Centrifugal pumps are widely employed in the oil refinery industry due to their efficiency and effectiveness in fluid transfer applications. The reliability of pumps plays a pivotal role in ensuring uninterrupted plant productivity and safe operations. Analysis of failure history data shows that bearings have been identified as critical components in oil refinery pump groups. However, traditional reliability estimation theories may not apply when data is limited or subject to right censoring. This paper addresses the complexity of estimating the Weibull distribution parameters using the maximum-likelihood method under the abovementioned conditions. The likelihood equation lacks an explicit analytical solution, necessitating the use of numerical methods for resolution. The proposed approach presented in this article leverages the Expectation-Maximization (EM) algorithm for estimating the Weibull distribution parameters. This method provides more accurate estimates of failure rates and probabilities by accounting for limited and censored data. The findings are demonstrated through a case study, showcasing the practical application of the proposed approach.

Quality control is a critical component in industrial manufacturing, directly influencing efficiency, product reliability, and ultimately, customer satisfaction. In the dynamic environment of industrial manufacturing, traditional methods of inspection may not adequately meet the evolving complexity, necessitating innovative approaches to bolster precision and productivity. In this study, we explore the application of mixed reality (MR) technology for real-time quality control in the assembly process. Our methodology involved the integration of smart glasses with a server-based image recognition system, designed to conduct real-time component analysis. The innovative aspect of our study lies in the harmonization of MR and computer vision algorithms, providing immediate visual feedback to inspectors and thereby improving the speed and accuracy of defect detection. YOLOv8 have been adopted in this study for detection object model. The project implementation occurred in a controlled environment to enable a comprehensive evaluation of the system functionality, the identification of possible problems and improvements in the system performance. The results indicated the viability of mixed reality as a powerful tool for enhancing traditional inspection processes. The fusion of MR and computer vision offers possibilities for future advancements in industrial quality control, paving the way for more efficient and reliable manufacturing ecosystems.

The aims of study was to evaluate the effects of rates, sources and timing of nitrogen application under cover of transgenic corn yield cultivated in Amazon Biome. The experiments were conducted in Parauapebas city, State of Pará, Brazil, in two years (2016/2017 and 2017/2018). The experimental design was randomized blocks, in a 5x2x2 factorial scheme, consisting of five rates of N (0; 45; 90; 135; and 180 kg ha-1), two nitrogen sources (urea and ammonium sulfate) and two application times of N (phenological stages V4 and V8), with four replications. The factor N rates promoted adjustment of linear equation (leaf area index, mass of thousand grains, and yield) and quadratic equation (dry mass of leaf index). Nitrogen fertilization promoted significant increases in mass of thousand grains and yield, obtaining the best results with 180 kg ha-1 of N applied at V4 phenological stage. Based on results obtained in two years of corn cultivated under conditions of Amazon Biome, the application of N at V4 phenological stage at rates of 121 to 131.39 kg ha-1 of N showed the best results for vegetative growth, while 180 kg ha-1 of N, regardless of source used, urea or ammonium sulfate, promoted greater grain weight and greater yield.

This review aimed to analyze the effects of additives in the process of producing silage from re-hydrated corn grains for ruminants. Control treatment studies used in this analysis was corn grain rehydrated with water only. To be included in the review, the studies needed to follow stand-ardized criteria, including the absence of additives in the control treatment and the evaluation of the silage in beef animals, such as cattle, goats, and sheep. A total of seven publications, published between 2014 and 2022, were included in the final dataset. To compare the results, the PROC ANOVA of SAS was used, which included a random effect of comparison within the study, per-forming a paired comparison. It was observed that the use of additives did not influence the chemical composition, pH, organic acid and ethanol content, microbial population, fermentative losses, aerobic stability, and dry matter in vitro digestibility of rehydrated corn grain silage (p >0.05). Based on this information, it is concluded that the use of additives in rehydrated corn grain silage did not show major differences on silage quality. It is important, however, to evaluate the effects of additives in silages on animal performance.

The family context has been associated with children's weight status. This study aims to investigate the association between parents' adherence to the Mediterranean diet and family time with the weight status of children. The research is part of the BeE-school, a cluster randomized trial implemented in primary schools located in social vulnerable contexts. A total of 735 children (380 boys), aged 6 to 10, participated in the study. Anthropometrics were assessed during school time, weight status categorized, while parents self-reported sociodemographic variables, adherence to the Mediterranean diet (MEDAS questionnaire), and family time. Children from families with higher education levels whose parents have a high adherence to the Mediterranean diet, have lower odds to have overweight/obesity (odds ratio (OR) 0.301, 95% CI 0.143-0.634, p=0.002). Also, children from families with lower education levels who have more time together with their family, have lower odds to have overweight/obesity (OR 0.731, 95% CI 0.573-0.934, p=0.012). The family environment, mainly family time together and adherence to Mediterranean diet, exerts a significant influence on children’s weight status. Professionals working in children’s health should consider the family when fostering health-promoting behaviors.