Results 11 to 20 of about 59,985 (224)
Improving of Robotic Virtual Agent's errors that are accepted by reaction and human's preference [PDF]
International Conference on Social Robotics, Dec 2023, 2023 One way to improve the relationship between humans and anthropomorphic agents is to have humans empathize with the agents. In this study, we focused on a task between an agent and a human in which the agent makes a mistake. To investigate significant factors for designing a robotic agent that can promote humans empathy, we experimentally examined the ...
arxiv +1 more source
In B. Lugrin, C. Pelachaud, D. Traum (Eds.), The Handbook on
Socially Interactive Agents, Volume 1 (pp. 107-146). ACM books (2021), 2021 Socially interactive agents (SIAs) are no longer mere visions for future user interfaces, as 20 years of research and technology development has enabled the use of virtual and physical agents in day-to-day interfaces and environments. This chapter of the ACM "The Handbook on Socially Interactive Agents" reviews research on and technologies involving ...
arxiv +1 more source
Archiv der Pharmazie, Volume 355, Issue 12, December 2022., 2022 The 18F‐labeled derivative [18F]3 of senicapoc was synthesized using the prosthetic group approach with 1‐azido‐2‐[18F]fluoroethane ([18F]6) in a “click” reaction. The biological activity of the new positron emission tomography tracer was evaluated in vitro and in vivo.
Christian P. Konken +11 more
wiley +1 more source
BioFactors, Volume 48, Issue 6, Page 1226-1249, November/December 2022., 2022 Abstract Ocular allergies are becoming more prevalent as more airborne pollutants, irritants and microbes pervade our environment. Inflammatory and allergic mediators released by dendritic and mast cells within the conjunctiva cause allergic conjunctivitis (AC), a prevalent ocular surface disorder that affects >40% of the world's human population on a ...
Najam A. Sharif
wiley +1 more source
Cancer Communications, Volume 42, Issue 12, Page 1257-1287, December 2022., 2022 Abstract Clustered regularly interspaced short palindromic repeats‐associated protein (CRISPR/Cas9), an adaptive microbial immune system, has been exploited as a robust, accurate, efficient and programmable method for genome targeting and editing. This innovative and revolutionary technique can play a significant role in animal modeling, in vivo genome
Khaled S. Allemailem +6 more
wiley +1 more source
Clinical Pharmacology in Drug Development, Volume 12, Issue 1, Page 30-37, January 2023., 2023 Abstract The bioequivalence of a generic fudosteine tablet vs a brand‐named fudosteine tablet under fasting and fed conditions was evaluated in this study. This randomized, open‐label, single‐dose, 4‐way replicate, crossover, bioequivalence study included 64 healthy Chinese subjects (fasting cohort, n = 32; fed cohort, n = 32) who were assigned to ...
Mingxue Zhu +6 more
wiley +1 more source
Endocrinology, Diabetes &Metabolism, Volume 6, Issue 1, January 2023., 2023 The aim of this study was to validate type 1 diabetes live births in the Danish national registries against a clinical cohort of confirmed cases.The study concludes that algorithms can reliably identify type 1 diabetes in pregnancy in health registries, with a PPV above 90% and completeness around 80%.
Tina Wullum Gundersen +8 more
wiley +1 more source
Hepatology, EarlyView., 2022 CHIN117 is a dual cysteinyl leukotriene receptor 1 (CYSLTR1) antagonist and G‐protein‐coupled bile acid receptor 1 (GPBAR1) agonist. In the liver, GPBAR1 and CYSLTR1 are coexpressed by liver sinusoidal endothelial cells (LSECs), HSCs, circulating monocytes/macrophages, and liver resident macrophages (Kupffer cells).
Michele Biagioli +13 more
wiley +1 more source
Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning [PDF]
arXiv, 2021 Training a multi-agent reinforcement learning (MARL) algorithm is more challenging than training a single-agent reinforcement learning algorithm, because the result of a multi-agent task strongly depends on the complex interactions among agents and their interactions with a stochastic and dynamic environment.
arxiv
Fact-based Agent modeling for Multi-Agent Reinforcement Learning [PDF]
arXiv, 2023 In multi-agent systems, agents need to interact and collaborate with other agents in environments. Agent modeling is crucial to facilitate agent interactions and make adaptive cooperation strategies. However, it is challenging for agents to model the beliefs, behaviors, and intentions of other agents in non-stationary environment where all agent ...
arxiv