Query：
学者姓名：鲍玲鑫
Refining：
Year
Type
Indexed by
Source
Complex
Co-Author
Language
Clean All
Abstract ：
Precisely measuring digital economy development is essential for optimizing regional spatial layouts and promoting coordinated growth. To address the limitations of traditional data sources and the weak integration of industrial structure in single remote sensing indicators, this study constructs a fusion index combining nighttime light (NTL) and point of interest (POI) data. Coupled with an Ε-support vector regression (Ε-SVR) model, this NTL&POI fusion index was used to estimate the digital economy index (DEI) for 367 Chinese cities during 2018–2023. The results reveal a marked improvement in urban digital economies: the proportion of starting-stage cities declined from 75 % to 58 %, while leading-stage cities more than doubled from 6 to 13. Spatially, an increasingly clustered distribution around core cities is indicated by the rise of global Moran's I from 0.235 to 0.381. Spatial imbalance remains significant, with an average annual Gini coefficient of 0.108, and between-region differences accounting for 40.60 % of the total variation. High-value clusters are concentrated in eastern coastal areas, whereas western regions lag behind. Increased spatial concentration is also evident from a contracting standard deviation ellipse, with the center of gravity remaining stable in Nanyang, Henan Province. This study proposes a novel spatial assessment framework for the digital economy using fused multi-source geospatial data as proxies. The findings offer empirical insights into the spatial dynamics and geographic restructuring of the digital economy in China and provide a foundation for targeted policymaking to foster cross-regional coordination, phased development, and integrated digital growth. © 2025
Keyword ：
Digital integrated circuits Digital integrated circuits Economic and social effects Economic and social effects Economics Economics Regional planning Regional planning Remote sensing Remote sensing Urban growth Urban growth
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Liu, Xiaojie , Zhang, Xiaowei , Chen, Honglong et al. Digital economy development assessment and spatiotemporal evolution at the urban level in China based on the NTL&POI fusion index [J]. | Geomatica , 2025 , 77 (2) . |
| MLA | Liu, Xiaojie et al. "Digital economy development assessment and spatiotemporal evolution at the urban level in China based on the NTL&POI fusion index" . | Geomatica 77 . 2 (2025) . |
| APA | Liu, Xiaojie , Zhang, Xiaowei , Chen, Honglong , Wang, Tingyan , Zhang, Jiadong , Zhang, Jinghua et al. Digital economy development assessment and spatiotemporal evolution at the urban level in China based on the NTL&POI fusion index . | Geomatica , 2025 , 77 (2) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Global warming has significantly increased the frequency and intensity of heatwaves, posing serious threats to the health of middle-aged and elderly adults. Hypertension is a common chronic disease that is profoundly affected by extreme heat. However, spatial variations in its relationship with heatwave exposure remain insufficiently studied. This study aims to evaluate the impact of heatwaves on hypertension and investigate its spatial heterogeneity. Utilizing data from the China Health and Retirement Longitudinal Study (CHARLS) from the baseline year (2015) to follow-up year (2018), we included 7152 participants aged 45 and older. Average heatwave intensity was employed as the exposure metric. Global logistic regression (GLR) models assessed the association between heatwave exposure and hypertension risk. Geographically weighted logistic regression (GWLR) models were utilized to examine the spatial variations in this relationship. The results show that heatwave exposure increased hypertension risk by 9.7% (odds ratio (OR) = 1.097, 95% CI = 1.016-1.185, P = 0.018). The GWLR models revealed significantly higher hypertension risk in southern China compared to northern regions, with OR values ranging from 1.027 to 1.120. Key risk factors for hypertension include marital status (excluding married/cohabiting, OR: 0.993-1.105), uneducated individuals (OR: 1.083-1.138), overweight/obese individuals (OR: 1.293-1.420), and fasting blood glucose (OR: 1.071-1.114). Conversely, a higher estimated glomerular filtration rate (eGFR) is considered to be a protective factor (OR: 0.848-0.987). No significant geographic correlations were found between hypertension risk and gender, residence, smoking, or drinking. This study found a significant spatial heterogeneity association between heatwave exposure and increased hypertension risk among middle-aged and older adults in China. Our findings underscore the need for targeted public health interventions, especially for high-risk populations during heatwaves.
Keyword ：
Average heatwave intensity Average heatwave intensity Cohort study Cohort study Geographically weighted logistic regression models Geographically weighted logistic regression models Hypertension Hypertension Spatial heterogeneity Spatial heterogeneity
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Chen, Honglong , Bao, Lingxin , Wang, Tingyan et al. Geographical specific association between heatwave intensity and the risk of new-onset hypertension among middle-aged and elderly adults [J]. | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY , 2025 , 69 (11) : 3215-3228 . |
| MLA | Chen, Honglong et al. "Geographical specific association between heatwave intensity and the risk of new-onset hypertension among middle-aged and elderly adults" . | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY 69 . 11 (2025) : 3215-3228 . |
| APA | Chen, Honglong , Bao, Lingxin , Wang, Tingyan , Liu, Xiaojie , Cai, Wenqin , Yao, Yuexian et al. Geographical specific association between heatwave intensity and the risk of new-onset hypertension among middle-aged and elderly adults . | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY , 2025 , 69 (11) , 3215-3228 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Orthostatic hypotension (OH) is defined as a decrease of >= 20 mm Hg systolic blood pressure (SBP) or >= 10 mm Hg diastolic blood pressure (DBP) within 3 min after standing. OH was associated with an increased risk of major adverse cardiovascular events (MACEs) and mortality. As an indicator reflecting the characteristics of orthostatic blood pressure (BP) changes, there is currently no research available on the relationship between the orthostatic BP drop rate and MACEs or mortality. A total of 448 hospitalized patients (mean age 62.07 +/- 12.15 years, 35.49% female) completed the follow-up. The median follow-up duration was 5.09 years (0.29-6.13 years). Ninety-two patients (20.54%) developed OH, 12 patients died (2.68%), and 21 patients developed MACEs (4.69%), including 8 cases of non-fatal acute myocardial infarction (MI), 3 cases of non-fatal stroke, and 10 cases died of cardiovascular disease and stroke. Patients were categorized into the BPdrop_rate_high group (defined as SBP drop rate >=>= 15% and/or DBP drop rate >=>= 5% within 3 min after standing) and the BPdrop_rate_normal group (defined as SBP drop rate << 15% and DBP drop rate << 5% within 3 min after standing). The Chi-square test and Kaplan-Meier survival analysis indicated that the BPdrop_rate_high group had a higher risk of MACEs and mortality than the BPdrop_rate_normal group (all p << 0.05). The Receiver Operating Characteristic (ROC) analysis demonstrated SBP drop rate >=>= 15% and/or DBP drop rate >=>= 5% within 3 min after standing has high diagnostic accuracy for OH, with an area under the curve (AUC) of 0.918.Cox regression analysis revealed that the cumulative survival rate of the BPdrop_rate_normal group was significantly higher than that of the BPdrop_rate_high group (98.45% vs. 93.69%, HR 0.304, 95% CI 0.095-0.969, p = 0.044). This study proposes a novel diagnostic threshold (SBP drop >= 15% and/or DBP drop >= 5% within 3 min after standing) for OH as a strong predictor of MACEs and mortality in hospitalized patients.
Keyword ：
blood pressure blood pressure cardiovascular risk cardiovascular risk diagnostic threshold diagnostic threshold mortality mortality orthostatic hypotension orthostatic hypotension
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Cai, Wenqin , Yao, Yuexian , Zheng, Suli et al. Relationship Between the Drop Rate of Standing Blood Pressure and Major Adverse Cardiovascular Events [J]. | JOURNAL OF CLINICAL HYPERTENSION , 2025 , 27 (5) . |
| MLA | Cai, Wenqin et al. "Relationship Between the Drop Rate of Standing Blood Pressure and Major Adverse Cardiovascular Events" . | JOURNAL OF CLINICAL HYPERTENSION 27 . 5 (2025) . |
| APA | Cai, Wenqin , Yao, Yuexian , Zheng, Suli , Chen, Wanting , Bao, Lingxin , Su, Jinzi et al. Relationship Between the Drop Rate of Standing Blood Pressure and Major Adverse Cardiovascular Events . | JOURNAL OF CLINICAL HYPERTENSION , 2025 , 27 (5) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Keyword ：
cardiovascular disease cardiovascular disease meta-analysis meta-analysis orthostatic hypotension orthostatic hypotension systematic review systematic review
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Chen, Wanting , Cai, Wenqin , Teng, Zhongming et al. Orthostatic Hypotension and Major Cardiovascular Diseases: A Systematic Review and Meta-Analysis [J]. | AMERICAN JOURNAL OF HYPERTENSION , 2025 , 38 (7) : 514-514 . |
| MLA | Chen, Wanting et al. "Orthostatic Hypotension and Major Cardiovascular Diseases: A Systematic Review and Meta-Analysis" . | AMERICAN JOURNAL OF HYPERTENSION 38 . 7 (2025) : 514-514 . |
| APA | Chen, Wanting , Cai, Wenqin , Teng, Zhongming , Bao, Lingxin . Orthostatic Hypotension and Major Cardiovascular Diseases: A Systematic Review and Meta-Analysis . | AMERICAN JOURNAL OF HYPERTENSION , 2025 , 38 (7) , 514-514 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
The reduction in agricultural carbon emissions (ACEs) in Shandong Province is essential to China's carbon peak and carbon neutrality objectives. In this regard, we constructed an ACE inventory for Shandong Province at a resolution of 1 km x 1 km, integrating the emission factor method with geographic information system (GIS) technology. Building upon this, we explored the dynamic evolution patterns of ACEs using kernel density estimation and conditional probability density estimation. Additionally, long short-term memory networks were trained to predict ACEs under various scenarios. The results showed that: (1) ACEs in Shandong Province exhibited two stages of change, i.e., "rise and decline". Notably, 64.39% of emissions originated from the planting industry. The distribution of emissions was closely correlated with regional agricultural production modes. Specifically, CO2 emissions were predominantly distributed in crop cultivation areas, while CH4 and N2O emissions were primarily distributed in livestock breeding areas. The uncertainty of the emission inventory ranged from -12.04% to 10.74%, mainly caused by emission factors. (2) The ACE intensity of various cities in Shandong Province is decreasing, indicating a decoupling between ACEs and agricultural economic growth. Furthermore, the emission disparities among different cities are diminishing, although significant spatial non-equilibrium still persists. (3) From 2022 to 2030, the ACEs in Shandong Province will show a continuous downward trend. By 2030, the projected values under the baseline scenario, low-carbon scenario I, and low-carbon scenario II will be 6301.74 x 104 tons, 5980.67 x 104 tons, and 5850.56 x 104 tons. The low-carbon scenario reveals greater potential for ACE reduction while achieving efficient rural economic development and urbanization simultaneously. This study not only advances the methodology of the ACE inventory but also provides quantitative references and scientific bases for promoting low-carbon, efficient, and sustainable regional agriculture.
Keyword ：
agricultural carbon emissions (ACE) agricultural carbon emissions (ACE) emission inventory emission inventory scenario projections scenario projections Shandong province Shandong province spatio-temporal evolution spatio-temporal evolution
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Gao, Chenxi , Hu, Qingping , Bao, Lingxin . Inventory, Dynamic Evolution, and Scenario Projections of Agricultural Carbon Emissions in Shandong Province, China [J]. | SUSTAINABILITY , 2024 , 16 (8) . |
| MLA | Gao, Chenxi et al. "Inventory, Dynamic Evolution, and Scenario Projections of Agricultural Carbon Emissions in Shandong Province, China" . | SUSTAINABILITY 16 . 8 (2024) . |
| APA | Gao, Chenxi , Hu, Qingping , Bao, Lingxin . Inventory, Dynamic Evolution, and Scenario Projections of Agricultural Carbon Emissions in Shandong Province, China . | SUSTAINABILITY , 2024 , 16 (8) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Crop diseases significantly impact yield and quality, posing a direct threat to food security. The application of Convolutional Neural Networks (CNN) in crop disease recognition has notably improved diagnosis accuracy and efficiency. This study presents an innovative crop disease classification model based on the VGG-16 network. Enhancements include the incorporation of Batch Normalization (BN) and a novel activation function synergizing with Exponential Linear Units (ELU), improving model convergence speed and accuracy. Additionally, Global Average Pooling (GAP) is integrated to streamline the network architecture, and the InceptionV2 module is introduced to extract leaf disease features from different dimensions, enhancing model robustness. Validation on the PlantVillage dataset shows an accuracy rate of 98.89%, demonstrating the model's competitiveness and its potential to support sustainable agricultural production.
Keyword ：
Convolutional neural network Convolutional neural network Crop disease Crop disease VGG-16 VGG-16
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Hong, Pengxiang , Luo, Xi , Bao, Lingxin . Crop disease diagnosis and prediction using two-stream hybrid convolutional neural networks [J]. | CROP PROTECTION , 2024 , 184 . |
| MLA | Hong, Pengxiang et al. "Crop disease diagnosis and prediction using two-stream hybrid convolutional neural networks" . | CROP PROTECTION 184 (2024) . |
| APA | Hong, Pengxiang , Luo, Xi , Bao, Lingxin . Crop disease diagnosis and prediction using two-stream hybrid convolutional neural networks . | CROP PROTECTION , 2024 , 184 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Empowering industrial green development with the digital economy represents a crucial approach to advancing the green transformation of China's economy and achieving high-quality economic development. Based on panel data from 279 cities in China from 2011 to 2021, this article uses the spatial econometrics model and threshold effect model to explore the spatial effect and nonlinearity of digital economy (DE) on industrial green development (IGD). The results show that, both DE and IGD exhibit fluctuating upward trends in China. There exists stronger spatial linkage effect in the eastern coastal areas, but this effect is weaker in the central and western regions. Furthermore, DE has significantly promoted IGD, and the conclusion remains robust after a series of endogeneity and robustness tests. Additionally, the promotion of the DE for IGD is characterized by regional spillovers and non-linear dynamics. The research results can serve as a theoretical support and decision-making basis for China to enhance industrial green development, promote the construction of an ecological civilization, and implement sustainable development strategies.
Keyword ：
digital economy digital economy industrial green development industrial green development spatial econometrics model spatial econometrics model threshold effect model threshold effect model
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Zhou, Mengxing , Zhang, Jinghua , Huang, Ling et al. Research on the spatio-temporal evolution and impact of China's industrial green development from the perspective of digital economy--based on analysis of 279 cities in China [J]. | ENVIRONMENTAL RESEARCH COMMUNICATIONS , 2024 , 6 (7) . |
| MLA | Zhou, Mengxing et al. "Research on the spatio-temporal evolution and impact of China's industrial green development from the perspective of digital economy--based on analysis of 279 cities in China" . | ENVIRONMENTAL RESEARCH COMMUNICATIONS 6 . 7 (2024) . |
| APA | Zhou, Mengxing , Zhang, Jinghua , Huang, Ling , Lu, Qiuping , Yuan, Huimei , Bao, Lingxin . Research on the spatio-temporal evolution and impact of China's industrial green development from the perspective of digital economy--based on analysis of 279 cities in China . | ENVIRONMENTAL RESEARCH COMMUNICATIONS , 2024 , 6 (7) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
A digital economy parallel with green development holds profound significance for achieving sustainability. The primary objective of this study was to explore the synergistic interaction effects between the digital economy and green development in China and forecast their future development. This study analyzed the spatio-temporal characteristics of provincial digital economy and green development in China by integrating a combined assignment method, an unconditional spatial kernel density estimation method, and a standard deviation ellipse model. The interplay between the digital economy and green development was examined using a panel vector autoregression model. Additionally, digital economy and green development levels were forecasted using univariate time series and radial basis function kernel epsilon-support vector regression models. The results indicate that both the digital economy and green development levels in China exhibited an upward trend from 2013 to 2021, with the digital economy increasing at a faster rate. However, both domains demonstrated regional disparities in their development processes. The mutual interaction between the digital economy and green development intensified as the lag period increased. The digital economy contributed 21% to green development, whereas green development contributed 18% to the digital economy. The initial effect of the digital economy on green development was negative, however, this impact gradually diminished over time. Additionally, the influence of green development on the digital economy was shown to follow a consistent trend of transitioning from negative to positive across the eastern, central, and western regions. Therefore, it can be seen that the digital economy exerts a sustainable impact on green development, albeit with a one-phase lag. This research provides a scientific basis for the deep integration of the digital economy and green development, thereby fostering sustainable socioeconomic growth.
Keyword ：
digital economy digital economy green development green development panel vector auto regression panel vector auto regression spatio-temporal characteristics spatio-temporal characteristics support vector regression support vector regression
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Chen, Tingting , Lu, Chunyan , Lai, Yuting et al. Spatio-Temporal Evolution and Interactive Relationship Between Digital Economy and Green Development in China [J]. | APPLIED SCIENCES-BASEL , 2024 , 14 (23) . |
| MLA | Chen, Tingting et al. "Spatio-Temporal Evolution and Interactive Relationship Between Digital Economy and Green Development in China" . | APPLIED SCIENCES-BASEL 14 . 23 (2024) . |
| APA | Chen, Tingting , Lu, Chunyan , Lai, Yuting , Zhou, Mengxing , Hu, Qingping , Wang, Tingyan et al. Spatio-Temporal Evolution and Interactive Relationship Between Digital Economy and Green Development in China . | APPLIED SCIENCES-BASEL , 2024 , 14 (23) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
Reducing carbon emissions in the transportation sector is a crucial aspect of China achieving its carbon peak and carbon neutrality goals. This study investigates the spatiotemporal differentiation characteristics of carbon emissions from transportation in the Yangtze River Economic Belt. Using the Geographically and Temporally Weighted Regression(GTWR) model to reveal the spatio-temporal heterogeneity of factors influencing transportation carbon emissions. Additionally, the Support Vector Regression(SVR) is trained to predict the carbon emissions reduction potential of transportation under different scenarios. The results showed that: From 2000 to 2021, the transportation emissions of the Yangtze River economic belt showed an overall upward trend. The high carbon emission regions are Jiangsu Province, Shanghai, Zhejiang Province and Hubei Province, and the emission center is located in Hubei Province. The total population, urbanization rate, per capita GDP, carbon emission intensity, passenger turnover volume, and civilian vehicle ownership all have a positive effect on transportation carbon emissions, while energy structure has a negative impact. Moreover, the influence of each factor exhibits significant spatial heterogeneity. Under three scenarios: baseline, low-carbon scenario I, and low-carbon scenario II, transportation carbon emissions in the Yangtze River Economic Belt are projected to peak by 2030. With the application of clean energy and a reduction in population size, low carbon scenario II demonstrates greater potential for carbon emission reduction, with a projected value of 88.552 million tons by 2032.
Keyword ：
geographically and temporally weighted regression geographically and temporally weighted regression support vector regression support vector regression transportation carbon emissions transportation carbon emissions Yangtze River Economic Belt Yangtze River Economic Belt
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | Liu, Rong , Yuan, Huimei , Chen, Wanting et al. Spatio-temporal heterogeneity and scenario prediction of influencing factors of transportation carbon emissions in the Yangtze River Economic Belt, China [J]. | ENVIRONMENTAL RESEARCH COMMUNICATIONS , 2024 , 6 (11) . |
| MLA | Liu, Rong et al. "Spatio-temporal heterogeneity and scenario prediction of influencing factors of transportation carbon emissions in the Yangtze River Economic Belt, China" . | ENVIRONMENTAL RESEARCH COMMUNICATIONS 6 . 11 (2024) . |
| APA | Liu, Rong , Yuan, Huimei , Chen, Wanting , Hu, Qingping , Zhou, Mengxing , Bao, Lingxin . Spatio-temporal heterogeneity and scenario prediction of influencing factors of transportation carbon emissions in the Yangtze River Economic Belt, China . | ENVIRONMENTAL RESEARCH COMMUNICATIONS , 2024 , 6 (11) . |
| Export to | NoteExpress RIS BibTex |
Version ：
Abstract ：
基于2007—2019年福建省九设区市的面板数据，采用组合赋权法、超效率SBM模型和Malmquist指数等研究方法，分别测度福建省基本公共服务均等化水平、公共服务供给效率和公共服务全要素生产率，并构建三者的面板向量自回归模型实证分析福建省基本公共服务均等化水平与公共服务供给效率之间的互动关系，进一步采用标准差椭圆分析二者的时空演变特征。研究发现：基本公共服务均等化水平的泰尔指数呈下降趋势，基本公共服务均等化整体发展较好，但厦门的基本公共服务均等化水平与其余城市的差距逐步拉大；九设区市的公共服务供给效率的演变趋势差异较大，仅漳州和厦门的公共服务供给效率大于1;公共服务全要素生产率整体呈下降趋势，下降的主要原因是技术进步变动指数的抑制作用；基本公共服务均等化水平与公共服务全要素生产率之间存在双向促进作用，公共服务供给效率对基本公共服务均等化水平具有单向抑制作用，基本公共服务均等化水平和公共服务供给效率均具有自我强化效应；基本公共服务均等化水平的重心迁移轨迹总体呈现出先向东部地区迁移、后向南部地区迁移的演变趋势，公共服务供给效率的重心迁移轨迹总体呈现出先向西南部地区迁移、后向东南部地区迁移的演变趋势；基本公共服务均等化水平尚未呈现出显著的空间集聚特征，公共服务供给效率则呈现出显著的空间集聚特征，二者均呈现出“东北—西南”的空间分布格局。据此提出，应进一步推进基本公共服务创新发展以提高基本公共服务供给水平，加大基本公共服务财政支出力度以提高公共服务供给效率，实施差异化区域发展策略以推进基本公共服务协同发展等，从而推进福建省公共服务高质量发展。
Keyword ：
公共服务供给效率 公共服务供给效率 公共服务全要素生产率 公共服务全要素生产率 基本公共服务均等化 基本公共服务均等化
Cite：
Copy from the list or Export to your reference management。
| GB/T 7714 | 卢秋萍 , 欧年青 , 高晨曦 et al. 福建省基本公共服务均等化水平与公共服务供给效率的互动关系及时空演变 [J]. | 福建农林大学学报(哲学社会科学版) , 2023 , 26 (06) : 76-90 . |
| MLA | 卢秋萍 et al. "福建省基本公共服务均等化水平与公共服务供给效率的互动关系及时空演变" . | 福建农林大学学报(哲学社会科学版) 26 . 06 (2023) : 76-90 . |
| APA | 卢秋萍 , 欧年青 , 高晨曦 , 鲍玲鑫 . 福建省基本公共服务均等化水平与公共服务供给效率的互动关系及时空演变 . | 福建农林大学学报(哲学社会科学版) , 2023 , 26 (06) , 76-90 . |
| Export to | NoteExpress RIS BibTex |
Version ：
Export
| Results： |
Selected to |
| Format： |
