Age Differences in the Experience of Daily Life Events: A Study Based on the Social Goals Perspective

This study examined age differences in daily life events related to different types of social goals based on the socioemotional selectivity theory (SST), and determined whether the positivity effect existed in the context of social goals in older adults’ daily lives. Over a course of 14 days, 49 older adults and 36 younger adults wrote about up to three life events daily and rated the valence of each event. The findings indicated that (1) although both older and younger adults recorded events related to both emotional and knowledge-acquisition goals, the odds ratio for reporting a higher number of events related to emotional goals compared to the number of events related to knowledge-acquisition goals was 2.12 times higher in older adults than that observed in younger adults. (2) Considering the number of events, there was an age-related positivity effect only for knowledge-related goals, and (3) older adults’ ratings for events related to emotional and knowledge-acquisition goals were significantly more positive compared to those observed in younger adults. These findings supported the SST, and to some extent, the positivity effect was demonstrated in the context of social goals

A solution and practice for combining multi-source heterogeneous data to construct enterprise knowledge graph

The knowledge graph is one of the essential infrastructures of artificial intelligence. It is a challenge for knowledge engineering to construct a high-quality domain knowledge graph for multi-source heterogeneous data. We propose a complete process framework for constructing a knowledge graph that combines structured data and unstructured data, which includes data processing, information extraction, knowledge fusion, data storage, and update strategies, aiming to improve the quality of the knowledge graph and extend its life cycle. Specifically, we take the construction process of an enterprise knowledge graph as an example and integrate enterprise register information, litigation-related information, and enterprise announcement information to enrich the enterprise knowledge graph. For the unstructured text, we improve existing model to extract triples and the F1-score of our model reached 72.77%. The number of nodes and edges in our constructed enterprise knowledge graph reaches 1,430,000 and 3,170,000, respectively. Furthermore, for each type of multi-source heterogeneous data, we apply corresponding methods and strategies for information extraction and data storage and carry out a detailed comparative analysis of graph databases. From the perspective of practical use, the informative enterprise knowledge graph and its timely update can serve many actual business needs. Our proposed enterprise knowledge graph has been deployed in HuaRong RongTong (Beijing) Technology Co., Ltd. and is used by the staff as a powerful tool for corporate due diligence. The key features are reported and analyzed in the case study. Overall, this paper provides an easy-to-follow solution and practice for domain knowledge graph construction, as well as demonstrating its application in corporate due diligence

Lysine-specific demethylase 5C promotes hepatocellular carcinoma cell invasion through inhibition BMP7 expression

The primers used for the amplification of the indicated genes.(DOCX 17 kb

One-Loop Factorization of the Nucleon g_2-Structure Function in the Non-Singlet Case

We consider the one-loop factorization of the simplest twist-three process: inclusive deep-inelastic scattering of longitudinally-polarized leptons on a transversely-polarized nucleon target. By studying the Compton amplitudes for certain quark and gluon states at one loop, we find the coefficient functions for the non-singlet twist-three distributions in the factorization formula of g_2(x_B,Q^2). The result marks the first step towards a next-to-leading order (NLO) formalism for this transverse-spin-dependent structure function of the nucleon.Comment: 14 pages, revtex4, four figures included, minor change

A multi-terminal current differential protection setting method for fully weak-infeed distribution networks based on restricted enumeration method

With the high penetration connection of inverterinterfaced distributed generators and the increasing application of large-capacity energy routers, fully weak-infeed distribution networks consisting entirely of power-electronized weak-infeed power sources are set to become one of the fundamental forms of future distribution networks. For fully weak-infeed distribution networks, multi-terminal current differential protection is considered an optional or even preferred line protection scheme. In this paper, a multi-terminal current differential protection setting method for fully weak-infeed distribution networks is proposed based on the restricted enumeration method. To address the impact of data synchronization errors and measurement errors of multi-terminal current on differential current, the problem of determining the maximum differential current superimposed with the multi-terminal current phasor errors is transformed into a high-dimensional non-convex optimization problem. The distribution law of the global optimal solution in the non-convex constraint space is deeply studied and analyzed, and a restricted enumeration method is proposed that can quickly solve the protection setting value, thereby solving the problem of multi-terminal current differential protection setting. The accuracy and rapidity of the proposed method are verified by comparing the calculation accuracy and time consumption of the restricted enumeration method and the exhaustive search. It is shown that the proposed multi-terminal differential protection setting method exhibits sufficient reliability and sensitivity in fully weak-infeed distribution networks, as verified through simulation analysis using a fully weak-infeed distribution network model built in PSCAD/EMTDC

The evolutionary history of 2,658 cancers.

Cancer develops through a process of somatic evolution1,2. Sequencing data from a single biopsy represent a snapshot of this process that can reveal the timing of specific genomic aberrations and the changing influence of mutational processes3. Here, by whole-genome sequencing analysis of 2,658 cancers as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA)4, we reconstruct the life history and evolution of mutational processes and driver mutation sequences of 38 types of cancer. Early oncogenesis is characterized by mutations in a constrained set of driver genes, and specific copy number gains, such as trisomy 7 in glioblastoma and isochromosome 17q in medulloblastoma. The mutational spectrum changes significantly throughout tumour evolution in 40% of samples. A nearly fourfold diversification of driver genes and increased genomic instability are features of later stages. Copy number alterations often occur in mitotic crises, and lead to simultaneous gains of chromosomal segments. Timing analyses suggest that driver mutations often precede diagnosis by many years, if not decades. Together, these results determine the evolutionary trajectories of cancer, and highlight opportunities for early cancer detection

Inferring structural variant cancer cell fraction

Abstract: We present SVclone, a computational method for inferring the cancer cell fraction of structural variant (SV) breakpoints from whole-genome sequencing data. SVclone accurately determines the variant allele frequencies of both SV breakends, then simultaneously estimates the cancer cell fraction and SV copy number. We assess performance using in silico mixtures of real samples, at known proportions, created from two clonal metastases from the same patient. We find that SVclone’s performance is comparable to single-nucleotide variant-based methods, despite having an order of magnitude fewer data points. As part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) consortium, which aggregated whole-genome sequencing data from 2658 cancers across 38 tumour types, we use SVclone to reveal a subset of liver, ovarian and pancreatic cancers with subclonally enriched copy-number neutral rearrangements that show decreased overall survival. SVclone enables improved characterisation of SV intra-tumour heterogeneity

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts