Generic structure and APPRAISAL resources in the editorial article Free money

Editorial is one of news genres aiming for opinion making and persuading. These functions determine that there are abundant evaluative resources in this genre. Exploring evaluative resources in the editorial could be conducive to understanding editorial text better and providing sensible suggestions for English learners to produce effectively persuasive writings. In view of this, the present study sets out to analyze the generic structure of the editorial Free money, then examine usage patterns of APPRAISAL resources in this text, and finally explore variations of APPRAISAL resources at different stages of the genre of this text. All APPRAISAL resources were coded based on APPRAISAL system and analyzed from quantitative and qualitative perspectives. It shows that Free money employed discussion genre with exposition and challenge embedded in the Background stage. An investigation into the usage of APPRAISAL resources found that negative ATTITUDE resources were mainly used to form the prosody of the text; more negation and concession resources within ENGAGEMENT were deployed to contract the dialogue; far more force raising GRADUATION resources were applied to amplify the evaluation. The APPRAISAL resources used at different stages of the editorial demonstrate distinct features with the aim of serving specific function of each stage. For instance, attribution resources were used in Issue stage to expand the dialogue and engage the readers; invoked resources were primarily employed in Background stage to make the statement objective; far more negative impressions in Side stage indicated the author’s concern, and more inscribed resources in Resolution stage manifested author’s attitude and made the conclusion impressive

Output prediction of alpha-type Stirling engines using gradient boosted regression trees and corresponding heat recovery system optimization based on improved NSGA-II

Climate change is becoming a pressing global concern, and the search for new energy and energy recovery technologies is becoming a worldwide research imperative. The broad adaptability of the Stirling engine to a wide variety of heat sources makes it a promising technology for industrial waste heat recovery and solar thermal generation. The operation of the Stirling engine involves a multi-physical coupled process of heat transfer and mechanics as well as non-linear losses due to mechanical friction and gas charge leaking. Therefore, accurate prediction of Stirling engine power output through theoretical analysis is complex and costly. Emerging machine learning algorithms like Gradient Boosted Regression Trees (GBRT) can offer new approaches to solve this problem. The GBRT model consists of multiple decision trees that branch by exhausting thresholds for all features under study to find the best split structure for data regression, and the principle of GBRT gives it the natural advantage of finding a wide range of distinguishing features and combinations, and a powerful generalization capability. A GBRT forecasting model is thus constructed to model the output power of Alpha-type Stirling engines. Test data from the General Motors 4L23 Stirling Engine are applied as the training and test set. Results from the random test set accounting for 25% of the total samples indicate that the GBRT model has a prediction accuracy of 96.23%. Furthermore, a regional microgrid containing Stirling engines, photovoltaic panels and batteries for industrial waste heat recovery is constructed and an evaluation system for energy supply performance is also established. Finally, based on the proposed power output model, multi-objective optimization based on improved NSGA-II is implemented, providing guidance for industrial application of Stirling engines

Potential susceptibility genes in patients with stage III and IV periodontitis: A whole-exome sequencing pilot study

The aim of this study was to screen potential susceptibility genes using whole-exome sequencing (WES) in 15 Han Chinese patients with stage III or IV periodontitis and to evaluate the quantity and quality of genomic DNA extracted from saliva. DNA was extracted from saliva epithelial cells, quality-tested, and then subjected to WES and bioinformatics analyses. All variation loci were analyzed and interpreted following the American College of Medical Genetics and Genomics (ACMG) criteria. Candidate pathogenic variation loci were identified and verified using Sanger sequencing. Correlation and functional analyses of the candidate genes were used to identify potential susceptibility genes in patients with severe periodontitis. LFNG, LENG8, NPHS1, HFE, ILDR1, and DMXL2 genes were identified in over two cases each with shared mutations. Following these analyses, the DMXL2 gene was identified as being associated with stage III and IV periodontitis. These results suggest a potential pathophysiological risk mechanism for periodontitis, but need to be verified through larger clinical studies and mechanistic experiments to determine the pathogenicity of these gene mutations and their generalizability to a wider population of periodontitis patients. By screening candidate pathogenic variation loci using WES in 15 Han Chinese patients with stage III or IV periodontitis, our study could provide a pipeline and feasibility support for the identification of susceptibility genes in patients with stage III and IV periodontitis

Genome Characterization and Phylogenetic Analysis of Bovine Hepacivirus in Inner Mongolia, Northeastern China

Bovine hepacivirus (BovHepV) is a new member of the genus Hepacivirus in the family Flaviviridae , which has been detected in cattle in more than seven countries. The purpose of this study was to identify and genetically characterize BovHepV in cattle in Inner Mongolia, northeastern (NE) China. A total of 116 serum samples from cattle were collected from HulunBuir in Inner Mongolia from April to May, 2021, and were divided into three pools for metagenomic sequencing. The samples were verified with semi-nested RT-PCR with primers based on the BovHepV sequences obtained from metagenomic sequencing. The complete genomes of BovHepV were amplified, and were used for genome characterization and phylogenetic analysis. BovHepV was detected in two pools through metagenomic sequencing. Five BovHepV positive samples were identified in Yakeshi of HulunBuir, thus indicating a prevalence of 8.8% (5/57). Two 8840 nucleotide long BovHepV strains YKS01/02 were amplified from the positive samples and showed 79.3%–91.9% nucleotide sequence identity with the discovered BovHepV strains. Phylogenetic analysis classified the YKS01/02 strains into BovHepV subtype G group. This study reports the first identification of BovHepV in cattle in northeastern China, and expands the known geographical distribution and genetic diversity of BovHepV in the country

PigBiobank: a valuable resource for understanding genetic and biological mechanisms of diverse complex traits in pigs

To fully unlock the potential of pigs as both agricultural species for animal-based protein food and biomedical models for human biology and disease, a comprehensive understanding of molecular and cellular mechanisms underlying various complex phenotypes in pigs and how the findings can be translated to other species, especially humans, are urgently needed. Here, within the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we build the PigBiobank (http://pigbiobank.farmgtex.org) to systematically investigate the relationships among genomic variants, regulatory elements, genes, molecular networks, tissues and complex traits in pigs. This first version of the PigBiobank curates 71 885 pigs with both genotypes and phenotypes from over 100 pig breeds worldwide, covering 264 distinct complex traits. The PigBiobank has the following functions: (i) imputed sequence-based genotype-phenotype associations via a standardized and uniform pipeline, (ii) molecular and cellular mechanisms underlying trait-associations via integrating multi-omics data, (iii) cross-species gene mapping of complex traits via transcriptome-wide association studies, and (iv) high-quality results display and visualization. The PigBiobank will be updated timely with the development of the FarmGTEx-PigGTEx project, serving as an open-access and easy-to-use resource for genetically and biologically dissecting complex traits in pigs and translating the findings to other species.National Natural Science Foundation of China [32022078]; National Key R&D Program of China [2022YFF1000900]; Local Innovative and Research Teams Project of Guangdong Province [2019BT02N630]; China Agriculture Research System [CARS-35]. Funding for open access charge: National Natural Science Foundation of China [32022078].info:eu-repo/semantics/publishedVersio

PigBiobank: a valuable resource for understanding genetic and biological mechanisms of diverse complex traits in pigs

© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] fully unlock the potential of pigs as both agricultural species for animal-based protein food and biomedical models for human biology and disease, a comprehensive understanding of molecular and cellular mechanisms underlying various complex phenotypes in pigs and how the findings can be translated to other species, especially humans, are urgently needed. Here, within the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we build the PigBiobank (http://pigbiobank.farmgtex.org) to systematically investigate the relationships among genomic variants, regulatory elements, genes, molecular networks, tissues and complex traits in pigs. This first version of the PigBiobank curates 71 885 pigs with both genotypes and phenotypes from over 100 pig breeds worldwide, covering 264 distinct complex traits. The PigBiobank has the following functions: (i) imputed sequence-based genotype-phenotype associations via a standardized and uniform pipeline, (ii) molecular and cellular mechanisms underlying trait-associations via integrating multi-omics data, (iii) cross-species gene mapping of complex traits via transcriptome-wide association studies, and (iv) high-quality results display and visualization. The PigBiobank will be updated timely with the development of the FarmGTEx-PigGTEx project, serving as an open-access and easy-to-use resource for genetically and biologically dissecting complex traits in pigs and translating the findings to other species.National Natural Science Foundation of China [32022078]; National Key R&D Program of China [2022YFF1000900]; Local Innovative and Research Teams Project of Guangdong Province [2019BT02N630]; China Agriculture Research System [CARS-35]. Funding for open access charge: National Natural Science Foundation of China [32022078].Peer reviewe

EDET: Entity Descriptor Encoder of Transformer for Multi-Modal Knowledge Graph in Scene Parsing

In scene parsing, the model is required to be able to process complex multi-modal data such as images and contexts in real scenes, and discover their implicit connections from objects existing in the scene. As a storage method that contains entity information and the relationship between entities, a knowledge graph can well express objects and the semantic relationship between objects in the scene. In this paper, a new multi-phase process was proposed to solve scene parsing tasks; first, a knowledge graph was used to align the multi-modal information and then the graph-based model generates results. We also designed an experiment of feature engineering’s validation for a deep-learning model to preliminarily verify the effectiveness of this method. Hence, we proposed a knowledge representation method named Entity Descriptor Encoder of Transformer (EDET), which uses both the entity itself and its internal attributes for knowledge representation. This method can be embedded into the transformer structure to solve multi-modal scene parsing tasks. EDET can aggregate the multi-modal attributes of entities, and the results in the scene graph generation and image captioning tasks prove that EDET has excellent performance in multi-modal fields. Finally, the proposed method was applied to the industrial scene, which confirmed the viability of our method

Intelligent Safety Assessment of Prestressed Steel Structures Based on Digital Twins

In the development process of intelligent construction, the safety assessment of prestressed steel structures as an important research direction has become more and more attractive in academia. Digital twins (DTs) is the key technology to realize intelligent construction. The virtual and real interaction of the DTs can provide an efficient management and control mechanism for the construction process. This research proposes an intelligent safety assessment method of prestressed steel structures based on DTs. In this research method, the structural safety assessment is divided into two aspects: performance analysis and maintenance. By analyzing the characteristics of the construction safety assessment, a DTs framework for construction safety assessment is built. Driven by the DTs framework, a physical space model and a virtual space model are constructed. On the basis of virtual and actual interaction, multidimensional information fusion of time and space is carried out to realize the analysis of structural safety performance. On this basis, the paper establishes a Bow-tie model for the maintenance modeling of unsafe construction events. Moreover, the theoretical method formed is applied to the construction of a symmetrical structure (wheel–spoke cable truss). The validity of the method is verified by comparing the cable force calculated by the theoretical method and measured on site. The assessment method driven by the DTs ensures the structural safety and improves the intelligence level of safety management and control of the structure construction