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With the widespread use of mobile computing devices in contemporary society, our trajectories in the physical space and virtual world are increasingly closely connected. Using the anonymous smartphone data of $1 \times 10^5$ users in 30 days, we constructed the mobility network and the attention network to study the correlations between online and offline human behaviours. In the mobility network, nodes are physical locations and edges represent the movements between locations, and in the attention network, nodes are websites and edges represent the switch of users between websites. We apply the box-covering method to renormalise the networks. The investigated network properties include the size of box $l_B$ and the number of boxes $N(l_B)$. We find two universal classes of behaviours: the mobility network is featured by a small-world property, $N(l_B) \simeq e^{-l_B}$, whereas the attention network is characterised by a self-similar property $N(l_B) \simeq l_B^{-\gamma}$. In particular, with the increasing of the length of box $l_B$, the degree correlation of the network changes from positive to negative which indicates that there are two layers of structure in the mobility network. We use the results of network renormalisation to detect the community and map the structure of the mobility network. Further, we located the most relevant websites visited in these communities, and identified three typical location-based behaviours, including the shopping, dating, and taxi-calling. Finally, we offered a revised geometric network model to explain our findings in the perspective of spatial-constrained attachment., Comment: 15 pages, 8 figures

The Mn K edge X-ray absorption near edge structure (XANES) of Pr0.67Sr0.33MnO3 films with different thicknesses on (001) LaAlO3 substrate was measured and the effects of strain relaxation on film properties were investigated. The films showed in-plane compressive and out-of-plane tensile strains. Strain relaxation occurred with increasing film thickness, affecting both lattice constant and MnO6 octahedral rotation. In polarization dependent XANES measurements using in-plane (parallel) and out-of-plane (perpendicular) geometries, the different values of absorption resonance energy Er confirmed the film anisotropy. The values of Er along these two directions shifted towards each other with increasing film thickness. Correlating with X-ray diffraction (XRD) results it is suggested that the strain relaxation decreased the local anisotropy and corresponding probability of electronic charge transfer between Mn 3d and O 2p orbitals along the in-plane and out-of-plane directions. The XANES results were used to explain the film-thickness dependent magnetic and transport properties.

Disorder among surface spins is a dominant factor in the magnetic response of magnetic nanoparticle systems. In this work, we examine time-dependent magnetization in high-quality, monodisperse hollow maghemite nanoparticles (NPs) with a 14.8 ± 0.5 nm outer diameter and enhanced surface-to-volume ratio. The nanoparticle ensemble exhibits spin-glass-like signatures in dc magnetic aging and memory protocols and ac magnetic susceptibility. The dynamics of the system slow near 50 K and become frozen on experimental time scales below 20 K. Remanence curves indicate the development of magnetic irreversibility concurrent with the freezing of the spin dynamics. A strong exchange-bias effect and its training behavior point to highly frustrated surface spins that rearrange much more slowly than interior spins. Monte Carlo simulations of a hollow particle corroborate strongly disordered surface layers with complex energy landscapes that underlie both glass-like dynamics and magnetic irreversibility. Calculated hysteresis loops reveal that magnetic behavior is not identical at the inner and outer surfaces, with spins at the outer surface layer of the 15 nm hollow particles exhibiting a higher degree of frustration. Our combined experimental and simulated results shed light on the origin of spin-glass-like phenomena and the important role played by the surface spins in magnetic hollow nanostructures.

We find that the flow of attention on the Web forms a directed, tree-like structure implying the time-sensitive browsing behavior of users. Using the data of a news sharing website, we construct clickstream networks in which nodes are news stories and edges represent the consecutive clicks between two stories. To identify the flow direction of clickstreams, we define the “flow distance” of nodes (Li), which measures the average number of steps a random walker takes to reach the ith node. It is observed that Li is related with the clicks (Ci) to news stories and the age (Ti) of stories. Putting these three variables together help us understand the rise and decay of news stories from a network perspective. We also find that the studied clickstream networks preserve a stable structure over time, leading to the scaling between users and clicks. The universal scaling behavior is confirmed by the 1,000 Web forums. We suggest that the tree-like, stable structure of clickstream networks reveals the time-sensitive preference of users in online browsing. To test our assumption, we discuss three models on individual browsing behavior, and compare the simulation results with empirical data.

Creating highly active and stable metal catalysts is a persistent goal in the field of heterogeneous catalysis. However, a real catalyst can rarely achieve both of these qualities simultaneously due to limitations in the design of the active site and support. One method to circumvent this problem is to fabricate firmly attached metal species onto the voids of a mesoporous support formed simultaneously. In this study, we developed a new type of ruthenium catalyst that was firmly confined by ordered mesoporous carbons through the fabrication of a cubic Ia3d chitosan-ruthenium-silica mesophase before pyrolysis and silica removal. This facile method generates fine ruthenium nanoparticles (ca. 1.7 nm) that are homogeneously dispersed on a mesoporous carbonaceous framework. This ruthenium catalyst can be recycled 22 times without any loss of reactivity, showing the highest stability of any metal catalysts; this catalyst displays a high activity (23.3 mol(LA)h(-1)g(metal)(-1)) during the catalytic hydrogenation of levulinic acid (LA) when the metal loading is 6.1 wt%. Even at an ultralow loading (0.3 wt%), this catalyst still outperforms the most active known Ru/C catalyst. This work reveals new possibilities for designing and fabricating highly stable and active metal catalysts by creating metal sites and mesoporous supports simultaneously.