Can Neuroscientists Test a New Physicalist Mind/Body View: DiCoToP (Diachronic Conjunctive Token Physicalism)?

Given that disparate mind/body views have interfered with interdisciplinary research in psychoanalysis and neuroscience, the mind/body problem itself is explored here. Adding a philosophy of mind framework, problems for both dualists and physicalists are presented, along with essential concepts including: independent mental causation, emergence, and multiple realization. To address some of these issues in a new light, this article advances an original mind/body account—Diachronic Conjunctive Token Physicalism (DiCoToP). Next, puzzles DiCoTop reveals, psychoanalytic problems it solves, and some empirical evidence accrued for views consistent with DiCoToP are presented. In closing, this piece challenges/appeals for neuroscience research to gain evidence for (or against) the DiCoToP view.

Dynamic Modeling of the Gas Discharge of a Mine in the Karaganda Coal Basin Under High Uncertainty Using a Multiple Realization Approach

The current work is intended to show the application of a multiple realization approach to produce a strategic development plan for one of the mines in Karaganda coal basin. The presented workflow suggests using a comprehensive reservoir simulator for a history matching process of a coal pillars on a detailed 3D grid and application of sensitivity and uncertainty analyses to produce probabilistic forecast. The suggested workflow significantly differs from the standard approaches previously implemented in the Karaganda Basin. First, a dynamic model has been constructed based on integrated algorithm of petrophysical interpretation and full cycle of geological modeling. Secondly, for the first time in the region, dynamic modeling has been performed via a combination of history matching to the observed degassing data and multiple realization uncertainty analysis. Thirdly, the described model parameters with defined range of uncertainty has been incorporated into the forecasting of degassing efficiency in the mine using different well completion technology. From the hydrodynamic modeling point of view, the coal seam gas (CSG) reservoir is presented as a dual porosity medium: a coal matrix containing adsorbed gas and a network of natural fractures (cleats), which are initially saturated with water. This approach has allowed the proper description of dynamic processes occurring in CSG reservoirs. The gas production from a coal is subject to gas diffusion in coal micropores, the degree of fracture intensity and fracture permeability. By tuning these parameters within reasonable ranges, we have been able to history match our model to the observed data. Moreover, application of an uncertainty analysis has resulted in a range of output parameters (P10, P50, and P90) that were historically observed. Performed full cycle of CSG dynamic modelling including history matching, sensitivity, and uncertainty analyses has been performed to create a robust model with the predictive power. Based on the obtained results, different optimization technologies have been simulated for fast and efficient degassing through a multiple realization probabilistic approach. The coal reservoir presented in this work is characterized by very low effective permeability and final degassing efficiency depends on well-reservoir contact surface. The decrease of the well spacing led to a proportional increase of gas recovery which is very similar to unconventional reservoirs. Therefore, vertical and horizontal wells with hydraulic fractures have been concluded the most efficient way to develop coal seams with low effective permeability in a secondary medium.

Saving Faculty Psychology

The future of faculty psychology depends in no small part on the productive collaboration between neuroscience and psychology. The argument from multiple realization has posed a significant philosophical stumbling block to this quest in the past. Multiple realization should not be taken as an empirical given—establishing that a kind is multiply realizable takes a good deal of work, as Shapiro has been at pains to show; and even when the existence of an MR kind can be verified, the details of its implementation do not suddenly become irrelevant. Structure and function are two sides of the same coin. Thus the multiple realization argument provides no basis for neglecting the discoveries of neuroscience. Faculty psychology’s strength lies precisely in its willingness to work with neuroscience.

Sawyer’s Theory of Social Causation: A Critique

This article critiques R. Keith Sawyer’s theory of social causation from his 2005 book Social Emergence. It considers his use of analogy with the philosophy of mind, his account of individual agency, the legacy of Emile Durkheim, the concepts of supervenience, multiple realization, and wild disjunction, and the role of history in social causation. Sawyer’s theory is also evaluated in terms of two examples of empirical research: his own micro-sociological studies into group creativity; and Margaret Archer’s macro-sociology of education systems.

Hazard-driven realization views for Component Fault Trees

Traditionally, the preferred means of documentation used by safety engineers have been sheets- and text-based solutions. However, in the last decades, the introduction of model-driven engineering in conjunction with Component-Based Design has been influencing the way safety engineers perform their tasks; especially in the area of fault analysis, model-driven approaches have been developed aimed at coupling fault trees with architecture models. Doing this fosters communication between engineers, may reduce design effort, and makes artifacts easier to maintain and reuse. In this paper, we want to move forward in this direction and take another step in the modeling of Component Fault Trees in combination with the modeling of the architecture design. We propose a hazard-centric approach for the definition of multiple realization views for fault analysis using Component Fault Trees. The approach is composed of a modeling method and a tool solution. We illustrate our approach with a real-life example from the automotive industry.