Abstract
As social media (SM) becomes increasingly prevalent, its impact on society is expected to grow accordingly. While SM has brought positive transformations, it has also amplified pre-existing issues such as misinformation, echo chambers, manipulation, and propaganda. A thorough comprehension of this impact, aided by state-of-the-art analytical tools and by an awareness of societal biases and complexities, enables us to anticipate and mitigate the potential negative effects. One such tool is BERTopic, a novel deep-learning algorithm developed for Topic Mining, which has been shown to offer significant advantages over traditional methods like Latent Dirichlet Allocation (LDA), particularly in terms of its high modularity, which allows for extensive personalization at each stage of the topic modeling process. In this study, we hypothesize that BERTopic, when optimized for Twitter data, can provide a more coherent and stable topic modeling. We began by conducting a review of the literature on topic-mining approaches for short-text data. Using this knowledge, we explored the potential for optimizing BERTopic and analyzed its effectiveness. Our focus was on Twitter data spanning the two years of the 117th US Congress. We evaluated BERTopic's performance using coherence, perplexity, diversity, and stability scores, finding significant improvements over traditional methods and the default parameters for this tool. We discovered that improvements are possible in BERTopic's coherence and stability. We also identified the major topics of this Congress, which include abortion, student debt, and Judge Ketanji Brown Jackson. Additionally, we describe a simple application we developed for a better visualization of Congress topics.

Abstract
This research revolves around the potential challenges, opportunities, and strategies associated with human-centered generative artificial intelligence (AI) in the music compositional practice, emphasizing the role of metaphorical design in shaping musicians' expectations toward the adoption of generative AI in their everyday creative activities. Through a human-computer interaction (HCI) lens, this paper aims to discuss the cultural implications of the human-AI metaphorical design space for the seamless integration of intelligent algorithmic experiences in a manner that aligns with cultural values and realistic expectations of music creators while promoting informed policies, sociotechnical imaginaries, and culturally sensitive generative AI design strategies with focus on user-friendly interfaces that resonate with diverse music creation groups.

Abstract
Synthetic aperture radar (SAR) technology has emerged as a pivotal tool in viticulture, offering unique capabilities for various applications. This study provides a comprehensive overview of the current state-of-the-art applications of SAR in viticulture, highlighting its significance in addressing key challenges and enhancing viticultural practices. The historical evolution and motivations behind SAR technology are also provided, along with a demonstration of its applications within viticulture, showcasing its effectiveness in various aspects of vineyard management, including delineating vineyard boundaries, assessing grapevine health, and optimizing irrigation strategies. Furthermore, future perspectives and trends in SAR applications in viticulture are discussed, including advancements in SAR technology, integration with other remote sensing techniques, and the potential for enhanced data analytics and decision support systems. Through this article, a comprehensive understanding of the role of SAR in viticulture is provided, along with inspiration for future research endeavors in this rapidly evolving field, contributing to the sustainable development and optimization of vineyard management practices.

Abstract
In this paper it is presented a Hardware-in-the-loop (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
Spectral imaging is a technique that captures spectral information from a scene and maps it onto a 2D image, featuring the potential to reveal hidden features and properties of objects that are invisible to the human eye, such as elemental and molecular compositions. Augmented reality (AR), on the other hand, is a technology that enhances the perception of reality by superimposing digital information on the physical world. While these technologies have different purposes, they can be considered one and the same in terms of providing an user-centric extension of reality. Spectral imaging provides the information that can reveal the underlying nature of objects, while AR provides the method of visualization that can display the information in an intuitive and interactive way. In this work, we present a novel Unity toolkit that combines spectral imaging and a HoloLens 2 AR device to create an interactive and immersive experience for the user. The toolkit enables the interactive visualization of various elemental maps of a 3D rock model in AR using a simple and intuitive interface. With this technique, the user can select a sample model and an elemental map from a preloaded asset library and then see the map projected onto the rock model in AR, using simple interactions such as zoom adjustment, rotation, and pan of the models to explore features and properties in detail. The toolkit offers several advantages, including better contextual interpretation of the spectral data by placing it in relation to the shape and texture of the rock, increased user engagement and curiosity through the creation of a realistic and immersive experience, and ease of decision-making through the provision of comparative tools. In short, by combining spectral imaging and AR, we present an innovative approach that can enrich the user experience and expand the user knowledge of the environment.

Abstract