Association between body image dissatisfaction and body anthropometric indices among Chinese children and adolescents at different developmental stages

ObjectiveChildren at different developmental stages show different physical development and psychological cognitive characteristics and may pay different attention to body parts. The purpose of this study was to analyze the associations between body image dissatisfaction (BID) and body anthropometric indices (BAIs) among Chinese children and adolescents at different developmental stages.MethodsA total of 609 Chinese primary and secondary school students aged 8–15 years (329 boys and 280 girls) were selected using stratified cluster sampling. The students' body height, sitting height (SH), weight, chest circumference (CC), hip circumference (HC), waist circumference (WC), scapular skinfold thickness (SST), triceps skinfold thickness (TST), and abdominal skinfold thickness (AST) were measured. Boys' testicular volumes and first spermatorrhea and girls' breast measures and menarche were assessed using the Tanner stage standard. A body shape questionnaire (BSQ) was used to survey the subject's BID.ResultsIn boys with testicular volume < 4 ml, the hip-to-height ratio (HHR) was positively correlated with BSQ score (β = 8.17, P < 0.01). In boys with testicular volume ≥4 ml and nonfirst spermatorrhea, the HHR and SST were positively correlated with BSQ score (β = 2.51, P = 0.04; β = 4.98, P < 0.01). In boys with first spermatorrhea, weight was positively correlated with BSQ score (β = 10.30, P < 0.01). In girls with breast development < Tanner stage II, waist-to-height ratio (WHtR) was positively correlated with BSQ score (β = 5.12, P < 0.01); In girls with breast development ≥ Tanner stage II and nonmenarche, chest-to-sitting height ratio (CSHR) was positively correlated with BSQ score (β = 10.82, P < 0.01), and waist-to-hip ratio (WHR) was negatively correlated with BSQ score (β = −3.61, P = 0.04). In girls with menarche, WHtR and sitting height-to-height ratio (SHHR) were positively correlated with BSQ score (β = 6.09, P < 0.01; β = 2.05, P = 0.02).ConclusionThe associations between body image dissatisfaction and anthropometric indices among Chinese children and adolescents at different developmental stages are different

Progress in Research on the Structure and Activity of Polysaccharides from Chlorella

Chlorella contains a variety of polysaccharides with complex composition and structure, which are composed of various monosaccharides such as galactose, rhamnose, glucose, arabinose, mannose, xylose and glucuronic acid. The glycosidic linkages of polysaccharides are diverse, including α-1,6-glucose, β-1,3-galactose, α-1,6-galactose, α-1,3-rhamnose, α-1,2-rhamnose, α-1,5-arabinose, α-1,6-mannose and β-1,4-xylose. Some polysaccharides are modified by methylation, sulfation and acetylation. Meanwhile, many studies have shown that polysaccharides have multiple functions such as immunoregulatory, anti-inflammatory, antioxidant, anti-tumor, antibacterial and intestinal flora-regulatory effects. At present, monosaccharide composition analysis, methylation combined with gas chromatography-mass spectrometry (GC-MS) and two-dimensional nuclear magnetic resonance (2D-NMR) spectroscopy are mainly used for research on the structure of chlorella polysaccharides such as analysis of monosaccharide composition, glycosidic bond types, branch chain substitution positions and branch chain types. This review hopes to provide valuable information for the fine structural analysis and structure-activity relationship study of polysaccharides from Chlorella

STATISTICAL ANALYSIS OF THE AIRGAP OF OFFSHORE STRUCTURES

Ph.DDOCTOR OF PHILOSOPHY (FOE

Teaching Active Human Learners

Teaching humans is an important topic under the umbrella of machine teaching, and its core problem is to design an algorithm for selecting teaching examples. Existing work typically regards humans as passive learners, where an ordered set of teaching examples are generated and fed to learners sequentially. However, such a mechanism is inconsistent with the behavior of human learners in practice. A real human learner can actively choose whether to review a historical example or to receive a new example depending on the belief of her learning states. In this work, we propose a model of active learners and design an efficient teaching algorithm accordingly. Experimental results with both simulated learners and real crowdsourcing workers demonstrate that our teaching algorithm has better teaching performance compared to existing methods

ANALYSIS OF THE EXTREME WAVE ELEVATION DUE TO SECOND-ORDER DIFFRACTION AROUND A VERTICAL CYLINDER

10.1016/j.apor.2019.01.03786222-23

Driving forces of digital transformation in chinese enterprises based on machine learning

Abstract With advanced science and digital technology, digital transformation has become an important way to promote the sustainable development of enterprises. However, the existing research only focuses on the linear relationship between a single characteristic and digital transformation. In this study, we select the data of Chinese A-share listed companies from 2010 to 2020, innovatively use the machine learning method and explore the differences in the predictive effects of multi-dimensional features on the digital transformation of enterprises based on the Technology-Organization-Environment (TOE) theory, thus identifying the main drivers affecting digital transformation and the fitting models with stronger predictive effect. The study found that: first, by comparing machine learning and traditional linear regression models, it is found that the prediction ability of ensemble earning method is generally higher than that of tradition measurement method. For the sample data selected in this research, XGBoost and LightGBM have strong explanatory ability and high prediction accuracy. Second, compared with the technical driving force and environmental driving force, the organizational driving force has a greater impact. Third, among these characteristics, equity concentration and executives’ knowledge level in organizational dimension have the greatest impact on digital transformation. Therefore, enterprise managers should always pay attention to the decision-making role of equity concentration and executives’ knowledge level. This study further enriches the literature on digital transformation in enterprises, expands the application of machine learning in economics, and provides a theoretical basis for enterprises to enhance digital transformation

The Anti-Inflammatory Mechanism of Flaxseed Linusorbs on Lipopolysaccharide-Induced RAW 264.7 Macrophages by Modulating TLR4/NF-κB/MAPK Pathway

Flaxseed linusorbs (FLs), cyclic peptides derived from flaxseed oils, have shown multiple activities such as anticancer, antibacterial, and anti-inflammatory effects. However, the anti-inflammatory monomers of FLs and their mechanisms are still unclear. In this study, we have elucidated that FLs suppress the modulation of NF-κB/MAPK signaling pathways by targeting the inhibition of activating TLR4 in LPS-induced RAW 264.7 cells. Therefore, the transcription and expression of inflammatory cytokines (i.e., TNF-α, IL-1β, and IL-6) and inflammatory mediator proteins (i.e., iNos and Cox-2) were significantly suppressed by FLs. In addition, an in silico study discovered that eight monomers of FLs showed high-affinity bindings with TLR4. In silico data combined with HPLC results indicated that FLA and FLE, accounting for 44%, were likely the major anti-inflammatory monomers in FLs. In summary, FLA and FLE were proposed as the main anti-inflammatory active cyclopeptides via hindering TLR4/NF-κB/MAPK signaling pathways, suggesting the potential use of food-derived FLs as natural anti-inflammatory supplements in a daily diet

Room temperature test of the continuous spontaneous localization model using a levitated micro-oscillator

12siThe continuous spontaneous localization (CSL) model predicts a tiny break of energy conservation via a weak stochastic force acting on physical systems, which triggers the collapse of the wave function. Mechanical oscillators are a natural way to test such a force; in particular, a levitated micromechanical oscillator has been recently proposed to be an ideal system. We report a proof-of-principle experiment with a micro-oscillator generated by a microsphere diamagnetically levitated in a magnetogravitational trap under high vacuum. Due to the ultralow mechanical dissipation, the oscillator provides a new upper bound on the CSL collapse rate, which gives an improvement of two orders of magnitude over the previous bounds in the same frequency range, and partially reaches the enhanced collapse rate suggested by Adler. Although being performed at room temperature, our experiment has already exhibited advantages over those operating at low temperatures. Our results experimentally show the potential for a magnetogravitational levitated mechanical oscillator as a promising method for testing the collapse model. Further improvements in cryogenic experiments are discussed.openopenZheng, Di; Leng, Yingchun; Kong, Xi; Li, Rui; Wang, Zizhe; Luo, Xiaohui; Zhao, Jie; Duan, Chang-Kui; Huang, Pu; Du, Jiangfeng; Carlesso, Matteo; Bassi, AngeloZheng, Di; Leng, Yingchun; Kong, Xi; Li, Rui; Wang, Zizhe; Luo, Xiaohui; Zhao, Jie; Duan, Chang-Kui; Huang, Pu; Du, Jiangfeng; Carlesso, Matteo; Bassi, Angel