scholarly journals Classifying the Diversity of Urban Diversities: an Inductive Analysis of European Cities

2021 ◽  
Author(s):  
Asya Pisarevskaya ◽  
Peter Scholten ◽  
Zeynep Kaşlı
Keyword(s):  
Urban Governance ◽  
Urban Setting ◽  
Classification Methods ◽  
Quantitative Classification ◽  
European Cities ◽  
Qualitative Understanding ◽  
Migration History ◽  
All Solutions ◽  
Geographical Position

AbstractThis paper provides an empirical classification of migration-related diversities in 166 European cities. The local turn in migration studies has shown that migration-related diversity may take varied forms in different cities. Our understanding of how and why cities differ is lagging behind the wealth of existing conceptualisations. This is partly because most studies look only at one kind of city, in particular, superdiverse global cities. This paper takes a systematic inductive approach to map the diversity of migration-related diversities in urban setting and understand the reasons behind such variations. Applying quantitative classification methods to European cities in France, Germany, the Netherlands and Italy, we search for a new meaningful classification of the urban diversity configurations based on measures of volume, variety and spread of migration-related diversity. Five empirical clusters of cities of migration are found: superdiverse cities, migrant minority cities, new diversity cities, low-migration cities and non-diverse cities. Subsequently, we develop a better qualitative understanding of these clusters by examining typical cities, their economic positioning, migration history, their policy and political structures, as well as their social and geographical position. A thorough classification, we argue, is necessary to have a more differentiated view of the existing urban diversities and go beyond one-size-fits-all solutions for urban governance of migration-related diversity.

The qualitative and quantitative classification of modern clastic marginal-marine depositional systems, Trinidad

2021 ◽  
Vol 91 (7) ◽  
pp. 710-734
Author(s):  
Saeed Khan ◽  
Hasley Vincent ◽  
Brent Wilson
Keyword(s):  
West Coast ◽  
East Coast ◽  
South Coast ◽  
Classification Methods ◽  
Sedimentary Record ◽  
Wave Regime ◽  
Quantitative Classification ◽  
Depositional Systems ◽  
Depositional Elements

ABSTRACT Trinidad's modern coastal depositional systems are for the first time documented by (traditional) descriptive and (modern) semiquantitative and quantitative classification methods. The processes controlling the morphology and distribution of these systems are also investigated. Google Earth™ satellite images, together with published basinal processes data (e.g., significant wave height, surface littoral currents, and tidal cyclicity) are used to describe system morphology, map depositional elements, and to determine the processes responsible for system distribution, respectively. Coastal depositional systems along Trinidad's east, south, and west coasts comprise deltas, estuaries, tidal-inlet complexes, strandplains, and tidal flats. Their distribution is controlled by the wave regime, although they are also influenced by tidal and fluvial processes. The wave regime changes from wave-dominated along the open east coast, to mixed-energy wave-dominated along the semi-sheltered south coast, and to mixed-energy tide-dominated along the sheltered west coast. Distribution of depositional systems related to this regime are such that the wave-dominated east coast sees the development of wave-dominated estuaries. The south coast has a series of wave-dominated, tide- and river-influenced deltas. The sheltered west coast is the most morphologically diverse with river- and wave-dominated deltas, strandplains, and tidal flats. The application of semiquantitative and quantitative classification methods on modern systems has showed their competence in classifying mixed-influence systems from their morphology and sedimentary record. Quantitative classification using depositional elements lends an appreciation to the morphological signatures of mixed-influence systems. Quantitative classification for sedimentary sections gives an appreciation of the preservation of mixed-influence physical processes. The combination of both allows the correlation of the impact of physical properties on morphology and sedimentary record (i.e., possible disparities between morphology and processes). The combination of semiquantitative and quantitative methods may also hold the key to unlocking the mixed-processes classification of depositional elements.

scholarly journals Machine learning algorithm improved automated droplet classification of ddPCR for detection of BRAF V600E in paraffin-embedded samples

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gabriel A. Colozza-Gama ◽  
Fabiano Callegari ◽  
Nikola Bešič ◽  
Ana C. de J. Paviza ◽  
Janete M. Cerutti
Keyword(s):  
Machine Learning ◽  
Sanger Sequencing ◽  
Learning Algorithm ◽  
Absolute Quantification ◽  
Braf V600e Mutation ◽  
Braf V600e ◽  
Driver Genes ◽  
Quantitative Classification ◽  
Cancer Driver

AbstractSomatic mutations in cancer driver genes can help diagnosis, prognosis and treatment decisions. Formalin-fixed paraffin-embedded (FFPE) specimen is the main source of DNA for somatic mutation detection. To overcome constraints of DNA isolated from FFPE, we compared pyrosequencing and ddPCR analysis for absolute quantification of BRAF V600E mutation in the DNA extracted from FFPE specimens and compared the results to the qualitative detection information obtained by Sanger Sequencing. Sanger sequencing was able to detect BRAF V600E mutation only when it was present in more than 15% total alleles. Although the sensitivity of ddPCR is higher than that observed for Sanger, it was less consistent than pyrosequencing, likely due to droplet classification bias of FFPE-derived DNA. To address the droplet allocation bias in ddPCR analysis, we have compared different algorithms for automated droplet classification and next correlated these findings with those obtained from pyrosequencing. By examining the addition of non-classifiable droplets (rain) in ddPCR, it was possible to obtain better qualitative classification of droplets and better quantitative classification compared to no rain droplets, when considering pyrosequencing results. Notable, only the Machine learning k-NN algorithm was able to automatically classify the samples, surpassing manual classification based on no-template controls, which shows promise in clinical practice.

Fast-HPLC Fingerprinting to Discriminate Olive Oil from Other Edible Vegetable Oils by Multivariate Classification Methods

2017 ◽  
Vol 100 (2) ◽  
pp. 345-350 ◽  
Author(s):  
Ana M Jiménez-Carvelo ◽  
Antonio González-Casado ◽  
Estefanía Pérez-Castaño ◽  
Luis Cuadros-Rodríguez
Keyword(s):  
Olive Oil ◽  
Vegetable Oils ◽  
Edible Oils ◽  
Support Vector ◽  
Classification Methods ◽  
Multivariate Classification ◽  
Chromatographic Fingerprint ◽  
K Nearest Neighbors ◽  
Pls Discriminant Analysis

Abstract A new analytical method for the differentiation of olive oil from other vegetable oils using reversed-phaseLC and applying chemometric techniques was developed. A 3 cm short column was used to obtain the chromatographic fingerprint of the methyl-transesterified fraction of each vegetable oil. The chromatographic analysis tookonly 4 min. The multivariate classification methods used were k-nearest neighbors, partial least-squares (PLS) discriminant analysis, one-class PLS, support vector machine classification, and soft independent modeling of class analogies. The discrimination of olive oil from other vegetable edible oils was evaluated by several classification quality metrics. Several strategies for the classification of the olive oil wereused: one input-class, two input-class, and pseudo two input-class.

Quantitative classification of near-fault ground motions selected by energy indicators

Structures ◽  
2022 ◽  
Vol 35 ◽  
pp. 780-791
Author(s):  
Dahai Zhao ◽  
Huiwei Wang ◽  
Ding Wang ◽  
Ruiguang Zhu ◽  
Jinghui Zhang
Keyword(s):  
Ground Motions ◽  
Quantitative Classification ◽  
Near Fault ◽  
Energy Indicators

Dubrovnik Republic in Russian Historiography in the 19th — the Beginning of the 20th Century

Istoriya ◽  
2021 ◽  
Vol 12 (9 (107)) ◽  
pp. 0
Author(s):  
Irina Vorobyova
Keyword(s):  
20Th Century ◽  
Urban Studies ◽  
Initial Period ◽  
Medieval History ◽  
European Cities ◽  
History Of ◽  
Imaginative Literature ◽  
Urban Problems ◽  
Scientific Results

This article concerns the initial period of the phenomena of Dubrovnik Republic, who kept its independence during centuries in the alien ethnic and confessional surroundings. This item seldom appeared in the sphere of attention of the specialists upon the European urban studies. The historian V. V. Makushev (1837—1883), being at the diplomatic service in Dubrovnik, studied the resources and published the scientific results in his articles and monographs. He created his author classification of the sources of the urban problems, evaluated their informational  capability, proved the historical value of the imaginative literature. This approach is actual for the analysis of the medieval history of the Mediterranean and other European cities.

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