5,725 research outputs found
Phenomenological Implications of the Topflavor Model
We explore phenomenologies of the topflavour model for the LEP experiment at
scale and the atomic parity violation (APV) experiment in the
atoms at low energies. Implications of the model on the peak data are
studied in terms of the precision variables 's. We find that the
LEP data give more stringent constraints on the model parameters than the APV
data.Comment: 23 pages (including 5 .eps figs), ReVTeX, the 1st revised version, to
appear in Phys. Lett.
Prevalent de novo somatic mutations in superantigen genes of mouse mammary tumor viruses in the genome of C57BL/6J mice and its potential implication in the immune system
<p>Abstract</p> <p>Background</p> <p>Superantigens (SAgs) of mouse mammary tumor viruses (MMTVs) play a crucial role in T cell selection in the thymus in a T cell receptor (TCR) Vβ-specific manner and SAgs presented by B cells activate T cells in the periphery. The peripheral T cell repertoire is dynamically shaped by the steady induction of T cell tolerance against self antigens throughout the lifespan. We hypothesize that <it>de novo </it>somatic mutation of endogenous MMTV SAgs contributes to the modulation of the peripheral T cell repertoire.</p> <p>Results</p> <p>SAg coding sequences were cloned from the genomic DNAs and/or cDNAs of various tissues of female C57BL/6J mice. A total of 68 unique SAg sequences (54 translated sequences) were identified from the genomic DNAs of liver, lungs, and bone marrow, which are presumed to harbor only three endogenous MMTV loci (<it>Mtv-8</it>, <it>Mtv-9</it>, and <it>Mtv-17</it>). Similarly, 69 unique SAg sequences (58 translated sequences) were cloned from the cDNAs of 18 different tissues. Examination of putative TCR Vβ specificity suggested that some of the SAg isoforms identified in this study have Vβ specificities different from the reference SAgs of <it>Mtv-8</it>, <it>Mtv-9</it>, or <it>Mtv-17</it>.</p> <p>Conclusion</p> <p>The pool of diverse SAg isoforms, generated by <it>de novo </it>somatic mutation, may play a role in the shaping of the peripheral T cell repertoire including the autoimmune T cell population.</p
Approximate Flavour Symmetries and See-Saw Mechanism
We study the approximate flavour symmetries imposed on the lepton sector
assuming see-saw mechanism as the neutrino mass structure. We apply the
symmetry to various neutrino phenomenologies and obtain constraints on neutrino
masses and mixings.Comment: 10 pages, RevTex, 2 PS figures (uuencoded in seperate file). To
appear in Mod. Phys. Lett.
Form Factors for Exclusive Semileptonic --Decays
We developed the new parton model approach for exclusive semileptonic decays
of -meson to by extending the inclusive parton model, and by
combining with the results of the HQET, motivated by Drell-Yan process. Without
the nearest pole dominance ans\"atze, we {\bf derived} the dependences of
hadronic form factors on . We also calculated numerically the slope of the
Isgur-Wise function, which is consistent with the experimental results.Comment: 20 pages, RevTex, 2 ps figure files(uuencoded in seperate file
Towards Neural Decoding of Imagined Speech based on Spoken Speech
Decoding imagined speech from human brain signals is a challenging and
important issue that may enable human communication via brain signals. While
imagined speech can be the paradigm for silent communication via brain signals,
it is always hard to collect enough stable data to train the decoding model.
Meanwhile, spoken speech data is relatively easy and to obtain, implying the
significance of utilizing spoken speech brain signals to decode imagined
speech. In this paper, we performed a preliminary analysis to find out whether
if it would be possible to utilize spoken speech electroencephalography data to
decode imagined speech, by simply applying the pre-trained model trained with
spoken speech brain signals to decode imagined speech. While the classification
performance of imagined speech data solely used to train and validation was
30.5 %, the transferred performance of spoken speech based classifier to
imagined speech data displayed average accuracy of 26.8 % which did not have
statistically significant difference compared to the imagined speech based
classifier (p = 0.0983, chi-square = 4.64). For more comprehensive analysis, we
compared the result with the visual imagery dataset, which would naturally be
less related to spoken speech compared to the imagined speech. As a result,
visual imagery have shown solely trained performance of 31.8 % and transferred
performance of 26.3 % which had shown statistically significant difference
between each other (p = 0.022, chi-square = 7.64). Our results imply the
potential of applying spoken speech to decode imagined speech, as well as their
underlying common features.Comment: 4 pages, 2 figure
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