Climate change presents a critical global challenge,threatening human well-being,ecosystems,economies,and societies.While mitigation efforts remain essential and critically important,the growing urgency of climate imp...Climate change presents a critical global challenge,threatening human well-being,ecosystems,economies,and societies.While mitigation efforts remain essential and critically important,the growing urgency of climate impacts necessitates immediate and effective adaptation measures.Effective adaptation strategies require advanced modeling tools with higher resolution,integration of ecosystem and social dynamics,and the ability to assess diverse adaptation scenarios.Local-scale models,which are performed at the scale of an administrative region,a country,or a specified region,are particularly valuable as they can incorporate specific adaptation measures and generate precise,contextspecific insights.These models play a key role in formulating tailored climate adaptation strategies and action plans.This paper explores the significance and challenges in developing such models,emphasizing the pressing need to accelerate their advancement.We call on the scientific community and policymakers to prioritize the development of tailored local-scale modeling tools and services to enhance resilience and better support adaptive responses to the complex and evolving challenges posed by climate change and rapid urbanization at the local level.展开更多
堆煤是输送机常见故障之一,为了保障煤矿工业生产的安全,需要对煤矿井下输送机的堆煤情况进行检测。然而现有的检测方法存在容易误触、检测可靠性较差等缺点,针对这些问题提出一种基于Transformer统一多尺度时序卷积(unified multi-scal...堆煤是输送机常见故障之一,为了保障煤矿工业生产的安全,需要对煤矿井下输送机的堆煤情况进行检测。然而现有的检测方法存在容易误触、检测可靠性较差等缺点,针对这些问题提出一种基于Transformer统一多尺度时序卷积(unified multi-scale temporal ConvTransformer,UnMS-TCT)网络用于输送机堆煤检测。首先融合RGB帧和光流帧提取的特征,使网络更全面地建模时空关系;然后在时序编码器中,将动态位置嵌入(dynamic position embedding,DPE),多头关系聚合器(multi-head relation aggregator,MHRA)以及多层感知机(multilayer perceptron,MLP)组成的全局模块,交叉注意力(cross-attention,CA)组成的局部模块,以交替方式形成全局-局部关系模块,增强多尺度下获取全局和局部时间关系的能力;其次利用残差全局-局部融合(residual global and local fusion,ResGLFus)模块融合多尺度特征,有效地提高融合过程的稳定性,最终实现高精度堆煤预测。实验结果表明:该方法能够实现对输送机堆煤的检测,mAP达到98.17%。展开更多
基金support of the National Natural Science Foundation of China(Nos.42288101&42375183)Shanghai International Science and Technology Partnership Project(No.21230780200)+1 种基金Shanghai B&R Joint Laboratory Project(No.22230750300)EU HORIZON Project FOCI(No.101056783).
文摘Climate change presents a critical global challenge,threatening human well-being,ecosystems,economies,and societies.While mitigation efforts remain essential and critically important,the growing urgency of climate impacts necessitates immediate and effective adaptation measures.Effective adaptation strategies require advanced modeling tools with higher resolution,integration of ecosystem and social dynamics,and the ability to assess diverse adaptation scenarios.Local-scale models,which are performed at the scale of an administrative region,a country,or a specified region,are particularly valuable as they can incorporate specific adaptation measures and generate precise,contextspecific insights.These models play a key role in formulating tailored climate adaptation strategies and action plans.This paper explores the significance and challenges in developing such models,emphasizing the pressing need to accelerate their advancement.We call on the scientific community and policymakers to prioritize the development of tailored local-scale modeling tools and services to enhance resilience and better support adaptive responses to the complex and evolving challenges posed by climate change and rapid urbanization at the local level.
文摘堆煤是输送机常见故障之一,为了保障煤矿工业生产的安全,需要对煤矿井下输送机的堆煤情况进行检测。然而现有的检测方法存在容易误触、检测可靠性较差等缺点,针对这些问题提出一种基于Transformer统一多尺度时序卷积(unified multi-scale temporal ConvTransformer,UnMS-TCT)网络用于输送机堆煤检测。首先融合RGB帧和光流帧提取的特征,使网络更全面地建模时空关系;然后在时序编码器中,将动态位置嵌入(dynamic position embedding,DPE),多头关系聚合器(multi-head relation aggregator,MHRA)以及多层感知机(multilayer perceptron,MLP)组成的全局模块,交叉注意力(cross-attention,CA)组成的局部模块,以交替方式形成全局-局部关系模块,增强多尺度下获取全局和局部时间关系的能力;其次利用残差全局-局部融合(residual global and local fusion,ResGLFus)模块融合多尺度特征,有效地提高融合过程的稳定性,最终实现高精度堆煤预测。实验结果表明:该方法能够实现对输送机堆煤的检测,mAP达到98.17%。
文摘目的对日间失眠症状反应量表(daytime insomnia symptom response scale,DISRS)进行汉化,形成中文版DISRS,并验证该量表汉化后的信效度及在军人群体中的应用。方法获得DISRS原作者授权后,根据Brislin翻译模型逐步进行正译、回译和文化调适。对海军某部983名官兵进行问卷调查,使用中文版DISRS、匹兹堡睡眠指数量表(Pittsburgh sleep quality index,PSQI)和抑郁-焦虑-压力量表(depression-anxiety and stress scale-21,DASS-21)进行测评。通过项目分析、内部一致性信度、重测信度、内容效度、结构效度和效标关联效度来检验量表的心理测量学特性。结果中文版DISRS共保留20个条目,验证性因子分析支持原量表3因子结构[近似误差均方根(root mean square error,RMSEA)=0.116、比较拟合指数(comparative fit index,CFI=0.879),增量拟合指数(incremental fit index,IFI)=0.879]。总量表的Cronbach′sα系数为0.967,重测信度为0.577。量表平均内容效度指数为1。中文版DISRS总分与PSQI、DASS-21总分均呈显著正相关(r值分别为0.525、0.589,P均<0.001)。结论中文版DISRS具有良好的信度和效度,可作为评估中国军人日间失眠症状的有效工具。
