A quantitative probabilistic investigation into the accumulation of rounding errors in numerical ODE solution.

We examine numerical rounding errors of some deterministic solvers for systems of ordinary differential equations (ODEs) from a probabilistic viewpoint. We show that the accumulation of rounding errors results in a solution which is inherently random and we obtain the theoretical distribution of the trajectory as a function of time, the step size and the numerical precision of the computer. We consider, in particular, systems which amplify the effect of the rounding errors so that over long time periods the solutions exhibit divergent behaviour. By performing multiple repetitions with different values of the time step size, we observe numerically the random distributions predicted theoretically. We mainly focus on the explicit Euler and fourth order Runge–Kutta methods but also briefly consider more complex algorithms such as the implicit solvers VODE and RADAU5 in order to demonstrate that the observed effects are not specific to a particular method

Synaptic Partner Assignment Using Attentional Voxel Association Networks

Connectomics aims to recover a complete set of synaptic connections within a dataset imaged by volume electron microscopy. Many systems have been proposed for locating synapses, and recent research has included a way to identify the synaptic partners that communicate at a synaptic cleft. We re-frame the problem of identifying synaptic partners as directly generating the mask of the synaptic partners from a given cleft. We train a convolutional network to perform this task. The network takes the local image context and a binary mask representing a single cleft as input. It is trained to produce two binary output masks: one which labels the voxels of the presynaptic partner within the input image, and another similar labeling for the postsynaptic partner. The cleft mask acts as an attentional gating signal for the network. We find that an implementation of this approach performs well on a dataset of mouse somatosensory cortex, and evaluate it as part of a combined system to predict both clefts and connections

Convolutional nets for reconstructing neural circuits from brain images acquired by serial section electron microscopy

Neural circuits can be reconstructed from brain images acquired by serial section electron microscopy. Image analysis has been performed by manual labor for half a century, and efforts at automation date back almost as far. Convolutional nets were first applied to neuronal boundary detection a dozen years ago, and have now achieved impressive accuracy on clean images. Robust handling of image defects is a major outstanding challenge. Convolutional nets are also being employed for other tasks in neural circuit reconstruction: finding synapses and identifying synaptic partners, extending or pruning neuronal reconstructions, and aligning serial section images to create a 3D image stack. Computational systems are being engineered to handle petavoxel images of cubic millimeter brain volumes

Environmental Health: Pest and Solid Waste Management

Presented for World Environmental Health Day, September 26, 2016 in Greenville, North Carolina

A Platform for the Analysis of Qualitative and Quantitative Data about the Built Environment and its Users

There are many scenarios in which it is necessary to collect data from multiple sources in order to evaluate a system, including the collection of both quantitative data - from sensors and smart devices - and qualitative data - such as observations and interview results. However, there are currently very few systems that enable both of these data types to be combined in such a way that they can be analysed side-by-side. This paper describes an end-to-end system for the collection, analysis, storage and visualisation of qualitative and quantitative data, developed using the e-Science Central cloud analytics platform. We describe the experience of developing the system, based on a case study that involved collecting data about the built environment and its users. In this case study, data is collected from older adults living in residential care. Sensors were placed throughout the care home and smart devices were issued to the residents. This sensor data is uploaded to the analytics platform and the processed results are stored in a data warehouse, where it is integrated with qualitative data collected by healthcare and architecture researchers. Visualisations are also presented which were intended to allow the data to be explored and for potential correlations between the quantitative and qualitative data to be investigated

Methanol as a fuel for internal combustion engines

Transportation of people and goods largely relies on the use of fossil hydrocarbons, contributing to global warming and problems with local air quality. There are a number of alternatives to fossil fuels that can avoid a net carbon emission and can also decrease pollutant emissions. However, many have significant difficulty in competing with fossil fuels due to either limited availability, limited energy density, high cost, or a combination of these. Methanol (CH3OH) is one of these alternatives, which was demonstrated in large fleet trials during the 1980s and 1990s, and is currently again being introduced in various places and applications. It can be produced from fossil fuels, but also from biomass and from renewable energy sources in carbon capture and utilization schemes. It can be used in pure form or as a blend component, in internal combustion engines (ICEs) or in direct methanol fuel cells (DMFCs). These features added to the fact it is a liquid fuel, making it an efficient way of storing and distributing energy, make it stand out as one of the most attractive scalable alternatives. This review focuses on the use of methanol as a pure fuel or blend component for ICEs. First, we introduce methanol historically, briefly introduce the various methods for its production, and summarize health and safety of using methanol as a fuel. Then, we focus on its use as a fuel for ICEs. The current data on the physical and chemical properties relevant for ICEs are reviewed, highlighting the differences with fuels such as ethanol and gasoline. These are then related to the research reported on the behaviour of methanol and methanol blends in spark ignition and compression ignition engines. Many of the properties of methanol that are significantly different from those of for example gasoline (such as its high heat of vaporization) lead to advantages as well as challenges. Both are extensively discussed. Methanol's performance, in terms of power output, peak and part load efficiency, and emissions formation is summarized, for so-called flex-fuel engines as well as for dedicated engines. We also briefly touch upon engine hardware changes and material compatibility. Methanol fuel reforming using engine waste heat is discussed, as a potential route towards further increases in efficiency and decreases in emissions. Next to the experimental work, research efforts into modelling the behaviour of methanol as a fuel are also reviewed, including mixture formation, normal and abnormal combustion. Methanol's properties such as high latent heat, fast burning velocity, high knock-resistance and no carbon-to-carbon bonds are shown to leverage engine technology developments such as increased compression ratios, downsizing and dilution; enabling much increased engine efficiencies. Finally, we point out the current gaps in knowledge to indicate which areas future research should be directed at

Methanol as a fuel for internal combustion engines

Transportation of people and goods largely relies on the use of fossil hydrocarbons, contributing to global warming and problems with local air quality. Thereare a number of alternatives to fossil fuels that can avoid a net carbon emission and can also decrease pollutant emissions. However, many have significant difficultyin competing with fossil fuels due to either limited availability, limited energy density, high cost, or a combination of these. Methanol (CH3OH) is one of these alternatives, which was demonstrated inlarge fleet trials during the 1980s and 1990s, and is currently again being introduced in various places and applications. It can be produced from fossil fuels,but also from biomass and from renewable energy sources in carbon capture and utilization schemes. It can be used in pure form or as a blend component, ininternal combustion engines (ICEs) or in direct methanol fuel cells (DMFCs). These features added to the fact it is a liquid fuel, making it an efficient way of storing and distributing energy, make it stand out as one of the most attractive scalable alternatives. This review focuses on the use of methanol as a pure fuel or blend componentfor ICEs. First, we introduce methanol historically, briefly introduce the various methods for its production, and summarize health and safety of using methanolas a fuel. Then, we focus on its use as a fuel for ICEs. The current data on the physical and chemical properties relevant for ICEs are reviewed, highlighting the differences with fuels such as ethanol and gasoline. These are then related to the research reported on the behaviour of methanol and methanol blendsin spark ignition and compression ignition engines. Many of the properties of methanol that are significantly different from those of for example gasoline (suchas its high heat of vaporization) lead to advantages as well as challenges. Both are extensively discussed.Methanol’s performance, in terms of power output, peak and part load efficiency, and emissions formation is summarized, for so-called flex-fuel engines as well as for dedicated engines. We also briefly touch upon engine hardware changes and material compatibility. Methanol fuel reforming using engine waste heat is discussed, as a potential route towards further increases in efficiency anddecreases in emissions. Next to the experimental work, research efforts into modelling the behaviour of methanol as a fuel are also reviewed, including mixtureformation, normal and abnormal combustion. Methanol’s properties such as high latent heat, fast burning velocity, high knock-resistance and no carbonto-carbonbonds are shown to leverage engine technology developments such as increased compression ratios, downsizing and dilution; enabling much increasedengine efficiencies. Finally, we point out the current gaps in knowledge to indicate which areas future research should be directed at