Rhizobia Isolated from Coal Mining Areas in the Nodulation and Growth of Leguminous Trees

ABSTRACT An alternative for recovery of areas degraded by coal mining is revegetation with rapidly growing leguminous trees, which often do not establish in low fertility soils. The objective of this study was to evaluate the efficiency of native rhizobia isolated from coal mining areas in the nodulation and growth of leguminous trees. We isolated 19 strains of rhizobia from a degraded soil near Criciúma, SC, Brazil, and evaluated the nodulation and growth-promoting capacity of the inoculated isolates for bracatinga (Mimosa scabrella), maricá (M. bimucronata) and angico-vermelho (Parapiptadenia rigida). Isolates UFSC-B2, B6, B8, B9, B11 and B16 were able to nodulate bracatinga, providing average increases of 165 % in shoot dry matter, with a significant contribution to N accumulation. Isolates UFSC-B5, B12, and M8 favored nodulation and growth of maricá, especially isolate UFSC-B12, which promoted increases of 370 % in N accumulation compared to treatment with N fertilizer. All strains were inefficient in promoting growth and N uptake by angico-vermelho. In conclusion, isolation and use of selected rhizobia for bracatinga and maricá plant inoculation can contribute to the growth and accumulation of N, with prospects for use in programs for revegetation of degraded soils in coal mining areas.

The role of actions in auditory object discrimination.

Action representations can interact with object recognition processes. For example, so-called mirror neurons respond both when performing an action and when seeing or hearing such actions. Investigations of auditory object processing have largely focused on categorical discrimination, which begins within the initial 100 ms post-stimulus onset and subsequently engages distinct cortical networks. Whether action representations themselves contribute to auditory object recognition and the precise kinds of actions recruiting the auditory-visual mirror neuron system remain poorly understood. We applied electrical neuroimaging analyses to auditory evoked potentials (AEPs) in response to sounds of man-made objects that were further subdivided between sounds conveying a socio-functional context and typically cuing a responsive action by the listener (e.g. a ringing telephone) and those that are not linked to such a context and do not typically elicit responsive actions (e.g. notes on a piano). This distinction was validated psychophysically by a separate cohort of listeners. Beginning approximately 300 ms, responses to such context-related sounds significantly differed from context-free sounds both in the strength and topography of the electric field. This latency is >200 ms subsequent to general categorical discrimination. Additionally, such topographic differences indicate that sounds of different action sub-types engage distinct configurations of intracranial generators. Statistical analysis of source estimations identified differential activity within premotor and inferior (pre)frontal regions (Brodmann's areas (BA) 6, BA8, and BA45/46/47) in response to sounds of actions typically cuing a responsive action. We discuss our results in terms of a spatio-temporal model of auditory object processing and the interplay between semantic and action representations.

A process for mining science & technology documents databases, illustrated for the case of "knowledge discovery and data mining"

This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

Inteligência obtida pela aplicação de data mining em base de teses francesas sobre o Brasil

O assunto Brasil foi analisado na base de teses francesas DocThèses, compreendendo os anos de 1969 a 1999. Utilizou-se a técnica de Data Mining como ferramenta para obter inteligência e conhecimento. O software utilizado para a limpeza da base DocThèses foi o Infotrans, e, para a preparação dos dados, empregou-se o Dataview. Os resultados da análise foram ilustrados com a aplicação dos pressupostos da Lei de Zipf, classificando-se as informações em trivial, interessante e ruído, conforme a distribuição de freqüência. Conclui-se que a técnica do Data Mining associada a softwares especialistas é uma poderosa aliada no emprego de inteligência no processo decisório em todos os níveis, inclusive o nível macro, pois oferece subsídios para a consolidação, investimento e desenvolvimento de ações e políticas.

Application of text-mining for updating protein post-translational modification annotation in UniProtKB.

BACKGROUND: The annotation of protein post-translational modifications (PTMs) is an important task of UniProtKB curators and, with continuing improvements in experimental methodology, an ever greater number of articles are being published on this topic. To help curators cope with this growing body of information we have developed a system which extracts information from the scientific literature for the most frequently annotated PTMs in UniProtKB. RESULTS: The procedure uses a pattern-matching and rule-based approach to extract sentences with information on the type and site of modification. A ranked list of protein candidates for the modification is also provided. For PTM extraction, precision varies from 57% to 94%, and recall from 75% to 95%, according to the type of modification. The procedure was used to track new publications on PTMs and to recover potential supporting evidence for phosphorylation sites annotated based on the results of large scale proteomics experiments. CONCLUSIONS: The information retrieval and extraction method we have developed in this study forms the basis of a simple tool for the manual curation of protein post-translational modifications in UniProtKB/Swiss-Prot. Our work demonstrates that even simple text-mining tools can be effectively adapted for database curation tasks, providing that a thorough understanding of the working process and requirements are first obtained. This system can be accessed at http://eagl.unige.ch/PTM/.

Iron mining in Goa (India) : an interdisciplinary study

En aquest article es presenten breument els diferents capítols d’un treball interdisciplinari per tal d’entendre el context de prohibició de la mineria de ferro a Goa a finals del 2012 i proporcionar la informació necessària per tal d’orientar i gestionar la presa de decisions sobre l’activitat minera en un futur. Els sis primers capítols consisteixen en l’estudi del medi abiòtic, medi biòtic, fluxos de materials, aspectes socials, aspectes econòmics i finalment aspectes polítics. En canvi, en els dos últims capítols s'avaluen i es gestionen els impactes ambientals de la mineria mitjançant, per una banda, una anàlisi DPSIR i, d'altra banda, es proposen tres escenaris per integrar les diferents variables i fomentar la participació en la presa de decisions. S’ha dut a terme una extensa recerca mitjançant la recopilació de dades, entrevistes i visites a les zones d’estudi d’interès per tal d’entendre el conflicte de la mineria a Goa.

Destination image of Girona: an online text-mining approach

The main objective of this Master Thesis is to discover more about Girona’s image as a tourism destination from different agents’ perspective and to study its differences on promotion or opinions. In order to meet this objective, three components of Girona’s destination image will be studied: attribute-based component, the holistic component, and the affective component. It is true that a lot of research has been done about tourism destination image, but it is less when we are talking about the destination of Girona. Some studies have already focused on Girona as a tourist destination, but they used a different type of sample and different methodological steps. This study is new among destination studies in the sense that it is based only on textual online data and it follows a methodology based on text-miming. Text-mining is a kind of methodology that allows people extract relevant information from texts. Also, after this information is extracted by this methodology, some statistical multivariate analyses are done with the aim of discovering more about Girona’s tourism image

Development of Object-Oriented Design and Specifications for Iowa DOT and Urban Standards: Phase I, TR-487, 2004

Currently, individuals including designers, contractors, and owners learn about the project requirements by studying a combination of paper and electronic copies of the construction documents including the drawings, specifications (standard and supplemental), road and bridge standard drawings, design criteria, contracts, addenda, and change orders. This can be a tedious process since one needs to go back and forth between the various documents (paper or electronic) to obtain information about the entire project. Object-oriented computer-aided design (OO-CAD) is an innovative technology that can bring a change to this process by graphical portrayal of information. OO-CAD allows users to point and click on portions of an object-oriented drawing that are then linked to relevant databases of information (e.g., specifications, procurement status, and shop drawings). The vision of this study is to turn paper-based design standards and construction specifications into an object-oriented design and specification (OODAS) system or a visual electronic reference library (ERL). Individuals can use the system through a handheld wireless book-size laptop that includes all of the necessary software for operating in a 3D environment. All parties involved in transportation projects can access all of the standards and requirements simultaneously using a 3D graphical interface. By using this system, users will have all of the design elements and all of the specifications readily available without concerns of omissions. A prototype object-oriented model was created and demonstrated to potential users representing counties, cities, and the state. Findings suggest that a system like this could improve productivity to find information by as much as 75% and provide a greater sense of confidence that all relevant information had been identified. It was also apparent that this system would be used by more people in construction than in design. There was also concern related to the cost to develop and maintain the complete system. The future direction should focus on a project-based system that can help the contractors and DOT inspectors find information (e.g., road standards, specifications, instructional memorandums) more rapidly as it pertains to a specific project.

Mining the human phenome using allelic scores that index biological intermediates.

It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.

Evaluación del estándar SQL:1999 respecto a las características orientadas al objeto que soporta y su implementación a los SGBD object-relational

Memoria de TFC en el que se analiza el estándar SQL:1999 y se compara con PostgreeSQL y Oracle.

Culture in infancy : an account of a way the object "sculpts" early development.

The
 aim
 of
 this
 paper
 is
 to
 bring
 into
 consideration
 a
 way
 of
 studying
 culture
 in
 infancy.
 An
 emphasis 
is 
put 
on
 the
 role 
that 
the 
material 
object 
plays 
in 
early 
interactive
 processes. 
Accounted
 as
 a
 cultural
 artefact,
 the
 object
 is
 seen
 as
 a
 fundamental
 element
 within
 triadic
 mother‐object‐ infant
 interactions
 and
 is
 believed
 to
 be
 a
 driving
 force
 both
 for
 communicative
 and
 cognitive
 development.
 In
 order
 to
 reconsider
 the
 importance
 of
 the
 object
 in
 child
 development
 and
 to
 present
 an 
approach
 of 
studying
object
 construction,
accounts 
in 
literature 
on 
early 
communication
 development
 and
 the
 importance
 of
 the
 object
 are
 reviewed
 and
 discussed
 under
 the
 light
 of
 the
 cultural 
specificity 
of 
the 
material 
object.


Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

Relationships between users, resources and services in learning object repositories

In this paper we describe a proposal for defining the relationships between resources, users and services in a digital repository. Nowadays, virtual learning environments are widely used but digital repositories are not fully integrated yet into the learning process. Our final goal is to provide final users with recommendation systems and reputation schemes that help them to build a true learning community around the institutional repository, taking into account their educational context (i.e. the courses they are enrolled into) and their activity (i.e. system usage by their classmates and teachers). In order to do so, we extend the basic resource concept in a traditional digital repository by adding all the educational context and other elements from end-users' profiles, thus bridging users, resources and services, and shifting from a library-centered paradigm to a learning-centered one.