An Alternative Approach to the Calculation and Analysis of Connectivity in the World City Network

Empirical research on world cities often draws on Taylor's (2001) notion of an 'interlocking network model', in which office networks of globalized service firms are assumed to shape the spatialities of urban networks. In spite of its many merits, this approach is limited because the resultant adjacency matrices are not really fit for network-analytic calculations. We therefore propose a fresh analytical approach using a primary linkage algorithm that produces a one-mode directed graph based on Taylor's two-mode city/firm network data. The procedure has the advantage of creating less dense networks when compared to the interlocking network model, while nonetheless retaining the network structure apparent in the initial dataset. We randomize the empirical network with a bootstrapping simulation approach, and compare the simulated parameters of this null-model with our empirical network parameter (i.e. betweenness centrality). We find that our approach produces results that are comparable to those of the standard interlocking network model. However, because our approach is based on an actual graph representation and network analysis, we are able to assess cities' position in the network at large. For instance, we find that cities such as Tokyo, Sydney, Melbourne, Almaty and Karachi hold more strategic and valuable positions than suggested in the interlocking networks as they play a bridging role in connecting cities across regions. In general, we argue that our graph representation allows for further and deeper analysis of the original data, further extending world city network research into a theory-based empirical research approach.Comment: 18 pages, 9 figures, 2 table

Artificial neural networks for 3D cell shape recognition from confocal images

We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.Comment: 17 pages, 8 figure

Evaluating 35 Methods to Generate Structural Connectomes Using Pairwise Classification

There is no consensus on how to construct structural brain networks from diffusion MRI. How variations in pre-processing steps affect network reliability and its ability to distinguish subjects remains opaque. In this work, we address this issue by comparing 35 structural connectome-building pipelines. We vary diffusion reconstruction models, tractography algorithms and parcellations. Next, we classify structural connectome pairs as either belonging to the same individual or not. Connectome weights and eight topological derivative measures form our feature set. For experiments, we use three test-retest datasets from the Consortium for Reliability and Reproducibility (CoRR) comprised of a total of 105 individuals. We also compare pairwise classification results to a commonly used parametric test-retest measure, Intraclass Correlation Coefficient (ICC).Comment: Accepted for MICCAI 2017, 8 pages, 3 figure

WLM-1: A Non-Rotating, Gravitationally Unperturbed, Highly Elliptical Extragalactic Globular Cluster

Globular clusters have long been known for presenting (at times) significant deviations from spherical symmetry. While rotation has been the main proposed explanation, other complicating factors such as their constant interaction with the strong gravitational potential of their host galaxy have made it difficult for a consensus to be reached. To address this question we have obtained high-resolution spectra of WLM-1, the lone globular cluster associated with the isolated, low-mass dwarf irregular galaxy WLM. Using archival HST WFPC2 data, we measure the radial ellipticity profile of WLM-1, finding it to be highly elliptical, with a mean value of 0.17 in the region 0.5-5" -- which is comparable to what is found in our Galaxy for the most elliptical globular clusters. There is no evidence of isophote twisting, except for the innermost regions of the cluster (r < 0.5"). To investigate whether the observed flattening can be ascribed to rotation, we have obtained long-slit high-resolution VLT/UVES spectra of this cluster along and perpendicular to the axis of flattening. Using cross-correlation we find that the velocity profile of the cluster is consistent with zero rotation along either axis. Thus neither cluster rotation nor galactic tides can be responsible for the flattened morphology of WLM-1. We argue that the required velocity dispersion anisotropy between the semi-major and semi-minor axes that would be required to account for the observed flattening is relatively small, of order 1 km/s. Even though our errors preclude us from conclusively establishing that such a difference indeed exists, velocity anisotropy remains at present the most plausible explanation for the shape of this cluster.Comment: 11 pages, 10 figures, submitted to the A

The association between preoperative body composition and aerobic fitness in patients scheduled for colorectal surgery

AIM: Although cardiopulmonary exercise testing (CPET) is considered the gold standard, a preoperative abdominal CT scan might also provide information concerning preoperative aerobic fitness for risk assessment. This study aimed to investigate the association between preoperative CT‐scan‐derived body composition variables and preoperative CPET variables of aerobic fitness in colorectal surgery. METHOD: In this retrospective cohort study, CT images at level L3 were analysed for skeletal muscle mass, skeletal muscle radiation attenuation, visceral adipose tissue (VAT) mass and subcutaneous adipose tissue mass. Regression analyses were performed to investigate the relation between CT‐scan‐derived body composition variables, CPET‐derived aerobic fitness and other preoperative patient‐related variables. Logistic regression analysis was performed to predict a preoperative anaerobic threshold (AT) ≤ 11.1 ml/kg/min as cut‐off for having a high risk for postoperative complications. RESULTS: Data from 78 patients (45 men; mean [SD] age 74.5 [6.4 years]) were analysed. A correlation coefficient of 0.55 was observed between absolute AT and skeletal muscle mass index. Absolute AT (R (2) of 51.1%) was lower in patients with a lower skeletal muscle mass index, together with higher age, lower body mass and higher American Society of Anesthesiologists (ASA) score. Higher ASA score (odds ratio 5.64; P = 0.033) and higher VAT mass (odds ratio 1.02; P = 0.036) were associated with an increased risk of an AT ≤ 11.1 ml/kg/min. CONCLUSION: Body composition variables from the preoperative CT scan were moderately associated with preoperative CPET‐derived aerobic fitness. Higher ASA score and higher VAT mass were associated with an increased risk of an AT ≤ 11.1 ml/kg/min