This paper uses machine learning approaches to predict the association between traffic volume, air pollution, and meteorological conditions. A key focus is on the interaction between these factors. The paper does this using hourly traffic volume, [[EQUATION]], and weather data for Oslo, Norway....

This paper uses machine learning approaches to explore the association between traffic volume, air pollution, and meteorological conditions. A focus is the interaction between these factors. The paper does this using hourly data for Oslo, Norway. I considered a total of ten datasets to verify...

There are a variety of reasons underlying the remarkable development of science and technology (S&T), and innovation in post-1978 China. This book seeks to achieve an understanding of such development from an institutional or a political economy perspective. Departing from the literature of S&T...

Since the mid-twentieth century, big-science research infrastructure (RI) has become an indispensable component in modern scientific research. Yet little is known about how emerging countries can use these expensive infrastructures to improve their indigenous innovation and catch up with...

Purpose Based on cognitive evaluation theory and gamification affordances, this study aims to understand how gamification affordances influence users’ intention to engage in sustainable behaviour and how new trends in Ant Forest influence its impact on green intrinsic motivation to support...

We provide a quantification of the impact of the recent US-China political tensions on talent flows from China to the US through the lens of monthly air passenger traffic data. By exploring variations across origin countries and geographical locations of US airports as well as differences over...