78 research outputs found
D* Production in Deep Inelastic Scattering at HERA
This paper presents measurements of D^{*\pm} production in deep inelastic
scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The
data have been taken with the ZEUS detector at HERA. The decay channel
(+ c.c.) has been used in the study. The
cross section for inclusive D^{*\pm} production with
and is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region
{ GeV and }. Differential cross
sections as functions of p_T(D^{*\pm}), and are
compared with next-to-leading order QCD calculations based on the photon-gluon
fusion production mechanism. After an extrapolation of the cross section to the
full kinematic region in p_T(D^{*\pm}) and (D^{*\pm}), the charm
contribution to the proton structure function is
determined for Bjorken between 2 10 and 5 10.Comment: 17 pages including 4 figure
Observation of Scaling Violations in Scaled Momentum Distributions at HERA
Charged particle production has been measured in deep inelastic scattering
(DIS) events over a large range of and using the ZEUS detector. The
evolution of the scaled momentum, , with in the range 10 to 1280
, has been investigated in the current fragmentation region of the Breit
frame. The results show clear evidence, in a single experiment, for scaling
violations in scaled momenta as a function of .Comment: 21 pages including 4 figures, to be published in Physics Letters B.
Two references adde
Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.
Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem
Observation of Events with an Energetic Forward Neutron in Deep Inelastic Scattering at HERA
In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample independent of Bjorken x and Q2 in the range 3 · 10-4 \u3c xBJ \u3c 6 · 10-3 and 10 \u3c Q2 \u3c 100 GeV2
Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) Conceptual Design Report Volume 2: The Physics Program for DUNE at LBNF
The Physics Program for the Deep Underground Neutrino Experiment (DUNE) at the Fermilab Long-Baseline Neutrino Facility (LBNF) is described
Thinking Creatively About Methodological Issues in Conflict-Affected Societies: A Primer from the Field
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