Sigmae 2024-02-21T22:17:33+00:00 Dra. Roberta Bessa Veloso Silva Open Journal Systems <p><strong>Sigmae</strong> journal, created in June 2012, is an electronic, free-of-charge, semiannual scientific journal, which aims to publish scientific articles, reviews, opinions and critical analyzes in the pure areas and applications of Mathematics or Statistics to any area of human knowledge.</p> <p>&nbsp;</p> Letter from the Coordinator 2024-01-27T13:38:24+00:00 Mariana Ragassi Urbano <p>Letter from the Coordinator</p> 2024-01-27T12:03:37+00:00 Copyright (c) 2024 Sigmae Description of weed germination curves at different temperatures using nonlinear models 2024-01-24T01:34:51+00:00 Edilene Azarias Rafaela de Carvalho Salvador Edilson Marcelino Silva Joel Augusto Muniz Luiz Elpídio de Melo Machado <p>The spread of weeds can occur in various ways, both through seeds that can detach from plants already present in the area and be carried by machinery, wind, animals, and humans. The use of statistical models can help in a better understanding of the cumulative seed germination process and aid in the management system. The objective of this study was to use the non-linear Logistic and Gompertz models, evaluating which one is more suitable to describe the cumulative germination curve of three weed species, as well as exploring the first to fourth-order derivatives to analyze the critical points of the curves. The following conditions were used: photoperiod (8 hours of light/16 hours of darkness) with temperature (alternating or constant), and the percentage germination of seeds was evaluated at 2, 4, 6, 8, 10, 12, and 14 days after sowing. The model parameters were estimated using the method of least squares with the iterative Gauss-Newton method. The quality of fit was assessed using the coefficient of determination, residual standard deviation, and Akaike information criterion, through R software. The Gompertz model was found to be the most suitable for describing the data. Under both germination conditions, the species A. viridis showed the lowest and highest values of $\beta$ and $k$, respectively, followed by A. spinosus and A. deflexus. Regarding critical points, A. viridis showed the earliest germination, but A. spinosus had the highest germination percentage.</p> 2023-08-15T10:53:14+00:00 Copyright (c) 2023 Sigmae Prediction of fresh and dry matter of the aerial part of the plant teosinte as a function of morphological traits 2023-12-31T23:46:53+00:00 Marcelo Konrad Alberto Cargnelutti Filho Murilo Vieira Loro Mikael Brum dos Reis Vithória Morena Ortiz João Augusto Andretta Bruno Raul Schuller <p><em>The objective of this work was to verify whether the fresh and dry matter of the aerial part of the teosinte plant can be estimated as a function of morphological traits. An experiment was conducted in the agricultural year 2021/2022, in nine sowing dates.</em> <em>The following morphological traits were measured: stem length of the main stem (CC, cm); length of the main stem tassel (CP, cm); number of leaves on the main stem (NF); and number of tillers of the plant (NPF) and the productive ones: fresh mass of the aerial part of the plant (MFPA, g) and dry mass of the aerial part of the plant (MSPA, g). The parameters of the multiple linear regression model and the coefficient of determination were estimated considering the variables MFPA and MSPA as dependent and the other (CC, CP, NF, NPF) as independent. The parameters of the regression tree algorithm for predicting MFPA and MSPA were estimated as a function of the other variables (CC, CP, NF, NPF). The fresh and dry mass of the aerial part of the teosinte plant can be estimated as a function of morphological characters. The MFPA can be estimated by the following regression model: MFPA= -740.42 + 3.38(CC) + 9.70(CP) + 41.05(NF) + 85.70(NPF). While the MSPA can be estimated by the following regression model: MSPA= -84.33 + 0.85(CC) + 0.27(CP) + 3.67(NF) + 19.46(NPF). Plants with NPF greater than 8 and CC greater than 154 cm show the highest production of MFPA and MSPA.</em></p> 2023-08-16T13:21:58+00:00 Copyright (c) 2023 Sigmae Phyllochron estimate for the teosinte crop 2023-12-31T23:46:54+00:00 João Carlos Junior Alberto Cargnelutti Filho Murilo Vieira Loro João Augusto Andretta Mikael Brum dos Reis Vithória Morena Ortiz Bruno Raul Schuller <p><em>The objective of this study was to estimate the phyllochron for teosinte crops across different sowing dates. An experiment was conducted on 12 sowing dates (10/08/2021 to &nbsp;01/01/2022. The sowings were carried out in a 5-meter-long row, spaced at 0.80 meters between rows and 0.20 meters between plants in the row. For each sowing date, five plants were randomly marked, and the number of expanded leaves (NF) was counted weekly until male flowering. Throughout the experimental period, daily mean air temperatures in °C were recorded. Degree days (ºC day) were calculated considering the base temperature of 10°C. The accumulated thermal sum (ºC day) from emergence was obtained by summing up the degree day values. For each sowing date, a linear regression was fitted using the equation y = a + bx, where y is the mean number of leaves of the five plants, and x is the accumulated thermal sum from emergence. The phyllochron, in °C day leaf<sup>-1</sup>, was determined by the inverse of the angular coefficient of the linear regression between NF and accumulated thermal sum (phyllochron = 1/b). The phyllochron for teosinte cultivation varied from 47.17°C day leaf<sup>-1</sup> (sowing on 01/01/2022) to 88.99°C day leaf<sup>-1</sup> (sowing on 12/04/2021), with an average across the 12 sowing dates of 70.14°C day for the emergence of a new leaf.</em></p> 2023-12-29T23:59:16+00:00 Copyright (c) 2023 Sigmae The First year of the SARS-CoV-2 pandemic in Maringá-PR 2024-01-27T13:42:17+00:00 Jefika Bezerra Fernando Henrique Martins Fernandes Rodolfo de Souza Nascimento Neylan Leal Dias Jefferson Bezerra <p><em>This study investigates the dynamics of the Covid-19 pandemic in Maringá, Brazil, during its first year and explores the utility of mathematical models for decision-making. Originating in Wuhan, China, Covid-19 rapidly evolved into a global pandemic, reaching Brazil in February 2020. Daily cumulative case data from April 2020 to April 2021 is analyzed, revealing temporal heterogeneity characterized by distinct waves of Covid-19 cases. Mathematical models, particularly exponential models, are employed to predict pandemic trends, and their accuracy is assessed. The results emphasize the effectiveness of interventions such as curfews and mask mandates in shaping transmission dynamics. Analysis of infection speed and acceleration demonstrates the impact of holidays and interventions on the spread of the virus. A parameter, Pi, is introduced to evaluate model fitness, indicating good agreement with real-world data for most of the study period. This research underscores the crucial role of mathematical modeling in pandemic management and provides valuable insights for decision-makers and stakeholders in mitigating the impact of outbreaks like Covid-19. Understanding the temporal dynamics of pandemics is essential for implementing effective interventions and safeguarding public health. Overall, this study contributes to our knowledge of pandemic control strategies and their application in future outbreaks.</em></p> 2023-12-31T14:18:57+00:00 Copyright (c) 2023 Sigmae Correlation analysis in time series of fruit prices produced in the São Francisco Valley 2024-01-09T21:35:45+00:00 Bruno de Freitas Assunção José Edvaldo de Oliveira Nunes Ikaro Daniel de Carvalho Barreto Borko Stosic Tatijana Stosic <p><em>Agribusiness is a significant economic activity in Brazil, representing 26.6% of the GDP in 2020.</em>&nbsp;Fruit<em> farming is a prominent sector, contributing to both the domestic and international markets and generating millions of direct jobs. The total production of fresh fruits in 2020 exceeded 44 million tons, positioning Brazil as the third-largest fruit producer in the world. Among the key fruits, mango and grapes stand out, ranking first and third in exports. This study analyzes the prices of two varieties of mango (Palmer and Tommy Atkins) and two of grapes (Italia and Benitaka) produced in the São Francisco Valley, a region of relevance for these productions and exports. The weekly average price data were obtained from the Center for Advanced Studies in Applied Economics (CEPEA/USP). Using the obtained price series, we calculated logarithmic returns and volatility. We applied the Detrended Fluctuation Analysis (DFA) and Detrended Cross-Correlation Analysis (DCCA) methods, which are useful for identifying the presence of autocorrelation and correlations between two time series simultaneously. The cross-correlation coefficient (ρDCCA) was used to infer the level of cross-correlation. The results indicated higher persistence in the volatility series and two regimes with antipersistence for larger scales in the return series. Cross-correlations suggest that price fluctuations of the leading export variety (Tommy Atkins) have a greater impact on prices in the domestic market (Palmer variety). The cross-correlation coefficient pointed to a stronger correlation between the return series.</em></p> 2023-12-31T16:02:36+00:00 Copyright (c) 2023 Sigmae Analysis of tips received in restaurants using a GAMLSS approach 2023-12-31T23:46:56+00:00 Elias Sabe Viviane Silva Luiz Nakamura Andréa Konrath Thiago Ramires <p>The main aim of this paper is to analyse the amount of tips obtained by a waiter in a restaurant, in dollars, while taking into account other collected variables within the establishment. In total, 244 observations were analysed, and six extra covariates were obtained in addition to the received tips (target variable), one numerical covariate (total bill in dollars) and five factors: payer gender (two levels: male; female), smoking status (two levels: yes; no), day of the week (four levels: Thursday; Friday; Saturday; Sunday), meal type (two levels: lunch; dinner), and number of people at the table (three levels: 1 or 2; 3; 4 or more). The generalised additive models for location, scale, and shape (GAMLSS) were considered due to its high flexibility. Given the asymmetric nature of the tip variable, three distributions were considered to explain the response: gamma, inverse Gaussian, and Box-Cox Cole and Green (BCCG). A stepwise-based procedure was utilised in the covariate selection process for each of the distribution parameters, and the best models for each distribution were compared using the Akaike information criterion (AIC). The model based on the BCCG distribution returned the lowest AIC and based on a residual analysis, it was found to be suitable for explaining the dataset under study.</p> 2023-12-31T17:44:07+00:00 Copyright (c) 2023 Sigmae Non-parametric analysis in the comparison of bioinsecticides to combat pests in guava trees 2023-12-31T23:46:56+00:00 Marina Rodrigues Maestre Inessa Steffany Torres de Oliveira Isaias de Oliveira Héber Ferreira dos Reis Elisângela de Souza Loureiro Manoel Araécio Uchoa Mariana Palachini de Oliveira Marcos Gino Fernandes <p>Consuming fruits treated with chemical insecticides can cause damage to your health. Biological insect control provides effective results in pest control. This work aims to compare the bioinsecticides <em>Metarhizium anisopliae</em> (Metsch.) - "Ma" and <em>Beauveria bassiana</em> (Bals.) - "Bb" on triozid nymphs present in the aerial part of guava trees, in the State of Mato Grosso do Sul. A randomized experiment was carried out in 4 blocks, with 7 treatments: a control - "T" and one, two and three applications of each bioinsecticide - "Ma1, Ma2, Ma3" and "Bb1, Bb2, Bb3", where numbers 1, 2 and 3 correspond to the number of applications, respectively. Five evaluations were carried out after the first application of treatments: after 21, 28, 35, 42 and 49 days. The normality and homoscedasticity of the residuals were not met. As a non-parametric alternative to the Analysis of Variance (ANOVA) test, the Friedman test was used for each evaluation separately to compare the homogeneity of the treatments and joining the 5 evaluations. When there was a significant difference between treatments, the Nemenyi test was used to compare pairs of treatments for data from a block design. With 10% significance, in the first evaluation there was a difference between T and Bb2; in the second one, between T and Ma3; combining the five evaluations, between T and Ma3. These results indicate that the application of the bioinsecticide is efficient when compared to the treatment using only the control.</p> <p>Keywords: <em>Metarhizium anisopliae</em>; <em>Beauveria bassiana</em>; Triozid nymphs; Friedman; Nemenyi.</p> 2023-12-31T23:13:54+00:00 Copyright (c) 2023 Sigmae Assessment of citrus canker severity in sweet orange genotypes by mixed models 2024-01-24T01:19:13+00:00 Haward Antunny da Silva Américo Lucimary Afonso dos Santos Vandely Janeiro <p>The citrus canker disease affects leaves and fruits of orange trees and causes great economic losses, therefore, the use of statistical methodologies in the analysis of citrus datasets is essential. In a lot of studies about the disease behavior, several measurements may be carried out in the same experimental unit, characterizing them as repeated measures, making it necessary to use statistical methods that take this fact into account. In this sense, linear mixed effects models have become an important analysis tool. The objective, in this work, was to study and apply the theory of linear mixed models to a dataset, coming from an experiment implemented in the Northwest region of the Paraná State, whose interest was to evaluate the severity of citrus canker in sweet orange leaves for fourteen different genotypes. Using available packages in the R statistical environment, it was observed that the mixed linear model provided a good fit of the model to the data. Even, it was concluded that some of the experimental varieties are more susceptible to the development of citrus canker than others.</p> 2024-01-01T17:10:57+00:00 Copyright (c) 2024 Sigmae Parametric survival models applied to the length of hospital stay until discharge of patients with classic and hemorrhagic dengue in the Southeast region of Brazil 2024-01-02T21:00:13+00:00 Daiane de Oliveira Gonçalves Luiz Otávio de Oliveira Pala Natalia da Silva Martins Fonseca Marcelo Angelo Cirillo <p>The analysis of disease behavior, such as dengue, plays a crucial role in formulating policies and efficient resource management, as well as cost assessment. In this study, we investigated the hospitalization periods required for the complete recovery of patients with classic dengue (ICD-A90) and hemorrhagic dengue (ICD-A91). The dataset was collected from the Department of Informatics of the Unified Health System (DATASUS) platform, specifically from the SIASUS database, corresponding to Hospital Admission Authorizations. We selected causes A90 and A91, both taken from the International Classification of Diseases list - ICD-10. Parametric models including Exponential, Weibull, and Lognormal were considered, utilizing the following explanatory variables: i) patient's age; ii) patient's gender (female and male); iii) Brazilian state where the hospitalization occurred (Espírito Santo, Minas Gerais, Rio de Janeiro, and São Paulo). The results indicated a better fit for the Lognormal response model, suggesting that younger patients tend to have shorter hospitalization periods compared to older individuals. This situation becomes important in the planning of future policies and resource allocation, given the effect of the aging population observed in the analyzed region.</p> 2024-01-02T21:00:13+00:00 Copyright (c) 2024 Sigmae Battle of "sertanejos" on Instagram 2024-01-02T23:54:25+00:00 Fernanda Lara Valadares Eric Batista Ferreira Carlos Pereira da Silva <p><em>Stories</em> are an Instagram resource for publishing images, videos, texts, <em>feed</em> publications, polls, and others. With the growing tendency to have battles on \textit{stories}, an open question is: who are the most beloved country singers in Brazil? 16 country artists were considered and were included in the list of the top 50 most played songs on Spotify Brazil. A random switch was drawn with 2^k$competitors, with k=4. About 100 people voted in each battle. The absolute and percentage frequencies were computed, fueling a parametric Bootstrap interval inference process, through the Beta distribution. 95% confidence intervals were constructed for the parameters <em>a</em> and <em>b</em>, and their intersections were verified. Singer Marília Mendonça won the championship. However, it was statistically equal to Henrique and Juliano, who came in second place. In third place were Jorge and Mateus and Zé Neto and Cristiano. In total there were 15 battles (2^k-1), but in only 5 of them there was a significant difference between the competitors: Marília Mendonça (2 wins), Jorge and Matheus (2 wins) and Israel and Rodolfo. The proposed methodology allows us to infer the difference between competitors, and thus, which ones won by pure chance.</p> 2024-01-02T23:53:52+00:00 Copyright (c) 2024 Sigmae Application of the Gamma Fragility Model in the analysis of smoking cessation in Brazil in 2019 2024-01-11T22:56:29+00:00 Cleane Sousa Santos Cleide Mayra Menezes Lima Valmaria Rocha Da Silva Ferraz Jackelya Araujo Da Silva <p>It is globally recognized that tobacco consumption is a risk factor for various diseases, making its reduction a fundamental concern for public health. In Brazil, although there is a<br>wealth of literature on smoking and cessation, these studies often limit themselves to experimental research. This study aims to analyze data from the 2019 National Health Survey, with the<br>goal of presenting Survival Analysis as an alternative approach for investigating the behavior of<br>smokers until they quit the habit. The considered variables include gender, income, marital status, and health conditions such as Stroke, hypertension, lung disease, physical exercise practice,<br>and alcohol consumption. The Cox-Gompertz parametric model was applied to analyze factors<br><span style="vertical-align: inherit;"><span style="vertical-align: inherit;">influenciando a duração do tabagismo, assumindo tempos de consumo de tabaco independentes e riscos proporcionais. </span><span style="vertical-align: inherit;">Além disso, o modelo univariado de fragilidade Gama-Gompertz foi utilizado para abordar </span></span><br><span style="vertical-align: inherit;"><span style="vertical-align: inherit;">fatores não observados que afetam a heterogeneidade dos dados. </span><span style="vertical-align: inherit;">As análises revelaram maior probabilidade de </span></span><br><span style="vertical-align: inherit;"><span style="vertical-align: inherit;">cessação do tabagismo entre mulheres e indivíduos que praticam exercício físico. </span><span style="vertical-align: inherit;">O </span></span><br><span style="vertical-align: inherit;"><span style="vertical-align: inherit;">modelo de fragilidade indicou a presença de fatores não observados influenciando o tempo de tabagismo, pois 0,17 </span></span><br><span style="vertical-align: inherit;"><span style="vertical-align: inherit;">da variabilidade dos dados não foi explicada pelas variáveis ​​consideradas.</span></span></p> 2024-01-03T01:39:44+00:00 Copyright (c) 2024 Sigmae Identification of risk factors associated with the performance of Canchim bulls, in confinement, using the theory of survival analysis 2024-01-04T00:03:06+00:00 Marina Oliveira Cunha Cleide Mayra Menezes Lima Waldomiro Barioni Júnior Vera Lucia Damasceno Tomazella Cintia Righetti Marcondes Jackelya Araujo da Silva Yuri Antonio Iriarte <p>The study of the performance of beef cattle in confinement has aroused a lot of interest and is growing in Brazil due to these animals being in a controlled environment, facilitating the measurement of performance parameters and feed efficiency with daily collections, which results in more accurate data. Associated with this, this practice also provides animals with greater weight gain in a shorter period of time, making it a more profitable option for slaughterhouses and producers. Therefore, the objective of this work was to analyze the time it takes for Canchim bulls to achieve a daily weight gain of 1.2 kg during a period of confinement, as well as the possible factors that may affect this time. For this, a survival analysis approach using non-parametric techniques and the parametric Cox model was considered. The parametric Cox-Gompertz model considering the covariate birth weight (PI) presented the best fit to the data, that is, within the set of covariates adopted for analysis, this variable had an important influence on the time for the animal to reach the desired weight during the confinement period; a low birth weight contributed to better performance.</p> 2024-01-04T00:03:06+00:00 Copyright (c) 2024 Sigmae Evaluation of the Papadakis technique applied to methods for estimating the size of experimental plots in soybean crops 2024-01-04T14:36:12+00:00 Joaquim Francisco Mazunga Renato Ribeiro de Lima Augusto Ramalho de Morais <p><em>The experimental plot size must be adequate to reduce experimental error and increase precision, hence there is a need to have more efficient experiments. And, to determine the sizes of experimental plots, many methods are found in the literature that present adequate results, but some methods have presented unsatisfactory results, with excessively small or large sizes. To overcome this problem, an alternative is to use the Papadakis technique. Therefore, the objective of this work is to evaluate the use of the Papadakis method for estimating the size of experimental plots for application in soybean crop. To estimate the size of plots, the modified maximum curvature method, the segmented linear model method with plateau and the maximum curvature coefficient of variation method were used considering the original data and the data adjusted by the Papadakis method. It was found that de use of the Papadakis method provides a good fit in the estimation of experimental plot sizes using estimates from the modified maximum curvature methods and maximum curvature coefficient of variation method.</em></p> 2024-01-04T14:36:12+00:00 Copyright (c) 2024 Sigmae Characterization of marked point processes by the marked correlation function 2024-01-05T18:46:55+00:00 Wélson Antônio de Oliveira Wigor Deivid de Melo Santos José Márcio de Mello João Domingos Scalon <p>A spatial point process is understood as a set of points (events) irregularly distributed in space, generated by a stochastic probabilistic mechanism. Associating an attribute (mark) with the coordinate determines a marked point process. In the analysis of marked point processes, the interest lies in characterizing the pattern of interaction between the stochastic processes that generated the points and the marks. Analyses start with the characterization of first-order effects for a complete visualization of occurrence intensities. Assuming stationarity, a second-order analysis can be performed to characterize the spatial dependence present in the phenomenon. The data consist of georeferenced locations of occurrence of tree individuals in a native forest fragment and their respective diameters at breast height (DBH). This work aims to characterize the marked point processes by continuous variables, given by the DBH of native trees, through the estimation of the marked correlation function. All analyses were performed using the R software, developed by the R Core Team (2023). From the results, it was possible to observe the potential of the methods used to characterize the patterns and dynamics of the forest under study.</p> 2024-01-05T01:48:49+00:00 Copyright (c) 2024 Sigmae BATS, Dynamic Regression, Harmonic and TBATS models in modeling electricity demand in Southeast Brazil (2018 – 2019) 2024-01-05T21:44:27+00:00 Tiago Chandiona Ernesto Franque Dúlcidia Carlos Ernesto Guezimane Eduardo Yoshio Nakano José Augusto Fiorucci <div class="page" role="region" data-page-number="1" aria-label="Página 1" data-loaded="true" data-listening-for-double-click="true"> <div class="textLayer"><span dir="ltr" role="presentation">The growing demand for electricity has stimulated studies and actions not only </span><span dir="ltr" role="presentation">to increase the generation capacity of power plants, but also the rational use of this impor</span><span dir="ltr" role="presentation">tant energy resource. This has led to an increase in the number of publications related to </span><span dir="ltr" role="presentation">electricity demand, generating a much larger number of scientific papers and qualitative </span><span dir="ltr" role="presentation">and/or quantitative research, which makes filtering and analysis very laborious.</span> <span dir="ltr" role="presentation">In this </span>sense, the analysis and modeling of electricity demand based on the database of past years</div> </div> <div class="page" role="region" data-page-number="2" aria-label="Página 2" data-loaded="true" data-listening-for-double-click="true"> <div class="textLayer"><span dir="ltr" role="presentation">is a fundamental action at this time to predict the future consumption of this important </span><span dir="ltr" role="presentation">resource.</span> <span dir="ltr" role="presentation">In view of the above, the aim of this article is to forecast electricity demand </span><span dir="ltr" role="presentation">in the coming years based on a database published by the National Electricity System </span><span dir="ltr" role="presentation">Operator of Brazil. The data used for this study refers to energy consumption in Megas </span><span dir="ltr" role="presentation">Whatts (MW) from 2018 to 2019 in the Southeast/Central-West states of Brazil.&nbsp;</span></div> </div> 2024-01-05T21:44:27+00:00 Copyright (c) 2024 Sigmae COVID-19 in Arapongas city – State of Paraná – Brazil 2024-01-27T13:51:14+00:00 Moacir Paludetto Junior André Silva Olak Aline Midori Susuki Fernando Marques De Marcos Priscila Andressa Catenace da Costa Fernanda Golas Trombini Rodrigo Rossetto Pescim Carlos Alberto de Oliveira Mariana Ragassi Urbano <p><em>The COVID-19 pandemic, caused by the SARS-CoV-2 virus, had strong impacts that go beyond the health aspect. This research was carried out with COVID-19 data from Arapongas - PR, Brazil. Between March 2020 and June 2023, 41305 cases and 644 deaths by COVID-19 were recorded. In the first half of 2021, the lethality rate for the period was 2.91%, and in the first half of 2023, the rate was 0.31%. The reduction in the lethality rate coincided with the increase in vaccination rates, since, by June 2023, 93.17% of the population had received at least one dose of the vaccine and 84.73% the second dose or single dose. If the lethality rate had remained at the level recorded until the first half of 2021, the city would have recorded 426 more deaths from COVID-19, reaching 1070 deaths, an increase of 66.15%. Despite hesitancy fueled by misinformation and social media, the vaccination campaign (COVID-19) was highly effective. Of the 644 deaths related to COVID-19, 73.9% were unvaccinated. No deaths were recorded among individuals under 60 years of age who received the fourth dose, 2nd booster or bivalent vaccine, and for individuals aged 60 or over, five deaths were recorded among those who received the fourth dose or 2nd booster, and no deaths for those who received the bivalent vaccine. The conclusions affirm the potential of vaccines to save lives and the need for ongoing public health initiatives to prevent and treat diseases, carry out vaccination campaigns and combat fake news.</em></p> 2024-01-06T15:46:13+00:00 Copyright (c) 2024 Sigmae Care in the evaluation of simulation models 2024-01-06T20:59:51+00:00 Alfredo José Barreto Luiz Fernando Antônio Macena da Silva <p>The use of simulation models is increasingly frequent in research. The greater capacity, both in memory and processing, as well as the great availability, accessibility and amount of data collected and stored, induces and sometimes makes the use of this tool mandatory. On the other hand, when calibrated, the simulation models allow the realization, in seconds and at almost zero cost, of countless estimates of future behavior, in the most different scenarios, which, otherwise, would require a lot of time and resources to be obtained. Crop growth models and climate models are among the most widespread and used in agricultural research. Some metrics have been frequently used by users of these models to assess their efficiency. However, the best techniques are not always employed. In this work, the simulation results of air and soil temperature data were analyzed by two different models: ETA-HADGEM and STICS, respectively. The metrics usually indicated: EF (modelling efficiency) and RMSE (root mean square error), were compared with results of regression analysis and sign test for bias. The introduction of bias correction was also applied and interpreted. It is concluded that the metrics, if used in isolation and without in-depth analysis of the characteristics of the simulated variables, may result in a misinterpretation of the efficiency of the models.</p> 2024-01-06T20:59:50+00:00 Copyright (c) 2024 Sigmae Sample size for evaluation productive traits of teosinte 2024-02-21T12:18:02+00:00 João Augusto Andretta Alberto Cargnelutti Filho Murilo Vieira Loro Vithória Morena Ortiz Mikael Brum dos Reis Bruno Raul Schuller <p><em>Teosinte (Zea mays ssp. mexicana) is a plant of the Poaceae family and cultivated for the purpose of forage production, pasture and grain. When designing experiments, it is common to ask about the sample size to use to estimate the mean for a given trait. Likewise, the objective of this work was to determine the sample size (number of plants) necessary to evaluate the productive traits of teosinte, in sowing data. An experiment was conducted with 12 sowing dates (10/08/2021, 10/15/2021, 10/23/2021, 10/30/2021, 11/13/2021, 11/20/2021, 11/27/2021, 12/04/2021, 12/11/2021, 12/18/2021, 12/25/2021 and 01/01/2022)</em><em>, in an experimental area located at </em><em>29º42'S, 53º49'W and 95m altitude. In the main stem of five plants, chosen at random, for each sowing date, the productive traits were evaluated: fresh mass of main stem leaf (FML), fresh mass of stem main stem (FMS), fresh mass of the main stem tassel (FMT) and fresh mass of main stem (FMMS=FML+FMS+FMT). For each trait the sample size (number of plants) was calculated assuming an estimation error (semi-amplitude of the confidence interval) equal to 10% of the mean estimate, with a confidence level (1- α) of 95%. The sample size for estimating the mean varied between eight plants for FMS (sowing on 11/13/2021) and 573 plants for FMT (sowing on 10/30/2021). The average of the 12 sowings data or sample size were 177, 113, 252 and 109 plants to estimate the average of the traits FML, FMS, FMT and FMMS, respectively.</em></p> 2024-01-07T19:20:36+00:00 Copyright (c) 2024 Sigmae Academic productivity and gender at Unesp 2024-01-07T23:41:36+00:00 Carlos Alberto Oliveira de Matos Gabriel Alexandre Pio <p>A spatial point process is understood as a set of points (events) irregularly distributed in space, generated by a stochastic probabilistic mechanism. Associating an attribute (mark) with the coordinate determines a marked point process. In the analysis of marked point processes, the interest lies in characterizing the pattern of interaction between the stochastic processes that generated the points and the marks. Analyses start with the characterization of first-order effects for a complete visualization of occurrence intensities. Assuming stationarity, a second-order analysis can be performed to characterize the spatial dependence present in the phenomenon. The data consist of georeferenced locations of occurrence of tree individuals in a native forest fragment and their respective diameters at breast height (DBH). This work aims to characterize the marked point processes by continuous variables, given by the DBH of native trees, through the estimation of the marked correlation function. All analyses were performed using the R software, developed by the R Core Team (2023). From the results, it was possible to observe the potential of the methods used to characterize the patterns and dynamics of the forest under study.</p> 2024-01-07T21:26:19+00:00 Copyright (c) 2024 Sigmae Spatial Analysis of dengue cases in the state of Paraíba, Brazil 2024-02-21T22:17:33+00:00 Samara Rilda Sousa Bezerra Ricardo Sandes Ehlers Mateus Santos Peixoto Maria Izabel de Andrade Araújo Tiago Almeida de Oliveira Diogo Francisco Rossoni <p>This research presents an analysis of the dissemination of dengue, transmitted by Aedes aegypti, commonly known as the dengue mosquito. The study highlights the global increase in cases over the years, with a significant rise in Brazil, specifically in Paraíba. The research aims to analyze the distribution of reported dengue cases in the years 2015 and 2022 in the State of Paraíba using spatial statistical methods, considering socioeconomic and environmental factors. Moran indices were used to test spatial dependence, and maps such as Box Map, Lisa Map, and Moran Map were employed to visualize spatial associations. A Spatial Autoregressive (SAR) regression model was applied to assess the influence of independent variables on the Spatial Incidence Ratio (SIR). The results suggest spatial autocorrelation in the SIR and highlight the significance of the variables (Municipal Human Development Index and Per Capita Income) in the SAR 4 model</p> 2024-02-21T01:20:24+00:00 Copyright (c) 2024 Sigmae Regression tree for prediction the yield of fresh matter of teosinte aerial part in function of meteorological variables 2023-12-31T23:46:57+00:00 Mikael Brum dos Reis Alberto Cargnelutti Filho Murilo Vieira Loro João Augusto Andretta Vithória Morena Ortiz Bruno Raul Schuller <p><em>The objective of this work was to verify if it is possible to predict the yield of fresh matter of teosinte aerial part in function of meteorological variables. An experiment was conducted with nine sowing dates (10/08/2021 to 01/01/2022). Sowings were carried out in a 5 m long row, spaced 0.80 m between rows and 0.20 m between plants in the row. In each row, five plants were randomly selected, totaling 45 plants. On 03/28/2022, in the first five sowing dates, and on 04/22/2022, in the last four sowing dates, the fresh matter of the aerial part of the plant (FMAP, in g) was determined. The cumulative global solar radiation and the thermal sum of the subperiods from sowing to male flowering (vegetative stage) and male flowering to harvest (reproductive stage) were calculated. The regression tree analysis algorithm was applied to forecast the FMAP as a function of meteorological variables. The regression tree was performed with data from all plants and sowing dates (n=45). The cumulative global solar radiation from male flowering to harvest was the main dividing point. In the second hierarchical node, the division criteria were thermal sum from sowing to male flowering and cumulative global solar radiation from sowing to male flowering. The highest productive performance (FMAP = 1162 g plant<sup>-1</sup>) was observed in plants with cumulative global solar radiation in the reproductive stage lower than 494 MJ m<sup>-2</sup> and global accumulated solar radiation in the vegetative stage lower than 3257 MJ m<sup>-2</sup> (33% of observations).</em></p> 2023-12-30T00:36:16+00:00 Copyright (c) 2023 Sigmae Text Mining Methods for Unifying Strategic Planning Indicators in the Municipalities of Mato Grosso 2023-12-31T23:46:57+00:00 Lia Hanna Martins Morita Rita de Cássia Cruz Anderson Castro Soares de Oliveira <p>Indicators are essential tools for resource management and monitoring public policies in municipalities. In the state of Mato Grosso, the Strategic Planning Management Program (GPE), developed in collaboration with the Tribunal de Contas, is an initiative that seeks to enhance public policies by adopting standardized indicators. Within this framework, text mining emerges as a valuable technique for analyzing and processing vast amounts of data in documents and reports. Regular expressions are sequences of characters in a text that follow a specific pattern, such as words accented with acute, circumflex, tilde, or grave accents. These patterns can be detected through algorithms, then replaced or removed. For example, if the objective is to remove the accent from all words in a sentence, algorithms can be employed likewise. Another assignment of interest is standardizing text to lowercase or title case using regular expressions. Such modifications streamline daily tasks and aid in the framing of managing reports, as standardized texts are more straightforward to analyze, derive insights from, and base business decisions on. In this study, text mining techniques and regular expressions were employed to standardize the nomenclature of indicators from municipalities participating in the GPE, thereby enhancing their management and oversight. Text mining allowed for a systematic analysis of the data, pinpointing improvement, correcting inconsistencies, and thereby bolstering the efficacy of public policies.</p> 2023-12-31T03:42:36+00:00 Copyright (c) 2023 Sigmae Few-shot learning in the era of Big Data 2024-01-02T00:55:33+00:00 João Carlos Pereira Alves Eric Batista Ferreira Iago Augusto de Carvalho <p>The advancement of Big Data has brought a large volume of data that has enabled the use of machine learning techniques for decision-making in different fields. However, the effectiveness of these models depends on the availability of large amounts of data, raising the challenge of dealing with learning from few samples. Learning from few samples is important in many applications when large volumes are not available, such as opinion surveys, due to the challenges of data collection, primarily due to lack of engagement and participation in questionnaires. This approach can facilitate or minimize the use of opinion surveys. However, there are challenges that need to be overcome to achieve accurate performance in few-shot learning tasks, such as the selection of relevant samples, the choice of appropriate training methods, among others. In light of this, we will discuss the perspectives and challenges of learning from few samples in the era of Big Data. A review of Few-shot learning techniques and their applications will be conducted as an alternative to deal with few samples. Reviewing these techniques and their application on limited datasets can provide valuable insights for improving machine learning models in different application domains.</p> 2024-01-02T00:47:14+00:00 Copyright (c) 2024 Sigmae Mathematical modeling of population dynamics in the city of Maringa, PR 2024-02-21T21:13:10+00:00 Fernando Henrique Martins Fernandes Jefika Bezerra Bezerra Rodolfo Souza Nascimento Neylan Dias Leal <p><em>The aim of this study is to model the population growth of Maringá, Paraná, using classic Population Dynamics models and compare them with real data obtained from IBGE and datasus between 1980 and 2012. To achieve this, it is necessary to obtain the parameters of the models, which will be obtained through Linear Regression. After obtaining the parameters and comparing the results with real data, it was observed that the Verhulst model performed the best, with a small margin of error when compared to the actual population. Consequently, the Malthusian model proved impractical for population projection. Therefore, mathematical modeling has proven to be effective in simulating real-world problems, especially in population dynamics where understanding population behavior is crucial for future public policy creation and disaster prevention.</em></p> 2023-12-31T01:43:13+00:00 Copyright (c) 2023 Sigmae The impact of remote teaching on the dropout and retention of students in the Statistis Course at UFSCar 2023-12-31T23:46:58+00:00 Estela Maris Pereira Bereta Pedro Ferreira Filho <p>Dropout in higher education has been studied by many researchers and, in particular, by higher education institutions in order to identify the reasons that lead students to abandon a course or university. In the specific case of Bachelor's degrees in Statistics in Brazil, studies indicate that around 25% of freshmen have completed the course in recent years, indicating a dropout rate of approximately 75% of students. In the case of the Statistics course at UFSCar, historically between 40% and 50% of students completed the course. During the Remote Teaching period, from the 2020 academic year to the 2021 academic year, UFSCar relaxed its minimum performance rule for students to continue in the courses. In this work, it was observed that dropout rates were lower during this period, as well as the retention of students in initial subjects, especially those related to the area of mathematics. These two facts should have contributed to a higher course completion rate, but this did not happen. Two hypotheses, in this case, are being investigated: the difficulty of readapting students to face-to-face teaching and the expansion of home office internships, which led several students to extend the duration of the course to make it compatible with remote work.</p> 2023-12-31T15:26:38+00:00 Copyright (c) 2023 Sigmae