As the demand for sustainable and renewable energy sources grows, the use photovoltaic (PV) systems have seen rise in popularity and recognition. The performance of PV systems is influenced by numerous factors such as solar irradiance, temperature, and the tilt angle of the PV modules. Among these factors, the tilt angle of the PV modules plays a crucial role in determining the amount of energy that can be generated by a PV system. This paper explores the impact of tilt angle on the output and performance of grid-connected PV systems by using the software PVsyst. The study will examine how different tilt angles affect the energy yield, electrical characteristics, and performance ratio of PV system. A study was conducted to compare the performance of a PV system with fixed tilt angle versus seasonal tilt arrangement. The results showed that a seasonal tilt arrangement led to improved performance and increased electricity generation.

Shallow mountain lakes are highly sensitive to eutrophication. Cyanobacteria and microalgae in planktonic communities are the main producers in lake ecosystems, but stability of its communities is impacted by numerous factors. The aim of this study is to analyze seasonal diversity and community structure of cyanobacteria and microalgae in plankton and periphyton of the lake Paučko, physical and chemical properties of water and evaluate trophic status. The mountain lake Paučko is the shallow natural lake in Protected landscape Konjuh in northeastern Bosnia and Herzegovina. Sampling of net – phytoplankton, periphyton and water for physical and chemical analysis was caried in two seasons in 2018. Light microscopes and immersion objective (magnification 1000x) were used for the identification and quantification of microalgae. Non metric multimensional scaling and Simper analysis were used to describe communities in periphytic and planktic samples. In total, 70 taxa were identified. The most numerous were Bacillariophyta with 52, and Chlorophyta with 7 taxa. Seasonal dynamics in plankton communities were observed in the direction of shift of abundant Cyclotella meneghiniana, Dinobryon divergens, Peridinum cinctum and Ankistrodesmus fusiformus in spring season to Rabdoderma lineare and Pantocsekiella comensis in summer sampling season. Physical and chemical analysis of water revealed high values of total phosphorus, which correspond to the evaluated meso to eutrophic status of the lake calculated by Rott Trophic Index. The lake Paučko is under high pressure caused by the influx and retention of nutrients, which makes it susceptible to eutrophication. The results of the study provide the first insight into the diversity of cyanobacteria and microalgae for this lake and can be useful in planning of restoration measures in the context of ecological monitoring.

Abstract Gut microbiota is known as unique collection of microorganisms (including bacteria, archaea, eukaryotes and viruses) that exist in a complex environment of the gut. Recently, this has become one of the most popular areas of research in medicine because this plays not only an important role in disease development, but gut microbiota also influences drug pharmacokinetics. These alterations in drug pharmacokinetic pathways and drug concentration in plasma and blood often lead to an increase in the incidence of toxicological events in patients. This review aims to present current knowledge of the most commonly used drugs in clinical practice and their dynamic interplay with the host’s gut microbiota as well as the mechanisms underlying these metabolic processes and the consequent effect on their therapeutic efficacy and safety. These new findings set a foundation for the development of personalized treatments specific to each metabolism, maximizing drugs’ therapeutic effects and minimizing the side effects because they are one of the major limiting factors in treating patients.

With the rise in the number of robots in our daily lives, human-robot encounters will become more frequent. To improve human-robot interaction (HRI), people will require explanations of robots' actions, especially if they do something unexpected. Our focus is on robot navigation, where we explain why robots make specific navigational choices. Building on methods from the area of Explainable Artificial Intelligence (XAI), we employ a semantic map and techniques from the area of Qualitative Spatial Reasoning (QSR) to enrich visual explanations with knowledge-level spatial information. We outline how a robot can generate visual and textual explanations simultaneously and test our approach in simulation.

Yusong Tian,a,∗ Giovanni Calderini, Imogen Camp, Thibaud Idriss Carcone, Paul Mickael Chabrillat, Artur Cordeiro Oudot Choi, Francesco Crescioli, Jörn Große-Knetter, Šejla Hadžić, Shunsuke Iizaka, Christopher Krause, Lingxin Meng, f Koji Nakamura, Arnulf Quadt, Stefano Terzo, Ana Sofia Torrento Coello and Hua Ye II. Physikalisches Institut, Georg-August-Universität Göttingen, Friedrich-Hund-Platz 1, DE 37077 Göttingen, Germany LPNHE, Sorbonne Université, Université Paris Cité, CNRS/IN2P3, 4 place Jussieu, FR 75005 Paris, France Max-Planck-Institut für Physik (Werner-Heisenberg-Institut), Föhringer Ring 6, DE 80805 München, Germany Division of Physics and Tomonaga Center for the History of the Universe, Faculty of Pure and Applied Sciences, University of Tsukuba, 1 Chome-1-1 Tennodai, Tsukuba, Japan Fakultät Physik, Technische Universität Dortmund, Otto-Hahn-Straße 4, DE 44227 Dortmund, Germany f Physics Department, Lancaster University, Bailrigg, Lancaster LA1 4YW, United Kingdom KEK, High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Japan Institut de Física d’Altes Energies (IFAE), Barcelona Institute of Science and Technology, UAB Campus, Edifici CN, ES 08193 Barcelona, Spain Detectors and Instrumentation Department, IJCLab – Laboratoire de Physique des 2 Infinis Irène Joliot-Curie, UMR 9012 – CNRS / Université Paris-Saclay / Université Paris Cité, 15 rue Georges Clémenceau, FR 91405 Orsay, France

The ITk detector, the new ATLAS silicon tracking system for the High Luminosity LHC (HL-LHC), will be equipped with 3D pixel sensor modules in the innermost layer (L0). The pixel cell dimensions will be 25 × 100 µ m 2 in the barrel and 50 × 50 µ m 2 in the end-caps, with one readout electrode at the centre of each pixel and four bias electrodes at the corners. Sensors from pre-production wafers (50 × 50 µ m 2 ) produced by FBK have been bump-bonded to ITkPixV1.1 chips at IZM. Bare modules have been assembled in Genoa on Single Chip Cards (SCCs) and characterized in laboratory measurements and in test beam campaigns. Some of these modules have been irradiated in Bonn and at the CERN IRRAD facility. Preliminary results of their characterization after irradiation

Various methods are nowadays available to design observers for broad classes of systems, where the primary focus is on establishing the convergence of the estimated states. Nevertheless, the question of the tuning of the observer to achieve satisfactory estimation performance remains largely open. In this context, we present a general design framework for the online tuning of the observer gains. Our starting point is a robust nominal observer designed for a general nonlinear system, for which an input-to-state stability property can be established. Our goal is then to improve the performance of this nominal observer. We present for this purpose a new hybrid multi-observer scheme, whose flexibility can be exploited to enforce various desirable properties, e.g., fast convergence and good sensitivity to measurement noise. We prove that an input-to-state stability property also holds for the proposed scheme and, importantly, we ensure that the estimation performance in terms of a quadratic cost is (strictly) improved. We illustrate the efficiency of the approach in improving the performance of given nominal observers in two numerical examples (Van der Pol oscillator and lithium-ion battery model).

Robotic Telepresence (RT) is a promising medium for students who are unable to attend in-person classes. It enables remote students to be present in the classroom and interact with their classmates and instructors. However, it can be limiting to their identity self-perception and projection, which may have repercussions on the social dynamics and inclusion within the classroom. We present preliminary findings of a qualitative analysis of 12 observations and interviews with RT attendees. We examine RT design and use aspects that either supported identity self-perception and projection or limited it. Finally, we present telepresence robots design and use recommendations for the classroom context.

Citizens and policy institutions increasingly express their concerns regarding the emerging challenges in the context of Artificial Intelligence (AI) and have concrete demands for the protection of human rights. In parallel, studies in the field of AI and Human-Robot Interaction (HRI) indicate the impact of social robots on children's development. We conducted a systematic review based on UNICEF's AI Policy Guidance to map the landscape of research on social robots and children's rights. We used the PRISMA method and identified N=37 papers that address one of the rights, which we then annotated to indicate tendencies and areas of alignment and misalignment with the UNICEF guidance. Our findings reveal that although the field of HRI is looking at specific rights, with a focus on inclusion, some of the rights have been under-researched. Furthermore, we observed a misalignment between HRI and UNICEF regarding the terminology. With this paper, we hope to bring awareness to the field of HRI regarding children's rights and to highlight directions for alignment among research, societal needs, and policy.

Robots could support older adults' well-being by engaging them in meaningful conversations, specifically to reflect on, support, and improve different aspects of their well-being. We implemented a system on a QT social robot to conduct short autonomous conversations with older adults, to help understand what brings them feelings of joy and meaning in life. We evaluated the system with written surveys and observations of 12 participants including older adults, caregivers, and dementia care staff. From this, we saw the need to improve user experience through personalized interaction that better support older adults as they talk about well-being. Improving the interactions will involve improving the conversation flow, detecting emotions and nonverbal cues, and natural language processing to extract topics around well-being.

We present an ethnographic observational study of six robot cafes in Japan to understand how service robots are performatively staged and presented to the public. We particularly attend to the diverse ways in which the physical setting and ambience of the cafes, the verbal characterization of and staff behaviors toward robots, explicit and implicit instructions on appropriate interactions with robots, and handling of robot malfunctions constitute robots as socially acceptable and useful in daily life. Such scaffolding enables robots to provide material and affective services to cafe visitors, and visitors to explore various interaction possibilities with robots. Our work contributes to the critical study of the ongoing construction of "robot cultures" in Japan, and calls attention to public interactions with robots and the importance of contextual staging beyond individual robot features in human-robot interaction design.

Evaluation of robots commonly occurs using various stimuli, including photos, videos, and live interaction. However, a better understanding of how and why chosen stimuli affect perceptions, and how evaluations using lower fidelity media (e.g. photos) compare to evaluations using higher context stimuli (e.g., videos), is needed. Through a survey of 599 M-Turk participants, we compare robot evaluations based on exposure to three types of media - photos, GIFs, and promotional videos. We analyze nine perception and behavioral intention measures of three home robots with varying levels of anthropomorphism (Olly, Jibo, and Liku): overall liking, liking of appearance, liking of intended use, eeriness, human-likeness, performance expectations, privacy concerns, information seeking intention, and purchase intention. We find that photos consistently differ from ratings of videos for all measures, except for liking of robots' intended use. Use of GIFs led to measurements in line with videos for seven of the nine measurements, due to the importance of movement in perceptual assessments and character judgments (e.g., friendly, creepy). Except for the most human-like robot, neither photos nor GIFs captured human-likeness to a similar degree as videos, due to the importance of speech in assessments. Though GIFs captured informational and overall privacy concerns well, they did not adequately capture physical privacy concerns.

As a step towards designing a home robot to support older adults' ikigai (meaning in life), we interviewed the family members who provide care for them. After conducting interviews with ten family caregivers in Japan, we found that older adults' physical health is a major concern to both caregivers and older adults. However, concerns over loneliness were not prioritized by caregivers, though they did perceive older adults' worries around this issue. Additionally, caregivers saw a number of ways a social robot could be designed to address this, as well as its ability to go beyond loneliness in promoting more fulfilling lives among older adults. Finally, we conclude that an ikigai robot may be designed to support both the ikigai of older adults and (indirectly) their family caregivers.

The use of socially assistive robots is able to alleviate some depression symptoms, according to existing research. However, due to comorbidities that often accompany depression and the unique experiences of each individual, it is necessary to get a better understanding of how SARs should be personalized. Through 10 hourlong workshops with 10 individuals living with depression, we explored the customization of a zoomorphic SAR for adults with depression. By using the SAR Therabot? as a base platform, participants designed their own unique covering for the robot, and discussed desired robot behaviors and privacy concerns around data collection. Though the physical designs of the robots varied greatly, participants expressed common themes regarding their preference for a soft touchable exterior, comfort with sharing data with their therapists, and interest in the robot producing more realistic sounds and movements, among other design features.