Transcranial Direct-Current Stimulation May Improve Discourse Production in Healthy Older Adults

Background: The use of transcranial direct-current stimulation (tDCS) for therapeutic and neurorehabilitation purposes has become increasingly popular in recent years. Previous research has found that anodal tDCS may enhance naming ability and verbal fluency in healthy participants. However, the effect of tDCS on more functional, higher level language skills such as discourse production has yet to be understood. Aims: The present study aimed to investigate in healthy, older adults (a) the effect of anodal tDCS on discourse production vs. sham stimulation and (b) optimal electrode placement for tDCS to target language improvement at the discourse level. / Methods: Fourteen healthy, older right-handed participants took part in this sham controlled, repeated measures pilot study. Each participant experienced three different experimental conditions; anodal tDCS on the left inferior frontal gyrus (IFG), anodal tDCS on the right IFG and sham stimulation while performing a story telling task. Significant changes in language performance before and after each condition were examined in three discourse production tasks: recount, procedural and narrative. / Results: Left and right IFG conditions showed a greater number of significant within-group improvements (p < 0.05) in discourse production compared to sham with 6/12 for left IFG, 4/12 for right IFG and 2/12 for sham. There were no significant differences noted between tDCS conditions. No relationship was noted between language performance and physical activity, age, or gender. / Conclusions: This study suggests that anodal tDCS may significantly improve discourse production in healthy, older adults. In line with previous tDCS language studies, the left IFG is highlighted as an optimal stimulation site for the modulation of language in healthy speakers. The findings support further exploration of tDCS as a rehabilitative tool for higher-level language skills in persons with aphasia

Numerical simulations of miscible channel flow with chemical reactions

We study the pressure-driven miscible displacement of one fluid by another in a horizontal channel in the presence of an exothermic chemical reaction. We solve the continuity, Navier-Stokes, and energy conservation equations coupled to convective-discussion equations of the reactant and product. The viscosity is assumed to depend on the volume fraction of the reactant and product as well as the temperature. The effects of relevant parameters such as the Reynolds number, Schmidt number, Damköhler number and viscosity ratio of the reactant and product are studied. Our results indicate that increasing the intensity of the chemical reaction by increasing the Damköhler number and decreasing the dimensionless activation energy increases the displacement rate. We have also found that increasing Reynolds number leads to more pronounced instabilities and roll-up phenomena, which in turn promote rapid displacement of the resident fluid inside the channel. Variation of the relative significance of the heat of reaction and the Schmidt numbers of the reactants and products, however, has a negligible influence on the displacement rates for the parameter ranges considered in the present work

Cycles of construing in radicalization and deradicalization: a study of Salafist Muslims.

© Taylor & Francis Group, LLC.This article explores radicalization and deradicalization by considering the experiences of six young Tunisian people who had become Salafist Muslims. Their responses to narrative interviews and repertory grid technique are considered from a personal construct perspective, revealing processes of construing and reconstruing, as well as relevant aspects of the structure and content of their construct systems. In two cases, their journeys involved not only radicalization but self-deradicalization, and their experiences are drawn on to consider implications for deradicalization.Peer reviewedFinal Accepted Versio

Dynamics of surfactant-laden evaporating droplets

We consider the flow dynamics of a thin evaporating droplet in\ud the presence of an insoluble surfactant and small particles in the bulk. Evolution\ud equations for the film height, the interfacial surfactant and bulk particle concentra-\ud tion are derived using a lubrication model coupled by a constitutive relation for the\ud dependence of the viscosity on local particle concentration. An important ingredient\ud of our model is that it takes into account the fact that the surfactant adsorbed at\ud the surface hinders the evaporation. Time-dependent simulations are performed to\ud determine how the presence of surfactants affects the evaporation and flow dynamics\ud with and without the presence of particles in the bulk. We discuss the various mech-\ud anisms that affect the shape of the droplet as it evaporates as well as the resulting\ud pattern of particle deposition

Numerical Modelling of Melt Behaviour in the Lower Vessel Head of a Nuclear Reactor

Acknowledgements The authors would like to thank the EPSRC MEMPHIS multi-phase programme grant, the EPSRC Computational modelling for advanced nuclear power plants project and the EU FP7 projects THINS and GoFastR for helping to fund this work.Peer reviewedPublisher PD

Numerical Modelling of Debris Bed Water Quenching

Acknowledgements The authors would like to thank the EPSRC MEMPHIS multi-phase programme grant, the EPSRC Computational modelling for advanced nuclear power plants project, the EU FP7 projects THINS and GoFastR and ExxonMobil for helping to fund this work.Peer reviewedPublisher PD

Liquid cloud optical property retrieval and associated uncertainties using multi-angular and bispectral measurements of the airborne radiometer OSIRIS

In remote sensing applications, clouds are generally characterized by two properties: cloud optical thickness (COT) and effective radius of water–ice particles (Reff), as well as additionally by geometric properties when specific information is available. Most of the current operational passive remote sensing algorithms use a mono-angular bispectral method to retrieve COT and Reff. They are based on pre-computed lookup tables while assuming a homogeneous plane-parallel cloud layer. In this work, we use the formalism of the optimal estimation method, applied to airborne near-infrared high-resolution multi-angular measurements, to retrieve COT and Reff as well as the corresponding uncertainties related to the measurement errors, the non-retrieved parameters, and the cloud model assumptions. The measurements used were acquired by the airborne radiometer OSIRIS (Observing System Including PolaRization in the Solar Infrared Spectrum), developed by the Laboratoire d'Optique Atmosphérique. It provides multi-angular measurements at a resolution of tens of meters, which is very suitable for refining our knowledge of cloud properties and their high spatial variability. OSIRIS is based on the POLDER (POlarization and Directionality of the Earth's Reflectances) concept as a prototype of the future 3MI (Multi-viewing Multi-channel Multi-polarization Imager) planned to be launched on the EUMETSAT-ESA MetOp-SG platform in 2024. The approach used allows the exploitation of all the angular information available for each pixel to overcome the radiance angular effects. More consistent cloud properties with lower uncertainty compared to operational mono-directional retrieval methods (traditional bispectral method) are then obtained. The framework of the optimal estimation method also provides the possibility to estimate uncertainties of different sources. Three types of errors were evaluated: (1) errors related to measurement uncertainties, which reach 6 % and 12 % for COT and Reff, respectively, (2) errors related to an incorrect estimation of the ancillary data that remain below 0.5 %, and (3) errors related to the simplified cloud physical model assuming independent pixel approximation. We show that not considering the in-cloud heterogeneous vertical profiles and the 3D radiative transfer effects leads to an average uncertainty of 5 % and 4 % for COT and 13 % and 9 % for Reff.</p

A one-dimensional mechanistic model for tracking unsteady slug flow.

A novel one-dimensional slug tracking mechanistic model for unsteady, upward gas-liquid slug flow in inclined pipes is presented. The model stems from the first principles of mass and momentum conservation applied to a slug unit cell consisting of a slug body of liquid and a region of stratified flow containing an elongated bubble and a liquid film. The slug body front and rear are treated as surfaces of discontinuity where mass and momentum balances or "jump laws"are prescribed. The former is commonly applied in mechanistic models for slug flow, whereas the latter is typically overlooked, thereby leading to the assumption of a continuous pressure profile at these points or to the adoption of a pressure drop due to the fluid acceleration on a heuristic basis. Our analysis shows that this pressure change arises formally from the momentum jump law at the slug body front. The flow is assumed to be isothermal, the gas is compressible, the pressure drop in the elongated bubble region is accounted for, the film thickness is considered uniform, and weight effects in the pressure from the interface level are included. Besides specifying momentum jump laws at both borders of the slug body, another novel feature of the present model is that we avoid adopting the quasi-steady approximation for the elongated bubble-liquid film region, and thus the unsteady terms in the mass and momentum balances are kept. The present model requires empirical correlations for the slug body length and the elongated bubble nose velocity. The non-linear equations are discretized and solved simultaneously for all the slug unit cells filling the pipe. Timespace variation of the slug body and film lengths, liquid holdup and void fraction, and pressures, among other quantities, can be predicted, and model performance is evaluated by comparing with data in the literature

Solving the discretised multiphase flow equations with interface capturing on structured grids using machine learning libraries

The authors would like to acknowledge the following EPSRC grants: the PREMIERE programme grant, “AI to enhance manufacturing, energy, and healthcare” (EP/T000414/1); ECO-AI, “Enabling CO capture and storage using AI” (EP/Y005732/1); MUFFINS, “MUltiphase Flow-induced Fluid-flexible structure InteractioN in Subsea” (EP/P033180/1); WavE-Suite, “New Generation Modelling Suite for the Survivability of Wave Energy Convertors in Marine Environments” (EP/V040235/1); INHALE, “Health assessment across biological length scales” (EP/T003189/1); AI-Respire, “AI for personalised respiratory health and pollution” (EP/Y018680/1); RELIANT, “Risk EvaLuatIon fAst iNtelligent Tool for COVID19” (EP/V036777/1); and CO-TRACE, “COvid-19 Transmission Risk Assessment Case Studies — education Establishments” (EP/W001411/1). Also, the authors acknowledge the Innovate UK grant D-XPERT, “AI-Powered Total Building Management System“ (TS/Y020324/1). Support from Imperial-X’s Eric and Wendy Schmidt Centre for AI in Science (a Schmidt Futures program) is gratefully acknowledged. The authors state that, for the purpose of open access, a Creative Commons Attribution (CC BY) license will be applied to any Author Accepted Manuscript version relating to this article.Peer reviewe