Analysis of some paper handling problems by a three-dimensional nonlinear finite element algorithm

A three-dimensional nonlinear finite element algorithm was developed to predict the change in paper topology as well as the wrinkle performance of the roll feeding systems. The initial shape of the thin plate to be analyzed can be perfectly flat or wavy. The roll system can be of any arbitrary configuration with manufacturing tolerance included. The algorithm described here uses the total Lagrange formulation with Piola-Kirchhoff stress and Green-Lagrange strain. Gap elements are used to simulate the physical significance of the paper supports. Quasistatic solutions at different time intervals are calculated. The change in topology and the locations of predicted wrinkles are found to agree with experiments.     

A Comparision of Starch Granules as Seen by Both Scanning Electron and Ordinary Light Microscopy

Starch being a transparent crystal often give images which are difficult to precisely define with the light microscope due to the diffraction and other effects such as internal structure which may appear as a surface phenomena. The scanning electron microscope (SEM); however, gives only surface detail. In a effort to differentiate between surface and internal details, the same starch granules have been studied by both ordinary light and scanning electron microscopy. In each case the granules were held in the same configuration as was seen with the light microscope when they were studied by SEM. In this way a direct comparison could be made between granules viewed by each microscopy technique. From such comparisons it is possible to determine the starch details that are actually due to internal features. The results for canna, potato and corn starches are given.     

Development of a Mortality Prediction Model in Hospitalised SARS-CoV-2 Positive Patients Based on Routine Kidney Biomarkers

Acute kidney injury (AKI) is a prevalent complication in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive inpatients, which is linked to an increased mortality rate compared to patients without AKI. Here we analysed the difference in kidney blood biomarkers in SARS-CoV-2 positive patients with non-fatal or fatal outcome, in order to develop a mortality prediction model for hospitalised SARS-CoV-2 positive patients. A retrospective cohort study including data from suspected SARS-CoV-2 positive patients admitted to a large National Health Service (NHS) Foundation Trust hospital in the Yorkshire and Humber regions, United Kingdom, between 1 March 2020 and 30 August 2020. Hospitalised adult patients (aged ≥ 18 years) with at least one confirmed positive RT-PCR test for SARS-CoV-2 and blood tests of kidney biomarkers within 36 h of the RT-PCR test were included. The main outcome measure was 90-day in-hospital mortality in SARS-CoV-2 infected patients. The logistic regression and random forest (RF) models incorporated six predictors including three routine kidney function tests (sodium, urea; creatinine only in RF), along with age, sex, and ethnicity. The mortality prediction performance of the logistic regression model achieved an area under receiver operating characteristic (AUROC) curve of 0.772 in the test dataset (95% CI: 0.694–0.823), while the RF model attained the AUROC of 0.820 in the same test cohort (95% CI: 0.740–0.870). The resulting validated prediction model is the first to focus on kidney biomarkers specifically on in-hospital mortality over a 90-day period.     

Single-Circulating Tumor Cell Whole Genome Amplification to Unravel Cancer Heterogeneity and Actionable Biomarkers

The field of single-cell analysis has advanced rapidly in the last decade and is providing new insights into the characterization of intercellular genetic heterogeneity and complexity, especially in human cancer. In this regard, analyzing single circulating tumor cells (CTCs) is becoming particularly attractive due to the easy access to CTCs from simple blood samples called “liquid biopsies”. Analysis of multiple single CTCs has the potential to allow the identification and characterization of cancer heterogeneity to guide best therapy and predict therapeutic response. However, single-CTC analysis is restricted by the low amounts of DNA in a single cell genome. Whole genome amplification (WGA) techniques have emerged as a key step, enabling single-cell downstream molecular analysis. Here, we provide an overview of recent advances in WGA and their applications in the genetic analysis of single CTCs, along with prospective views towards clinical applications. First, we focus on the technical challenges of isolating and recovering single CTCs and then explore different WGA methodologies and recent developments which have been utilized to amplify single cell genomes for further downstream analysis. Lastly, we list a portfolio of CTC studies which employ WGA and single-cell analysis for genetic heterogeneity and biomarker detection.     

Preferred Orientations in Iodide Titanium

The wire textures for cold rolled and recrystallized iodide titanium and the sheet textures for this material produced by cold and hot rolling, and recrystallization at a series of temperatures were determined. The effect of the α → β transformation on the sheet texture was noted.     

美国的下一代航空运输系统——发展愿景、成就与未来方向

1. Introduction The US Federal Aviation Administration (FAA) manages the lar-gest air traffic control system in the world. This system controls approximate...