AIM To analyze how many measurements are needed for non-invasive assessment of liver stiffness (LS) by means of 2D-Shear Wave Elastography (2D-SWE) and if the use of mean of median values of 2D-SWE measurements is needed. METHODS We evaluated 449 consecutive subjects (with or without chronic liver disease) by means of Transient Elastography (TE) and 2D-SWE. We compared the correlation of LS a...

The purpose of our study is to explore the efficiency of Shear Wave Elastography (SWE) in predicting malignancy Breast Cancer (BC). 63 patients with normal mammary glands and 61 patients with invasive carcinoma were detected by Real-time Tissue Elastography (RTE). Two SWE images of breast hyperplasia with fibroadenoma and invasive breast carcinoma were also obtained. For the SWE characteristics...

Snow meltwaters account for most of the yearly water budgets of many catchments in High Mountain Asia (HMA). We examine trends in snow water equivalent (SWE) using passive microwave data (1987 to 2009). We find an overall decrease in SWE in HMA, despite regions of increased SWE in the Pamir, Kunlun Shan, Eastern Himalaya, and Eastern Tien Shan. Although the average decline in annual SWE across ...

Seaweeds and seaweed extract (SWE) possess antimicrobial, anti-inflammatory, prebiotic, and growth-promoting properties. Extracts can be prepared in different ways including wet, spray-dried, and freeze-dried forms. The aim of this study was to determine if spray drying of laminarin and fucoidan derived from Laminaria digitata had an effect on the microbiological and cytokine profile of the gas...

The Meteorological Service of Canada (MSC) has developed a suite of land-cover sensitive algorithms to extract snow water equivalent (SWE) estimates from satellite passive microwave brightness temperatures. In the boreal forest, however, accurate passive microwave SWE retrievals using the MSC coniferous forest algorithm are hampered by consistent under-estimation. In February 2003, a collection...

......................................................................................................................... 2 Chapter 1 Semantic Word Embedding ........................................................................ 3 1.1 The Skip-gram moel ..................................................................................... 3 1.2 SWE as Constrained Optimization ....................