What is the current state of the Multilingual Web of Data?

The Semantic Web is growing at a fast pace, recently boosted by the creation of the Linked Data initiative and principles. Methods, standards, techniques and the state of technology are becoming more mature and therefore are easing the task of publication and consumption of semantic information on the Web

datos.bne.es and MARiMbA: an insight into Library Linked Data

Purpose – Linked data is gaining great interest in the cultural heritage domain as a new way for publishing, sharing and consuming data. The paper aims to provide a detailed method and MARiMbA a tool for publishing linked data out of library catalogues in the MARC 21 format, along with their application to the catalogue of the National Library of Spain in the datos.bne.es project. Design/methodology/approach – First, the background of the case study is introduced. Second, the method and process of its application are described. Third, each of the activities and tasks are defined and a discussion of their application to the case study is provided. Findings – The paper shows that the FRBR model can be applied to MARC 21 records following linked data best practices, librarians can successfully participate in the process of linked data generation following a systematic method, and data sources quality can be improved as a result of the process. Originality/value – The paper proposes a detailed method for publishing and linking linked data from MARC 21 records, provides practical examples, and discusses the main issues found in the application to a real case. Also, it proposes the integration of a data curation activity and the participation of librarians in the linked data generation process

Publishing Linked Data - There is no One-Size-Fits-All Formula

Publishing Linked Data is a process that involves several design decisions and technologies. Although some initial guidelines have been already provided by Linked Data publishers, these are still far from covering all the steps that are necessary (from data source selection to publication) or giving enough details about all these steps, technologies, intermediate products, etc. Furthermore, given the variety of data sources from which Linked Data can be generated, we believe that it is possible to have a single and uni�ed method for publishing Linked Data, but we should rely on di�erent techniques, technologies and tools for particular datasets of a given domain. In this paper we present a general method for publishing Linked Data and the application of the method to cover di�erent sources from di�erent domains

datos.bne.es: A library linked dataset

We describe the datos.bne.es library dataset. The dataset makes available the authority and bibliography catalogue from the Biblioteca Nacional de España (BNE, National Library of Spain) as Linked Data. The catalogue contains around 7 million authority and bibliographic records. The records in MARC 21 format were transformed to RDF and modelled using IFLA (International Federation of Library Associations) ontologies and other well-established vocabularies such as RDA (Resource Description and Access) or the Dublin Core Metadata Element Set. A tool named MARiMbA automatized the RDF generation process and the data linkage to DBpedia and other library linked data resources such as VIAF (Virtual International Authority File) or GND (Gemeinsame Normdatei, the authority dataset from the German National Library)

Use of 13Ca chemical-shifts in protein structure determination

A physics-based method aimed at determining protein structures by using NOE-derived distances together with observed and computed 13C chemical shifts is proposed. The approach makes use of 13Cα chemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without making a priori use of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed 13Cα chemical shifts match the experimental ones. A test is carried out on a 76-amino acid, all-α-helical protein; namely, the Bacillus subtilis acyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed 13Cα chemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank.Fil: Vila, Jorge Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi"; Argentina. Cornell University; Estados UnidosFil: Ripoll, Daniel R.. Cornell Theory Center; Estados UnidosFil: Scheraga, Harold A.. Cornell University; Estados Unido

Probabilistic analysis of groundwater-related risks at subsurface excavation sites

      Construction of underground structures (e.g., subway lines, railways and highway tunnels) is inherently hazardous, posing risks to both workers and machinery at the site and to surrounding buildings. The presence of groundwater may increase these risks. We develop a general probabilistic risk assessment (PRA) framework to quantify risks driven by groundwater to the safety of underground constructions. The proposed approach is fully compatible with standard PRA practices, employing well-developed risk analysis tools based on the fault tree analysis method. The novelty and computational challenges of the proposed approach stem from the reliance on a combination of approaches including extracting information from databases, solving stochastic differential equations, or relying on expert judgment to compute probabilities of basic events. The general framework is presented in a case study and used to estimate and minimize risks at a construction site of an underground station for a new subway line in the Barcelona metropolitan area. &nbsp

An improved near-real-Time precipitation retrieval for Brazil

Observations from geostationary satellites can provide spatially continuous coverage at continental scales with high spatial and temporal resolution. Because of this, they are commonly used to complement ground-based precipitation measurements, whose coverage is often more limited. We present Hydronn, a neural-network-based, near-real-Time precipitation retrieval for Brazil based on visible and infrared (Vis-IR) observations from the Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite 16 (GOES-16). The retrieval, which employs a convolutional neural network to perform Bayesian precipitation retrievals, was developed with the aims of (1) leveraging the full potential of latest-generation geostationary observations and (2) providing probabilistic precipitation estimates with well-calibrated uncertainties. The retrieval is trained using more than 3 years of collocations with combined radar and radiometer retrievals from the Global Precipitation Measurement (GPM) core observatory over South America. The accuracy of instantaneous precipitation estimates is assessed using a separate year of GPM combined retrievals and compared to retrievals from passive microwave (PMW) sensors and HYDRO, the Vis-IR retrieval that is currently in operational use at the Brazilian Institute for Space Research. Using all available channels of the ABI, Hydronn achieves accuracy close to that of state-of-The-Art PMW precipitation retrievals in both precipitation estimation and detection despite the lower information content of the Vis-IR observations. Hourly, daily, and monthly precipitation accumulations are evaluated against gauge measurements for June and December 2020 and compared to HYDRO, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) Cloud Classification System (CCS), and the Integrated Multi-satellitE Retrievals for GPM (IMERG). Compared to HYDRO, Hydronn reduces the mean absolute error for hourly accumulations by 21% (22%) compared to HYDRO by 44% (41%) for the mean squared error (MSE) and increases the correlation by 138% (312%) for June (December) 2020. Compared to IMERG, the improvements correspond to 16% (14%), 12% (12%), and 20% (56%), respectively. Furthermore, we show that the probabilistic retrieval is well calibrated against gauge measurements when differences in the distributions of the training data and the gauge measurements are accounted for. Hydronn has the potential to significantly improve near-real-Time precipitation retrievals over Brazil. Furthermore, our results show that precipitation retrievals based on convolutional neural networks (CNNs) that leverage the full range of available observations from latest-generation geostationary satellites can provide instantaneous precipitation estimates with accuracy close to that of state-of-The-Art PMW retrievals. The high temporal resolution of the geostationary observation allows Hydronn to provide more accurate precipitation accumulations than any of the tested conventional precipitation retrievals. Hydronn thus clearly shows the potential of deep-learning-based precipitation retrievals to improve precipitation estimates from currently available satellite imagery

Trapping and Characterization of a Reaction Intermediate in Carbapenem Hydrolysis by \u3cem\u3eB. cereus\u3c/em\u3e Metallo-β-lactamase

Metallo-β-lactamases hydrolyze most β-lactam antibiotics. The lack of a successful inhibitor for them is related to the previous failure to characterize a reaction intermediate with a clinically useful substrate. Stopped-flow experiments together with rapid freeze−quench EPR and Raman spectroscopies were used to characterize the reaction of Co(II)−BcII with imipenem. These studies show that Co(II)−BcII is able to hydrolyze imipenem in both the mono- and dinuclear forms. In contrast to the situation met for penicillin, the species that accumulates during turnover is an enzyme−intermediate adduct in which the β-lactam bond has already been cleaved. This intermediate is a metal-bound anionic species with a novel resonant structure that is stabilized by the metal ion at the DCH or Zn2 site. This species has been characterized based on its spectroscopic features. This represents a novel, previously unforeseen intermediate that is related to the chemical nature of carbapenems, as confirmed by the finding of a similar intermediate for meropenem. Since carbapenems are the only substrates cleaved by B1, B2, and B3 lactamases, identification of this intermediate could be exploited as a first step toward the design of transition-state-based inhibitors for all three classes of metallo-β-lactamases

Datos enlazados en la Biblioteca Nacional de España

Datos enlazados en la Biblioteca Nacional de Españ