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Differential semantics

About: Differential semantics is a research topic. Over the lifetime, 40 publications have been published within this topic receiving 10132 citations.

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Book
01 Jan 1957
TL;DR: In this article, the authors deal with the nature and theory of meaning and present a new, objective method for its measurement which they call the semantic differential, which can be adapted to a wide variety of problems in such areas as clinical psychology, social psychology, linguistics, mass communications, esthetics, and political science.
Abstract: In this pioneering study, the authors deal with the nature and theory of meaning and present a new, objective method for its measurement which they call the semantic differential. This instrument is not a specific test, but rather a general technique of measurement that can be adapted to a wide variety of problems in such areas as clinical psychology, social psychology, linguistics, mass communications, esthetics, and political science. The core of the book is the authors' description, application, and evaluation of this important tool and its far-reaching implications for empirical research.

9,476 citations

Proceedings ArticleDOI
11 Jul 2010
TL;DR: A reduction method is constructed which generates (typically) far smaller systems of differential equations than the concrete/canonical one, and it is shown that the abstract/reduced differential system has solutions which are linear combinations of the canonical ones.
Abstract: Rule-based approaches (as in our own Kappa, or the BNG language, or many other propositions allowing the consideration of "reaction classes'') offer new and more powerful ways to capture the combinatorial interactions that are typical of molecular biological systems. They afford relatively compact and faithful descriptions of cellular interaction networks despite the combination of two broad types of interaction: the formation of complexes (a biological term for the ubiquitous non-covalent binding of bio-molecules), and the chemical modifications of macromolecules (aka post-translational modifications). However, all is not perfect. This same combinatorial explosion that pervades biological systems also seems to prevent the simulation of molecular networks using systems of differential equations. In all but the simplest cases the generation (and even more the integration) of the explicit system of differential equations which is canonically associated to a rule set is unfeasible. So there seems to be a price to pay for this increase in clarity and precision of the description, namely that one can only execute such rule-based systems using their stochastic semantics as continuous time Markov chains, which means a slower if more accurate simulation. In this paper, we take a fresh look at this question, and, using techniques from the abstract interpretation framework, we construct a reduction method which generates (typically) far smaller systems of differential equations than the concrete/canonical one. We show that the abstract/reduced differential system has solutions which are linear combinations of the canonical ones. Importantly, our method: 1) does not require the concrete system to be explicitly computed, so it is intensional, 2) nor does it rely on the choice of a specific set of rate constants for the system to be reduced, so it is symbolic, and 3) achieves good compression when tested on rule-based models of significant size, so it is also realistic.

98 citations

Journal ArticleDOI
TL;DR: The application of differential semantics to structure the semantic space of casual shoes showed that comfort and quality were independently perceived by consumers, but whereas comfort was clearly identified by users, quality was not.

79 citations

Journal ArticleDOI
TL;DR: The aim of the present work is to determine, by means of a case study, how different ways of representing a product can affect the ability to transmit the product's symbolic value to the observer.

78 citations

Book ChapterDOI
27 Sep 2017
TL;DR: The strong (uniform computability) Turing completeness of chemical reaction networks over a finite set of molecular species under the differential semantics is derived, solving a long standing open problem.
Abstract: When seeking to understand how computation is carried out in the cell to maintain itself in its environment, process signals and make decisions, the continuous nature of protein interaction processes forces us to consider also analog computation models and mixed analog-digital computation programs. However, recent results in the theory of analog computability and complexity establish fundamental links with classical programming. In this paper, we derive from these results the strong (uniform computability) Turing completeness of chemical reaction networks over a finite set of molecular species under the differential semantics , solving a long standing open problem. Furthermore we derive from the proof a compiler of mathematical functions into elementary chemical reactions. We illustrate the reaction code generated by our compiler on trigonometric functions, and on various sigmoid functions which can serve as markers of presence or absence for implementing program control instructions in the cell and imperative programs. Then we start comparing our compiler-generated circuits to the natural circuit of the MAPK signaling network, which plays the role of an analog-digital converter in the cell with a Hill type sigmoid input/output functions.

63 citations

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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20213
20181
20172
20161
20155
20141