A multi-agent model for assessing electricity tariffs

This paper describes the framework for modelling a multi-agent approach for assessing dynamic pricing of electricity and demand response. It combines and agent-based model with decision-making data, and a standard load-flow model. The multi-agent model described here represents a tool in investigating not only the relation between different dynamic tariffs and consumer load profiles, but also the change in behaviour and impact on low-voltage electricity distribution networks.The authors acknowledge the contribution of the EPSRC Transforming Energy Demand Through Digital Innovation Programme, grant agreement numbers EP/I000194/1 and EP/I000119/1, to the ADEPT project

Recent advances in low oxidation state aluminium chemistry

Documenting the synthesis and isolation of novel low oxidation state aluminium (Al) compounds, which until recently has seen relatively slow progress over the 30 years since such species were first isolated

Aluminum Amidinates: Insights into Alkyne Hydroboration.

The mechanism of the aluminum-mediated hydroboration of terminal alkynes was investigated using a series of novel aluminum amidinate hydride and alkyl complexes bearing symmetric and asymmetric ligands. The new aluminum complexes were fully characterized and found to facilitate the formation of the (E)-vinylboronate hydroboration product, with rates and orders of reaction linked to complex size and stability. Kinetic analysis and stoichiometric reactions were used to elucidate the mechanism, which we propose to proceed via the initial formation of an Al-borane adduct. Additionally, the most unstable complex was found to promote decomposition of the pinacolborane substrate to borane (BH3), which can then proceed to catalyze the reaction. This mechanism is in contrast to previously reported aluminum hydride-catalyzed hydroboration reactions, which are proposed to proceed via the initial formation of an aluminum acetylide, or by hydroalumination to form a vinylboronate ester as the first step in the catalytic cycle

Towards a framework for testing general relativity with extreme-mass-ratio-inspiral observations

Extreme-mass-ratio-inspiral observations from future space-based gravitational-wave detectors such as LISA will enable strong-field tests of general relativity with unprecedented precision, but at prohibitive computational cost if existing statistical techniques are used. In one such test that is currently employed for LIGO black hole binary mergers, generic deviations from relativity are represented by N deformation parameters in a generalized waveform model; the Bayesian evidence for each of its 2N combinatorial submodels is then combined into a posterior odds ratio for modified gravity over relativity in a null-hypothesis test. We adapt and apply this test to a generalized model for extreme-mass-ratio inspirals constructed on deformed black hole spacetimes, and focus our investigation on how computational efficiency can be increased through an evidence-free method of model selection. This method is akin to the algorithm known as product-space Markov chain Monte Carlo, but uses nested sampling and improved error estimates from a rethreading technique. We perform benchmarking and robustness checks for the method, and find order-of-magnitude computational gains over regular nested sampling in the case of synthetic data generated from the null model.AJKC acknowledges support from the Jet Propulsion Laboratory (JPL) Research and Technology Development programme. SH thanks the Science and Technology Facilities Council (STFC) for financial support. CJM acknowledges financial support provided under the European Union’s H2020 ERC Consolidator Grant ‘Matter and strong-field gravity: New frontiers in Einstein’s theory’ grant agreement no. MaGRaTh646597, and networking support by the COST Action CA16104. Parts of this work were performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from STFC. Parts of this work were also undertaken on the COSMOS Shared Memory system at DAMTP, University of Cambridge operated on behalf of the STFC DiRAC HPC Facility; this equipment is funded by BIS National E-infrastructure capital grant ST/J005673/1 and STFC grants ST/H008586/1, ST/K00333X/1. Parts of this work were also carried out at JPL, California Institute of Technology, under a contract with the National Aeronautics and Space Administration

Impact of the Covid-19 Pandemic on ALS Care in the UK

The Covid-19 pandemic has impacted healthcare. Our aim was to identify how amyotrophic lateral sclerosis (ALS) care in the UK has been affected by the pandemic by exploring the experiences of people living with ALS (plwALS), healthcare professionals (HCPs) working with plwALS, and ALS care centers. Three surveys were carried out to explore the experiences of plwALS, HCPs and ALS care centers during the pandemic. Quantitative data were analyzed using descriptive and inferential statistics and triangulated with the qualitative data which were analyzed thematically. Responses from 53 plwALS, 73 HCPs and 23 ALS care centers were analyzed. Five main themes were identified: keeping safe, losses, negative emotions, delivering care and alternative care delivery in a pandemic. PlwALS and HCPs felt that care was sub-optimal as a result of the pandemic. Changes to care included longer waiting times and face-to-face appointments being canceled or replaced by virtual consultations. While benefits of virtual consultations were reported, concerns were raised about incomplete clinical assessments and the disruption of provision of testing and interventions. ALS care has changed as a result of the pandemic. Patients have had a lack of face-to-face contact with HCPs and have experienced delays to investigations and treatments. PlwALS and HCPs were concerned about the impact of this change, but the long-term implications remain unclear. We propose recommendations for HCPs caring for plwALS, that will promote continuity of evidenced based care in the context of a pandemic

Development of Iron Speciation Reference Materials for Palaeoredox Analysis

The development and application of geochemical techniques to identify redox conditions in modern and ancient aquatic environments has intensified over recent years. Iron (Fe) speciation has emerged as one of the most widely used procedures to distinguish different redox regimes in both the water column and sediments, and is the main technique used to identify oxic, ferruginous (anoxic, Fe(II) containing) and euxinic (anoxic, sulfidic) water column conditions. However, an international sediment reference material has never been developed. This has led to concern over the consistency of results published by the many laboratories that now utilise the technique. Here, we report an interlaboratory comparison of four Fe speciation reference materials for palaeoredox analysis, which span a range of compositions and reflect deposition under different redox conditions. We provide an update of extraction techniques used in Fe speciation, and assess the effects of both test portion mass, and the use of different analytical procedures, on the quantification of different Fe fractions in sedimentary rocks. While atomic adsorption spectroscopy and inductively coupled plasma‐optical emission spectrometry produced comparable Fe measurements for all extraction stages, the use of ferrozine consistently underestimated Fe in the extraction step targeting mixed ferrous‐ferric minerals such as magnetite. We therefore suggest that the use of ferrozine is discontinued for this Fe pool. Finally, we report the combined data of four independent Fe speciation laboratories to characterise the Fe speciation composition of the reference materials. These reference materials are available to the community to provide an essential validation of in‐house Fe speciation measurements

Delayed self-recognition in children with autism spectrum disorder.

This study aimed to investigate temporally extended self-awareness (awareness of one’s place in and continued existence through time) in autism spectrum disorder (ASD), using the delayed self-recognition (DSR) paradigm (Povinelli et al., Child Development 67:1540–1554, 1996). Relative to age and verbal ability matched comparison children, children with ASD showed unattenuated performance on the DSR task, despite showing significant impairments in theory-of-mind task performance, and a reduced propensity to use personal pronouns to refer to themselves. The results may indicate intact temporally extended self-awareness in ASD. However, it may be that the DSR task is not an unambiguous measure of temporally extended self-awareness and it can be passed through strategies which do not require the possession of a temporally extended self-concept

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations

Variability in Isotope Discrimination Factors in Coral Reef Fishes: Implications for Diet and Food Web Reconstruction

Interpretation of stable isotope ratios of carbon and nitrogen (δ13C and δ15N) is generally based on the assumption that with each trophic level there is a constant enrichment in the heavier isotope, leading to diet-tissue discrimination factors of 3.4‰ for 15N (ΔN) and ∼0.5‰ for 13C (ΔC). Diet-tissue discrimination factors determined from paired tissue and gut samples taken from 152 individuals from 26 fish species at Ningaloo Reef, Western Australia demonstrate a large amount of variability around constant values. While caution is necessary in using gut contents to represent diet due to the potential for high temporal variability, there were significant effects of trophic position and season that may also lead to variability in ΔN under natural conditions. Nitrogen enrichment increased significantly at higher trophic levels (higher tissue δ15N), with significantly higher ΔN in carnivorous species. Changes in diet led to significant changes in ΔN, but not tissue δ15N, between seasons for several species: Acanthurus triostegus, Chromis viridis, Parupeneus signatus and Pomacentrus moluccensis. These results confirm that the use of meta-analysis averages for ΔN is likely to be inappropriate for accurately determining diets and trophic relationships using tissue stable isotope ratios. Where feasible, discrimination factors should be directly quantified for each species and trophic link in question, acknowledging the potential for significant variation away from meta-analysis averages and, perhaps, controlled laboratory diets and conditions