. We further demonstrate that replication of infectious SARS coronavirus (SARS-CoV) and entry mediated by the SARS-CoV spike (S) protein are restricted by IFITM proteins. The profile of IFITM-mediated restriction of SARS-CoV was more similar to that of filoviruses than to IAV. Trypsin treatment of receptor-associated SARS-CoV pseudovirions, which bypasses their dependence on lysosomal cathepsin L, also bypassed IFITM-mediated restriction. However, IFITM proteins did not reduce cellular cathepsin activity or limit access of virions to acidic intracellular compartments. Our data indicate that IFITM-mediated restriction is localized to a late stage in the endocytic pathway. They further show that IFITM proteins differentially restrict the entry of a broad range of enveloped viruses, and modulate cellular tropism independently of viral receptor expression

DNA methylation-based classification of central nervous system tumours.

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology

Sampling the Solution Space in Genome-Scale Metabolic Networks Reveals Transcriptional Regulation in Key Enzymes

Genome-scale metabolic models are available for an increasing number of organisms and can be used to define the region of feasible metabolic flux distributions. In this work we use as constraints a small set of experimental metabolic fluxes, which reduces the region of feasible metabolic states. Once the region of feasible flux distributions has been defined, a set of possible flux distributions is obtained by random sampling and the averages and standard deviations for each of the metabolic fluxes in the genome-scale model are calculated. These values allow estimation of the significance of change for each reaction rate between different conditions and comparison of it with the significance of change in gene transcription for the corresponding enzymes. The comparison of flux change and gene expression allows identification of enzymes showing a significant correlation between flux change and expression change (transcriptional regulation) as well as reactions whose flux change is likely to be driven only by changes in the metabolite concentrations (metabolic regulation). The changes due to growth on four different carbon sources and as a consequence of five gene deletions were analyzed for Saccharomyces cerevisiae. The enzymes with transcriptional regulation showed enrichment in certain transcription factors. This has not been previously reported. The information provided by the presented method could guide the discovery of new metabolic engineering strategies or the identification of drug targets for treatment of metabolic diseases