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Abstract
The aquaculture industry faces significant challenges related to sustainability, productivity, and fish welfare. Key issues include managing environmental conditions, disease, pests, and data integration from various sensors and monitoring systems. The BigFish project aims to address these challenges through advanced analytics and machine learning, focusing on three case studies in Atlantic salmon farms: predicting oxygen levels, reducing sea lice infestations, and improving data interaction and visualization. Predictive models for oxygen levels and sea lice infestation, as well as natural language interfaces for data visualization, demonstrate the potential for improved decision-making and management practices in aquaculture. Early results indicate the effectiveness of these approaches, highlighting the importance of data-driven solutions in enhancing industry sustainability and productivity. © 2024 IEEE.

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.

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Energy and materials are increasingly important in industrialized countries, and they impact the economy, sustainability, and people's future. The purpose of this work was to study the relationship between energy and the circular economy using methods such as Pearson's correlation and a principal component analysis. Thus, 12 strong correlations were found, with 5 of them between the following relevant variables from two different subjects: the correlations of the raw material consumption, the domestic material consumption, and the material import dependency with the final energy consumption in transport (0.81, 0.92, and 0.81); the correlation of the circular material use rate with the final energy consumption in households (0.70); and the correlation of the material import dependency with the final energy consumption in industry (0.89). The time series forecast was only conclusive for the waste generated, showing that it will increase in the next 10 years.

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This paper describes a study developed to analyse the interest in investing in Li-ion batteries to perform price arbitrage in the power system of Portugal. In this context, it was developed a methodology to identify the most suitable hours for charging and discharging the energy, and the new market prices were estimated for these hours. It was concluded that at current investment costs in this storage technology, and current market prices, this investment would not be viable in the lifetime of the batteries despite the recent rise of electricity market prices and also the larger price spread. This spread is now larger given the depression of prices at sunny hours that is getting typical in the Iberian electricity market.

Abstract
Purpose: Inherited retinal diseases (IRDs) are a group of degenerative disorders of the retina, that can be potentially associated with changes in the anterior segment, but their prevalence and impact are not known. Exploring these concomitant ophthalmologic changes with biomechanical assessment may help identify other non-retina causes of vision loss in these patients, such as corneal ectasia or susceptibility to glaucoma. This study aimed to measure and compare corneal biomechanics in patients with and without IRDs. Methods: A total of 77 patients (154 eyes) with IRD were recruited as the study group. The control group consisted of 77 healthy adults (154 eyes) with matched age and sphere equivalents. All participants underwent a comprehensive assessment including corneal tomography (Pentacam (R)) and biomechanical assessment (Corvis ST (R)). A total of 4 second-generation biomechanical parameters and 3 indexes were collected: Ambrosio Relational Thickness (ARTh), Deflection Amplitude Ratio Max (DARM), Integrated Radius (IR) and Stiffness Parameter at Applanation (SP-A1), the final deviation value D of the Belin/Ambrosio Enhanced Ectasia Display (BADResults: For IRD patients, there was a higher DARM (p < 0.001), lower ARTh (p < 0.001), higher CBI (p < 0.001), higher TBI (p<0.001), and higher BAD-D (p < 0.001) compared to the control group. Regarding discrimination of healthy subjects and IRD patients, ARTh was the most sensitive parameter. Conclusion: The results showed that IRD patients tend to have softer corneal behaviour, compared to eyes without pathology, which may predispose patients to corneal ectasia or glaucoma development. ARTh could be used to screen IRD patients if a non-retina cause of vision loss is suspected.