Automatic identification of relevant places from cellular network data

We present a methodology to automatically identify users\u2019 relevant places from cellular network data.1 In this work we used anonymized Call Detail Record (CDR) comprising information on where and when users access the cellular network. The key idea is to effectively cluster CDRs together and to weigh clusters to determine those associated to frequented places. The approach can identify users\u2019 home and work locations as well as other places (e.g., associated to leisure and night life). We evaluated our approach threefold: (i) on the basis of groundtruth information coming from a fraction of users whose relevant places were known, (ii) by comparing the resulting number of inhabitants of a given city with the number of inhabitants as extracted by the national census. (iii) Via stability analysis to verify the consistency of the extracted results across multiple time periods. Results show the effectiveness of our approach with an average 90% precision and recall

Argumentative Link Prediction using Residual Networks and Multi-Objective Learning.

We explore the use of residual networks for argumentation mining, with an emphasis on link prediction. We propose a domain-agnostic method that makes no assumptions on document or argument structure. We evaluate our method on a challenging dataset consisting of user-generated comments collected from an online platform. Results show that our model outperforms an equivalent deep network and offers results comparable with state-of-the-art methods that rely on domain knowledge

Attention in Natural Language Processing

Attention is an increasingly popular mechanism used in a wide range of neural architectures. The mechanism itself has been realized in a variety of formats. However, because of the fast-paced advances in this domain, a systematic overview of attention is still missing. In this article, we define a unified model for attention architectures in natural language processing, with a focus on those designed to work with vector representations of the textual data. We propose a taxonomy of attention models according to four dimensions: the representation of the input, the compatibility function, the distribution function, and the multiplicity of the input and/or output. We present the examples of how prior information can be exploited in attention models and discuss ongoing research efforts and open challenges in the area, providing the first extensive categorization of the vast body of literature in this exciting domain

Multi-Task Attentive Residual Networks for Argument Mining

We explore the use of residual networks and neural attention for argument mining and in particular link prediction. The method we propose makes no assumptions on document or argument structure. We propose a residual architecture that exploits attention, multi-task learning, and makes use of ensemble. We evaluate it on a challenging data set consisting of user-generated comments, as well as on two other datasets consisting of scientific publications. On the user-generated content dataset, our model outperforms state-of-the-art methods that rely on domain knowledge. On the scientific literature datasets it achieves results comparable to those yielded by BERT-based approaches but with a much smaller model size.Comment: 12 pages, 2 figures, submitted to IEEE Transactions on Neural Networks and Learning System

Exploring copepod distribution patterns at three nested spatial scales in a spring system. Habitat partitioning and potential for hydrological bioindication

In groundwater-fed springs, habitat characteristics are primarily determined by a complex combination of geomorphic features and physico-chemical parameters, while species assemblages are even more intricate. Springs host species either inhabiting the spring mouth, or colonizing spring habitats from the surface or from the aquifers which feed the springs. Groundwater species living in springs have been claimed as good candidates for identifying dual aquifer flowpaths or changes in groundwater pathways before reaching the spring outlets. However, the reliability of spring species as hydrological biotracers has not been widely investigated so far. Our study was aimed at analysing a large karstic spring system at three nested spatial scales in order: i) to assess, at whole spring system scale, the presence of a groundwater divide separating two aquifers feeding two spring units within a single spring system, by combining isotope analyses, physico-chemistry, and copepod distribution patterns; ii) to test, at vertical spring system scale, the effectiveness of copepods in discriminating surface and subsurface habitat patches within the complex mosaic spring environment; iii) to explore, at local spring unit level, the relative role of hydrochemistry and sediment texture as describers of copepod distribution among microhabitats. The results obtained demonstrated the presence of a hierarchical spatial structure, interestingly reflected in significant differences in assemblage compositions. Copepod assemblages differed between the two contiguous spring units, which were clearly characterized by their hydrochemistry and by significant differences in the groundwater flowpaths and recharge areas, as derived by the isotope analyses. The biological results suggested that stygobiotic species seem to be related to the origin of groundwater, suggesting their potential role as hydrological biotracers. At vertical scale, assemblage composition in surface and subsurface habitats was significantly different, both between spring units and among microhabitats, supporting strong habitat preferences of copepod species. At the smaller local scale, the response to habitat patchiness of subsurface copepod assemblages resulted in distribution patterns primarily defined by sediment texture, while the sensitivity to differences in hydrochemistry was negligible

Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning

Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks. In this position paper, we posit that neural-symbolic and statistical relational learning could play a crucial role in the integration of symbolic and sub-symbolic methods to achieve this goal

Correlation between Primary Myelofibrosis and the Association of Portal Thrombosis with Portal-Biliary Cavernoma: US, MDCT, and MRI Features

Abstract Objective Myelofibrosis is a rare chronic myelolymphoproliferative disease and is associated with increased risk of venous thromboembolism. The objective of this study is to retrospectively evaluate patients with primary myelofibrosis who underwent abdominal US, MDCT and MRI, in order to identify the development of portal thrombosis and its correlation with portal-biliary cavernoma. Methods We evaluated 125 patients with initial diagnosis of primary myelofibrosis and nonspecific abdominal pain who had undergone US with color Doppler. In 13 patients (8 men, 5 females; age: 45–85), US detected portal thrombosis with associated portal-biliary cavernoma. All patients subsequently underwent contrast-enhanced MDCT and MRI and 4 patients MR-cholangiography. The correlation between primary myelofibrosis and portal thrombosis and cavernoma respectively was calculated using χ2 test. Results About 10% of patients with primary myelofibrosis preliminary evaluated with US had partial (8 pts) or complete (5 pts) portal thrombosis associated with portal-biliary cavernoma with a χ2 = 0. In all patients, US detected a concentric thickening of main bile duct (MBD) wall (mean value: 7 mm); color Doppler always showed dilated venous vessels within the thickened wall of the biliary tract. Contrast-enhanced CT and MRI confirmed thickening of MBD walls with their progressive enhancement and allowed better assessment of the extent of the portal system thrombosis. MR-cholangiography showed a thin appearance of the MBD lumen with evidence of ab extrinsic compression. Conclusions The evidence of portal thrombosis and portal-biliary cavernoma in 10% of the patients with primary myelofibrosis indicates a close correlation between the two diseases. In the detection of portal thrombosis and portal-biliary cavernoma, US with color Doppler is the most reliable and economical diagnostic technique while contrast-enhanced MDCT and MRI allow better assessment of the extent of the portal vein thrombosis and of the complications of myelofibrosis

Atmosferic pressure non-thermal plasma: Preliminary investigation

Antibacterial activity of atmosferic pressure non-thermal plasma (APNTP) was assessed for bacterial, yeast and mold strains. This investigation is to be considered preliminary: a second step is envisaged in which the efficacy of the technique and the device will be assessed directly on food of animal and plant origin. The strains (ATCC or wild type) of Listeria innocua, Escherichia coli, Salmonella thyphimurium, Pseudomonas aeruginosa, Staphylococcus aureus, Enterococcus faecalis, Proteus mirabilis (bacteria); Alternaria alternata, Aspergillus flavus, Cladosporium herbarum, Fusarium graminearum, Geotrichum candidum, Penicillium roqueforti, Rhizopus nigricans (moulds); Candida parapsilosis and Candida albicans (yeasts) were subjected to plasma plume generated by the action of electric fields with a gas mixture (oxygen and helium) delivered for 5 min at a distance of 2 cm. Types of experiments were listed as following: microorganism at concentration 1×10^8 and 1×104 cfu on PCA (Plate Count Agar); Listeria innocua and Salmonella thiphymurium at concentration 1×10^4 cfu on semi-synthetic and synthetic medium; mycetes (moulds and yeasts) at concentration 1×10^8 and 1×10^4 cfu on SDA (Sabouraud Dextrose Agar). The results obtained on the bacteria subjected to atmospheric cold plasma were evident on all the strains tested except for Proteus mirabilis (1×10^8 cfu), most evident at a concentration of 1×10^4 cfu, not only on culture media PCA but also on semi-synthetic medium and jelly meat-PCA medium. In spite of bacterial results, treatment with plasma plume did not decrease or inhibit of fungal growth. That means plasma plume was neither fungicidal nor fungistatic activities

The dark side of springs: what drives small-scale spatial patterns of subsurface meiofaunal assemblages?

International audience; Springs are amongst the most relevant Groundwater Dependent Ecosystems (GDEs) and are key research environments in freshwater ecology and biology. The strict dependency on ground water of surface spring biodiversity is widely recognized, whereas the biodiversity occurring below the spring is very poorly known. This study analyzes copepod assemblages in the subsurface habitat of a karstic rheo- limnocrenic spring in relation to seventeen environmental parameters. Subsurface copepod assemblages were sensitive to microspatial variation in habitat structure, and species distributions were mostly driven by groundwater flowpath and substratum type, resulting in biologically distinct limnocrenic and rheocrenic sectors at the spring system scale. Habitat patchiness was reflected in differences in the microdistribution of subsurface copepods, stygobiotic assemblages being more sensitive to the measured environmental gradients than non-stygobiotic ones. In spite of the apparent stability of spring environments, copepods, as a target group, performed well as de- scriptors of sediment texture and hydrodynamics, and may offer relevant information for a better understanding of the potential changes generated by anthropogenic disturbance on these ecosystems

Earthquakes trigger the loss of groundwater biodiversity

Earthquakes are among the most destructive natural events. The 6 April 2009, 6.3-Mw earthquake in L\u27Aquila (Italy) markedly altered the karstic Gran Sasso Aquifer (GSA) hydrogeology and geochemistry. The GSA groundwater invertebrate community is mainly comprised of small-bodied, colourless, blind microcrustaceans. We compared abiotic and biotic data from two pre-earthquake and one post-earthquake complete but non-contiguous hydrological years to investigate the effects of the 2009 earthquake on the dominant copepod component of the obligate groundwater fauna. Our results suggest that the massive earthquake-induced aquifer strain biotriggered a flushing of groundwater fauna, with a dramatic decrease in subterranean species abundance. Population turnover rates appeared to have crashed, no longer replenishing the long-standing communities from aquifer fractures, and the aquifer became almost totally deprived of animal life. Groundwater communities are notorious for their low resilience. Therefore, any major disturbance that negatively impacts survival or reproduction may lead to local extinction of species, most of them being the only survivors of phylogenetic lineages extinct at the Earth surface. Given the ecological key role played by the subterranean fauna as decomposers of organic matter and "ecosystem engineers", we urge more detailed, long-term studies on the effect of major disturbances to groundwater ecosystems