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Category relevance attenuates overshadowing in human predictive learning
No full textIn situations in which multiple predictors anticipate the presence or absence of an outcome, cues compete to anticipate the outcome, resulting in a loss of associative strength compared to control conditions without additional cues. Critically, there are multiple factors modulating the magnitude and direction of such competition, although in some scenarios the effect of these factors remains unexplored. We sought to assess whether the relative salience of the elements in a compound of cues modulates the magnitude of the overshadowing effect in human predictive learning. Two separable categories (i.e., colors and symbols) were used in a predictive learning task. In Experiment 1, different groups of participants were granted with different time of exposure to a compound of cues belonging to different categories (color and symbol) to evaluate potential differences in the magnitude of overshadowing. Furthermore, we used post-test questionnaires to assess whether participants used either only one or both categories during training, and assessed if this impacted the magnitude of overshadowing. In general, overshadowing was not modulated by the time of exposition, except in the case of very short time of exposition with prominent learning about the most salient category. In Experiment 2, the relative salience of a category was biased via prior experience either with a biconditional discrimination or attending only the relevant category (either color or symbol). Previously relevant categories were less prone to overshadowing, but not in the alternative one. Results are discussed in light of attentional and configural theories of associative learning
Data for "Rejection-free quantum Monte Carlo in continuous time from transition path sampling"
No full textContains the data used in all figures throughout the publication "Rejection-free quantum Monte Carlo in continuous time from transition path sampling" by Luke Causer, Konstantinos Sfairopoulos, Jamie F. Mair, and Juan P. Garrahan
Responsible Research and Innovation (RRI) Prompts and Practice Cards
No full textThese cards highlight 4 key activities and 16 different aspects of Responsible Innovation (RI) for researchers and innovators to consider. You can use the cards to reflect on a project and plan RI activities. You can use the cards to facilitate a discussion about priorities for RI in a research or application area. Or do something completely different…
Please note that there is now an updated version of these cards available: http://doi.org/10.17639/nott.735
Teacher education for inclusive education in the Global South bibliography
No full textThis dataset comprises 95 journal articles published 2012 - 202
Time resolved growth of (N)-polycyclic aromatic hydrocarbons in engine deposits uncovered with OrbiSIMS depth profiling
No full textCarbonaceous deposits are ubiquitous, being formed on surfaces in engines, fuel systems and on catalysts operating at high temperatures for hydrocarbon transformations. In internal combustion engines, their formation negatively affects worldwide vehicle emissions and fuel economy, leading to premature deaths and environmental damage. Deposit composition and formation pathways are poorly understood due to their insolubility and the intrinsic complexity of their layered carbonaceous matrix. Here, we apply the in-situ high resolution analysis capabilities of 3D Orbitrap secondary ion mass spectrometry (3D OrbiSIMS) depth profiling on 16 lab grown deposits and evidence common molecular distributions in deposit depth and in positions relative to the combustion chamber. We observe the products of the growth of both planar and curved polycyclic aromatic hydrocarbons to form small fullerenes over time in the engine and propose possible formation pathways which explain the molecular distributions observed. These include alkyl scission, cyclisation of aliphatic side chains and hydrogen abstraction C2H2 addition to form larger aromatic structures. We apply this pathway to previously unidentified nitrogen containing structures in deposits including quinolines and carbazoles. For the first time, 3D OrbiSIMS results were compared and validated with data from atmospheric pressure matrix assisted laser desorption ionization MS. The comprehensive characterization provided will help the development of a new generation of chemical additives to reduce deposits, and thus improve vehicle emissions and global air quality
Inference for a spatio-temporal model with partial spatial data: African horse sickness virus in Morocco example
No full textAn example randomly generated region-level spatial distribution and code associated with Emma L. Fairbanks, Matthew Baylis, Janet M. Daly, Michael J. Tildesley. Inference for a spatio-temporal model with partial spatial data: African horse sickness virus in Morocco,
Epidemics, 2022, 100566, ISSN 1755-4365, https://doi.org/10.1016/j.epidem.2022.100566.
(https://www.sciencedirect.com/science/article/pii/S1755436522000202)
Abstract: African horse sickness virus (AHSV) is a vector-borne virus spread by midges (Culicoides spp.). The virus causes African horse sickness (AHS) disease in some species of equid. AHS is endemic in parts of Africa, previously emerged in Europe and in 2020 caused outbreaks for the first time in parts of Eastern Asia. Here we analyse a unique historic dataset from the 1989-1991 emergence of AHS in Morocco in a naïve population of equids. Sequential Monte Carlo and Markov chain Monte Carlo techniques are used to estimate parameters for a spatial–temporal model using a transmission kernel. These parameters allow us to observe how the transmissiblity of AHSV changes according to the distance between premises. We observe how the spatial specificity of the dataset giving the locations of premises on which any infected equids were reported affects parameter estimates. Estimations of transmissiblity were similar at the scales of village (location to the nearest 1.3 km) and region (median area 99 km2), but not province (median area 3000 km2). This data-driven result could help inform decisions by policy makers on collecting data during future equine disease outbreaks, as well as policies for AHS control.
Keywords: Vector-borne disease; Spatio-temporal model; Bayesian inferenc
Mushroom-shaped structures formed in Acinetobacter baumannii biofilms grown in a roller bioreactor are associated with quorum sensing dependent Csu-pilus assembly
No full textStudy on the influence of quorum sensing regulation on biofilm maturation in Acinetobacter baumanni
Golden ratio - planetary orbits Python source code
No full textPython code that simulates the planetary orbits showing the Golden Ratio nature of their conjunctions
