How do urban mobility (geo)graph’s topological properties fill a map?

Urban mobility data are important to areas ranging from traffic engineering to the analysis of outbreaks and disasters. In this paper, we study mobility data from a major Brazilian city from a geographical viewpoint using a Complex Network approach. The case study is based on intra-urban mobility data from the Metropolitan area of Rio de Janeiro (Brazil), presenting more than 480 spatial network nodes. While for the mobility flow data a log-normal distribution outperformed the power law, we also found moderate evidence for scale-free and small word effects in the flow network’s degree distribution. We employ a novel open-source GIS tool to display (geo)graph’s topological properties in maps and observe a strong traffic-topology association and also a fine adjustment for hubs location for different flow threshold networks. In the central commercial area for lower thresholds and in high population residential areas for higher thresholds. This set of results, including statistical, topological and geographical analysis may represent an important tool for policymakers and stakeholders in the urban planning area, especially by the identification of zones with few but strong links in a real data-driven mobility network.

Gravisensors in plant cells behave like an active granular liquid

Plants are able to sense and respond to minute tilt from the vertical direction of the gravity, which is key to maintain their upright posture during development. However, gravisensing in plants relies on a peculiar sensor made of microsize starch-filled grains (statoliths) that sediment and form tiny granular piles at the bottom of the cell. How such a sensor can detect inclination is unclear, as granular materials like sand are known to display flow threshold and finite avalanche angle due to friction and interparticle jamming. Here, we address this issue by combining direct visualization of statolith avalanches in plant cells and experiments in biomimetic cells made of microfluidic cavities filled with a suspension of heavy Brownian particles. We show that, despite their granular nature, statoliths move and respond to the weakest angle, as a liquid clinometer would do. Comparison between the biological and biomimetic systems reveals that this liquid-like behavior comes from the cell activity, which agitates statoliths with an apparent temperature one order of magnitude larger than actual temperature. Our results shed light on the key role of active fluctuations of statoliths for explaining the remarkable sensitivity of plants to inclination. Our study also provides support to a recent scenario of gravity perception in plants, by bridging the active granular rheology of statoliths at the microscopic level to the macroscopic gravitropic response of the plant.

Size-dependence of the flow threshold in dense granular materials

A size-dependent flow threshold is measured in discrete-element method simulations of dense granular flow across several different flow configurations and may be quantitatively captured using a nonlocal continuum model for dense granular flow.

MRI-based mismatch detection in acute ischemic stroke: Optimal PWI maps and thresholds validated with PET

Perfusion-weighted (PW) magnetic resonance imaging (MRI) is used to detect penumbral tissue in acute stroke, but the selection of optimal PW-maps and thresholds for tissue at risk detection remains a matter of debate. We validated the performance of PW-maps with 15O-water-positron emission tomography (PET) in a large comparative PET-MR cohort of acute stroke patients. In acute and subacute stroke patients with back-to-back MRI and PET imaging, PW-maps were validated with 15O-water-PET. We pooled two different cerebral blood flow (CBF) PET-maps to define the critical flow (CF) threshold, (i) quantitative (q)CBF-PET with the CF threshold <20 ml/100 g/min and (ii) normalized non-quantitative (nq)CBF-PET with a CF threshold of <70% (corresponding to <20 ml/100 g/min according to a previously published normogram). A receiver operating characteristic (ROC) curve analysis was performed to specify the accuracy and the optimal critical flow threshold of each PW-map as defined by PET. In 53 patients, (stroke to imaging: 9.8 h; PET to MRI: 52 min) PW-time-to-maximum (Tmax) with a threshold >6.1 s (AUC = 0.94) and non-deconvolved PW-time-to-peak (TTP) >4.8 s (AUC = 0.93) showed the best performance to detect the CF threshold as defined by PET. PW-Tmax with a threshold >6.1 s and TTP with a threshold >4.8 s are the most predictive in detecting the CF threshold for MR-based mismatch definition.