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Dependence of Equilibrium Propagation Training Success on Network Architecture
No full textThe rapid rise of artificial intelligence has led to an unsustainable growth in energy consumption. This has motivated progress in neuromorphic computing and physics-based training of learning machines as alternatives to digital neural networks. Many theoretical studies focus on simple architectures like all-to-all or densely connected layered networks. However, these may be challenging to realize experimentally, e.g. due to connectivity constraints. In this work, we investigate the performance of the widespread physics-based training method of equilibrium propagation for more realistic architectural choices, specifically, locally connected lattices. We train an XY model and explore the influence of architecture on various benchmark tasks, tracking the evolution of spatially distributed responses and couplings during training. Our results show that sparse networks with only local connections can achieve performance comparable to dense networks. Our findings provide guidelines for further scaling up architectures based on equilibrium propagation in realistic settings
A Methodology for Deciphering the Transmembrane Resistance Variability of Supported Lipid Bilayers
No full textReversible switching through irradiation of capacitors and organic transistors employing dielectrics blended with non-ionic molecular photoswitches
No full textNachhaltige Ammoniak‐Elektrosynthese Gekoppelt mit Glycerin‐Valorisierung Mittels Eines Adaptiven Dreikomponenten‐Katalysators
No full textRisk factors associated with gastrointestinal parasite infections in urban long-tailed macaques (Macaca fascicularis): The role of network centrality and synanthropy (advance online)
No full textEvaluating risk factors of infections in primates is essential to understand infection dynamics and predict epizootic threats at the human-primate interfaces. In Bali, Indonesia, long-tailed macaques (Macaca fascicularis) frequently interact with humans in touristic areas, living sometimes in high demographic density, which may increase exposure to or alter transmission dynamics of gastrointestinal (GI) parasites. This study investigates risk factors of infection in macaques, specifically how their social network centrality, individual traits, and human-macaque interactions influence GI parasite infections in synanthropic macaques. Over two years (2022–2023), we opportunistically collected 142 fecal samples from 53 macaques in the Ubud Monkey Forest, and we analyzed GI parasites using direct smear and flotation techniques. We recorded behavioral data, including macaque grooming interactions and human-macaque contacts, through focal sampling and integrated the former into social network analysis. Generalized linear mixed models assessed the effects of social centrality, synanthropic nature, and host characteristics of the macaques on their infection risk. We found GI parasites in 75% of the samples and we identified six GI parasite taxa: Entamoeba spp., Iodamoeba spp., Balantioides-like ciliate, Strongyloides spp., Trichuris spp., and Strongylida (fam. gen. indet). Individuals central in the grooming network had fewer parasite species, suggesting a potential social buffering effect. Human-macaque contacts positively influenced the presence of Iodamoeba spp. and showed a positive trend in influencing GI parasite richness. These findings highlight that infection dynamics in primates result from complex interactions between social, anthropogenic, and biological factors
