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This article is motivated by the lack of flexibility in Bayesian quantile regression for ordinal models where the error follows an asymmetric Laplace (AL) distribution. The inflexibility arises because the skewness of the distribution is completely specified when a quantile is chosen. To overcome this shortcoming, we derive the cumulative distribution function (and the moment-generating function) of the generalized asymmetric Laplace (GAL) distribution – a generalization of AL distribution that separates the skewness from the quantile parameter – and construct a working likelihood for the ordinal quantile model. The resulting framework is termed flexible Bayesian quantile regression for ordinal (FBQROR) models. However, its estimation is not straightforward. We address estimation issues and propose an efficient Markov chain Monte Carlo (MCMC) procedure based on Gibbs sampling and joint Metropolis–Hastings algorithm. The advantages of the proposed model are demonstrated in multiple simulation studies and implemented to analyze public opinion on homeownership as the best long-term investment in the United States following the Great Recession.

The high density of defects mainly attributed to the presence of silicon oxycarbides, residual C clusters, Si- and C-dangling bonds at or near the SiO₂/SiC interface degrades the performance of metal-oxide-semiconductor (MOS) devices. In the effort of further improving the quality and enhancement of the SiC oxides thickness, post-oxidation annealed by a combination of nitric acid (HNO₃) and water (H₂O) vapor technique on thermally grown wet-oxides is introduced in this work. The paper aims to discuss these issues.

A new technique of post-oxidation annealing (POA) on wet-oxidized n-type 4H-SiC in a combination of HNO₃ and H₂O vapor at various heating temperatures (70°C, 90°C and 110°C) of HNO₃ solution has been introduced in this work.

It has been revealed that the samples annealed in HNO₃ + H₂O vapour ambient by various heating temperatures of HNO₃ solution; particularly at 110°C is able to produce oxide with lower interface-state density and higher breakdown voltage as compared to wet-oxidized sample annealed in N2 ambient. The substrate properties upon oxide removal show surface roughness reduces as the heating temperature of HNO₃ solution increases, which is mainly attributed due to the significant reduction of carbon content at the SiC/SiO₂ interface by C=N passivation and CO or CO₂ out-diffusion.

Despite being as a strong oxidizing agent, vaporized HNO₃ can also be utilized as nitridation and hydrogen passivation agent in high temperature thermal oxidation ambient and these advantages were demonstrated in 4H-SiC.

This chapter will situate the global paradigm shift toward Post-Education-For-All (Post-EFA) not only in the policy trends in the field of international education development, but also in the academic context of international relations and comparative education.

The chapter highlights three dimensions which characterize the paradigm shift; namely, discourse on norms, diversifying actors, and the changed mode of communication and participation in the global consultation processes. The existing formal structure of the EFA global governance is based on multilateralism which recognizes sovereign nation-states, representing national interests, as the participants. However, such an assumption is eroding, given that there is a growing number of state and nonstate actors who influence decision-making not only through conventional formal channels, but also informally. Urging the revision of theories of multilateralism, the chapter introduces the attention given to nontraditional donors and horizontal networks of civil society actors in this volume.

The introduction also shows that that the widening basis of participation in the global consultation processes on post-EFA and advanced communication technology have changed the ways in which discourse is formulated. While the amount and the speed of exchanging information have been enhanced and different types of actors have been encouraged to take part, it also obliges scholars to adopt innovative methods of analyzing discourse formation.

The chapter also demonstrates the importance of the focus on the Asia-Pacific region, which is composed of diverse actors who often underscore Asian cultural roots in contrast to Western hegemony. By focusing on the discourse, actors, and the structure through which the consensus views on the post-EFA agenda were built, the volume attempts to untangle the nature of the post-EFA paradigm shift, at the global, Asia-Pacific regional, and national levels.

This chapter uses an application to explore the utility of Bayesian quantile regression (BQR) methods in producing density nowcasts. Our quantile regression modeling strategy is designed to reflect important nowcasting features, namely the use of mixed-frequency data, the ragged-edge, and large numbers of indicators (big data). An unrestricted mixed data sampling strategy within a BQR is used to accommodate a large mixed-frequency data set when nowcasting; the authors consider various shrinkage priors to avoid parameter proliferation. In an application to euro area GDP growth, using over 100 mixed-frequency indicators, the authors find that the quantile regression approach produces accurate density nowcasts including over recessionary periods when global-local shrinkage priors are used.

Schools play an important role in Japan by becoming evacuation centers after disasters. Depending on the nature of disaster, the school can be occupied for several days to several months. Therefore, schools play a crucial role in disaster risk reduction and can contribute to very strong bonding with the local communities. This chapter describes the experiences of six cities with the roles of schools during disasters. Kamaishi, Kesennuma, and Natori, three cities affected by the tsunami, have shown the important role that schools played in the time of disaster. Although some schools were destroyed in these three cities, people spent significant time in other schools as evacuees. Pre-disaster preparedness of schools and communities helped a lot in this regard. Taking the experiences from the East Japan disaster, Saijo, Owase, and Oobu cities in West Japan demonstrated their preparedness for future disaster. The chapter also shows that school-centered disaster preparedness before the disaster leads to an effective role during the disaster and also facilitates post-disaster recovery with schools as the center.

This chapter develops a framework for quantile regression in binary longitudinal data settings. A novel Markov chain Monte Carlo (MCMC) method is designed to fit the model and its computational efficiency is demonstrated in a simulation study. The proposed approach is flexible in that it can account for common and individual-specific parameters, as well as multivariate heterogeneity associated with several covariates. The methodology is applied to study female labor force participation and home ownership in the United States. The results offer new insights at the various quantiles, which are of interest to policymakers and researchers alike.

The 60 GHz unlicensed band is being utilized for high-speed wireless networks with data rates in the gigabit range. To successfully make use of these high-speed signals in a digital system, a high-speed analog-to-digital converter (ADC) is necessary. This paper aims to present the use of a common collector (CC) input tree and Cherry Hooper (C-H) differential amplifier to enable analog-to-digital conversion at high frequencies.

The CC input tree is designed to separate the input Miller capacitance of each comparator stage. The CC stages are biased to obtain bandwidth speeds higher than the comparator stages while using less current than the comparator stages. The C-H differential amplifier is modified to accommodate the low breakdown voltages of the technology node and implemented as a comparator. The comparator stages are biased to obtain a high output voltage swing and have a small signal bandwidth up to 29 GHz. Simulations were performed using foundry development kits to verify circuit operation. A two-bit ADC was prototyped in IBM’s 130 nm SiGe BiCMOS 8HP technology node. Measurements were carried out on test printed circuit boards and compared with simulation results.

The use of the added CC input tree showed a simulated bandwidth improvement of approximately 3.23 times when compared to a basic flash architecture, for a two-bit ADC. Measured results showed an effective number of bits (ENOB) of 1.18, from DC up to 2 GHz, whereas the simulated result was 1.5. The maximum measured integral non-linearity and differential non-linearity was 0.33 LSB. The prototype ADC had a figure of merit of 42 pJ/sample.

The prototype ADC results showed that the group delay for the C-H comparator plays a critical role in ADC performance for high frequency input signals. For minimal component variation, the group delay between channels deviate from each other, causing incorrect output codes. The prototype ADC had a low gain which reduced the comparator performance. The two-bit CC C-H ADC is capable of achieving an ENOB close to 1.18, for frequencies up to 2 GHz, with 180 mW total power consumption.

Stochastic volatility models are of great importance in the field of mathematical finance, especially for accurately explaining the dynamics of financial derivatives. A quantile-based estimator for the location parameter of a stochastic volatility model is proposed by solving an optimization problem. In this chapter, the asymptotic distribution of the estimator is derived without assuming that the density function of the noise is positive around the corresponding population quantile. We also discuss a Bayesian approach to the quantile estimation problem and establish a result regarding the nature of the posterior distribution.