Natural Language Understanding and Multimodal Discourse Analysis for Interpreting Extremist Communications and the Re-Use of These Materials Online

This paper reports on a study that is part of a project which aims to develop a multimodal analytical approach for big data analytics, initially in the context of violent extremism. The findings reported here tested the application of natural language processing models to the text of a sample of articles from the online magazines Dabiq and Rumiyah, produced by the Islamic extremist organisation ISIS. For comparison, text of articles found by reverse image search software which re-used the lead images from the original articles in text which either reported on or opposed extremist activities was also analysed. The aim was to explore what insights the natural language processing models could provide to distinguish between texts produced as propaganda to incite violent extremism and texts which either reported on or opposed violent extremism. The results showed that some valuable insights can be gained from such an approach and that these results could be improved through integrating automated analyses with a theoretical approach with analysed language and images in their immediate and social contexts. Such an approach will inform the interpretation of results and will be used in training software so that stronger results can be achieved in the future

FluTE, a Publicly Available Stochastic Influenza Epidemic Simulation Model

Mathematical and computer models of epidemics have contributed to our understanding of the spread of infectious disease and the measures needed to contain or mitigate them. To help prepare for future influenza seasonal epidemics or pandemics, we developed a new stochastic model of the spread of influenza across a large population. Individuals in this model have realistic social contact networks, and transmission and infections are based on the current state of knowledge of the natural history of influenza. The model has been calibrated so that outcomes are consistent with the 1957/1958 Asian A(H2N2) and 2009 pandemic A(H1N1) influenza viruses. We present examples of how this model can be used to study the dynamics of influenza epidemics in the United States and simulate how to mitigate or delay them using pharmaceutical interventions and social distancing measures. Computer simulation models play an essential role in informing public policy and evaluating pandemic preparedness plans. We have made the source code of this model publicly available to encourage its use and further development

Computational Modelling of Patella Femoral Kinematics During Gait Cycle and Experimental Validation

The effect of loading and boundary conditions on patellar mechanics is significant due to the complications arising in patella femoral joints during total knee replacements. To understand the patellar mechanics with respect to loading and motion, a computational model representing the patella femoral joint was developed and validated against experimental results. The computational model was created in IDEAS NX and simulated in MSC ADAMS/VIEW software. The results obtained in the form of internal external rotations and anterior posterior displacements for a new and experimentally simulated specimen for patella femoral joint under standard gait condition were compared with experimental measurements performed on the Leeds ProSim knee simulator. A good overall agreement between the computational prediction and the experimental data was obtained for patella femoral kinematics. Good agreement between the model and the past studies was observed when the ligament load was removed and the medial lateral displacement was constrained. The model is sensitive to ±5 % change in kinematics, frictional, force and stiffness coefficients and insensitive to time step

Inconsistent strategies to spin up models in CMIP5: Implications for ocean biogeochemical model performance assessment

This is the final version of the article. Available from EGU via the DOI in this record.During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to-model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.We sincerely thank I. Kriest, F. Joos, the anonymous reviewer and A. Yool for their useful comments on this paper. This work was supported by H2020 project CRESCENDO “Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach”, which received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 641816 and by the EU FP7 project CARBOCHANGE “Changes in carbon uptake and emissions by oceans in a changing climate” which received funding from the European community’s Seventh Framework Programme under grant agreement no. 264879. Supercomputing time was provided by GENCI (Grand Equipement National de Calcul Intensif) at CCRT (Centre de Calcul Recherche et Technologie), allocation 016178. Finally, we are grateful to the ESGF project which makes data available for all the community. Roland Séférian is grateful to Aurélien Ribes for his kind advices on statistics. Jerry Tjiputra acknowledges ORGANIC project (239965/F20) funded by the Research Council of Norway. Christoph Heinze and Jerry Tjiputra are grateful for support through project EVA – Earth system modelling of climate variations in the Anthropocene (229771/E10) funded by the Research Council of Norway, as well as CPU-time and mass storage provided through NOTUR project NN2345K as well as NorStore project NS2345K. Keith Lindsay and Scott C. Doney acknowledge support from the National Science Foundation

Factors associated with viremia in people living with HIV on antiretroviral therapy in Guatemala

INTRODUCTION: Viral suppression prevents HIV transmission and disease progression, but socio-economic and clinical factors can hinder the goal of suppression. We evaluated factors associated with viral non suppression (VNS) and persistent viremia (PV) in people living with HIV (PLHIV) receiving antiretroviral therapy (ART) in Guatemala. METHODS: We conducted a cross sectional analysis using data from an ongoing cohort of PLHIV attending the largest HIV clinic in Guatemala. Univariable and multivariable analyses were conducted between PLHIV with viral suppression and detectable viremia. VNS was defined as most recent HIV RNA ≥ 200 copies/ml and PV as two consecutive HIV RNA ≥ 200 copies/ml. RESULTS: Of 664 participants, 13.3% had VNS and 7.1% had PV. In univariable analysis disaggregated by gender, low income, poor education, perceived difficulty attending healthcare, and alcohol use were associated with VNS in men while low CD4 at diagnosis, multiple prior ART regimens and treatment interruptions were significant in both genders. Multiple prior ART regimens (adjusted Odds Ratio (aOR) 2.82, [95% confidence interval (CI) 1.59, 4.99], p \u3c 0.01), treatment interruptions (aOR 4.51, [95% CI 2.13, 9.58], p \u3c 0.01), excessive alcohol consumption (aOR 2.56, [95% CI 1.18, 5.54], p \u3c 0.05) perceived difficulty attending healthcare (aOR 2.07, [ 95% CI 1.25, 3.42], p \u3c 0.01) and low CD4 at diagnosis (aOR 2.34, 95% [CI 1.30, 4.20], p \u3c 0.01) were independently associated with VNS on multivariable regression. CONCLUSIONS: We conclude that socio-economic and clinical factors influence viral suppression in our cohort and vary between men and women. Gender specific approaches are necessary to achieve the 90% suppression goal

Evaluation of vaccination strategies for SIR epidemics on random networks incorporating household structure

This paper is concerned with the analysis of vaccination strategies in a stochastic SIR (susceptible → infected → removed) model for the spread of an epidemic amongst a population of individuals with a random network of social contacts that is also partitioned into households. Under various vaccine action models, we consider both household-based vaccination schemes, in which the way in which individuals are chosen for vaccination depends on the size of the households in which they reside, and acquaintance vaccination, which targets individuals of high degree in the social network. For both types of vaccination scheme, assuming a large population with few initial infectives, we derive a threshold parameter which determines whether or not a large outbreak can occur and also the probability and fraction of the population infected by such an outbreak. The performance of these schemes is studied numerically, focusing on the influence of the household size distribution and the degree distribution of the social network. We find that acquaintance vaccination can significantly outperform the best household-based scheme if the degree distribution of the social network is heavy-tailed. For household-based schemes, when the vaccine coverage is insufficient to prevent a major outbreak and the vaccine is imperfect, we find situations in which both the probability and size of a major outbreak under the scheme which minimises the threshold parameter are \emph{larger} than in the scheme which maximises the threshold parameter

The Impact of the Unstructured Contacts Component in Influenza Pandemic Modeling

Individual based models have become a valuable tool for modeling the spatiotemporal dynamics of epidemics, e.g. influenza pandemic, and for evaluating the effectiveness of intervention strategies. While specific contacts among individuals into diverse environments (family, school/workplace) can be modeled in a standard way by employing available socio-demographic data, all the other (unstructured) contacts can be dealt with by adopting very different approaches. This can be achieved for instance by employing distance-based models or by choosing unstructured contacts in the local communities or by employing commuting data.Here we show how diverse choices can lead to different model outputs and thus to a different evaluation of the effectiveness of the containment/mitigation strategies. Sensitivity analysis has been conducted for different values of the first generation index G(0), which is the average number of secondary infections generated by the first infectious individual in a completely susceptible population and by varying the seeding municipality. Among the different considered models, attack rate ranges from 19.1% to 25.7% for G(0) = 1.1, from 47.8% to 50.7% for G(0) = 1.4 and from 62.4% to 67.8% for G(0) = 1.7. Differences of about 15 to 20 days in the peak day have been observed. As regards spatial diffusion, a difference of about 100 days to cover 200 km for different values of G(0) has been observed.To reduce uncertainty in the models it is thus important to employ data, which start being available, on contacts on neglected but important activities (leisure time, sport mall, restaurants, etc.) and time-use data for improving the characterization of the unstructured contacts. Moreover, all the possible effects of different assumptions should be considered for taking public health decisions: not only sensitivity analysis to various model parameters should be performed, but intervention options should be based on the analysis and comparison of different modeling choices

Web-based physical activity intervention for people with progressive multiple sclerosis: application of consensus-based intervention development guidance.

OBJECTIVES: People with progressive multiple sclerosis (PwPMS) report that they recognise the benefits of activity on their physical and psychological health but need support to achieve their physical activity goals. We aimed to systematically develop a theoretically informed intervention that would enable PwPMS to more readily engage in regular physical activity. DESIGN: We used an intervention mapping approach to inform intervention development. SETTING: We conducted semistructured interviews with PwPMS and their families/carers and physiotherapists recruited from secondary care settings. PARTICIPANTS: Fourteen PwPMS with an Expanded Disability Status Scale score of between 6 and 8 and 7 of their families/carers and 13 physiotherapists and 1 physiotherapy technician participated. RESULTS: Interview data suggested that the development of supportive coaching relationships with physiotherapists could promote the ability of PwPMS to achieve a desirable and achievable physical activity plan. These interview data informed the prototype 'Lifestyle Exercise and Activity Package for Multiple Sclerosis' (LEAP-MS) consisting of a secure multiuser web-based platform (with an education and activity suite, interactive components enabling selection of exercises, goal setting and activity logging), up to six flexible face-to-face or web-based physiotherapy coaching sessions and remote support via an embedded web-based messaging function that all together draw on specific theory-based methods to achieve physical activity behaviour change, namely active learning, reinforcement, modelling, feedback, facilitation, goal setting and guided practice. Implementation is within a multiuser platform accessible to participants, trained physiotherapists and researchers. CONCLUSIONS: We have followed an inclusive, systematic and transparent process to develop the LEAP-MS intervention that enables detailed description of components, context and guiding principles to inform ongoing evaluation. Importantly, PwPMS expressed the need for autonomy in developing physical activity plans. This has been achieved through the embedding of self-management principles in the design and delivery of the LEAP-MS intervention