Artificial Intelligence in geospatial analysis: applications of self-organizing maps in the context of geographic information science.

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsThe size and dimensionality of available geospatial repositories increases every day, placing additional pressure on existing analysis tools, as they are expected to extract more knowledge from these databases. Most of these tools were created in a data poor environment and thus rarely address concerns of efficiency, dimensionality and automatic exploration. In addition, traditional statistical techniques present several assumptions that are not realistic in the geospatial data domain. An example of this is the statistical independence between observations required by most classical statistics methods, which conflicts with the well-known spatial dependence that exists in geospatial data. Artificial intelligence and data mining methods constitute an alternative to explore and extract knowledge from geospatial data, which is less assumption dependent. In this thesis, we study the possible adaptation of existing general-purpose data mining tools to geospatial data analysis. The characteristics of geospatial datasets seems to be similar in many ways with other aspatial datasets for which several data mining tools have been used with success in the detection of patterns and relations. It seems, however that GIS-minded analysis and objectives require more than the results provided by these general tools and adaptations to meet the geographical information scientist‟s requirements are needed. Thus, we propose several geospatial applications based on a well-known data mining method, the self-organizing map (SOM), and analyse the adaptations required in each application to fulfil those objectives and needs. Three main fields of GIScience are covered in this thesis: cartographic representation; spatial clustering and knowledge discovery; and location optimization.(...

A computational literature review of football performance analysis through probabilistic topic modeling

Principe, V. A., de Souza Vale, R. G., de Castro, J. B. P., Carvano, L. M., Henriques, R. A. P., Lobo, V. J. D. A. E. S., & de Alkmim Moreira Nunes, R. (2022). A computational literature review of football performance analysis through probabilistic topic modeling. Artificial Intelligence Review, 55(2). [Advanced online publication on 4 April 2021]. https://doi.org/10.1007/s10462-021-09998-8This research aims to illustrate the potential use of concepts, techniques, and mining process tools to improve the systematic review process. Thus, a review was performed on two online databases (Scopus and ISI Web of Science) from 2012 to 2019. A total of 9649 studies were identified, which were analyzed using probabilistic topic modeling procedures within a machine learning approach. The Latent Dirichlet Allocation method, chosen for modeling, required the following stages: 1) data cleansing, and 2) data modeling into topics for coherence and perplexity analysis. All research was conducted according to the standards of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses in a fully computerized way. The computational literature review is an integral part of a broader literature review process. The results presented met three criteria: (1) literature review for a research area, (2) analysis and classification of journals, and (3) analysis and classification of academic and individual research teams. The contribution of the article is to demonstrate how the publication network is formed in this particular field of research, and how the content of abstracts can be automatically analyzed to provide a set of research topics for quick understanding and application in future projects.authorsversionpublishe

BacHBerry: BACterial Hosts for production of Bioactive phenolics from bERRY fruits

BACterial Hosts for production of Bioactive phenolics from bERRY fruits (BacHBerry) was a 3-year project funded by the Seventh Framework Programme (FP7) of the European Union that ran between November 2013 and October 2016. The overall aim of the project was to establish a sustainable and economically-feasible strategy for the production of novel high-value phenolic compounds isolated from berry fruits using bacterial platforms. The project aimed at covering all stages of the discovery and pre-commercialization process, including berry collection, screening and characterization of their bioactive components, identification and functional characterization of the corresponding biosynthetic pathways, and construction of Gram-positive bacterial cell factories producing phenolic compounds. Further activities included optimization of polyphenol extraction methods from bacterial cultures, scale-up of production by fermentation up to pilot scale, as well as societal and economic analyses of the processes. This review article summarizes some of the key findings obtained throughout the duration of the project

Worldwide trends in hypertension prevalence and progress in treatment and control from 1990 to 2019: a pooled analysis of 1201 population-representative studies with 104 million participants

Background Hypertension can be detected at the primary health-care level and low-cost treatments can effectively control hypertension. We aimed to measure the prevalence of hypertension and progress in its detection, treatment, and control from 1990 to 2019 for 200 countries and territories. Methods We used data from 1990 to 2019 on people aged 30–79 years from population-representative studies with measurement of blood pressure and data on blood pressure treatment. We defined hypertension as having systolic blood pressure 140 mm Hg or greater, diastolic blood pressure 90 mm Hg or greater, or taking medication for hypertension. We applied a Bayesian hierarchical model to estimate the prevalence of hypertension and the proportion of people with hypertension who had a previous diagnosis (detection), who were taking medication for hypertension (treatment), and whose hypertension was controlled to below 140/90 mm Hg (control). The model allowed for trends over time to be non-linear and to vary by age. Findings The number of people aged 30–79 years with hypertension doubled from 1990 to 2019, from 331 (95% credible interval 306–359) million women and 317 (292–344) million men in 1990 to 626 (584–668) million women and 652 (604–698) million men in 2019, despite stable global age-standardised prevalence. In 2019, age-standardised hypertension prevalence was lowest in Canada and Peru for both men and women; in Taiwan, South Korea, Japan, and some countries in western Europe including Switzerland, Spain, and the UK for women; and in several low-income and middle-income countries such as Eritrea, Bangladesh, Ethiopia, and Solomon Islands for men. Hypertension prevalence surpassed 50% for women in two countries and men in nine countries, in central and eastern Europe, central Asia, Oceania, and Latin America. Globally, 59% (55–62) of women and 49% (46–52) of men with hypertension reported a previous diagnosis of hypertension in 2019, and 47% (43–51) of women and 38% (35–41) of men were treated. Control rates among people with hypertension in 2019 were 23% (20–27) for women and 18% (16–21) for men. In 2019, treatment and control rates were highest in South Korea, Canada, and Iceland (treatment >70%; control >50%), followed by the USA, Costa Rica, Germany, Portugal, and Taiwan. Treatment rates were less than 25% for women and less than 20% for men in Nepal, Indonesia, and some countries in sub-Saharan Africa and Oceania. Control rates were below 10% for women and men in these countries and for men in some countries in north Africa, central and south Asia, and eastern Europe. Treatment and control rates have improved in most countries since 1990, but we found little change in most countries in sub-Saharan Africa and Oceania. Improvements were largest in high-income countries, central Europe, and some upper-middle-income and recently high-income countries including Costa Rica, Taiwan, Kazakhstan, South Africa, Brazil, Chile, Turkey, and Iran. Interpretation Improvements in the detection, treatment, and control of hypertension have varied substantially across countries, with some middle-income countries now outperforming most high-income nations. The dual approach of reducing hypertension prevalence through primary prevention and enhancing its treatment and control is achievable not only in high-income countries but also in low-income and middle-income settings

CARTO-SOM - Cartogram creation using self-organizing maps

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Ciência e Sistemas de Informação GeográficaThe basic idea of a cartogram is to distort a map. This distortion comes from the substitution of area for some other variable (in most examples population). The objective is to scale each region according to the value it represents for the new variable, while keeping the map recognizable. The first cartograms were created to show the geographic distribution of population, in the context of human geography. Cartograms can be seen as variants of a map. The difference between a map and a cartogram is the variable that defines the size of the regions. In a map this variable is the geographic area of the regions, while in the cartogram any other georeferenced variable may be used. In this dissertation we present a general method for constructing density-equalizing projections or cartograms, using the basic SOM algorithm, providing a tool for geographic data presentation and analysis

Production of Ti-35Nb alloy by powder metallurgy for aerospace application

Titanium and its alloys provide high strength-to-weight ratios, good fatigue strength and increased corrosion resistance compared with others materials. Its acceptance in aerospace has been limited by costs considerations such as high cost of raw material, high buy-to-fly ratios and expensive machining operations. Significant cost reductions can be obtained by vacuum sintering and powder metallurgy (P/M) techniques by producing near net shapes and consequently minimizing material waste and machining time. The Ti 35Nb alloy exhibit a low modulus of elasticity. Stemming from the unique combination of high strength, low modulus of elasticity and low density, this alloy is intrinsically more resistant to shock and explosion damages than most other engineering materials. Samples were produced by mixing of initial metallic powders followed by uniaxial and cold isostatic pressing with subsequent densification by sintering between 900 and 1600 °C, in vacuum. Sintering behavior was studied by means of dilatometry. Sintered samples were characterized for phase composition, microstructure and microhardness by X-ray diffraction, scanning electron microscopy and Vickers indentation, respectively. Density was measured by Archimedes method. Copyright © 2004 Society of Automotive Engineers, Inc

Production of a low young modulus titanium alloy by powder metallurgy

Titanium alloys have several advantages over ferrous and non-ferrous metallic materials, such as high strengthto-weight ratio and excellent corrosion resistance. A blended elemental titanium powder metallurgy process has been developed to offer low cost commercial products. The process employs hydride-dehydride (HDH) powders as raw material. In this work, results of the Ti-35Nb alloy sintering are presented. This alloy due to its lower modulus of elasticity and high biocompatibility is a promising candidate for aerospace and medical use. Samples were produced by mixing of initial metallic powders followed by uniaxial and cold isostatic pressing with subsequent densification by isochronal sintering between 900 up to 1600 °C, in vacuum. Sintering behavior was studied by means of microscopy and density. Sintered samples were characterized for phase composition, microstructure and microhardness by X-ray diffraction, scanning electron microscopy and Vickers indentation, respectively. Samples sintered at high temperatures display a fine plate-like alpha structure and intergranular beta. A few remaining pores are still found and density above 90% for specimens sintered in temperatures over 1500 °C is reached

Clinical characteristics and outcomes of hospital-manifested COVID-19 among Brazilians

ABSTRACT: Objectives: To analyze the clinical characteristics and outcomes of admitted patients with the hospital- versus community-manifested COVID-19 and to evaluate the risk factors related to mortality in the first population. Methods: This retrospective cohort included consecutive adult patients with COVID-19, hospitalized between March and September 2020. The demographic data, clinical characteristics, and outcomes were extracted from medical records. Patients with hospital-manifested COVID-19 (study group) and those with community-manifested COVID-19 (control group) were matched by the propensity score model. Logistic regression models were used to verify the risk factors for mortality in the study group. Results: Among 7,710 hospitalized patients who had COVID-19, 7.2% developed symptoms while admitted for other reasons. Patients with hospital-manifested COVID-19 had a higher prevalence of cancer (19.2% vs 10.8%) and alcoholism (8.8% vs 2.8%) than patients with community-manifested COVID-19 and also had a higher rate of intensive care unit requirement (45.1% vs 35.2%), sepsis (23.8% vs 14.5%), and death (35.8% vs 22.5%) (P <0.05 for all). The factors independently associated with increased mortality in the study group were increasing age, male sex, number of comorbidities, and cancer. Conclusion: Hospital-manifested COVID-19 was associated with increased mortality. Increasing age, male sex, number of comorbidities, and cancer were independent predictors of mortality among those with hospital-manifested COVID-19 disease