How Noisy Data Affects Geometric Semantic Genetic Programming

Noise is a consequence of acquiring and pre-processing data from the environment, and shows fluctuations from different sources---e.g., from sensors, signal processing technology or even human error. As a machine learning technique, Genetic Programming (GP) is not immune to this problem, which the field has frequently addressed. Recently, Geometric Semantic Genetic Programming (GSGP), a semantic-aware branch of GP, has shown robustness and high generalization capability. Researchers believe these characteristics may be associated with a lower sensibility to noisy data. However, there is no systematic study on this matter. This paper performs a deep analysis of the GSGP performance over the presence of noise. Using 15 synthetic datasets where noise can be controlled, we added different ratios of noise to the data and compared the results obtained with those of a canonical GP. The results show that, as we increase the percentage of noisy instances, the generalization performance degradation is more pronounced in GSGP than GP. However, in general, GSGP is more robust to noise than GP in the presence of up to 10% of noise, and presents no statistical difference for values higher than that in the test bed.Comment: 8 pages, In proceedings of Genetic and Evolutionary Computation Conference (GECCO 2017), Berlin, German

Dispatcher3 D7.1 - Project communication, dissemination and exploitation plan

This document is the Communication, Dissemination and Exploitation Plan (D7.1) of the Clean Sky 2 Innovation Action Dispatcher3. The document defines the communication and dissemination actions to be performed during the project, and the potential exploitation of the project results. A complete strategy of communication is presented, as well as the items and content already prepared for it

A distributed bio-inspired method for multisite grid mapping

Computational grids assemble multisite and multiowner resources and represent the most promising solutions for processing distributed computationally intensive applications, each composed by a collection of communicating tasks. The execution of an application on a grid presumes three successive steps: the localization of the available resources together with their characteristics and status; the mapping which selects the resources that, during the estimated running time, better support this execution and, at last, the scheduling of the tasks. These operations are very difficult both because the availability and workload of grid resources change dynamically and because, in many cases, multisite mapping must be adopted to exploit all the possible benefits. As the mapping problem in parallel systems, already known as NP-complete, becomes even harder in distributed heterogeneous environments as in grids, evolutionary techniques can be adopted to find near-optimal solutions. In this paper an effective and efficient multisite mapping, based on a distributed Differential Evolution algorithm, is proposed. The aim is to minimize the time required to complete the execution of the application, selecting from among all the potential ones the solution which reduces the use of the grid resources. The proposed mapper is tested on different scenarios

A thermoanalytical insight into the composition of biodegradable polymers and commercial products by EGA-MS and Py-GC-MS

Biodegradable polymers are proposed as a potential solution to environmental problems related to plastic pollution. Potential benefits have been suggested in applications such as agricultural mulching and fishing gear, where there can be considerable difficulty recovering products from the environment at the end of their service life. Biodegradation is a complex process influenced by both the properties of the material and the receiving environment in which it needs to biodegrade. Assessing the degradation process necessitates the chemical composition (i.e. polymer and additives) of biodegradable products to be characterised by reliable analytical methods. Pyrolysis coupled to Gas Chromatography and Mass Spectrometry (Py-GC-MS) and Evolved Gas Analysis coupled to Mass Spectrometry (EGA-MS) are emerging techniques to characterise plastic materials, providing a greater sensitivity and resolution when compared to more widely used spectroscopic techniques (FTIR and Raman). In this work, we have applied a systematic approach combining EGA-MS and multi-shot Py-GC-MS for the thermoanalytical investigation of 5 biodegradable polymers and 5 biodegradable-labelled commercial products. We identified thermal degradation profiles, main m/z ions and pyrolysis markers for the polymers PBAT, PBS, PBHV and two types of PLA. We applied the obtained information to investigate the composition of 4 mulch films and 1 fishing net. EGA-MS was fundamental to optimise single or multi shot pyrolysis acquisition, allowing an optimal Py-GC-MS separation and identification of the pyrolysis products. PLA and PBAT were detected in three mulch films, with the addition of starch in a film labelled as Mater-Bi and in one of unknown composition. Online silylation was crucial for detecting polysaccharides in a composite film containing hemp fibres. The presence of butylene, succinate, adipate and terephthalate units was highlighted analysing a fishing net made of a newly developed PBSAT resin. Finally, Py-GC-MS was effective in identifying the presence of additives such as 1,6-diisocyanato-hexane (chain extender) and di(3-butenyl) ester of sebacic acid derived from the plasticizer dibutyl sebacate

Automated optical identification of a large complete northern hemisphere sample of flat spectrum radio sources with S_6cm > 200 mJy

This paper describes the automated optical APM identification of radio sources from the Jodrell Bank - VLA Astrometric Survey (JVAS), as used for the search for distant radio-loud quasars. The sample has been used to investigate possible relations between optical and radio properties of flat spectrum radio sources. From the 915 sources in the sample, 756 have an optical APM identification at a red (e) and/or blue (o) plate,resulting in an identification fraction of 83% with a completeness and reliability of 98% and 99% respectively. About 20% are optically identified with extended APM objects on the red plates, e.g. galaxies. However the distinction between galaxies and quasars can not be done properly near the magnitude limit of the POSS-I plates. The identification fraction appears to decrease from >90% for sources with a 5 GHz flux density of >1 Jy, to <80% for sources at 0.2 Jy. The identification fraction, in particular that for unresolved quasars, is found to be lower for sources with steeper radio spectra. In agreement with previous studies, we find that the quasars at low radio flux density levels also tend to have fainter optical magnitudes, although there is a large spread. In addition, objects with a steep radio-to-optical spectral index are found to be mainly highly polarised quasars, supporting the idea that in these objects the polarised synchrotron component is more prominent. It is shown that the large spread in radio-to-optical spectral index is possibly caused by source to source variations in the Doppler boosting of the synchrotron component [Abridged].Comment: LaTex, 17 pages, 5 gif figures, 4 tables. Accepted for publication in MNRAS. High resolution figures can be found at http://www.roe.ac.uk/~ignas

An Explicit Framework for Interaction Nets

Interaction nets are a graphical formalism inspired by Linear Logic proof-nets often used for studying higher order rewriting e.g. \Beta-reduction. Traditional presentations of interaction nets are based on graph theory and rely on elementary properties of graph theory. We give here a more explicit presentation based on notions borrowed from Girard's Geometry of Interaction: interaction nets are presented as partial permutations and a composition of nets, the gluing, is derived from the execution formula. We then define contexts and reduction as the context closure of rules. We prove strong confluence of the reduction within our framework and show how interaction nets can be viewed as the quotient of some generalized proof-nets

Prolyl 3‐hydroxylase 2 is a molecular player of angiogenesis

Prolyl 3‐hydroxylase 2 (P3H2) catalyzes the post‐translational formation of 3‐ hydroxyproline on collagens, mainly on type IV. Its activity has never been directly associated to angiogenesis. Here, we identified P3H2 gene through a deep‐sequencing transcriptome analysis of human umbilical vein endothelial cells (HUVECs) stimulated with vascular endothelial growth factor A (VEGF‐A). Differently from many previous studies we carried out the stimulation not on starved HUVECs, but on cells grown to maintain the best condition for their in vitro survival and propagation. We showed that P3H2 is induced by VEGF‐A in two primary human endothelial cell lines and that its transcription is modulated by VEGF‐A/VEGF receptor 2 (VEGFR‐2) signaling pathway through p38 mitogen‐activated protein kinase (MAPK). Then, we demonstrated that P3H2, through its activity on type IV Collagen, is essential for angiogenesis properties of endothelial cells in vitro by performing experiments of gain‐ and loss‐of‐function. Immunofluorescence studies showed that the overexpression of P3H2 induced a more condensed status of Collagen IV, accompanied by an alignment of the cells along the Collagen IV bundles, so towards an evident pro‐angiogenic status. Finally, we found that P3h2 knockdown prevents pathological angiogenesis in vivo, in the model of laser‐induced choroid neovascularization. Together these findings reveal that P3H2 is a new molecular player involved in new vessels formation and could be considered as a potential target for anti‐angiogenesis therapy

Evolution of a single incised valley related to inherited geology, sea level rise and climate changes during the Holocene (Tirso river, Sardinia, western Mediterranean Sea)

We performed a morpho-stratigraphic study of the Tirso River incised valley (Sardinia Island, western Mediterranean Sea), an erosional feature crossing the Sinis fault, a major normal fault bordering the Campidano basin between the Gulf of Oristano and the western Sardinia shelf. High-resolution seismic reflection profiles and multibeam echosounder data, integrated by age-constrained stratigraphic logs derived from 9 sediment cores enabled us to reconstruct the valley evolution during the Holocene. We found that the Tirso valley is the result of a single event of incision and infill during the last eustatic cycle, strongly controlled by the presence of the Sinis fault. In fact, this structure represents a geological threshold that marks an abrupt change in substrate lithology and seabed slope, which controlled the valley morphology, narrow when downcutting early Pliocene formations along the steeper open shelf, and wider inside the Gulf, in the Pleistocene alluvial deposits of the flatter Gulf of Oristano. The sedimentary record starts with alluvial sediments filling the valley along the shelf during the initial phase of sea level rise, i.e., over 10 ka. During the last ~9.0 ka, a bay head delta developed, with the formation of barriers at the gulf entrance. In the mid-late Holocene, the progressive sea-level rise led to rapid drowning of the barrier system, recorded by marine and estuarine sediments filling the valley. Analysis of ecological associations in the cores, collected along a valley-normal transect, allowed for a detailed reconstruction of the paleo-environmental conditions during the latest phase of the incised valley filling controlled by global climatic variations in the Mediterranean region between ~9.0 and ~ 4.5 ka. Together with eustasy, our work reveals that the evolution and sedimentary infill of the Tirso incised valley was strongly controlled by inherited geological constraints, which influenced the morphology of the valley and the stratigraphic pattern