| 1. |
|
|
| 2. |
- Campbell, PJ, et al.
(författare)
-
Pan-cancer analysis of whole genomes
- 2020
-
Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
-
Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
|
|
| 3. |
- Zhou, X., et al.
(författare)
-
Novel Evaluation Method to Determine the Mixing Time in a Ladle Refining Process
- 2022
-
Ingår i: Metallurgical and materials transactions. B, process metallurgy and materials processing science. - : Springer Nature. - 1073-5615 .- 1543-1916. ; 53:6, s. 4114-4123
-
Tidskriftsartikel (refereegranskat)abstract
- Mixing plays a key role in mass and heat transfer, as well as chemical reactions in various vessels involving agitation. Several studies have confirmed that the mixing time obtained from several monitor locations cannot reflect the mixing time for the whole bath because stirring situation in different locations is variable due to the change of operation schemes. It is proved that some zones with inefficient stirring cannot be monitored by applying a limited amount of probes in physical and mathematical models. This study provides a novel approach to quantify mixing time evaluation considering the tracer variation for the whole bath using a mathematical model. It was found that the mixing time obtained by considering the whole bath is more representative than that of the probe monitor method. Compared with the traditional probe method, about 50 to 70 pct longer mixing times were obtained for different operations by applying the volume track method. In addition, the volume integral of the concerned variable for the whole bath is more representative to determine the developed flow compared to the points monitoring method for a transient simulation.
|
|
| 4. |
- Kanai, M, et al.
(författare)
-
- 2023
-
swepub:Mat__t
|
|
| 5. |
- Barausse, Enrico, et al.
(författare)
-
Prospects for fundamental physics with LISA
- 2020
-
Ingår i: General Relativity and Gravitation. - : SPRINGER/PLENUM PUBLISHERS. - 0001-7701 .- 1572-9532. ; 52:8
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- In this paper, which is of programmatic rather than quantitative nature, we aim to further delineate and sharpen the future potential of the LISA mission in the area of fundamental physics. Given the very broad range of topics that might be relevant to LISA,we present here a sample of what we view as particularly promising fundamental physics directions. We organize these directions through a "science-first" approach that allows us to classify how LISA data can inform theoretical physics in a variety of areas. For each of these theoretical physics classes, we identify the sources that are currently expected to provide the principal contribution to our knowledge, and the areas that need further development. The classification presented here should not be thought of as cast in stone, but rather as a fluid framework that is amenable to change with the flow of new insights in theoretical physics.
|
|
| 6. |
|
|
| 7. |
- Klionsky, DJ, et al.
(författare)
-
Autophagy in major human diseases
- 2021
-
Ingår i: The EMBO journal. - : EMBO. - 1460-2075 .- 0261-4189. ; 40:19, s. e108863-
-
Tidskriftsartikel (refereegranskat)
|
|
| 8. |
|
|
| 9. |
|
|
| 10. |
- Liu, X., et al.
(författare)
-
Surface roughness prediction method of titanium alloy milling based on CDH platform
- 2022
-
Ingår i: The International Journal of Advanced Manufacturing Technology. - : Springer Nature. - 0268-3768 .- 1433-3015. ; 119:11-12, s. 7145-7157
-
Tidskriftsartikel (refereegranskat)abstract
- Generally, off-line methods are used for surface roughness prediction of titanium alloy milling. However, studies show that these methods have poor prediction accuracy. In order to resolve this shortcoming, a prediction method based on Cloudera’s Distribution including Apache Hadoop (CDH) platform is proposed in the present study. In this regard, data analysis and process platform are designed based on the CDH, which can upload, calculate, and store data in real time. Then this platform is combined with the Harris hawk optimization (HHO) algorithm and pattern search strategy, and an improved Harris hawk optimization optimization (IHHO) method is proposed accordingly. Then this method is applied to optimize the support vector machine (SVM) algorithm and predict the surface roughness in the CDH platform. The obtained results show that the prediction accuracy of IHHO method reaches 95%, which is higher than the conventional methods of SVM, BAT-SVM, gray wolf optimizer (GWO-SVM), and whale optimization algorithm (WOA-SVM).
|
|
