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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Theoretical medicine and bioethics 12 (1991), S. 69-79 
    ISSN: 1573-1200
    Keywords: behaviorism ; coma ; consciousness ; locked-in syndrome ; other minds problem
    Source: Springer Online Journal Archives 1860-2000
    Topics: Medicine , Philosophy
    Notes: Abstract In this paper, the problem of correct ascriptions of consciousness to patients in neurological intensive care medicine is explored as a special case of the general philosophical ‘other minds problem’. It is argued that although clinical ascriptions of consciousness and coma are mostly based on behavioral evidence, a behaviorist epistemology of other minds is not likely to succeed. To illustrate this, the so-called ‘total locked-in syndrome’, in which preserved consciousness is combined with a total loss of motor abilities due to a lower ventral brain stem lesion, is presented as a touchstone for behaviorism. It is argued that this example of consciousness without behavioral expression does not disprove behaviorism specifically, but rather illustrates the need for a non-verificationist theory of other minds. It is further argued that a folk version of such a theory already underlies our factual ascriptions of consciousness in clinical contexts. Finally, a non-behaviorist theory of other minds for patients with total locked-in syndrome is outlined.
    Type of Medium: Electronic Resource
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  • 2
    Publication Date: 2020-03-11
    Language: German
    Type: doctoralthesis , doc-type:doctoralThesis
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  • 3
    Publication Date: 2022-11-28
    Description: Markov State Models (MSM) sind der Goldstandard zur Modellierung biomolekularer Dynamik, da sie die Identifizierung und Analyse metastabiler Zustände ermöglichen. Die robuste Perron-Cluster-Cluster-Analyse (PCCA+) ist ein verbreiteter Spectral-Clustering-Algorithmus, der für das Clustering hochdimensionaler MSM verwendet wird. Da die PCCA+ auf reversible Prozesse beschränkt ist, wird sie zur Generalisierten PCCA+ (G-PCCA) verallgemeinert, die geeignet ist, nichtreversible Prozesse aufzuklären. Bernhard Reuter untersucht hier mittels G-PCCA die nichtthermischen Auswirkungen von Mikrowellen auf die Proteindynamik. Dazu führt er molekulardynamische Nichtgleichgewichtssimulationen des Amyloid-β-(1–40)-Peptids durch und modelliert diese.
    Language: German
    Type: book , doc-type:book
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  • 4
    Publication Date: 2023-11-03
    Description: Markov state models (MSMs) have received an unabated increase in popularity in recent years, as they are very well suited for the identification and analysis of metastable states and related kinetics. However, the state-of-the-art Markov state modeling methods and tools enforce the fulfillment of a detailed balance condition, restricting their applicability to equilibrium MSMs. To date, they are unsuitable to deal with general dominant data structures including cyclic processes, which are essentially associated with nonequilibrium systems. To overcome this limitation, we developed a generalization of the common robust Perron Cluster Cluster Analysis (PCCA+) method, termed generalized PCCA (G-PCCA). This method handles equilibrium and nonequilibrium simulation data, utilizing Schur vectors instead of eigenvectors. G-PCCA is not limited to the detection of metastable states but enables the identification of dominant structures in a general sense, unraveling cyclic processes. This is exemplified by application of G-PCCA on nonequilibrium molecular dynamics data of the Amyloid β (1−40) peptide, periodically driven by an oscillating electric field.
    Language: English
    Type: article , doc-type:article
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  • 5
    Publication Date: 2023-11-03
    Description: Markov state models are to date the gold standard for modeling molecular kinetics since they enable the identification and analysis of metastable states and related kinetics in a very instructive manner. The state-of-the-art Markov state modeling methods and tools are very well developed for the modeling of reversible processes in closed equilibrium systems. On the contrary, they are largely not well suited to deal with nonreversible or even nonautonomous processes of nonequilibrium systems. Thus, we generalized the common Robust Perron Cluster Cluster Analysis (PCCA+) method to enable straightforward modeling of nonequilibrium systems as well. The resulting Generalized PCCA (G-PCCA) method readily handles equilibrium as well as nonequilibrium data by utilizing real Schur vectors instead of eigenvectors. This is implemented in the G-PCCA algorithm that enables the semiautomatic coarse graining of molecular kinetics. G-PCCA is not limited to the detection of metastable states but also enables the identification and modeling of cyclic processes. This is demonstrated by three typical examples of nonreversible systems.
    Language: English
    Type: article , doc-type:article
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