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From July through September this year, up to 30 million people are traveling to the cities of Nashik and Trimbakeshwar in India to bathe in the holy waters of the Godavari River, as part of the Kumbh Mela Hindu religious festival. Amidst this mass gathering—supported by acres and acres of temporary parking lots, police stations, fire stations, health clinics, streetlights and toilets—a small band of health and IT experts from the U.S. and India has introduced a new mobile health surveillance system to help keep the millions of visitors healthy while they’re at the festival. The Jana Swasthya Project (“Jana Swasthya” means “public health” in Hindi), has two goals: One is to conduct disease surveillance in real time to help health workers at the festival nip potential outbreaks in the bud and allocate health resources wisely. Another is more long-term: to conduct a mass screening program for oral health and hypertension for visitors and workers at the festival.

This dataset contains the prices offered under experimental conditions by 400 participants for a pound of three types of rice (regular, premium, and biofortified) in the Cartagena municipality in Colombia—furthermore, a brief socio-economic characterization of the participants and their nutrition knowledge.<br><br> The dataset can be used to identify the willingness to pay for a biofortified crop. To understand this willingness, analyze its variation under different information contexts and examine the potential market segments for this product. <br><br> Methodology: Experimental Auction with three rounds varying the participants' level of information regarding the rice they were testing. In the case of the characterization in-person one-to-one survey.

<p>This data collection - The Trachtenberg Papers - broadly concerns Cold War policy from the end of WWII to 1964. The data was accumulated in order to write several books and articles relating to Cold War relations during this pivotal period, most notably <i>A Constructed Peace: The Making of the European Settlement, 1945-1963</i> (Princeton: Princeton University Press, February 1999).</p> <p>This particular data project encompasses Cold War documents from France. Data encompass the period between 1945 and 1959; and are organized in three folders, each folder including data for a five year period. </p>

The MOBILISE project examines why some people respond to discontent by protesting, others by migrating while yet others stay immobile. It focuses on four countries that have seen outmigration and protest in recent year (Ukraine, Poland, Morocco and Argentina) and migrants from these countries who live in Germany, the United Kingdom and Spain. The main body of MOBILISE survey data are nationally representative face-to-face surveys in Ukraine, Poland, Morocco and Argentina. As these surveys are unable to capture (current) migrants from these countries – a group that is crucial to answering the MOBILISE research question – MOBILISE employs a migrant survey targeted at three destination countries; Germany, the UK and Spain. MOBILISE migrant surveys were closely oriented to the national surveys in order to achieve the longitudinal nature of the data. All of the surveys thoroughly ask for political views and beliefs as well as socio economic background, the reasons and motivations to (or not) migrate and the reason to (or not) protest. The migrant survey was run online. We also ran two supplementary online national surveys targeting the general population in Ukraine and Argentina. All MOBILISE national and migrant surveys are set-up as a two wave panel. The first wave of data collection for the migrant and national survey started in September 2019 and finished in March 2020. The second wave started between December 2020 and December 2021. This data deposit contains wave one and two of the migrant and national online surveys (the nationally representative surveys are deposited separately).

Subject: STANDARD DEPOSIT TERMS 1.0 Type: DATAPASS:TERMS:STANDARD:1.0 Notes: of the Archive), within the Data Preservation Alliance for the Social Sciences ("Data-PASS") in accordance with the Data-PASS terms (the "Terms") of use (available from: http://www.icpsr.org/Data-PASS). Including permission to: (a) redisseminate copies of the Data Collection in a variety of distribution formats only according to the standard terms of use of the Archive; (b) promote and advertise the Data Collection in any publicity (in any form) for Data-PASS and the Archive; (c) describe, catalog, validate and document the Content; (d) store, translate, copy or re-format the Data Collection in any way to ensure its future preservation and accessibility, improve usability and/or protect respondent confidentiality; (e) incorporate metadata (cataloging information) or documentation regarding this study into public access catalogues. The Archive represents and warrants that the Content conforms to all Terms and that the Archive is lawfully entitled and has full authority to license Data-Pass to use the Materials in the ways described in the Terms.; Contains non-confidential data on patients admitted to and discharged from all California acute care hospitals, including general acute care, skilled nursing, psychiatric care, alcohol/drug rehabilitation care, and rehabilitation care facilities. Details include county identification, age, gender, race, length of stay, date of admission, site from which the patient was admitted (i.e., emergency room, short term acute care hospital, intermediate care facility, skilled nursing, home health service, newborn, etc.), type of admission, diagnoses, procedures, patient disposition, expected source of payment, and total charges.

Les données mises à disposition relatent un suivi temporel et spatial de la bactérie Xylella fastidiosa en France de 2015 à aujourd’hui. Cette bactérie, organisme de quarantaine sur le territoire de l'Union Européenne est transmise par des insectes piqueurs-suceurs et s’attaquent à une large gamme de plantes hôtes (cultures arboricoles, viticoles, ornementales, Plantes à Parfum, Aromatiques et Médicinales). Elle a été détectée dans les régions Corse et PACA en 2015 puis en Occitanie en 2020. Chaque année une surveillance officielle est mise en place sur le territoire national, conformément à la réglementation européenne (règlement d'exécution (UE) 2020/1201), et des milliers de végétaux sont échantillonnés puis analysés en laboratoire pour recherche de la bactérie et identification de sa sous-espèce le cas échéant. Ces données centralisées par l’ANSES proviennent de différentes structures de terrain (SRALs, FREDONs…), du réseau de laboratoires agréés et du laboratoire national de référence. Les référentiels OEPP et INSEE sont utilisés pour renseigner respectivement l'espèce végétale et les données de localisation des végétaux prélevés (codes INSEE). Deux fichiers sont mis à disposition, le jeu de données issu de la surveillance de la bactérie (data_XF_dateMAJdata), un tableau des attributs décrivant les variables retenues (tableau_attributs_XF) ainsi que la grille spatiale (500m x 500m) dans le cadre de la construction du dataset (grid_quadrat_XF).

Zbirka kratke proze. Mešanica potopisne, lirične, osmišljene in tudi »pop« pripovedi bralca popelje tako v intimen svet avtorice kot v osrčje Manhattna, ki ga je – Flisova je mojstrica podrobnosti in ustvarjanja vzdušja – mogoče začutiti s prav vsemi čutili.

An assessment of what is known about problems related to pharmacist prescribing, options for addressing these problems, and key implementation considerations. The citizen brief was an input to a citizen panel on the topic of exploring models for pharmacist prescribing in Ontario.

The promotion of green purchase is one of the ways to minimize the environmental impact form increasing consumption. Eurobarometer's conducted survey (year 2012) showed big differences in green purchase behavior in European Union which did not depend on economic development and location. Austria was the only EU country where the relative majority of citizens (48%) often buy the environmentally friendly products, meanwhile the least respondents answer that they often buy these products in Lithuania (only 15%). Applying the approach of Structural Equation Modeling with latent variables, in the context of environmentally friendly behavior we searched for the main external determinants of green purchase behavior in both these both countries. We revealed the factors which are associated with country level. We chose these countries because they had very different level of GDP. The results showed that environmental friendly social norms, importance of products prices, sex and country aspect had significant impact on green purchase behavior, meanwhile the environmentally friendly behavior is not directly related to purchase behavior. Moreover despite that the country as a factor was not associated with environmentally friendly social norms, the differences of green purchase, emvironmentally friendly behavior and importance of product price between countries were considerable. These findings have important implication for sales management and state policy to consider the countries specificities in seeking the promotion of green purchase in the EU.