21,979 research outputs found
Coupling of cytoplasm and adhesion dynamics determines cell polarization and locomotion
Observations of single epidermal cells on flat adhesive substrates have
revealed two distinct morphological and functional states, namely a
non-migrating symmetric unpolarized state and a migrating asymmetric polarized
state. These states are characterized by different spatial distributions and
dynamics of important biochemical cell components: F-actin and myosin-II form
the contractile part of the cytoskeleton, and integrin receptors in the plasma
membrane connect F-actin filaments to the substratum. In this way, focal
adhesion complexes are assembled, which determine cytoskeletal force
transduction and subsequent cell locomotion. So far, physical models have
reduced this phenomenon either to gradients in regulatory control molecules or
to different mechanics of the actin filament system in different regions of the
cell.
Here we offer an alternative and self-organizational model incorporating
polymerization, pushing and sliding of filaments, as well as formation of
adhesion sites and their force dependent kinetics. All these phenomena can be
combined into a non-linearly coupled system of hyperbolic, parabolic and
elliptic differential equations. Aim of this article is to show how relatively
simple relations for the small-scale mechanics and kinetics of participating
molecules may reproduce the emergent behavior of polarization and migration on
the large-scale cell level.Comment: v2 (updates from proof): add TOC, clarify Fig. 4, fix several typo
The Watchdog Task: Concurrent error detection using assertions
The Watchdog Task, a software abstraction of the Watchdog-processor, is shown to be a powerful error detection tool with a great deal of flexibility and the advantages of watchdog techniques. A Watchdog Task system in Ada is presented; issues of recovery, latency, efficiency (communication) and preprocessing are discussed. Different applications, one of which is error detection on a single processor, are examined
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Firm technological responses to regulatory changes: A longitudinal study in the Le Mans Prototype racing
Despite the critical role of regulations on competition and innovation, little is known about firm responses and related effects on performance under regulatory contingencies that are permissive or restrictive. By longitudinally investigating hybrid cars competing in the Le Mans Prototype racing (LMP1), we counter-intuitively suggest that permissive regulations increase technological uncertainty and thus decrease the firms’ likelihood of shifting their technological trajectory, while restrictive regulations lead to the opposite outcome. Further, we suggest that permissive regulations favour firms that innovate their products by sequentially upgrading core and peripheral subsystems, while restrictive regulations—in the long term— favour firms upgrading them simultaneously. Implications for theory and practice are discussed
On merging the fields of neural networks and adaptive data structures to yield new pattern recognition methodologies
The aim of this talk is to explain a pioneering exploratory research endeavour that attempts to merge two completely different fields in Computer Science so as to yield very fascinating results. These are the well-established fields of Neural Networks (NNs) and Adaptive Data Structures (ADS) respectively. The field of NNs deals with the training and learning capabilities of a large number of neurons, each possessing minimal computational properties. On the other hand, the field of ADS concerns designing, implementing and analyzing data structures which adaptively change with time so as to optimize some access criteria. In this talk, we shall demonstrate how these fields can be merged, so that the neural elements are themselves linked together using a data structure. This structure can be a singly-linked or doubly-linked list, or even a Binary Search Tree (BST). While the results themselves are quite generic, in particular, we shall, as a prima facie case, present the results in which a Self-Organizing Map (SOM) with an underlying BST structure can be adaptively re-structured using conditional rotations. These rotations on the nodes of the tree are local and are performed in constant time, guaranteeing a decrease in the Weighted Path Length of the entire tree. As a result, the algorithm, referred to as the Tree-based Topology-Oriented SOM with Conditional Rotations (TTO-CONROT), converges in such a manner that the neurons are ultimately placed in the input space so as to represent its stochastic distribution. Besides, the neighborhood properties of the neurons suit the best BST that represents the data
Trajectory generation for road vehicle obstacle avoidance using convex optimization
This paper presents a method for trajectory generation using convex optimization to find a feasible, obstacle-free path for a road vehicle. Consideration of vehicle rotation is shown to be necessary if the trajectory is to avoid obstacles specified in a fixed Earth axis system. The paper establishes that, despite the presence of significant non-linearities, it is possible to articulate the obstacle avoidance problem in a tractable convex form using multiple optimization passes. Finally, it is shown by simulation that an optimal trajectory that accounts for the vehicle’s changing velocity throughout the manoeuvre is superior to a previous analytical method that assumes constant speed
In silico case studies of compliant robots: AMARSI deliverable 3.3
In the deliverable 3.2 we presented how the morphological computing ap-
proach can significantly facilitate the control strategy in several scenarios,
e.g. quadruped locomotion, bipedal locomotion and reaching. In particular,
the Kitty experimental platform is an example of the use of morphological
computation to allow quadruped locomotion. In this deliverable we continue
with the simulation studies on the application of the different morphological
computation strategies to control a robotic system
Collective motion of cells: from experiments to models
Swarming or collective motion of living entities is one of the most common
and spectacular manifestations of living systems having been extensively
studied in recent years. A number of general principles have been established.
The interactions at the level of cells are quite different from those among
individual animals therefore the study of collective motion of cells is likely
to reveal some specific important features which are overviewed in this paper.
In addition to presenting the most appealing results from the quickly growing
related literature we also deliver a critical discussion of the emerging
picture and summarize our present understanding of collective motion at the
cellular level. Collective motion of cells plays an essential role in a number
of experimental and real-life situations. In most cases the coordinated motion
is a helpful aspect of the given phenomenon and results in making a related
process more efficient (e.g., embryogenesis or wound healing), while in the
case of tumor cell invasion it appears to speed up the progression of the
disease. In these mechanisms cells both have to be motile and adhere to one
another, the adherence feature being the most specific to this sort of
collective behavior. One of the central aims of this review is both presenting
the related experimental observations and treating them in the light of a few
basic computational models so as to make an interpretation of the phenomena at
a quantitative level as well.Comment: 24 pages, 25 figures, 13 reference video link
Urban and extra-urban hybrid vehicles: a technological review
Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use
(implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used
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