A5100616062- Topic Modeling
- Plant Growth Enhancement Techniques
- Plant Stress Responses and Tolerance
- Impact of Technology on Adolescents
- COVID-19 and Mental Health
- Polymer-Based Agricultural Enhancements
- Growth and nutrition in plants
- Data Quality and Management
- Biomedical Text Mining and Ontologies
- Advanced Computational Techniques and Applications
- Hormonal Regulation and Hypertension
- Sleep and related disorders
- Psychological and Temporal Perspectives Research
- Video Surveillance and Tracking Methods
- Advanced Neural Network Applications
- Data Mining Algorithms and Applications
- Translation Studies and Practices
- Biometric Identification and Security
- Advanced Image and Video Retrieval Techniques
- Reproductive Physiology in Livestock
- Semantic Web and Ontologies
- Heavy Metals in Plants
- Plant Micronutrient Interactions and Effects
- Aluminum toxicity and tolerance in plants and animals
- Advanced Graph Neural Networks
Henan Agricultural University
2024
China Medical University
2021-2024
Ministry of Ecology and Environment
2023
Gannan Medical University
2023
Beijing University of Posts and Telecommunications
2022
Zhejiang University
2021
Jinzhou Medical University
2021
Shenyang University
2014
Salinity is an obstacle to global agriculture, as it affects plant growth and development. Chitosan (CTS) has been suggested a regulator alleviate environmental stresses. In this study, the morphological biochemical responses of chitosan application (75 mg L−1) on maize seedling under salt stress (150 mM) were conducted with hydroponic experiment. The results exhibited that CTS effectively recovered salt-inhibited biomass accumulation root architecture by increasing chlorophyll content...
Abstract The decommissioning and overall relocation of urban industrial enterprises have generated a large number decommissioned contaminated sites, the leftover soil pollution is gradually becoming major problem that restricts green development damages human health. Deep mining efficient management site information through digitization informatization are needed to solve these problems more accurately efficiently. Knowledge mapping for visual analysis relevant pathways forward‐looking...
3β-Hydroxysteroid dehydrogenase (3β-HSD) performs essential roles in the regulation of follicular development and level at which it is expressed may reflect steroidogenic capacity follicles their physiological status. The aim this study was to investigate expression 3β-HSD protein mRNA normal categorized by size into small (2 4 mm), medium (5 7 large (8 10 mm) cystic (> 21 mm). levels were evaluated western blotting quantitative real-time PCR, respectively; whereas, immunolocalization...
Object detection for aerial images has achieved remarkable progress in recent years. Nevertheless, most exiting studies do not differentiate oriented object from horizontal detection. Certain schemes ignore the ambiguity of representation and leverage label assignment designed directly. Consequently, it leads to unstable training causes performance degradation, because high-quality samples surrounding bounding boxes can be leveraged effectively. To address this problem, we propose a gliding...
This study assessed the relationships among cognitive risk, phone use behaviors, and sleep quality. We used a questionnaire, which included Pittsburgh Sleep Quality Index (PSQI), mobile behaviours, questionnaires on risk to gather information from 1204 college students. T-test, chi-square test, Wilcoxon signed rank test were applied differences in measurement data. Generalized linear regression analysis was analyze factors influencing The percentage of people with poor quality significantly...
Abstract Objectives: This study aimed to assess the influence of risk cognitive and characteristics mobile phones using on sleep quality during COVID-19 epidemic. Methods: We used Pittsburgh Sleep Quality Index (PSQI), phone use a questionnaire, which was answered by 1207 college students. The data were statistically analyzed with SPSS 21.0 software. Results: There significant differences in general poor groups (p=0.013 0.037, respectively) between before period. In PSQI scores there...