다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Supplementary Table 9, column 'Edoxaban', row 'eGFR category', '95 mL/min' (page 15). The cell should be coloured green instead of yellow. It should also read "60 mg"instead of "60 mg (use with caution in 'supranormal' renal function)."In the above-indicated cell, a footnote has also been added to state: "Edoxaban should be used in patients with high creatinine clearance only after a careful evaluation of the individual thromboembolic and bleeding risk."Supplementary Table 9, column 'Edoxaban', row 'Dose reduction in selected patients' (page 16). The cell should read "Edoxaban 60 mg reduced to 30 mg once daily if any of the following: creatinine clearance 15-50 mL/min, body weight <60 kg, concomitant use of dronedarone, erythromycin, ciclosporine or ketokonazole"instead of "Edoxaban 60 mg reduced to 30 mg once daily, and edoxaban 30 mg reduced to 15mg once daily, if any of the following: creatinine clearance of 30-50 mL/min, body weight <60 kg, concomitant us of verapamil or quinidine or dronedarone."

/pdf/2020-esc-guidelines-for-the-diagnosis-and-management-of-38dpic1xu8.pdf

2020 ESC Guidelines for the diagnosis and management of atrial fibrillation developed in collaboration with the European Association for Cardio-Thoracic Surgery (EACTS).

We present a preliminary set of updated NLO parton distributions. For the first time we have a quantitative extraction of the strange quark and antiquark distributions and their uncertainties determined from CCFR and NuTeV dimuon cross sections. Additional jet data from HERA and the Tevatron improve our gluon extraction. Lepton asymmetry data and neutrino structure functions improve the flavour separation, particularly constraining the down quark valence distribution.

http://inspirehep.net/record/752235/files/arXiv:0706.0456.pdf

Parton distributions for the LHC

We propose a new type of saliency – context-aware saliency – which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting we demonstrate that using our saliency prevents distortions in the important regions. In summarization we show that our saliency helps to produce compact, appealing, and informative summaries.

Context-aware saliency detection

EPOS is a Monte-Carlo event generator for minimum bias hadronic interac- tions, used for both heavy ion interactions and cosmic ray air shower simulations. Since the last public release in 2009, the LHC experiments have provided a number of very inter- esting data sets comprising minimum bias p-p, p-Pb and Pb-Pb interactions. We describe the changes required to the model to reproduce in detail the new data available from LHC and the consequences in the interpretation of these data. In particular we discuss the effect of the collective hadronization in p-p scattering. A different parametrization of flow has been introduced in the case of a small volume with high density of thermalized matter (core) reached in p-p compared to large volume produced in heavy ion collisions. Both parametrizations depend only on the geometry and the amount of secondary particles en- tering in the core and not on the beam mass or energy. The transition between the two flow regimes can be tested with p-Pb data. EPOS LHC is able to reproduce all minimum bias results for all particles with transverse momentum from pt = 0 to a few GeV/c.

/pdf/epos-lhc-test-of-collective-hadronization-with-data-measured-2jes7fgrgq.pdf

EPOS LHC: Test of collective hadronization with data measured at the CERN Large Hadron Collider

Color balancing of digital photos using simple image statistics

During a Nuclear Medicine project that called for the optimal design of a coded aperture we found that lowthroughput masks do not always provide a Signal-to-Noise Ratio (SNR) advantage. In this paper, we present the simulations of the performance of some coded aperture patterns chosen from different families and compare the results with theoretical predictions. A general expression for the SNR and its particular form for different patterns are provided. The choice of the optimal pattern family is discussed with reference to the characteristics of the object to be imaged and in light of the effect of near-field artifacts. No-Two-Holes-Touching (NTHT) arrays based on Modified Uniformly Redundant Arrays (MURAs) proved to offer the best compromise between SNR performance and practical fabrication constraints. r 2001 Elsevier Science B.V. All rights reserved.

Optimal coded aperture patterns for improved SNR in nuclear medicine imaging

We propose a new self-adaptive image cropping algorithm where the processing steps are driven by the classification of the images into semantic classes. The algorithm exploits both visual and semantic information. Visual information is obtained from a visual attention model, while semantic information relates to the automatically assigned image genre and to the detection of face and skin regions.

Self-Adaptive Image Cropping for Small Displays

The segmentation of skin regions in color images is a preliminary step in several applications. Many different methods for discriminating between skin and non-skin pixels are available in the literature. The simplest, and often applied, methods build what is called an "explicit skin cluster" classifier which expressly defines the boundaries of the skin cluster in certain color spaces. These binary methods are very popular as they are easy to implement and do not require a training phase. The main difficulty in achieving high skin recognition rates, and producing the smallest possible number of false positive pixels, is that of defining accurate cluster boundaries through simple, often heuristically chosen, decision rules. In this study we apply a genetic algorithm to determine the boundaries of the skin clusters in multiple color spaces. To quantify the performance of these skin detection methods, we use recall and precision scores. A good classifier should provide both high recall and high precision, but generally, as recall increases, precision decreases. Consequently, we adopt a weighted mean of precision and recall as the fitness function of the genetic algorithm. Keeping in mind that different applications may have sharply different requirements, the weighting coefficients can be chosen to favor either high recall or high precision, or to satisfy a reasonable tradeoff between the two, depending on application demands. To train the genetic algorithm (GA) and test the performance of the classifiers applying the GA suggested boundaries, we use the large and heterogeneous Compaq skin database.

/pdf/skin-segmentation-using-multiple-thresholding-56cj2f5mbd.pdf

Skin segmentation using multiple thresholding

A method for contrast enhancement is proposed. The algorithm is based on a local and image-dependent exponential cor- rection. The technique aims to correct images that simultaneously present overexposed and underexposed regions. To prevent halo artifacts, the bilateral filter is used as the mask of the exponential correction. Depending on the characteristics of the image (piloted by histogram analysis), an automated parameter-tuning step is intro- duced, followed by stretching, clipping, and saturation preserving treatments. Comparisons with other contrast enhancement tech- niques are presented. The Mean Opinion Score (MOS) experiment on grayscale images gives the greatest preference score for our algorithm. © 2010 SPIE and IS&T. DOI: 10.1117/1.3386681

Francesca Gasparini

Papers

Color balancing of digital photos using simple image statistics

Optimal coded aperture patterns for improved SNR in nuclear medicine imaging

Self-Adaptive Image Cropping for Small Displays

Skin segmentation using multiple thresholding

Contrast image correction method