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Output stability or drift overtime has long been a major performance deficiency for gas sensors irrespective of what technology or methodology is used for their conception. Software correction may alleviate the problem somewhat but it is not always applicable. It has long been the objective of many researchers in this field to overcome this problem fundamentally and for good. The purpose of this paper is to show that this objective has now finally been achieved.

Conventional non‐dispersive infrared (NDIR) dual beam methodology utilizes the ratio of signal channel output over reference channel output for signal processing. The signal filter overlaps the absorption band of the gas of interest while the reference filter does not. However, this ratio changes as the source ages. The current methodology uses an absorption bias between signal and reference channel outputs. This absorption bias is created by using a path length for the signal channel greater than that for the reference channel. Both the signal and reference detectors carry an identical spectral filter overlapping the absorption band of the gas to be measured.

Implementation of the currently patented NDIR gas‐sensing methodology has been carried out in different gas sensor configurations for over a year in the laboratory. Performance results for these sensors showing insignificant output drifts overtime have been repeatedly demonstrated via simulated aging for the source.

The paper puts forward the view that the recent breakthrough of the Near Zero Drift methodology for NDIR gas sensors will very quickly change the hierarchy of technology dominance and utility for gas sensors at large.

Massively parallel desktop computing capabilities now well within the reach of individual academics modify the environment for posterior simulation in fundamental and potentially quite advantageous ways. But to fully exploit these benefits algorithms that conform to parallel computing environments are needed. This paper presents a sequential posterior simulator designed to operate efficiently in this context. The simulator makes fewer analytical and programming demands on investigators, and is faster, more reliable, and more complete than conventional posterior simulators. The paper extends existing sequential Monte Carlo methods and theory to provide a thorough and practical foundation for sequential posterior simulation that is well suited to massively parallel computing environments. It provides detailed recommendations on implementation, yielding an algorithm that requires only code for simulation from the prior and evaluation of prior and data densities and works well in a variety of applications representative of serious empirical work in economics and finance. The algorithm facilitates Bayesian model comparison by producing marginal likelihood approximations of unprecedented accuracy as an incidental by-product, is robust to pathological posterior distributions, and provides estimates of numerical standard error and relative numerical efficiency intrinsically. The paper concludes with an application that illustrates the potential of these simulators for applied Bayesian inference.

There has been a resurgence of interest in comparative and international research on teacher education that has been driven, in large part, by the emergence over the past two decades of comprehensive international studies of student achievement supported by (1) the Organisation for Economic Co-operation and Development (OECD), Programme for International Student Assessment (PISA) and (2) the International Association for the Evaluation of Educational Achievement (IEA), Trends in International Mathematics and Science Study (TIMSS), and Progress in International Reading Literacy Study (PIRLS). Widely published country rankings that set benchmarks for student achievement suggest the importance of understanding more fully what specific characteristics set highly ranked countries apart, especially quality of teaching and teacher education.

Recent literature on comparative and international teacher education is reviewed, focusing on special issues of Prospects (Vol. 42, March 2012, “Internationalization of Teacher Education”), sponsored by the UNESCO International Bureau of Education (IBE) in Geneva, Switzerland, and the International Journal of Science and Mathematics Education (Vol. 11, August 2013, “International Perspectives on Mathematics and Science Teacher Education for the Future”), sponsored by the National Science Council of Taiwan.

A conceptual framework for describing the complexity of teacher education in comparative and international context is presented, adapting an approach used for understanding educational change and reform in emerging democracies. The chapter concludes with a discussion of theoretical perspectives that have been applied to teacher education in comparative and international education with recommendations for new directions that might inform scholarly understanding as well as practice.

Concepts equip the mind with thought, provide our theories with ideas, and assign variables for testing our hypotheses. Much of contemporary research deals with narrowly circumscribed concepts, termed simple concepts herein, which are the grist for much empirical inquiry in the field. In contrast to simple concepts, which exhibit a kind of unity, complex concepts are structures of simple concepts, and in certain instances unveil meaning going beyond simple concepts or their aggregation. When expressed in hylomorphic structures, complex concepts achieve unique ontological status and serve particular explanatory capabilities. We develop the philosophical foundation for hylomorphic structures and show how they are rooted in dispositions, dispositional causality, and various mind–body trade-offs. Examples are provided for this emerging perspective on “Big concepts” or “Big Ideas.”

The deployment of artificial intelligence (AI) technologies in travel and tourism has received much attention in the wake of the pandemic. While societal adoption of AI has accelerated, it also raises some trust challenges. Literature on trust in AI is scant, especially regarding the vulnerabilities faced by different stakeholders to inform policy and practice. This work proposes a framework to understand the use of AI technologies from the perspectives of institutional and the self to understand the formation of trust in the mandated use of AI-based technologies in travelers.

An empirical investigation using partial least squares-structural equation modeling was employed on responses from 209 users. This paper considered factors related to the self (perceptions of self-threat, privacy empowerment, trust propensity) and institution (regulatory protection, corporate privacy responsibility) to understand the formation of trust in AI use for travelers.

Results showed that self-threat, trust propensity and regulatory protection influence trust in users on AI use. Privacy empowerment and corporate responsibility do not.

Insights from the past studies on AI in travel and tourism are limited. This study advances current literature on affordance and reactance theories to provide a better understanding of what makes travelers trust the mandated use of AI technologies. This work also demonstrates the paradoxical effects of self and institution on technologies and their relationship to trust. For practice, this study offers insights for enhancing adoption via developing trust.

This bibliography is offered as a practical guide to published papers, conference proceedings papers and theses/dissertations on the finite element (FE) and boundary element (BE) applications in different fields of biomechanics between 1976 and 1991. The aim of this paper is to help the users of FE and BE techniques to get better value from a large collection of papers on the subjects. Categories in biomechanics included in this survey are: orthopaedic mechanics, dental mechanics, cardiovascular mechanics, soft tissue mechanics, biological flow, impact injury, and other fields of applications. More than 900 references are listed.