Why Do Cascade Sizes Follow a Power-Law?

We introduce random directed acyclic graph and use it to model the information diffusion network. Subsequently, we analyze the cascade generation model (CGM) introduced by Leskovec et al. [19]. Until now only empirical studies of this model were done. In this paper, we present the first theoretical proof that the sizes of cascades generated by the CGM follow the power-law distribution, which is consistent with multiple empirical analysis of the large social networks. We compared the assumptions of our model with the Twitter social network and tested the goodness of approximation.Comment: 8 pages, 7 figures, accepted to WWW 201

High Voltage Apparatus for Nuclear Physics

The design and performance of a transformer-rectifier voltage quadrupling installation for potentials up to 600 KV will be described

Educational outcomes in extremely preterm children : neuropsychological correlates and predictors of attainment

This study assessed the impact of extremely preterm birth on academic attainment at 11 years of age, investigated neuropsychological antecedents of attainment in reading and mathematics, and examined early predictors of educational outcomes. Children born extremely preterm had significantly poorer academic attainment and a higher prevalence of learning difficulties than their term peers. General cognitive ability and specific deficits in visuospatial skills or phoneme deletion at 6 years were predictive of mathematics and reading attainment at 11 years in both extremely preterm and term children. Phonological processing, attention, and executive functions at 6 years were also associated with academic attainment in children born extremely preterm. Furthermore, social factors, neonatal factors (necrotizing enterocolitis, breech delivery, abnormal cerebral ultrasound, early breast milk provision), and developmental factors at 30 months (head circumference, cognitive development), were independent predictors of educational outcomes at 11 years. Neonatal complications combined with assessments of early cognitive function provide moderate prediction for educational outcomes in children born extremely preterm

Analysis of a microscopic stochastic model of microtubule dynamic instability

A novel theoretical model of dynamic instability of a system of linear (1D) microtubules (MTs) in a bounded domain is introduced for studying the role of a cell edge in vivo and analyzing the effect of competition for a limited amount of tubulin. The model differs from earlier models in that the evolution of MTs is based on the rates of single unit (e.g., a heterodimer per protofilament) transformations, in contrast to postulating effective rates/frequencies of larger-scale changes, extracted, e.g., from the length history plots of MTs. Spontaneous GTP hydrolysis with finite rate after polymerization is assumed, and theoretical estimates of an effective catastrophe frequency as well as other parameters characterizing MT length distributions and cap size are derived. We implement a simple cap model which does not include vectorial hydrolysis. We demonstrate that our theoretical predictions, such as steady state concentration of free tubulin, and parameters of MT length distributions, are in agreement with the numerical simulations. The present model establishes a quantitative link between microscopic parameters governing the dynamics of MTs and macroscopic characteristics of MTs in a closed system. Lastly, we use a computational Monte Carlo model to provide an explanation for non-exponential MT length distributions observed in experiments. In particular, we show that appearance of such non-exponential distributions in the experiments can occur because the true steady state has not been reached, and/or due to the presence of a cell edge.Comment: 14 pages, 7 figure

Controlled packing and single-droplet resolution of 3D-printed functional synthetic tissues

3D-printing networks of droplets connected by interface bilayers are a powerful platform to build synthetic tissues in which functionality relies on precisely ordered structures. However, the structural precision and consistency in assembling these structures is currently limited, which restricts intricate designs and the complexity of functions performed by synthetic tissues. Here, we report that the equilibrium contact angle (θDIB) between a pair of droplets is a key parameter that dictates the tessellation and precise positioning of hundreds of picolitre-sized droplets within 3D-printed, multi-layer networks. When θDIB approximates the geometrically-derived critical angle (θc) of 35.3°, the resulting networks of droplets arrange in regular hexagonal close-packed (hcp) lattices with the least fraction of defects. With this improved control over droplet packing, we can 3D-print functional synthetic tissues with single-droplet-wide conductive pathways. Our new insights into 3D droplet packing permit the fabrication of complex synthetic tissues, where precisely positioned compartments perform coordinated tasks

Stability of the Autism Diagnostic Interview—Revised from Pre-School to Elementary School Age in Children with Autism Spectrum Disorders

This study examined the stability of scores on the ADI-R from pre-school to elementary school age in children with autism spectrum disorders (ASD). Participants were 35 children who, at T1, all had a clinical diagnosis of ASD. On initial assessment (mean age 3.5 years; SD 0.6), all met ADI-R algorithm criteria for autism. ADI-R assessments were repeated at follow up (FU; mean age 10.5 years; SD 0.8). Changes in ADI-R total, domain and ADI-R algorithm item scores were assessed. Twentyeight children continued to score above the ADI-R cut-off for autism at FU, although significant decreases in ADI-R domain and item scores were also found. In conclusion, while classification of children according to ADI-R criteria, generally remained stable between pre-school and elementary school age, many children demonstrated significant improvements in symptom severity

A multiscale hybrid model for pro-angiogenic calcium signals in a vascular endothelial cell

Cytosolic calcium machinery is one of the principal signaling mechanisms by which endothelial cells (ECs) respond to external stimuli during several biological processes, including vascular progression in both physiological and pathological conditions. Low concentrations of angiogenic factors (such as VEGF) activate in fact complex pathways involving, among others, second messengers arachidonic acid (AA) and nitric oxide (NO), which in turn control the activity of plasma membrane calcium channels. The subsequent increase in the intracellular level of the ion regulates fundamental biophysical properties of ECs (such as elasticity, intrinsic motility, and chemical strength), enhancing their migratory capacity. Previously, a number of continuous models have represented cytosolic calcium dynamics, while EC migration in angiogenesis has been separately approached with discrete, lattice-based techniques. These two components are here integrated and interfaced to provide a multiscale and hybrid Cellular Potts Model (CPM), where the phenomenology of a motile EC is realistically mediated by its calcium-dependent subcellular events. The model, based on a realistic 3-D cell morphology with a nuclear and a cytosolic region, is set with known biochemical and electrophysiological data. In particular, the resulting simulations are able to reproduce and describe the polarization process, typical of stimulated vascular cells, in various experimental conditions.Moreover, by analyzing the mutual interactions between multilevel biochemical and biomechanical aspects, our study investigates ways to inhibit cell migration: such strategies have in fact the potential to result in pharmacological interventions useful to disrupt malignant vascular progressio