Quantification of Lifeline System Interdependencies after the 27 February 2010 Mw 8.8 Offshore Maule, Chile, Earthquake

Data on lifeline system service restoration is seldom exploited for the calibration of performance prediction models or for response comparisons across systems and events. This study explores utility restoration curves after the 2010 Chilean earthquake through a time series method to quantify coupling strengths across lifeline systems. When consistent with field information, cross-correlations from restoration curves without significant lag times quantify operational interdependence, whereas those with significant lags reveal logistical interdependence. Synthesized coupling strengths are also proposed to incorporate cross-correlations and lag times at once. In the Chilean earthquake, coupling across fixed and mobile phones was the strongest per region followed by coupling within and across telecommunication and power systems in adjacent regions. Unapparent couplings were also revealed among telecommunication and power systems with water networks. The proposed methodology can steer new protocols for post-disaster data collection, including anecdotal information to evaluate causality, and inform infrastructure interdependence effect prediction models

Evaluación y talleres de prevención de abuso sexual para padres e hijos del 5to año de la Escuela Fiscal Mixta "Carlos Aguilar"

Currently, sexual abuse is a problem that ails and affects society around the world and that provokes a series of several negative consequences in those that have suffered it. Without a doubt, minors and specially children are potential victims of sexual abuse due to their high vulnerability. For these reasons, it is important to provide and implement tools that would contribute to prevent it. One of these tools without a doubt is education. For this investigation the researchers used a sample 35 children and twenty 26 parents. Over this sample, which was extracted from the population of students of the Public Primary School “Carlos Aguilar”, lectures and workshops were implemented based on standardized manuals about sexual abuse prevention. This was made with the purpose of increasing their knowledge on this subject. The statistical analysis made, showed and demonstrated that the results obtained from the intervention were statistically significant in the case of children; however it was not significant in the case of the parents. The knowledge on sexual abuse can give solid and strong tools to the children and their parents in order to prevent it.Actualmente, el abuso sexual es un problema que afecta a todas las sociedades alrededor del mundo. Sin duda alguna, los niños son potenciales víctimas por su alta vulnerabilidad. Así mismo, el abuso sexual provoca una serie de consecuencias negativas en quienes lo han sufrido. Por estas razones, es importante proporcionar e implementar herramientas que contribuyan con su prevención, una de ella sin duda alguna es la educación. Para el presente trabajo, los investigadores utilizaron una muestra de 35 niños y 26 padres de familia extraída de la población de estudiantes de la Escuela Fiscal Mixta “Carlos Aguilar” a quienes se implementaron charlas y talleres basados en manuales estandarizados sobre prevención de abuso sexual, con el fin de incrementar sus conocimientos sobre el tema. El análisis estadístico demostró que los resultados obtenidos a partir de la intervención fueron estadísticamente significativos en el caso de los niños pero no en el caso de los padres. El conocimiento de abuso sexual puede brindar a los niños y sus padres herramientas sólidas para prevenirlo

A Closed-Form Technique for the Reliability and Risk Assessment of Wind Turbine Systems

This paper proposes a closed-form method to evaluate wind turbine system reliability and associated failure consequences. Monte Carlo simulation, a widely used approach for system reliability assessment, usually requires large numbers of computational experiments, while existing analytical methods are limited to simple system event configurations with a focus on average values of reliability metrics. By analyzing a wind turbine system and its components in a combinatorial yet computationally efficient form, the proposed approach provides an entire probability distribution of system failure that contains all possible configurations of component failure and survival events. The approach is also capable of handling unique component attributes such as downtime and repair cost needed for risk estimations, and enables sensitivity analysis for quantifying the criticality of individual components to wind turbine system reliability. Applications of the technique are illustrated by assessing the reliability of a 12-subassembly turbine system. In addition, component downtimes and repair costs of components are embedded in the formulation to compute expected annual wind turbine unavailability and repair cost probabilities, and component importance metrics useful for maintenance planning and research prioritization. Furthermore, this paper introduces a recursive solution to closed-form method and applies this to a 45-component turbine system. The proposed approach proves to be computationally efficient and yields vital reliability information that could be readily used by wind farm stakeholders for decision making and risk management

The influencer-politician narrative and his/her fandom. The case of Isabel Díaz Ayuso and the ayusers on Instagram

La influencia de la cultura de los medios sociales en la comunicación política ha propiciado la aparición de la narrativa del político-influencer como la adaptación del político-estrella al medio. El trabajo analiza la comunicación de la política Isabel Díaz Ayuso y la de su fandom (ayusers) en Instagram durante un periodo no electoral (junio 2021-junio 2022). Para ello, se realizó un análisis de contenido cuantitativo y cualitativo sobre el perfil oficial de la política y las cinco cuentas ayusers con más seguidores. Los resultados muestran que Díaz Ayuso utiliza estrategias características del discurso publicitario y comercial de los influencers, encontrándose una mayor presencia de marcas y celebridades que de representantes políticos o información sobre sus iniciativas de gobierno. La decisión de mostrar contenidos personales y comerciales, siguiendo la lógica de la humanización del político, es además premiada por sus seguidores, que manifiestan más engagement hacia estas publicaciones. En paralelo, su fandom se centra en ensalzar el atractivo físico de Díaz ayuso y el ataque político a la izquierda (regional y nacional). Así, su comunicación y la de los ayusers funciona de modo complementario en Instagram: la política se muestra siempre activa y positiva, de acuerdo con la lógica del medio y los mandatos culturalmente asociados al género femenino, mientras que su fandom incorpora los contenidos políticos y de ataque. El trabajo avanza en el conocimiento sobre las narrativas de humanización del político en los medios sociales, así como en la creciente importancia del fandom en un contexto de campaña permanente.The influence of social media culture on political communication has led to the emergence of the influencer-politician narrative as the adaptation of the celebrity-politician to the medium. This paper analyses the communication of the politician Isabel Díaz Ayuso and her fandom (ayusers) on Instagram during a non-electoral period (June 2021-June 2022). To this end, a quantitative and qualitative content analysis was carried out on Díaz Ayuso’s official profile and the five most followed fandom accounts. The results show that Díaz Ayuso uses the same advertising and commercial strategies as influencers. Also, the presence of brands and celebrities was greater than that of political representatives or information about their own government initiatives in her posts. The decision to show personal and commercial content, following the logic of the politician’s humanisation, is rewarded by her followers showing more engagement towards these themes. At the same time, her fandom focuses its publications on praising Díaz Ayuso’s physical attractiveness and the political attack on the left (regional and national). Thus, Díaz Ayuso and the ayusers’ communication work in a complementary way on Instagram: the politician is always active and positive, in accordance with the logic of the medium and the cultural ideas associated with the female gender, while her fandom incorporates political and attacking content. This research advances knowledge about the narratives of humanisation of the politician in social media, as well as the growing importance of fandom within a context of digital permanent campaigning

Probabilistic Assessment of Decentralized Decision-making for Interdependent Network Restoration

This study introduces a statistical model that guides decentralized infrastructure restoration processes aligned with field practices. In particular, we make more analytically tractable the previously proposed Judgment Call method to simulate real-world decisions under time and resource constraints. The Judgment Call method explicitly models the largely ignored feature of decentralization in the restoration planning across interdependent networks. The method solves the Decentralized Interdependent Network Design Problem (D-INDP) while acknowledging the lack of proper communication among decision making agents, and hence, the lack of essential information. Here, we use a Bayesian Hierarchical Model (BHM) to simulate the agents practical use of their field expertise and judgments to compensate for essential information shortage. We train the model using synthetic restoration plans that emphasize the local preferences of the agents. The method is applied to the interdependent infrastructure network of Shelby County, TN, and the results show that the performance of BHM-aided restoration plans is close to the conceptual upper bound.The authors gratefully acknowledge the support by the U.S. Department of Defense (Grant W911NF-13-1-0340) and the U.S. National Science Foundation (Grant CMMI-1541033)

Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures. I: Methodology

The state-of-the-practice in seismic network reliability assessment of highway bridges often ignores bridge failure correlations imposed by factors such as the network topology, construction methods, and present-day condition of bridges, amongst others. Additionally, aging bridge seismic fragilities are typically determined using historical estimates of deterioration parameters. This research presents a methodology to estimate bridge fragilities using spatially interpolated and updated deterioration parameters from limited instrumented bridges in the network, while incorporating the impacts of overlooked correlation factors in bridge fragility estimates. Simulated samples of correlated bridge failures are used in an enhanced Monte Carlo method to assess bridge network reliability, and the impact of different correlation structures on the network reliability is discussed. The presented methodology aims to provide more realistic estimates of seismic reliability of aging transportation networks and potentially helps network stakeholders to more accurately identify critical bridges for maintenance and retrofit prioritization

Recovery of Infrastructure Networks via Importance-based Multicentric Percolation Processes

Recovery processes across infrastructure systems after disasters are critical to improve their resilience, yet poorly understood. The common assumption of prioritizing the size of the reconnected network as the goal for recovery in many algorithms today is impractical, given that satisfaction of demands is more important for the functional recovery of infrastructure systems such as power grids. Mixed-integer programming formulations that guarantee optimality under practical resource and time constraints continue advancing, but become computationally intractable even for systems with only hundreds of elements. Algorithms approximating the optimal solution with lower computational cost are in need, including competitive percolation or surrogate models. We propose a method based on statistical mechanics that exhibits phase transitions, as when restoring networked systems. Our importance-based multicentric percolation recovery strategy for spatially distributed engineered networks, approximates optimal restoration solutions with a substantially lower computational cost. Small tree-like clusters form first in the network, which then interconnect into bigger components gradually mirroring optimal restoration and aligning with field practices. A key observation is that the formation of large connected components is suppressed during the recovery process, which enables balancing computational efficiency and accuracy. The proposed strategy is very close to optimization-based methods and methods based on competitive percolation, particularly when load is homogeneous and the fraction of generators is smallillustrative examples showcase the adequate trade-off between computation cost and accuracy relative to competing alternatives.The authors gratefully acknowledge the support by the U.S. Department of Defense (Grant W911NF-13-1-0340) and the U.S. National Science Foundation (Grants CMMI-1436845 and CMMI-1541033)

Optimization of base isolation systems using low-cost bearings and frictional devices

Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2001.Vita.Includes bibliographical references (leaves 52-53).by Leonardo Augusto Dueñas Osorio.M.Eng

Ising Model Partition Function Computation as a Weighted Counting Problem

While the Ising model remains essential to understand physical phenomena, its natural connection to combinatorial reasoning makes it also one of the best models to probe complex systems in science and engineering. We bring a computational lens to the study of Ising models, where our computer-science perspective is two-fold: On the one hand, we consider the computational complexity of the Ising partition-function problem, or #Ising, and relate it to the logic-based counting of constraint-satisfaction problems, or #CSP. We show that known dichotomy results for #CSP give an easy proof of the hardness of #Ising and provide new intuition on where the difficulty of #Ising comes from. On the other hand, we also show that #Ising can be reduced to Weighted Model Counting (WMC). This enables us to take off-the-shelf model counters and apply them to #Ising. We show that this WMC approach outperforms state-of-the-art specialized tools for #Ising, thereby expanding the range of solvable problems in computational physics.Comment: 16 pages, 2 figure