Dulcis cantus en la Oda II, 12 de Horacio

Este artículo busca indagar en los aspectos metaliterarios de la Oda II, 12 una clave de lectura de la propuesta poética horaciana. Observamos que el autor utiliza un artificio literario de raigambre helenística, ampliamente desarrollado en la literatura del período augusteo y romanizado, según D'Anna (1979), a partir de Virgilio en la Egloga VI: la recusatio-excusatio. Este recurso funciona en Horacio para distanciarse no sólo del genus grande sino también del género elegíaco y para proponer su propio genus tenue, cuyos rasgos característicos se concentran en la expresión dulcis cantus

Dulcis cantus en la Oda II, 12 de Horacio

Este artículo busca indagar en los aspectos metaliterarios de la Oda II, 12 una clave de lectura de la propuesta poética horaciana. Observamos que el autor utiliza un artificio literario de raigambre helenística, ampliamente desarrollado en la literatura del período augusteo y romanizado, según D'Anna (1979), a partir de Virgilio en la Egloga VI: la recusatio-excusatio. Este recurso funciona en Horacio para distanciarse no sólo del genus grande sino también del género elegíaco y para proponer su propio genus tenue, cuyos rasgos característicos se concentran en la expresión dulcis cantus

Dulcis cantus en la Oda II, 12 de Horacio

Este artículo busca indagar en los aspectos metaliterarios de la Oda II, 12 una clave de lectura de la propuesta poética horaciana. Observamos que el autor utiliza un artificio literario de raigambre helenística, ampliamente desarrollado en la literatura del período augusteo y romanizado, según D'Anna (1979), a partir de Virgilio en la Egloga VI: la recusatio-excusatio. Este recurso funciona en Horacio para distanciarse no sólo del genus grande sino también del género elegíaco y para proponer su propio genus tenue, cuyos rasgos característicos se concentran en la expresión dulcis cantus

BayGO: Bayesian analysis of ontology term enrichment in microarray data

Abstract Background The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem. Results BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses. Conclusion The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

Modelling the effects of nitrogen deposition and carbon dioxide enrichment on forest carbon balance

Atmospheric CO2 concentration ([CO2]) has increased over the last 250 years, mainly due to human activities. Of total anthropogenic emissions, almost 31% has been sequestered by the terrestrial biosphere. A considerable contribution to this sink comes from temperate and boreal forest ecosystems of the northern hemisphere, which contain a large amount of carbon (C) stored as biomass and soil organic matter. Several potential drivers for this forest C sequestration have been proposed, including increasing atmospheric [CO2], temperature, nitrogen (N) deposition and changes in management practices. However, it is not known which of these drivers are most important. The overall aim of this thesis project was to develop a simple ecosystem model which explicitly incorporates our best understanding of the mechanisms by which these drivers affect forest C storage, and to use this model to investigate the sensitivity of the forest ecosystem to these drivers. I firstly developed a version of the Generic Decomposition and Yield (G’DAY) model to explicitly investigate the mechanisms leading to forest C sequestration following N deposition. Specifically, I modified the G’DAY model to include advances in understanding of C allocation, canopy N uptake, and leaf trait relationships. I also incorporated a simple forest management practice subroutine. Secondly, I investigated the effect of CO2 fertilization on forest productivity with relation to the soil N availability feedback. I modified the model to allow it to simulate short-term responses of deciduous forests to environmental drivers, and applied it to data from a large-scale forest Free-Air CO2 Enrichment (FACE) experiment. Finally, I used the model to investigate the combined effects of recent observed changes in atmospheric [CO2], N deposition, and climate on a European forest stand. The model developed in my thesis project was an effective tool for analysis of effects of environmental drivers on forest ecosystem C storage. Key results from model simulations include: (i) N availability has a major role in forest ecosystem C sequestration; (ii) atmospheric N deposition is an important driver of N availability on short and long time-scales; (iii) rising temperature increases C storage by enhancing soil N availability and (iv) increasing [CO2] significantly affects forest growth and C storage only when N availability is not limiting.

Generic skills in design teams : literature review

Recent developments in networked three dimensional (3D) virtual worlds, and the proliferation of high bandwidth communications technology, have the potential to dramatically improve collaboration in the construction industry. This research project focuses on the early stages of a construction project in which the models for the project are developed and revised. The project investigates three aspects of collaboration in virtual environments: 1. The processes that enable effective collaboration using high bandwidth information communication technology (ICT); 2. The models that allow for multiple disciplines to share their views in a synchronous virtual environment; 3. The generic skills used by individuals and teams when engaging with high bandwidth information communication technology. The third aspect of the project, listed above, led by the University of Newcastle, explores the domain of People and the extent to which they contribute to the effectiveness of virtual teams. This report relates, primarily, to this aspect.

Generic skills in design teams

Recent developments in networked three dimensional (3D) virtual worlds and the proliferation of high bandwidth communications technology have the potential to dramatically improve collaboration in the construction industry. This research project focuses on the early stages of a design/construction project in which models for a project are developed and revised. We have investigated three aspects of collaboration in virtual environments: 1. The processes that enable effective collaboration using high bandwidth information communication technology (ICT); 2. The models that allow for multiple disciplines to share their views in a synchronous virtual environment; 3. The generic skills used by individuals and teams when engaging with high bandwidth information communication technology.

Best Practice Guide : Generic Overview

The construction industry is a key national economic component. It tends to be at the forefront of cyclic changes in the Australian economy. It has a significant impact, both directly and indirectly, on the efficiency and productivity of other industries. Moreover it affects everyone to a greater or lesser extent; through its products whether they are manifested in the physical infrastructure that supports the operation of the economy or through the built environment that directly impacts on the quality of life experienced by individuals. In financial terms the industry makes one of the largest contributions to the Australian economy, accounting for 4.7 per cent of GDP 1 which was worth over $30B in 20012. The construction industry is comprised of a myriad of small firms, across several important sectors including, o Residential building, o Commercial building, o Building services, o Engineering, o Infrastructure o Facilities Management o Property Development Each sector is typified by firms that have distinctive characteristics such as the number of employees, size and value of contracts, number of jobs, and so forth. It tends to be the case that firms operating in commercial building are larger than those involved in residential construction. The largest contractors are found in engineering and infrastructure, as well as in the commercial building sub-sectors. However all sectors are characterised by their reliance upon sub-contractors to carry out on-site operations. Professionals from the various design consultant groups operate across all of these sectors. This description masks one of the most significant underlying causes of inefficiency in the construction industry, namely its fragmentation. The Construction Industry chapter of the 2004 Australian Year Book3, published by the Australian Bureau of Statistics unmasks the industry’s fragmented structure, typified by the large number of operating businesses within it, the vast majority of which are small companies employing less than 5 people. It identifies over 190,000 firms, of which over 90 percent employ less than 5 people. At the other end of the spectrum, firms employing 20 or more people account for fractionally more than one percent of businesses in the industry.

Information enrichment for quality recommender systems

The explosive growth of the World-Wide-Web and the emergence of ecommerce are the major two factors that have led to the development of recommender systems (Resnick and Varian, 1997). The main task of recommender systems is to learn from users and recommend items (e.g. information, products or books) that match the users’ personal preferences. Recommender systems have been an active research area for more than a decade. Many different techniques and systems with distinct strengths have been developed to generate better quality recommendations. One of the main factors that affect recommenders’ recommendation quality is the amount of information resources that are available to the recommenders. The main feature of the recommender systems is their ability to make personalised recommendations for different individuals. However, for many ecommerce sites, it is difficult for them to obtain sufficient knowledge about their users. Hence, the recommendations they provided to their users are often poor and not personalised. This information insufficiency problem is commonly referred to as the cold-start problem. Most existing research on recommender systems focus on developing techniques to better utilise the available information resources to achieve better recommendation quality. However, while the amount of available data and information remains insufficient, these techniques can only provide limited improvements to the overall recommendation quality. In this thesis, a novel and intuitive approach towards improving recommendation quality and alleviating the cold-start problem is attempted. This approach is enriching the information resources. It can be easily observed that when there is sufficient information and knowledge base to support recommendation making, even the simplest recommender systems can outperform the sophisticated ones with limited information resources. Two possible strategies are suggested in this thesis to achieve the proposed information enrichment for recommenders: • The first strategy suggests that information resources can be enriched by considering other information or data facets. Specifically, a taxonomy-based recommender, Hybrid Taxonomy Recommender (HTR), is presented in this thesis. HTR exploits the relationship between users’ taxonomic preferences and item preferences from the combination of the widely available product taxonomic information and the existing user rating data, and it then utilises this taxonomic preference to item preference relation to generate high quality recommendations. • The second strategy suggests that information resources can be enriched simply by obtaining information resources from other parties. In this thesis, a distributed recommender framework, Ecommerce-oriented Distributed Recommender System (EDRS), is proposed. The proposed EDRS allows multiple recommenders from different parties (i.e. organisations or ecommerce sites) to share recommendations and information resources with each other in order to improve their recommendation quality. Based on the results obtained from the experiments conducted in this thesis, the proposed systems and techniques have achieved great improvement in both making quality recommendations and alleviating the cold-start problem.