Evaluation of Preferential Flow Processes in Reclamation Soil Covers

To predict the effectiveness of land reclamation, it is important to understand how water and solutes are transported within reconstructed landscapes. The objective of this study was to examine the influence of preferential flow on salt leaching in reclamation soil covers. The study site was a reconstructed landscape where saline-sodic minespoil from oil sands mining was capped with layers of glacial and peat mix soil. Preferential flow was investigated using laboratory column experiments and in situ adsorptive dye and conservative tracer experiments. Results from column experiments and dye tracer experiments indicate that preferential flow is an important and prevalent mechanism of solute transport. Column experiments, which used time-domain reflectometry to monitor the transport of a chloride tracer through an undisturbed core of peat mix soil, determined immobile water fractions (èim/è) ranging from 80-99% and diffusive mass transfer rates (á) between 0.15 - 2.0 h-1. Breakthrough curves showed the early arrival of chloride and extended tailing. Dye tracer experiments, in which Brilliant Blue dye was applied in solution to the soil surface, were carried out at 6 hillslopes plots. Approximately 24 hours after dye application, a vertical soil face was excavated to reveal stained flow patterns. Preferential flow as macropore flow, fingering, and / or funneling was observed at each plot. Results from the conservative tracer field study indicated soil solutes were flushed by a combination of vertical and lateral flow processes. A large pulse of bromide and chloride was applied across the lower slope of the 0.35-m cover. Soil sampling at approximately 1 and 2 years later determined vertical leaching, lateral translocation downslope, and upwards movement of soil solutes. Matrix flow during the spring melt, combined with matrix flow and / or preferential flow during summer and fall periods, was responsible for the vertical leaching of solutes. Subsurface flow generated in response to the spring melt or due to differences in soil hydraulic conductivity was responsible for the lateral transport of solutes. As a result of advective or diffusive processes, solutes were transported upwards into the overlying soil. These results suggested that despite the existence of preferential flow, there were other mechanisms of solute transport which served to leach and flush salts from the soil

Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics

Gene functional annotations are an essential part of knowledge discovery in the analysis of large datasets, with the Gene Ontology [Ashburner et al., 2000] as the de facto standard for such annotations. A considerable number of approaches for quantifying functional similarity between gene products based on the semantic similarity between their annotations have been developed, but little guidance exists as to which of these measures are the most appropriate for different purposes. This was addressed here by comparing the performances of a number of similarity measures and associated parameters. This comparison provided some interesting new insights as well as confirming emerging trends from the literature. There is also a pressing need for novel ways of applying these measures to facilitate the functional analysis of lists of gene products. We developed a novel algorithm, FuSiGroups, to group GO terms based on their semantic similarity and genes based on their functional similarity. This two-fold grouping results in groups of not only functionally similar genes but also an associated set of related GO terms that characterise a single functional aspect relating the genes in the group, which facilitates analysis by creating more coherent groups. Each gene can belong to multiple groups, so the groups more accurately reflect the complexity of biological reality than clusters generated using traditional approaches. FuSiGroups was tested on a number of scenarios and in each case, successfully generated biologically relevant groups, identifying the key functional aspects of the dataset. The algorithm also managed to eliminate genes that were functionally unrelated to the bulk of the dataset and distinguish between different biological pathways. Although dataset size is currently a limiting factor, with smaller datasets performing the best, FuSiGroups has been demonstrated as a promising approach for the functional analysis of gene products.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics

Gene functional annotations are an essential part of knowledge discovery in the analysis of large datasets, with the Gene Ontology [Ashburner et al., 2000] as the de facto standard for such annotations. A considerable number of approaches for quantifying functional similarity between gene products based on the semantic similarity between their annotations have been developed, but little guidance exists as to which of these measures are the most appropriate for different purposes. This was addressed here by comparing the performances of a number of similarity measures and associated parameters. This comparison provided some interesting new insights as well as confirming emerging trends from the literature. There is also a pressing need for novel ways of applying these measures to facilitate the functional analysis of lists of gene products. We developed a novel algorithm, FuSiGroups, to group GO terms based on their semantic similarity and genes based on their functional similarity. This two-fold grouping results in groups of not only functionally similar genes but also an associated set of related GO terms that characterise a single functional aspect relating the genes in the group, which facilitates analysis by creating more coherent groups. Each gene can belong to multiple groups, so the groups more accurately reflect the complexity of biological reality than clusters generated using traditional approaches. FuSiGroups was tested on a number of scenarios and in each case, successfully generated biologically relevant groups, identifying the key functional aspects of the dataset. The algorithm also managed to eliminate genes that were functionally unrelated to the bulk of the dataset and distinguish between different biological pathways. Although dataset size is currently a limiting factor, with smaller datasets performing the best, FuSiGroups has been demonstrated as a promising approach for the functional analysis of gene products

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Webulous and the Webulous Google Add-On - a web service and application for ontology building from templates

Background: Authoring bio-ontologies is a task that has traditionally been undertaken by skilled experts trained in understanding complex languages such as the Web Ontology Language (OWL), in tools designed for such experts. As requests for new terms are made, the need for expert ontologists represents a bottleneck in the development process. Furthermore, the ability to rigorously enforce ontology design patterns in large, collaboratively developed ontologies is difficult with existing ontology authoring software.Description: We present Webulous, an application suite for supporting ontology creation by design patterns. Webulous provides infrastructure to specify templates for populating ontology design patterns that get transformed into OWL assertions in a target ontology. Webulous provides programmatic access to the template server and a client application has been developed for Google Sheets that allows templates to be loaded, populated and resubmitted to the Webulous server for processing.Conclusions: The development and delivery of ontologies to the community requires software support that goes beyond the ontology editor. Building ontologies by design patterns and providing simple mechanisms for the addition of new content helps reduce the overall cost and effort required to develop an ontology. The Webulous system provides support for this process and is used as part of the development of several ontologies at the European Bioinformatics Institute

Supporting findability of COVID-19 research with large-scale text mining of scientific publications

When the COVID-19 pandemic hit in early 2020, a lot of research efforts were quickly redirected towards studies on SARS-CoV2 and COVID-19 disease, from the sequencing and assembly of viral genomes to the elaboration of robust testing methodologies and the development of treatment and vaccination strategies. At the same time, a flurry of scientific publications around SARS-CoV-2 and COVID-19 began to appear, making it increasingly difficult for researchers to stay up-to-date with latest trends and developments in this rapidly evolving field. The BioKB platform is a pipeline which, by exploiting text mining and semantic technologies, helps researchers easily access semantic content of thousands of abstracts and full text articles. The content of the articles is analysed and concepts from a range of contexts, including proteins, species, chemicals, diseases and biological processes are tagged based on existing dictionaries of controlled terms. Co-occurring concepts are classified based on their asserted relationship and the resulting subject-relation-object triples are stored in a publicly accessible human- and machine-readable knowledge base. All concepts in the BioKB dictionaries are linked to stable, persistent identifiers, either a resource accession such as an Ensembl, Uniprot or PubChem ID for genes, proteins and chemicals, or an ontology term ID for diseases, phenotypes and other ontology terms. In order to improve COVID-19 related text mining, we extended the underlying dictionaries to include many additional viral species (via NCBI Taxonomy identifiers), phenotypes from the Human Phenotype Ontology (HPO), COVID-related concepts including clinical and laboratory tests from the COVID-19 ontology, as well as additional diseases (DO) and biological processes (GO). We also added all viral proteins found in UniProt and gene entries from EntrezGene to increase the sensitivity of the text mining pipeline to viral data. To date, BioKB has indexed over 270’000 sentences from 21’935 publications relating to coronavirus infections, with publications dating from 1963 to 2021, 3’863 of which were published this year. We are currently working to further refine the text mining pipeline by training it on the extraction of increasingly complex relations such as protein-phenotype relationships. We are also regularly adding new terms to our dictionaries for areas where coverage is currently low, such as clinical and laboratory tests and procedures and novel drug treatments

A CONTRIBUIÇÃO DE POLÍTICAS PÚBLICAS MUNICIPAIS NO ATINGIMENTO DO DESENVOLVIMENTO SUSTENTÁVEL: RISCOS, MUDANÇAS CLIMÁTICAS E RESILIÊNCIA

Perante todas as problemáticas socioambientais presentes no planeta, é difícil de identificar qual ação deve ser iniciada imediatamente, pois, quando se trata de questões ambientais, do meio biótico e abiótico, até as relações socioculturais, tudo é urgência. As mudanças climáticas por exemplo, tem se tornado um assunto prioritário, pois exigem esforços conjunto entre ações de adaptação e políticas públicas para a busca da resiliência. A partir da perspectiva de que as mudanças devem começar na escala local, este trabalho se propõe a analisar se as políticas públicas do município de Novo Hamburgo, no sul do Brasil, contemplam os objetivos 11 e 13 da agenda 2030, que estão associadas as questões de riscos, mudanças climáticas e resiliência. Deste modo, buscou-se compreender de que forma este local está preparado para se tornar um lugar mais sustentáveis, tendo em vista os riscos ambientais presentes no município, com ênfase para as ameaças relacionadas à deslizamentos e inundações, que podem resultar em desastres naturais. Foram realizadas pesquisas bibliográficas e um estudo detalhado das políticas públicas do município de Novo Hamburgo, através de análise qualitativa e documental. Em suma, destaca-se a importância de políticas públicas que direcionem um planejamento adequado para que o ambiente se desenvolva economicamente para um crescimento sustentável, principalmente onde possui parte da população vulneráveis com a qualidade de vida afetada.