Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing

Darwin's Rainbow: Evolutionary radiation and the spectrum of consciousness

Evolution is littered with paraphyletic convergences: many roads lead to functional Romes. We propose here another example - an equivalence class structure factoring the broad realm of possible realizations of the Baars Global Workspace consciousness model. The construction suggests many different physiological systems can support rapidly shifting, sometimes highly tunable, temporary assemblages of interacting unconscious cognitive modules. The discovery implies various animal taxa exhibiting behaviors we broadly recognize as conscious are, in fact, simply expressing different forms of the same underlying phenomenon. Mathematically, we find much slower, and even multiple simultaneous, versions of the basic structure can operate over very long timescales, a kind of paraconsciousness often ascribed to group phenomena. The variety of possibilities, a veritable rainbow, suggests minds today may be only a small surviving fraction of ancient evolutionary radiations - bush phylogenies of consciousness and paraconsciousness. Under this scenario, the resulting diversity was subsequently pruned by selection and chance extinction. Though few traces of the radiation may be found in the direct fossil record, exaptations and vestiges are scattered across the living mind. Humans, for instance, display an uncommonly profound synergism between individual consciousness and their embedding cultural heritages, enabling efficient Lamarkian adaptation

Parallel Natural Language Parsing: From Analysis to Speedup

Electrical Engineering, Mathematics and Computer Scienc

Novel approaches for large-scale phylogenetics and applications in the context of the amphibian tree of life

During this thesis, I addressed some problems associated with large-scale phylogenetic analyses by tackling issues related to missing data and careful handling and addition of novel data in large-scale reconstructions, presenting an application of this approach in the context of amphibian phylogenetics. I developed a method (called “Concatabominations”) building on the original Safe Taxonomic Reduction method (Wilkinson 1995) as an alternative approach to the issue of identifying rogue taxa. The safe removal of rogue taxa due to missing data can potentially reduce the terraces in tree space search and improve resolution in the final consensus tree. In a pragmatic point of view, the new method can help in targeting taxa that require further sampling during a research design. Novel sequence data for the rediscovered Ericabatrachus baleensis allowed to explore its placement in the Amphibian tree of life. I tested the inclusion of novel data using a backbone alignment from a previous work (de novo analysis) and a backbone phylogenetic tree (constrained analysis), after careful curation of gene partitions to include in an analysis. I found that the use of a constrained phylogenetic inference using a previous accepted tree seems to be a practical solution to the rapid phylogenetic placement of a taxon in cases of well-supported relationships. However, a de novo analysis might ensure an optimal alignment and avoid risks introduced when adding new data. Finally, I investigated the evolutionary relationships of the three lineages of the extant amphibians (Anura, Caudata and Gymnophiona) using an independent source of evidence: miRNAs, recently used to help resolve difficult phylogenetic problems. The analyses yielded a high number of shared miRNAs using the Xenopus tropicalis genome, contrasting with a lower number of miRNAs discovered using the Axolotl transcriptome. This suggests that not using genomic data is not ideal to validate miRNAs. Nevertheless, in spite of the limitations, I was able to find two potential novel miRNAs: one supporting the monophyly of Lissamphibia, and another supporting the Batrachia hypothesis. Overall, I hope the work developed in this thesis contributes with new insights into large-scale phylogenetics and in particular to amphibian phylogenetics

Predictive Modelling Approach to Data-Driven Computational Preventive Medicine

This thesis contributes novel predictive modelling approaches to data-driven computational preventive medicine and offers an alternative framework to statistical analysis in preventive medicine research. In the early parts of this research, this thesis presents research by proposing a synergy of machine learning methods for detecting patterns and developing inexpensive predictive models from healthcare data to classify the potential occurrence of adverse health events. In particular, the data-driven methodology is founded upon a heuristic-systematic assessment of several machine-learning methods, data preprocessing techniques, models’ training estimation and optimisation, and performance evaluation, yielding a novel computational data-driven framework, Octopus. Midway through this research, this thesis advances research in preventive medicine and data mining by proposing several new extensions in data preparation and preprocessing. It offers new recommendations for data quality assessment checks, a novel multimethod imputation (MMI) process for missing data mitigation, a novel imbalanced resampling approach, and minority pattern reconstruction (MPR) led by information theory. This thesis also extends the area of model performance evaluation with a novel classification performance ranking metric called XDistance. In particular, the experimental results show that building predictive models with the methods guided by our new framework (Octopus) yields domain experts' approval of the new reliable models’ performance. Also, performing the data quality checks and applying the MMI process led healthcare practitioners to outweigh predictive reliability over interpretability. The application of MPR and its hybrid resampling strategies led to better performances in line with experts' success criteria than the traditional imbalanced data resampling techniques. Finally, the use of the XDistance performance ranking metric was found to be more effective in ranking several classifiers' performances while offering an indication of class bias, unlike existing performance metrics The overall contributions of this thesis can be summarised as follow. First, several data mining techniques were thoroughly assessed to formulate the new Octopus framework to produce new reliable classifiers. In addition, we offer a further understanding of the impact of newly engineered features, the physical activity index (PAI) and biological effective dose (BED). Second, the newly developed methods within the new framework. Finally, the newly accepted developed predictive models help detect adverse health events, namely, visceral fat-associated diseases and advanced breast cancer radiotherapy toxicity side effects. These contributions could be used to guide future theories, experiments and healthcare interventions in preventive medicine and data mining

The use of functional traits to elucidate the causes and consequences of biological diversity.

The rapid and global rise in species extinctions has prompted much research into the causes and consequences of biodiversity loss. In the past two decades, efforts have expanded beyond characterizing diversity through numbers of species -- or species richness -- and integrated additional information on how species interact with one another and their environment via functional traits. Functional traits permit a more nuanced exploration of patterns in community structure and composition, and provide a mechanistic basis to link community diversity to ecosystem processes. In this dissertation, I apply functional traits to observational surveys and a small-scale experimental manipulation to understand and explain patterns in diversity, and to link functional diversity to ecosystem functioning. In all three cases, I show that functional traits yield substantial additional insight into ecological patterns and processes beyond what can be gained via richness alone.;In the first chapter, I use functional traits and two newly-derived phylogenies to understand the role of biotic interactions in determining how local communities of reef fishes assemble from the available pool of species. to address this question, I utilized data from the Reef Life Survey network, a global citizen science program that has conducted visual censuses of reef fish communities at nearly 2,000 sites across the globe. to rigorously disentangle the biotic and abiotic drivers of assembly, I aimed to factor out the effect of environment by grouping species based on their fine-scale habitat requirements, then tested for significant patterns in functional and phylogenetic diversity of local communities relative to the regional species pool. I found that most communities were functionally and phylogenetically clustered relative to the regional pool, meaning that species found in these communities were more functionally- and phylogenetically-similar than expected by chance. This clustering increased with increasing latitude independent of several major axes of environmental variation. I propose several non-mutually exclusive explanations for this pattern, including: (1) increased competition at higher latitudes, potentially driven by variability in resources; (2) higher mobility of fishes at high latitudes reducing trait and evolutionary composition at any given site relative to what could be observed there (i.e., high turnover), and; (3) reduced richness at high latitudes reducing the probability of capturing functionally and phylogenetically unique species. This chapter is one of the first studies to unite a macroecological perspective on assembly with functional biogeography across global gradients, particularly for vertebrates.;In the second chapter, I utilized data from a 15-year observational survey of an eelgrass Zostera marina L. bed in the York River Estuary, Chesapeake Bay, USA to test the relative strength of top-down and bottom-up control and the role of species richness and functional diversity in mediating trophic processes. I united biological data on eelgrass, microalgal epiphyte, and invertebrate grazer biomass, and predator abundances with physical data on temperature, light, turbidity, and nutrients using structural equation modeling. Across spring, summer, and fall seasons, biological variables appeared to be largely controlled by temperature and turbidity. However, there was weaker but statistically significant evidence for top-down control in the spring and summer, changing over to bottom-up control in the fall. In contrast to evidence from small-scale experiments, there was no effect of diversity on ecosystem properties such as standing stock biomass of eelgrass, grazers, and predators, which may have been a consequence of the overall low diversity and high functional redundancy present in this system. This chapter reveals a small but significant role for biology in the face of strong, long-term natural variation in abiotic parameters in a temperate eelgrass bed.;In the third and final chapter, I experimentally manipulated functional trait diversity of estuarine mesograzers and predators within multiple levels of species richness to test the relative predictive ability of functional diversity and species richness on ecosystem functioning. I found that multivariate functional diversity based on 8 traits was a better predictor and explained more variation in standing stock biomass of predator, grazer, and recruiting invertebrates than did species richness. Aggregating across all 8 traits in a multivariate index of functional diversity improved prediction accuracy relative to any individual trait. I then used structural equation modeling to show that the positive effects of community-level functional diversity were a consequence of both predator and grazer functional diversity, although predator effects were much stronger. I also modeled the contributions of each individual species to show that different functions were driven by different species with unique combinations of traits, suggestive of functional complementarity. Together, these results suggest that functional diversity is a powerful alternative to species richness in predicting the ecosystem consequences of species loss. This chapter is one of the first studies to conduct an a priori manipulation of functional traits using consumers, and the first to manipulate traits across multiple levels of a realistic food web

A complete design path for the layout of flexible macros

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