7 resultados para MAP Kinase Signaling System

em Cochin University of Science


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The recent developments in neurobiology have rendered new prominence and potential to study about the structure and function of brain and related disorders. Human behaviour is the net result of neural control of the communication between brain cells. Neurotransmitters are chemicals that are used to relay, amplify and modulate electrical signals between neurons and/or another cell. It mediates rapid intercellular communication through the nervous system by interacting with cell surface receptors. These receptors often trigger second messenger signaling pathways that regulate the activity of ion channels. The functional balance of different neurotransmitters such as Acetylcholine (Ach), Dopamine (DA), Serotonin (5-HT), Norepinephrine (NE), Epinephrine (EPI), Glutamate and Gamma amino butyric acid (GABA) regulates the growth, division and other vital functions of a normal cell / organism (Sudha, 1998). Any change in neurotransmitters' functional balance will result in the failure of cell function and may lead to the occurrence of diseases. Abnormalities in the production or functioning of neurotransmitters have been implicated in a number of neurological disorders like Schizophrenia, Alzheimer's, Epilepsy, Depression and Parkinson's disease. Changes in central and peripheral neuronal signaling system is also noted in diabetes, cancer, cell proliferation, alcoholism and aging. Elucidation of neurotransmitters receptor interaction pathways and gene expression regulation by second messengers and transcriptional factors in health and disease conditions can lead to new small molecules for development of therapeutic agents to improve neurological disease conditions. Increased awareness of the global effects of neurological disorders should help health care planners and the neurological community set appropriate priorities in research, prevention, and management of these diseases.

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We present the analytical investigations on a logistic map with a discontinuity at the centre. An explanation for the bifurcation phenomenon in discontinuous systems is presented. We establish that whenever the elements of an n-cycle (n > 1) approach the discontinuities of the nth iterate of the map, a bifurcation other than the usual period-doubling one takes place. The periods of the cycles decrease in an arithmetic progression, as the control parameter is varied. The system also shows the presence of multiple attractors. Our results are verified by numerical experiments as well.

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We have studied the bifurcation structure of the logistic map with a time dependant control parameter. By introducing a specific nonlinear variation for the parameter, we show that the bifurcation structure is modified qualitatively as well as quantitatively from the first bifurcation onwards. We have also computed the two Lyapunov exponents of the system and find that the modulated logistic map is less chaotic compared to the logistic map.

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This is a sequel to our earlier work on the modulated logistic map. Here, we first show that the map comes under the universality class of Feigenbaum. We then give evidence for the fact that our model can generate strange attractors in the unit square for an uncountable number of parameter values in the range μ∞<μ<1. Numerical plots of the attractor for several values of μ are given and the self-similar structure is explicity shown in one case. The fractal and information dimensions of the attractors for many values of μ are shown to be greater than one and the variation in their structure is analysed using the two Lyapunov exponents of the system. Our results suggest that the map can be considered as an analogue of the logistic map in two dimensions and may be useful in describing certain higher dimensional chaotic phenomena.

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We study the period-doubling bifurcations to chaos in a logistic map with a nonlinearly modulated parameter and show that the bifurcation structure is modified significantly. Using the renormalisation method due to Derrida et al. we establish the universal behaviour of the system at the onset of chaos.

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Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

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A GIS has been designed with limited Functionalities; but with a novel approach in Aits design. The spatial data model adopted in the design of KBGIS is the unlinked vector model. Each map entity is encoded separately in vector fonn, without referencing any of its neighbouring entities. Spatial relations, in other words, are not encoded. This approach is adequate for routine analysis of geographic data represented on a planar map, and their display (Pages 105-106). Even though spatial relations are not encoded explicitly, they can be extracted through the specially designed queries. This work was undertaken as an experiment to study the feasibility of developing a GIS using a knowledge base in place of a relational database. The source of input spatial data was accurate sheet maps that were manually digitised. Each identifiable geographic primitive was represented as a distinct object, with its spatial properties and attributes defined. Composite spatial objects, made up of primitive objects, were formulated, based on production rules defining such compositions. The facts and rules were then organised into a production system, using OPS5