scholarly journals Classification of left–right symmetric heterotic string vacua

2018 ◽  
Vol 936 ◽  
pp. 472-500 ◽  
Author(s):  
Alon E. Faraggi ◽  
Glyn Harries ◽  
John Rizos
Keyword(s):  
Heterotic String

scholarly journals Towards classification of SO(10) heterotic string vacua

2011 ◽  
Vol 59 (11-12) ◽  
pp. 1159-1163 ◽  
Author(s):  
J. Rizos
Keyword(s):  
Heterotic String

scholarly journals Classification of standard-like heterotic-string vacua

2018 ◽  
Vol 927 ◽  
pp. 1-34 ◽  
Author(s):  
Alon E. Faraggi ◽  
John Rizos ◽  
Hasan Sonmez
Keyword(s):  
Heterotic String

scholarly journals Non-SUSY heterotic string vacua of Gepner models with vanishing cosmological constant

2021 ◽  
Vol 2021 (3) ◽  
Author(s):  
Koji Aoyama ◽  
Yuji Sugawara
Keyword(s):  
Cosmological Constant ◽  
Discrete Subgroup ◽  
Natural Generalization ◽  
Heterotic String ◽  
Type Ii ◽  
Heterotic Strings ◽  
Cyclic Groups ◽  
The One ◽  
Gepner Model

Abstract We study a natural generalization of the results given in K. Aoyama and Y. Sugawara, Prog. Theor. Exp. Phys. 2020, 103B01 (2020) to heterotic strings. Namely, starting from the generic Gepner models for Calabi –Yau three-folds, we construct non-SUSY heterotic string vacua with vanishing cosmological constant at the one-loop level. We especially focus on asymmetric orbifolding based on some discrete subgroup of the chiral $U(1)$ action which acts on both the Gepner model and the $SO(32)$ or $E_8\times E_8$ sector. We present a classification of the relevant orbifold models leading to the string vacua with the properties mentioned above. In some cases, the desired vacua can be constructed in a manner quite similar to those given in the previous paper for the type II string, in which the orbifold groups contain two generators with discrete torsions. On the other hand, we also have simpler models that are just realized as asymmetric orbifolds of cyclic groups with only one generator.

scholarly journals Classification of nonsupersymmetric Pati-Salam heterotic string models

2021 ◽  
Vol 104 (4) ◽  
Author(s):  
Alon E. Faraggi ◽  
Viktor G. Matyas ◽  
Benjamin Percival
Keyword(s):  
Heterotic String ◽  
String Models

scholarly journals Towards the classification of tachyon-free models from tachyonic ten-dimensional heterotic string vacua

2020 ◽  
Vol 961 ◽  
pp. 115231 ◽  
Author(s):  
Alon E. Faraggi ◽  
Viktor G. Matyas ◽  
Benjamin Percival
Keyword(s):  
Heterotic String

scholarly journals Classification of flipped SU(5) heterotic-string vacua

2014 ◽  
Vol 886 ◽  
pp. 202-242 ◽  
Author(s):  
Alon E. Faraggi ◽  
John Rizos ◽  
Hasan Sonmez
Keyword(s):  
Heterotic String

Note on the spectral classification of carbon stars in the photographic infrared region

1966 ◽  
Vol 24 ◽  
pp. 21-23
Author(s):  
Y. Fujita
Keyword(s):  
Infrared Region ◽  
Spectral Classification ◽  
Carbon Stars

We have investigated the spectrograms (dispersion: 8Å/mm) in the photographic infrared region fromλ7500 toλ9000 of some carbon stars obtained by the coudé spectrograph of the 74-inch reflector attached to the Okayama Astrophysical Observatory. The names of the stars investigated are listed in Table 1.

Diagnostic Value of Electron Microscopy in Soft Tissue Tumors

1970 ◽  
Vol 28 ◽  
pp. 220-221
Author(s):  
Gerald Fine ◽  
Azorides R. Morales
Keyword(s):  
Cardiac Myxoma ◽  
Osteogenic Sarcoma ◽  
Diagnostic Value ◽  
Soft Tissue Tumors ◽  
Amelanotic Melanoma ◽  
Growth Patterns ◽  
Light Microscopic Level ◽  
Mesenchymal Tumors ◽  
Good Agreement

For years the separation of carcinoma and sarcoma and the subclassification of sarcomas has been based on the appearance of the tumor cells and their microscopic growth pattern and information derived from certain histochemical and special stains. Although this method of study has produced good agreement among pathologists in the separation of carcinoma from sarcoma, it has given less uniform results in the subclassification of sarcomas. There remain examples of neoplasms of different histogenesis, the classification of which is questionable because of similar cytologic and growth patterns at the light microscopic level; i.e. amelanotic melanoma versus carcinoma and occasionally sarcoma, sarcomas with an epithelial pattern of growth simulating carcinoma, histologically similar mesenchymal tumors of different histogenesis (histiocytoma versus rhabdomyosarcoma, lytic osteogenic sarcoma versus rhabdomyosarcoma), and myxomatous mesenchymal tumors of diverse histogenesis (myxoid rhabdo and liposarcomas, cardiac myxoma, myxoid neurofibroma, etc.)

Ultrastructure of mesotheliomas

1984 ◽  
Vol 42 ◽  
pp. 98-101
Author(s):  
Irving Dardick
Keyword(s):  
Electron Microscopy ◽  
Latent Period ◽  
Spindle Cell ◽  
Spindle Cell Sarcoma ◽  
Metastatic Adenocarcinoma ◽  
Cell Sarcoma ◽  
Cytological Features ◽  
Industrial Use ◽  
Degree Of Differentiation

With the extensive industrial use of asbestos in this century and the long latent period (20-50 years) between exposure and tumor presentation, the incidence of malignant mesothelioma is now increasing. Thus, surgical pathologists are more frequently faced with the dilemma of differentiating mesothelioma from metastatic adenocarcinoma and spindle-cell sarcoma involving serosal surfaces. Electron microscopy is amodality useful in clarifying this problem.In utilizing ultrastructural features in the diagnosis of mesothelioma, it is essential to appreciate that the classification of this tumor reflects a variety of morphologic forms of differing biologic behavior (Table 1). Furthermore, with the variable histology and degree of differentiation in mesotheliomas it might be expected that the ultrastructure of such tumors also reflects a range of cytological features. Such is the case.

Interpreting HVEM of muscle-cell impulse networks

1992 ◽  
Vol 50 (1) ◽  
pp. 126-127
Author(s):  
Paul DeCosta ◽  
Kyugon Cho ◽  
Stephen Shemlon ◽  
Heesung Jun ◽  
Stanley M. Dunn
Keyword(s):  
Structural Analysis ◽  
Muscle Cell ◽  
Electron Micrographs ◽  
Relative Size ◽  
Automatic Classification ◽  
Nerve Fibers ◽  
Analysis Algorithm ◽  
Structural Networks

Introduction: The analysis and interpretation of electron micrographs of cells and tissues, often requires the accurate extraction of structural networks, which either provide immediate 2D or 3D information, or from which the desired information can be inferred. The images of these structures contain lines and/or curves whose orientation, lengths, and intersections characterize the overall network.Some examples exist of studies that have been done in the analysis of networks of natural structures. In, Sebok and Roemer determine the complexity of nerve structures in an EM formed slide. Here the number of nodes that exist in the image describes how dense nerve fibers are in a particular region of the skin. Hildith proposes a network structural analysis algorithm for the automatic classification of chromosome spreads (type, relative size and orientation).

Sign in / Sign up

Export Citation Format

Share Document