984 resultados para Self-defense
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Bovine viral diarrhea virus (BVDV), together with Classical swine fever virus (CSFV) and Border disease virus (BDV) of sheep, belongs to the genus Pestivirus of the Flaviviridae. BVDV is either cytopathic (cp) or noncytopathic (ncp), as defined by its effect on cultured cells. Infection of pregnant animals with the ncp biotype may lead to the birth of persistently infected calves that are immunotolerant to the infecting viral strain. In addition to evading the adaptive immune system, BVDV evades key mechanisms of innate immunity. Previously, we showed that ncp BVDV inhibits the induction of apoptosis and alpha/beta interferon (IFN-alpha/beta) synthesis by double-stranded RNA (dsRNA). Here, we report that (i) both ncp and cp BVDV block the induction by dsRNA of the Mx protein (which can also be induced in the absence of IFN signaling); (ii) neither biotype blocks the activity of IFN; and (iii) once infection is established, BVDV is largely resistant to the activity of IFN-alpha/beta but (iv) does not interfere with the establishment of an antiviral state induced by IFN-alpha/beta against unrelated viruses. The results of our study suggest that, in persistent infection, BVDV is able to evade a central element of innate immunity directed against itself without generally compromising its activity against unrelated viruses ("nonself") that may replicate in cells infected with ncp BVDV. This highly selective "self" and "nonself" model of evasion of the interferon defense system may be a key element in the success of persistent infection in addition to immunotolerance initiated by the early time point of fetal infection.
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Shipping list no.: 93-0170-P.
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"August 1988."
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May 1976.
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"July 1984"--Cover.
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Includes index.
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"April 1977."
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"February 1975."
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The present study extends previous findings by examining whether defense styles, selfobject needs, attachment styles relate to Neediness and Self-Criticism, as maladaptive personality dimensions focused, respectively, on relatedness and self-definition in an Iranian sample. Three hundred and fifty two participants completed a socio-demographic questionnaire as well as the Persian forms of the Depressive Experiences Questionnaire, Experience of Close Relationships-Revised, Defense Style Questionnaire, Beck Depression Inventory–II and Selfobject Needs Inventory. Two Multiple Linear Regression Analyses, entering Self-criticism and Neediness as criterion variables, were computed. According to the results high Attachment anxiety, high Immature defenses, high depressive symptoms, and high need for idealization were related to self-criticism, and explained 47% of its variance. In addition, high attachment anxiety, low mature defenses, high neurotic defenses, high avoidance of mirroring, and low avoidance of idealization/twinship were related to neediness, and explained 40% of its variance. A Principal Component Analysis was performed, entering all the studied variables. Three factors emerged; one describing a maladaptive form of psychological functioning and two describing more mature modes of psychological functioning. The results are discussed in their implications for the understanding of neediness and self-criticism as maladaptive personality dimensions focused, respectively, on relatedness and self-definition.
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Indigenous peoples have the right of self-determination, in accordance with international law by virtue of which tehy may freely determine their political status and institutions and freely pursue their economic, social and cultural development. an integral part of this is the right to autonomy and self-government. The essential feature of racism is not hostility or misperception, but rather the defense [sic] of a system from which advantage is derived on the basis of race. The manner in which the defense [sic] is articulated - either as hostility or subtlety - is not nearly as important as the fact that it insures the continuation of a privileged relationship.
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A self-supported 40W Direct Methanol Fuel Cell (DMFC) system has been developed and performance tested. The auxiliaries in the DMFC system comprise a methanol sensor, a liquid-level indicator, and fuel and air pumps that consume a total power of about 5W. The system has a 15-cell DMFC stack with active electrode-area of 45 cm(2). The self-supported DMFC system addresses issues related to water recovery from the cathode exhaust, and maintains a constant methanol-feed concentration with thermal management in the system. Pure methanol and water from cathode exhaust are pumped to the methanol-mixing tank where the liquid level is monitored and controlled with the help of a liquid-level indicator. During the operation, methanol concentration in the feed solution at the stack outlet is monitored using a methanol sensor, and pure methanol is added to restore the desired methanol concentration in the feed tank by adding the product water from the cathode exhaust. The feed-rate requirements of fuel and oxidant are designed for the stack capacity of 40W. The self-supported DMFC system is ideally suited for various defense and civil applications and, in particular, for charging the storage batteries.
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Most bacterial genomes harbor restriction-modification systems, encoding a REase and its cognate MTase. On attack by a foreign DNA, the REase recognizes it as nonself and subjects it to restriction. Should REases be highly specific for targeting the invading foreign DNA? It is often considered to be the case. However, when bacteria harboring a promiscuous or high-fidelity variant of the REase were challenged with bacteriophages, fitness was maximal under conditions of catalytic promiscuity. We also delineate possible mechanisms by which the REase recognizes the chromosome as self at the noncanonical sites, thereby preventing lethal dsDNA breaks. This study provides a fundamental understanding of how bacteria exploit an existing defense system to gain fitness advantage during a host-parasite coevolutionary ``arms race.''
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Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semisupervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative lowdimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.bu.edu/SSART/.
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Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. How these hexagonal patterns arise has excited intense interest. It has previously been shown how a selforganizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? A neural model is proposed that converts path integration signals into hexagonal grid cell patterns of multiple scales. This GRID model creates only grid cell patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support a unified computational framework for explaining how entorhinal-hippocampal interactions support spatial navigation.
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British Petroleum (89A-1204); Defense Advanced Research Projects Agency (N00014-92-J-4015); National Science Foundation (IRI-90-00530); Office of Naval Research (N00014-91-J-4100); Air Force Office of Scientific Research (F49620-92-J-0225)