Hochschule Bonn-Rhein-Sieg
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Archaeometric study of execution techniques of white Attic vases: the case of the Perseus crater in Agrigento
The white ground crater by the Phiale Painter (450–440 BC) exhibited in the “Pietro Griffo” Archaeological Museum in Agrigento (Italy) depicts two scenes from Perseus myth. The vase is of utmost importance to archaeologists because the figures are drawn on a white background with remarkable daintiness and attention to detail. Notwithstanding the white ground ceramics being well documented from an archaeological and historical point of view, doubts concerning the compositions of pigments and binders and the production technique are still unsolved. This kind of vase is a valuable rarity, the use of which is documented in elitist funeral rituals. The study aims to investigate the constituent materials and the execution technique of this magnificent crater. The investigation was carried out using non-destructive and non-invasive techniques in situ. Portable X-ray fluorescence and Fourier-transform total reflection infrared spectroscopy complemented the use of visible and ultraviolet light photography to get an overview and specific information on the vase. The XRF data were used to produce false colour maps showing the location of the various elements detected, using the program SmART_scan. The use of gypsum as the material for the white ground is an important result that deserves to be further investigated in similar vases
Therapeutic Treatments for Osteoporosis-Which Combination of Pills Is the Best among the Bad?
Osteoporosis is a chronical, systemic skeletal disorder characterized by an increase in bone resorption, which leads to reduced bone density. The reduction in bone mineral density and therefore low bone mass results in an increased risk of fractures. Osteoporosis is caused by an imbalance in the normally strictly regulated bone homeostasis. This imbalance is caused by overactive bone-resorbing osteoclasts, while bone-synthesizing osteoblasts do not compensate for this. In this review, the mechanism is presented, underlined by in vitro and animal models to investigate this imbalance as well as the current status of clinical trials. Furthermore, new therapeutic strategies for osteoporosis are presented, such as anabolic treatments and catabolic treatments and treatments using biomaterials and biomolecules. Another focus is on new combination therapies with multiple drugs which are currently considered more beneficial for the treatment of osteoporosis than monotherapies. Taken together, this review starts with an overview and ends with the newest approaches for osteoporosis therapies and a future perspective not presented so far
Digitally co-created corporate social responsibility: Testing the effectiveness of “You decide, we donate” approaches
Comparative study of 3D object detection frameworks based on LiDAR data and sensor fusion techniques
Estimating and understanding the surroundings of the vehicle precisely forms the basic and crucial step for the autonomous vehicle. The perception system plays a significant role in providing an accurate interpretation of a vehicle's environment in real-time. Generally, the perception system involves various subsystems such as localization, obstacle (static and dynamic) detection, and avoidance, mapping systems, and others. For perceiving the environment, these vehicles will be equipped with various exteroceptive (both passive and active) sensors in particular cameras, Radars, LiDARs, and others. These systems are equipped with deep learning techniques that transform the huge amount of data from the sensors into semantic information on which the object detection and localization tasks are performed. For numerous driving tasks, to provide accurate results, the location and depth information of a particular object is necessary. 3D object detection methods, by utilizing the additional pose data from the sensors such as LiDARs, stereo cameras, provides information on the size and location of the object. Based on recent research, 3D object detection frameworks performing object detection and localization on LiDAR data and sensor fusion techniques show significant improvement in their performance. In this work, a comparative study of the effect of using LiDAR data for object detection frameworks and the performance improvement seen by using sensor fusion techniques are performed. Along with discussing various state-of-the-art methods in both the cases, performing experimental analysis, and providing future research directions
Building Appropriate Trust in Human-AI Interactions
AI (artificial intelligence) systems are increasingly being used in all aspects of our lives, from mundane routines to sensitive decision-making and even creative tasks. Therefore, an appropriate level of trust is required so that users know when to rely on the system and when to override it. While research has looked extensively at fostering trust in human-AI interactions, the lack of standardized procedures for human-AI trust makes it difficult to interpret results and compare across studies. As a result, the fundamental understanding of trust between humans and AI remains fragmented. This workshop invites researchers to revisit existing approaches and work toward a standardized framework for studying AI trust to answer the open questions: (1) What does trust mean between humans and AI in different contexts? (2) How can we create and convey the calibrated level of trust in interactions with AI? And (3) How can we develop a standardized framework to address new challenges
Examining Generation Z’s Attitudes, Behavior and Awareness Regarding Eco-Products: A Bayesian Approach to Confirmatory Factor Analysis
The research examines Generation Z’s (Gen Z’s) attitudes, behavior and awareness regarding sustainability-oriented products in two European countries, located in the region of Western Balkans, Bosnia–Herzegovina and Serbia. The research deploys generational cohort theory (GCT) and a quantitative analysis of primary data collected through an online questionnaire among 1338 primary, high school and university students, all belonging to Generation Z. It deploys a Confirmatory Factor Analysis (CFA) by running both Maximum Likelihood (ML) and Markov Chain Monte Carlo (MCMC) procedures, the latter being suitable for binary variables, which have been deployed in the study. The results of MLCFA provide evidence that there is a statistically significant and relatively strong relation between sustainability and circular economy attitudes (SCEA) and sustainability and circular economy behavior (SCEB), while there is a statistically insignificant and relatively weak relation between sustainability and circular economy behavior (SCEB) and circular economy awareness (CEW). The results of the BCFA, which is based on MCMC procedure, are similar to the results based on a rather commonly used MLCFA procedure. The results also confirm that Gen Z knows more about the companies which recycle products than it does about the CE as a concept, while the vast majority is concerned about the future of the planet and is motivated to learn more about the CE through CE and various awareness-raising measures
Point Containment Queries on Ray Tracing Cores for AMR Flow Visualization
Modern GPUs come with dedicated hardware to perform ray/triangle intersections and bounding volume hierarchy (BVH) traversal. While the primary use case for this hardware is photorealistic 3D computer graphics, with careful algorithm design scientists can also use this special-purpose hardware to accelerate general-purpose computations such as point containment queries. This article explains the principles behind these techniques and their application to vector field visualization of large simulation data using particle tracing