Abstract
To meet the growing demand of robotics applications in industry high efforts are placed on research and education for robotics fundamentals, as a more intuitive and easier access to robotics must be ensured. Based on this, the aim of this work is to make a contribution to investigate new approaches for teaching robotics fundamentals using immersive technologies. In this work an existing digital twin for a desktop robot was extended by adding a feature for the positioning of way-points for path planning in an existing Augmented Reality (AR) application as well as update the robot controller with the inverse kinematics for the corresponding motion implementation. The performance of the new functionality was evaluated by means of a pick-and-place application and validated via a test series with an associated questionnaire. The conducted experiments have been carried out in a comparative study between the AR based digital twin and an ABB industrial robot where a clear benefit of the proposed systems for entry into robotics as well as for teaching was identified.

Abstract
This paper describes the development of an optical tweezers system that operates in fully automatic mode. It features image recognition for particle tracking, allowing for the optical trapping and analysis of identified targets. The system can perform analysis of forward scattered light and Raman spectroscopy of the trapped particles, facilitating the automated analysis of a large number of samples without manual intervention. By leveraging combined analytical methods and AI for robust classification, this system contributes to the advancement of automated diagnostic tools. Preliminary results demonstrate the system's effectiveness using different kinds of standard and biofunctionalized PMMA microparticles.

Abstract
In this paper it is presented a Hardware-in-theloop (HIL) mobile robot programming approach, to be applied in a robotics educational context. The motivation to apply this approach is the fact that students can program the robots without access to the robot hardware, but still maintain some important closed loop control critical features, such as a realistic lag time and the possibility for a larger number of students to program at the same time. Therefore, the developed software is applied to the real hardware without any change. The HIL approach was applied to provide a simulation close to reality, once the processing occurs in the real robot processor and the actuation and sensorization inside the simulation, adding to the advantage to test the firmware avoiding damage in the physical robot.

Abstract
This paper presents a methodology for assessing the long-term economic feasibility of renewable energy-based systems for green hydrogen and ammonia production. A key innovation of this approach is the incorporation of a predictive algorithm that optimizes day-ahead system operation on an hourly basis, aiming to maximize profit. By integrating this feature, the methodology accounts for forecasting errors, leading to a more realistic economic evaluation. The selected case study integrates wind and PV as renewable energy sources, supplying an electrolyser and a Haber-Bosch ammonia production plant. Additionally, all supporting equipment, including an air separation unit for nitrogen production, compressors, and hydrogen / nitrogen / ammonia storage devices, is also considered. Furthermore, an electrochemical battery is included, allowing for an increased electrolyser load factor and smoother operating regimes. The results demonstrate the effectiveness of the proposed methodology, providing valuable insights and performance indicators for this type of energy systems, enabling informed decision-making by investors and stakeholders.

Abstract
Covid-19 is a serious disease caused by the Sars-CoV-2 virus that has been first reported in China at late 2019 and has rapidly spread around the world. As the virus affects mostly the lungs, chest X-rays are one of the safest and most accessible ways of diagnosing the infection. In this paper, we propose the use of an approach for detecting Covid-19 in chest X-ray images through the extraction and classification of local and global percolation-based features. The method was applied in two datasets: one containing 2,002 segmented samples split into two classes (Covid-19 and Healthy); and another containing 1,125 non-segmented samples split into three classes (Covid-19, Healthy and Pneumonia). The 48 obtained percolation features were given as input to six different classifiers and then AUC and accuracy values were evaluated. We employed the 10-fold cross-validation method and evaluated the lesion sub-types with binary and multiclass classification using the Hermite Polynomial classifier, which had never been employed in this context. This classifier provided the best overall results when compared to other five machine learning algorithms. These results based in the association of percolation features and Hermite polynomial can contribute to the detection of the lesions by supporting specialists in clinical practices.

Abstract
The determination of grape quality parameters is intricately linked to the mineral composition of the fruit; this relationship is increasingly affected by the impacts of climate change. The conventional chemical methodologies employed for the mineral quantification of grape tissues are expensive and impracticable for widespread commercial applications. This paper utilized Laser-Induced Breakdown Spectroscopy (LIBS) to analyze the mineral constituents within the skin, pulp, and seeds of two distinct Vitis vinifera cultivars: a white cultivar (Loureiro) and a red cultivar (Vinh & atilde;o). The primary objective was to discriminate the potential variations in the calcium (Ca), magnesium (Mg), and nitrogen (N) concentrations and water content among different grape tissues, explaining their consequential impact on the metabolic constitution of the grapes and, by extension, their influence on various quality parameters. Additionally, the study compared the mineral contents of the white and red grape cultivars across three distinct time points post veraison. Significant differences (p < 0.05) were observed between the Loureiro and Vinh & atilde;o cultivars in Ca concentrations across all the dates and tissues and for Mg in the skin and pulp, N in the pulp and seeds, and water content in the skin and pulp. In the Vinh & atilde;o cultivar, Ca differences were found in the pulp across the dates, N in the seeds, and water content in the skin, pulp, and seeds. Comparing the cultivars within tissues, Ca exhibited differences in the pulp, Mg in the skin and pulp, N in the pulp and seeds, and water content in the skin, pulp, and seeds. These findings provide insights into the relationship between the grape mineral and water content, climatic factors, and viticulture practices within a changing climate.