Relationship between solar radiation and surface distribution of vegetation in Fildes Peninsula and Ardley Island,Maritime Antarctica

The aim of this work is to produce a simplified vegetation map of ice-free areas of the Fildes Peninsula (FP) and Ardley Island (AI) thought object-oriented classification using a QuickBird satellite image and to evaluate the influence of the global solar radiation (GSR) over the vegetation distribution. The vegetation data were generated from multiresolution segmentation using the panchromatic and infrared layers, and for the classification we calculated the normalized vegetative difference index (NVDI) and the green NVDI. Two classes were created – Lichen and Moss Cushion SubFormation and Moss Subformation – with 48 vegetation samples collected on surveys during the austral summers of 2008 and 2009. We used a kappa index to evaluate the classification efficiency using 100 sampled points obtained in austral summer of 2013. The GSR was estimated, and in order to evaluate the effect of meteorological phenomena and cloudless, we measured the GSR using a net radiometer model CNR4 installed in FP between 2014 and 2016. The estimate of GSR was done for seasons of 2015, in order to estimate the light compensation point and the saturation point for the plant communities in FP and AI. The kappa index was 0.73 and the global accuracy was 0.78, showing consistency between the classification and ground truth. The area was covered by vegetation in FP was 16.7% and in AI is 59.1%. The vegetation cover is distributed differently at FP and AI, and our results suggest GSR plays an important role in vegetation distribution and these tendencies could be related to greater GSR demand by mosses when compared to lichens.     

Construction of baselines for VoIP traffic management on open MANs

In the last century, owing to the constant evolution of technologies telecommunication networks have become increasingly robust, being able to support multiple services. These services are part of the heterogeneous network traffic that can be carried through the Internet. Many of these services, including VoIP, are latency sensitive. In other words, this means that their quality depends directly on the network quality of service. Since users tend to become more sensitive with the instability and unavailability of the network, it is important to improve traffic management. A particular type of data that could be used to improve VoIP traffic management is the Internet Protocol Detail Record (IPDR). IPDRs are tickets created by all VoIP call attempts which contain a group of information related to the call history. Because of its full range of information, IPDRs can be used to create VoIP traffic baselines. This paper presents the development of baselines based on IPDRs to support VoIP traffic management in open‐access Metropolitan Area Networks (MAN). Copyright © 2013 John Wiley & Sons, Ltd.     

Dual joints for 3D-structures

The increasing popularity of 3D printing is drawing the interest of the research community to the possibilities and challenges of this manufacturing method. Amongst its many uncertainties, we are concerned here with one of its certainties—that reduction of the material required in 3D printing is critical for efficiency and affordability. In this paper, we propose a solution to the computer graphics problem of, given a volume boundary, automatically defining the mesh of a low density internal structure that is 3D-printable. The proposed solution involves two steps. The first step is to define a cell complex partition for the internal space of a volume defined by its boundaries. The second step, is to apply the Skin4Skeleton algorithm, which uses the cell complex dual to produce a 3D-printable cell-complex mesh with a parametrised thickness.     

Synthesis and characterisation of fluorescent pyrene‐end‐capped polylactide fibres

Fluorescent markers are critical for tracking the position and movement of molecules both in vivo and in vitro. Conventionally, synthetic dyes are non‐covalently added to polymers for fluorescent tracking, but often diffuse away. Here we demonstrate, for the first time, a facile method for the synthesis of fluorescent poly(lactic acid) nano‐/microfibres for biomedical applications using solution spin blowing. Pyrene‐end‐capped poly(l ‐lactide) (PLLA) derivatives were synthesised using the ring‐opening polymerisation of l ‐lactide and they were characterised using spectroscopic and thermal analyses. Submicrometre‐sized fluorescent fibres were produced from these PLLA derivatives using solution blow spinning techniques generating polymer blends and core–shell fibres. Such system could be further exploited to incorporate electrically conductive carbon allotropes via the pyrene aromaticity, producing fluorescent and electrically active fibres for in vitro monitoring and electrical stimulation. © 2018 Society of Chemical Industry     

A cluster-DEE-based strategy to empower protein design

The Medical and Pharmaceutical industries have shown high interest in the precise engineering of protein hormones and enzymes that perform existing functions under a wide range of conditions. Proteins are responsible for the execution of different functions in the cell: catalysis in chemical reactions, transport and storage, regulation and recognition control. Computational Protein Design (CPD) investigates the relationship between 3-D structures of proteins and amino acid sequences and looks for all sequences that will fold into such 3-D structure. Many computational methods and algorithms have been proposed over the last years, but the problem still remains a challenge for Mathematicians, Computer Scientists, Bioinformaticians and Structural Biologists. In this article we present a new method for the protein design problem. Clustering techniques and a Dead-End-Elimination algorithm are combined with a SAT problem representation of the CPD problem in order to design the amino acid sequences. The obtained results illustrate the accuracy of the proposed method, suggesting that integrated Artificial Intelligence techniques are useful tools to solve such an intricate problem.     

Building a bridge between performance management,radical innovation,and innovation networks: A systematic literature review

Research on performance management (PM) of networks and radical innovation has largely developed along two isolated paths. On the one hand, a growing body of knowledge addresses the use of performance management systems in the context of networks (notably for production and incremental innovation). On the other hand, radical innovation scholars have shown how innovation initiatives that are more uncertain demand the use of new approaches (e.g., new project management routines or different evaluative tools for portfolios). Some scholars even suggest that traditional PM may suppress radical innovation. Our study takes a different approach. It aims to bridge radical innovation and network performance management through a systematic review of the literature. Here, we adopt a hybrid approach that combines bibliometrics with content analysis. Whereas the literature often separates the issues of network performance management and radical innovation, our contribution expands the theory of network management and radical innovation by developing a conceptual framework based on these concepts, thus combining them. We also offer suggestions for further research on this approach. Our framework suggests that overall, the performance management of radical innovation networks presents different features (e.g., recursive rather than linear) and constructs (e.g., openness and unintended performance) from those of innovation network management.     

A semantic role labelling-based framework for learning ontologies from Spanish documents

Currently, most of the information available in the Web is adapted primarily for human consumption, but there is so much information that can no longer be processed by a person in a reasonable time, either in digital or physical formats. To solve this problem, the idea of the Semantic Web arose. The Semantic Web deals with adding machine-readable information to Web pages. Ontologies represent a very important element of this web, as they provide a valid and robust structure to represent knowledge based on concepts, relations, axioms, etc. The need for overcoming the bottleneck provoked by the manual construction of ontologies has generated several studies and research on obtaining semiautomatic methods to learn ontologies. In this sense, this paper proposes a new ontology learning methodology based on semantic role labeling from digital Spanish documents. The method makes it possible to represent multiple semantic relations specially taxonomic and partonomic ones in the standardized OWL 2.0. A set of experiments has been performed with the approach implemented in educational domain that show promising results.     

Mining: The Challenge Knocks on our Door

Mining will continue to be an important economic component due to the incessant demand for raw materials, but the industry needs to balance the extraction of mineral resources with its obligations to abide by all laws, benefit the local community, and contribute to regional development. Proper management of mine water through reuse, reduced consumption, and desalination is key to attaining a higher level of public acceptance, as is making sure that the public learns of the advantages that our industry brings.