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Cover -- Title -- Copyright -- Dedication -- CONTENTS -- List of Figures -- List of Tables and Appendices -- Acknowledgments -- 1 Introduction -- 2 Global Patterns of Exposure to Political Intermediaries -- 3 Mobilization, Informal Networks and the Social Contexts of Turnout -- 4 Value Cleavages Revisited -- 5 The Changing Determinants of the Vote -- 6 Parties, Elections, Voters and Democracy -- 7 Intermediation, Mobilization, Voting and Citizen Participation: Findings From In-Depth and Longitudinal Analyses of Spain -- 8 Conclusion -- About the Contributors -- References -- Index.

Voting in Old and New Democracies examines voting behavior and its determinants based on 26 surveys from 18 countries on five continents between 1992 and 2008. It systematically analyzes the impact on voting choice of factors rooted in the currently dominant approaches to the study of electoral behavior, but adds to this analysis factors introduced or reintroduced into this field by the Comparative National Elections Project (CNEP)socio-political values, and political communication through media, personal discussion, and organizational intermediaries. It demonstrates empirically that these long-neglected factors have significant political impact in many countries that previous studies have overlooked, while "economic voting" is insignificant in most elections once long-term partisan attitudes are taken into consideration. Its examination of electoral turnout finds that the strongest predictor is participation by other family members, demonstrating the importance of intermediation. Another chapter surveys cross-national variations in patterns of intermediation, and examines the impact of general social processes (such as socioeconomic and technological modernization), country-specific factors, and individual-level attitudinal factors as determinants of those patterns. Complementing its cross-national comparative analysis is a detailed longitudinal case study of one country over 25 years. Finally, it examines the extent of support for democracy as well as significant cross-national differences in how democracy is understood by citizens.--

Some 25 years have elapsed since international financial institutions espoused a package of power sector reform measures that became known as the Washington Consensus. This package encompassed the establishment of autonomous regulatory entities, the vertical and horizontal unbundling of integrated national monopoly utilities, private sector participation in generation and distribution, and eventually the introduction of competition into power generation and even retail services. Exploiting a unique new data set on the timing and scope of power sector reforms adopted by 88 countries across the developing world over 25 years, this paper seeks to improve understanding of the uptake, diffusion, packaging, and sequencing of power sector reforms, and the extent to which they were affected by the economic and political characteristics of the countries concerned. The analysis focuses on describing the patterns of reform without judging their desirability or evaluating their impact. The paper finds that following rapid diffusion during 1995-2005, the spread of power sector reforms slowed significantly in 2005-15. Only a small minority of developing countries fully implemented the reform model as originally conceived. For the majority, reforms were only selectively adopted according to ease of implementation, often stagnated at an intermediate stage, and were sometimes packaged and sequenced in ways unrelated to the original logic. Country characteristics such as geography, income group, power system size, and political economy all had a significant influence on the uptake of reform. Moreover, a significant number of countries experienced reversals of private sector participation, or were unable to follow through with reform plans that were officially announced. Overall, power sector reform in the developing world lags far behind what was achieved in the developed world during the same time period. Yet, even in the developed world, the full package of reforms does not seem to have been universally adopted.

Buenaventura es un territorio de fronteras políticas, culturales y económicas; por su cercanía a Panamá y proximidad a países del Asia-Pacífico y ciudades del este de los Estados Unidos se ha convertido en el puerto más importante del país en términos geoestratégicos. Su ubicación y actividad portuaria la hacen una de las ciudades del Pacífico más importantes para las economías comerciales regionales y nacionales.

Cover -- Contents -- List of Figures -- List of Tables -- Acknowledgments -- List of Contributors -- 1 The 2012 Election in Context -- 2 Chronicle of a Victory Foretold: Candidates, Parties, and Campaign Strategies in the 2012 Mexican Presidential Election -- 3 The Electoral Institutions: Party Subsidies, Campaign Decency, and Entry Barriers -- 4 Time to Turn Back the Clock? Retrospective Judgments of the Single-Party Era and Support for the Institutional Revolutionary Party in 2012 -- 5 Public Mood and Presidential Election Outcomes in Mexico -- 6 Campaign Effects in Mexico since Democratization -- 7 Drugs, Bullets, and Ballots: The Impact of Violence on the 2012 Presidential Election -- 8 How Governmental Corruption Breeds Clientelism -- 9 Clientelism, Declared Support, and Mexico's -- 10 Effects of #YoSoy132 and Social Media in Mexico's 2012 Presidential Campaigns -- 11 Mexico's 2012 Presidential Election: Conclusions -- Index -- A -- B -- C -- D -- E -- F -- G -- H -- I -- J -- K -- L -- M -- N -- O -- P -- Q -- R -- S -- T -- U -- V -- W -- Y -- Z.

This research was partially supported by CONACyT (Mexico), the Alliance for Training and Research in Infrastructure for Development of Mexico, A.C. (FIIDEM). This research project also benefited from ITESO, the Jesuit University of Guadalajara, for Research Support Program scholarships for Ivana Georgina Kroepfly Cota and the SUPA program for Gabriela Ochoa-Covarrubias. ; The equitable accessibility to higher education favours social fairness in economic opportunities. This paper provides an empirical approach to the assessment of the (in)equity of accessibility from universities to sustainable transport modes: Light Rail Transit, Bus Rapid Transit, buses, and bicycle infrastructure in the Guadalajara Metropolitan Area (Mexico). In particular, the study designed and calculated an Access to Sustainable Transport from University Index by combining governmental and crowdsourced Open Access Data. It used spatial analysis techniques within a Geographic Information Systems environment, and multivariate statistical methods such as Principal Component Analysis and Cluster Analysis. The findings highlight the weakness in the accessibility to sustainable transport modes from the universities in the Metropolitan Area. Furthermore, this study revealed an unfavourable bias in the location of sustainable transport stations/stops in the vicinity of public universities. The results provide a methodology and empirical evidence for transport policy makers to reduce inequalities and therefore transport-related social exclusion in this under-represented, but socially relevant, student community. ; Consejo Nacional de Ciencia y Tecnologia (CONACyT) ; Alliance for Training and Research in Infrastructure for Development of Mexico, A.C. (FIIDEM) ; ITESO, the Jesuit University of Guadalajara

This book presents the trends in beliefs and values of people in 85 countries around the world from 1981 to 2004. It shows the cultural differences and similarities between countries and how human values are changing. It is based on the survey data collected in 1981-1984 and 1989-1993 by the European Values Study, the 1995-1997 World Values Surveys.

Infrasound is an increasingly popular tool for volcano monitoring, providing insights of the unrest by detecting and characterizing acoustic waves produced by volcanic processes, such as explosions, degassing, rockfalls, and lahars. Efficient event detection from large infrasound databases gathered in volcanic settings relies on the availability of robust and automated workflows. While numerous triggering algorithms for event detection have been proposed in the past, they mostly focus on applications to seismological data. Analyses of acoustic infrasound for signal detection is often performed manually or by application of the traditional short-term average/long-term average (STA/LTA) algorithms, which have shown limitations when applied in volcanic environments, or more generally to signals with poor signal-to-noise ratios. Here, we present a new algorithm specifically designed for automated detection of volcanic explosions from acoustic infrasound data streams. The algorithm is based on the characterization of the shape of the explosion signals, their duration, and frequency content. The algorithm combines noise reduction techniques with automatic feature extraction in order to allow confident detection of signals affected by non-stationary noise. We have benchmarked the performances of the new detector by comparison with both the STA/LTA algorithm and human analysts, with encouraging results. In this manuscript, we present our algorithm and make its software implementation available to other potential users. This algorithm has potential to either be implemented in near real-time monitoring workflows or to catalog pre-existing databases. ; This research was partially funded by KNOWAVES TEC2015- 68752 (MINECO/FEDER), by NERC Grant NE/P00105X/1, by Spanish research grant MECD Jose Castillejo CAS17/00154 and by VOLCANOWAVES European Union's Horizon 2020 Research and Innovation Programme Under the Marie Sklodowska-Curie Grant Agreement no 798480. ; Published ; Article 335 ; 4V. Processi pre-eruttivi ; JCR Journal

Multispectral and conventional cameras (red, green, blue [RGB] imager) onboard unmanned aerial vehicles (UAVs) provide very high spatial, temporal, and spectral resolution data. To evaluate the capacity of these techniques to assess vineyard water status, we carried out a study in a cv. Monastrell vineyard located in southeastern Spain in 2018 and 2019. Several irrigation strategies were applied, including different water quality and quantity regimes. Flights were performed using conventional and multispectral cameras mounted on the UAV throughout the growth cycle. Several visible and multispectral vegetation indices (VIs) were determined from the images with only vegetation (without soil and shadows, among others). Stem water potential was measured by pressure chamber, and the water stress integral (Sψ) was obtained during the season. Simple linear regression models that used VIs and green cover canopy (GCC) to predict Sψ were tested. The results indicate that visible VIs best correlated with Sψ. The green leaf index (GLI), visible atmospherically resistant index (VARI), and GCC showed the best fits in 2018, with R = 0.8, 0.72, and 0.73, respectively. When the best model developed with the 2018 data was applied to the 2019 data set, the model fit poorly. This suggests that on-ground measurements of vine stress must be taken each growing season to redevelop a model that predicts water stress from UAV-based imaging. ; This research was funded by Ministry of Science, Innovation and Universities, grant numbers RTC-2017-6365-2, AGL2017-82927- C3-2-R, and AGL2017-83738-C3-3-R; and by the Government of Castilla-La Mancha, grant number SBPLY/17/180501/000251. The authors acknowledge the funding from Ministry of Science, Innovation and Universities with a University Teaching Scholarship (Formación de Profesorado Universitario, FPU)

Multispectral and conventional cameras (red, green, blue [RGB] imager) onboard unmanned aerial vehicles (UAVs) provide very high spatial, temporal, and spectral resolution data. To evaluate the capacity of these techniques to assess vineyard water status, we carried out a study in a cv. Monastrell vineyard located in southeastern Spain in 2018 and 2019. Several irrigation strategies were applied, including different water quality and quantity regimes. Flights were performed using conventional and multispectral cameras mounted on the UAV throughout the growth cycle. Several visible and multispectral vegetation indices (VIs) were determined from the images with only vegetation (without soil and shadows, among others). Stem water potential was measured by pressure chamber, and the water stress integral (Sψ) was obtained during the season. Simple linear regression models that used VIs and green cover canopy (GCC) to predict Sψ were tested. The results indicate that visible VIs best correlated with Sψ. The green leaf index (GLI), visible atmospherically resistant index (VARI), and GCC showed the best fits in 2018, with R = 0.8, 0.72, and 0.73, respectively. When the best model developed with the 2018 data was applied to the 2019 data set, the model fit poorly. This suggests that on-ground measurements of vine stress must be taken each growing season to redevelop a model that predicts water stress from UAV-based imaging. ; This research was funded by Ministry of Science, Innovation and Universities, grant numbers RTC-2017-6365-2, AGL2017-82927- C3-2-R, and AGL2017-83738-C3-3-R; and by the Government of Castilla-La Mancha, grant number SBPLY/17/180501/000251. The authors acknowledge the funding from Ministry of Science, Innovation and Universities with a University Teaching Scholarship (Formación de Profesorado Universitario, FPU)