ICT and exporting: the effects of broadband on the extensive margin of business service exports.

Over recent decades the global economy has witnessed rapid growth of international trade in services. This has been particularly true of service-intensive countries such as the UK. Developments in information and communication technologies are an obvious explanation for this. We provide empirical evidence for the effects of broadband use on the firm-extensive margin of UK service exports. To deal with the issue of causality we build a novel instrument that exploits exogenous variation in access to broadband technologies due to the historic telephone network. We find evidence for a causal effect from the internet on trade in business services, but no evidence for an effect on trade in services more generally

Broadband infrastructure, ICT use and firm performance: evidence for UK firms

The recent economics literature has begun to recognise that ICT is a heterogeneous technology altering information storage, processing and communication in distinct ways. In this paper we use the arrival of a new communication technology, ADSL broadband, to study the effects of heterogeneous types of ICT on firm performance. To do so free from endogeneity bias, we construct instruments using postcode-level geographic variation in the infrastructure underlying broadband internet - the pre-existing telephone network. We show that after placing various restrictions on the sample, instruments based on the timing of ADSL broadband enablement and the cable distance to the local telephone exchange satisfy the conditions for instrument relevancy and validity. We find in turn, that ICT causally affects firm size (captured by either sales or employment) but not productivity

Intangibles and industry concentration: supersize me

This paper presents new evidence on the growing scale of big businesses in the United States, Japan and 11 European countries. It documents a broad increase in industry concentration across the majority of countries and sectors over the period 2002 to 2014. The rising concentration is strongly associated with intensive investment in intangibles, particularly innovative assets, software and data, and this relationship is magnified in more globalized and digital-intensive industries. The results are consistent with intangibles disproportionately benefiting large firms and enabling them to scale up and raise their market shares, increasingly over time

Evolving Test Environments to Identify Faults in Swarm Robotics Algorithms

Swarm robotic systems are often considered to be dependable. However, there is little empirical evidence or theoretical analysis showing that dependability is an inherent property of all swarm robotic system. Recent literature has identified potential issues with respect to dependability within certain types of swarm robotic algorithms. There appears to be a dearth of literature relating to the testing of swarm robotic systems; this provides motivation for the development of the novel testing methods for swarm robotic systems presented in this paper. We present a search based approach, using genetic algorithms, for the automated identification of unintended behaviors during the execution of a flocking type algorithm, implemented on a simulated robotic swarm. Results show that this proposed approach is able to reveal faults in such flocking algorithms and has the potential to be used in further swarm robotic applications

Industry connection in Europe and North America

This report presents new evidence on industry concentration trends in Europe and in North America. It uses two novel data sources: representative firm-level concentration measures from the OECD MultiProd project, and business-group-level concentration measures using matched OrbisWorldscope-Zephyr data. Based on the MultiProd data, it finds that between 2001 and 2012 the average industry across 10 European economies saw a 2-3-percentage-point increase in the share of the 10% largest companies in industry sales. Using the Orbis-Worldscope-Zephyr data, it documents a clear increase in industry concentration in Europe as well as in North America between 2000 and 2014 of the order of 4-8 percentage points for the average industry. Over the period, about 3 out of 4 (2-digit) industries in each region saw their concentration increase. The increase is observed for both manufacturing and non-financial services and is not driven by digital-intensive sectors

Using Emulation to Engineer and Understand Simulations of Biological Systems

Modeling and simulation techniques have demonstrated success in studying biological systems. As the drive to better capture biological complexity leads to more sophisticated simulators, it becomes challenging to perform statistical analyses that help translate predictions into increased understanding. These analyses may require repeated executions and extensive sampling of high-dimensional parameter spaces: analyses that may become intractable due to time and resource limitations. Significant reduction in these requirements can be obtained using surrogate models, or emulators, that can rapidly and accurately predict the output of an existing simulator. We apply emulation to evaluate and enrich understanding of a previously published agent-based simulator of lymphoid tissue organogenesis, showing an ensemble of machine learning techniques can reproduce results obtained using a suite of statistical analyses within seconds. This performance improvement permits incorporation of previously intractable analyses, including multi-objective optimization to obtain parameter sets that yield a desired response, and Approximate Bayesian Computation to assess parametric uncertainty. To facilitate exploitation of emulation in simulation-focused studies, we extend our open source statistical package, spartan, to provide a suite of tools for emulator development, validation, and application. Overcoming resource limitations permits enriched evaluation and refinement, easing translation of simulator insights into increased biological understanding

Cylindabot: Transformable Wheg Robot Traversing Stepped and Sloped Environments

The ability of an autonomous robot to adapt to different terrain affords the flexibility to move successfully in a range of environments. This paper proposes the Cylindabot, a transformable Wheg robot that can move with two large wheels, each of which can rotate out, producing three legs. This ability to change its mode of locomotion allows for specialised performance. The Cylindabot has been tested in simulation and on a physical robot on steps and slopes as an indication of its efficacy in different environments. These experiments show that such robots are capable of climbing up to a 32 degree slope and a step 1.43 times their initial height. Theoretical limits are devised that match the results, and a comparison with existing Wheg platforms is made

Cloud computing and firm growth

Cloud computing has shifted how firms access IT away from investment in fixed capital to pay-on-demand services that facilitate remote and simultaneous use. Using new firm-level data we examine the impact of cloud adoption on firm performance and organizational geography with an IV approach that exploits cross-section and time-series variation in fiber broadband speeds as instruments. Cloud leads younger firms to increase revenue, employment, and productivity, whereas incumbent firms experience no scale effects and weaker productivity gains. Incumbents however undergo restructuring through establishment deaths and fewer births, while both types of firms experience geographic reorganization as activity shifts farther from the headquarters

Leukocyte Motility Models Assessed through Simulation and Multi-objective Optimization-Based Model Selection

The advent of two-photon microscopy now reveals unprecedented, detailed spatio-temporal data on cellular motility and interactions in vivo. Understanding cellular motility patterns is key to gaining insight into the development and possible manipulation of the immune response. Computational simulation has become an established technique for understanding immune processes and evaluating hypotheses in the context of experimental data, and there is clear scope to integrate microscopy-informed motility dynamics. However, determining which motility model best reflects in vivo motility is non-trivial: 3D motility is an intricate process requiring several metrics to characterize. This complicates model selection and parameterization, which must be performed against several metrics simultaneously. Here we evaluate Brownian motion, Lévy walk and several correlated random walks(CRWs) against the motility dynamics of neutrophils and lymph node T cells under inflammatory conditions by simultaneously considering cellular translational and turn speeds, and meandering indices. Heterogeneous cells exhibiting a continuum of inherent translational speeds and directionalities comprise both datasets, a feature significantly improving capture of in vivo motility when simulated as a CRW. Furthermore, translational and turn speeds are inversely correlated, and the corresponding CRW simulation again improves capture of our in vivo data, albeit to a lesser extent. In contrast, Brownian motion poorly reflects our data. Lévy walk is competitive in capturing some aspects of neutrophil motility, but T cell directional persistence only, therein highlighting the importance of evaluating models against several motility metrics simultaneously. This we achieve through novel application of multi-objective optimization, wherein each model is independently implemented and then parameterized to identify optimal trade-offs in performance against each metric. The resultant Pareto fronts of optimal solutions are directly contrasted to identify models best capturing in vivo dynamics, a technique that can aid model selection more generally. Our technique robustly determines our cell populations’ motility strategies, and paves the way for simulations that incorporate accurate immune cell motility dynamics

The effects of temporal pressure on obstacle negotiation and gaze behaviour in young adults with simulated vision loss

Individuals with vision loss adapt their locomotion and gaze behaviour to safely negotiate objects in temporally unconstrained situations. However, everyday activities are often performed under time-pressure. We investigated the effects of blur on anxiety, movement kinematics and gaze behaviour during the negotiation of a floor-based obstacle under three amounts of pressure: 1) no-pressure; 2) tonal-pressure: an intermittent tone was played at a constant frequency; 3) tonal + time pressure: the intermittent tone increased in frequency and participants had to walk 20% faster to reach the end of the lab. Irrespective of the amount of pressure, the blurred vs. normal vision group reported 32% more anxiety, lifted the lead foot 43% higher and 10% slower over the obstacle, and looked 6% longer and 6% more frequently ahead of the obstacle. In the tonal + time pressure vs. no-pressure condition, both groups were more anxious, showed adaptations in movement kinematics related to walking faster, and adopted a ‘checking strategy’ by shortening their fixation durations at the obstacle. These results show that irrespective of temporal pressure, the blurred vision group remained more cautious as to how the lead foot negotiated the obstacle, in order to reduce the chance of tripping during crossing