The Arab Spring and its social media audiences : English and Arabic Twitter users and their networks

2011 ‘Arab Spring’ are likely to overstate the impact of Facebook and Twitter on these uprisings, it is nonetheless true that protests and unrest in countries from Tunisia to Syria generated a substantial amount of social media activity. On Twitter alone, several millions of tweets containing the hashtags #libya or #egypt were generated during 2011, both by directly affected citizens of these countries, and by onlookers from further afield. What remains unclear, though, is the extent to which there was any direct interaction between these two groups (especially considering potential language barriers between them). Building on hashtag datasets gathered between January and November 2011, this paper compares patterns of Twitter usage during the popular revolution in Egypt and the civil war in Libya. Using custom-made tools for processing ‘big data’, we examine the volume of tweets sent by English-, Arabic-, and mixed-language Twitter users over time, and examine the networks of interaction (variously through @replying, retweeting, or both) between these groups as they developed and shifted over the course of these uprisings. Examining @reply and retweet traffic, we identify general patterns of information flow between the English- and Arabic-speaking sides of the Twittersphere, and highlight the roles played by users bridging both language spheres.

Professional development and social networks in digital content industry micro businesses

This study explores the professional development strategies of digital content professionals in Australian micro businesses. This thesis presents the argument that as these professionals are working in cutting edge creative fields where digital technology drives ongoing change, formal education experiences may be less important than for other professionals, and that specific types of online and face-to-face socially mediated informal learning strategies may be critical to currency. This thesis documents the findings of a broad survey of industry professionals' learning needs and development strategies, in conjunction with rich data from in-depth interviews and social network analyses.

Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

The role and future challenges of wireless communication networks for cooperative autonomous city vehicles

This paper elaborates on the use of future wireless communication networks for autonomous city vehicles. After addressing the state of technology, the paper explains the autonomous vehicle control system architecture and the Cybercars-2 communication framework; it presents experimental tests of communication-based real-time decision making; and discusses potential applications for communication in order to improve the localization and perception abilities of autonomous vehicles in urban environments.

The role of biological extracellular matrix scaffolds in vascularized three-dimensional tissue growth in vivo

An in vivo murine vascularized chamber model has been shown to generate spontaneous angiogenesis and new tissue formation. This experiment aimed to assess the effects of common biological scaffolds on tissue growth in this model. Either laminin-1, type I collagen, fibrin glue, hyaluronan, or sea sponge was inserted into silicone chambers containing the epigastric artery and vein, one end was sealed with adipose tissue and the other with bone wax, then incubated subcutaneously. After 2, 4, or 6 weeks, tissue from chambers containing collagen I, fibrin glue, hyaluronan, or no added scaffold (control) had small amounts of vascularized connective tissue. Chambers containing sea sponge had moderate connective tissue growth together with a mild "foreign body" inflammatory response. Chambers containing laminin-1, at a concentration 10-fold lower than its concentration in Matrigel™, resulted in a moderate adipogenic response. In summary, (1) biological hydrogels are resorbed and gradually replaced by vascularized connective tissue; (2) sponge-like matrices with large pores support connective tissue growth within the pores and become encapsulated with granulation tissue; (3) laminin-containing scaffolds facilitate adipogenesis. It is concluded that the nature and chemical composition of the scaffold exerts a significant influence on the amount and type of tissue generated in this in vivo chamber model.

Second-harmonic generation from biological tissues : effect of excitation wavelength

We report on the measurement of second-harmonic signals from hyperplastic parenchyma and stroma in malignant human prostate tissue under femtosecond pulsed illumination in the wavelength range from 730 to 870 nm. In particular, the relationship of the second-harmonic generation to the excitation wavelength is measured. The result in these two regions behaves considerably differently and thus provides a possible indicator for identifying tissue components and malignancy.

Two-photon fluorescence spectroscopy for identification of healthy and malignant biological tissues

Two-photon fluorescence spectroscopy has been performed on rat skeletal muscles to investigate the effect of fixation processes on the micro-environments of the endogenous fluorophors in rat skeletal muscles. The two-photon fluorescence spectra measured for different fixation periods show a differential among those samples that were fixed in water, formalin and methanol, respectively. The results imply that two-photon fluorescence spectroscopy can be a potential technique for identification of healthy and malignant biological tissues.

Biological performance of a polycaprolactone-based scaffold plus recombinant human morphogenetic protein-2 (rhBMP-2) in an ovine thoracic interbody fusion model

PURPOSE. We develop a sheep thoracic spine interbody fusion model to study the suitability of polycaprolactone-based scaffold and recombinant human bone morphogenetic protein-2 (rhBMP-2) as a bone graft substitute within the thoracic spine. The surgical approach is a mini- open thoracotomy with relevance to minimally invasive deformity correction surgery for adolescent idiopathic scoliosis. To date there are no studies examining the use of this biodegradable implant in combination with biologics in a sheep thoracic spine model. METHODS. In the present study, six sheep underwent a 3-level (T6/7, T8/9 and T10/11) discectomy with randomly allocated implantation of a different graft substitute at each of the three levels; (i) calcium phosphate (CaP) coated polycaprolactone-based scaffold plus 0.54μg rhBMP-2, (ii) CaP coated PCL- based scaffold alone or (iii) autograft (mulched rib head). Fusion was assessed at six months post-surgery. RESULTS. Computed Tomographic scanning demonstrated higher fusion grades in the rhBMP-2 plus PCL- based scaffold group in comparison to either PCL-based scaffold alone or autograft. These results were supported by histological evaluations of the respective groups. Biomechanical testing revealed significantly higher stiffness for the rhBMP-2 plus PCL- based scaffold group in all loading directions in comparison to the other two groups. CONCLUSION. The results of this study demonstrate that rhBMP-2 plus PCL- based scaffold is a viable bone graft substitute, providing an optimal environment for thoracic interbody spinal fusion in a large animal model.

Nowhere to hide: informal disease surveillance networks tracing state behaviour

Since the revisions to the International Health Regulations (IHR) in 2005, much attention has turned to how states, particularly developing states, will address core capacity requirements attached to the revised IHR. Primarily, how will states strengthen their capacity to identify and verify public health emergencies of international concern (PHEIC)? Another important but under-examined aspect of the revised IHR is the empowerment of the World Health Organization (WHO) to act upon non-governmental reports of disease outbreaks. The revised IHR potentially marks a new chapter in the powers of ‘disease intelligence’ and how the WHO may press states to verify an outbreak event. This article seeks to understand whether internet surveillance response programs (ISRPs) are effective in ‘naming and shaming’ states into reporting disease outbreaks.

Applying Enterprise Architecture to Business Networks

Globalization, financial deregulation, economic turmoil, and technology breakthroughs are profoundly exposing organizations to business networks. Engaging these networks requires explicit planning from the strategic level down to the operational level of an organization, which significantly affects organizational artefacts such as business services, processes, and resources. Although enterprise architecture (EA) aligns business and IT aspects of organizational systems, previous applications of EA have not comprehensively addressed a methodological framework for planning. In the context of business networks, this study seeks to explore the application of EA for business network planning where it builds upon relevant and well-established prescriptive and descriptive aspects of EA. Prescriptive aspects include integrated models of services, business processes, and resources among other organizational artefacts, at both business and IT levels. Descriptive aspects include ontological classifications of business functionality, which allow EA models to be aligned semantically to organizational artefacts and, ultimately higher-level business strategy. A prominent approach for capturing descriptive aspects of EA is business capability modelling. In order to explore and develop the illustrative extensions of EA through capability modelling, a list of requirements (capability dimensions) for business network planning will be identified and validated through a revelatory case study encompassing different business network manifestations, or situations. These include virtual organization, liquid workforce, business network orchestration, and headquarters-subsidiary. The use of artefacts, conventionally, modelled through EA will be considered in these network situations. Two general considerations for EA extensions are explored for the identified requirements at the level of the network: extension of artefacts through the network and alignment of network level artefacts with individual organization artefacts. The list of requirements provides the basis for a constructivist extension of EA in the following ways. Firstly, for descriptive aspects, it offers constructivist insights to guide extensions for particular EA techniques and concepts. Secondly, for prescriptive aspects it defines a set of capability dimensions, which improve the analysis and assessment of organization capabilities for business network situations.

Optimal Bayesian experimental design for models with intractable likelihoods using indirect inference applied to biological process models

This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

Large networks of vertical multi-layer graphenes with morphology-tunable magnetoresistance

We report on the comparative study of magnetotransport properties of large-area vertical few-layer graphene networks with different morphologies, measured in a strong (up to 10 T) magnetic field over a wide temperature range. The petal-like and tree-like graphene networks grown by a plasma enhanced CVD process on a thin (500 nm) silicon oxide layer supported by a silicon wafer demonstrate a significant difference in the resistance-magnetic field dependencies at temperatures ranging from 2 to 200 K. This behaviour is explained in terms of the effect of electron scattering at ultra-long reactive edges and ultra-dense boundaries of the graphene nanowalls. Our results pave a way towards three-dimensional vertical graphene-based magnetoelectronic nanodevices with morphology-tuneable anisotropic magnetic properties. © The Royal Society of Chemistry 2013.