Hausdorff Dimension of the Record Set of a Fractional Brownian Motion

We prove that the Hausdorff dimension of the record set of a fractional Brownian motion with Hurst parameter $H$ equals $H$

Endothelin receptor antagonism versus combined ECE/NEP inhibition in patients with type 2 diabetes and nephropathy

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Trapped Ion Mobility Spectrometry coupled to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry for the analysis of Complex Mixtures.

Analytical Characterization of complex mixtures, such as crude oil, environmental samples, and biological mixtures, is challenging because of the large diversity of molecular components. Mass spectrometry based techniques are among the most powerful tools for the separation of molecules based on their molecular composition, and the coupling of ion mobility spectrometry has enabled the separation and structural elucidation using the tridimensional structure of the molecule. The present work expands the ability of analytical chemists by furthering the development of IMS-MS instrumentation by coupling Trapped Ion Mobility Spectrometry to Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (TIMS-FT-ICR MS). The TIMS-FT-ICR MS platform combines the high-resolution separation of TIMS, which has mobility resolving powers up to 400, and ultra-high mass resolution of FT-ICR MS, with mass resolving power over 1,000,000. This instrumentation allows the assignment of exact chemical composition for compounds in a complex mixture, as well as measurement of the collision cross-section of the molecule. Herein, the principles of the TIMS separation and its coupling to FT-ICR MS are described, as well as how the platform can be applied to targeted analysis of molecules, and untargeted characterization of complex mixtures. Molecular standards were analyzed by TIMS-MS in order to develop a computational workflow that can be utilized to elucidate molecular structure, using the measured collision cross-section of the ion. This workflow enabled identification of structural, cis/trans isomers, and chelated molecules and provides the basis for unsupervised structural elucidation of a complex mixture, and in particular for the elucidation of hydrocarbons from fossil fuels. In summary, this work presents the coupling of TIMS-FT-ICR MS and provides examples of applications as a proof of concept of the potential of this platform for solving complex analytical challenges

Km4City Ontology Building vs Data Harvesting and Cleaning for Smart-city Services

Presently, a very large number of public and private data sets are available from local governments. In most cases, they are not semantically interoperable and a huge human effort would be needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity, to allow the data reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big data volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to a smart-city ontology, called KM4City (Knowledge Model for City), and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users via specific applications of public administration and enterprises. The paper presents the process adopted to produce the ontology and the big data architecture for the knowledge base feeding on the basis of open and private data, and the mechanisms adopted for the data verification, reconciliation and validation. Some examples about the possible usage of the coherent big data knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection