1,010 research outputs found
Interpretación y equidad: de la Aequitas medieval a la Epikeia altomoderna
Actas del Congreso "Incidencias del lenguaje en los negocios jurídicos a lo largo de la Historia" celebrado en la Universidad Carlos III de Getafe, Madrid, los días 14 y 15 de abril de 201
Rafael del Riego. Una vida por la Constitución
Alternatives to the restored 1812 Spanish Constitution preceded the second constitutional period. The Doctrinairism, professed by a relevant part of the deputies in the Cortes, and by most of the governments, was the most important influence. All of them defended a model similar to the French Charte constitutionnelle of June 4, 1814; consequently, they vehemently opposed the single-chambered system, the suspensive veto and the preeminence of the Legislative branch, among other characteristics of the 1812 Constitution. This book aims to confront the ideas of the Constitution and the constitutional types of the two main ramifications of Spanish liberalism through the analysis of General and deputy Rafael del Riego cases, an eloquent expression of that political struggle.illustratorLa instauración del segundo periodo constitucional en 1820 venía precedida por alternativas a la Constitución restaurada, las más importantes de las cuales estaban influidas por el moderantismo y doctrinarismo que profesaban una parte relevante de diputados en las Cortes inauguradas en junio de ese año y la mayoría de los Gobiernos del periodo. Todos ellos defendieron un modelo similar a la Charte constitutionnelle francesa de 4 de junio de 1814 y, en consecuencia, se opusieron con vehemencia al sistema monocameral, al veto suspensivo y a la preeminencia del Legislativo entre otras características que ofrecía la de 1812. Este libro tiene por objeto la confrontación de las ideas de constitución y los tipos constitucionales de las dos principales ramas del liberalismo a través del análisis de los casos que afectaron al general y diputado exaltado Rafael del Riego. En ellos, esa lucha, a través de una de sus expresiones más elocuentes -el enfrentamiento entre el Ejecutivo y el Legislativo y el surgimiento de prácticas espurias-, se manifiesta de una manera elocuente
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of tendencies. Note, however, that the
effects of the measures’ control that start on a given day are not observed until approximately 5-7 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
a: the velocity at which spreading specific rate slows down; the higher the value, the better the
control.
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages
because growth is still exponential.
Next, we show a report with 8 graphs and a table with the short-term predictions for (1) European Union and
its countries, (2) other countries, (3) Spain and its autonomous communities.
We are currently adjusting the model to countries and regions with at least 4 days with more than 100
confirmed cases and a current load over 200 cases. The predicted period of a country depends on the number
of datapoints over this 100 cases threshold:
Group A: countries that have reported more than 100 cumulated cases for 10 consecutive days or
more ¿ 3-5 days prediction;
Group B: countries that have reported more than 100 cumulated cases for 7 to 9 consecutive days
¿ 2 days prediction;
Group C: countries that have reported more than 100 cumulated cases for 4 to 6 days ¿ 1 d ay
prediction.
We have introduced a change in fittings, that are now weighted at some points. The whole methodology
employed in the inform is explained in the last pages of this document.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version
Empiric model for short-time prediction of COVID-19 spreading
Covid-19 appearance and fast spreading took by surprise the international community.
Collaboration between researchers, public health workers and politicians has been
established to deal with the epidemic. One important contribution from researchers in
epidemiology is the analysis of trends so that both current state and short-term future
trends can be carefully evaluated. Gompertz model has shown to correctly describe
the dynamics of cumulative confirmed cases, since it is characterized by a decrease in
growth rate that is able to show the effect of control measures. Thus, it provides a
way to systematically quantify the Covid-19 spreading velocity. Moreover, it allows to
carry out short-term predictions and long-term estimations that may facilitate policy
decisions and the revision of in-place confinement measures and the development of
new protocols. This model has been employed to fit the cumulative cases of Covid-19
from several Chinese provinces and from other countries with a successful containment
of the disease. Results show that there are systematic differences in spreading velocity
between countries. In countries that are in the initial stages of the Covid-19 outbreak,
model predictions provide a reliable picture of its short-term evolution and may
permit to unveil some characteristics of the long-term evolution. These predictions can
also be generalized to short-term hospital and Intensive Care Units (ICU)
requirements, which together with the equivalent predictions on mortality provide key
information for health officials.CP, PJC and MC received funding from La Caixa Foundation (ID 100010434), under agreement LCF/PR/GN17/50300003; PJC received funding from Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR), Grup Unitat de Tuberculosi
Experimental, 2017-SGR-500; CP, DL, SA, MC received funding from Ministerio de Ciencia, Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00. This work has been also partially funded by the European
Comission - DG Communications Networks, Content and Technology through the contract LC-01485746.Preprin
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of tendencies. Note, however, that the
effects of the measures’ control that start on a given day are not observed until approximately 5-7 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
a: the velocity at which spreading specific rate slows down; the higher the value, the better the
control.
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages
because growth is still exponential.
Next, we show a report with 8 graphs and a table with the short-term predictions for (1) European Union and
its countries, (2) other countries, (3) Spain and its autonomous communities.
We are currently adjusting the model to countries and regions with at least 4 days with more than 100
confirmed cases and a current load over 200 cases. The predicted period of a country depends on the number
of datapoints over this 100 cases threshold:
Group A: countries that have reported more than 100 cumulated cases for 10 consecutive days or
more ¿ 3-5 days prediction;
Group B: countries that have reported more than 100 cumulated cases for 7 to 9 consecutive days
¿ 2 days prediction;
Group C: countries that have reported more than 100 cumulated cases for 4 to 6 days ¿ 1 d ay
prediction.
We have introduced a change in fittings, that are now weighted at some points. The whole methodology
employed in the inform is explained in the last pages of this document.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID‐19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of trends. Note, however, that the effects
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
a: the velocity at which spreading specific rate slows down; the higher the value, the better the control.
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages because growth is still exponential.
We show an individual report with 8 graphs and a table with the short-term predictions for different
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole
methodology employed in the inform is explained in the last pages of this document.
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints.
We also discuss a specific issue every day.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (author's final draft
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of trends. Note, however, that the effects
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
a: the velocity at which spreading specific rate slows down; the higher the value, the better the
control.
K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages
because growth is still exponential.
We show an individual report with 8 graphs and a table with the short-term predictions for different
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole
methodology employed in the inform is explained in the last pages of this document.
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints.
We also discuss a specific issue every day.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of trends. Note, however, that the effects
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
¿ a: the velocity at which spreading specific rate slows down; the higher the value, the better the
control.
¿ K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages
because growth is still exponential.
We show an individual report with 8 graphs and a table with the short-term predictions for different
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole
methodology employed in the inform is explained in the last pages of this document.
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints.
We also discuss a specific issue every day.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version
Analysis and prediction of COVID-19 for EU-EFTA-UK and other countries
The present report aims to provide a comprehensive picture of the pandemic situation of COVID-19 in the
EU countries, and to be able to foresee the situation in the next coming days.
We employ an empirical model, verified with the evolution of the number of confirmed cases in previous
countries where the epidemic is close to conclude, including all provinces of China. The model does not
pretend to interpret the causes of the evolution of the cases but to permit the evaluation of the quality of
control measures made in each state and a short-term prediction of trends. Note, however, that the effects
of the measures’ control that start on a given day are not observed until approximately 7-10 days later.
The model and predictions are based on two parameters that are daily fitted to available data:
¿ a: the velocity at which spreading specific rate slows down; the higher the value, the better the
control.
¿ K: the final number of expected cumulated cases, which cannot be evaluated at the initial stages
because growth is still exponential.
We show an individual report with 8 graphs and a table with the short-term predictions for different
countries and regions. We are adjusting the model to countries and regions with at least 4 days with more
than 100 confirmed cases and a current load over 200 cases. The predicted period of a country depends on
the number of datapoints over this 100 cases threshold, and is of 5 days for those that have reported more
than 100 cumulated cases for 10 consecutive days or more. For short-term predictions, we assign higher
weight to last 3 points in the fittings, so that changes are rapidly captured by the model. The whole
methodology employed in the inform is explained in the last pages of this document.
In addition to the individual reports, the reader will find an initial dashboard with a brief analysis of the
situation in EU-EFTA-UK countries, some summary figures and tables as well as long-term predictions for
some of them, when possible. These long-term predictions are evaluated without different weights to datapoints.
We also discuss a specific issue every day.These reports are funded by the European Commission (DG CONNECT, LC-01485746)
PJC and MC received funding from “la Caixa” Foundation (ID 100010434), under agreement
LCF/PR/GN17/50300003; CP, DL, SA, MC, received funding from Ministerio de Ciencia,
Innovación y Universidades and FEDER, with the project PGC2018-095456-B-I00Postprint (published version
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