Abstract
Organizations aim to achieve operational efficiency capable of responding to high market competitiveness. The implementation of automation systems in organizational processes is a key factor in improving operational efficiency. This paper intends to contribute for a better understanding of the adoption of automation systems in organizations and analyze their impact on employee performance, considering the conditions under which they were implemented. The methodology for this study was qualitative research, in which semi-structured exploratory interviews conducted with employees from the Accounts Receivable department of automotive sector companies were carried out. The main goal was to understand their perception of the use of automation systems in their work tasks. The results of this research led to the conclusion that automation systems, even when underutilized, are beneficial in reducing repetitive and manual tasks. Nevertheless, the way in which they are implemented has a direct impact on the motivation of employees to use them.

Abstract
This research aims to analyze the positioning theory and discourse within Sao Paulo's Place Branding from 2014 to 2019, investigating the symbolic representations employed by the Sao Paulo Tourism Bureau to emphasize its branding endeavors. The methodology employed a framework based on Semprini's [10] Project/Manifestation approach and Discourse Analysis. The impetus behind this study arises from the substantial investments made by cities to craft comprehensive disclosure strategies and establish place branding for their respective regions. We observed aspects of Communication and DigitalMarketing in the three promotional videos produced by SPTuris in 2014, 2017, and 2019, which underwent meticulous analysis. Our findings unveiled a consistent thematic discourse despite shifts in political administration. The 2014 video accentuated multiculturalism and cosmopolitanism, while the 2017 edition highlighted experiential marketing, business, consumption, and cosmopolitan elements. Remarkably, the 2019 presentation featured images emphasizing receptivity. Themes such as Culture, Arts, and Gastronomy were recurrent across all videos. The scrutinized discourse reaffirms Sao Paulo's capital as a trendsetter within Brazil.

Abstract
After the pandemic we experienced, companies have felt the need to reinvent themselves and adapt to the present moment. The Internet and social networks have developed and increased their activity substantially. Users spend more time on social networks, shop more online, and feel more than ever a need for information and to view content. The main objective of this research is to define and implement a content marketing strategy for the social networks, through a quarterly content plan in the marketing services company Naive. In the first part of the research, presented in this paper, the work consisted of designing and implementing a questionnaire, obtaining a sample of 200 respondents to assess their perceptions and habits regarding social networks and the content offered on social networks, to study the results. The results obtained and analysis done will be used to develop a content strategy for Naive, which include studying the specific objectives for the company's different social networks, the actions to be developed and the content to be implemented.

Abstract
The United Nations has set Sustainable Development Goals (SDGs) to build a more sustainable future. The SDG analyzes progress to understand major implementation challlenges, define disparities across nations or regions, and propose priorities for action. It has 17 objectives and more than 200 indicators. Cluster analysis was used to categorize the 10 municipalities. It was carried out using IBM SPSS software, which calculated the Euclidean distance and put the investigated regions into clusters with the traits they shared the most in common.

Abstract
Gliomas are a common and aggressive kind of brain tumour that is difficult to diagnose due to their infiltrative development, variable clinical presentation, and complex behaviour, making them an important focus in neuro-oncology. Segmentation of brain tumour images is critical for improving diagnosis, prognosis, and treatment options. Manually segmenting brain tumours is time-consuming and challenging. Automatic segmentation algorithms can significantly improve the accuracy and efficiency of tumour identification, thus improving treatment planning and outcomes. Deep learning-based segmentation tumours have shown significant advances in the last few years. This study evaluates the impact of four denoising filters, namely median, Gaussian, anisotropic diffusion, and bilateral, on tumour detection and segmentation. The U-Net architecture is applied for the segmentation of 3064 contrast-enhanced magnetic resonance images from 233 patients diagnosed with meningiomas, gliomas, and pituitary tumours. The results of this work demonstrate that bilateral filtering yields superior outcomes, proving to be a robust and computationally efficient approach in brain tumour segmentation. This method reduces the processing time by 12 epochs, which in turn contributes to lowering greenhouse gas emissions by optimizing computational resources and minimizing energy consumption.

Abstract