We introduce and define 'heterotic computing' as a combination of two or more computational systems such that they provide an advantage over either substrate used separately. This first requires a definition of physical computation. We take the framework in Horsman et al. (Horsman et al. 2014 Proc. R. Soc. A 470, 20140182. (doi:10.1098/rspa.2014.0182)), now known as abstract-representation theory, then outline how to compose such computational systems. We use examples to illustrate the ubiquity of heterotic computing, and to discuss the issues raised when one or more of the substrates is not a conventional silicon-based computer. We briefly outline the requirements for a proper theoretical treatment of heterotic computational systems, and the advantages such a theory would provide.
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http://dx.doi.org/10.1098/rsta.2014.0225 | DOI Listing |
Biomed Phys Eng Express
January 2025
Physics and Applied Mathematics, Pakistan Institute of Engineering and Applied Sciences, Qau, Islamabad, Islamabad, 44000, PAKISTAN.
The current study investigated the geometry, design and solid angle impacts on full energy peak efficiency (FEPE) of NaI(Tl) detectors for a line source. A line source is fabricated using 99mTc solution filled in a borosilicate glass tube of inner diameter 3 mm, tube wall thickness 2.5 mm and length 12.
View Article and Find Full Text PDFChaos
January 2025
Physics Institute, University of São Paulo, 05508-090 São Paulo, SP, Brazil.
In this work, we investigate the dynamics of a discrete-time prey-predator model considering a prey reproductive response as a function of the predation risk, with the prey population growth factor governed by two parameters. The system can evolve toward scenarios of mutual or only of predators extinction, or species coexistence. We analytically show all different types of equilibrium points depending on the ranges of growth parameters.
View Article and Find Full Text PDFChaos
January 2025
Department of Applied Mathematics, College of Applied Sciences, Kyung Hee University, Yongin 17104, Republic of Korea.
Investment in resources is essential for facilitating information dissemination in real-world contexts, and comprehending the influence of resource allocation on information dissemination is, thus, crucial for the efficacy of collaborative networks. Nonetheless, current studies on information dissemination frequently fail to clarify the complex interplay between information distribution and resources in network contexts. In this work, we establish a resource-based information dissemination model to identify the complex interplay by examining the propagation threshold and equilibriums.
View Article and Find Full Text PDFChaos
January 2025
Institute for Theoretical Physics, University of Leipzig, D-04081 Leipzig, Germany.
We consider a dynamical system undergoing a saddle-node bifurcation with an explicitly time-dependent parameter p(t). The combined dynamics can be considered a dynamical system where p is a slowly evolving parameter. Here, we investigate settings where the parameter features an overshoot.
View Article and Find Full Text PDFAnn Intern Med
January 2025
Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).
Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.
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