DATA MINING IN ORGANIC GEOCHEMISTRY: CASE STUDY IN POTIGUAR BASIN: Mineração de dados na Geoquímica Orgânica: estudo de caso na Bacia Potiguar

The amount of data from geochemical analysis using samples collected in oil wells grows simultaneously to the investment in the exploration and production sector. On the other hand, the treatment and interpretation of these results are still very dependent on experts and demand time. With the generation of extensive databases, data mining presents itself as a good alternative to explore them through statistical methods and computational algorithms, providing technological differential and agility to the system. In an experimental way, with data from 200 oils from the Potiguar Basin, these tools were implemented, with the consequent suggestion of a workflow that would, in the end, return a reasonable accuracy in predicting their genetic classification. Using multidimensional scaling (MDS) and clustering (dendrogram and k-means types) from 60 initial attributes, the optimal set was reduced to 26. Applying Machine Learning, 92.50% of median accuracy were obtained in the Decision Tree algorithm, 95.00% in Random Forest and 87.50% in Artificial Neural Network. Comparing to an analysis previously presented at the pertinent literature, the benefits in terms of efficiency can be realized with the adoption of the methodology herein proposed.   Keywords: Organic geochemistry; Data Mining; Multivariate Statistics; Workflow.A quantidade de dados provenientes de análises geoquímicas de amostras coletadas em poços de petróleo cresce simultaneamente ao investimento no setor de exploração e produção. Por outro lado, o tratamento e a interpretação desses resultados ainda é muito dependente de especialistas, e demanda tempo. Com a geração de extensas bases de dados, a mineração de dados se apresenta como uma boa alternativa para explorá-los por meio de métodos estatísticos e computacionais, proporcionando diferencial tecnológico e agilidade ao sistema. De forma experimental, com dados de 200 óleos da Bacia Potiguar, essas ferramentas foram implementadas, com a consequente sugestão de um fluxo de trabalho que, ao final, pôde retornar uma precisão razoável na previsão da classificação genética das amostras. Usando escalonamento multidimensional (MDS) e agrupamentos (dos tipos dendrograma e k-means) de 60 atributos iniciais, o conjunto ideal foi reduzido para 26. Aplicando aprendizado de máquinas, 92,50% de acurácia mediana foram obtidos no algoritmo de Árvore de Decisão, 95,00% na Floresta Aleatória e 87,50% em Rede Neural Artificial. Comparando a uma análise previamente apresentada na literatura pertinente, os benefícios em termos de eficiência podem ser percebidos com a adoção da metodologia aqui proposta.   Palavras-chave: Geoquímica Orgânica; Mineração de dados; Estatística multivariada; Fluxo de Trabalho

The Tree Biodiversity Network (BIOTREE-NET): prospects for biodiversity research and conservation in the Neotropics

Biodiversity research and conservation efforts in the tropics are hindered by the lack of knowledge of the assemblages found there, with many species undescribed or poorly known. Our initiative, the Tree Biodiversity Network (BIOTREE-NET), aims to address this problem by assembling georeferenced data from a wide range of sources, making these data easily accessible and easily queried, and promoting data sharing. The database (GIVD ID NA-00-002) currently comprises ca. 50,000 tree records of ca. 5,000 species (230 in the IUCN Red List) from \u3e2,000 forest plots in 11 countries. The focus is on trees because of their pivotal role in tropical forest ecosystems (which contain most of the world\u27s biodiversity) in terms of ecosystem function, carbon storage and effects on other species. BIOTREE-NET currently focuses on southern Mexico and Central America, but we aim to expand coverage to other parts of tropical America. The database is relational, comprising 12 linked data tables. We summarise its structure and contents. Key tables contain data on forest plots (including size, location and date(s) sampled), individual trees (including diameter, when available, and both recorded and standardised species name), species (including biological traits of each species) and the researchers who collected the data. Many types of queries are facilitated and species distribution modelling is enabled. Examining the data in BIOTREE-NET to date, we found an uneven distribution of data in space and across biomes, reflecting the general state of knowledge of the tropics. More than 90% of the data were collected since 1990 and plot size varies widely, but with most less than one hectare in size. A wide range of minimum sizes is used to define a \u27tree\u27. The database helps to identify gaps that need filling by further data collection and collation. The data can be publicly accessed through a web application at http://portal.biotreenet.com. Researchers are invited and encouraged to contribute data to BIOTREE-NET

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

La Red Internacional de Inventarios Forestales (BIOTREE-NET) en Mesoamérica: avances, retos y perspectivas futuras

Conservation efforts in Neotropical regions are often hindered by lack of data, since for many species there is a vacuum of information, and many species have not even been described yet. The International Network of Forest Inventory Plots (BIOTREE-NET) gathers and facilitates access to tree data from forest inventory plots in Mesoamerica, while encouraging data exchange between researchers, managers and conservationists. The information is organised and standardised into a single database that includes spatially explicit data. This article describes the scope and objectives of the network, its progress, and the challenges and future perspectives. The database includes above 50000 tree records of over 5000 species from more than 2000 plots distributed from southern Mexico through to Panama. Information is heterogeneous, both in nature and shape, as well as in the geographical coverage of inventory plots. The database has a relational structure, with 12 inter-connected tables that include information about plots, species names, dbh, and functional attributes of trees. A new system that corrects typographical errors and achieves taxonomic and nomenclatural standardization was developed using The Plant List (http://theplantlist.org/) as reference. Species distribution models have been computed for around 1700 species using different methods, and they will be publicly accessible through the web site in the future (http://portal.biotreenet.com). Although BIOTREE-NET has contributed to the development of improved species distribution models, its main potential lies, in our opinion, in studies at the community level. Finally, we emphasise the need to expand the network and encourage researchers willing to share data and to join the network and contribute to the generation of further knowledge about forest biodiversity in Neotropical regions