922017 research outputs found
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Development and external validation of prediction models for adverse health outcomes in rheumatoid arthritis: a multinational real-world cohort analysis
No full textBackgroundIdentification of rheumatoid arthritis (RA) patients at high risk of adverse health outcomes remains a major challenge. We aimed to develop and validate prediction models for a variety of adverse health outcomes in RA patients initiating first-line methotrexate (MTX) monotherapy. MethodsData from 15 claims and electronic health record databases across 9 countries were used. Models were developed and internally validated on Optum® De-identified Clinformatics® Data Mart Database using L1-regularized logistic regression to estimate the risk of adverse health outcomes within 3 months (leukopenia, pancytopenia, infection), 2 years (myocardial infarction (MI) and stroke), and 5 years (cancers [colorectal, breast, uterine]) after treatment initiation. Candidate predictors included demographic variables and past medical history. Models were externally validated on all other databases. Performance was assessed using the area under the receiver operator characteristic curve (AUC) and calibration plots. FindingsModels were developed and internally validated on 21,547 RA patients and externally validated on 131,928 RA patients. Models for serious infection (AUC: internal 0.74, external ranging from 0.62 to 0.83), MI (AUC: internal 0.76, external ranging from 0.56 to 0.82), and stroke (AUC: internal 0.77, external ranging from 0.63 to 0.95), showed good discrimination and adequate calibration. Models for the other outcomes showed modest internal discrimination (AUC < 0.65) and were not externally validated.InterpretationWe developed and validated prediction models for a variety of adverse health outcomes in RA patients initiating first-line MTX monotherapy. Final models for serious infection, MI, and stroke demonstrated good performance across multiple databases and can be studied for clinical use.<br/
ESBMC-CHERI: Towards Verification of C Programs for CHERI Platforms with ESBMC
No full textIn this paper we present ESBMC-CHERI – first bounded model checker capable of formally verifying C programs for CHERI-enabled platforms. CHERI provides run-time protection for the memory unsafe programming languages such as C/C++ at the hardware level. At the same time, it introduces new semantics to C programs, making some safe C programs cause hardware exceptions on CHERI-extended platforms. Hence, it is crucial to detect memory safety violations and compatibility issues ahead of compilation. However, there are no verification tools currently available for reasoning over CHERI-C programs. We demonstrate the work undertaken towards implementing support for CHERI-C in our state-of-the-art bounded model checker ESBMC and the plans for future work and extensive evaluation of ESBMC-CHERI. The ESBMC-CHERI demonstration and the source code are available at https://github.com/esbmc/esbmc/tree/cheri-clang
ESBMC-Jimple: Verifying Kotlin Programs via Jimple Intermediate Representation
No full textIn this work, we describe and evaluate the first model checker for verifying Kotlin programs through the Jimple intermediate representation. The verifier, named ESBMC-Jimple, is built on top of the Efficient SMT-based Context-Bounded Model Checker (ESBMC). It uses the Soot framework to obtain the Jimple IR, representing a simplified version of the Kotlin source code, containing a maximum of three operands per instruction. ESBMC-Jimple processes Kotlin source code together with a model of the standard Kotlin libraries and checks a set of safety properties. Experimental results show that ESBMC-Jimple can correctly verify a set of Kotlin benchmarks from the literature and that it is competitive with state-of-theart Java bytecode verifiers. A demonstration is available at https://youtu.be/J6WhNfXvJNc
Augmenting a Nature Documentary with a Lifelike Hologram in Virtual Reality
No full textWhile augmented reality television (ARTV) is being investigated in research labs, the high cost of AR headsets makes it difficult foraudiences to benefit from the research. However, the relative affordability of virtual reality (VR) headsets provides ARTV researcherswith opportunities to test their prototypes in VR. Additionally, as VR becomes an acceptable medium for watching conventional TV,augmenting such viewing experiences in VR creates new opportunities. We prototype a nature documentary ARTV experience inVR and conduct a remote user study (𝑛 = 10) to investigate six points on the visual display design dimension of presenting a lifelikeprogramme-related hologram. We manipulated the starting point and the movement behaviour of the hologram to gain insight intoviewer preferences. Our findings highlight the importance of personal preferences and that of the perceived role of a hologram inrelation to the underlying TV content; suggesting there may not be a single way to augment a TV programme. Instead, creators mayneed to provide the audiences with capabilities to customise ARTV content
Optimised cell growth and poly(3-hydroxybutyrate) synthesis from saponified spent coffee grounds oil
No full textSpent coffee grounds (SCG) oil is an ideal substrate for the biosynthesis of polyhydroxyalkanoates (PHAs) by Cupriavidus necator. The immiscibility of lipids with water limits their bioavailability, but this can be resolved by saponifying the oil with potassium hydroxide to form water-soluble fatty acid potassium salts and glycerol. Total saponification was achieved with 0.5 mol/L of KOH at 50 °C for 90 min. The relationship between the initial carbon substrate concentration (C0) and the specific growth rate (µ) of C. necator DSM 545 was evaluated in shake flask cultivations; crude and saponified SCG oils were supplied at matching initial carbon concentrations (C0 = 2.9-23.0 g/L). The Han-Levenspiel model provided the closest fit to the experimental data and accurately described complete growth inhibition at 32.9 g/L (C0 = 19.1 g/L) saponified SCG oil. Peak µ-values of 0.139 h−1 and 0.145 h−1 were obtained with 11.99 g/L crude and 17.40 g/L saponified SCG oil, respectively. Further improvement to biomass production was achieved by mixing the crude and saponified substrates together in a carbon ratio of 75:25% (w/w), respectively. In bioreactors, C. necator initially grew faster on the mixed substrates (µ = 0.35 h−1) than on the crude SCG oil (µ = 0.23 h−1). After harvesting, cells grown on crude SCG oil obtained a total biomass concentration of 7.8 g/L and contained 77.8 % (w/w) PHA. Whereas cells grown on the mixed substrates produced 8.5 g/L of total biomass and accumulated 84.4 % (w/w) of PHA
Emotionally Based School Non-Attendance: Two Successful Returns to School Following Lockdown
No full textEmotionally based school non-attendance (EBSNA) needs are complex, with a distinctive combination of risk factors affecting each individual. This study presents an exploration of the perceived facilitators to successful returns to school for two primary-aged children who had previously experienced anxiety around school attendance. The perspectives of parents, school staff, and educational psychologists were gathered using semi-structured interviews to identify effective support. A reflexive thematic analysis was conducted to generate themes. Findings demonstrate that the support in each case was highly individualised. Key facilitators considered to achieve this included: effective home-school communication; taking a functional approach; engaging other professional support; cultivating positive relationships; and practitioners regularly reflecting on their practice. The significant overlap between themes supports an interactionist, ecological model of early identification and intervention for EBSNA difficulties. Implications for practitioners include the need to ensure a reflective, individualised approach, and the importance of facilitating the home-school relationship.Keywords: emotionally based school non-attendance; anxiety; school absenteeism; educational psychology; intervention<br/
Robust Formation Control for Networked Robotic Systems Using Negative Imaginary Dynamics
No full textThis paper proposes a consensus-based formation tracking scheme for multi-robot systems utilising the Negative Imaginary (NI) theory. The proposed scheme applies to a class of networked robotic systems that can be modelled as a group of single integrator agents with stable uncertainties connected via an undirected graph. NI/SNI property of networked agents facilitates the design of a distributed Strictly Negative Imaginary (SNI) controller to achieve the desired formation tracking. A new theoretical proof of asymptotic convergence of the formation tracking trajectories is derived based on the integral controllability of a networked SNI systems. The proposed scheme is an alternative to the conventional Lyapunov-based formation tracking schemes. It offers robustness to NI/SNI-type model uncertainties and fault-tolerance to a sudden loss of robots due to hardware/communication fault. The feasibility and usefulness of the proposed formation tracking scheme were validated by lab-based real-time hardware experiments involving miniature mobile robots