Zhiliang Ying
Biographic Data
| ID | 134352 |
|---|---|
| NAME | Zhiliang Ying |
| GIVEN NAMES | Zhiliang |
| FAMILY NAME | Ying |
| SIGNATURE | YING Z |
| AFFILIATIONS | Columbia University |
| ORCID | 0000-0001-6228-5433 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2010 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Enhancing Student Satisfaction With the Practical Relevance of Teacher Training for Early Childhood Preservice Educators in China
This study aims to develop a comprehensive framework to assess the level of satisfaction among students in their fourth year of undergraduate studies specializing in early childhood education in China during their practical teacher training (PTT). Drawing upon customer satisfaction theory and pertinent literature, the research employs factor analysis and structural equation modeling to discern and scrutinize pivotal variables contributing to stud…
Examining the Interaction Effects Among Multiple Terminals in an Online Q&A Community
The rapid proliferation of multiple terminals in online communities has significantly transformed user behavior, making the effective management of these terminals crucial for user acquisition, retention, activation, and conversion. Despite the growing importance of multi-terminal environments, existing research has largely overlooked the interaction effects among terminals. To address this gap, this study investigates how multiple terminals inte…
Mining semantic information of co-word network to improve link prediction performance
New insights into scaling of fat‐free mass to height across children and adults
OBJECTIVE: Forbes expressed fat-free mass (FFM, in kg) as the cube of height (H, in m): FFM = 10.3 × H(3). Our objective is to examine the potential influence of gender and population ancestry on the association between FFM and height. METHODS: This is a cross-sectional analysis involving an existing dataset of 279 healthy subjects (155 males and 124 females) with age 5-59 years and body mass index (BMI) 14-28 kg/m(2). FFM was measured by a four-…
Evaluation of specific metabolic rates of major organs and tissues
OBJECTIVES: The specific resting metabolic rates (K(i) , in kcal/kg per day) of major organs and tissues in the Reference Man were suggested in 1992 by Elia: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue and 12 for the residual mass. However, it is unknown whether gender influences the K(i) values. The aim of the present study was to compare the K(i) values observed in nonelderly nonobese …
A cellular level approach to predicting resting energy expenditure
We previously derived a cellular level approach for a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging (MRI) combined with their individual cellularity and assumed stable-specific resting metabolic rates. Although this approach predicts REE well in both young and elderly adults, there were no studies in adolescents that specifically evaluated REE in relation to orga…
No prominent works on this page.
A cellular level approach to predicting resting energy expenditure
We previously derived a cellular level approach for a whole-body resting energy expenditure (REE) prediction model by using organ and tissue mass measured by magnetic resonance imaging (MRI) combined with their individual cellularity and assumed stable-specific resting metabolic rates. Although this approach predicts REE well in both young and elderly adults, there were no studies in adolescents that specifically evaluated REE in relation to orga…
Evaluation of specific metabolic rates of major organs and tissues
OBJECTIVES: The specific resting metabolic rates (K(i) , in kcal/kg per day) of major organs and tissues in the Reference Man were suggested in 1992 by Elia: 200 for liver, 240 for brain, 440 for heart and kidneys, 13 for skeletal muscle, 4.5 for adipose tissue and 12 for the residual mass. However, it is unknown whether gender influences the K(i) values. The aim of the present study was to compare the K(i) values observed in nonelderly nonobese …
New insights into scaling of fat‐free mass to height across children and adults
OBJECTIVE: Forbes expressed fat-free mass (FFM, in kg) as the cube of height (H, in m): FFM = 10.3 × H(3). Our objective is to examine the potential influence of gender and population ancestry on the association between FFM and height. METHODS: This is a cross-sectional analysis involving an existing dataset of 279 healthy subjects (155 males and 124 females) with age 5-59 years and body mass index (BMI) 14-28 kg/m(2). FFM was measured by a four-…
Mining semantic information of co-word network to improve link prediction performance
Enhancing Student Satisfaction With the Practical Relevance of Teacher Training for Early Childhood Preservice Educators in China
This study aims to develop a comprehensive framework to assess the level of satisfaction among students in their fourth year of undergraduate studies specializing in early childhood education in China during their practical teacher training (PTT). Drawing upon customer satisfaction theory and pertinent literature, the research employs factor analysis and structural equation modeling to discern and scrutinize pivotal variables contributing to stud…
Examining the Interaction Effects Among Multiple Terminals in an Online Q&A Community
The rapid proliferation of multiple terminals in online communities has significantly transformed user behavior, making the effective management of these terminals crucial for user acquisition, retention, activation, and conversion. Despite the growing importance of multi-terminal environments, existing research has largely overlooked the interaction effects among terminals. To address this gap, this study investigates how multiple terminals inte…
Medicine (4 works) · Body Composition Measurement Techniques (3 works) · Body mass index (3 works) · Internal Medicine (3 works) · Body weight (2 works) · Confidence interval (2 works) · Diet and metabolism studies (2 works) · Endocrinology (2 works) · Fat free mass (2 works) · Fat mass (2 works)