Quantiles for Counts

This paper studies the estimation of conditional quantiles of counts. Given the discreteness of the data, some smoothness has to be artificially imposed on the problem. The methods currently available to estimate quantiles of count data either assume that the counts result from the discretization of a continuous process, or are based on a smoothed objective function. However, these methods have several drawbacks. We show that it is possible to smooth the data in a way that allows inference to be performed using standard quantile regression techniques. The performance and implementation of the estimator are illustrated by simulations and an application.Asymmetric maximum likelihood, Jittering, Maximum score estimator, Quantile regression, Smoothing.

Quantiles for Fractions and Other Mixed Data

This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset.

Smart and sustainable cities in the Mediterranean region: The contribution of short supply chains of food

The cities around the world in general, and in the Mediterranean area in particular, are facing tremendous challenges at the environmental, social, economic, and institutional levels, due to the urbanization trend, environmental climatic changes and challenges due to the ongoing COVID-19 pandemic. Therefore, cities need to be sustainable and smart in the future. An economically important and innovative sector in urban areas is food security. Nowadays, most of the literature explores the concept of smart cities from the point of view of information and communications technology, indeed, the connection with the sustainability aspects of the food supply chain and the ways to operationalize that, remains unsolved. This paper tries to overcome this gap in the literature. The main aim is to analyze the contribution of the short supply chain of food in terms of sustainability in smart cities, regarding current urban trends in cities in general and in Mediterranean areas in particular. The methodology was based on a literature review and includes quantitative and qualitative analysis. The results confirm the existence of positive impacts in the short supply chains of food in urban areas in terms of sustainability. Despite the existence of a considerable number of papers about smart cities and ICT-related topics, the benefits from society of short supply chains of food, and the linkage among the topics and subjects, remain unreferred to or with a limited knowledge exchange. The conclusions of this paper will be helpful for public decision makers to implement policies in order to promote the sustainability of Mediterranean cities.info:eu-repo/semantics/publishedVersio

Quantiles for Fractions and Other Mixed Data

This paper studies the estimation of quantile regression for fractional data, focusing on the case where there are mass-points at zero or/and one. More generally, we propose a simple strategy for the estimation of the conditional quantiles of data from mixed distributions, which combines standard results on the estimation of censored and Box-Cox quantile regressions. The implementation of the proposed method is illustrated using a well-known dataset

Symbolic Computation of Variational Symmetries in Optimal Control

We use a computer algebra system to compute, in an efficient way, optimal control variational symmetries up to a gauge term. The symmetries are then used to obtain families of Noether's first integrals, possibly in the presence of nonconservative external forces. As an application, we obtain eight independent first integrals for the sub-Riemannian nilpotent problem (2,3,5,8).Comment: Presented at the 4th Junior European Meeting on "Control and Optimization", Bialystok Technical University, Bialystok, Poland, 11-14 September 2005. Accepted (24-Feb-2006) to Control & Cybernetic

Influência de diferentes temperaturas no crescimento micelial de Rosellinia sp.

Editores técnicos: Marcílio José Thomazini, Elenice Fritzsons, Patrícia Raquel Silva, Guilherme Schnell e Schuhli, Denise Jeton Cardoso, Luziane Franciscon. EVINCI. Resumos

Temperature in Machining of Aluminum Alloys

The objective this work is to study the effect of the mechanical property of the workpiece (tensile strength) and cutting conditions (cutting speed, feed rate, depth of cut and lubri-cooling system) over the cutting temperature in turning of aluminum alloys. A 2k factorial planning was used to determine the machining test conditions. ANOVA and Regression Analysis of the results were performed. The main contribution of this work lies on its efficiency of describing the behavior of the cutting temperature as a function of the input variables. The results found in the present work have considered the interactions of the input variables, describing the cutting temperature in a complete way, not seen previously in the literature

A Multistate Model for Analyzing Transitions Between Body Mass Index Categories During Childhood: The Generation XXI Birth Cohort Study

Prevalences of overweight and obesity in young children have risen dramatically in the last several decades in most developed countries. Childhood overweight and obesity are known to have immediate and long-term health consequences and are now recognized as important public health concerns. We used a Markov 4-state model with states defined by 4 body mass index (BMI; weight (kg)/height (m)(2)) categories (underweight (2 SDs of BMI z score)) to study the rates of transition to higher or lower BMI categories among children aged 4-10 years. We also used this model to study the relationships between explanatory variables and their transition rates. The participants consisted of 4,887 children from the Generation XXI Birth Cohort Study (Porto, Portugal; 2005-2017) who underwent anthropometric evaluation at age 4 years and in at least 1 of the subsequent follow-up waves (ages 7 and 10 years). Children who were normal weight were more likely to move to higher BMI categories than to lower categories, whereas overweight children had similar rates of transition to the 2 adjacent categories. We evaluated the associations of maternal age and education, type of delivery, sex, and birth weight with childhood overweight and obesity, but we observed statistically significant results only for sex and maternal education with regard to the progressive transitions.L.M.-M. received financial support from the Spanish Ministry of Economy and Competitiveness through project M2017-82379-R, funded by the Agencia Estatal de Investigacion and the European Regional Development Fund. A.C.S. holds an FCT Investigator contract (contract IF/01060/2015) from the Fundacao para a Ciencia e Tecnologia (FCT). The Generation XXI Birth Cohort Study was funded by Programa Operacional de Saude XXI, Quadro Comunitario de Apoio III, and the Administracao Regional de Saude Norte (a regional department of the Portuguese Ministry of Health). The current study was funded by the Fundo Europeu de Desenvolvimento Regional through the Operational Thematic Programme for Competitiveness and Internationalization (COMPETE 2020); by the FCT, Ministerio Portugues da Ciencia, Tecnologia e Ensino Superior (grant POCI-01-0145-FEDER-016837); by the project PathMOB: Risco Cardiometabolico na Infancia: Desde o Inicio da Vida ao Fim da Infancia (grant FCT PTDC/DTP-EPI/3306/2014); by the Unidade de Investigacao em Epidemiologia (EPIUnit), Instituto de Saude Publica da Universidade do Porto (grant POCI-01-0145-FEDER-006862); and by the Fundacao Calouste Gulbenkian (Lisbon, Portugal). This study also resulted from the DOCnet Project (Diabetes and Obesity at the Crossroads Between Oncological and Cardiovascular Diseases-A System Analysis Network Towards Precision Medicine) (grant NORTE-01-0145-FEDER-000003), which is supported by the Programa Operacional da Regiao Norte (NORTE 2020) under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund