271 research outputs found
sj-docx-1-tct-10.1177_15330338231164191 - Supplemental material for Competitive Risk Model Nomogram to Predict Prognosis in Patients Aged Over 65 Years with nonmetastatic Cervical Cancer: A SEER Population-Based Study
No full textSupplemental material, sj-docx-1-tct-10.1177_15330338231164191 for Competitive Risk Model Nomogram to Predict Prognosis in Patients Aged Over 65 Years with nonmetastatic Cervical Cancer: A SEER Population-Based Study by Shengyuan Jiao, MS, Li Guo, PhD, Fei Da, PhD, Qiaohui Gao, MS, Zhenghua Ren, MS, JianyuWang, MS, Quanwei Fu, PhD, and Junye Liu, PhD in Technology in Cancer Research & Treatment</p
Why Cannot I Stop Phubbing? Boredom Proneness and Phubbing: A Multiple Mediation Model
No full textBin Gao,1,2,* Yuanyuan Liu,3,* Quanwei Shen,4 Changqing Fu,3 Weiyi Li,5 Xu Li4 1Research Institute for International and Comparative Education, Shanghai Normal University, Shanghai, 200234, People’s Republic of China; 2Lab for Educational Big Data and Policymaking, Shanghai Normal University, Shanghai, 200234, People’s Republic of China; 3Mental Health Center, Hubei University of Medicine, Shiyan, 442000, People’s Republic of China; 4School of Education, Shanghai Normal University, Shanghai, 200234, People’s Republic of China; 5School of Business Administration, Jimei University, Xiamen, 361021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Quanwei Shen, School of Education, Shanghai Normal University, 100 Guilin Road, Xuhui District, Shanghai, 200234, People’s Republic of China, Tel +86 13429962432, Email [email protected]: With the popularity of smartphone and their increasingly rich functions, people’s attachment to their phones is increasing. While people enjoy the convenience that smartphone bring (eg, accessing information and socializing), it also leads to problematic smartphone use (eg, phubbing). Previous research has shown that boredom proneness can trigger phubbing. However, the underlying psychological mechanisms are not yet clear.Methods: To address this research gap, we surveyed 556 Chinese college students (Mage = 18.89 years, SD = 1.18) during the COVID-19 pandemic and all participants completed a self-report questionnaire. Drawing the Interaction of Person-Affect-Cognition-Execution model (I-PACE) for addictive behaviors, this study developed and examined a multiple mediation model incorporating boredom proneness, loneliness, fear of missing out (FoMO), and phubbing.Results: (1) Boredom proneness could positively predict phubbing; (2) loneliness and FoMO mediated the relationship between boredom proneness and phubbing, respectively; and (3) loneliness and FoMO sequentially mediated the relationship between boredom proneness and phubbing.Conclusion: These findings are not only valuable for understanding the underlying mechanisms linking boredom proneness and phubbing, but also suggest that three types of interventions could be effectively used to decrease the risk of phubbing among college students, namely, reducing boredom proneness, relieving loneliness, and decreasing FoMO.Keywords: boredom proneness, loneliness, FoMO, phubbing, multiple mediation model, college student
Modelling Vertical Crustal Deformation in Time and Position Domains, Inferred from GPS Levelling
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Experimental Study on Anchoring Performance of Short-Lapped-Rebar Splices with Pre-Set Holes and Spiral Hoops
No full textThe precast concrete structure has the advantage of a short construction period, less labor consumption, and less pollution. The lapped-rebar splice is a type of connection for assembled reinforced concrete shear walls in the precast concrete structure. In this study, the anchoring performance of a short-lapped-rebar splice with a corrugated metal duct and spiral hoops is investigated. A total of 30 specimens were designed considering the influences of the rebar diameter and the lapped length, and the tension testing of the splice was carried out. The results show that the specimens with 0.15 times the suggested length in GB 50010-2010 fail by the fracture of rebar, while the specimens with 0.1 times and 0.05 times the suggested length show the pull-out failure of rebar. The ultimate bond strength of specimens with the suggested length is higher than that of the conventional specimens. The stress of the anchored rebar in the short-lapped-rebar splices is distributed symmetrically along the longitudinal direction. The maximum bond stress of the anchored rebar reaches 35 MPa, which is approximately 1.4 times that in the conventional specimens. A semi-empirical model for predicting the ultimate bond strength of the short-lapped-rebar splice is proposed, and it shows good agreement with tested values; the average error estimated from the proposed model is only 4.49%
Evaluating Polymer Representations via Quantifying Structure-Property Relationships
No full textMachine learning techniques are being applied in quantifying structure-property relationships for a wide variety of materials, where the properly representing materials plays key roles. Although algorithms for representation learning are extensively studied, their applications to domain-specific areas, such as polymer, are limited largely due to the lack of benchmark databases. In this work, we investigate different types of polymer representations, including Morgan Fingerprint (MF), molecular embedding (ME) and molecular graph (MG), based on a benchmark database from a subset of PolyInfo. We evaluate the quality of different polymer representations via quantifying the relationships between the representations and polymer properties, including density, melting temperature and glass transition temperature. Different representation learning schemes, such as supervised learning, semi-supervised learning and transfer learning, are investigated. It is found that ME outperforms the other representations for structure-property relationship quantification in all cases studied, and MG is shown to be much inferior than ME and MF, likely due to the relatively small volumes of training data available. For MEs, it is found that the similarities of substructure MEs under different learning schemes (e.g., SL, SSL and TL) are differently estimated, thus leading to different performance scores in structure-property relation quantification. Several ME mixtures have shown to outperform the single MEs in the corresponding regression tasks, and this is attributed to the information gain when mixing different ME
SMRT Sequencing Technology Was Used to Construct the Batocera horsfieldi (Hope) Transcriptome and Reveal Its Features
No full textBatocera horsfieldi (Hope) (Coleoptera: Cerambycidae) is an important forest pest in China that mainly infests timber and economic forests. This pest primarily causes plant tissue to necrotize, rot, and eventually die by feeding on the woody parts of tree trunks. To gain a deeper understanding of the genetic mechanism of B. horsfieldi, this study employed single-molecule real-time sequencing (SMRT) and Illumina RNA-seq technologies to conduct full-length transcriptome sequencing of the insect. Total RNA extracted from male and female adults was mixed and subjected to SMRT sequencing, generating a complete transcriptome. Transcriptome analysis, prediction of long non-coding RNA (lncRNA), coding sequences (CDs), analysis of simple sequence repeats (SSR), prediction of transcription factors, and functional annotation of transcripts were performed in this study. The collective 20,356,793 subreads (38.26 G, clean reads) were generated, including 432,091 circular consensus sequences and 395,851 full-length non-chimera reads. The full-length non-chimera reads (FLNC) were clustered and redundancies were removed, resulting in 39,912 consensus reads. SSR and ANGEL software v3.0 were used for predicting SSR and CDs. In addition, four tools were used for annotating 6058 lncRNAs, identifying 636 transcription factors. Furthermore, a total of 84,650 transcripts were functionally annotated in seven different databases. This is the first time that the full-length transcriptome of B. horsfieldi has been obtained using SMRT sequencing. This provides an important foundation for investigating the gene regulation underlying the interaction between B. horsfieldi and its host plants through gene editing in the future and provides a scientific basis for the prevention and control of B. horsfieldi
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