The HEPD particle detector of the CSES satellite mission for investigating seismo-associated perturbations of the Van Allen belts

CSES(China Seismo-Electromagnetic Satellite) is a mission developed by CNSA(Chinese National Space Administration) and ASI(Italian Space Agency), to investigate the near-Earth electromagnetic, plasma and particle environment, for studying the seismo-associated disturbances in the ionosphere-magnetosphere transition zone. The anthropogenic and electromagnetic noise,as well as the natural non-seismic electromagnetic emissions is mainly due to tropospheric activity. In particular, the mission aims to confirming the existence of possible temporal correlations between the occurrence of earthquakes for medium and strong magnitude and the observation in space of electromagnetic perturbations, plasma variations and precipitation of bursts with highenergy charged particles from the inner Van Allen belt. In this framework, the high energy particle detector(HEPD) of the CSES mission has been developed by the Italian LIMADOU Collaboration. HEPD is an advanced detector based on a tower of scintillators and a silicon tracker that provides good energy and angular resolution and a wide angular acceptance, for electrons of 3–100 Me V, protons of 30–200 Me V and light nuclei up to the oxygen. CSES satellite has been launched on February 2~(nd), 2018 from the Jiuquan Satellite Launch Center(China).     

Multi-scale computational model for design of flexible pavement – part I: expanding multi-scaling

A computational multi-scale procedure for designing flexible pavement is developed in this, the first of a three part series. In this paper, computational analyses are performed on sequentially larger length scales, termed expanding multi-scaling. The model is constructed by the finite element method at each length scale, thereby creating a one-way coupled multi-scale algorithm that is capable of accounting for the effects of variations in design parameters at each length scale on the performance of flexible pavements. For example, the algorithm can be utilised to predict the effects of small-scale design variables such as volume fractions of additives, fines and aggregate, as well as the effects of large-scale design variables such as asphalt concrete thickness and degree of base layer compaction on rutting due to cyclic loading. The computational procedure is briefly herein, including the experimental properties required to deploy the computational scheme for the purpose of pavement design. The paper concludes with several demonstrative examples intended to elucidate the power of this predictive technology for the purpose of designing more sustainable pavements.     

Population dynamics of yeasts inhabiting bioethanol production with cell recycling

Seeking to understand the dynamics of the yeast population in a bioethanol fermentation process that uses cell recycling, the yeast inhabiting the fermentation tanks throughout the production season were monitored. A total of 26 yeasts were isolated from tanks in a Brazilian bioethanol distillery plant during six different periods of the season. These yeasts were evaluated with regard to fermentative capacity and all yeasts were qualified to be used for bioethanol production. Based on the numerical taxonomy, it was possible to say that they were all representative of Saccharomyces sensu stricto. A total of 10 different banding patterns were obtained from the 16 strains isolated. This work has shown that the yeast introduced at the beginning of the season was quickly replaced by one or more native yeast strains. It was also shown that the replacement of these strains is not always harmful to the process and isolating such yeasts found in the fermentation tanks could be an interesting strategy for new strain selection. Copyright © 2015 The Institute of Brewing & Distilling     

Methodology for Data and Information Quality Assessment in the Context of Emergency Situational Awareness

Universal Access in the Information Society - Situation Assessment (SA) approaches aim to provide powerful resources to support decision makers in enhancing their Situational Awareness (SAW). The...     

Degradation of 14c‐maneb in sediment from a Nicaraguan estuary

Sediment samples were collected at 5 sites in the Nicaraguan estuary “El Naranjo” in July 94 and September 94. The samples were incubated with ¹⁴C‐maneb (0.08 μg.g^‐1 dw sediment), and evolved ¹⁴CO₂ and residual ¹⁴C‐ETU in soil were measured. Mineralization kinetics of ^I4C‐maneb was best described with kinetic models which include growth of microorganisms. The amounts of ¹⁴C‐maneb mineralized were highest at the sites closest to the mouth of the river. No significant differences in degradation between July and September were seen. After 67 days between 9.73 and 16.18% of added ¹⁴C had evolved as ¹⁴CO₂ in the July samples and after 150 days between 11.18 and 27.37% of added ¹⁴C had evolved as ¹⁴CO₂ from the September samples. When 4.61–8.20% of added ^I4C was found in the soil extract, 0.00–2.72% was ¹⁴C‐ETU.     

Towards an ontology modeling tool. A validation in software engineering scenarios

Ontology creation and management related processes are very important to define and develop semantic services. Ontology Engineering is the research field that provides the mechanisms to manage the life cycle of the ontologies. However, the process of building ontologies can be tedious and sometimes exhaustive. OWL-VisMod is a tool designed for developing ontological engineering based on visual analytics conceptual modeling for OWL ontologies life cycle management, supporting both creation and understanding tasks. This paper is devoted to evaluate OWL-VisMod through a set of defined tasks. The same tasks also will be done with the most known tool in Ontology Engineering, Protégé, in order to compare the obtained results and be able to know how is OWL-VisMod perceived for the expert users. The comparison shows that both tools have similar acceptation scores, but OWL-VisMod presents better feelings regarding user’s perception tasks due to the visual analytics influence.