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学者姓名：丁铮
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Abstract ：
1940 年,萨一佛在福建永安地区创办《战时木刻画报》刊物已开始努力摆脱欧洲艺术作风,向着大众化和民族化的方向前进.本文以《战时木刻画报》切入,对萨一佛木刻艺术中的大众化和民族形式进行研究,集中探察当时福建木刻所面临的社会背景、十日漫画社时期萨一佛思想转捩、萨一佛对于早期木刻中民族形式存在的问题以及民族形式的探索手段这四个问题,借此引入萨一佛视角理解新兴木刻版画的大众化、民族化等核心议题,让学界对永安抗战文艺能有更为清晰、客观、完整的认识.
Keyword ：
抗战转型 抗战转型 新兴木刻 新兴木刻 民族化和大众化 民族化和大众化 萨一佛 萨一佛
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| GB/T 7714 | 陈少枫 , 苏晨茜 , 丁铮 . 转捩与宣传 [J]. | 美与时代 , 2025 , (3) : 77-84 . |
| MLA | 陈少枫 等. "转捩与宣传" . | 美与时代 3 (2025) : 77-84 . |
| APA | 陈少枫 , 苏晨茜 , 丁铮 . 转捩与宣传 . | 美与时代 , 2025 , (3) , 77-84 . |
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| GB/T 7714 | Yang, Litian , Yang, Lixin , Ding, Zheng et al. Study on effects of different land use types on heat island effect and its potential effects on residents' mental health in main city of Zhengzhou City [J]. | INTERNATIONAL JOURNAL OF MENTAL HEALTH NURSING , 2025 , 34 : 44-45 . |
| MLA | Yang, Litian et al. "Study on effects of different land use types on heat island effect and its potential effects on residents' mental health in main city of Zhengzhou City" . | INTERNATIONAL JOURNAL OF MENTAL HEALTH NURSING 34 (2025) : 44-45 . |
| APA | Yang, Litian , Yang, Lixin , Ding, Zheng , Lu, Dongfang . Study on effects of different land use types on heat island effect and its potential effects on residents' mental health in main city of Zhengzhou City . | INTERNATIONAL JOURNAL OF MENTAL HEALTH NURSING , 2025 , 34 , 44-45 . |
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Global climate change has intensified the regional linkage of the urban heat island effect (UHI), posing major challenges to urban sustainability. This study examines three major metropolitan areas in China to understand how thermal environments interact under different geographical conditions. It aims to improve the heat island network structure and enhance governance strategies. The study combines XGBoost machine learning with the GeoSHapley method to build a high-precision thermal resistance surface, overcoming the bias of traditional methods and capturing nonlinear effects, spatial variation, and factor interactions. The heat island network is modeled using circuit theory and evaluated and verified using structural indicators such as alpha closure, (3 line-to-point ratio and gamma connectivity. Key findings include: 1) Resistance factors vary significantly across regions. In Chongqing, topographic factors (DEM and SLOPE) account for 72 % of the resistance, dominating the network. In Xiamen-Zhangzhou-Quanzhou and Wuhan, NDBI contributes 0.37 and 0.38, respectively, as the main driver. 2)GeoSHapley analysis identified cooling thresholds for resistance factors. For example, NDVI thresholds are [0.75-0.85] in Xiamen-Zhangzhou-Quanzhou and [0.65-0.70] in Wuhan, offering a scientific basis for resistance classification. 3)The Chongqing network shows the highest connectivity (gamma = 0.81) and integrity (alpha = 0.70), with a model fit of R2 = 0.907. Xiamen-Zhangzhou-Quanzhou also performs well, proving the method works in complex terrain. This study improves upon past methods by introducing dynamic resistance classification and interaction analysis. It offers a scalable framework for managing urban thermal environments based on local geography, supporting ecological and sustainable urban development.
Keyword ：
GeoSHapely GeoSHapely Resistive surface Resistive surface Spatial network Spatial network Surface temperature Surface temperature Thermal environment Thermal environment XGBoost XGBoost
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| GB/T 7714 | Chen, Shaofeng , Qiu, Yuwei , Xu, Yuhan et al. Modeling and optimization of heat island networks based on machine learning and the perspective of spatial heterogeneity in metropolitan areas [J]. | URBAN CLIMATE , 2025 , 63 . |
| MLA | Chen, Shaofeng et al. "Modeling and optimization of heat island networks based on machine learning and the perspective of spatial heterogeneity in metropolitan areas" . | URBAN CLIMATE 63 (2025) . |
| APA | Chen, Shaofeng , Qiu, Yuwei , Xu, Yuhan , Huang, Jiafang , Ding, Zheng . Modeling and optimization of heat island networks based on machine learning and the perspective of spatial heterogeneity in metropolitan areas . | URBAN CLIMATE , 2025 , 63 . |
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The rapid growth of the aging population, alongside functional decline and more older adults living independently, has increased demand for age-friendly infrastructure and walkable communities. This study proposes a quantitative framework to assess how multi-scale built environments influence older adults' walkability, addressing the scarcity of scalable and interpretable models in age-friendly urban research. By combining the cumulative opportunity method, street-scene semantic segmentation, XGBoost, and GeoSHapley-based spatial effect analysis, the study finds that (1) significant spatial disparities in walkability exist in Xiamen's central urban area. Over half of the communities (54.46%) failed to meet the minimum threshold (20 points) within the 15 min community life circle (15-min CLC), indicating inadequate infrastructure. The primary issue is low coverage of older adults' welfare facilities (only 16.26% of communities are within a 15 min walk). Despite renovations in Jinhu Community, walkability remains low, highlighting persistent disparities. (2) Communities with abundant green space are predominantly newly developed areas (64.06%). However, these areas provide fewer facilities on average (2.3) than older communities (5.7), resulting in a "green space-service mismatch", where visually appealing environments lack essential services. (3) Human perception variables such as safety, traffic flow, and closure positively influence walkability, while visual complexity, heat risk, exposure, and greenness have negative effects. (4) There is a clear supply and demand mismatch. Central districts combine high walkability with substantial older adults' service demand. Newly built residential areas in the periphery and north have low density and insufficient pedestrian facilities. They fail to meet daily accessibility needs, revealing delays in age-friendly development. This framework, integrating nonlinear modeling and spatial analysis, reveals spatial non-stationarity and optimal thresholds in how the built environment influences walkability. Beyond methodological contributions, this study offers guidance for planners and policymakers to optimize infrastructure allocation, promote equitable, age-friendly cities, and enhance the health and wellbeing of older residents.
Keyword ：
age-friendly urban renewal age-friendly urban renewal community-level built environment community-level built environment explainable machine learning explainable machine learning multi-scale living circles multi-scale living circles walkability walkability
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| GB/T 7714 | Su, Chenxi , Chen, Zhengyan , Cheng, Yuxuan et al. Decoding Multi-Scale Environmental Configurations for Older Adults' Walkability with Explainable Machine Learning [J]. | SUSTAINABILITY , 2025 , 17 (18) . |
| MLA | Su, Chenxi et al. "Decoding Multi-Scale Environmental Configurations for Older Adults' Walkability with Explainable Machine Learning" . | SUSTAINABILITY 17 . 18 (2025) . |
| APA | Su, Chenxi , Chen, Zhengyan , Cheng, Yuxuan , Chen, Shaofeng , Li, Wenting , Ding, Zheng . Decoding Multi-Scale Environmental Configurations for Older Adults' Walkability with Explainable Machine Learning . | SUSTAINABILITY , 2025 , 17 (18) . |
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Natural landscapes are crucial resources for enhancing visitor experiences in ecotourism destinations. Previous research indicates that high temperatures may impact tourists' perception of landscapes and emotions. Still, the potential value of natural landscape perception in regulating tourists' emotions under high-temperature conditions remains unclear. In this study, we employed machine learning models such as LSTM-CNN, Hrnet, and XGBoost, combined with hotspot analysis and SHAP methods, to compare and reveal the potential impacts of natural landscape elements on tourists' emotions under different temperature conditions. The results indicate: (1) Emotion prediction and spatial analysis reveal a significant increase in the proportion of negative emotions under high-temperature conditions, reaching 30.1%, with negative emotion hotspots concentrated in the downtown area, whereas, under non-high temperature conditions, negative emotions accounted for 14.1%, with a more uniform spatial distribution. (2) Under non-high temperature conditions, the four most influential factors on tourists' emotions were Color complexity (0.73), Visual entropy (0.71), Greenness (0.68), and Aquatic rate (0.6). In contrast, under high-temperature conditions, the most influential factors were Greenness (0.6), Openness (0.56), Visual entropy (0.55), and Color complexity (0.55). (3) Compared to non-high temperature conditions, high temperatures enhanced the positive effects of environmental perception on emotions, with Greenness (0.94), Color complexity (0.84), and Enclosure (0.71) showing stable positive impacts. Additionally, aquatic elements under high-temperature conditions had a significant emotional regulation effect (contribution of 1.05), effectively improving the overall visitor experience. This study provides a data foundation for optimizing natural landscapes in ecotourism destinations, integrating the advantages of various machine learning methods, and proposing a framework for data collection, comparison, and evaluation of natural landscape perception under different temperature conditions. It thoroughly explores the potential of natural landscapes to enhance visitor experiences under various temperature conditions and provides sustainable planning recommendations for the sustainable conservation of natural ecosystems and ecotourism.
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| GB/T 7714 | Ye, Cuicui , Chen, Zhengyan , Ding, Zheng . How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China [J]. | PLOS ONE , 2025 , 20 (5) . |
| MLA | Ye, Cuicui et al. "How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China" . | PLOS ONE 20 . 5 (2025) . |
| APA | Ye, Cuicui , Chen, Zhengyan , Ding, Zheng . How does high temperature weather affect tourists' nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China . | PLOS ONE , 2025 , 20 (5) . |
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Abstract ：
【目的】探究福州市儿童友好城市街道空间感知对居民（特别是儿童及其监护人）情绪的影响机制，揭示街道设计要素与居民情绪间的复杂关联，为儿童友好空间的精细化营造提供理论支撑与设计路径。【方法】融合百度街景、社交媒体用户生成内容及政府投诉数据，构建多源数据集；采用CNN-BiLSTM混合模型进行居民情感分析，结合XGBoost回归算法建模和SHapley加性解释方法，解析交通流量、视觉复杂度、空间安全感知、栅栏占比等12项景观指标对居民情绪感知的非线性作用。通过图像语义分割、人机对抗评分框架量化街道环境特征，利用SHAP贡献值揭示关键指标的边际效应与交互关系。【结果】交通流量、视觉复杂度、空间安全感知和栅栏占比4项指标构成核心驱动层，其解释力显著高于其他指标。揭示指标之间协同作用机制：1）交通流量指标存在双阈值效应；2）视觉复杂度指标值在0时为居民情绪转折点，视觉复杂度过高导致居民情绪下降；3）儿童绿视率指标与空间安全感知发展才能有正向情绪驱动。【结论】基于街道空间对居民情绪的作用机制，提出儿童友好城市街道三级优化路径：1）交通流量与居民情绪呈非线性影响，需分级管控，通过趣味化街道设计拓展儿童活动空间；2）建立空间安全感知与儿童绿视率的协同优化机制，完善基础设施与标识系统；3）视觉复杂度存在阈值效应，建议采用互动装置艺术实现场景活化；4）平衡街道天空开阔率与建筑占比。为构建儿童友好型城市提供了新的理论依据。
Keyword ：
儿童友好城市 儿童友好城市 居民情绪 居民情绪 机器学习 机器学习 福州 福州 街景感知 街景感知
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| GB/T 7714 | 陈少枫 , 陈铮衍 , 徐雨涵 et al. 福州市儿童友好城市街道空间感知对居民情绪的影响机制 [J]. | 风景园林 , 2025 , 32 (05) : 105-115 . |
| MLA | 陈少枫 et al. "福州市儿童友好城市街道空间感知对居民情绪的影响机制" . | 风景园林 32 . 05 (2025) : 105-115 . |
| APA | 陈少枫 , 陈铮衍 , 徐雨涵 , 丁铮 . 福州市儿童友好城市街道空间感知对居民情绪的影响机制 . | 风景园林 , 2025 , 32 (05) , 105-115 . |
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Abstract ：
1940年，萨一佛在福建永安地区创办《战时木刻画报》刊物已开始努力摆脱欧洲艺术作风，向着大众化和民族化的方向前进。本文以《战时木刻画报》切入，对萨一佛木刻艺术中的大众化和民族形式进行研究，集中探察当时福建木刻所面临的社会背景、十日漫画社时期萨一佛思想转捩、萨一佛对于早期木刻中民族形式存在的问题以及民族形式的探索手段这四个问题，借此引入萨一佛视角理解新兴木刻版画的大众化、民族化等核心议题，让学界对永安抗战文艺能有更为清晰、客观、完整的认识。
Keyword ：
抗战转型 抗战转型 新兴木刻 新兴木刻 民族化和大众化 民族化和大众化 萨一佛 萨一佛
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| GB/T 7714 | 陈少枫 , 苏晨茜 , 丁铮 . 转捩与宣传——福建萨一佛抗战主题探索及新兴木刻民族形象的塑造研究 [J]. | 美与时代(下) , 2025 , 8 (01) : 77-84 . |
| MLA | 陈少枫 et al. "转捩与宣传——福建萨一佛抗战主题探索及新兴木刻民族形象的塑造研究" . | 美与时代(下) 8 . 01 (2025) : 77-84 . |
| APA | 陈少枫 , 苏晨茜 , 丁铮 . 转捩与宣传——福建萨一佛抗战主题探索及新兴木刻民族形象的塑造研究 . | 美与时代(下) , 2025 , 8 (01) , 77-84 . |
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在科技革新的背景下，技术驱动舞台空间设计的核心命题在于找到技术、艺术与观众之间的平衡。当下，舞台空间设计需解决的问题是技术应以何种方式增强观者的参与感。英国皇家莎士比亚剧团的《暴风雨》是以数字技术增强传统舞台作品，后来的《Dream》则是沉浸式技术孕育下的新戏剧形式，是线上交互戏剧的一次大胆尝试，既为观众带来了便捷、平等的戏剧艺术参与方式，也有效解决了传统戏剧吸引力匮乏的问题，成为探索解决技术、艺术与观众之间平衡的生动案例，可为中国戏曲舞台空间的数字演绎提供参考。
Keyword ：
《Dream》 《Dream》 数字演绎 数字演绎 沉浸式 沉浸式 英国皇家莎士比亚剧团 英国皇家莎士比亚剧团
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| GB/T 7714 | 谢佳晖 , 丁铮 . 英国皇家莎士比亚剧团舞台空间的数字演绎策略探析 [J]. | 四川戏剧 , 2025 , 5 (06) : 81-85 . |
| MLA | 谢佳晖 et al. "英国皇家莎士比亚剧团舞台空间的数字演绎策略探析" . | 四川戏剧 5 . 06 (2025) : 81-85 . |
| APA | 谢佳晖 , 丁铮 . 英国皇家莎士比亚剧团舞台空间的数字演绎策略探析 . | 四川戏剧 , 2025 , 5 (06) , 81-85 . |
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As universities become increasingly open, campuses are no longer only places for study and daily life for students and faculty, but also essential spaces for public visits and cultural identity. Traditional perception evaluation methods that rely on manual surveys are limited by sample size and subjective bias, making it challenging to reveal differences in experiences between groups (students/visitors) and the complex relationships between spatial elements and perceptions. This study uses a comprehensive open university in China as a case study to address this. It proposes a research framework that combines street-view image semantic segmentation, perception survey scores, and interpretable machine learning with sample augmentation. First, full-sample modeling is used to identify key image semantic features influencing perception indicators (nature, culture, aesthetics), and then to compare how students and visitors differ in their perceptions and preferences across campus spaces. To overcome the imbalance in survey data caused by group-space interactions, the study applies the CTGAN method, which expands minority samples through conditional generation while preserving distribution authenticity, thereby improving the robustness and interpretability of the model. Based on this, attribution analysis with an interpretable decision tree algorithm further quantifies semantic features' contribution, direction, and thresholds to perceptions, uncovering heterogeneity in perception mechanisms across groups. The results provide methodological support for perception evaluation of campus functional zones and offer data-driven, human-centered references for campus planning and design optimization.
Keyword ：
campus functional zones campus functional zones campus space campus space image semantic segmentation image semantic segmentation SHAP SHAP student-visitor differences student-visitor differences
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| GB/T 7714 | Zhuang, Xiaowen , Cai, Yi , Tang, Zhenpeng et al. Optimizing University Campus Functional Zones Using Landscape Feature Recognition and Enhanced Decision Tree Algorithms: A Study on Spatial Response Differences Between Students and Visitors [J]. | BUILDINGS , 2025 , 15 (19) . |
| MLA | Zhuang, Xiaowen et al. "Optimizing University Campus Functional Zones Using Landscape Feature Recognition and Enhanced Decision Tree Algorithms: A Study on Spatial Response Differences Between Students and Visitors" . | BUILDINGS 15 . 19 (2025) . |
| APA | Zhuang, Xiaowen , Cai, Yi , Tang, Zhenpeng , Ding, Zheng , Gan, Christopher . Optimizing University Campus Functional Zones Using Landscape Feature Recognition and Enhanced Decision Tree Algorithms: A Study on Spatial Response Differences Between Students and Visitors . | BUILDINGS , 2025 , 15 (19) . |
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晚明时期著名文人曹学佺在福建地区所建园林——石仓园，不仅展示了闽中地区的独特文化风情，更彰显出文人对风雅文化的执着追求。石仓园内所承载的景观空间不仅揭示了曹学佺个人的情感流变，还映射出晚明文人在园林中所呈现的情感寄托，因此从个人的思绪投射到景观的情绪，共筑成石仓园的情感逻辑。通过对石仓园的详细梳理，更能理解其在建成前后的情感流变以及深刻的文化内涵。
Keyword ：
文人心境 文人心境 晚明文化 晚明文化 曹学佺 曹学佺 石仓园 石仓园
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| GB/T 7714 | 庄晓雯 , 陈少枫 , 苏晨茜 et al. 失落的风雅——晚明福州石仓园中的情感逻辑探赜 [J]. | 建筑与文化 , 2025 , 4 (04) : 139-142 . |
| MLA | 庄晓雯 et al. "失落的风雅——晚明福州石仓园中的情感逻辑探赜" . | 建筑与文化 4 . 04 (2025) : 139-142 . |
| APA | 庄晓雯 , 陈少枫 , 苏晨茜 , 丁铮 . 失落的风雅——晚明福州石仓园中的情感逻辑探赜 . | 建筑与文化 , 2025 , 4 (04) , 139-142 . |
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