159 research outputs found
Searching for physics beyond the Standard Model through the dipole interaction
The magnetic dipole interaction played a central role in the development of
QED, and continued in that role for the Standard Model. The muon anomalous
magnetic moment has served as a benchmark for models of new physics, and the
present experimental value is larger than the standard-model value by more than
three standard deviations. The electric dipole moment (EDM) violates parity
({}) and time-reversal ({}) symmetries, and in the context of the
theorem, the combination of charge conjugation and parity (). Since a new
source of {} violation outside of that observed in the and meson
systems is needed to help explain the baryon asymmetry of the universe,
searches for EDMs are being carried out worldwide on a number of systems. The
standard-model value of the EDM is immeasurably small, so any evidence for an
EDM would signify the observation of new physics. Unique opportunities exist
for EDM searches using polarized proton, deuteron or muon beams in storage
rings. This talk will provide an overview of the theory of dipole moments, and
the relevant experiments. The connection to the transition dipole moment that
could produce lepton flavor violating interactions such as is also mentioned.Comment: Invited Plenary talk at the 19th International Spin Physics
Symposium, Juelic
The Particle Spectrum of Heterotic Compactifications
Techniques are presented for computing the cohomology of stable, holomorphic
vector bundles over elliptically fibered Calabi-Yau threefolds. These
cohomology groups explicitly determine the spectrum of the low energy,
four-dimensional theory. Generic points in vector bundle moduli space manifest
an identical spectrum. However, it is shown that on subsets of moduli space of
co-dimension one or higher, the spectrum can abruptly jump to many different
values. Both analytic and numerical data illustrating this phenomenon are
presented. This result opens the possibility of tunneling or phase transitions
between different particle spectra in the same heterotic compactification. In
the course of this discussion, a classification of SU(5) GUT theories within a
specific context is presented.Comment: 77 pages, 3 figure
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An Active Learning Approach for Rapid Characterization of Endothelial Cells in Human Tumors
Currently, no available pathological or molecular measures of tumor angiogenesis predict response to antiangiogenic therapies used in clinical practice. Recognizing that tumor endothelial cells (EC) and EC activation and survival signaling are the direct targets of these therapies, we sought to develop an automated platform for quantifying activity of critical signaling pathways and other biological events in EC of patient tumors by histopathology. Computer image analysis of EC in highly heterogeneous human tumors by a statistical classifier trained using examples selected by human experts performed poorly due to subjectivity and selection bias. We hypothesized that the analysis can be optimized by a more active process to aid experts in identifying informative training examples. To test this hypothesis, we incorporated a novel active learning (AL) algorithm into FARSIGHT image analysis software that aids the expert by seeking out informative examples for the operator to label. The resulting FARSIGHT-AL system identified EC with specificity and sensitivity consistently greater than 0.9 and outperformed traditional supervised classification algorithms. The system modeled individual operator preferences and generated reproducible results. Using the results of EC classification, we also quantified proliferation (Ki67) and activity in important signal transduction pathways (MAP kinase, STAT3) in immunostained human clear cell renal cell carcinoma and other tumors. FARSIGHT-AL enables characterization of EC in conventionally preserved human tumors in a more automated process suitable for testing and validating in clinical trials. The results of our study support a unique opportunity for quantifying angiogenesis in a manner that can now be tested for its ability to identify novel predictive and response biomarkers
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