658 research outputs found
Photon Splitting in a Strong Magnetic Field: Recalculation and Comparison With Previous Calculations
We recalculate the amplitude for photon splitting in a strong magnetic field
below the pair production threshold, using the worldline path integral variant
of the Bern--Kosower formalism. Numerical comparison (using programs that we
have made available for public access on the Internet) shows that the results
of the recalculation are identical to the earlier calculations of Adler and
later of Stoneham, and to the recent recalculation by Baier, Milstein, and
Shaisultanov.Comment: Revtex, 9 pages, no figure
Bistable states of quantum dot array junctions for high-density memory
We demonstrate that two-dimensional (2D) arrays of coupled quantum dots (QDs)
with six-fold degenerate p orbitals can display bistable states, suitable for
application in high-density memory device with low power consumption. Due to
the inter-dot coupling of and orbitals in these QD arrays, two
dimensional conduction bands can be formed in the x-y plane, while the
orbitals remain localized in the x-y plane such that the inter-dot coupling
between them can be neglected. We model such systems by taking into account the
on-site repulsive interactions between electrons in orbitals and the
coupling of the localized orbitals with the 2D conduction bands formed by
and orbitals. The Green's function method within an extended
Anderson model is used to calculate the tunneling current through the QDs. We
find that bistable tunneling current can exist for such systems due to the
interplay of the on-site Coulomb interactions (U) between the orbitals
and the delocalized nature of conduction band states derived from the
hybridization of / orbitals. This bistable current is not sensitive
to the detailed band structure of the two dimensional band, but depends
critically on the strength of and the ratio of the left and right tunneling
rates. The behavior of the electrical bistability can be sustained when the 2D
QD array reduces to a one-dimensional QD array, indicating the feasibility for
high-density packing of these bistable nanoscale structures
Measuring Charge Transport in an Amorphous Semiconductor Using Charge Sensing
We measure charge transport in hydrogenated amorphous silicon (a-Si:H) using
a nanometer scale silicon MOSFET as a charge sensor. This charge detection
technique makes possible the measurement of extremely large resistances. At
high temperatures, where the a-Si:H resistance is not too large, the charge
detection measurement agrees with a direct measurement of current. The device
geometry allows us to probe both the field effect and dispersive transport in
the a-Si:H using charge sensing and to extract the density of states near the
Fermi energy.Comment: 4 pages, 4 figure
Small beams, fast predictions: a comparison of machine learning dose prediction models for proton minibeam therapy
Background:
Dose calculations for novel radiotherapy cancer treatments such as proton minibeam radiation therapy is often done using full Monte Carlo (MC) simulations. As MC simulations can be very time consuming for this kind of application, deep learning models have been considered to accelerate dose estimation in cancer patients.
Purpose:
This work systematically evaluates the dose prediction accuracy, speed and generalization performance of three selected state-of-the-art deep learning models for dose prediction applied to the proton minibeam therapy. The strengths and weaknesses of those models are thoroughly investigated, helping other researchers to decide on a viable algorithm for their own application.
Methods:
The following recently published models are compared: first, a 3D U-Net model trained as a regression network, second, a 3D U-Net trained as a generator of a generative adversarial network (GAN) and third, a dose transformer model which interprets the dose prediction as a sequence translation task. These models are trained to emulate the result of MC simulations. The dose depositions of a proton minibeam with a diameter of 800μm and an energy of 20–100 MeV inside a simple head phantom calculated by full Geant4 MC simulations are used as a case study for this comparison. The spatial resolution is 0.5 mm. Special attention is put on the evaluation of the generalization performance of the investigated models.
Results:
Dose predictions with all models are produced in the order of a second on a GPU, the 3D U-Net models being fastest with an average of 130 ms. An investigated 3D U-Net regression model is found to show the strongest performance with overall 61.0%±0.5% of all voxels exhibiting a deviation in energy deposition prediction of less than 3% compared to full MC simulations with no spatial deviation allowed. The 3D U-Net models are observed to show better generalization performance for target geometry variations, while the transformer-based model shows better generalization with regard to the proton energy.
Conclusions:
This paper reveals that (1) all studied deep learning models are significantly faster than non-machine learning approaches predicting the dose in the order of seconds compared to hours for MC, (2) all models provide reasonable accuracy, and (3) the regression-trained 3D U-Net provides the most accurate predictions
A rare case of low-grade myofibroblastic sarcoma of the femur in a 38-year-old woman: a case report
<p>Abstract</p> <p>Introduction</p> <p>Primary myofibroblastic sarcoma of the bone is a rare spindle cell tumour with, to the best of our knowledge, only eight cases reported in the available English language literature. The disease's rarity and its low-grade features make an accurate diagnosis difficult in most cases. The differential diagnoses of this unusual tumour include various benign entities as well as other sarcomas. Due to the difference in prognosis, a precise pathologic diagnosis is essential, which requires a combination of thorough morphologic examination, immunohistochemistry and electron microscopy wherever available.</p> <p>Case presentation</p> <p>We report the case of a 38-year-old Indian woman with a lytic lesion in her left femur. The tumour was associated with cortical destruction and soft tissue extension. A biopsy from the soft tissue component showed features suggestive of a low-grade malignant mesenchymal tumour. Excision of the tumour was performed and histopathological examination showed a low-grade spindle cell sarcoma with collagenous stroma. Expressions of vimentin and smooth muscle actin were also noted. Ultrastructural examination confirmed its myofibroblastic nature. A final diagnosis of low-grade myofibroblastic sarcoma of the left femur was thus rendered.</p> <p>Conclusion</p> <p>Low-grade myofibroblastic sarcoma is one of the rarer osseous spindle cell sarcomas depicting a favourable prognosis in the cases reported so far. Its diagnosis requires ancillary techniques like immunohistochemistry and electron microscopy. To the best of our knowledge, we report the ninth case in the literature and the first case from our subcontinent.</p
Photon Splitting in a Very Strong Magnetic Field
Photon splitting in a very strong magnetic field is analyzed for energy
. The amplitude obtained on the base of operator-diagram technique
is used. It is shown that in a magnetic field much higher than critical one the
splitting amplitude is independent on the field. Our calculation is in a good
agreement with previous results of Adler and in a strong contradiction with
recent paper of Mentzel et al.Comment: 5 pages,Revtex , 4 figure
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