11 research outputs found

    A Systems Approach to Minimize Wasted Work in Blockchains

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    Blockchain systems and distributed ledgers are getting increasing attention since the release of Bitcoin. Everyday they make headlines in the news involving economists, scientists, and technologists. The technology invented by Satoshi Nakamoto gave to the world a quantum leap in the fields of distributed systems and digital currencies. Even so, there are still some problems regarding the architecture in most existing blockchain systems. One of the main challenges in these systems is the structure of the network topology and how peers disseminate messages between them, this leads to problems regarding the system scalability and the efficiency of the transaction and blocks propagation, wasting computational power, energy and network resources. In this work we propose a novel solution to tackle these limitations. We propose the design of membership and message dissemination protocols, based on the state-ofart, that will boost the efficiency of the overlay network that support the interactions between miners, reducing the number of exchanged messages and the used bandwidth. This solution also reduces the computational power and energy consumed across all nodes in the network, since the nodes avoid to process redundant network messages, and, becoming aware of mined blocks faster, avoid to perform computations over an outdated chain configuration

    Répteis da Ilha de Santa Catarina

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    Guia fotográficoNeste guia fotográfico apresentamos as 43 espécies de lagartos, serpentes, anfisbaenias e tarturugas registradas na Ilha de Santa Catarina, região insular do município de Florianópolis, Santa Catarina. Além do nome cientifico, incluimos o nome popular, status de conservação e para as serpentes, destacamos aquelas que podem oferecer riscos de acidente.FAPES

    GeoERA Raw Materials Monograph : the past and the future

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    ABSTRACT: GeoERA Minerals projects have produced data aimed at supporting Europe’s minerals sector and to assist the European Commission to realise its goals for raw materials. Data has been compiled on mineral occurrences and mineral provinces across Europe, in particular, areas with potential to host Critical Raw Materials. Anecdotal evidence from the minerals sector provides an indication of the likelihood of exploration leading to mine development. For every 1,000 mineral showings examined, only 100 may receive further exploration work and of those 100, only 10 may warrant more detailed sampling either through trenching, drilling or other means and of those 10 only 1 may proceed to an evaluation through a full feasibility study which itself has only 50% chance of being positive. Following this, any project for which a mine proposal is made must undergo a full evaluation and permitting by authorities including full public consultation. The proposal may or may not pass this scrutiny. In terms of a schedule, the generally accepted minimum time frame from discovery to production is 10 years and usually much more, up to 20 years.info:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

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    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

    Pervasive gaps in Amazonian ecological research

    Get PDF

    Pervasive gaps in Amazonian ecological research

    Get PDF
    Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost
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