Myocardial rupture after percutaneous coronary intervention of an unstable RCA lesion in myocardial infarction and concomitant stroke treated with intravenous fibrinolytic agents: A case report [PDF]
Benjamin Bay+4 more
openalex +3 more sources
The Use of Fibrinolytic Agents in the Salvage of Free Flaps: A Systematic Review [PDF]
Patrick Mandal+8 more
openalex +2 more sources
Combining Antithrombotic and Fibrinolytic Agents [PDF]
Pooja Khatri, Marie‐Luise Mono
openalex +2 more sources
The efficacy and safety of anti-fibrinolytic agents in blood management following peri-acetabular osteotomy [PDF]
Mian Wang+3 more
openalex +2 more sources
Improving of Robotic Virtual Agent's errors that are accepted by reaction and human's preference [PDF]
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
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
Shared features of endothelial dysfunction between sepsis and its preceding risk factors (aging and chronic disease) [PDF]
Acute vascular endothelial dysfunction is a central event in the pathogenesis of sepsis,increasing vascular permeability, promoting activation of the coagulation cascade, tissue edema and compromising perfusion of vital organs. Aging and chronic diseases(hypertension,dyslipidaemia,diabetes mellitus,chronic kidney disease,cardiovascular disease ...
arxiv +1 more source
Cooperative and Competitive Biases for Multi-Agent Reinforcement Learning [PDF]
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]
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
Cooperative Heterogeneous Deep Reinforcement Learning [PDF]
Numerous deep reinforcement learning agents have been proposed, and each of them has its strengths and flaws. In this work, we present a Cooperative Heterogeneous Deep Reinforcement Learning (CHDRL) framework that can learn a policy by integrating the advantages of heterogeneous agents.
arxiv