Techniques for the inference of mileage rates from MOT data

Mathematical and computational techniques are developed for the processing and analysis of annual MOT (roadworthiness) test data that the UK Department for Transport has placed in the public domain. Firstly, techniques are given that clean erroneous records and a linking procedure is provided that permits the inference of an individual vehicle's mileage between consecutive tests. Methods are then developed that analyse aggregate mileage totals, as a function of vehicle age, class and geography. The inference of aggregate mileage rates as a function of time is then considered

The consolidated European synthesis of CH4 and N2O emissions for the European Union and United Kingdom: 1990–2017

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g., anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr-1 (EDGAR v5.0) and 19.0 Tg CH4 yr-1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr-1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr-1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4 yr-1) and surface network (24.4 Tg CH4 yr-1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 Tg CH4 yr-1. For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr-1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr-1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr-1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at. (Petrescu et al., 2020b)

Track D Social Science, Human Rights and Political Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138414/1/jia218442.pd

Scrutinizing the grey areas of declarative memory: Do the self-reference and temporal orientation of a trait knowledge task modulate the Late Positive Component (LPC)?

Knowledge about the future self may engage cognitive processes typically ascribed to episodic memory, such as awareness of the future self as an extension of the current self (i.e., autonoetic awareness) and the construction of future events. In a prior study (Tanguay et al., 2018), temporal orientation influenced the Late Positive Component (LPC), an ERP correlate of recollection. The LPC amplitude for present traits was intermediate between semantic and episodic memory, whereas thinking about one's future traits produced a larger LPC amplitude that was similar to episodic memory. Here, we examined further the effect of temporal orientation on the LPC amplitude and investigated if it was influenced by whether knowledge concerns the self or another person, with the proximity of the other being considered. Participants verified whether traits (e.g., Enthusiastic) were true of themselves and the “other,” both now and in the future. Proximity of the other person was manipulated between subjects, such that participants either thought about the typical traits of a close friend (n = 31), or those of their age group more broadly (n = 35). Self-reference and temporal orientation interacted: The LPC amplitude for future knowledge was larger than for present knowledge, but only for the self. This effect of temporal orientation was not observed when participants thought about the traits of other people. The proximity of the other person did not modify these effects. Future-oriented cognition can engage different cognitive processes depending on self-reference; knowledge about the personal future increased the LPC amplitude unlike thinking about the future of other people. Our findings strengthen the notion of self-knowledge as a grey area between semantic and episodic memory

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely