SOFTWARE SELECTION THROUGH DECISION ANALYSIS AND INFORMATION SYSTEMS MANAGEMENT

This paper aims to access the best alternative, from a set of five, of software for statistical analysis in a seed company in Brazil. The methodology considers the costs related to the process, R programming and its relationship with the final decision made regarding the software selection, being all these aspects framed by the tool discussed in (Howard, 1988; Howard, 2004) applied to the information technology context. The results present cost reduction in the process of statistical analysis and a change in the decision about the statistical software to be used by the enterprise. The paper consider only one specific application of analysis used by the enterprise which can be improved with the use of platforms such as Rstudio, and the packages Knitr and Shiny.Howard, 1988 Howard, 200

GEN-O-MA project: an Italian network studying clinical course and pathogenic pathways of moyamoya disease—study protocol and preliminary results

Background: GENetics of mOyaMoyA (GEN-O-MA) project is a multicenter observational study implemented in Italy aimed at creating a network of centers involved in moyamoya angiopathy (MA) care and research and at collecting a large series and bio-repository of MA patients, finally aimed at describing the disease phenotype and clinical course as well as at identifying biological or cellular markers for disease progression. The present paper resumes the most important study methodological issues and preliminary results. Methods: Nineteen centers are participating to the study. Patients with both bilateral and unilateral radiologically defined MA are included in the study. For each patient, detailed demographic and clinical as well as neuroimaging data are being collected. When available, biological samples (blood, DNA, CSF, middle cerebral artery samples) are being also collected for biological and cellular studies. Results: Ninety-eight patients (age of onset mean ± SD 35.5 ± 19.6 years; 68.4% females) have been collected so far. 65.3% of patients presented ischemic (50%) and haemorrhagic (15.3%) stroke. A higher female predominance concomitantly with a similar age of onset and clinical features to what was reported in previous studies on Western patients has been confirmed. Conclusion: An accurate and detailed clinical and neuroimaging classification represents the best strategy to provide the characterization of the disease phenotype and clinical course. The collection of a large number of biological samples will permit the identification of biological markers and genetic factors associated with the disease susceptibility in Italy

Factores de riesgo asociados a enfermedad renal crónica en la población adulta en cuatro estratos socioeconómicos del municipio de Guatemala

Describir el comportamiento epidemiológico de los factores de riesgo asociados a enfermedad renal crónica, en la población adulta de cuatro estratos socioeconómicos del Municipio de Guatemala en abril 2015. Estudio de tipo descriptivo, transversal, con muestreo no probabilístico por conveniencia, en 4 sectores cartográficos, 223 viviendas. Los datos se recolectaron por medio de una encuesta con base al cuestionario del método progresivo (STEPS) modificado. La prevalencia de factores de riesgo modificables asociados a enfermedad renal crónica en población adulta, en 4 estratos socioeconómicos del municipio de Guatemala fue de:sedentarismo(76%),sobrepeso/obesidad (56%), consumo de sal (36%), presión arterial elevada (31%) consumo de bebidas artificiales (30%), consumo de alcohol (21%), consumo de tabaco (1%). La prevalencia de factores de riesgo no modificables asociados a enfermedad renal crónica en población adulta, en 4 estratos socioeconómicos del municipio de Guatemala fue de: antecedente médico de hipertensión (35%), antecedente médico de de hipercolesterolemia (17%) y antecedente de diabetes mellitus. (11%). los factores de riesgo de mayor prevalencia asociado a desarrollar enfermedad renal crónica fueron sedentarismo, sobrepeso/obesidad y consumo de sal. El comportamiento epidemiológico de los factores de riesgo asociados para el desarrollo ERC fue ser sexo femenino, estar entre el rango de edad de 40 a 60 años, con un estado civil de casado, haber terminado diversificado como nivel de escolaridad, pertenecer a la población trabajadora, tener ingresos económicos en el hogar menores a Q3,247.20 y pertenecer al grupo étnico ladino

A cross-sectional study evaluating hospitalization rates for chronic limb-threatening ischemia during the COVID-19 outbreak in Campania, Italy

The expansion of coronavirus disease 2019 (COVID-19) prompted measures of disease containment by the Italian government with a national lockdown on March 9, 2020. The purpose of this study is to evaluate the rate of hospitalization and mode of in-hospital treatment of patients with chronic limb-threatening ischemia (CLTI) before and during lockdown in the Campania region of Italy. The study population includes all patients with CLTI hospitalized in Campania over a 10-week period: 5 weeks before and 5 weeks during lockdown (n = 453). Patients were treated medically and/or underwent urgent revascularization and/or major amputation of the lower extremities. Mean age was 69.2 +/- 10.6 years and 27.6% of the patients were women. During hospitalization, 21.9% of patients were treated medically, 78.1% underwent revascularization, and 17.4% required amputations. In the weeks during the lockdown, a reduced rate of hospitalization for CLTI was observed compared with the weeks before lockdown (25 vs 74/100,000 inhabitants/year; incidence rate ratio: 0.34, 95% CI 0.32-0.37). This effect persisted to the end of the study period. An increased amputation rate in the weeks during lockdown was observed (29.3% vs 13.4%; p < 0.001). This study reports a reduced rate of CLTI-related hospitalization and an increased in-hospital amputation rate during lockdown in Campania. Ensuring appropriate treatment for patients with CLTI should be prioritized, even during disease containment measures due to the COVID-19 pandemic or other similar conditions

EVALITA Evaluation of NLP and Speech Tools for Italian - December 17th, 2020

Welcome to EVALITA 2020! EVALITA is the evaluation campaign of Natural Language Processing and Speech Tools for Italian. EVALITA is an initiative of the Italian Association for Computational Linguistics (AILC, http://www.ai-lc.it) and it is endorsed by the Italian Association for Artificial Intelligence (AIxIA, http://www.aixia.it) and the Italian Association for Speech Sciences (AISV, http://www.aisv.it)

O paradigma estatístico: análise probabilística e multivariada aplicadas via simulação computacional no contexto da interação genótipo ambiente

Statistical analysis is based on an elementary paradigm and the relationship between probabilistic inductive inference, generation and validation of models, and the use of such information in decisions within a specific domain of knowledge. Additionally, techniques can be used to design specific experiments, such as the multi-environmental trials MET, to study the interaction between genotypes and environments. The fitting of probability distributions to data from phenomena allows the knowledge of the behavior of random variables and the later usage of such models in computational simulation. This procedure was carried out in the adjustment of models for maize grains weight, obtained via multi environmental trials. Several methods of adjustment of distribution and mixtures of normal distributions by the EM algorithm were used. The data were obtained through the use of scrapping with software R. Adjusted models were used to simulate, through computational methods implemented in language R, data with behavior known in parametric terms, generating a table that simulates the interaction between genotype and environment factors. Such simulated data were used to verify and compare models based on multivariate analysis, namely AMMI, weighted AMMI and GGE for the study of genotype environment interaction GxE. The results demonstrated the great effectiveness of the models in capturing the properties of the simulated data, contextualizing them as informational tools in the development of new products.A estatística fundamenta-se em um paradigma elementar, baseado na relação entre a inferência indutiva probabilística, geração e validação de modelos e o uso de tais informações como subsídio em decisões em um domínio específico de conhecimento. Aliado a isso, técnicas podem ser utilizadas para delinear tipos específicos de experimentos, como os ensaios multi ambientais MET para estudos de interação entre genótipos e ambientes. O ajuste de distribuição de probabilidades a dados provenientes de fenômenos permite o conhecimento do comportamento de variáveis aleatórias e posterior uso de tais modelos em simulação computacional. Tal procedimento foi realizado no ajuste de modelos para peso de grãos de genótipos de milho em ensaios multi ambientais, através de diversos métodos de ajuste de distribuição e mixturas de distribuições normais pelo algoritmo EM. Os dados foram obtidos através do uso de scrapping via software R. Por sua vez, os modelos ajustados foram utilizados para simular, através de métodos computacionais implementados em linguagem R, dados com comportamento conhecido em termos paramétricos, através de uma tabela que simula a interação entre os fatores genótipo e ambiente. Tais dados simulados foram utilizados para verificar, e comparar os modelos baseados em análise multivariada de dados, a saber AMMI, AMMI ponderado e GGE, para o estudo da interação genótipo ambiente (GxE). Os resultados demonstraram a grande efetividade dos modelos em captar as propriedades dos dados simulados, contextualizando-os como ferramentas informacionais no desenvolvimento de novos produtos

Uncertainty management through decision analysis: applications to production optimization and uncertain demands

A produção de sementes de milho é um processo que engloba variáveis de diversas naturezas. A quantidade de sementes a ser produzida é decisão fundamental para um produtor de sementes. Dessa forma, é necessário contextualizar a decisão da quantidade a se produzir dentro de todas as decisões que um produtor de sementes realiza no desenvolvimento de produtos e na produção. Assim, é possível com o uso de um modelo de custo associado ao excesso de oferta e demanda, determinar-se a quantidade de sementes à ser produzida que otimize este custo. Para tal, é necessário a obtenção de uma projeção para a demanda futura por simulação computacional. Dentro desse contexto, foi confeccionado um fluxograma para o processo de desenvolvimento de produtos e produção de sementes. Após isso, mapearam-se as decisões envolvidas com uso de diagramas de influências e determinou-se através de projeção da demanda por simulação a quantidade ótima de sementes de um cultivar a ser produzida para abastecer uma região de referência, determinada pelo modelo econômico desenvolvido no referencial. Além disso, devido à quantidade de informações simuladas foi possível a obtenção das probabilidades de diferentes faixas de lucro obtidas com o cultivar de interesse na região considerada.Corn seed production is a complex process. The quantity of seed that a firm should produce is an important parameter. It is important for a seed producer to put the decision related to quantity to be produced in the context of all decisions made for product development and for the production process. Thus, with support of an model for costs related to excess of demand or supply, a firm could set the optimal quantity of seed to be produced that minimizes this cost. This methodology requires the use of a projection of demand through simulation. In these context, was built a flowchart for the process of product development and seed production. Then decisions and related uncertainties in these processes were mapped through influence diagrams. After the map production, the decision regarding the quantity to be produced was put in context and this quantity was determined by the methodology discussed. The analysis considered a cultivar and an interest region. Information got through simulation was also used to quantify the probabilities of different potential profits reached by the cultivar in the interest region

Seleção de software utilizando análise de decisões e gerenciamento de tecnologia e sistemas de informação

Este trabalho objetivou determinar a melhor alternativa, dentre cinco alternativas, para implementação de análises estatísticas através de software em uma empresa de sementes. A metodologia utilizada considerou custos relacionados ao processo, programação em R e sua relação com a decisão acerca do software estatístico da empresa através da ferramenta de análise de decisões (Howard, 1988; Howard, 2004) aplicada no contexto da gestão de T.I. Os resultados mostram redução de custos no processo estatístico e mudança na decisão sobre software estatístico a ser utilizado pela empresa. O trabalhou contemplou apenas uma aplicação específica da empresa e a solução adotada pode ser melhorada com uso da plataforma Rstudio, além dos packages Knitr e shiny.This paper aims to access the best alternative, from a set of five, of software for statistical analysis in a seed company in Brazil. The methodology considers the costs related to the process, R programming and its relationship with the final decision made regarding the software selection, being all these aspects framed by the tool discussed in (Howard, 1988; Howard, 2004) applied to the information technology context. The results present cost reduction in the process of statistical analysis and a change in the decision about the statistical software to be used by the enterprise. The paper consider only one specific application of analysis used by the enterprise which can be improved with the use of platforms such as Rstudio, and the packages Knitr and Shiny