Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
210
result(s) for
"Zheng, Xinli"
Sort by:
China's 40 years of economic reform and development : how the miracle was created
This book aims to explain the secret to China's rapid growth over the last 40 years from the viewpoint of a firsthand witness. Zheng Xinli was enrolled as a graduate student of economics 40 years ago, at a time when very few Chinese people could enroll in higher-level education, let alone graduate school. Since 1978, he has been engaged in the study of macroeconomic theory and economic policy. He has worked with the economic group of the Research Section of the Secretariat of the Central Committee of the Communist Party of China, the State Information Center, and the Policy Research Office of the State Planning Commission, as well as other organizations. His work serves to help Chinese leaders in making economic decisions. In 2013, Zheng Xinli appeared on the list of China's Top Ten Economists. With the addition of several up-to-date articles, this book is mainly a condensed version of a 16-volume collection of essays selected from among the more-than-500 articles published by Zheng between 1981 and 2016. Addressing some of the major issues in China, namely, Reform and Development, Development Patterns, Macro Regulation, Balanced Urban and Rural Development, Innovation, and Industry Revitalization, the book, as Zheng himself puts it, visualizes the birth process of different polices and measures which have catered to the different stages of reform. As an insider, and also partly as a designer and architect, Zheng Xinli provides readers with a view of China's reform from the top. -- Provided by publisher.
Book
Small Target Detection in Refractive Panorama Surveillance Based on Improved YOLOv8
Panoramic imaging is increasingly critical in UAVs and high-altitude surveillance applications. In addressing the challenges of detecting small targets within wide-area, high-resolution panoramic images, particularly issues concerning accuracy and real-time performance, we have proposed an improved lightweight network model based on YOLOv8. This model maintains the original detection speed, while enhancing precision, and reducing the model size and parameter count by 10.6% and 11.69%, respectively. It achieves a 2.9% increase in the overall mAP@0.5 and a 20% improvement in small target detection accuracy. Furthermore, to address the scarcity of reflective panoramic image training samples, we have introduced a panorama copy–paste data augmentation technique, significantly boosting the detection of small targets, with a 0.6% increase in the overall mAP@0.5 and a 21.3% rise in small target detection accuracy. By implementing an unfolding, cutting, and stitching process for panoramic images, we further enhanced the detection accuracy, evidenced by a 4.2% increase in the mAP@0.5 and a 12.3% decrease in the box loss value, validating the efficacy of our approach for detecting small targets in complex panoramic scenarios.
Journal Article
Single-cell nuclear RNA-sequencing reveals dynamic changes in breast muscle cells during the embryonic development of Ding'an goose
Breast muscle is a crucial trait in poultry meat production. Previous studies have identified embryonic day 15 (E15), E21, and E31 as key time points in the breast muscle development of Ding'an goose, yet the specific molecular mechanisms remain unclear. In this study, we analyzed cellular heterogeneity and molecular dynamics at 15th day of embryonic breast muscle of Dingan goose (E15), E21, and E31 by using single-nucleus RNA-sequencing (snRNA-seq) technology. Nine types of cells were discovered, including fibroblast adipogenic progenitor cells (FAPs), myocytes and muscle stem cells (MuSCs), with notable differences among the three developmental stages in terms of cell type and abundance: FAPs and MuSCs gradually decreased from 42.3% and 35.6% (E15) to 15.7% and 12.2% (E31), respectively, while myocytes increased from 18.5% (E15) to 70.1% (E31). Additionally, the distinct heterogeneity of myocytes, MuSCs and FAPs was determined based on the analysis of gene regulatory networks for each cluster. Developmental trajectory analysis identified genes related to the function and development of MuSCs. The identified differentially expressed genes elucidate the molecular mechanisms of cellular dynamic changes during breast muscle development. This study generated a nuclear profile for single muscle cells that played a key role in the development of breast muscle in Ding'an goose embryos. We investigated metabolic changes at the cellular level during three key developmental stages, thereby refining our understanding of the molecular mechanisms underlying pectoral muscle development specifically in embryonic Ding'an goose.
Journal Article
Numerical study on solar photovoltaic/thermal system with tesla valve
In recent years, photovoltaic/thermal (PV/T) systems have played a crucial role in reducing energy consumption and environmental degradation, nonetheless, the low energy conversion efficiency presents a considerable obstacle for PV/T systems. Therefore, improving heat conversion efficiency is essential to enhance energy efficiency. In this paper, the PV/T system with the Tesla valve is proposed to solve this problem. Firstly, the cooling effect is simulated and analyzed in the system with four different flow channel structures: semicircle, rectangle, triangle and Tesla valve. The results indicate that the system with the Tesla valve exhibits superior cooling performance. Subsequently, several factors including angle, valve number, valve type, and pipe diameter ratio for the Tesla valve are further studied through numerical and simulation analysis. The results reveal that Tesla valves demonstrate optimal cooling performance when possessing the following structural parameters: complete symmetry, more valves, a 30-degree angle and a pipe diameter ratio of 1. Finally, four different types of fluid are selected to explore the Tesla valve. The conclusion shows that nanofluids with high density, low specific heat, and high thermal conductivity also improve the cooling performance. Thus, the PV/T system with the Tesla valve exhibits good heat dissipation and energy storage efficiency, electrical efficiency can reach 16.32% and thermal efficiency reach 59.65%.
Journal Article
Rapid high-throughput isolation and purification of chicken myoblasts based on deterministic lateral displacement microfluidic chips
Myoblasts are defined as stem cells containing skeletal muscle cell precursors. However, there are some challenges associated with the purification of myoblast samples, including long culture times and ease of bacterial contamination. In this study, we propose a microfluidic myoblast cell enrichment and purification platform based on the principle of deterministic lateral displacement (DLD). To achieve this, we designed a DLD chip with three outlets and tested it on 11-day-old (E11) Wenchang chicken pectoral muscle tissue. A cell suspension was prepared using the collagenase method, pretreated, and then passed into the designed DLD chip for myoblast enrichment and purification. In this study, the number of myoblasts and the diameter of myoblasts increased slowly before E9, and the diameter of myofibers decreased and the number of myofibers increased rapidly after E9. The period when the muscle fibers are most numerous is on the E12, and the period when the diameter of the muscle fibers begins to increase again after reaching its lowest point is also on the E12. After E12, the diameter of the muscle fibers increased and the number of muscle fibers decreased. At E12, myoblasts clustered and fused, and the proliferation of myoblasts was greatly reduced. E12 is both intact myoblasts and the most vigorous proliferation period, so the best time to determine isolation is E12. We attained a myoblast cell recovery rate of 80%, a target outlet collection purity of 99%, and a chip throughput of 50 μ m/min. In this paper, we innovate chips design according to specific geometries and functions for Wenchang chicken pectoral muscle tissue, so as to optimize the isolation and purification process of myoblasts. This study provides a novel and effective method for the isolation and purification of skeletal muscle myoblasts.
Journal Article
The Connection Between Lipid Metabolism in the Heart and Liver of Wuzhishan Pigs
Lipid metabolism is critical for the physiological activities of signal transduction, metabolic regulation, and energy provision, and Wuzhishan (WZS) pigs are a promising animal model for studying human diseases. However, lipid metabolites in the heart and liver of WZS pigs are indistinct. In this study, we detected gene expression, blood biochemical parameters, and metabolic profiles of hearts and livers of WZS and Large White (LW) pigs, and analyzed correlations between metabolites. The results showed that the fatty acid metabolic process was present in both the heart and liver, and was more dominant in the liver. Although the expression of lipid absorption-related genes of CYP7A1 increased in the liver, CEBPB levels increased in both the liver and heart; the fatty acid beta-oxidation genes RXRA and ACSS2 also showed increased expression. The quantity of metabolites related to lipid synthesis decreased in the liver, heart, and blood for WZS pigs compared to that of LW pigs, indicating a balance of lipid synthesis and breakdown for WZS pigs. Moreover, the lipid metabolites in the liver and heart exhibited strong correlations with each other and showed similar correlations to blood biochemical parameters, respectively. This study declared the balance of lipid metabolism in both the heart and liver, and identified their connections for WZS pigs.
Journal Article
METTL14 regulates proliferation and differentiation of duck myoblasts through targeting MiR-133b
The development of duck pectoral muscle has a significant impact on meat quality, and miRNA and m6A modification play key roles in this process. In the early stage, by using MeRIP-seq and miRNA-seq to analyze the pectoral muscle tissue of duck embryos at day 13 (E13), day 19 (E19), and day 27 (E27) of incubation, we found that METTL14, as a core component of the m6A methylation transferase complex, showed significant differences in expression at different developmental stages and may have an important impact on pectoral muscle development. In this study, qRT-PCR detection revealed that the expression of proliferation and differentiation marker genes CDK2, CyclinD1, MYOG and MYHC varied at different stages, with the highest m6A level at E13 and the lowest expression of METTL14 at the same stage. After constructing overexpression and interference vectors for METTL14, we found that METTL14 interference promoted the proliferation of duck embryo myoblasts and inhibited differentiation, while overexpression inhibited proliferation and accelerated differentiation. In particular, the overexpression of METTL14 increased the expression of miR-133b, whose precursor sequence contains m6A modification sites, suggesting that METTL14 may participate in the regulation of muscle development by affecting the expression of miR-133b. This study provides new insights into the molecular mechanisms of duck pectoral muscle development and offers potential molecular targets for the genetic improvement of duck pectoral muscle.
Journal Article
CPSF4-mediated regulation of alternative splicing of HMG20B facilitates the progression of triple-negative breast cancer
Background
Aberrant alternative splicing (AS) contributes to tumor progression. A crucial component of AS is cleavage and polyadenylation specificity factor 4 (CPSF4). It remains unclear whether CPSF4 plays a role in triple-negative breast cancer (TNBC) progression through AS regulation. In this study, our objective is to investigate the prognostic value of CPSF4 and pinpoint pivotal AS events governed by CPSF4 specifically in TNBC.
Methods
We examined the expression levels and prognostic implications of CPSF4 in patients diagnosed with TNBC through public databases. CPSF4-interacting transcripts, global transcriptome, and alternative splicing were captured through RNA immunoprecipitation sequencing (RIP-seq) and RNA sequencing (RNA-seq). The top 10 CPSF4-regulated alternative splicing events (ASEs) were validated using qRT-PCR. TNBC cells transfected with high mobility group 20B (HMG20B) siRNA were subjected to CCK-8 and transwell assays.
Results
In TNBC, CPSF4 exhibited heightened expression levels and was correlated with unfavorable prognosis. Overexpression of CPSF4 significantly promoted colony formation and migration, whereas knockdown of CPSF4 had the opposite effect. Inhibition of CPSF4 altered the transcriptome profile of MDA-MB-231 cells. CPSF4-regulated numerous genes showed enrichment in cancer-related functional pathways, including mRNA processing, cell cycle, RNA transport, mRNA surveillance pathway, and apoptosis. CPSF4-regulated ASEs were highly validated by qRT-PCR. CPSF4 modulated selective splicing events by inhibiting alternative 3′ splice site events of HMG20B and promoted cell proliferation, migration, and invasion.
Conclusion
CPSF4 promotes TNBC progression by regulating AS of HMG20B. These findings contribute to the development of more useful prognostic, diagnostic and potentially therapeutic biomarkers for TNBC.
Journal Article
Solar Radiation Prediction Based on the Sparrow Search Algorithm, Convolutional Neural Networks, and Long Short-Term Memory Networks
With the challenge of increasing global carbon emissions and climate change, the importance of solar energy as a clean energy source is becoming more pronounced. Accurate solar radiation prediction is crucial for planning and operating solar energy systems. However, the accurate measurement of solar radiation faces challenges due to the high cost of instruments, strict maintenance, and technical complexity. Therefore, this paper proposes a deep learning approach that integrates the Sparrow Search Algorithm (SSA), Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks for solar radiation forecasting. The study utilizes solar radiation data from Songjiang District, Shanghai, China, from 2019 to 2020 for empirical analysis. Initially, a correlation analysis was conducted to identify the main factors affecting the intensity of solar radiation, including temperature, clear-sky GHI, solar zenith angle, and relative humidity. Subsequently, the forecasting effectiveness of the model was compared on datasets of 10 min, 30 min, and 60 min, revealing that the model performed best on the 60 min dataset, with a determination coefficient (R2) of 0.96221, root mean square error (RMSE) of 65.9691, and mean absolute error (MAE) of 37.9306. Moreover, comparative experimental results show that the SSA-CNN-LSTM model outperforms traditional LSTM, BiLSTM, and CNN-LSTM models in forecasting accuracy, confirming the effectiveness of SSA in parameter optimization. Thus, the SSA-CNN-LSTM model provides a new and efficient tool for solar radiation forecasting, which is of significant importance for the design and management of solar energy systems.
Journal Article
Multi-Modal Sentiment Analysis Based on Interactive Attention Mechanism
In recent years, multi-modal sentiment analysis has become more and more popular in the field of natural language processing. Multi-modal sentiment analysis mainly concentrates on text, image and audio information. Previous work based on BERT utilizes only text representation to fine-tune BERT, while ignoring the importance of nonverbal information. Most current research methods are fine-tuning models based on BERT that do not optimize BERT’s internal structure. Therefore, in this paper, we propose an optimized BERT model that is composed of three modules: the Hierarchical Multi-head Self Attention module realizes the hierarchical extraction process of the features; the Gate Channel module replaces BERT’s original Feed-Forward layer to realize information filtering; the tensor fusion model based on self-attention mechanism utilized to implement the fusion process of different modal features. In CMU-MOSI, a public mult-imodal sentiment analysis dataset, the accuracy and F1-Score were improved by 0.44% and 0.46% compared with the original BERT model using custom fusion. Compared with traditional models, such as LSTM and Transformer, they are improved to a certain extent.
Journal Article