Clustering Cities over Features Extracted from Multiple Virtual Sensors Measuring Micro-Level Activity Patterns Allows One to Discriminate Large-Scale City Characteristics.

The impact of micro-level people's activities on urban macro-level indicators is a complex question that has been the subject of much interest among researchers and policymakers. Transportation preferences, consumption habits, communication patterns and other individual-level activities can significantly impact large-scale urban characteristics, such as the potential for innovation generation of the city. Conversely, large-scale urban characteristics can also constrain and determine the activities of their inhabitants. Therefore, understanding the interdependence and mutual reinforcement between micro- and macro-level factors is critical to defining effective public policies. The increasing availability of digital data sources, such as social media and mobile phones, has opened up new opportunities for the quantitative study of this interdependency. This paper aims to detect meaningful city clusters on the basis of a detailed analysis of the spatiotemporal activity patterns for each city. The study is carried out on a worldwide city dataset of spatiotemporal activity patterns obtained from geotagged social media data. Clustering features are obtained from unsupervised topic analyses of activity patterns. Our study compares state-of-the-art clustering models, selecting the model achieving a 2.7% greater Silhouette Score than the next-best model. Three well-separated city clusters are identified. Additionally, the study of the distribution of the City Innovation Index over these three city clusters shows discrimination of low performing from high performing cities relative to innovation. Low performing cities are identified in one well-separated cluster. Therefore, it is possible to correlate micro-scale individual-level activities to large-scale urban characteristics.

Non-Intrusive Assessment of COVID-19 Lockdown Follow-Up and Impact Using Credit Card Information: Case Study in Chile.

In this paper, we propose and validate with data extracted from the city of Santiago, capital of Chile, a methodology to assess the actual impact of lockdown measures based on the anonymized and geolocated data from credit card transactions. Using unsupervised Latent Dirichlet Allocation (LDA) semantic topic discovery, we identify temporal patterns in the use of credit cards that allow us to quantitatively assess the changes in the behavior of the people under the lockdown measures because of the COVID-19 pandemic. An unsupervised latent topic analysis uncovers the main patterns of credit card transaction activity that explain the behavior of the inhabitants of Santiago City. The approach is non-intrusive because it does not require the collaboration of people for providing the anonymous data. It does not interfere with the actual behavior of the people in the city; hence, it does not introduce any bias. We identify a strong downturn of the economic activity as measured by credit card transactions (down to 70%), and thus of the economic activity, in city sections (communes) that were subjected to lockdown versus communes without lockdown. This change in behavior is confirmed by independent data from mobile phone connectivity. The reduction of activity emerges before the actual lockdowns were enforced, suggesting that the population was spontaneously implementing the required measures for slowing virus propagation.

Phylogenetic evaluation of taxonomic definition of didelphid mouse opossum of the genus Thylamys from valleys of Coquimbo region, Chile.

Only two species of Didelphidae are currently recognized in Chile, the sister species Thylamys elegans, endemic of Mediterranean ecorregion and Thylamys pallidior, the inhabitant of the Puna and desert canyons. Three subspecies have been described for T. elegans: T. e. elegans, T. e. coquimbensis and T. e. soricinus. However, a recent study based on morphological analyses, synonymized T. elegans coquimbensis from the Coquimbo valleys (30-31° S) with T. pallidior and proposed that T. elegans and T. pallidior could be in sympatry at Coquimbo valleys between Fray Jorge (30°40'S) and Paiguano (30°02' S). We assess the current definition of T. e. coquimbensis and T. e. elegans, as well as this taxonomical conflict among the mouse opossums from the Coquimbo valleys through phylogenetic analyses of cytochrome b mitochondrial gene sequences. In this study, for the first time, we used specimens from the type localities of T. e. coquimbensis and T. e. elegans. In addition, we analyzed diagnostic cranial structures for this taxonomic revision. The results supported two allopatric clades, allowing us to keep the taxonomic definition of T. e. elegans and T. e. coquimbensis as phylogenetic reciprocal monophyletic clades and polyphyletic with T. pallidior. This result corroborates previous morphological analyses, which support that mouse opossums from the Coquimbo valleys are T. e. coquimbensis, thus extending its geographic distribution to the coast of Coquimbo and Atacama regions. We don´t have evidence for sympatric distribution between T. elegans and T. pallidior in the Coquimbo region.

Caracterización de los ecosistemas de la fiebre aftosa

Esta monografía ha sido preparada en el Centro Panamericano de Fiebre Aftosa tomando como base los estudios sobre el tema realizados por los Servicios Oficiales de Salud Animal de cada uno de los países sudamericanos bajo los auspícios del Programa de Adiestramiento de Profesionales Latinoamericanos en Salud Animal (PROASA), 1982-1985.