Classifier identification in Ancient Egyptian as a low-resource sequence-labelling task

The complex Ancient Egyptian (AE) writing system was characterised by widespread use ofgraphemic classifiers (determinatives): silent (unpronounced) hieroglyphic signs clarifyingthe meaning or indicating the pronunciation of the host word. The study of classifiers has intensified in recent years with the launch and quick growth of the iClassifier project, a webbased platform for annotation and analysis of classifiers in ancient and modern languages. Thanks to the data contributed by the project participants, it is now possible to formulate the identification of classifiers in AE texts as an NLP task. In this paper, we make first steps towards solving this task by implementing a series of sequence-labelling neural models, which achieve promising performance despite the modest amount of training data. We discuss tokenisation and operationalisation issues arising from tackling AE texts and contrast our approach with frequency-based baselines

A fuzzing‐based test‐creation approach for evaluating digital TV receivers via transport streams

Many digital TV (DTV) broadcasters inadvertently misconfigure their devices and transmit wrong information, which may cause incorrect receiver behavior. Moreover, the way those problems are usually introduced in DTV signals presents some randomness, which resembles fuzzing techniques. This scenario is addressed here, which led to a novel receiver robustness evaluation methodology based on non-compliance tests using grammar-based guided fuzzing. Experiments with such a scheme have shown its efficacy and provided opportunities to improve robustness regarding commercial DTV platforms. Index Terms—Digital TV, Fuzzing, Robustness Testing, Transport Stream, Testing Methodolog

Non-Unique Machine Learning Mapping in Data-Driven Reynolds Averaged Turbulence Models

Recent growing interest in using machine learning for turbulence modelling has led to many proposed data-driven turbulence models in the literature. However, most of these models have not been developed with overcoming non-unique mapping (NUM) in mind, which is a significant source of training and prediction error. Only NUM caused by one-dimensional channel flow data has been well studied in the literature, despite most data-driven models having been trained on two-dimensional flow data. The present work aims to be the first detailed investigation on NUM caused by two-dimensional flows. A method for quantifying NUM is proposed and demonstrated on data from a flow over periodic hills, and an impinging jet. The former is a wall-bounded separated flow, and the latter is a shear flow containing stagnation and recirculation. This work confirms that data from two-dimensional flows can cause NUM in data-driven turbulence models with the commonly used invariant inputs. This finding was verified with both cases, which contain different flow phenomena, hence showing that NUM is not limited to specific flow physics. Furthermore, the proposed method revealed that regions containing low strain and rotation or near pure shear cause the majority of NUM in both cases - approximately 76% and 89% in the flow over periodic hills and impinging jet, respectively. These results led to viscosity ratio being selected as a supplementary input variable (SIV), demonstrating that SIVs can reduce NUM caused by data from two-dimensional flows

CASPER: Cognitive Architecture for Social Perception and Engagement in Robots

Our world is being increasingly pervaded by intelligent robots with varying degrees of autonomy. To seamlessly integrate themselves in our society, these machines should possess the ability to navigate the complexities of our daily routines even in the absence of a human’s direct input. In other words, we want these robots to understand the intentions of their partners with the purpose of predicting the best way to help them. In this paper, we present the initial iteration of CASPER (Cognitive Architecture for Social Perception and Engagement in Robots): a symbolic cognitive architecture that uses qualitative spatial reasoning to anticipate the pursued goal of another agent and to calculate the best collaborative behavior. This is performed through an ensemble of parallel processes that model a low-level action recognition and a high-level goal understanding, both of which are formally verified. We have tested this architecture in a simulated kitchen environment and the results we have collected show that the robot is able to both recognize an ongoing goal and to properly collaborate towards its achievement. This demonstrates a new use of Qualitative Spatial Relations applied to the problem of intention reading in the domain of human-robot interaction

Composition-Dependent Morphology of Stoichiometric and Oxygen Deficient PuO₂ Nanoparticles in the Presence of H₂O and CO₂: A Density-Functional Theory Study

Among the most pressing challenges faced by the UK nuclear industry is how to safely handle its large stockpile of plutonium dioxide. In particular, understanding how the exposed surfaces interact with the environment is critical to establishing the chemical reactivity and determining suitable processing and storage conditions. In this work, we apply an ab initio modelling approach to predict the morphology and surface speciation of stoichiometric and oxygen deficient PuO2 nanoparticles as a function of temperature and in the presence of individually- and co-adsorbed H2O and CO2. We find that co-adsorption of the two species has a significant impact on the surface composition, resulting in the equilibrium particle morphology being strongly dependent on the storage conditions. This work provides valuable insight into the behaviour of nanoparticulate PuO2 in the presence of ubiquitous small molecules and marks an important step toward more realistic models extendable to other adsorbates and actinide oxides

Use of Mendelian Randomization to assess the causal status of modifiable exposures for rheumatic diseases

The explosion in Mendelian randomization (MR) publications is hard to ignore and shows no signs of slowing. Clinician readers, who may not be familiar with jargon-ridden methods, are expected to discern the good from the many low-quality studies that make overconfident claims of causality or stretch the plausibility of what MR can investigate. We aim to equip readers with foundational concepts, contextualized using examples in rheumatology, to appraise the many MR papers that are or will appear in their journals. We highlight the importance of assessing whether exposures are under plausibly specific genetic influence, whether the hypothesized causal pathways make biological sense, and whether results stand up to replication and use of control outcomes. Quality of research can vary substantially using MR as with any design, and all methods have inherent limitations. MR studies have provided and can still contribute valuable insights in the context of evidence triangulation

Outcomes following anti-TNF originator to biosimilar switching in children and young people with Juvenile Idiopathic Arthritis (JIA)

Objectives: For cost-saving, children and young people with JIA are being switched (non-medical) from biologic originators to biosimilars. This analysis investigates what happens to those who switch from an anti-TNF originator to biosimilar, regarding drug survival and disease activity, compared with a matched-cohort who remain on originator.Methods: Includes all patients in the UK JIA Biologics Register (cohort study) switching directly from an anti-TNF originator to biosimilar of the same product. All patients were matched (age, gender, disease duration, calendar-year, line of therapy, ILAR) to patients receiving originator. For those matched successfully, Cox-proportional hazard models assessed whether drug persistence differed between those who switched versus those remaining on originator. Change in JADAS-71, and proportion worsening (by ≥1.7units), after six-months was compared between cohorts. This analysis was designed to address a priority research area set by our patient-partners.Results: 224 patients switched from originator to biosimilar; 143(63%) adalimumab, 56(25%) etanercept, 25(11%) infliximab. Of these, 164 patients were matched successfully to those remaining on originator. There was no evidence that patients switching were more likely to stop treatment compared with those remaining on originator: hazard ratio 1.44 (95%CI:0.91-2.26). Of the 50 biosimilar patients who stopped treatment, 18 switched-back to the originator (14 in year one), 27 started a different biologic, and five remained off treatment at last follow-up. Of the 87 matched-patients with available disease activity, there was no evidence that JADAS-71 worsened more after six-months: odds ratio 0.71 (95%CI:0.34-1.52).Conclusions: In this large matched comparative effectiveness analysis, many children and young people with JIA have switched from originators to biosimilars. Disease activity remained similar between patients switching versus those remaining on originator. Three-in-four were still receiving their biosimilar after one year, with switching back to originator uncommon, 9% after one year, suggesting good tolerability of non-medical switching in this patient population.<br/

Heart rate estimation using on-nail wearable photoplethysmography

Heart Rate (HR) measurements in current wearables are mostly derived from photoplethysmography (PPG). PPG signals have been measured at various locations on the body, however, to date, limited studies have investigated wearable, reflective mode, PPG signals from the finger- and toe- nails. Being rigid surfaces, they may provide comparatively motion robust measurements compared to sensors placed on flexible and stretchable skin. Here, we present an on-nail wearable PPG sensor to estimate HR from nail locations in motionfree and motion-present recordings. We compare to commercial electrocardiogram (ECG) and pulse oximeter (PO) units for 20 participants. PPG HR estimation demonstrated strong correlations with the ECG estimated HR, with a root mean square error of 1.6 beats per minute (bpm) and 2.2 bpm, for finger and toenail locations respectively. During motion these figures increased to 5.6 bpm and 12.8 bpm. No substantial difference in accuracy was found across the skin tone of participants. These results demonstrate the potential feasibility of HR monitoring from nail locations. With sensors placed, for example, inside a shoe, this may offer very discrete monitoring for long term applications