Abstract
Under the premise of rationality, politicians behave to maximize re-election probability. Favorable macroeconomic contexts, alignment with central governance, and balanced public finance will be rewarded leading to re-election. Logit estimations applied to Portuguese municipalities in the period 2002-2017 fail to empirically support these theoretical effects, providing no incentive-controlled policy actions. Local voters do not punish mayors for the adverse economic performance, staying loyal to ideological voting geographically and over time. Only turnout punishes incumbents over the entire period. The introduction of the law of limitation of terms did not change the incentives towards wise governance; therefore, lack of electoral punishments to undesirable policy actions withstands the potential misconduct of incumbents. Existing evidence points to the need of reforms in what concerns electoral participation as when we compel voters to express their democratic rights, they become more critical to undesirable achievements.

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Abstract

Abstract
Complex data management on healthcare institutions makes very hard to identify illegitimate accesses which is a serious issue. We propose to develop a system to detect accesses with suspicious behavior for further investigation. We modeled use cases (UC) and sequence diagrams (SD) showing the data flow between users and systems. The algorithms represented by activity diagrams apply rules based on professionals' routines, use data from an audit trail (AT) and classify accesses as suspicious or normal. The algorithms were evaluated between 23rd and 31st July 2019. The results were analyzed using absolute and relative frequencies and dispersion measures. Access classification was in accordance to rules applied. "Check time of activity" UC had 64,78% of suspicious classifications, being 55% of activity period shorter and 9,78% longer than expected, "Check days of activity" presented 2,27% of suspicious access and "EHR read access" 79%, the highest percentage of suspicious accesses. The results show the first picture of HIS accesses. Deeper analysis to evaluate algorithms sensibility and specificity should be done. Lack of more detailed information about professionals' routines and systems. and low quality of systems logs are some limitations. Although we believe this is an important step in this field.

Abstract
This paper develops a novel approach to track power system state evolution based on the maximum correntropy criterion, due to its robustness against non-Gaussian errors. It includes the temporal aspects on the estimation process within a maximum-correntropy-based extended Kalman filter (MCEKF), which is able to deal with both nonlinear supervisory control and data acquisition (SCADA) and phasor measurement unit (PMU) measurement models. By representing the behavior of the state variables with a nonparametric model within the kernel density estimation, it is possible to include abrupt state transitions as part of the process noise with non-Gaussian characteristics. Also, a novel strategy to update the size of Parzen windows in the kernel estimation is proposed to suppress the effects of suspect samples. By properly adjusting the kernel bandwidth, the proposed MCEKF keeps its accuracy during sudden load changes and contingencies, or in the presence of bad data. Simulations with IEEE test systems and the Brazilian interconnected system are carried out. The results show that the method deals with non-Gaussian noises in both the process and measurement, and provides accurate estimates of the system state under normal and abnormal conditions.

Abstract
The Kyrgyz Republic, as well as other countries of Central Asia, is highly exposed to natural-environmental hazards, which continues undermining efforts to achieve sustainable development. National disaster risk assessment procedures in Central Asian countries are mainly based on the evaluation of hazards without a detailed analysis of vulnerability and resilience. Additionally, the available practices of hazard assessments are mostly based on a zone-by-zone approach, which would make it difficult to develop a comparative assessment of facilities located in the same hazard zone. This situation hampers the efforts of the local governments to effectively plan and implement disaster risk reduction (DRR) actions when they cannot differentiate the individual facilities according to the risk level in order to focus the existing capacity (which is usually very limited) on increasing the resilience and reducing the vulnerability of the facilities with the highest risk. For improvement of DRR practices, the quantitative comprehensive approach of risk analysis applied in this study is used for risk assessment of educational institutions in one of the most seismically active and most disaster-prone mountain regions of Central Asia - the Alay valley, a wide intermontane valley situated in between the two biggest mountain systems in Asia: Tian Shan and Pamir. The developed multidisciplinary study suggests that the quantitative multi-risk assessment approach - can play a crucial role in understanding risks and can significantly improve the quality of disaster risk reduction planning.