A semiotic cultural psychology theory analysis of the signs ‘We’, ‘Us’, ‘I’ and ‘Me’

Relevant to the emerging field of semiotic cultural psychology theory (SCPT), the present paper considers ‘We’, ‘Us’, ‘I’ and ‘Me’ as semiotic and cultural psychology phenomena. Drawing on the semiotics of Saussure, Peirce, Jakobson, and Cousins, a semiotic dynamic ‘double-dyadic’ model of the signifier and the referent is proposed. For each ‘We’, ‘Us’, ‘I’ and ‘Me’, the COVID-19 global pandemic related cases are used to analyse and illustrate the signifier-referent model. Implications are drawn from the new model for the complex systems entailed in organizing self and culture. Finally, suggestions are made for testing the model.

Predicting the Strength of Rectangular Reinforced Concrete Columns Confined with FRP Sheets

A complete reorganization about the behavior of rectangular RC columns confined with FRP sheet is very important to predict the axial compressive strength values of the strengthened rectangular RC columns. That is because the process of strengthening RC rectangular column depending on several parameters that role this type of strengthening. These parameters include the characteristics of the used fiber, the grade of concrete and the geometry of the cross section including the rectangularity aspect ratio, corner radius, and size of specimens. Besides that, using a wide scope of experimental data may affect positively to generalize a model that considers the whole parameters affect the value of the axial strength. So, in this paper a review about parameters that affect the axial compressive strength values of rectangular RC columns was conducted. After that, based on the test results regarding FRP-confined rectangular RC columns available in the literature or conducted by the author, some existing confinement models for rectangular RC columns were assessed. Further, a new model is proposed through regression analysis of the database. A new model is proposed through regression analysis of the database. The proposed model was found to be in good agreement with the test results in the database. Finally, based on the results conclusions were drawn.

A dynamical evolution of GRB-afterglows in a new generic model

In this paper, a new model using a general expression of the radiation energy and explaining the dynamics of the afterglows is proposed. It is shown that this model is suitable for the ultra-relativistic and non-relativistic phases as well as the study of radiative and adiabatic fireballs.

Uncertainty-guided learning with scaled prediction errors in the basal ganglia

To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward, and the estimate of the mean reward should be updated to a smaller extent after each observation. However, it is not known how the magnitude of the observation noise might be tracked and used to control prediction updates in the brain reward system. Here, we introduce a new model that uses simple, tractable learning rules that track the mean and standard deviation of reward, and leverages prediction errors scaled by uncertainty as the central feedback signal. We provide a normative analysis, comparing the performance of the new model with that of conventional models in a value tracking task. We find that the new model has an advantage over conventional models when tested across various levels of observation noise. Further, we propose a possible biological implementation of the model in the basal ganglia circuit. The scaled prediction error feedback signal is consistent with experimental findings concerning dopamine prediction error scaling relative to reward magnitude, and the update rules are found to be consistent with many features of striatal plasticity. Our results span across the levels of implementation, algorithm, and computation, and might have important implications for understanding the dopaminergic prediction error signal and its relation to adaptive and effective learning.