The Scale and Structure of Funding Expenditures for China’s Firstclass Universities

Adequate funding is identified as a crucial factor in ensuring the success of these universities,impacting talent cultivation,scientific research,and social services.Since the 1990s,China has launched several key projects to enhance the development of its first universities and aimed at elevating these institutions to world-class status.Using data from 34 first-class universities in China from 2014 to 2022,this study analyzes the characteristics and differences in expenditure.It employs an independent sample t-test model to compare the C9 League universities with other first-class universities.The findings reveal significant gaps in total expenditure and varying priorities in expenditure categories,with education being the dominant expenditure item.The study concludes with suggestions for optimizing the efficiency of fund utilization to support the development of world-class universities in China.

中国陆生脊椎动物野外调查的发展现状与文献分析

新中国成立以来,我国已开展了大量陆生脊椎动物的本底调查和多样性研究项目,取得了一系列成果,并有学者针对兽类、鸟类和两栖爬行类的野外调查监测进行了总结和展望,但尚缺乏对所有陆生脊椎动物类群的调查历史和现状的分析及基于文献收集的研究,特别是对调查方法和技术手段的对比与总结。因此,本文通过文献收集的方法,基于中国知网、Web of Science核心合集和以图书检索为主的读秀学术搜索,以“兽类”“鸟类”“爬行类”“两栖类”“动物资源”“调查”“监测”“新种”“新记录”和“物种多样性”作为检索词,检索并筛选了与兽类、鸟类、爬行类及两栖类陆生脊椎动物调查相关的文献资料共3,504篇,对陆生脊椎动物调查的研究文献在全国各省级行政区、生物多样性热点地区的分布,及其运用的调查方法和技术手段进行了系统的分析和比较。结果表明:相较兽类和两栖爬行类的调查,我国鸟类多样性的调查最多,发表文献占所有文献的70.26%。四川、云南的陆生脊椎动物调查最多,分别发表285篇、260篇文献。分布于我国的4个全球生物多样性热点地区的调查强度存在显著差异,印缅生物多样性热点地区和中国西南山地的研究文献较多,分别为348篇、324篇文献;中亚山地、喜马拉雅山地的研究文献较少,分别为71篇、66篇文献。陆生脊椎动物调查方法主要采用样线法、样点法、样方法和直接计数法,或将上述几种方法综合应用,样线法在所有场景(如:高山冻原、农田、城市等)中应用频率最高;技术手段以直接观察法、采集法、红外相机陷阱法为主,其中直接观察法在所有场景(如城市、湿地、草原等)中应用频率最高。当前,我国陆生脊椎动物调查已取得很多新进展,包括新兴物种采集和物种识别技术的发展(如无人机技术在大型兽类和集群水鸟上的应用、卫星追踪在迁徙鸟类上的应用等)、大数据时代下调查方法的改善和数据管理的提升等。未来我国的陆生脊椎动物调查,应拓宽新兴物种采集方法和识别技术的应用范围,进一步关注和发掘脊椎动物的新调查技术,以大数据为基础完善种群数据分析与调查管理体系,并朝着面向大众、服务社会的方向发展,以引起全社会对生物多样性保护的重视。本文以整体的视角概述了陆生脊椎动物各类群调查的情况,评估了不同地区调查强度的差异,并在调查方法和技术手段方面作了总结和展望,可为未来国内陆生脊椎动物野外调查工作的总体方向、调查侧重、方法运用等方面提供一定的参考。

Molecular insights of nanozymes from design to catalytic mechanism

Emerging as cost-effective potential alternatives to natural enzymes,nanozymes have attracted increasing interest in broad fields.To exploit the in-depth potential of nanozymes,rational structural engineering and explicit catalytic mechanisms at the molecular scale are required.Recently,impressive progress has been made in mimicking the characteristics of natural enzymes by constructing metal active sites,binding pockets,scaffolds,and delicate allosteric regulation.Ingenious in-depth studies have been conducted with advances in structural characterization and theoretical calculations,unveiling the“black box”of nanozymecatalytic mechanisms.This review introduces the state-of-art synthesis strategies by learning from the natural enzyme counterparts and summarizes the general overview of the nanozyme mechanism with a particular emphasis on the adsorbed intermediates and descriptors that predict the nanozyme activity.The emerging activity assessment methodology that illustrates the relationship between electrochemical oxygen reduction and enzymatic oxygen reduction is discussed with up-to-date advances.Future opportunities and challenges are presented in the end to spark more profound work and attract more researchers from various backgrounds to the flourishing field of nanozymes.

Molecular engineering of carbon nitrides for overall photosynthesis of H_(2)O_(2)

Artificial photocatalysis offers a promising strategy to sustainably produce hydrogen peroxide(H_(2)O_(2))that is one of the most valuable multifunctional chemicals.Among various photocatalysts,polymeric carbon nitride(pCN)has drawn continuous attention in non-sacrificial H_(2)O_(2)production.However,the poor activ-ity of half reactions,ie.,the oxygen reduction reaction(ORR)and water oxidation reaction(WOR),greatly restricts the efficiency of photocatalytic H_(2)O_(2) production.In this highlight,we discuss the significant ad-vances in molecular engineering of carbon nitrides for H_(2)O_(2) photosynthesis and the importance of the deep understanding of the photocatalysis process for rational design and reaction pathways of organic conjugated polymers to address the growing H_(2)O_(2)demand.Furthermore,we summarize the emerging applications of photocatalytic H_(2)O_(2)productions beyond energy and environment.

GroupNet:Learning to group corner for object detection in remote sensing imagery

Due to the attractive potential in avoiding the elaborate definition of anchor attributes,anchor-free-based deep learning approaches are promising for object detection in remote sensing imagery.Corner Net is one of the most representative methods in anchor-free-based deep learning approaches.However,it can be observed distinctly from the visual inspection that the Corner Net is limited in grouping keypoints,which significantly impacts the detection performance.To address the above problem,a novel and effective approach,called Group Net,is presented in this paper,which adaptively groups corner specific to the objects based on corner embedding vector and corner grouping network.Compared with the Corner Net,the proposed approach is more effective in learning the semantic relationship between corners and improving remarkably the detection performance.On NWPU dataset,experiments demonstrate that our Group Net not only outperforms the Corner Net with an AP of 12.8%,but also achieves comparable performance to considerable approaches with 83.4%AP.