Geographica: A Benchmark for Geospatial RDF Stores

Geospatial extensions of SPARQL like GeoSPARQL and stSPARQL have recently been defined and corresponding geospatial RDF stores have been implemented. However, there is no widely used benchmark for evaluating geospatial RDF stores which takes into account recent advances to the state of the art in this area. In this paper, we develop a benchmark, called Geographica, which uses both real-world and synthetic data to test the offered functionality and the performance of some prominent geospatial RDF stores

Accumulated Damage In Nonlinear Cyclic Static And Dynamic Analysis Of Reinforced Concrete Structures Through 3D Detailed Modeling

Accurate nonlinear cyclic static and dynamic analysis of reinforced concrete structures is necessary when trying to capture the behavior of concrete structures during earthquake excitations. The development of an objective and robust 3D constitutive modeling approach that will be able to account for the accumulated material damage during the cyclic loading of concrete structures is of great importance in order to realistically describe the physical failure mechanisms [1]. The proposed method is based on the experimental results and the concrete modelling of Kotsovos and Pavlovic [2] as modified by Markou and Papadrakakis [3]. The objective of this research work is to propose a computationally efficient modeling method that accounts for the accumulated damage developed in both concrete and steel materials during cyclic static and dynamic excitations.Two new damage factors are proposed herein that take into account the number of openings and closures of cracks during the nonlinear cyclic analysis, thus provide with the ability to account for the accumulated damage in both steel and concrete materials. Furthermore, a solution strategy that describes the behavior of concrete during the cyclic static and dynamic analysis is also presented.The proposed numerical method is validated by comparing its numerical response with the corresponding experimental data of a beam-column frame joint and a two-storey reinforced concrete frame, which were tested under cyclic static and dynamic loading conditions, respectively. Based on the numerical findings, the proposed algorithm manages to accurately capture the experimental results, while the simulation of the understudy models was performed with computational robustness and efficiency. This numerical outcome demonstrates the potential of the proposed 3D detailed modeling approach to be implemented for the seismic assessment of full-scale reinforced concrete structures through nonlinear cyclic static and dynamic analysis

Complementation of Lymphotoxin α Knockout Mice with Tumor Necrosis Factor–expressing Transgenes Rectifies Defective Splenic Structure and Function

Lymphotoxin (LT)α knockout mice, as well as double LTα/tumor necrosis factor (TNF) knockout mice, show a severe splenic disorganization with nonsegregating T/B cell zones and complete absence of primary B cell follicles, follicular dendritic cell (FDC) networks, and germinal centers. In contrast, as shown previously and confirmed in this study, LTβ-deficient mice show much more conserved T/B cell areas and a reduced but preserved capacity to form germinal centers and FDC networks. We show here that similar to the splenic phenotype of LTβ-deficient mice, complementation of LTα knockout mice with TNF-expressing transgenes leads to a p55 TNF receptor–dependent restoration of B/T cell zone segregation and a partial preservation of primary B cell follicles, FDC networks, and germinal centers. Notably, upon lipopolysaccharide challenge, LTα knockout mice fail to produce physiological levels of TNF both in peritoneal macrophage supernatants and in their serum, indicating a coinciding deficiency in TNF expression. These findings suggest that defective TNF expression contributes to the complex phenotype of the LTα knockout mice, and uncover a predominant role for TNF and its p55 TNF receptor in supporting, even in the absence of LTα, the development and maintenance of splenic B cell follicles, FDC networks, and germinal centers

Pseudo-polymorphic Ventricular Tachycardia in a 12-lead Holter Recording

AbstractWe present an image of pseudo-polymorphic ventricular tachycardia recording on a 12-lead surface ECG Holter. Although at first glance the appearance of the recording resembled polymorphic ventricular tachycardia, careful investigation revealed normal electrocardiographic findings

ChatGPT and Persuasive Technologies for the Management and Delivery of Personalized Recommendations in Hotel Hospitality

Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies, have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity and personalization, recommender systems can effectively influence user decision-making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present a pilot experi-ment with a case study involving a hotel recommender system. We aim to study the impact of integrating ChatGPT and persua-sive techniques on user engagement, satisfaction, and conversion rates. The preliminary results demonstrate the potential of these technologies in enhancing the overall guest experience and business performance. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between LLMs and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue.Comment: 17 pages, 12 figure