980 research outputs found
Supraorganized Collagen Enhances Schwann Cell Reactivity And Organization In Vitro.
We investigated the reactivity and expression of basal lamina collagen by Schwann cells (SCs) cultivated on a supraorganized bovine-derived collagen substrate. SC cultures were obtained from sciatic nerves of neonatal Sprague-Dawley rats and seeded on 24-well culture plates containing collagen substrate. The homogeneity of the cultures was evaluated with an SC marker antibody (anti-S-100). After 1 week, the cultures were fixed and processed for immunocytochemistry by using antibodies against type IV collagen, S-100 and p75NTR (pan neurotrophin receptor) and for scanning electron microscopy (SEM). Positive labeling with antibodies to the cited molecules was observed, indicating that the collagen substrate stimulates SC alignment and adhesion (collagen IV labeling - organized collagen substrate: 706.33 ± 370.86, non-organized collagen substrate: 744.00 ± 262.09; S-100 labeling - organized collagen: 3809.00 ± 120.28, non-organized collagen: 3026.00 ± 144.63, P < 0.05) and reactivity (p75NTR labeling - organized collagen: 2156.33 ± 561.78, non-organized collagen: 1424.00 ± 405.90, P < 0.05; means ± standard error of the mean in absorbance units). Cell alignment and adhesion to the substrate were confirmed by SEM analysis. The present results indicate that the collagen substrate with an aligned suprastructure, as seen by polarized light microscopy, provides an adequate scaffold for SCs, which in turn may increase the efficiency of the nerve regenerative process after in vivo repair.44682-
Cognition as Embodied Morphological Computation
Cognitive science is considered to be the study of mind (consciousness and thought) and intelligence in humans. Under such definition variety of unsolved/unsolvable problems appear. This article argues for a broad understanding of cognition based on empirical results from i.a. natural sciences, self-organization, artificial intelligence and artificial life, network science and neuroscience, that apart from the high level mental activities in humans, includes sub-symbolic and sub-conscious processes, such as emotions, recognizes cognition in other living beings as well as extended and distributed/social cognition. The new idea of cognition as complex multiscale phenomenon evolved in living organisms based on bodily structures that process information, linking cognitivists and EEEE (embodied, embedded, enactive, extended) cognition approaches with the idea of morphological computation (info-computational self-organisation) in cognizing agents, emerging in evolution through interactions of a (living/cognizing) agent with the environment
Towards Autopoietic Computing
A key challenge in modern computing is to develop systems that address
complex, dynamic problems in a scalable and efficient way, because the
increasing complexity of software makes designing and maintaining efficient and
flexible systems increasingly difficult. Biological systems are thought to
possess robust, scalable processing paradigms that can automatically manage
complex, dynamic problem spaces, possessing several properties that may be
useful in computer systems. The biological properties of self-organisation,
self-replication, self-management, and scalability are addressed in an
interesting way by autopoiesis, a descriptive theory of the cell founded on the
concept of a system's circular organisation to define its boundary with its
environment. In this paper, therefore, we review the main concepts of
autopoiesis and then discuss how they could be related to fundamental concepts
and theories of computation. The paper is conceptual in nature and the emphasis
is on the review of other people's work in this area as part of a longer-term
strategy to develop a formal theory of autopoietic computing.Comment: 10 Pages, 3 figure
"Meaning" as a sociological concept: A review of the modeling, mapping, and simulation of the communication of knowledge and meaning
The development of discursive knowledge presumes the communication of meaning
as analytically different from the communication of information. Knowledge can
then be considered as a meaning which makes a difference. Whereas the
communication of information is studied in the information sciences and
scientometrics, the communication of meaning has been central to Luhmann's
attempts to make the theory of autopoiesis relevant for sociology. Analytical
techniques such as semantic maps and the simulation of anticipatory systems
enable us to operationalize the distinctions which Luhmann proposed as relevant
to the elaboration of Husserl's "horizons of meaning" in empirical research:
interactions among communications, the organization of meaning in
instantiations, and the self-organization of interhuman communication in terms
of symbolically generalized media such as truth, love, and power. Horizons of
meaning, however, remain uncertain orders of expectations, and one should
caution against reification from the meta-biological perspective of systems
theory
Modeling relationships between calving traits: a comparison between standard and recursive mixed models
<p>Abstract</p> <p>Background</p> <p>The use of structural equation models for the analysis of recursive and simultaneous relationships between phenotypes has become more popular recently. The aim of this paper is to illustrate how these models can be applied in animal breeding to achieve parameterizations of different levels of complexity and, more specifically, to model phenotypic recursion between three calving traits: gestation length (GL), calving difficulty (CD) and stillbirth (SB). All recursive models considered here postulate heterogeneous recursive relationships between GL and liabilities to CD and SB, and between liability to CD and liability to SB, depending on categories of GL phenotype.</p> <p>Methods</p> <p>Four models were compared in terms of goodness of fit and predictive ability: 1) standard mixed model (SMM), a model with unstructured (co)variance matrices; 2) recursive mixed model 1 (RMM1), assuming that residual correlations are due to the recursive relationships between phenotypes; 3) RMM2, assuming that correlations between residuals and contemporary groups are due to recursive relationships between phenotypes; and 4) RMM3, postulating that the correlations between genetic effects, contemporary groups and residuals are due to recursive relationships between phenotypes.</p> <p>Results</p> <p>For all the RMM considered, the estimates of the structural coefficients were similar. Results revealed a nonlinear relationship between GL and the liabilities both to CD and to SB, and a linear relationship between the liabilities to CD and SB.</p> <p>Differences in terms of goodness of fit and predictive ability of the models considered were negligible, suggesting that RMM3 is plausible.</p> <p>Conclusions</p> <p>The applications examined in this study suggest the plausibility of a nonlinear recursive effect from GL onto CD and SB. Also, the fact that the most restrictive model RMM3, which assumes that the only cause of correlation is phenotypic recursion, performs as well as the others indicates that the phenotypic recursion may be an important cause of the observed patterns of genetic and environmental correlations.</p
“Structuration” by intellectual organization: the configuration of knowledge in relations among structural components in networks of science
Using aggregated journal–journal citation networks, the measurement of the knowledge base in empirical systems is factor-analyzed in two cases of interdisciplinary developments during the period 1995–2005: (i) the development of nanotechnology in the natural sciences and (ii) the development of communication studies as an interdiscipline between social psychology and political science. The results are compared with a case of stable development: the citation networks of core journals in chemistry. These citation networks are intellectually organized by networks of expectations in the knowledge base at the specialty (that is, above-journal) level. The “structuration” of structural components (over time) can be measured as configurational information. The latter is compared with the Shannon-type information generated in the interactions among structural components: the difference between these two measures provides us with a measure for the redundancy generated by the specification of a model in the knowledge base of the system. This knowledge base incurs (against the entropy law) to variable extents on the knowledge infrastructures provided by the observable networks of relations
Recent developments and future trends of industrial agents
The agent technology provides a new way to design and engineer control solutions based on the decentralization of control over distributed structures, addressing the current requirements for modern control systems in industrial domains. This paper presents the current situation of the development and deployment of agent technology, discussing the initiatives and the current trends faced for a wider dissemination and industrial adoption, based on the work that is being carried out by the IEEE IES Technical Committee on Industrial Agents
The Non-linear Dynamics of Meaning-Processing in Social Systems
Social order cannot be considered as a stable phenomenon because it contains
an order of reproduced expectations. When the expectations operate upon one
another, they generate a non-linear dynamics that processes meaning. Specific
meaning can be stabilized, for example, in social institutions, but all meaning
arises from a horizon of possible meanings. Using Luhmann's (1984) social
systems theory and Rosen's (1985) theory of anticipatory systems, I submit
equations for modeling the processing of meaning in inter-human communication.
First, a self-referential system can use a model of itself for the
anticipation. Under the condition of functional differentiation, the social
system can be expected to entertain a set of models; each model can also
contain a model of the other models. Two anticipatory mechanisms are then
possible: one transversal between the models, and a longitudinal one providing
the modeled systems with meaning from the perspective of hindsight. A system
containing two anticipatory mechanisms can become hyper-incursive. Without
making decisions, however, a hyper-incursive system would be overloaded with
uncertainty. Under this pressure, informed decisions tend to replace the
"natural preferences" of agents and an order of cultural expectations can
increasingly be shaped
Pareto Autonomous Local Search
This paper presents a study for the dynamic selection of operators in a local search process. The main purpose is to propose a generic autonomous local search method which manages operator selection from a set of available operators, built on neighborhood relations and neighbor selection functions, using the concept of Pareto dominance with respect to quality and diversity. The latter is measured using two different metrics. This control method is implemented using the Comet language in order to be easily introduced in various constraint local search algorithms. Focusing on permutation-based problems, experimental results are provided for the QAP and ATSP to assess the method’s effectiveness
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