Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules

Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed method is adequate in practice and can be integrated within the workflow of systems unable to cope with very large ontologies

Human-centric Transfer Learning Explanation via Knowledge Graph [Extended Abstract]

Transfer learning which aims at utilizing knowledge learned from one problem (source domain) to solve another different but related problem (target domain) has attracted wide research attentions. However, the current transfer learning methods are mostly uninterpretable, especially to people without ML expertise. In this extended abstract, we brief introduce two knowledge graph (KG) based frameworks towards human understandable transfer learning explanation. The first one explains the transferability of features learned by Convolutional Neural Network (CNN) from one domain to another through pre-training and fine-tuning, while the second justifies the model of a target domain predicted by models from multiple source domains in zero-shot learning (ZSL). Both methods utilize KG and its reasoning capability to provide rich and human understandable explanations to the transfer procedure

ColNet: Embedding the Semantics of Web Tables for Column Type Prediction

Automatically annotating column types with knowledge base(KB) concepts is a critical task to gain a basic understandingof web tables. Current methods rely on either table metadatalike column name or entity correspondences of cells in theKB, and may fail to deal with growing web tables with in-complete meta information. In this paper we propose a neu-ral network based column type annotation framework namedColNetwhich is able to integrate KB reasoning and lookupwith machine learning and can automatically train Convolu-tional Neural Networks for prediction. The prediction modelnot only considers the contextual semantics within a cell us-ing word representation, but also embeds the semantics of acolumn by learning locality features from multiple cells. Themethod is evaluated with DBPedia and two different web ta-ble datasets, T2Dv2 from the general Web and Limaye fromWikipedia pages, and achieves higher performance than thestate-of-the-art approaches

Revisiting the dynamics of catastrophic late Pleistocene glacial-lake drainage, Altai Mountains, central Asia

In this work, we present a whole system model of megafloods from catastrophic ice-dam failure in the late Pleistocene that comprises the study of the dynamics of the glacial lake, the propagation of the flood wave downstream of the dam, and an approximation to the ice breach process. The ice-dam incision rate was simply considered an unknown constant, which was varied systematically to best fit the maximum altitude of the simulated water surface and the paleostage indicators in the downstream valley during the transient megaflood. Hence, the hydrograph resulting from the breach of the ice dam was not prescribed but was an output of the paleohydraulic reconstruction. By considering two possible configurations of the breach in the ice dam, i.e. full or partial removal of the ice, we constrained the incision rate in the narrow range of 28 − 42 m ⋅ h−1. Two connected glacial lakes, Kuray and Chuja, released 95% of the stored water volume (i.e., 564 km3) in 33.8 hours. A peak discharge of 10.5 M m3 ⋅ s−1 was required to form numerous giant bars and run-up deposits in the Chuja and Katun valleys. The peak streamflow occurred after 11 h when 45% of the available lake volume had been evacuated from the Kuray and Chuja basins. Further verification of the reconstructed megaflood was achieved by studying the computed hydraulic conditions during the lake draining that justify the existence and orientation of several fields of subaqueous gravel-dunes in the glacial lake. Complex spatiotemporal patterns during the recession stage of the flood built most of the fields of bedforms. In terms of nondimensional parameters, the Froude and Shields numbers that formed the dune fields were similar to those observed in large sandy rivers, but the flow was undoubtedly unsteady and two-dimensional. We conclude by noting that the extensions of the simulated area cannot be cropped or analysed by independent parts in order to predict the formation of the most relevant geological records due to the unsteady, two-dimensional nature of the flow motion and the development of backwater effects in the drainage network. Lastly, the paleohydrological reconstruction of a megaflood has helped not only to infer the dynamics of the event but also to retrodict the mean parameters of the ice-dam failure mechanism.This work was supported by the Spanish Ministry of Science, Innovation and Universities (MICINN/FEDER, UE) under Grant SEDRETOCGL2015-70736-R. P.R.J. was supported by the European Social Fund and the University of Jaén

Epizootic and Zoonotic Helminths of the Bobcat (Lynx rufus) in Illinois and a Comparison of Its Helminth Component Communities across the American Midwest

A total of 6257 helminths of 19 taxa were recovered from the digestive tract and lungs of 67 bobcats in Illinois. Infections caused by Alaria mustelae, Diphyllobothrium latum, and Macracanthorhynchus ingens are reported for the first time in bobcats. From all the taxa recovered, only three species occurred in high prevalence and caused intense infections: Taenia rileyi, Alaria marcianae, and Toxocara cati, with prevalence and mean intensity of 70% and 6; 42% and 193, and 25% and 14 individuals, respectively. Prevalence lower than 15% of 14 helminth species suggests bobcats are not continuously exposed to infective stages of a single parasite, and may be exposed to a large variety of generalists during their lifespan. No significant difference in parasite species according to host sex or age was detected, except for Diphyllobothrium spp., which were found more frequently in females and in trapped bobcats, and the hookworm, Ancylostoma caninum, which infected juveniles more frequently. Average species richness per infracommunity was 2.4 (±1.2), and the parasite component community showed low qualitative similarity with neighbor communities. The taxa A. caninum, Alaria spp., Diphyllobothrium spp., Paragonimus kellicotti, and T. cati are etiological agents of epizootic and zoonotic diseases

Learning Semantic Annotations for Tabular Data

The usefulness of tabular data such as web tables critically depends on understanding their semantics. This study focuses on column type prediction for tables without any meta data. Unlike traditional lexical matching-based methods, we propose a deep prediction model that can fully exploit a table's contextual semantics, including table locality features learned by a Hybrid Neural Network (HNN), and inter-column semantics features learned by a knowledge base (KB) lookup and query answering algorithm.It exhibits good performance not only on individual table sets, but also when transferring from one table set to another

Embedding OWL ontologies with OWL2Vec

In this paper, we present a preliminary study to compute embeddings for OWL 2 ontologies by projecting the ontology axioms into a graph and performing (random) walks over the ontology graph to create a corpus of sentences. This corpus is then given to a neural language model to create concept embeddings. The conducted preliminary evaluation shows promising results

Relativistic Runge-Lenz vector: from N=4{\cal N}=4 SYM to SO(4) scalar field theory

Starting from ${\cal N}=4$ SYM and using an appropriate Higgs mechanism we reconsider the construction of a scalar field theory non-minimally coupled to a Coulomb potential with a relativistic SO(4) symmetry and check for scalar field consistency conditions. This scalar field theory can also be obtained from a relativistic particle Lagrangian with a proper implementation of the non-minimal coupling. We provide the generalization of the non-relativistic construction of the Runge-Lenz vector to the relativistic case and show explicitly that this new vector generates the SO(4) algebra. Using the power of the SO(4) symmetry, we calculate the relativistic hydrogen atom spectrum. We provide a generalization of the Kustaanheimo-Stiefel transformation to the relativistic case and relate our results with the corresponding relativistic oscillator. Finally, in the light of these results, we reconsider the calculation of the hydrogen atom spectrum from the cusp anomalous dimension given in [2].Comment: 17 pages. Enhaced version matching the published JHEP version. Typos corrected. The argument of concistence at the end of section 2 was correcte

Slackwater sediments record the increase in sub-daily rain flood due to climate change in a European Mediterranean catchment

In this work we propose an original method to determine the magnitude of the discharge, the intensity of the precipitation and the duration of short-rain floods in small torrential basins (< 2000 km2), extending our earlier approach for long-rain floods in larger basins (Water 2016, 8, 526; Remote Sens. 2017, 9, 727). The studied areas are located in ungauged catchments with high erosion rates where torrents deposit slackwater sediments near the outlet of the basins. Such deposits and erosive morphologies allow us to analyse sub-daily extreme hydrological events by combining standard techniques in paleohydrology, the kinematic wave method and remote-sensed paleostage indicators. The formulation was correctly verified in extreme events through reliable gauge measurements and a high-resolution distributed hydrological model showing the accuracy of our calculations (10% ≤ relative error ≤ 22%). In catchments of the European Mediterranean region where the frequency and magnitude of short-rain floods are increasing (e.g. the Guadalquivir Basin), the main hydrological variables can thus be quantified post-event using the proposed approach. The outputs may serve to construct a new database for this kind of events complementary to the existing daily database for long-rain floods (> 24 h). The need is evident for safety designs of civil infrastructures and flood risk mitigation strategies in the current climate change scenario.This work was supported by the Spanish Ministry of Science, Innovation and Universities (MICINN/FEDER, UE) under Grant SEDRETO CGL2015-70736-R. J.D.d.M.E. was supported by the PhD scholarship BES-2016-079117 (MINECO/FSE, UE) from the Spanish National Programme for the Promotion of Talent and its Employability (call 2016)

Conditional U1 gene silencing in Toxoplasma gondii

The functional characterisation of essential genes in apicomplexan parasites, such as Toxoplasma gondii or Plasmodium falciparum, relies on conditional mutagenesis systems. Here we present a novel strategy based on U1 snRNP-mediated gene silencing. U1 snRNP is critical in pre-mRNA splicing by defining the exon-intron boundaries. When a U1 recognition site is placed into the 3’-terminal exon or adjacent to the termination codon, pre-mRNA is cleaved at the 3’-end and degraded, leading to an efficient knockdown of the gene of interest (GOI). Here we describe a simple method that combines endogenous tagging with DiCre-mediated positioning of U1 recognition sites adjacent to the termination codon of the GOI which leads to a conditional knockdown of the GOI upon rapamycin-induction. Specific knockdown mutants of the reporter gene GFP and several endogenous genes of T. gondii including the clathrin heavy chain gene 1 (chc1), the vacuolar protein sorting gene 26 (vps26), and the dynamin-related protein C gene (drpC) were silenced using this approach and demonstrate the potential of this technology. We also discuss advantages and disadvantages of this method in comparison to other technologies in more detail