[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3624":3,"related-3624":45},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"search_phrases":21,"slug":22,"view_count":15,"doi":23,"paper":24,"created_at":44},3624,"USING QUALITY FUNCTION DEPLOYMENT AS A DECISION SUPPORT TOOL IN FOOD PRODUCT QUALITY MANAGEMENT","https:\u002F\u002Fdoi.org\u002F10.24874\u002Fijqr20.03-10","This study examines the application of Quality Function Deployment (QFD) as a structured decision-support framework for environmentally oriented food product development, with particular emphasis on the integration of consumer-derived quality requirements, technical characteristics, and quantitative environmental indicators.Unlike prior QFD applications relying on qualitative environmental proxies, the present study incorporates a simplified cradle-to-gate Life Cycle Assessment (LCA) to provide a more rigorous and quantitatively grounded basis for sustainability-related trade-off analysis.Blind sensory evaluation conducted with a Generation Z consumer panel (n = 100) identified key customer requirementstaste intensity, creaminess, freshness perception, aftertaste, and overall liking which were systematically mapped to controllable technical characteristics within an extended House of Quality (HOQ).The analysis reveals that taste intensity and overall liking are the primary drivers of consumer acceptance across both conventional dairy and plant-based yogurt-type products, with fermentation time emerging as the most strategically significant controllable process parameter.The HOQ correlation structure further exposes critical trade-offs between compositional intensificationparticularly fat contentand carbon footprint reduction objectives, demonstrating the framework's capacity to surface consequential managerial dilemmas.These findings contribute to the quality management and decision sciences literature by extending QFD beyond design-centric applications toward a comprehensive managerial decision-support tool that systematically reconciles consumer satisfaction with sustainability objectives in food product development contexts.","本研究探讨了质量功能展开(QFD)作为面向环境的食品产品开发的结构化决策支持框架的应用，特别强调消费者质量需求、技术特性与定量环境指标三者的整合。与以往依赖定性环境替代指标的QFD应用不同，本研究引入简化的“从摇篮到大门”生命周期评价(LCA)，为可持续性相关的权衡分析提供更为严谨且以定量数据为基础的依据。由Z世代消费者小组(n = 100)进行的盲法感官评价识别出关键顾客需求——味道强度、细腻度、新鲜感、余味和整体喜好度——并将其系统映射至扩展质量屋(HOQ)内可控的技术特性。分析表明，味道强度和整体喜好度是传统乳制品和植物基酸奶类产品中消费者接受度的主要驱动因素，而发酵时间则是最具战略意义的可控工艺参数。质量屋的相关结构进一步揭示了成分强化——尤其是脂肪含量——与碳足迹削减目标之间的关键权衡，表明该框架能够揭示具有重要管理意义的困境。这些发现通过将QFD从以设计为中心的应用拓展为综合性的管理决策支持工具，系统性地协调食品产品开发情境中的消费者满意度与可持续性目标，为质量管理与决策科学文献作出了贡献。",null,"International Journal for Quality Research","2026-09-25T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文研究食品产品质量管理中的QFD决策支持方法，与三农、农业信息化、智慧农业等主题无直接关联，不予入选。",[19],{"name":10,"url":6},[12],[],"USINGQUALITYFUNCTIONDEPLOYMENTASADECISIO-3624","10.24874\u002Fijqr20.03-10",{"doi":23,"openalex_id":25,"authors":26,"venue":10,"cited_by_count":15,"oa_url":6,"card":36,"direction":42,"ingested_from":43},"W7214289064",[27,30,33],{"name":28,"orcid":29},"Petronela Švikruhová","https:\u002F\u002Forcid.org\u002F0000-0003-1785-040X",{"name":31,"orcid":32},"Zuzana Kapsdorferová","https:\u002F\u002Forcid.org\u002F0000-0002-4244-5695",{"name":34,"orcid":35},"Dominika Čeryová","https:\u002F\u002Forcid.org\u002F0000-0003-2924-2284",{"tldr":37,"method":38,"finding":39,"direction":40,"opportunity":41},"将QFD结合简化LCA，用于食品产品开发中消费者需求与碳足迹的权衡决策。","扩展质量屋(HOQ)整合盲测感官评价(n=100)与摇篮到大门LCA。","发酵时间是最关键可控参数，脂肪含量与碳减排目标存在显著权衡。","农业绿色发展与碳","可将QFD-LCA框架拓展至更多农产品品类，并引入动态消费者偏好与供应链碳数据。","数字乡村与农业信息化","openalex","2026-09-27T23:30:59.335807Z",{"total":46,"page":47,"page_size":46,"items":48},6,1,[49,91,122,159,190,220],{"id":50,"title":51,"url":52,"summary":53,"summary_zh":54,"content":9,"source_name":55,"source_url":52,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":56,"sources":58,"tags":60,"search_phrases":61,"slug":62,"view_count":15,"doi":63,"paper":64,"created_at":90},3629,"4-Dimensional Chess: Acoustic Localisation Reveals Nested Spatio-temporal Strategies in an Arboreal Communication Network","https:\u002F\u002Fdoi.org\u002F10.64898\u002F2026.09.21.752596","1. Adaptive behavioural strategies require animals to simultaneously navigate social and ecological domains across multiple spatial and temporal scales. Although drones and computer vision have recently transformed the study of wild animal societies, many nocturnal species and those occupying structurally complex habitats remain inaccessible to these approaches, limiting our understanding of behaviour in natural settings. 2. We aimed to determine how behavioural strategies are organised across nested spatial and temporal scales within a wild communication network. 3. We used three-dimensional acoustic localisation and source separation to track individual male Hyperolius sp. A, a nocturnal African reed frog, within a natural rainforest chorus and quantify patterns of site fidelity, movement, spatial organisation, and call-timing interactions. 4. Males exhibited significant site fidelity across nights, while chorus spatial structure varied with local caller density. Within nights, individuals followed a stereotyped behavioural sequence, descending from elevated arboreal refugia before settling into lower calling positions near breeding sites. At finer temporal scales, call-timing interactions varied according to both local competitor density and the proximity of neighbouring rivals. 5. These findings demonstrate that behavioural strategies emerge across nested spatial and temporal scales and that long-term spatial positioning, short-term movement decisions, and moment-to-moment signalling interactions are tightly linked within natural communication networks. More broadly, acoustic localisation provides a powerful framework for studying behaviour in species and habitats that remain difficult to observe using conventional approaches.","1. 适应性行为策略要求动物在多个空间和时间尺度上同时应对社会与生态领域。尽管无人机和计算机视觉近来已改变了野生动物社会的研究，但许多夜行性物种以及栖息于结构复杂生境中的物种仍无法通过这些方法进行研究，这限制了我们对自然环境中行为的理解。2. 我们旨在确定行为策略如何在野生通信网络中以嵌套的空间和时间尺度进行组织。3. 我们利用三维声学定位和声源分离技术，在自然雨林合唱群中追踪雄性Hyperolius sp. A个体——一种夜行性非洲苇蛙，并量化其地点忠诚度、移动、空间组织和鸣叫时序互作模式。4. 雄性在夜间表现出显著的地点忠诚度，而合唱群的空间结构随局部鸣叫者密度而变化。在夜间，个体遵循固定的行为序列，先从高处树栖庇护所下降，然后定居于繁殖地附近的较低鸣叫位置。在更精细的时间尺度上，鸣叫时序互作随局部竞争者密度和邻近竞争对手的接近程度而变化。5. 这些发现表明，行为策略在嵌套的空间和时间尺度上涌现，且长期空间定位、短期移动决策和瞬时信号互作在自然通信网络中紧密关联。更广泛而言，声学定位为研究那些用传统方法难以观察的物种和生境中的行为提供了一个强有力的框架。","bioRxiv (Cold Spring Harbor Laboratory)",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":57},"该论文研究非洲雨林蛙类的声学定位与通讯网络行为，属基础动物行为生态学，与三农、农业信息化、智慧农业等主题无关。",[59],{"name":55,"url":52},[12],[],"4-DimensionalChess:AcousticLocalisationR-3629","10.64898\u002F2026.09.21.752596",{"doi":63,"openalex_id":65,"authors":66,"venue":55,"cited_by_count":15,"oa_url":82,"card":83,"direction":89,"ingested_from":43},"W7214363262",[67,70,73,76,79],{"name":68,"orcid":69},"Edmund W. Basham","https:\u002F\u002Forcid.org\u002F0000-0002-0167-7908",{"name":71,"orcid":72},"Luke C. Larter","https:\u002F\u002Forcid.org\u002F0000-0003-0758-1883",{"name":74,"orcid":75},"Patrick S. Champagne","https:\u002F\u002Forcid.org\u002F0000-0001-9125-8493",{"name":77,"orcid":78},"Douglas L. Jones","https:\u002F\u002Forcid.org\u002F0000-0002-7817-7629",{"name":80,"orcid":81},"Timothy H. Keitt","https:\u002F\u002Forcid.org\u002F0000-0002-4587-1083","https:\u002F\u002Fwww.biorxiv.org\u002Fcontent\u002Fbiorxiv\u002Fearly\u002F2026\u002F09\u002F25\u002F2026.09.21.752596.full.pdf",{"tldr":84,"method":85,"finding":86,"direction":87,"opportunity":88},"用三维声学定位追踪非洲树蛙，揭示其跨时空尺度的嵌套行为策略。","三维声学定位与声源分离，在自然雨林合唱中追踪个体雄蛙。","雄蛙具夜间位点忠诚，合唱空间结构随密度变化，行为序列与鸣叫时序受竞争密度和邻近对手影响。","其他","将声学定位与物联网结合，用于复杂生境下难观测物种的长期行为监测与生态网络分析。","农业人工智能与决策模型","2026-09-27T23:31:33.043317Z",{"id":92,"title":93,"url":94,"summary":95,"summary_zh":96,"content":9,"source_name":97,"source_url":94,"published_at":98,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":99,"sources":101,"tags":103,"search_phrases":104,"slug":105,"view_count":15,"doi":106,"paper":107,"created_at":121},3559,"Multiscale dynamics and nonlinear associations of ecological quality in the Hangzhou Bay urban agglomeration, China","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffevo.2026.1955721","Ecological quality change in rapidly urbanizing regions is spatially heterogeneous, but assessments based on a single analytical scale may obscure local changes and alter the apparent factor importance. This study constructed a 2000–2024 Remote Sensing Ecological Index (RSEI) series for the Hangzhou Bay Urban Agglomeration using Google Earth Engine and Landsat imagery. Ecological changes were compared across 1, 3, 5, and 10 km grids and county units with XGBoost–SHAP model fitted to pooled observations from six benchmark years. Mean RSEI showed an early decline followed by sustained recovery, yielding a net increase of 0.0423. High values were concentrated in southwestern forested areas, whereas low values occurred mainly in the northern plain, densely urbanized bay areas, and urban-expansion corridors. The proportion of improved area increased from 75.34% at 1 km to 84.25% at the county scale. During 2015–2020, county-level aggregation increased the stable proportion while reducing the improved proportion, indicating that coarse units can mask opposing local changes. Land-use intensity had the largest relative mean absolute SHAP contribution at all scales (44.59%–55.43%), while the contribution of nighttime light intensity rose with aggregation and reached 20.33% at the county scale. These results demonstrate that ecological-change detection and interpretation of modeled associations are scale dependent, supporting a nested multiscale assessment framework.","快速城市化地区的生态质量变化具有空间异质性，但基于单一分析尺度的评估可能掩盖局部变化并改变因子重要性的表观结果。本研究利用Google Earth Engine和Landsat影像构建了2000—2024年杭州湾城市群遥感生态指数（RSEI）序列。在1、3、5和10 km网格及县级单元上比较了生态变化，并采用XGBoost–SHAP模型对六个基准年的汇总观测数据进行拟合。RSEI均值呈先下降后持续恢复的趋势，净增加0.0423。高值集中在西南部森林地区，低值主要出现在北部平原、高度城市化的湾区及城市扩张廊道。改善面积比例从1 km尺度的75.34%增至县级尺度的84.25%。2015—2020年期间，县级聚合提高了稳定比例而降低了改善比例，表明粗尺度单元可掩盖相反的局部变化。土地利用强度在所有尺度上均具有最大的相对平均绝对SHAP贡献（44.59%—55.43%），而夜间灯光强度的贡献随聚合程度上升，在县级尺度达到20.33%。这些结果表明，生态变化检测和模型关联解释具有尺度依赖性，支持构建嵌套多尺度评估框架。","Frontiers in Ecology and Evolution","2026-09-24T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":100},"该文为杭州湾城市群生态质量遥感评估的生态学论文，与三农、农业信息化、智慧农业、数字乡村等主题无直接关联，不建议进入每日精选。",[102],{"name":97,"url":94},[12],[],"Multiscaledynamicsandnonlinearassociatio-3559","10.3389\u002Ffevo.2026.1955721",{"doi":106,"openalex_id":108,"authors":109,"venue":97,"cited_by_count":15,"oa_url":114,"card":115,"direction":119,"ingested_from":43},"W7214202972",[110,112],{"name":111,"orcid":9},"Zhiyuan Xu",{"name":113,"orcid":9},"Fuyan Ke","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fecology-and-evolution\u002Farticles\u002F10.3389\u002Ffevo.2026.1955721\u002Fpdf",{"tldr":116,"method":117,"finding":118,"direction":119,"opportunity":120},"构建杭州湾城市群2000-2024年RSEI序列，揭示生态质量的多尺度动态与非线性驱动关联。","Google Earth Engine与Landsat构建RSEI，结合XGBo","生态质量先降后升净增0.0423，改善区比例随尺度由75.34%升至84.25%，驱动因子重要性具尺","农业遥感与作物表型","可将多尺度嵌套框架与非线性归因迁移至农田生态质量评估，探究耕地利用强度与夜间灯光的尺度效应。","2026-09-26T23:30:31.485495Z",{"id":123,"title":124,"url":125,"summary":126,"summary_zh":127,"content":9,"source_name":128,"source_url":125,"published_at":129,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":130,"sources":132,"tags":134,"search_phrases":135,"slug":136,"view_count":15,"doi":137,"paper":138,"created_at":158},3486,"starU‐Net: An enhanced U‐Net architecture with star operation and multi‐view fusion for improved vessel segmentation","https:\u002F\u002Fdoi.org\u002F10.1002\u002Fviw2.70197","Abstract Accurate vessel segmentation is crucial for diagnosing vascular diseases and supporting research in developmental biology. However, existing methods struggle to preserve fine capillaries and the topological continuity of vascular structures. In this study, we aim to develop a novel deep learning architecture that specializes in thin vessel segmentation for improved continuity. We propose starU‐Net, a four‐layer encoder‒decoder framework for vessel segmentation. It integrates three components in a problem‐driven design: (1) an enhanced feature extraction module leveraging a “star operation” to enable multiplicative feature interaction, (2) a shallow network design to minimize spatial degradation, and (3) a multi‐view feature fusion module using dynamic snake convolution to capture continuous tubular structures from multiple orientations. The model was trained and evaluated on three public retinal datasets and a novel, self‐constructed chick embryo dataset. Against CNN‐based, transformer‐based, and foundation‐model baselines, starU‐Net obtained the highest sensitivity, F 1 , area under the curve, and centreline Dice on all three public retinal datasets, at the cost of slightly lower specificity. The improvement in centreline Dice provides quantitative support for the reduction in thin vessel discontinuity. On the chick embryo dataset, whose vessels are markedly wider, the proposed starU‐Net was competitive but not leading. In summary, starU‐Net is an architecture that combines star operation‐based feature extraction with multi‐view tubular feature modeling to improve vascular segmentation. The proposed framework demonstrates strong performance in both clinical retinal imaging datasets and self‐constructed chick embryo angiogenesis data, serving as a promising computational tool for clinical decision support, biomedical research, and large‐scale vascular phenotyping in biomedical applications.","摘要　精确的血管分割对于诊断血管疾病和支持发育生物学研究至关重要。然而，现有方法难以保留细小毛细血管及血管结构的拓扑连续性。本研究旨在开发一种新型深度学习架构，专门针对细血管分割以改善其连续性。我们提出starU‐Net，一种用于血管分割的四层编码器‐解码器框架。该框架以问题驱动设计整合了三个组件：(1) 利用“星操作”实现乘性特征交互的增强特征提取模块，(2) 最小化空间退化的浅层网络设计，(3) 使用动态蛇形卷积从多方向捕获连续管状结构的多视角特征融合模块。该模型在三个公开视网膜数据集和一个新构建的鸡胚数据集上进行了训练和评估。与基于CNN、基于Transformer及基础模型的基线方法相比，starU‐Net在三个公开视网膜数据集上均获得了最高的灵敏度、F1值、曲线下面积和中心线Dice，代价是特异性略低。中心线Dice的提升为细血管不连续性的减少提供了定量支持。在血管明显更宽的鸡胚数据集上，所提出的starU‐Net具有竞争力但并非领先。总之，starU‐Net是一种结合基于星操作的特征提取与多视角管状特征建模以改进血管分割的架构。所提出的框架在临床视网膜成像数据集和自构建的鸡胚血管生成数据中均展现出强大性能，可作为临床决策支持、生物医学研究及生物医学应用中大规模血管表型分析的有前景的计算工具。","Open Research (University of Surrey)","2026-09-22T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":131},"该论文聚焦医学血管分割的深度学习架构，与三农、农业信息化、智慧农业等主题无关，不予入选。",[133],{"name":128,"url":125},[12],[],"starU‐Net:AnenhancedU‐Netarchitecturewit-3486","10.1002\u002Fviw2.70197",{"doi":137,"openalex_id":139,"authors":140,"venue":128,"cited_by_count":15,"oa_url":152,"card":153,"direction":119,"ingested_from":43},"W7213971471",[141,143,146,149],{"name":142,"orcid":9},"Mengwei Bai",{"name":144,"orcid":145},"Tong Li","https:\u002F\u002Forcid.org\u002F0000-0003-1556-1241",{"name":147,"orcid":148},"Jing Lin","https:\u002F\u002Forcid.org\u002F0000-0001-9865-2098",{"name":150,"orcid":151},"Peng Fei Huang","https:\u002F\u002Forcid.org\u002F0000-0003-3651-7813","https:\u002F\u002Fonlinelibrary.wiley.com\u002Fdoi\u002Fpdfdirect\u002F10.1002\u002Fviw2.70197",{"tldr":154,"method":155,"finding":156,"direction":89,"opportunity":157},"提出starU-Net，用星操作和多视角融合提升血管分割连续性。","四层编解码器，星操作特征提取，动态蛇卷积多视角融合，视网膜和鸡胚数据。","在三个视网膜数据集上敏感度、F1、AUC和中心线Dice最高，细血管连续性改善。","可将该细管状结构分割架构迁移至农业场景，如作物根系、叶脉或灌溉管道提取。","2026-09-25T23:30:22.913090Z",{"id":160,"title":161,"url":162,"summary":163,"summary_zh":164,"content":9,"source_name":165,"source_url":162,"published_at":166,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":167,"sources":169,"tags":171,"search_phrases":172,"slug":173,"view_count":15,"doi":174,"paper":175,"created_at":189},3476,"Explainability and Reliability in Large Language Model Systems: A Survey of SHAP, LIME and Attention Frameworks","https:\u002F\u002Fdoi.org\u002F10.67317\u002Fijmsrt26sep093","Increasing adoption of language models in sensitive sectors such as healthcare, finance, cybersecurity, education, etc., highlights the significance of developing transparent decision support systems. This paper reviews the use of explanation techniques for language and machine learning models, including SHAP, LIME, attention-based explanations and frameworks that transform outputs from models into natural language explanations. It turns out that the existing literature demonstrates that although classical language models demonstrate good predictive and semantic performance, they lack transparency. In this regard, SHAP and LIME help in the detection of feature importance and combination of frameworks lead to explanations being more understandable for users. The literature also outlines some limitations of the existing techniques such as explanation faithfulness, hallucinations, biases, privacy issues, computational complexity and lack of benchmarks for evaluation. The use of explainability in healthcare, finance, cybersecurity, industrial systems and IoT is discussed based on the evidence found in the literature.","语言模型在医疗、金融、网络安全、教育等敏感领域的应用日益广泛，这使得开发透明的决策支持系统变得尤为重要。本文综述了用于语言模型和机器学习模型的可解释性技术，包括SHAP、LIME、基于注意力的解释方法，以及将模型输出转化为自然语言解释的框架。现有文献表明，尽管经典语言模型在预测和语义方面表现良好，但缺乏透明度。在这方面，SHAP和LIME有助于识别特征重要性，而框架的组合则使解释更易于用户理解。文献还指出了现有技术的一些局限性，如解释忠实度、幻觉、偏见、隐私问题、计算复杂性以及缺乏评估基准。基于文献中发现的证据，本文讨论了可解释性在医疗、金融、网络安全、工业系统和物联网中的应用。","International Journal of Modern Science and Research Technology","2026-09-23T00:00:00Z",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":168},"该文为通用大语言模型可解释性综述，未涉及三农或农业信息化场景，与平台主题无关。",[170],{"name":165,"url":162},[12],[],"ExplainabilityandReliabilityinLargeLangu-3476","10.67317\u002Fijmsrt26sep093",{"doi":174,"openalex_id":176,"authors":177,"venue":165,"cited_by_count":15,"oa_url":182,"card":183,"direction":188,"ingested_from":43},"W7214085362",[178,180],{"name":179,"orcid":9},"Mary Shakkina C",{"name":181,"orcid":9},"Miranda Lakshmi Travis","https:\u002F\u002Fwww.ijmsrt.com\u002Fstorages\u002Fdownload-paper\u002FIJMSRT26SEP093",{"tldr":184,"method":185,"finding":186,"direction":89,"opportunity":187},"综述大语言模型可解释性技术SHAP、LIME与注意力框架及其在敏感领域的应用。","文献综述，分析SHAP、LIME、注意力解释及自然语言解释框架。","经典模型预测好但缺乏透明；SHAP\u002FLIME可识别特征重要性，但存在忠实性、幻觉等局限。","农业大模型决策可解释性研究空白：构建面向农业场景的忠实性评估基准与可解释框架。","智慧农业 \u002F 农业物联网","2026-09-25T23:30:11.362189Z",{"id":191,"title":192,"url":193,"summary":194,"summary_zh":195,"content":9,"source_name":196,"source_url":193,"published_at":197,"category":12,"cover_url":9,"hotness":198,"is_selected":14,"score":15,"score_detail":199,"sources":201,"tags":205,"search_phrases":206,"slug":207,"view_count":15,"doi":208,"paper":209,"created_at":219},3346,"The Confluence of AI and Eco-Innovation: Shaping the Future of Multidisciplinary Research","https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22912613","Abstract Artificial Intelligence (AI) and eco-innovation are increasingly converging to redefine how societies address environmental degradation, resource scarcity, and climate risk. This paper examines the intersection of these two domains as an emerging site of multidisciplinary inquiry, one that draws simultaneously on computer science, environmental economics, engineering, and policy studies. Rather than treating AI merely as a technical enabler bolted onto existing green technologies, the paper argues that AI is reshaping the very logic of eco-innovation—accelerating discovery cycles, enabling predictive resource management, and creating new business models built around circularity and efficiency. Drawing on a structured review of academic literature, industry reports, and policy documents published largely over the past decade, the study identifies recurring themes: AI-driven materials discovery, smart energy grids, precision agriculture, and algorithmic carbon accounting. It also surfaces tensions that are often underexplored, including the substantial energy footprint of AI systems themselves, questions of data governance in environmental monitoring, and the risk of techno-solutionism crowding out structural policy reform. Using a qualitative-interpretive methodology combined with thematic content analysis, the paper maps the current research landscape and proposes a framework for understanding AI-eco-innovation convergence across four layers: technological, organizational, institutional, and ecological. The paper concludes that meaningful progress in this space depends not on AI alone but on deliberate multidisciplinary collaboration among technologists, environmental scientists, economists, and regulators. It offers directions for future research, including longitudinal impact studies and frameworks for measuring the net environmental value of AI-enabled innovation.","摘要 人工智能（AI）与生态创新正日益融合，重新定义社会应对环境退化、资源稀缺和气候风险的方式。本文考察这两个领域的交汇点，将其视为一个新兴的多学科研究场域，同时涉及计算机科学、环境经济学、工程学和政策研究。本文并不将AI仅仅视为附加于现有绿色技术之上的技术赋能工具，而是认为AI正在重塑生态创新的内在逻辑——加速发现周期、实现预测性资源管理，并围绕循环性与效率创造新的商业模式。基于对过去十年间主要发表的学术文献、行业报告和政策文件的结构化综述，本研究识别出反复出现的主题：AI驱动的材料发现、智能电网、精准农业和算法碳核算。研究还揭示了常被忽视的张力，包括AI系统自身的巨大能源足迹、环境监测中的数据治理问题，以及技术解决方案主义排挤结构性政策改革的风险。本文采用定性-阐释方法并结合主题内容分析，描绘了当前的研究图景，并提出了一个理解AI-生态创新融合的框架，涵盖四个层面：技术、组织、制度和生态。本文的结论是，该领域的有意义进展不仅取决于AI本身，还取决于技术专家、环境科学家、经济学家和监管者之间自觉的多学科协作。本文提出了未来研究方向，包括纵向影响研究以及衡量AI赋能创新净环境价值的框架。","Zenodo (CERN European Organization for Nuclear Research)","2026-09-30T00:00:00Z",25,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":200},"该论文讨论AI与生态创新的跨学科融合，未聚焦三农、农业信息化或智慧农业等本平台主题，相关性不足。",[202,203],{"name":196,"url":193},{"name":196,"url":204},"https:\u002F\u002Fdoi.org\u002F10.5281\u002Fzenodo.22912614",[12],[],"TheConfluenceofAIandEco-Innovation:Shapi-3346","10.5281\u002Fzenodo.22912613",{"doi":208,"openalex_id":210,"authors":211,"venue":196,"cited_by_count":15,"oa_url":193,"card":214,"direction":188,"ingested_from":43},"W7214104704",[212],{"name":213,"orcid":9},"Saleha Javed Abbas Syed",{"tldr":215,"method":216,"finding":217,"direction":40,"opportunity":218},"综述AI与生态创新融合的多学科研究，提出四层分析框架并指出未来方向。","结构化文献综述与主题内容分析，涵盖学术、产业与政策文本。","AI正重塑生态创新逻辑，但需警惕能耗、数据治理与技术解决主义风险。","可聚焦AI赋能农业碳核算与精准管理的净环境价值评估及跨学科治理框架。","2026-09-24T23:30:09.754901Z",{"id":221,"title":222,"url":223,"summary":224,"summary_zh":225,"content":9,"source_name":226,"source_url":223,"published_at":129,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":227,"sources":229,"tags":231,"search_phrases":232,"slug":233,"view_count":15,"doi":234,"paper":235,"created_at":245},3281,"Economic Growth Nowcasting in Mauritania using Machine Learning and Satellite Data","https:\u002F\u002Fdoi.org\u002F10.63620\u002Fmkijbaft.2026.1027","This paper examines the role of satellite data and machine learning techniques in improving the nowcasting of real GDP in Mauritania, a context characterized by limited data availability and delays in official statistics. By combining traditional macroeconomic indicators with satellite-based variables such as Nighttime Lights and the Normalized Difference Vegetation Index (NDVI), the study develops a framework capable of capturing real-time economic dynamics. The results show that the inclusion of satellite data improves predictive accuracy, particularly when using non-linear models such as XGBoost. In particular, XGBoost records a reduction in RMSE from 0.019 to 0.017 and an increase in R² from 0.372 to 0.483 when satellite variables are included. Nighttime Lights are strongly correlated with economic activity, while NDVI exhibits more limited explanatory power. Overall, the findings highlight the potential of integrating alternative data sources and machine learning methods to enhance economic monitoring and support decision-making in data-constrained environments.","本文考察了卫星数据和机器学习技术在改进毛里塔尼亚实际GDP即时预测（nowcasting）中的作用，该国面临数据可得性有限和官方统计数据滞后的背景。通过将传统宏观经济指标与夜间灯光（Nighttime Lights）和归一化植被指数（NDVI）等卫星变量相结合，本研究构建了一个能够捕捉实时经济动态的框架。结果表明，纳入卫星数据提高了预测精度，尤其是在使用XGBoost等非线性模型时。具体而言，当纳入卫星变量后，XGBoost的均方根误差（RMSE）从0.019降至0.017，R²从0.372提升至0.483。夜间灯光与经济活动高度相关，而NDVI的解释力则较为有限。总体而言，研究结果凸显了整合替代数据源和机器学习方法以增强经济监测并支持数据受限环境下决策的潜力。","OpenAlex",{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":228},"研究毛里塔尼亚GDP即时预测，与三农、农业信息化、智慧农业无关，不予入选。",[230],{"name":226,"url":223},[12],[],"EconomicGrowthNowcastinginMauritaniausin-3281","10.63620\u002Fmkijbaft.2026.1027",{"doi":234,"openalex_id":236,"authors":237,"venue":9,"cited_by_count":15,"oa_url":223,"card":240,"direction":89,"ingested_from":43},"W7213984344",[238],{"name":239,"orcid":9},"Yahya Abou LY",{"tldr":241,"method":242,"finding":243,"direction":119,"opportunity":244},"结合卫星数据与机器学习改进毛里塔尼亚实时GDP预测。","使用夜间灯光和NDVI卫星变量，结合XGBoost等非线性模型。","加入卫星数据后XGBoost的RMSE降低、R²提升，夜间灯光解释力强。","可探索多源卫星数据融合与可解释AI，提升数据稀缺地区经济监测精度。","2026-09-23T23:30:35.177095Z"]