1,399 research outputs found
Collective states of the odd-mass nuclei within the framework of the Interacting Vector Boson Model
A supersymmetric extension of the dynamical symmetry group of
the Interacting Vector Boson Model (IVBM), to the orthosymplectic group
is developed in order to incorporate fermion degrees of
freedom into the nuclear dynamics and to encompass the treatment of odd mass
nuclei. The bosonic sector of the supergroup is used to describe the complex
collective spectra of the neighboring even-even nuclei and is considered as a
core structure of the odd nucleus. The fermionic sector is represented by the
fermion spin group .
The so obtained, new exactly solvable limiting case is applied for the
description of the nuclear collective spectra of odd mass nuclei. The
theoretical predictions for different collective bands in three odd mass
nuclei, namely , and from rare earth region are
compared with the experiment. The transition probabilities for the
and between the states of the ground band are also
studied. The important role of the symplectic structure of the model for the
proper reproduction of the behavior is revealed. The obtained results
reveal the applicability of the models extension.Comment: 18 pages, 8 figure
An Extended Version ofGustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering Evolving Intelligent Systems: Methodology and Applications
The chapter deals with a recursive clustering algorithm that
enables a real time partitioning of data streams. Proposed algorithm
incorporates the advantages of the Gustafson-Kessel clustering algorithm of
identifying clusters with different shape and orientation while expanding
its area of application to the challenging problem of real time data
clustering. The algorithm is applicable to a wide range of practical
evolving system type applications as diagnostics and prognostics, system
identification, real time classification, and process quality monitoring and control
Gustafson-Kessel Algorithm for Evolving Data Stream Clustering
A simplified clustering algorithm that enables on-line
partitioning of data streams is proposed. The algorithm applies
adaptive-distance metric to identify clusters with different shape and
orientation. It is applicable to a wide range of practical evolving system
type applications as diagnostics and prognostics, system identification,
real time classification, and process quality monitoring and control
Antiphospholipid Syndrome in Acute Cerebral Blood Flow Disorders
The purpose of the present study was to dynamically analyze the role of antiphospholipid syndrome in patients with acute disturbances of cerebral blood flow. Twenty-eight patients (16 females and 12 males) aged between 47 and 61 years were examined. The following criteria for patient's incorporation into the study were observed: presence of a focal neurological deficit, ultrasonographic evidence of disturbed cerebral blood flow, CT or MRI data about brain stroke. According to the data from the clinical or x-ray examination, the patients were divided into three groups: with hemorrhagic, embolic, or thrombotic stroke. Anticardiolipid (aCL) antibodies were assessed by ELISA method for a 12-month period. Elevated titres of aCL antibodies were proved in 12 patients (in 43 per cent of the cases) - in ten with ischemic and in two - with hemorrhagic stroke. The treatment with neuroprotective, antiaggregation and immunomodulatory means resulted in improvement of the clinical symptoms and antiphospholipid syndrome as well. It could be concluded that the summarized clinical, roentgenological and immunological data suggest the involvement of elevated titres of aCL antibodies into the pathogenesis of the acute cerebral blood flow disorders. The estimation of these antibodies should be considered obligatory in the patients with stroke with a view to enlargement of the prognostic criteria and more adequate therapeutic approach
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