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Endogenous tariff formation has been the subject of theoretical studies that attempt to determine the fundamental economic variables that influence the structure of industry protection implemented by international trade policy makers. An empirical analysis of endogenous tariff formation under the framework of a regional trade agreement implemented by the Andean Community Group is offered in this dissertation. Econometric models for the group's common external tariff (CET) and for individual country tariff deviations with respect to the CET are estimated. The analysis is based on cross-sectional industrial and trade data for 1996, collected at four digit level of aggregation. The level of aggregation refers to the specific definition of industrial sectors included in the International Standard Industrial Code (ISIC). While previous studies on another regional integrated group in South America (MERCOSUR) use data at the three digit level, the aggregation used in this research implies a significant increase in the sample size, and also a more homogeneous specification regarding the composition of the industrial sectors under analysis. The causal links among the variables are obtained by using the directed acyclical graphs (DAGs) approach. This allows for a refined search for causal relationships. The approach is particularly appealing for the analysis of endogenous trade protection since it allows analyzing economic systems that involve policy intervention. The empirical analysis supports several of the classic theoretical models on trade protection. The results are consistent with the equity concern model, which suggests that governments tend to protect industrial sectors that employ a significant number of low wage unskilled workers. The estimated models also support the interest group and the adding machine theoretical formulations. However, a rather interesting result derived from the DAG analysis is the feedback interaction that seems to operate between tariffs and policy variables. The current literature restricts the estimation of trade protection by imposing tariffs as the dependent variable with no reverse effect from this variable to the policy variables. Our results challenge this unidirectional causality view, since an effect from tariffs to the policy variables shows up in most of the estimated specifications.

Cold water is perhaps the most common quenchant used for heat treatable aluminum alloys. In many situations, excessive distortion and cracking problems require the use of a less severe quenchant such as hot water or a Type I aqueous polymer quenchant. However, when these alternative quenching media are used, the distortion improvement achieved is typically accompanied by a corresponding loss of strength. This paper will provide an overview of cold versus hot water quenching and the potential use of Type I polymer quenchants. The potential use of quench factor analysis to aid in quenchant media selection and corresponding property prediction is reviewed and applications are demonstrated. The often dramatic impact of the surface condition of aluminum on quenching performance and properties achieved will also be included in this review.

Polycrystalline aluminum nitride thin films were produced with a microwave-plasma enhanced chemical vapor deposition technique. The plasma-injector distance, the substrate temperature and the RF bias were the main variables which allowed achieving this objective. At the time, it was possible to control the preferential orientation as 0001 or 1010, both interesting for piezoelectric applications. The growth mechanisms that conducted to film microstructure development under different process conditions were explained, enriched by the comparison with a physical vapor deposition sputtering technique. The obtained films were characterized in their piezoelectric performance, including the construction of surface acoustic wave devices and bulk acoustic wave devices. Adequate piezoelectric response and acoustic velocities were obtained for 0001 oriented films, while 1010 oriented films did not show piezoelectric response under the configurations essayed. An extensive analysis was done in order to explain these behaviors.

Abstract: Dengue disease epidemics have increased in time and space due to climatic and non-climatic factors such as urbanization. In the absence of an effective vaccine, preventing dengue outbreak relies on vector control activities. Employing computerized tools to predict outbreaks and respond in advance has great potential for improving dengue disease control. Evidence of integrating or implementing such applications into control programs and their impact are scarce, and endemic countries demand for experience sharing and know-how transfer. Mexico has extensive experience of pre-validated EWARS (Early Warning And Response System), a tool that was developed in 2012 as part of a collaboration with the Special Program for Research and Training in Tropical Diseases Unit (TDR) at the World Health Organization and used at national level. The advancement of EWARS since 2014 and its stepwise integration into the national surveillance system has increased the appreciation of the need for integrated surveillance (including disease, vector and climate surveillance), and for linking inter-institutional and trans-sectoral information for holistic epidemiological intelligence. The integration of the EWARS software into the national surveillance platform in Mexico was a remarkable milestone and a successful experience. This manuscript describes the implementation process of EWARS in Mexico, which started in 2012 and further demonstrates benefits, threats, and opportunities of integrating EWARS into existing national surveillance programs