A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation

This paper advances Kim, Taber, and Lodge's work (2010). Specifically, it is shown here that the psychological model of political judgment proposed by Kim et al (2010) is consistent with a set of well-known empirical regularities repeatedly found in electoral and psychological researches, that the model in general implies motivated reasoning - discounting contradictory information to the prior while accepting consistent information more or less at its face value - under general conditions, and that (prior) evaluative affect towards candidates plays a fundamental role in this process. It is also discussed the implication of motivated reasoning in accounting for the responsiveness, persistence, and polarization of candidate evaluation often observed in elections.Candidate Evaluation, Election, Cognition and Affect, Political Judgment, ACT-r

The quality management ecosystem for predictive maintenance in the Industry 4.0 era

The Industry 4.0 era requires new quality management systems due to the ever increasing complexity of the global business environment and the advent of advanced digital technologies. This study presents new ideas for predictive quality management based on an extensive review of the literature on quality management and five realworld cases of predictive quality management based on new technologies. The results of the study indicate that advanced technology enabled predictive maintenance can be applied in various industries by leveraging big data analytics, smart sensors, artificial intelligence (AI), and platform construction. Such predictive quality management systems can become living ecosystems that can perform cause-effect analysis, big data monitoring and analytics, and effective decision-making in real time. This study proposes several practical implications for actual design and implementation of effective predictive quality management systems in the Industry 4.0 era. However, the living predictive quality management ecosystem should be the product of the organizational culture that nurtures collaborative efforts of all stakeholders, sharing of information, and co-creation of shared goals

The quality management ecosystem for predictive maintenance in the Industry 4.0 era

The Industry 4.0 era requires new quality management systems due to the ever increasing complexity of the global business environment and the advent of advanced digital technologies. This study presents new ideas for predictive quality management based on an extensive review of the literature on quality management and five realworld cases of predictive quality management based on new technologies. The results of the study indicate that advanced technology enabled predictive maintenance can be applied in various industries by leveraging big data analytics, smart sensors, artificial intelligence (AI), and platform construction. Such predictive quality management systems can become living ecosystems that can perform cause-effect analysis, big data monitoring and analytics, and effective decision-making in real time. This study proposes several practical implications for actual design and implementation of effective predictive quality management systems in the Industry 4.0 era. However, the living predictive quality management ecosystem should be the product of the organizational culture that nurtures collaborative efforts of all stakeholders, sharing of information, and co-creation of shared goals

Formation characteristics and photoluminescence of Ge nanocrystals in HfO[sub 2]

Genanocrystals (NCs) are shown to form within HfO₂ at relatively low annealing temperatures (600–700 °C) and to exhibit characteristic photoluminescence(PL) emission consistent with quantum confinement effects. After annealing at 600 °C, sample implanted with 8.4×10¹⁵ Ge cm⁻² show two major PL peaks, at 0.94 and 0.88 eV, which are attributed to no-phonon and transverse-optical phonon replica of Ge NCs, respectively. The intensity reaches a maximum for annealing temperatures around 700 °C and decreases at higher temperatures as the NC size continues to increase. The no-phonon emission also undergoes a significant redshift for temperatures above 800 °C. For fluences in the range from 8.4×1015 to 2.5×10¹⁶ cm⁻², the average NC size increases from ∼13.5±2.6 to ∼20.0±3.7 nm. These NC sizes are much larger than within amorphous SiO₂. Implanted Ge is shown to form Ge NCs within the matrix of monoclinic (m)-HfO₂ during thermal annealing with the orientation relationship of [101]m-HfO₂//[110]Ge NC.S.H.C. and R.G.E. acknowledge supports from the Korea Research Foundation Grant Grant No. KRF-2007-521- C00094 and from the Australian Research Council Discovery Project, respectively

Massive transfusion protocol: the reason it is necessary

Objective. The purpose of this study is to identify problems of emergency transfusion at the bedside and to determine need for massive transfusion protocol. Methods. We included patients who met the criteria for “trauma team activation” and were admitted to division of trauma. The amount of blood product transfused in each unit was investigated for balanced transfusion. We also investigated the compliance with assessment of blood consumption score. The correlation between the time elapsed from patient visit to first transfusion order and time elapsed from first transfusion order to transfusion start was analyzed. Finally, we investigated various factors which serve to influence the decision-making process regarding early transfusion order. Results. Ratio of packed Red blood cells (pRBC): Fresh frozen plasma (FFP) was well-balanced, but platelet transfusion done was much lower than pRBC and FFP in emergency room. The application of emergency blood release did not match the criteria of assessment of blood consumption (ABC) score. The time from the first transfusion order to the transfusion start was found to be constant irrespective of time from patient visit to first transfusion order. And, the time from the first transfusion order to transfusion start did not differ significantly among patients with early transfusion order and delayed transfusion order. Only systolic blood pressure of < 90 mmHg was identified as a major predictor for early transfusion order. Conclusion. Balanced transfusion is not easy and emergency transfusion could be delayed at the bedside. Integrated and systematic structures for massive transfusion protocol would be invaluable and indispensable

An Improved Finite Difference Type Numerical Method for Structural Dynamic Analysis

An improved finite difference type numerical method to solve partial differential equations for one-dimensional (1-D) structure is proposed. This numerical scheme is a kind of a single-step, second-order accurate and implicit method. The stability, consistency, and convergence are examined analytically with a second-order hyperbolic partial differential equation. Since the proposed numerical scheme automatically satisfies the natural boundary conditions and at the same time, all the partial differential terms at boundary points are directly interpretable to their physical meanings, the proposed numerical scheme has merits in computing 1-D structural dynamic motion over the existing finite difference numeric methods. Using a numerical example, the suggested method was proven to be more accurate and effective than the well-known central difference method. The only limitation of this method is that it is applicable to only 1-D structure

Radar-based nowcasting by combining centroid tracking and motion vector of convective storm

Póster presentado en: 3rd European Nowcasting Conference, celebrada en la sede central de AEMET en Madrid del 24 al 26 de abril de 2019