Diseño de dos rutas turísticas para la parroquia rural San Pedro de Quingeo del cantón Cuenca

El proyecto de intervención “Diseño de dos rutas turísticas para la parroquia rural San Pedro de Quingeo del cantón Cuenca” tiene como objetivo identificar los antecedentes del centro histórico de Quingeo, analizar el inventario de los bienes patrimoniales del sector y proponer dos rutas turísticas que impulsen la interpretación del patrimonio cultural en la zona, buscando de esta manera revalorizar el patrimonio cultural de la parroquia, declarada Patrimonio Cultural de la Nación, a través del turismo. Es así que como primera parte se realiza una conceptualización general de la situación actual de la parroquia; su delimitación geográfica, organización política y social, estado económico y desarrollo del turismo en la zona. A continuación, a fin de determinar el potencial turístico de la parroquia, se efectúa un análisis de la demanda turística probable mediante el desarrollo de encuestas a distintos actores turísticos dentro y fuera de la zona de estudio. En tercer lugar, y con la información obtenida de las encuestas, se realiza el trazado de las dos rutas turísticas propuestas; se definen actividades, atractivos a visitar, actores rurales involucrados, logos, slogans y material publicitario. Finalmente, se opera y valida las dos rutas turísticas propuestas con el apoyo de actores turísticos con enfoques distintos, se realizan instrumentos de evaluación que reflejan el nivel de satisfacción de los participantes. Palabras claves: Turismo. Rutas turísticas. Quingeo. Patrimonio.The intervention project "Design of two tourist routes for the rural parish of San Pedro de Quingeo in the canton of Cuenca" aims to identify the background of the historic center of Quingeo, analyze the inventory of heritage assets in the sector and propose two tourist routes that promote the interpretation of cultural heritage in the area, seeking in this way to revalue the cultural heritage of the parish, declared Cultural Heritage of the Nation, through tourism. Thus, as a first part, a general conceptualization of the current situation of the parish is carried out; its geographical delimitation, political and social organization, economic status and development of tourism in the area. Next, in order to determine the tourist potential of the parish, an analysis of the probable tourist demand is carried out through the development of surveys to different tourist actors inside and outside the study area. Thirdly, and with the information obtained from the surveys, the layout of the two proposed tourist routes is carried out; activities, attractions to visit, rural actors involved, logos, slogans and advertising material are defined. Finally, the two proposed tourist routes are operated and validated with the support of tourist actors with different approaches, evaluation instruments are carried out that reflect the level of satisfaction of the participants. Keywords: Tourism, Tourist routes, Quingeo, Heritage.Licenciado en TurismoCuenc

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

So, to Speak

This anthology, the first in a series of publications entitled "Prendre Parole", contains 26 texts by Canadian visual artists who were asked to comment on how they conceive their artistic practice interweaving with the social fabric. The diverse styles of writing presented - fictional, anecdotal, polemical, biographical, philosophical - offer a wide range of critical perspectives on the relationship between art and society, and the personal/political responsibilities of being an artist. Artistic disciplines, cultural events and everyday life experiences are considered (directly and indirectly) in relation to topics such as place, language, story, science and technology, identity, time and space. Includes reprinted texts by Frenkel and Carr-Harris. 14 bibl. ref

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks