Registry of all events from the Tara Oceans Expedition (2009-2013)

The Tara Oceans Expedition (2009-2013) sampled the world oceans on board a 36 m long schooner, collecting environmental data and organisms from viruses to planktonic metazoans for later analyses using modern sequencing and state-of-the-art imaging technologies. Tara Oceans Data are particularly suited to study the genetic, morphological and functional diversity of plankton. The present data set is a registry of all events conducted during the Tara Oceans Expedition (2009-2013). The registry provides details about the sampling date, time, location and methodology of each event. Uniform resource locators (URLs) offer direct links to the corresponding (1) event logsheet filled on board, (2) environmental data published at PANGAEA, (3) list of samples prepared on board from each event, and (4) nucleotides data published at the European Nucleotides Archive (EBI-ENA).

Registry of selected samples from the Tara Oceans Expedition (2009-2013)

The present data set is a registry of samples from the Tara Oceans Expedition (2009-2013) that were selected for publication in a special issue of the SCIENCE journal (see related references below). The registry provides details about the sampling location and methodology of each sample. Uniform resource locators (URLs) offer direct links to additional contextual environmental data and to the corresponding sequence runs used for analysis in the related literature publications in the SCIENCE journal.

Biodiversity context of selected samples from the Tara Oceans Expedition (2009-2013)

The present data set provides contextual data for samples from the Tara Oceans Expedition (2009-2013) that were selected for publication in a special issue of the SCIENCE journal (see related references below). Contextual data include various diversity indexes calculated for the sampling location using satellite and model climatologies (Darwin project, Physat) and results from the sequencing of Tara Oceans samples.

A Naturalist Abroad in the Museum of Ontology : Phillipe Descola's Beyond Nature and Culture

Peer reviewed

Implicit Feature Selection with the Value Difference Metric

Publisher PDF

An Ontology for Experimentation with a Social Simulation of Land Use Change

Publisher PDF

Ontology and gnoseology of capitalism in Isaak Illich Rubin: 'Essays on marxist theory of value'

This concise essay attempts to show why Isaak Illich Rubin is, until today, the best interpreter, commentator and developer of The Capital of Karl Marx, understanding Marx’s work as an ontology and a gnoseology of the capitalist economic system. To do this, we analyze the relations existing between Marx, Rubin and the theory of science of the Spanish Marxist philosopher Gustavo Bueno. In this way, we can interpret the work “Essays on Marxist theory of value” also as an ontology and a gnoseology of capitalism.

Large volume metrology process model:measurability analysis with integration of metrology classification model and feature-based selection model

Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.

Formation of sub-7 nm feature size PS-b-P4VP block copolymer structures by solvent vapour process

The nanometer range structure produced by thin films of diblock copolymers makes them a great of interest as templates for the microelectronics industry. We investigated the effect of annealing solvents and/or mixture of the solvents in case of symmetric Poly (styrene-block-4vinylpyridine) (PS-b-P4VP) diblock copolymer to get the desired line patterns. In this paper, we used different molecular weights PS-b-P4VP to demonstrate the scalability of such high χ BCP system which requires precise fine-tuning of interfacial energies achieved by surface treatment and that improves the wetting property, ordering, and minimizes defect densities. Bare Silicon Substrates were also modified with polystyrene brush and ethylene glycol self-assembled monolayer in a simple quick reproducible way. Also, a novel and simple in situ hard mask technique was used to generate sub-7nm Iron oxide nanowires with a high aspect ratio on Silicon substrate, which can be used to develop silicon nanowires post pattern transfer.

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Language, Logos, and Social Ontology: Naturalist and Post-Naturalist Narratives of Human Rationality and Social Reality

I distinguish two ways that philosophers have approached and explained the reality and status of human social institutions. I call these approaches “naturalist” and “post-naturalist”. Common to both approaches is an understanding that the status of mind and its relation to the world or “nature” has implications on a conception of the status of institutional reality. Naturalists hold that mind is explicable within a scientific frame that conceives of mind as a fundamentally material process. By proxy, social reality is also materially explicable. Post-naturalists critique this view, holding instead that naturalism is parasitic on contemporary science—it therefore is non-compulsory and distorts how we ought to understand mind and social reality. A comparison of naturalism and post-naturalism will comprise the content of the first chapter. The second chapter turns to tracing out the dimensions of a post-naturalist narrative of mind and social reality. Post-naturalists conceive of mind and its activity of thought as sui generis, and it transpires from this that social institutions are better understood as a rational mind’s mode of the expression in the world. Post-naturalism conceives of social reality as a necessary dimension of thought. Thought requires a second person and thereby a tradition or context of norms that come to both structure its expression and become the products of expression. This is in contrast to the idea that social reality is a production of minds, and thereby derivative. Social reality, self-conscious thought, and thought of the second person are therefore three dimensions of a greater unity.

City dweller aspirations for cities of the future: How do environmental and personal wellbeing feature?

This paper explores city dweller aspirations for cities of the future in the context of global commitments to radically reduce carbon emissions by 2050; cities contribute the vast majority of these emissions and a growing bulk of theworld's population lives in cities. The particular challenge of creating a carbon reduced future in democratic countries is that the measures proposed must be acceptable to the electorate. Such acceptability is fostered if carbon reduced ways of living are also felt to bewellbeing maximising. Thus the objective of the paper is to explore what kinds of cities people aspire to live in, to ascertain whether these aspirations align with or undermine carbon reduced ways of living, as well as personal wellbeing. Using a novel free associative technique, city aspirations are found to cluster around seven themes, encompassing physical and social aspects. Physically, people aspire to a city with a range of services and facilities, green and blue spaces, efficient transport, beauty and good design. Socially, people aspire to a sense of community and a safe environment. An exploration of these themes reveals that only a minority of the participants' aspirations for cities relate to lowering carbon or environmental wellbeing. Far more consensual is emphasis on, and a particular vision of, aspirations that will bring personal wellbeing. Furthermore, city dweller aspirations align with evidence concerning factors that maximise personal wellbeing but, far less, with those that produce lowcarbonways of living. In order to shape a lower carbon future that city dwellers accept the potential convergence between environmental and personal wellbeing will need to be capitalised on: primarily aversion to pollution and enjoyment of communal green space.

Looking for Determinants of Ontological Security in the Spain of the Crisis

The concept of ontological security has a remarkable echo in the current sociology to describe emotional status of men of late modernity. However, the concept created by Giddens in the eighties has been little used in empirical research covering various sources of risk or uncertainty. In this paper, a scale for ontological security is proposed. To do this, we start from the results of a research focused on the relationship between risk, uncertainty and vulnerability in the context of the economic crisis in Spain. These results were produced through nine focus groups and a telephone survey with standardized questionnaire applied to a national sample of 2,408 individuals over 18 years. This work is divided into three main sections. In the fi rst, a scale has been built from the results of the application of different items present in the questionnaire used. The second part explores the relationships of the scale obtained with the variables further approximate the emotional dimensions of individuals. The third part observes the variables that contribute to changes in the scale: These variables show the structural feature of the ontological security.

Feature recognition & tool path generation for 5 axis step-nc machining of free form / irregular contoured surfaces

This research paper presents a five step algorithm to generate tool paths for machining Free form / Irregular Contoured Surface(s) (FICS) by adopting STEP-NC (AP-238) format. In the first step, a parametrized CAD model with FICS is created or imported in UG-NX6.0 CAD package. The second step recognizes the features and calculates a Closeness Index (CI) by comparing them with the B-Splines / Bezier surfaces. The third step utilizes the CI and extracts the necessary data to formulate the blending functions for identified features. In the fourth step Z-level 5 axis tool paths are generated by adopting flat and ball end mill cutters. Finally, in the fifth step, tool paths are integrated with STEP-NC format and validated. All these steps are discussed and explained through a validated industrial component.