Consistent Estimation of Integrated Volatility Using Intraday Absolute Returns for SV Jump Diffusion Processes

In this paper, we consider an integrated volatility estimation of a stochastic volatility jump diffusion model using intraday absolute returns. We introduce our estimator as a natural extension of realized absolute variation, proposed by Barndorff-Nielsen and Shephard (2003), and show its consistency and asymptotic normality. We also show our estimator is asymptotically more efficient than another jump-robust estimator, bi-power variation, proposed by Barndorff-Nielsen and Shephard (2004, 2006). The results of a simulation to assess the finite-sample behavior of our estimator compliment the asymptotic result.High-frequency data, Bi-power variation, Integrated volatility, Jumps

Image synthesis of monoenergetic CT image in dual-energy CT using kilovoltage CT with deep convolutional generative adversarial networks

Purpose: To synthesize a dual-energy computed tomography (DECT) image from an equivalent kilovoltage computed tomography (kV-CT) image using a deep convolutional adversarial network. Methods: A total of 18,084 images of 28 patients are categorized into training and test datasets. Monoenergetic CT images at 40, 70, and 140 keV and equivalent kVCT images at 120 kVp are reconstructed via DECT and are defined as the reference images. An image prediction framework is created to generate monoenergetic computed tomography (CT) images from kV-CT images. The accuracy of the images generated by the CNN model is determined by evaluating the mean absolute error (MAE), mean square error (MSE), relative root mean square error (RMSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mutual information between the synthesized and reference monochromatic CT images. Moreover, the pixel values between the synthetic and reference images are measured and compared using a manually drawn region of interest (ROI). Results: The difference in the monoenergetic CT numbers of the ROIs between the synthetic and reference monoenergetic CT images is within the standard deviation values. The MAE, MSE, RMSE, and SSIM are the smallest for the image conversion of 120 kVp to 140 keV. The PSNR is the smallest and the MI is the largest for the synthetic 70 keV image. Conclusions: The proposed model can act as a suitable alternative to the existing methods for the reconstruction of monoenergetic CT images in DECT from single-energy CT images

Dose compensation based on biological effectiveness due to interruption time for photon radiation therapy

Objective:To evaluate the biological effectiveness of dose associated with interruption time; and propose the dose compensation method based on biological effectiveness when an interruption occurs during photon radiation therapy. Methods:The lineal energy distribution for human salivary gland tumor was calculated by Monte Carlo simulation using a photon beam. The biological dose (Dbio) was estimated using the microdosimetric kinetic model. The dose compensating factor with the physical dose for the difference of the Dbio with and without interruption (Δ) was derived. The interruption time (τ) was varied to 0.1, 0.2, 0.3, 0.4, 0.5, 1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 75, and 120 min. The dose per fraction and dose rate varied from 2 to 8 Gy and 0.1 to 24 Gy/min, respectively. Results:The maximum Δ with 1 Gy/min occurred when the interruption occurred at half the dose. The Δ with 1 Gy/min at half of the dose was over 3% for τ >= 20 min for 2 Gy, τ = 10 min for 5 Gy, and τ = 10 min for 8 Gy. The maximum difference of the Δ due to the dose rate was within 3% for 2 and 5 Gy, and achieving values of 4.0% for 8 Gy. The dose compensating factor was larger with a high dose per fraction and high-dose rate beams. Conclusion:A loss of biological effectiveness occurs due to interruption. Our proposal method could correct for the unexpected decrease of the biological effectiveness caused by interruption time. Advances in knowledge:For photon radiotherapy, the interruption causes the sublethal damage repair. The current study proposed the dose compensation method for the decrease of the biological effect by the interruption

Direct Sequence Analysis of a Cyanogen Bromide-Generated Peptide Corresponding to the Region of Subfragment-1 of Adult Chicken Gizzard Myosin Heavy Chain Predicted to Contain a Seven-Amino Acid Insertion

The amino acid sequence of a cyanogen bromide-generated peptide corresponding to the region of subfragment-1 of chicken gizzard myosin, predicted from the cDNA sequence to contain a seven-amino acid insertion, was determined directly. Subfragment-1 was prepared from adult chicken gizzard myosin by limited digestion with papain, and a 137-residue peptide was obtained by cleaving subfragment-1 with cyanogen bromide. Amino acid composition analysis and sequence analysis of the fragments generated from this peptide by formic acid or a-chymotrypsin revealed that the peptide corresponded to leucine-165 to methionine-301 of chicken gizzard myosin heavy chain previously deduced from the cDNA sequence by Yanagisawa, M. et al.. The predicted seven-amino acid insertion (Gln-Gly-Pro-Ser-Phe-Ser-Tyr), absent from other smooth muscle myosin,was thus confirmed to be present in chicken gizzard myosin. The amino acid sequence surrounding the insertion site of chicken gizzard myosin shows greater homology to the corresponding sequence of other known smooth muscle and non-muscle myosins than to those of chicken skeletal and cardiac muscle myosins. The insertion sequence may confer gizzard-specific functions to the gizzard myosin heavy chain, whereas the amino acid sequence surrounding the insertion site may be specific to smooth muscle