Entre el orden y el desorden: el clero diocesano barcelonés de la contrarrefoma (1564-1700)
Resumen
La implantación de los decretos tridentinos en la diócesis de Barcelona fue un proceso lento en el tiempo que requirió del impulso decidido de los obispos que la gobernaron a partir de la segunda mitad del siglo xvi. El análisis de las constituciones sinodales así como de los procesos de la corte episcopal nos permite un acercamiento a la realidad del clero barcelonés tridentino.
- Referencias
- Cómo citar
- Del mismo autor
- Métricas
United Nations, Department of Economic and Social Affairs, Population Division, 2013. World Population Prospects: The 2012 Revision, Highlights and Advance Tables. Working Paper No. ESA/P/WP.228.
Paré, G, Jaana, M., and Sicotte, C., 2007. Systematic Review of Home Telemonitoring for Chronic Diseases: The Evidence Base. Journal of the American Medical Informatics Association, 14, 3, May/June.
Holland, T.M., Healthy at Home: The Economic Benefits of Remote Patient Monitoring.
https://insights.samsung.com/2016/02/05/healthy-at-home-the-economic-benefits-of-remote-patient-monitoring/; date of access: 2016/10/10.
European Commission, Joint Research Centre, Institute for Prospective Technological Studies. “Strategic Intelligence Monitor on Personal Health Systems (SIMPHS). Market Structure and Innovation Dynamics”, EUR 24669 EN.
CASAS, Center for Advanced Studies in Adaptive Systems.
http://casas.wsu.edu/research-projects, date of access: 2016/05/09.
Massachusetts Institute of Technology, Media Lab Project April 2015.
http://www.media.mit.edu/files/projects.pdf; date of access: 2016/05/08.
Mobile and Pervasive Computing Research, University of Florida.
http://www.icta.ufl.edu/gt.htm; date of access: 2016/05/09.
Phillips Enterprise Telehealth.
http://www.usa.philips.com/healthcare/solutions/enterprise-telehealth; date of access: 2016/05/11.
Samsung, Business Home, Telecare.
http://www.samsung.com/us/business/by-industry/healthcare/; date of access: 2016/05/11.
Suryawanshi, C.R., and Bhute, Y.C., 2014. A WSN based system for enhancing intra mobility solutions for healthcare – A review, International Journal of Computer Sciences and Engineering, 2 (9), pp. 33 – 37.
Cardinaux, F., Brownsell, S., Bradley, D., and Hawley, M.S., 2013. A home daily activity simulation model for the evaluation of lifestyle monitoring systems, Computers in Biology and Medicine, 43, pp. 1428 – 1436.
UCI Machine Learning Repository.
http://archive.ics.uci.edu/ml/datasets.html?sort=nameUp&view=list; date of access: 2016/08/17.
Kormanyos, B., and Pataki, B., 2013. Multilevel Simulation of Daily Activities: Why and How. 2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 15-17 July.
Elfaham, A., Hagras, H., Helal, S., Hossain, S., Woong Lee, J., and Cook, D., 2010. A Fuzzy Based Verification Agent for the Persim Human Activity Simulator in Ambient Intelligent Environments, 2010 IEEE International Conference on Fuzzy Systems (FUZZ), 18-23.
Evans, J.R., and Olson, D.L., 1998. Introduction to Simulation and Risk Analysis, Prentice Hall.
Schnotz, W., and Lowe, R.K., 2008. A unified view of learning from animated and static graphics, In: Lowe, R.K., Schnotz, W. (eds.) Learning with animation: Research implications for design, New York: Cambridge University Press, pp. 304-356.
Ding, D., Cooper, R.A., Pasquina, P.F., and Fici-Pasquina, L., 2011. Sensor technology for smart homes, Maturitas, 69, pp. 131-136.
Ozkul, T., and Sevin, A., 2014. Survey of Popular Networks Used for Biosensors, Biosensors Journal, 3, 1.
Coronel A., Feldman, S.R., Jozami, E., Kehoe, F., Piacentini, R. D. Dubbeling, M., and Escobedo, F. J., 2015. Effect of urban green areas on air temperature in a medium size Argentine city. Environment Science 2, pp 803-826.
Paré, G, Jaana, M., and Sicotte, C., 2007. Systematic Review of Home Telemonitoring for Chronic Diseases: The Evidence Base. Journal of the American Medical Informatics Association, 14, 3, May/June.
Holland, T.M., Healthy at Home: The Economic Benefits of Remote Patient Monitoring.
https://insights.samsung.com/2016/02/05/healthy-at-home-the-economic-benefits-of-remote-patient-monitoring/; date of access: 2016/10/10.
European Commission, Joint Research Centre, Institute for Prospective Technological Studies. “Strategic Intelligence Monitor on Personal Health Systems (SIMPHS). Market Structure and Innovation Dynamics”, EUR 24669 EN.
CASAS, Center for Advanced Studies in Adaptive Systems.
http://casas.wsu.edu/research-projects, date of access: 2016/05/09.
Massachusetts Institute of Technology, Media Lab Project April 2015.
http://www.media.mit.edu/files/projects.pdf; date of access: 2016/05/08.
Mobile and Pervasive Computing Research, University of Florida.
http://www.icta.ufl.edu/gt.htm; date of access: 2016/05/09.
Phillips Enterprise Telehealth.
http://www.usa.philips.com/healthcare/solutions/enterprise-telehealth; date of access: 2016/05/11.
Samsung, Business Home, Telecare.
http://www.samsung.com/us/business/by-industry/healthcare/; date of access: 2016/05/11.
Suryawanshi, C.R., and Bhute, Y.C., 2014. A WSN based system for enhancing intra mobility solutions for healthcare – A review, International Journal of Computer Sciences and Engineering, 2 (9), pp. 33 – 37.
Cardinaux, F., Brownsell, S., Bradley, D., and Hawley, M.S., 2013. A home daily activity simulation model for the evaluation of lifestyle monitoring systems, Computers in Biology and Medicine, 43, pp. 1428 – 1436.
UCI Machine Learning Repository.
http://archive.ics.uci.edu/ml/datasets.html?sort=nameUp&view=list; date of access: 2016/08/17.
Kormanyos, B., and Pataki, B., 2013. Multilevel Simulation of Daily Activities: Why and How. 2013 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA), 15-17 July.
Elfaham, A., Hagras, H., Helal, S., Hossain, S., Woong Lee, J., and Cook, D., 2010. A Fuzzy Based Verification Agent for the Persim Human Activity Simulator in Ambient Intelligent Environments, 2010 IEEE International Conference on Fuzzy Systems (FUZZ), 18-23.
Evans, J.R., and Olson, D.L., 1998. Introduction to Simulation and Risk Analysis, Prentice Hall.
Schnotz, W., and Lowe, R.K., 2008. A unified view of learning from animated and static graphics, In: Lowe, R.K., Schnotz, W. (eds.) Learning with animation: Research implications for design, New York: Cambridge University Press, pp. 304-356.
Ding, D., Cooper, R.A., Pasquina, P.F., and Fici-Pasquina, L., 2011. Sensor technology for smart homes, Maturitas, 69, pp. 131-136.
Ozkul, T., and Sevin, A., 2014. Survey of Popular Networks Used for Biosensors, Biosensors Journal, 3, 1.
Coronel A., Feldman, S.R., Jozami, E., Kehoe, F., Piacentini, R. D. Dubbeling, M., and Escobedo, F. J., 2015. Effect of urban green areas on air temperature in a medium size Argentine city. Environment Science 2, pp 803-826.
Entre el orden y el desorden: el clero diocesano barcelonés de la contrarrefoma (1564-1700). (2018). Studia Historica: Historia Moderna, 40(1), 185-232. https://doi.org/10.14201/shhmo2018401185232
+
−