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学者姓名：徐学荣
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Abstract ：
基于“三圈理论”分析框架，利用对陕西咸阳SG村、福建福州YZ村和厦门D村的调研访谈数据，分析乡村治理积分制的运行机制及其现实困境。结果表明：乡村治理积分制有效运行需要价值、能力和支持等3个维度的协同支撑。价值维度需契合乡村公共价值导向，具体体现在增强乡村凝聚力与向心力、引导多元共治格局、促进乡风文明建设及提升治理效能等方面；能力维度需具备相应资源与能力，如必要的资金供给、基层治理组织的能力建设、数字基建与人才支撑；支持维度需得到村民、村干部、政府部门和社会力量等利益相关者的支持。在当前乡村治理积分制运行中，“价值圈”存在公共价值偏离，“能力圈”存在基层治理资源和能力建设不足问题，“支持圈”面临利益相关者行动支持不足的挑战。据此，建议重塑积分制的公共价值导向、强化资源保障与能力建设体系、构建多元主体协同参与的激励机制，以推动乡村治理积分制的可持续发展。
Keyword ：
“三圈理论” “三圈理论” 乡村治理 乡村治理 数字技术 数字技术 积分制 积分制
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| GB/T 7714 | 马改艳 , 徐学荣 . 乡村治理积分制的运行机制、现实困境与破解策略——基于“三圈理论”的解释框架 [J]. | 农林经济管理学报 , 2025 , 24 (02) : 185-194 . |
| MLA | 马改艳 等. "乡村治理积分制的运行机制、现实困境与破解策略——基于“三圈理论”的解释框架" . | 农林经济管理学报 24 . 02 (2025) : 185-194 . |
| APA | 马改艳 , 徐学荣 . 乡村治理积分制的运行机制、现实困境与破解策略——基于“三圈理论”的解释框架 . | 农林经济管理学报 , 2025 , 24 (02) , 185-194 . |
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基于当前农业绿色生产的重要发展背景,以福建省内六地市314 个葡萄种植户的微观调查数据为支撑,运用面向投入规模报酬可变的DEA模型测度农户技术效率水平,并构建Tobit模型,实证避雨栽培的绿色生产模式下经营规模对农户技术效率的影响.结果表明:适度规模化经营有助于农户提高绿色生产的技术效率,葡萄种植面积的适度区间为 0.67～3.33 hm2,但随着经营规模增加,要素配置难度和雇工道德风险上升将会给农户造成一定的效率损失.因此,农户在实际生产中应根据自身要素禀赋状况选择合适的经营规模,不宜盲目扩张.
Keyword ：
技术效率 技术效率 经营规模 经营规模 绿色生产 绿色生产 要素错配 要素错配 道德风险 道德风险
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| GB/T 7714 | 宋芳 , 徐学荣 . 绿色生产背景下经营规模对农户技术效率的影响研究 [J]. | 黑龙江八一农垦大学学报 , 2024 , 36 (2) : 113-120 . |
| MLA | 宋芳 等. "绿色生产背景下经营规模对农户技术效率的影响研究" . | 黑龙江八一农垦大学学报 36 . 2 (2024) : 113-120 . |
| APA | 宋芳 , 徐学荣 . 绿色生产背景下经营规模对农户技术效率的影响研究 . | 黑龙江八一农垦大学学报 , 2024 , 36 (2) , 113-120 . |
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柚产业是福建省漳州市平和县的支柱产业，为分散当地柚生产的经营风险，基于福建省漳州市平和县1985-2022年柚产量及对应年份3月中旬至8月上旬的天气数据，将柚单产数据分解成趋势单产和气象单产，并调整单产数据使其转化到2024年的生产力水平下的单产，选用核密度估计法拟合该序列的概率密度函数并用于纯费率厘定；而后利用调整后单产数据和天气数据进行相关性分析，筛选显著的天气指数。结果显示：4月中下旬降雨量指数与调整后单产的线性关系最为显著。对于2024年约定的保障产量51 000 kg·hm~(-2)和保险价格2.8元·kg~(-1)，即每667m2保险金额为9 520元，厘定纯费率为4.019 1%、保险费率为4.622 0%；对于降雨量指数RI的保险赔付触发值160 mm以及RI的8个分级赔付区间，分别计算得到了对应的赔付事件发生概率，并给出了对应的赔付金额计算公式。
Keyword ：
保险赔付 保险赔付 天气指数保险 天气指数保险 柚单产 柚单产 费率厘定 费率厘定 降雨量指数 降雨量指数
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| GB/T 7714 | 徐学荣 , 李丽容 , 王丹 et al. 福建漳州平和柚天气指数保险产品设计与定价 [J]. | 福建农业科技 , 2024 , 55 (03) : 62-69 . |
| MLA | 徐学荣 et al. "福建漳州平和柚天气指数保险产品设计与定价" . | 福建农业科技 55 . 03 (2024) : 62-69 . |
| APA | 徐学荣 , 李丽容 , 王丹 , 林玲玲 . 福建漳州平和柚天气指数保险产品设计与定价 . | 福建农业科技 , 2024 , 55 (03) , 62-69 . |
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Abstract ：
基于当前农业绿色生产的重要发展背景，以福建省内六地市314个葡萄种植户的微观调查数据为支撑，运用面向投入规模报酬可变的DEA模型测度农户技术效率水平，并构建Tobit模型，实证避雨栽培的绿色生产模式下经营规模对农户技术效率的影响。结果表明：适度规模化经营有助于农户提高绿色生产的技术效率，葡萄种植面积的适度区间为0.67～3.33 hm~2，但随着经营规模增加，要素配置难度和雇工道德风险上升将会给农户造成一定的效率损失。因此，农户在实际生产中应根据自身要素禀赋状况选择合适的经营规模，不宜盲目扩张。
Keyword ：
技术效率 技术效率 经营规模 经营规模 绿色生产 绿色生产 要素错配 要素错配 道德风险 道德风险
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| GB/T 7714 | 宋芳 , 徐学荣 . 绿色生产背景下经营规模对农户技术效率的影响研究——基于福建省葡萄种植户的调查数据 [J]. | 黑龙江八一农垦大学学报 , 2024 , 36 (02) : 113-120 . |
| MLA | 宋芳 et al. "绿色生产背景下经营规模对农户技术效率的影响研究——基于福建省葡萄种植户的调查数据" . | 黑龙江八一农垦大学学报 36 . 02 (2024) : 113-120 . |
| APA | 宋芳 , 徐学荣 . 绿色生产背景下经营规模对农户技术效率的影响研究——基于福建省葡萄种植户的调查数据 . | 黑龙江八一农垦大学学报 , 2024 , 36 (02) , 113-120 . |
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Abstract ：
Studying the impact of agricultural digitalization (ADT) on the carbon emission intensity of planting industry (PCI) can help promote sustainable development and realize the "dual carbon" goal. Based on the panel data of 31 provinces in China from 2010 to 2020, this study uses the entropy weight method and emission coefficient method to measure the development level of ADT and PCI, respectively. By using the regression analysis method, as well as the robustness test, heterogeneity test, and spatial spillover effect and threshold tests, the impact of ADT on PCI was examined. The results are as follow: (1) PCI is high in the north and low in the south, and the north-south divide is becoming prominent. (2) ADT in China can significantly reduce PCI, as verified through the robustness test. (3) Regional differences exist in the impact of ADT on PCI, with the most significant effect observed in the northeast region, followed by the western and central regions. (4) ADT exerts a significant spatial spillover effect on PCI and an inhibitory effect on PCI of adjacent provinces. (5) The proportion of urban population exerts a threshold effect in the impact of ADT on PCI. When the urban population ratio crosses 69 %, the inhibitory effect of agricultural carbon emissions decreases marginally. Therefore, promoting the green and lowcarbon development of the planting industry is highly recommended.
Keyword ：
Agriculture digitalization Agriculture digitalization Planting carbon emission intensity Planting carbon emission intensity Spatial spillover effect Spatial spillover effect Sustainable development Sustainable development Threshold effect Threshold effect
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| GB/T 7714 | Wang, Dan , Chen, Chongcheng , Zhu, Ningteng et al. Impact of agricultural digitalization on carbon emission intensity of planting industry: Evidence from China [J]. | HELIYON , 2024 , 10 (10) . |
| MLA | Wang, Dan et al. "Impact of agricultural digitalization on carbon emission intensity of planting industry: Evidence from China" . | HELIYON 10 . 10 (2024) . |
| APA | Wang, Dan , Chen, Chongcheng , Zhu, Ningteng , Xu, Xuerong . Impact of agricultural digitalization on carbon emission intensity of planting industry: Evidence from China . | HELIYON , 2024 , 10 (10) . |
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Enabling cost-effective safety monitoring of shellfish is an important measure for the healthy development of the coastal marine economy. Herein, a new aptamer@metal-organic framework (MOF)-functionalized affinity monolithic column was proposed and applied in selective in-tube solid-phase microextraction (IT-SPME) coupled with HPLC for the accurate recognition of domoic acid (DA) in shellfish. Using a surface engineering strategy, ZIF-8 MOF was grown in situ inside the poly(epoxy-MA-co-POSS-MA) hybrid monolith. A high BET surface area and abundant metal reactive sites of the MOF framework were obtained for anchoring massive aptamers with terminal-modified phosphate groups. Various characterizations, such as SEM, elemental mapping, XRD, and BET, were performed, and the affinity performance was also studied. The presence of a massive amount of aptamers with a super coverage density of 3140 mu mol L-1 bound on ZIF-8 MOF activated a high-performance bionic-affinity interface, and perfect specificity was exhibited with little interference of tissue matrixes, thus assuring the highly selective capture of DA from the complex matrixes. Under the optimal conditions, DA toxins in shellfish were detected with the limit of detection (LOD) of 7.0 ng mL(-1) (equivalent to 14.0 mu g kg(-1)), representing a 5-28 fold enhancement in detection sensitivity over traditional SPE or MIP adsorbents reported previously. The recoveries of fortified mussel and clam samples were achieved as 91.8 +/- 1.2%-94.1 +/- 1.9% (n = 3) and 91.2 +/- 1.1%-94.5 +/- 3.6% (n = 3), respectively. This work sheds light on a cost-effective method for online selective IT-SPME and the accurate monitoring of DA toxins using an aptamer@MOF-mediated affinity monolith system coupled with the inexpensive HPLC-UV technique.
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| GB/T 7714 | Song, Fang , Zhang, Zhexiang , Xu, Xuerong et al. Online highly selective recognition of domoic acid by an aptamer@MOFs affinity monolithic column coupled with HPLC for shellfish safety monitoring [J]. | RSC ADVANCES , 2023 , 13 (44) : 30876-30884 . |
| MLA | Song, Fang et al. "Online highly selective recognition of domoic acid by an aptamer@MOFs affinity monolithic column coupled with HPLC for shellfish safety monitoring" . | RSC ADVANCES 13 . 44 (2023) : 30876-30884 . |
| APA | Song, Fang , Zhang, Zhexiang , Xu, Xuerong , Lin, Xucong . Online highly selective recognition of domoic acid by an aptamer@MOFs affinity monolithic column coupled with HPLC for shellfish safety monitoring . | RSC ADVANCES , 2023 , 13 (44) , 30876-30884 . |
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Abstract ：
Prediction results in big data analysis can vary greatly depending on the data preprocessing methods used. Time series-based processing methods are particularly advantageous for prediction. While popular neural network models such as Back Propagation (BP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) are based on weight, loss function, and other factors, their training efficiency is still relatively low. In this paper, we propose an efficient Time-series Recurrent Neural Network (TRNN) for stock price prediction. In the proposed model, trading volume is established and sliding windows are used to process the time series data. The trends and turning points of the data are extracted according to financial market features, and data compression is achieved. To improve the impact of recent trading volume on the current stock price, the price-volume relationship is upgraded from one dimension to two dimensions based on RNN. The information about trading volume is processed and compressed to establish the TRNN model, which guarantees both accuracy and efficiency. We compare our TRNN model with the original RNN and LSTM models in terms of efficiency and accuracy. We further discuss the feasibility of related expanded schemes of our TRNN model, as well as the extendability of the time-series compression and TRNN model to other fields.
Keyword ：
Neural network Neural network Sliding windows Sliding windows Stock price prediction Stock price prediction Time series Time series Trading volume Trading volume
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| GB/T 7714 | Lu, Minrong , Xu, Xuerong . TRNN: An efficient time-series recurrent neural network for stock price prediction [J]. | INFORMATION SCIENCES , 2023 , 657 . |
| MLA | Lu, Minrong et al. "TRNN: An efficient time-series recurrent neural network for stock price prediction" . | INFORMATION SCIENCES 657 (2023) . |
| APA | Lu, Minrong , Xu, Xuerong . TRNN: An efficient time-series recurrent neural network for stock price prediction . | INFORMATION SCIENCES , 2023 , 657 . |
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Abstract ：
在当前农业绿色生产的重要发展背景下，基于福建省314户采用避雨栽培的巨峰葡萄种植户的微观调研数据，运用面向投入规模报酬可变的BCC-DEA模型测度了种植户的技术效率水平，并按照不同生产规模进行了描述统计分析。研究结果表明：种植户技术效率水平整体较高，且适度规模化经营有助于种植户提高技术效率，但随着经营规模增加，要素配置难度和雇工道德风险上升将会给种植户造成一定的效率损失，在生产实际中种植户应根据自身要素禀赋状况选择合适的经营规模，不宜盲目扩张。
Keyword ：
DEA DEA 巨峰葡萄 巨峰葡萄 技术效率 技术效率 绿色生产 绿色生产 避雨栽培 避雨栽培
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| GB/T 7714 | 宋芳 , 徐学荣 . 福建省‘巨峰’葡萄避雨栽培的技术效率研究 [J]. | 东南园艺 , 2023 , 11 (01) : 37-43 . |
| MLA | 宋芳 et al. "福建省‘巨峰’葡萄避雨栽培的技术效率研究" . | 东南园艺 11 . 01 (2023) : 37-43 . |
| APA | 宋芳 , 徐学荣 . 福建省‘巨峰’葡萄避雨栽培的技术效率研究 . | 东南园艺 , 2023 , 11 (01) , 37-43 . |
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Abstract ：
柚产业是福建漳州的农业特色产业之一。基于1985-2019年的漳州柚采摘面积、总产量、单产数据，采用具有饱和增长趋势的Logistic模型拟合漳州柚产业发展历程。结果表明，漳州柚产业在2005-2019年15年间呈准线性增长模式，2019年到达成熟点，此后起步入顶极期。分析漳州柚种植区域分布、产品结构变动状况，查找了漳州柚产业存在的问题，以高质量发展为要求，有针对性地提出对策建议。
Keyword ：
Logistic曲线模型 Logistic曲线模型 漳州柚 漳州柚 精深加工 精深加工 结构优化 结构优化 贮藏保鲜 贮藏保鲜
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| GB/T 7714 | 徐学荣 , 李丽容 , 陈秀兰 et al. 漳州柚产业高质量发展问题研究 [J]. | 福建热作科技 , 2023 , 48 (02) : 22-27 . |
| MLA | 徐学荣 et al. "漳州柚产业高质量发展问题研究" . | 福建热作科技 48 . 02 (2023) : 22-27 . |
| APA | 徐学荣 , 李丽容 , 陈秀兰 , 林玲玲 . 漳州柚产业高质量发展问题研究 . | 福建热作科技 , 2023 , 48 (02) , 22-27 . |
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Abstract ：
Prediction results in big data analysis can vary greatly depending on the data preprocessing methods used. Time series-based processing methods are particularly advantageous for prediction. While popular neural network models such as Back Propagation (BP), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) are based on weight, loss function, and other factors, their training efficiency is still relatively low. In this paper, we propose an efficient stock price prediction neural network (TRNN) model based on RNN and price-volume time series. In the proposed model, trading volume is established and sliding windows are used to process the time series data. The trends and turning points of the data are extracted according to financial market features, and data compression is achieved. To improve the impact of recent trading volume on the current stock price, the price-volume relationship is upgraded from one dimension to two dimensions based on a cyclic neural network model. The information about trading volume is processed and compressed to establish the TRNN model, which guarantees both accuracy and efficiency. We compare our TRNN model with the original RNN and LSTM models in terms of efficiency and accuracy. © 2023, The Authors. All rights reserved.
Keyword ：
Backpropagation Backpropagation Commerce Commerce Decoding Decoding Efficiency Efficiency Electronic trading Electronic trading Financial markets Financial markets Forecasting Forecasting Long short-term memory Long short-term memory Neural network models Neural network models Time series Time series
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| GB/T 7714 | Lu, Minrong , Xu, Xuerong . Trnn: An Efficient Stock Price Prediction Neural Network Model Based on Recurrent Neural Network and Price-Volume Time Series [J]. | SSRN , 2023 . |
| MLA | Lu, Minrong et al. "Trnn: An Efficient Stock Price Prediction Neural Network Model Based on Recurrent Neural Network and Price-Volume Time Series" . | SSRN (2023) . |
| APA | Lu, Minrong , Xu, Xuerong . Trnn: An Efficient Stock Price Prediction Neural Network Model Based on Recurrent Neural Network and Price-Volume Time Series . | SSRN , 2023 . |
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