Too sick to drive : how motion sickness severity impacts human performance

There are multiple concerns surrounding the development and rollout of self-driving cars. One issue has largely gone unnoticed - the adverse effects of motion sickness as induced by self-driving cars. The literature suggests conditionally, highly and fully autonomous vehicles will increase the onset likelihood and severity of motion sickness. Previous research has shown motion sickness can have a significant negative impact on human performance. This paper uses a simulator study design with 51 participants to assess if the scale of motion sickness is a predictor of human performance degradation. This paper finds little proof that subjective motion sickness severity is an effective indicator of the scale of human performance degradation. The performance change of participants with lower subjective motion sickness is mostly statistically indistinguishable from those with higher subjective sickness. Conclusively, those with even acute motion sickness may be just as affected as those with higher sickness, considering human performance. Building on these results, it could indicate motion sickness should be a consideration for understanding user ability to regain control of a self-driving vehicle, even if not feeling subjectively unwell. Effectiveness of subjective scoring is discussed and future research is proposed to help ensure the successful rollout of self-driving vehicles

Extracting and re-using research data from chemistry e-theses: the SPECTRa-T project

Scientific e-theses are data-rich resources, but much of the information they contain is not readily accessible. For chemistry, the SPECTRa-T project has addressed this problem by developing data-mining techniques to extract experimental data, creating RDF (Resource Description Framework) triples for exposure to sophisticated Semantic Web searches. We used OSCAR3, an Open Source chemistry text-mining tool, to parse and extract data from theses in PDF, and from theses in Office Open XML document format. Theses in PDF suffered data corruption and a loss of formatting that prevented the identification of chemical objects. Theses in .docx yielded semantically rich SciXML that enabled the additional extraction of associated data. Chemical objects were placed in a data repository, and RDF triples deposited in a triplestore. Data-mining from chemistry e-theses is both desirable and feasible; but the use of PDF, the de facto format standard for deposit in most repositories, prevents the optimal extraction of data for semantic querying. In order to facilitate this, we recommend that universities also require deposition of chemistry e-theses in an XML document format. Further work is required to clarify the complex IPR issues and ensure that they do not become an unwarranted barrier to data extraction and re-use

A semantic Grid for molecular science

Proceedings of the 2003 UK e-Science All Hands Meeting, 31st August - 3rd September, Nottingham UKThe properties of molecules have very well defined semantics and allow the creation of a semantic GRID. Markup languages (CML - Chemical Markup Language) and dictionary-based ontologies have been designed to support a wide range of applications, including chemical supply, publication and the safety of compounds. Many properties can be computed by Quantum Mechanical (QM) programs and we have developed a "black-box" system based on XML wrappers for all components. This is installed on a Condor system on which we have computed properties for 250, 000 compounds. The results of this will be available in an OpenData/OpenSource peer-to-peer (P2P) system (WorldWide Molecular Matrix - WWMM)

Spin correlations in Ca3Co2O6: A polarised-neutron diffraction and Monte Carlo study

We present polarised-neutron diffraction measurements of the Ising-like spin-chain compound Ca3Co2O6 above and below the magnetic ordering temperature TN. Below TN, a clear evolution from a single-phase spin-density wave (SDW) structure to a mixture of SDW and commensurate antiferromagnet (CAFM) structures is observed on cooling. For a rapidly-cooled sample, the majority phase at low temperature is the SDW, while if the cooling is performed sufficiently slowly, then the SDW and the CAFM structure coexist between 1.5 and 10 K. Above TN, we use Monte Carlo methods to analyse the magnetic diffuse scattering data. We show that both intra- and inter-chain correlations persist above TN, but are essentially decoupled. Intra-chain correlations resemble the ferromagnetic Ising model, while inter-chain correlations resemble the frustrated triangular-lattice antiferromagnet. Using previously-published bulk property measurements and our neutron diffraction data, we obtain values of the ferromagnetic and antiferromagnetic exchange interactions and the single-ion anisotropy.Comment: 10 pages, 7 figure