On the relationship of congruence closureand unification

Congruence closure is a fundamental operation for symbolic computation. Unification closureis defined as its directional dual, i.e., on the same inputs but top-down as opposed to bottom-up. Unifying terms is another fundamental operation for symbolic computation and is commonly computed using unification closure. We clarify the directional duality by reducing unification closure to a special form of congruence closure. This reduction reveals a correspondence between repeated variables in terms to be unified and equalities of monadic ground terms. We then show that: (1) single equality congruence closure on a directed acyclic graph, and (2) acyclic congruence closure of a fixed number of equalities, are in the parallel complexity class NC. The directional dual unification closures in these two cases are known to be log-space complete for PTIME. As a consequence of our reductions we show that if the number of repeated variables in the input terms is fixed, then term unification can be performed in NC; this extends the known parallelizable cases of term unification. Using parallel complexity we also clarify the relationship of unification closure and the testing of deterministic finite automata for equivalence

Driving success towards zero carbon energy targets for UK's Local Authorities

This paper draws on three case studies which show feasible and economic results in meeting net zero carbon emissions targets through Smart Local Energy Systems (SLES) in different localities across England, exploring opportunities to utilise waste heat from industry. They are based on the GreenSCIES model for which the blueprint was developed in London, Study 1. It consists of a fifth generation (5G) ambient loop district heat network using waste heat from a data centre, integrated with electric vehicle charging, storage and solar PV. The network includes decentralised heat pumps and allows for (i) heat sharing between buildings and (ii) applications for heat recovery from local sources. Study 2 is based on a heat network with waste heat from a foundry and some cooling supply and heat storage in the aquifer. Study 3 explored waste heat from a glassworks and considered mine workings for providing heat storage. These SLES projects illustrate how to integrate local waste heat sources in 3G and 4G heat networks, adapting the original GreenSCIES concept, providing pathways towards net zero carbon for a diverse range of urban locations with different waste heat sources, and further demonstrate the importance of collaboration between researchers, local government and industry

Ambient loop district heating and cooling networks with integrated mobility, power and interseasonal storage

This paper describes a heat pump investigation for GreenSCIES (GS), a fifth Generation district heating and cooling (5DHC) network in Islington, London. The paper describes the GreenSCIES concept integrating Mobility, Power and Heat into a Smart Local Energy System (SLES). At the heart of the system is an ultra-low temperature ambient loop network, which permits bi-directional flow within the pipes to allow energy exchange between heating and cooling customers at different times and in different locations, depending on where demand is at any given time. An existing data centre provides the primary source of waste heat for the scheme. Heat pumps in distributed energy centres are utilised to amplify the temperature of the ambient loop to deliver heat in connected buildings. The energy centres integrate heat pumps with building-mounted solar photovoltaic (PV) systems and electric vehicle (EV) charging points. The paper provides an overview of the integrated SLES concept, focussing on the heat pump selection and the short and long-term thermal storage options designed for the scheme. The results show that even the smaller constructible ‘New River’ scheme will save 5,000 tons of CO2e annually. This will tend to 100% as the grid decarbonise further. Therefore, the GS SLES concept applied to urban areas could deliver significant carbon emission savings in the UK and elsewhere. Practical application: Project GreenSCIES, is a detailed design study to develop a Smart, Local Energy System (SLES) for a large community in the London Borough of Islington. Our consortium have developed an innovative SLES concept, centred around a fifth generation district heating and cooling network. The GS ambient loop systems have negligible losses and much greater efficiencies than traditional district heat networks. As recognised by the UK Government’s Heat and Buildings Strategy, ambient loop systems should be considered where large-scale neighbourhood regeneration occurs. The proposed SLES concept applied to wider urban areas could deliver significant carbon emission savings in the UK

The Importance of Heat Pump COP in the Economics of 5th Generation District Heating and Cooling Networks

This paper describes the investigation of heat pumps for GreenSCIES, a 5th Generation heat network in Islington, London. The paper describes the GreenSCIES concept integrating Mobility, Power and Heat into a local energy system. At the heart of the system is a 5th generation heat network, which utilises an ambient heat network to capture secondary heat and share heat between different applications. The GreenSCIES network, technology utilised and buildings connected are described. Heat pumps are used to amplify the temperature of the ambient loop to deliver heat at the required temperature in connected buildings. A number of different heat pumps using different refrigerants and configurations were appraised in this study. This considered the performance, safety, environmental impact, operational and capital expenditure point of view. The study shows the importance of heat pump COP on the economics of operating the system and suggests innovative series arrangements in order to improve performance and economics

GEM-E3 Model Documentation

The computable general equilibrium model GEM-E3 has been used in a large set of climate policy applications supporting Commission policy proposals during the last decade, as well as in other environmental and economic policy areas. It can be considered a multi-purpose macroeconomic model, designed to estimate the effects of sector-specific policies on the economy as a whole. The main purpose of this publication is to provide extensive documentation of the model's equations and its underlying databases, in order to offer to the broader audience an accurate description of the model characteristics.JRC.J.1-Economics of Climate Change, Energy and Transpor

GreenSCIES – Green Smart Community Integrated Energy Systems – Integration with Data Centres

The GreenSCIES project aims to deliver low carbon, affordable energy through a novel smart energy system that connects flexible electricity demands such as heat pumps and electric vehicles to intermittent renewable energy sources such as solar power. This paper presents the results of the feasibility study of a 5th generation district mobility, power and heat network in the London Borough of Islington. The smart network facilitates the transition to electric vehicles and vehicle-to-grid supply to make the most of intermittent renewable energy and ensure end-users always get the best tariff. Heating and cooling are provided by heat pumps in buildings connected to a local network, which integrates thermal energy storage and waste heat recovered from local datacentres. Artificial intelligence underpins the system optimisation and demand side response. Low carbon heating and cooling is achieved by sharing heat between buildings and by shifting the timing of their demand to off-peak cheaper electricity; this requires a sophisticated control system and thermal energy storage. The feasibility study also worked with key stakeholders to understand the views of end-users and others in the supply chain. The role of key thermal energy providers such as Transport for London and Data Centres is fundamental. The preliminary results indicate that the smart network can deliver up to 25% reduction on energy bills and 80% CO2 savings compared to a baseline scenario with gas boilers, chillers and grid electricity. As the electricity grid decarbonises further it is forecasted that the network will tend to net zero carbon before 2050. The GreenSCIES concept is suitable to be replicated throughout the country and has the potential to become a world-leading example

Expressiveness of Temporal Query Languages: On the Modelling of Intervals, Interval Relationships and States

Storing and retrieving time-related information are important, or even critical, tasks on many areas of Computer Science (CS) and in particular for Artificial Intelligence (AI). The expressive power of temporal databases/query languages has been studied from different perspectives, but the kind of temporal information they are able to store and retrieve is not always conveniently addressed. Here we assess a number of temporal query languages with respect to the modelling of time intervals, interval relationships and states, which can be thought of as the building blocks to represent and reason about a large and important class of historic information. To survey the facilities and issues which are particular to certain temporal query languages not only gives an idea about how useful they can be in particular contexts, but also gives an interesting insight in how these issues are, in many cases, ultimately inherent to the database paradigm. While in the area of AI declarative languages are usually the preferred choice, other areas of CS heavily rely on the extended relational paradigm. This paper, then, will be concerned with the representation of historic information in two well known temporal query languages: it Templog in the context of temporal deductive databases, and it TSQL2 in the context of temporal relational databases. We hope the results highlighted here will increase cross-fertilisation between different communities. This article can be related to recent publications drawing the attention towards the different approaches followed by the Databases and AI communities when using time-related concepts

The midbrain to pons ratio: a simple and specific MRI sign of progressive supranuclear palsy.

MRI-based measurements used to diagnose progressive supranuclear palsy (PSP) typically lack pathologic verification and are not easy to use routinely. We aimed to develop in histologically proven disease a simple measure of the midbrain and pons on sagittal MRI to identify PSP

White matter DNA methylation profiling reveals deregulation of HIP1, LMAN2, MOBP, and other loci in multiple system atrophy

Multiple system atrophy (MSA) is a fatal late-onset neurodegenerative disease. Although presenting with distinct pathological hallmarks, which in MSA consist of glial cytoplasmic inclusions (GCIs) containing fbrillar α-synuclein in oligodendrocytes, both MSA and Parkinson’s disease are α-synucleinopathies. Pathologically, MSA can be categorized into striatonigral degeneration (SND), olivopontocerebellar atrophy (OPCA) or mixed subtypes. Despite extensive research, the regional vulnerability of the brain to MSA pathology remains poorly understood. Genetic, epigenetic and environmental factors have been proposed to explain which brain regions are afected by MSA, and to what extent. Here, we explored for the frst time epigenetic changes in post-mortem brain tissue from MSA cases. We conducted a case–control study, and profled DNA methylation in white mater from three brain regions characterized by severe-to-mild GCIs burden in the MSA mixed subtype (cerebellum, frontal lobe and occipital lobe). Our genome-wide approach using Illumina MethylationEPIC arrays and a powerful cross-region analysis identifed 157 CpG sites and 79 genomic regions where DNA methylation was signifcantly altered in the MSA mixed-subtype cases. HIP1, LMAN2 and MOBP were amongst the most diferentially methylated loci. We replicated these fndings in an independent cohort and further demonstrated that DNA methylation profles were perturbed in MSA mixed subtype, and also to variable degrees in the other pathological subtypes (OPCA and SND). Finally, our comethylation network analysis revealed several molecular signatures (modules) signifcantly associated with MSA (disease status and pathological subtypes), and with neurodegeneration in the cerebellum. Importantly, the co-methylation module having the strongest association with MSA included a CpG in SNCA, the gene encoding α-synuclein. Altogether, our results provide the frst evidence for DNA methylation changes contributing to the molecular processes altered in MSA, some of which are shared with other neurodegenerative diseases, and highlight potential novel routes for diagnosis and therapeutic interventions