Abstract This research aimed the performance evaluation of a structured-bed reactor with different cycles of Intermittent Aeration (IA)(SBRRIA) in the municipal sewage treatment and the verification of the effect of IA cycles on the total... more
Abstract This research aimed the performance evaluation of a structured-bed reactor with different cycles of Intermittent Aeration (IA)(SBRRIA) in the municipal sewage treatment and the verification of the effect of IA cycles on the total nitrogen (TN) removal and organic matter (COD). Three IA cycles were evaluated: phase I (4h AE (aeration on) - 2h NA (aeration off)); II (2h AE - 1h NA) and III (2h AE - 2h NA), with Hydraulic Retention Time of 16 hours. The best nitrogen removal was obtained during the phase II, with the lowest non-aeration time: efficiency of nitrification, denitrification, TN and COD removal of 80 ± 15%, 82 ± 12%, 67±6% and 94 ± 7%, respectively. The mean cell residence time was 19, 26 and 33 d in phases I, II and III, respectively. The statistical analysis applied to the AE/NA profiles showed that the time of AE and NA in the cycles did not influence nitrogen and organic matter removal. Thus, this indicates the recirculation and the gradient formed in the support material facilitate the process of Simultaneous Nitrification and Denitrification. The lowest concentration of nitrifying and denitrifying microorganisms was obtained in effluent and sludge at the end of phase III. From the TP (Total Proteins)/TPS (Total Polysaccharides) ratio obtained (0.8±0.1, 1.3±0.1 e 1.5±0.1 in phases I, II and III), it was possible to conclude that the biofilm in phase I was more porous, with a thin layer if compared to that in phase II and III.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
The large amount of data generated during the COVID-19 pandemic requires advanced tools for the long-term prediction of risk factors associated with COVID-19 mortality with higher accuracy. Machine learning (ML) methods directly address... more
The large amount of data generated during the COVID-19 pandemic requires advanced tools for the long-term prediction of risk factors associated with COVID-19 mortality with higher accuracy. Machine learning (ML) methods directly address this topic and are essential tools to guide public health interventions. Here, we used ML to investigate the importance of demographic and clinical variables on COVID-19 mortality. We also analyzed how comorbidity networks are structured according to age groups. We conducted a retrospective study of COVID-19 mortality with hospitalized patients from Londrina, Parana, Brazil, registered in the database for severe acute respiratory infections (SIVEP-Gripe), from January 2021 to February 2022. We tested four ML models to predict the COVID-19 outcome: Logistic Regression, Support Vector Machine, Random Forest, and XGBoost. We also constructed a comorbidity network to investigate the impact of co-occurring comorbidities on COVID-19 mortality. Our study comprised 8358 hospitalized patients, of whom 2792 (33.40%) died. The XGBoost model achieved excellent performance (ROC-AUC = 0.90). Both permutation method and SHAP values highlighted the importance of age, ventilatory support status, and intensive care unit admission as key features in predicting COVID-19 outcomes. The comorbidity networks for old deceased patients are denser than those for young patients. In addition, the co-occurrence of heart disease and diabetes may be the most important combination to predict COVID-19 mortality, regardless of age and sex. This work presents a valuable combination of machine learning and comorbidity network analysis to predict COVID-19 outcomes. Reliable evidence on this topic is crucial for guiding the post-pandemic response and assisting in COVID-19 care planning and provision.
Research Interests:
Research Interests:
Research Interests:
ABSTRACT We formulate and study a four-parameter lifetime model called the beta extended half-normal distribution. This model includes as sub-models the exponential, extended half-normal and half-normal distributions. We derive expansions... more
ABSTRACT We formulate and study a four-parameter lifetime model called the beta extended half-normal distribution. This model includes as sub-models the exponential, extended half-normal and half-normal distributions. We derive expansions for the new density function which do not depend on complicated functions. We obtain explicit expressions for the moments and incomplete moments, generating function, mean deviations, Bonferroni and Lorenz curves and Rényi entropy. In addition, the model parameters are estimated by maximum likelihood. We provide the observed information matrix. The new model is modified to cope with possible long-term survivors in the data. The usefulness of the new distribution is shown by means of two real data sets.
Research Interests:
Research Interests:
Research Interests:
ABSTRACT Cooray and Ananda (2008) pioneered a lifetime model commonly used in reliability studies. Based on this distribution, we propose a new model called the odd log-logistic generalized half-normal distribution for describing fatigue... more
ABSTRACT Cooray and Ananda (2008) pioneered a lifetime model commonly used in reliability studies. Based on this distribution, we propose a new model called the odd log-logistic generalized half-normal distribution for describing fatigue lifetime data. Various of its structural properties are derived. We discuss the method of maximum likelihood to fit the model parameters. For different parameter settings and sample sizes, some simulation studies compare the performance of the new lifetime model. It can be very useful, and its superiority is illustrated by means of a real dataset.
Research Interests:
Research Interests:
Research Interests:
Research Interests: Engineering, Mathematics, Applied Mathematics, Approximation Theory, Computer Science, and 15 moreEconometrics, Information Theory, Data Analysis, Biology, Biometrics, Bayesian Analysis, Industry, Maximum Likelihood, Industrie, Logistic Distribution, Likelihood Function, Lorenz Curve, Generating Function, Beta Distribution, and Distribution Function
Research Interests:
Research Interests:
Research Interests:
Research Interests: Mathematics and Physics
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Malathion is an organophosphate insecticide used in agriculture and for controlling vector-borne diseases such as Zika. Humans can be exposed to malathion by means of ingestion of contaminated food. The juvenile and peripubertal periods... more
Malathion is an organophosphate insecticide used in agriculture and for controlling vector-borne diseases such as Zika. Humans can be exposed to malathion by means of ingestion of contaminated food. The juvenile and peripubertal periods are a large window of vulnerability to the action of toxic agents. The aim of the present study was to evaluate the effects of low doses of malathion during the development of testes in the juvenile and peripubertal periods in rats. For this purpose, 45 male Wistar rats (postnatal day (PND) 25) were assigned to 3 experimental groups and treated for 40 days. The animals were exposed daily to malathion 10 mg/kg (M10 group) or 50 mg/kg (M50 group) diluted in 0.9 % saline via gavage. The control group received only the vehicle. On the 40th experimental day, the rats were anaesthetized and euthanized. The blood was collected for determination of testosterone concentration. The testes were removed and weighed. Spermatozoa from the vas deferens were used for sperm morphological analysis. The testes were used for evaluation of sperm count and oxidative stress status to determine the inflammatory profile and analysis of tissue constitution. The results showed that both malathion doses reduced the sperm count and increased the number of abnormal sperms. Furthermore, both doses altered the spermatogenetic process, delayed spermiogenesis, reduced the Leydig and Sertoli cell number and increased the thickness of tunica albuginea. The M10 group presented increased IL-10 levels and reduced GSH levels. These parameters did not change in the M50 group. However, the M50 group showed an increase in the number of abnormal seminiferous tubules, a decrease in plasma testosterone concentration and an increase in lipid peroxidation in the testes. In conclusion, the exposure to low doses of malathion during juvenile and peripubertal development resulted in testicular toxicity and compromised the testicular morphology and function.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Background Recent studies have established that vaccination plays a significant role in reducing COVID-19-related deaths. Here, we investigated differences in COVID-19 case fatality rates (CFRs) among vaccinated and unvaccinated... more
Background Recent studies have established that vaccination plays a significant role in reducing COVID-19-related deaths. Here, we investigated differences in COVID-19 case fatality rates (CFRs) among vaccinated and unvaccinated populations, and analyzed whether the age composition of confirmed cases has a significant effect on the variations in the observed CFRs across these groups. Methods The study considered 59,853 confirmed cases and 1,687 deaths from COVID-19, reported between January 1st to October 20th, 2021, by the Health Department of Londrina, a city in Southern Brazil. We used Negative Binomial regression models to estimate CFRs according to vaccination status and age range. Results There are significant differences between the CFR for fully vaccinated and unvaccinated populations (IRR=0.596, 95% CI [0.460 - 0.772], p<0.001). Vaccinated populations experience fatality rates 40.4% lower than non-vaccinated. In addition, the age composition of confirmed cases explains more than two-thirds of the variation in the CFR between these two groups. Conclusion Our novel findings reinforce the importance of vaccination as an essential public health measure for reducing COVID-19 fatality rates in all age groups. The results also provide means for accurately assessing differences in CFRs across vaccinated and unvaccinated populations. Such assessment is essential to inform and determine appropriate containment and mitigation interventions in Brazil and elsewhere.
Research Interests:
A new weighted exponentiated-exponential distribution is proposed to model financial data. It has heavy-tailed behavior which is suitable for data with right tails. Some actuarial measures for the new model are determined, and simulations... more
A new weighted exponentiated-exponential distribution is proposed to model financial data. It has heavy-tailed behavior which is suitable for data with right tails. Some actuarial measures for the new model are determined, and simulations are reported. Its parameters are estimated using nine approaches including a Bayesian method. A new Log-WEx-Exponential regression model is defined for right censored data. The importance of the new models is proved by applications to financial data.
Research Interests:
Research Interests:
Research Interests:
We propose and study a two-parameter weighted Nadarajah and Haghighi distribution. The new distribution can be viewed as an alternative model to some of the classical two-parameter distributions such as the Weibull, gamma, exponentiated... more
We propose and study a two-parameter weighted Nadarajah and Haghighi distribution. The new distribution can be viewed as an alternative model to some of the classical two-parameter distributions such as the Weibull, gamma, exponentiated half-logistic and exponentiated exponential distributions. We explore some of its mathematical properties. The maximum likelihood estimation method is adopted to estimate the model parameters. A Monte Carlo simulation study is performed to assess the adequacy of the estimates. We compare the fits of the proposed distribution and other competitive models to three real data sets.
Research Interests:
Research Interests:
Research Interests:
Research Interests:
This research aimed the performance evaluation of a structured-bed reactor with different cycles of Intermittent Aeration (IA)(SBRRIA) in the municipal sewage treatment and the verification of the effect of IA cycles on the total nitrogen... more
This research aimed the performance evaluation of a structured-bed reactor with different cycles of Intermittent Aeration (IA)(SBRRIA) in the municipal sewage treatment and the verification of the effect of IA cycles on the total nitrogen (TN) removal and organic matter (COD). Three IA cycles were evaluated: phase I (4h AE (aeration on) - 2h NA (aeration off)); II (2h AE - 1h NA) and III (2h AE - 2h NA), with Hydraulic Retention Time of 16 hours. The best nitrogen removal was obtained during the phase II, with the lowest non-aeration time: efficiency of nitrification, denitrification, TN and COD removal of 80 ± 15%, 82 ± 12%, 67±6% and 94 ± 7%, respectively. The mean cell residence time was 19, 26 and 33 d in phases I, II and III, respectively. The statistical analysis applied to the AE/NA profiles showed that the time of AE and NA in the cycles did not influence nitrogen and organic matter removal. Thus, this indicates the recirculation and the gradient formed in the support materi...
Research Interests:
Research Interests:
Research Interests: Engineering, Mathematics, Approximation Theory, Computer Science, Econometrics, and 15 moreInformation Theory, Data Analysis, Biology, Biometrics, Bayesian Analysis, Industry, Maximum Likelihood, Industrie, Logistic Distribution, Likelihood Function, Lorenz Curve, Generating Function, Beta Distribution, Mean Deviation, and Distribution Function
... a , E-mail The Corresponding Author , Clarice GB Demétrio a , E-mail The Corresponding Author , Gauss M. Cordeiro b , E-mail The Corresponding Author , Edwin MM Ortega a , Corresponding ... Starting from a parent cumulative... more
... a , E-mail The Corresponding Author , Clarice GB Demétrio a , E-mail The Corresponding Author , Gauss M. Cordeiro b , E-mail The Corresponding Author , Edwin MM Ortega a , Corresponding ... Starting from a parent cumulative distribution function (cdf) G(x), Eugene et al. ...
Research Interests: Approximation Theory, Econometrics, Statistics, Information Theory, Data Analysis, and 15 moreDensity-functional theory, Maximum Likelihood, Density Functional Theory, Gaussian distribution, Statistical Theory, Weibull distribution, Probability Density Function, Expansion, Normal Distribution, Computational Statistics and Data Analysis, maximum likelihood estimate, Beta Distribution, Statistical distribution theory, Generalized function, and Distribution Function
Research Interests:
Research Interests:
The normal distribution is the most popular model in applications to real data. We propose a new extension of this distribution, called the Kummer beta normal distribution, which presents greater flexibility to model scenarios involving... more
The normal distribution is the most popular model in applications to real data. We propose a new extension of this distribution, called the Kummer beta normal distribution, which presents greater flexibility to model scenarios involving skewed data. The new probability density function can be represented as a linear combination of exponentiated normal pdfs. We also propose analytical expressions for some mathematical quantities: Ordinary and incomplete moments, mean deviations and order statistics. The estimation of parameters is approached by the method of maximum likelihood and Bayesian analysis. Likelihood ratio statistics and formal goodnessof-fit tests are used to compare the proposed distribution with some of its sub-models and non-nested models. A real data set is used to illustrate the importance of the proposed model.
Research Interests:
Research Interests:
Absenteeism is the practice or custom of an employee to be absent from workplace. Its causes are diverse and may aect the workers income as well as to cause operational disruption, stress the administration and also nancial losses for the... more
Absenteeism is the practice or custom of an employee to be absent from workplace. Its causes are diverse and may aect the workers income as well as to cause operational disruption, stress the administration and also nancial losses for the company. Cluster analysis is a multivariate tool that can be used to determine groups in the sense that each group has its own characteristics in terms of the observed variables.In this sense, that technique can be used as a support to show which characteristics may contribute to absenteeism. We use the Ward hierarchical algorithm to build the clusters and to compare the groups the Kruskal-Wallis nonparametric test is adopted. Finally, a study on the strength of association among the variables is developed using Spearman's correlation and for the relationship among those variables related to absence and social aspects, we use the principal component analysis. Moreover, the study indicates the possibility to determine three heterogeneous groups ...