Maxwell's role in turning the concept of model into the methodology of modeling

This is a contribution towards a history and philosophy of modeling in its early stages in electromagnetism. In 1873, James Clerk Maxwell (1831–1879) hinted at the methodology of modeling at the end of his Treatise on Electricity and Magnetism. We focus on Maxwell's impact on physicists who immediately followed him, specifically Oliver Lodge (1851–1940) and George Francis FitzGerald (1851–1901). We begin with the role that the scientific concept of model played in the late nineteenth century, as assessed by Ludwig Boltzmann (1844–1906). We then discuss the role of hypothesis as a methodology, the appeal to (dynamical) illustration, and the way Maxwell applied model and working model in his studies of electromagnetism. We show that for Maxwell these key terms were kept distinct, but Lodge did not maintain these distinctions and, in this regard, FitzGerald followed Lodge. Notwithstanding Lodge's influence, Fitzgerald modified Maxwell's theory based on the mechanical model he designed, thereby implicitly taking the first step towards modeling. This methodology consists in drawing consequences from the (mechanical) model to the (electrodynamic) theory and modifying the latter in light of the functioning of the former. At the core of our argument is the thesis that it was a methodological novelty to move from the concept of model to the methodology of modeling. The introduction of modeling as a new methodology into physics in the late nineteenth century was a major event which deserves proper recognition.     

基于熵评价模态分解的雷达信号双谱特征识别

针对在低信噪比下雷达信号调制识别准确率低、抗噪性差的问题, 提出一种基于熵评价模态分解和双谱特征提取的识别方法。利用双谱可以抑制高斯噪声的特点, 分析了在低信噪比下进行信号调制识别的可行性并引入了噪声项。由于噪声项的干扰, 双谱在0 dB以下时, 噪声抑制效果变差, 提出了基于信息熵评价的经验模态化分解对信号进行预处理, 提高信噪比。最后, 设计了卷积神经网络分类器, 实现对不同调制类型信号的识别。仿真实验结果表明, 本文方法相比传统方法具有良好的抗噪性, 能够在低信噪比下对不同类型信号进行有效识别。     

谈“十四五”生态保护与绿色发展的生态关系

 从“十四五”保护与发展的生态关系角度，探讨了生态保护与绿色发展的十大生态关系，阐述了生态保护和绿色发展中的一系列有关生态关系的生态智慧及生态技术，并对长江、黄河等流域的生态保护和修复提出了相关建议。     

动力学模态分解方法重构及预测流场误差分析

利用动力学模态分解(dynamic mode decomposition,DMD)方法可以实现非定常流场的分解、重构和预测,但该方法重构和预测流场的误差需要给出定量分析.鉴于此,提出了定量描述动力学模态分解重构和预测流场的误差分析方法,以雷诺数Re=80的圆柱绕流二维流场数值模拟结果为例,研究了非线性流动和周期性流场重构和预测误差的动态变化情况.结果表明:依据能量大小确定的模态反映了流场的主要相干结构;低频、低增长/衰减率和大尺度的相干结构能量占比大,对流场的影响较大;DMD方法可以准确重构非线性和周期性变化流场,重构的误差小于10-10,预测流场的误差较重构流场出现跳跃增大现象;DMD方法预测非线性变化流场的误差在样本时间区间内较小(小于10-3),超出样本区间误差的发展急剧增大,变化情况依赖于数据样本;预测周期性流场的误差稳定在10-4左右.     

实验动物行业兽医现状分析

实验动物行业中,兽医体现在实验动物相关工作中的每一个环节,包括实验动物的日常管理、动物实验的设计、实验过程中动物健康保障和护理、实验动物福利的监督和管理、动物实验技术的应用、实验动物取材、施行安死术等。通过参阅相关文献资料,结合自身工作总结,就目前实验动物兽医现状进行分析,供各位同仁以参考。     

创新文化竞争力国际比较研究

提升中国创新文化国际竞争力,是全面塑造发展新优势的关键着力点,对我国建设创新型国家具有基础性、长期性、决定性影响.通过构建创新文化竞争力指标体系,选取GII创新指数排名和GDP总量排名均为前20的国家作为研究对象,运用主成分分析法对创新文化国际竞争力进行评价,研究发现:①从综合竞争力水平来看,英国、荷兰、美国、瑞士处于第一梯队,德国、加拿大、法国处于第二梯队,中国、韩国、日本为第三梯队;②从竞争力构成要素来看,中国创新文化可持续发展能力和国家创新驱动力具有相对竞争优势,发展基础力和创新型产业支撑力亟待提升,创新文化吸引力也存在进步空间.为此,提出完善创新文化发展的基础条件、讲好中国故事、加大要素投入等管理启示,以期为提升中国创新文化国际竞争力,建设创新型国家提供针对性建议.     

Little-known and phylogenetically obscure South African estuarine microgastropods (Mollusca: Truncatelloidea) as living animals

Areas of the Knysna estuarine bay in the Western Cape are dominated by three endemic South African truncatelloid microgastropods, temporarily known as ‘Hydrobia’ knysnaensis (Krauss), ‘Assiminea’ capensis (Sowerby) and ‘Assiminea’ globulus Connolly. Although first described 80–170 years ago and present in abundance (up to 100,000 m^?2), they remain surrounded by confusion and still await taxonomic assignment, largely because they appear most atypical members of their groups by virtue of anatomy and/or biogeography and/or habitat. This study contributes in-life perspectives to morphological and phylogenetic analyses known to be on-going. At Knysna, they are syntopic: at least two occurring in >85% and all three in >40% of individual 0.0026 m² samples from their region of dominance. Nevertheless, they tend to greater abundance in divergent microhabitats; ‘A.’ globulus dominating higher tidal levels, and ‘A.’ capensis and ‘Hydrobia’ lower ones; the former especially unvegetated sediment, the latter, if anything, seagrass. Interspecific feeding interactions appear unlikely to be responsible for these patterns, other evidence suggesting that all are maintained below carrying capacity. Field biology of ‘H.’ knysnaensis generally appears equivalent to that of northern-hemisphere intertidal hydrobiids and that of ‘A.’ globulus is typically assimineid, albeit at atypically low shore height. Unlike assimineids, however, ‘A.’ capensis is truly aquatic. The success of these truncatelloids in unusual circumstances may be consequent on the absence from South Africa of other microgastropod groups that fill their niches elsewhere in the southern hemisphere.     

Constructing and evaluating core inflation measures from component‐level inflation data

This paper undertakes a comprehensive examination of 10 measures of core inflation and evaluates which measure produces the best forecast of headline inflation out‐of‐sample. We use the Personal Consumption Expenditure Price Index as our measure of inflation. We use two sets of components (17 and 50) of the Personal Consumption Expenditure Price Index to construct these core inflation measures and evaluate these measures at the three time horizons (6, 12 and 24 months) most relevant for monetary policy decisions. The best measure of core inflation for both sets of components and over all time horizons uses weights based on the first principal component of the disaggregated (component‐level) prices. Interestingly, the results vary by the number of components used; when more components are used the weights based on the persistence of each component is statistically equivalent to the weights generated by the first principal component. However, those forecasts using the persistence of 50 components are statistically worse than those generated using the first principal component of 17 components. The statistical superiority of the principal component method is due to the fact that it extracts (in the first principal component) the common source of variation in the component level prices that accurately describes trend inflation over the next 6–24 months.