The fourth industrial revolution use modern technologies that produce a continues flow of data. This large amount of data cannot be analyzed with traditional technologies to detect and diagnose problem without the need of a human. Deep learning consists of a set of methods based on neural networks that can process and extract information from a such amount of data. Deep learning frameworks provide ...

Abstract: In holothuroids, oocyte maturation is stopped in ovaries at the prophase I stage of meiosis. In natural conditions, the blockage is removed during the spawning by an unknown mechanism. When oocytes are isolated by dissection, the meiotic release can be successfully induced by a natural inducer, the REES (i.e., Rough Extract of Echinoid Spawn) that is used in aquaculture to obtain ...

GPUs benefit from much more computation power with the same order of energy consumption than CPUs. Thanks to their massive data parallel architecture, GPUs can outperform CPUs, especially on Single Program Multiple Data (SPMD) programming paradigm on a large amount of data. Database engines are now everywhere, from different sizes and complexities, for multiple usages, embedded or distributed; ...

Energy consumption is one of the main limiting factors for designing and deploying ultrascalesystems. Therefore, this paper presents challenges and trends associated with energy efficiency forultrascale systems based on current activities of the working group on ”Energy Efficiency” inthe European COST Action Nesus IC1305. The analysis contains major areas that are related tostudies of ...

End-user systems are increasingly impacted by the exponential growth of data volumes and their processing. Moreover, post-processing operations, essentially dedicated to ergonomic features, require more and more resources. Improving overall performances of embedded relational database management systems (RDBMS) can contribute to deliver better responsiveness of end-user systems while increasing the ...

Relational database management systems (RDBMS) are still widely required by numerous business applications. Boosting performances without compromising functionalities represents a big challenge. To achieve this goal, we propose to boost an existing RDBMS by making it able to use hardware architectures with high memory bandwidth like GPUs. In this paper we present a solution named CuDB. We compare ...

Clinical and environmental meta-omics studies are accumulating an ever-growing amount of microbial abundance data over a wide range of ecosystems. With a sufficiently large sample number, these microbial communities can be explored by constructing and analyzing co-occurrence networks, which detect taxon associations from abundance data and can give insights into community structure. Here, we investigate ...

The Common-pool resource (CPR) game is a social dilemma where agents have to decide how to consume a shared CPR. Either they each take their cut, completely destroying the CPR, or they restrain themselves, gaining less immediate profit but sustaining the resource and future profit. When no consumption takes place the CPR simply grows to its carrying capacity. As such, this dilemma provides a ...

Deep learning presents an efficient set of methods that allow learning from massive volumes of data using complex deep neural networks. To facilitate the design and implementation of algorithms, deep learning frameworks provide a high-level programming interface. Based on these frameworks, new models, and applications are able to make better and better predictions. One type of deep learning application ...

Chromatographic fractions of a rough extract of echinoid spawn (REES) is demonstrated to efficiently induce oocyte maturation in aspidochirote holothuroids. The method is so efficient that it is currently used in holothuriculture to obtain fertilised eggs even outside the reproductive period of the aquacultivated species. In the present study, we isolated and identified from echinoid spawns the ...