Comuns: An Open-Data Provider, Explorer and Analytic Toolbox Based on FOSS

Contém resumo

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

An agent-based model to assess the attractiveness of industrial estates

This article describes the main approaches adopted in a study focused on planning industrial estates on a sub-regional scale. The study was supported by an agent-based model, using firms as agents to assess the attractiveness of industrial estates. The simulation was made by the NetLogo toolkit and the environment represents a geographical space. Three scenarios and four hypotheses were used in the simulation to test the impact of different policies on the attractiveness of industrial estates. Policies were distinguished by the level of municipal coordination at which they were implemented and by the type of intervention. In the model, the attractiveness of industrial estates was based on the level of facilities, amenities, accessibility and on the price of land in each industrial estate. Firms are able to move and relocate whenever they find an attractive estate. The relocating firms were selected by their size, location and distance to an industrial estate. Results show that a coordinated policy among municipalities is the most efficient policy to promote advanced-qualified estates. In these scenarios, it was observed that more industrial estates became attractive, more firms were relocated and more vacant lots were occupied. Furthermore, the results also indicate that the promotion of widespread industrial estates with poor-quality infrastructures and amenities is an inefficient policy to attract firms.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Scenario-based assessment of future land use change on butterfly species distributions

Species distribution models (SDMs) are increasingly used to predict environmentally induced range shifts of habitats of plant and animal species. Consequently SDMs are valuable tools for scientifically based conservation decisions. The aims of this paper are (1) to identify important drivers of butterfly species persistence or extinction, and (2) to analyse the responses of endangered butterfly species of dry grasslands and wetlands to likely future landscape changes in Switzerland. Future land use was represented by four scenarios describing: (1) ongoing land use changes as observed at the end of the last century; (2) a liberalisation of the agricultural markets; (3) a slightly lowered agricultural production; and (4) a strongly lowered agricultural production. Two model approaches have been applied. The first (logistic regression with principal components) explains what environmental variables have significant impact on species presence (and absence). The second (predictive SDM) is used to project species distribution under current and likely future land uses. The results of the explanatory analyses reveal that four principal components related to urbanisation, abandonment of open land and intensive agricultural practices as well as two climate parameters are primary drivers of species occurrence (decline). The scenario analyses show that lowered agricultural production is likely to favour dry grassland species due to an increase of non-intensively used land, open canopy forests, and overgrown areas. In the liberalisation scenario dry grassland species show a decrease in abundance due to a strong increase of forested patches. Wetland butterfly species would decrease under all four scenarios as their habitats become overgrown

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Learning-induced plasticity in human audition: Objects, time, and space.

The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.

Segmentation of brain structures in presence of a space-occupying lesion.

Brain deformations induced by space-occupying lesions may result in unpredictable position and shape of functionally important brain structures. The aim of this study is to propose a method for segmentation of brain structures by deformation of a segmented brain atlas in presence of a space-occupying lesion. Our approach is based on an a priori model of lesion growth (MLG) that assumes radial expansion from a seeding point and involves three steps: first, an affine registration bringing the atlas and the patient into global correspondence; then, the seeding of a synthetic tumor into the brain atlas providing a template for the lesion; finally, the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. The method was applied on two meningiomas inducing a pure displacement of the underlying brain structures, and segmentation accuracy of ventricles and basal ganglia was assessed. Results show that the segmented structures were consistent with the patient's anatomy and that the deformation accuracy of surrounding brain structures was highly dependent on the accurate placement of the tumor seeding point. Further improvements of the method will optimize the segmentation accuracy. Visualization of brain structures provides useful information for therapeutic consideration of space-occupying lesions, including surgical, radiosurgical, and radiotherapeutic planning, in order to increase treatment efficiency and prevent neurological damage.

Agent based simulation to optimise emergency departments

Nowadays, many of the health care systems are large and complex environments and quite dynamic, specifically Emergency Departments, EDs. It is opened and working 24 hours per day throughout the year with limited resources, whereas it is overcrowded. Thus, is mandatory to simulate EDs to improve qualitatively and quantitatively their performance. This improvement can be achieved modelling and simulating EDs using Agent-Based Model, ABM and optimising many different staff scenarios. This work optimises the staff configuration of an ED. In order to do optimisation, objective functions to minimise or maximise have to be set. One of those objective functions is to find the best or optimum staff configuration that minimise patient waiting time. The staff configuration comprises: doctors, triage nurses, and admissions, the amount and sort of them. Staff configuration is a combinatorial problem, that can take a lot of time to be solved. HPC is used to run the experiments, and encouraging results were obtained. However, even with the basic ED used in this work the search space is very large, thus, when the problem size increases, it is going to need more resources of processing in order to obtain results in an acceptable time.

Liver hyperplasia and paradoxical regulation of glycogen metabolism and glucose-sensitive gene expression in GLUT2-null hepatocytes. Further evidence for the existence of a membrane-based glucose release pathway.

We investigated the impact of GLUT2 gene inactivation on the regulation of hepatic glucose metabolism during the fed to fast transition. In control and GLUT2-null mice, fasting was accompanied by a approximately 10-fold increase in plasma glucagon to insulin ratio, a similar activation of liver glycogen phosphorylase and inhibition of glycogen synthase and the same elevation in phosphoenolpyruvate carboxykinase and glucose-6-phosphatase mRNAs. In GLUT2-null mice, mobilization of glycogen stores was, however, strongly impaired. This was correlated with glucose-6-phosphate (G6P) levels, which remained at the fed values, indicating an important allosteric stimulation of glycogen synthase by G6P. These G6P levels were also accompanied by a paradoxical elevation of the mRNAs for L-pyruvate kinase. Re-expression of GLUT2 in liver corrected the abnormal regulation of glycogen and L-pyruvate kinase gene expression. Interestingly, GLUT2-null livers were hyperplasic, as revealed by a 40% increase in liver mass and 30% increase in liver DNA content. Together, these data indicate that in the absence of GLUT2, the G6P levels cannot decrease during a fasting period. This may be due to neosynthesized glucose entering the cytosol, being unable to diffuse into the extracellular space, and being phosphorylated back to G6P. Because hepatic glucose production is nevertheless quantitatively normal, glucose produced in the endoplasmic reticulum may also be exported out of the cell through an alternative, membrane traffic-based pathway, as previously reported (Guillam, M.-T., Burcelin, R., and Thorens, B. (1998) Proc. Natl. Acad. Sci. U. S. A. 95, 12317-12321). Therefore, in fasting, GLUT2 is not required for quantitative normal glucose output but is necessary to equilibrate cytosolic glucose with the extracellular space. In the absence of this equilibration, the control of hepatic glucose metabolism by G6P is dominant over that by plasma hormone concentrations.

Space-time within general relativity : a structural realist understanding

ABSTRACT This dissertation investigates the, nature of space-time as described by the theory of general relativity. It mainly argues that space-time can be naturally interpreted as a physical structure in the precise sense of a network of concrete space-time relations among concrete space-time points that do not possess any intrinsic properties and any intrinsic identity. Such an interpretation is fundamentally based on two related key features of general relativity, namely substantive general covariance and background independence, where substantive general covariance is understood as a gauge-theoretic invariance under active diffeomorphisms and background independence is understood in the sense that the metric (or gravitational) field is dynamical and that, strictly speaking, it cannot be uniquely split into a purely gravitational part and a fixed purely inertial part or background. More broadly, a precise notion of (physical) structure is developed within the framework of a moderate version of structural realism understood as a metaphysical claim about what there is in the world. So, the developement of this moderate structural realism pursues two main aims. The first is purely metaphysical, the aim being to develop a coherent metaphysics of structures and of objects (particular attention is paid to the questions of identity and individuality of these latter within this structural realist framework). The second is to argue that moderate structural realism provides a convincing interpretation of the world as described by fundamental physics and in particular of space-time as described by general relativity. This structuralist interpretation of space-time is discussed within the traditional substantivalist-relationalist debate, which is best understood within the broader framework of the question about the relationship between space-time on the one hand and matter on the other. In particular, it is claimed that space-time structuralism does not constitute a 'tertium quid' in the traditional debate. Some new light on the question of the nature of space-time may be shed from the fundamental foundational issue of space-time singularities. Their possible 'non-local' (or global) feature is discussed in some detail and it is argued that a broad structuralist conception of space-time may provide a physically meaningful understanding of space-time singularities, which is not plagued by the conceptual difficulties of the usual atomsitic framework. Indeed, part of these difficulties may come from the standard differential geometric description of space-time, which encodes to some extent this atomistic framework; it raises the question of the importance of the mathematical formalism for the interpretation of space-time.

Tethyan margins in space and time

Rifting processes, leading to sea-floor spreading, are characterized by a sequence of events: transtensive phase of extension with syn-rift volcanism; simple shear extension accompanied by lithospheric thinning and asthenospheric up-welling and thermal uplift of the rift shoulder and asymmetric volcanism. The simple shear model of extension leads to an asymmetric model of passive margin: a lower plate tilted block margin and an upper plate flexural, ramp-like margin- Both will be affected by thermal contraction and subsidence, starting soon after sea-floor spreading. Based on these actualistic models Tethyan margins are classified as one type or the other. Their evolution from the first transtensional phase of extension to the passive margin stage are analyzed. Four main rifting events are recognized in the Tethyan realm: an episode of lower Paleozoic events leading to the formation of the Paleotethys; a Late Paleozoic event leading to the opening of the Permotethys and East Mediterranean basin: an early Mesozoic event leading to the opening of the Pindos Neotethys and a Jurassic event related to the opening of the Alpine/Atlantic Neotethys. Type margins are given as example of each rifting event: -Northern Iran (Alborz) as a type area for the Late Ordovician to Silurian rifting of Paleotethys. -Northern India and Oman for the Late Carboniferous to early Permian rifting of Permotethys. -The East Mediterranean (Levant, Tunisia) as a Late Carboniferous rifting event. -The Neotethyan rifting phases are separated in two types: an eastern Pindos system found in Turkey and Greece is genetically linked to the Permotethys with a sea-floor spreading delayed until middle Triassic: a western Alpine system directly linked to the opening of the central Atlantic is characterized by a Late Triassic transtensive phase, an early to Middle Liassic break-away phase and. following sea-floor spreading, a thermal subsidence phase starting in Dogger. Problems related to the closure of the Paleozoic oceanic domains are reviewed. A Late Permian, early Triassic phase of `'docking'' between an European accretionary prism (Chios) and a Paleotethyan margin is supported by recent findings in the Mediterranean area. Back-arc rifting within the European active margin led to the formation of marginal seas during Permian and Triassic times and will contribute to the closure of the Paleozoic oceans.

Global regulation of the knowledge-based economy: The rise of standards in educational services

This article examines the extent and limits of non-state forms of authority in international relations. It analyses how the information and communication technology (ICT) infrastructure for the tradability of services in a global knowledge-based economy relies on informal regulatory practices for adjustment of ICT-related skills. Companies and associations provide training and certification programmes as part of a growing market for educational services setting their own standards. The existing literature on non-conventional forms of authority in the global political economy has emphasised that the consent of actors subject to informal rules and explicit or implicit state recognition remains crucial for the effectiveness of those new forms of power. However, analyses based on a limited sample of actors tend toward a narrow understanding of the issues and fail to fully explore the differentiated space in which non-state authority is emerging. This paper examines the form of authority underpinning the global knowledge-based economy within the broader perspective of the issues likely to be standardised by technical ICT specification, the wide range of actors involved, and the highly differentiated space where standards become authoritative. The empirical findings highlight the role of different private actors in establishing international educational norms in this field. They also pinpoint the limits of profit-oriented standard-settings, notably with regard to generic norms.

Towards a Social Learning Space for Open Educational Resources

We identify a number of meanings of "Open", as part of the motivating rationale for a social media space tuned for learning, called SocialLearn. We discuss why online social learning seems to be emerging so strongly at this point, explore features of social learning, and identify some of the dimensions that we believe characterize the social learning design space, before describing the emerging design concept and implementation.