Urban green space is thought to contribute to citizen happiness by promoting physical and mental health. Nevertheless, how urban green space and happiness are related across many countries with different socioeconomic conditions has not been explored. By measuring the urban green space score (UGS) from high-resolution satellite imagery of 90 global cities covering 179,168 km2 and 230 million people in 60 developed countries, we find that the amount of urban green space and GDP are correlated with a nation’s happiness level. More specifically, urban green space and GDP are each individually associated with happiness. Yet, only urban green space is related to happiness in the 30 wealthiest countries, whereas GDP alone can explain happiness in the subsequent 30 countries in terms of wealth. We further show that the relationship between urban green space and happiness is mediated by social support and that GDP moderates this relationship. These findings corroborate the importance of maintaining urban green space as a place for social cohesion to support people’s happiness.

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Is there a universal economic pathway individual cities recapitulate over and over? This evolutionary structure—if any—would inform a reference model for fairer assessment, better maintenance, and improved forecasting of urban development. Using employment data including more than 100 million U.S. workers in all industries between 1998 and 2013, we empirically show that individual cities indeed recapitulate a common pathway where a transition to innovative economies is observed at the population of 1.2 million. This critical population is analytically derived by expressing the urban industrial structure as a function of scaling relations such that cities are divided into two economic categories: small city economies with sublinear industries and large city economies with superlinear industries. Last, we define a recapitulation score as an agreement between the longitudinal and the cross-sectional scaling exponents and find that nontradeable industries tend to adhere to the universal pathway more than the tradeable.

Understanding the mechanisms behind human mobility patterns is crucial to improve our ability to optimize and predict traffic flows. Two representative mobility models, i.e., radiation and gravity models, have been extensively compared to each other against various empirical data sets, while their fundamental relation is far from being fully understood. In order to study such a relation, we first model the heterogeneous population landscape by generating a fractal geometry of sites and then by assigning to each site a population independently drawn from a power-law distribution. Then the radiation model on this population landscape, which we call the radiation-on-landscape (RoL) model, is compared to the gravity model to derive the distance exponent in the gravity model in terms of the properties of the population landscape, which is confirmed by the numerical simulations. Consequently, we provide a possible explanation for the origin of the distance exponent in terms of the properties of the heterogeneous population landscape, enabling us to better understand mobility patterns constrained by the travel distance.

The first prototype microwave imaging reflectometry (MIR) system [H. Park et al., Rev. Sci. Instrum. 74, 4239 (2004)] clearly demonstrated the shortcomings of conventional reflectometry when the probe beam encountered a large amplitude and/or high fluctuation wavenumber at the reflection layer in laboratory tests, the distinctive advantages shown in these tests were not fully realized in the plasma operation. To understand the discrepancies, the MIR system performance has been thoroughly investigated at POSTECH. In this paper, a possible cause of the MIR performance degradation on TEXTOR will be presented together with a concept of multifrequency MIR system design that will be developed for KSTAR.

Recently, two-dimensional microwave imaging diagnostics such as the electron cyclotron emission imaging (ECEI) system and microwave imaging reflectometry (MIR) have been developed to study magnetohydrodynamics instabilities and turbulence in magnetically confined plasmas. These imaging systems utilize large optics to collect passive emission or reflected radiation. The design of this optics can be classified into two different types: reflective or refractive optical systems. For instance, an ECEI/MIR system on the TEXTOR tokamak [Park et al., Rev. Sci. Instrum. 75, 3787 (2004)] employed the reflective optics which consisted of two large mirrors, while the TEXTOR ECEI upgrade [B. Tobias et al., Rev. Sci. Instrum. 80, 093502 (2009)] and systems on DIII-D, ASDEX-U, and KSTAR adopted refractive systems. Each system has advantages and disadvantages in the standing wave problem and optical aberrations. In this paper, a comparative study between the two optical systems has been performed in order to design a MIR system for KSTAR.

A new microwave imaging reflectometry (MIR) system for KSTAR is being developed based on the experience gained via the TEXTOR proof-of-principle system [H. Park et al., Rev. Sci. Instrum. 74, 4239 (2003)] which aimed to measure the poloidal image of the electron density fluctuations essential for transport studies. The KSTAR system will adopt a multi-frequency probe beam source in the range of 90 ∼ 100 GHz (X-mode case), which will enable the measurement of 2-D (radial and poloidal) fluctuations of the multiple cutoff layers, simultaneously. The optical system of the MIR system will be combined with the 2nd ECEI system (identical to the first ECEI system [G.S. Yun et al., Rev. Sci. Instrum. 81, 10D930 (2010)]) on KSTAR. The design of the launching and receiving optics of the MIR system will be constrained in order to maintain the performance of the ECEI system and thus it is necessary to consider sharing the zoom lens of the ECEI system. This stringent constraint is a challenge considering the tight wavefront matching requirement to obtain proper images for a wide range of cutoff layers within the focal depth. This paper discusses the details of the MIR system design that is compatible with the 2nd ECEI system on KSTAR.

Protest diffusion is a cascade process that can spread over different regions of the planet. The way and the extension that this phenomenon can occur is still not properly understood. Here, we empirically investigate this question using protest data from GDELT and ICEWS, two of the most extensive and longest-running data sets freely available. We divide the globe into grid cells and construct a temporal network for each data set where nodes represent cells and links are established between nodes if their protest events co-occur. We show that the temporal networks are small-world, indicating that the cells are directly linked or separated by a few steps on average. Furthermore, the average path lengths are decreasing through the years, which suggests that the world is becoming “smaller”. The persistent temporal hubs present in both data sets indicate that protests can spread faster through the hubs. This topological feature is consistent with the hypothesis that protests can quickly diffuse from one region to any other part of the globe.