612 research outputs found

    Towards a Reproducible Pan-European Soil Erosion Risk Assessment - RUSLE

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    Soil is a valuable, non-renewable natural resource that offers a multitude of ecosystems goods and services. Given the increasing threat of soil erosion in Europe and the implications this has on future food security and water quality, it is important that land managers and decision makers are provided with accurate and appropriate information on the areas more prone to erosion phenomena. The present study shows an attempt to locate, at regional scale, the most sensitive areas and to highlight any changes of soil erosion trends with climate change. The choice of the input datasets is crucial as they have to offer the most homogeneous and complete covering at the pan-European level and to allow the produced information to be harmonized and easily validated. The model is based on available datasets (HWSD, SGDBE, SRTM, CLC and E-OBS) and The Revised Universal Soil Loss Equation (RUSLE) is used because of its flexibility and least data demanding. A significant effort has been made to select the better simplified equations to be used when a strict application of the RUSLE model was not possible. In particular for the computation of the Rainfall Erosivity factor a validation based on measured precipitation time series (having a temporal resolution of 10-15 minutes) has been implemented to be easily reproducible. The validation computational framework is available as free software. Designing the computational modeling architecture with the aim to ease as much as possible the future reuse of the model in analyzing climate change scenarios has also been a challenging goal of the research

    Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

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    [Excerpt] Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental, global) environmental problems need transdisciplinary integration within a context of modelling complexity and multiple sources of uncertainty. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. Approaches (either of computational science or of policy-making) suitable at a given domain-specific scale may not be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and corresponding policy-making. In WSTMe, the characteristic heterogeneity of available spatial information and complexity of the required data-transformation modelling (D-TM) appeal for a paradigm shift in how computational science supports such peculiarly extensive integration processes. In particular, emerging wide-scale integration requirements of typical currently available domain-specific modelling strategies may include increased robustness and scalability along with enhanced transparency and reproducibility. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP exploits the joint semantics provided by SemAP and geospatial tools to split a complex D-TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...

    Free and Open Source Software underpinning the European Forest Data Centre

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    Worldwide, governments are growingly focusing on free and open source software (FOSS) as a move toward transparency and the freedom to run, copy, study, change and improve the software. The European Commission (EC) is also supporting the development of FOSS [...]. In addition to the financial savings, FOSS contributes to scientific knowledge freedom in computational science (CS) and is increasingly rewarded in the science-policy interface within the emerging paradigm of open science. Since complex computational science applications may be affected by software uncertainty, FOSS may help to mitigate part of the impact of software errors by CS community- driven open review, correction and evolution of scientific code. The continental scale of EC science-based policy support implies wide networks of scientific collaboration. Thematic information systems also may benefit from this approach within reproducible integrated modelling. This is supported by the EC strategy on FOSS: "for the development of new information systems, where deployment is foreseen by parties outside of the EC infrastructure, [F]OSS will be the preferred choice and in any case used whenever possible". The aim of this contribution is to highlight how a continental scale information system may exploit and integrate FOSS technologies within the transdisciplinary research underpinning such a complex system. A European example is discussed where FOSS innervates both the structure of the information system itself and the inherent transdisciplinary research for modelling the data and information which constitute the system content. [...

    dReDBox: Materializing a full-stack rack-scale system prototype of a next-generation disaggregated datacenter

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    Current datacenters are based on server machines, whose mainboard and hardware components form the baseline, monolithic building block that the rest of the system software, middleware and application stack are built upon. This leads to the following limitations: (a) resource proportionality of a multi-tray system is bounded by the basic building block (mainboard), (b) resource allocation to processes or virtual machines (VMs) is bounded by the available resources within the boundary of the mainboard, leading to spare resource fragmentation and inefficiencies, and (c) upgrades must be applied to each and every server even when only a specific component needs to be upgraded. The dRedBox project (Disaggregated Recursive Datacentre-in-a-Box) addresses the above limitations, and proposes the next generation, low-power, across form-factor datacenters, departing from the paradigm of the mainboard-as-a-unit and enabling the creation of function-block-as-a-unit. Hardware-level disaggregation and software-defined wiring of resources is supported by a full-fledged Type-1 hypervisor that can execute commodity virtual machines, which communicate over a low-latency and high-throughput software-defined optical network. To evaluate its novel approach, dRedBox will demonstrate application execution in the domains of network functions virtualization, infrastructure analytics, and real-time video surveillance.This work has been supported in part by EU H2020 ICTproject dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

    Entanglement purification of unknown quantum states

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    A concern has been expressed that ``the Jaynes principle can produce fake entanglement'' [R. Horodecki et al., Phys. Rev. A {\bf 59}, 1799 (1999)]. In this paper we discuss the general problem of distilling maximally entangled states from NN copies of a bipartite quantum system about which only partial information is known, for instance in the form of a given expectation value. We point out that there is indeed a problem with applying the Jaynes principle of maximum entropy to more than one copy of a system, but the nature of this problem is classical and was discussed extensively by Jaynes. Under the additional assumption that the state ρ(N)\rho^{(N)} of the NN copies of the quantum system is exchangeable, one can write down a simple general expression for ρ(N)\rho^{(N)}. We show how to modify two standard entanglement purification protocols, one-way hashing and recurrence, so that they can be applied to exchangeable states. We thus give an explicit algorithm for distilling entanglement from an unknown or partially known quantum state.Comment: 20 pages RevTeX 3.0 + 1 figure (encapsulated Postscript) Submitted to Physical Review

    An overview of the ciao multiparadigm language and program development environment and its design philosophy

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    We describe some of the novel aspects and motivations behind the design and implementation of the Ciao multiparadigm programming system. An important aspect of Ciao is that it provides the programmer with a large number of useful features from different programming paradigms and styles, and that the use of each of these features can be turned on and off at will for each program module. Thus, a given module may be using e.g. higher order functions and constraints, while another module may be using objects, predicates, and concurrency. Furthermore, the language is designed to be extensible in a simple and modular way. Another important aspect of Ciao is its programming environment, which provides a powerful preprocessor (with an associated assertion language) capable of statically finding non-trivial bugs, verifying that programs comply with specifications, and performing many types of program optimizations. Such optimizations produce code that is highly competitive with other dynamic languages or, when the highest levéis of optimization are used, even that of static languages, all while retaining the interactive development environment of a dynamic language. The environment also includes a powerful auto-documenter. The paper provides an informal overview of the language and program development environment. It aims at illustrating the design philosophy rather than at being exhaustive, which would be impossible in the format of a paper, pointing instead to the existing literature on the system

    Identification and manipulation of tumor associated macrophages in human cancers

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    Evading immune destruction and tumor promoting inflammation are important hallmarks in the development of cancer. Macrophages are present in most human tumors and are often associated with bad prognosis. Tumor associated macrophages come in many functional flavors ranging from what is known as classically activated macrophages (M1) associated with acute inflammation and T-cell immunity to immune suppressive macrophages (M2) associated with the promotion of tumor growth. The role of these functionally different myeloid cells is extensively studied in mice tumor models but dissimilarities in markers and receptors make the direct translation to human cancer difficult. This review focuses on recent reports discriminating the type of infiltrating macrophages in human tumors and the environmental cues present that steer their differentiation. Finally, immunotherapeutic approaches to interfere in this process are discussed
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