Leveraging comprehensive baseline datasets to quantify property variability in nuclear-grade graphites

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Microstructural characterization of next generation nuclear graphites.

This article reports the microstructural characteristics of various petroleum and pitch based nuclear graphites (IG-110, NBG-18, and PCEA) that are of interest to the next generation nuclear plant program. Bright-field transmission electron microscopy imaging was used to identify and understand the different features constituting the microstructure of nuclear graphite such as the filler particl...

متن کامل

Leveraging distant relatedness to quantify human

20 The rate at which human genomes mutate is a central biological parameter that 21 has many implications for our ability to understand demographic and evolutionary 22 phenomena. We present a method for inferring mutation and gene conversion rates 23 using the number of sequence differences observed in identical-by-descent (IBD) 24 segments together with a reconstructed model of recent populati...

متن کامل

Leveraging genome-wide datasets to quantify the functional role of the anti-Shine–Dalgarno sequence in regulating translation efficiency

Studies dating back to the 1970s established that sequence complementarity between the anti-Shine-Dalgarno (aSD) sequence on prokaryotic ribosomes and the 5' untranslated region of mRNAs helps to facilitate translation initiation. The optimal location of aSD sequence binding relative to the start codon, the full extents of the aSD sequence and the functional form of the relationship between aSD...

متن کامل

Leveraging prognostic baseline variables to gain precision in randomized trials.

We focus on estimating the average treatment effect in a randomized trial. If baseline variables are correlated with the outcome, then appropriately adjusting for these variables can improve precision. An example is the analysis of covariance (ANCOVA) estimator, which applies when the outcome is continuous, the quantity of interest is the difference in mean outcomes comparing treatment versus c...

متن کامل

Leveraging Common Structure to Improve Prediction across Related Datasets

In many applications, training data is provided in the form of related datasets obtained from several sources, which typically affects the sample distribution. The learned classification models, which are expected to perform well on similar data coming from new sources, often suffer due to bias introduced by what we call ‘spurious’ samples – those due to source characteristics and not represent...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Nuclear Engineering and Design

سال: 2016

ISSN: 0029-5493

DOI: 10.1016/j.nucengdes.2016.06.028