Ground State Spin Logic

Designing and optimizing cost functions and energy landscapes is a problem encountered in many fields of science and engineering. These landscapes and cost functions can be embedded and annealed in experimentally controllable spin Hamiltonians. Using an approach based on group theory and symmetries, we examine the embedding of Boolean logic gates into the ground state subspace of such spin systems. We describe parameterized families of diagonal Hamiltonians and symmetry operations which preserve the ground state subspace encoding the truth tables of Boolean formulas. The ground state embeddings of adder circuits are used to illustrate how gates are combined and simplified using symmetry. Our work is relevant for experimental demonstrations of ground state embeddings found in both classical optimization as well as adiabatic quantum optimization.Comment: 6 pages + 3 pages appendix, 7 figures, 1 tabl

When do young birds disperse? : Tests from studies of golden eagles in Scotland

Peer reviewedPublisher PD

Design requirements for laminar airflow clean rooms and devices

Laminar airflow and airborne contamination control concepts with clean room specifications and laminar flow facility design

Simulation of Classical Thermal States on a Quantum Computer: A Transfer Matrix Approach

We present a hybrid quantum-classical algorithm to simulate thermal states of a classical Hamiltonians on a quantum computer. Our scheme employs a sequence of locally controlled rotations, building up the desired state by adding qubits one at a time. We identify a class of classical models for which our method is efficient and avoids potential exponential overheads encountered by Grover-like or quantum Metropolis schemes. Our algorithm also gives an exponential advantage for 2D Ising models with magnetic field on a square lattice, compared with the previously known Zalka's algorithm.Comment: 5 pages, 3 figures; (new in version 2: added new figure, title changed, rearranged paragraphs

Intelligent integrated maintenance for wind power generation

A novel architecture and system for the provision of Reliability Centred Maintenance (RCM) for offshore wind power generation is presented. The architecture was developed by conducting a bottom-up analysis of the data required to support RCM within this specific industry, combined with a top-down analysis of the required maintenance functionality. The architecture and system consists of three integrated modules for Intelligent Condition Monitoring, Reliability and Maintenance Modelling, and Maintenance Scheduling that provide a scalable solution for performing dynamic, efficient and cost effective preventative maintenance management within this extremely demanding renewable energy generation sector. The system demonstrates for the first time, the integration of state-of-the-art advanced mathematical techniques: Random Forests, Dynamic Bayesian Networks, and Memetic Algorithms in the development of an intelligent autonomous solution. The results from the application of the intelligent integrated system illustrated the automated detection of faults within a wind farm consisting of over 100 turbines, the modelling and updating of the turbines’ survivability and creation of a hierarchy of maintenance actions, and the optimising of the maintenance schedule with a view to maximising the availability and revenue generation of the turbines

Methodology for the comparative assessment of the Satellite Power System (SPS) and alternative technologies

The energy systems concerned are the satellite power system, several coal technologies, geothermal energy, fission, fusion, terrestrial solar systems, and ocean thermal energy conversion. Guidelines are suggested for the characterization of these systems, side-by-side analysis, alternative futures analysis, and integration and aggregation of data. A description of the methods for assessing the technical, economic, environmental, societal, and institutional issues surrounding the development of the selected energy technologies is presented

Supporting 'design for reuse' with modular design

Engineering design reuse refers to the utilization of any knowledge gained from the design activity to support future design. As such, engineering design reuse approaches are concerned with the support, exploration, and enhancement of design knowledge prior, during, and after a design activity. Modular design is a product structuring principle whereby products are developed with distinct modules for rapid product development, efficient upgrades, and possible reuse (of the physical modules). The benefits of modular design center on a greater capacity for structuring component parts to better manage the relation between market requirements and the designed product. This study explores the capabilities of modular design principles to provide improved support for the engineering design reuse concept. The correlations between modular design and 'reuse' are highlighted, with the aim of identifying its potential to aid the little-supported process of design for reuse. In fulfilment of this objective the authors not only identify the requirements of design for reuse, but also propose how modular design principles can be extended to support design for reuse

Altered functional connectivity in lesional peduncular hallucinosis with REM sleep behavior disorder

Brainstem lesions causing peduncular hallucinosis (PH) produce vivid visual hallucinations occasionally accompanied by sleep disorders. Overlapping brainstem regions modulate visual pathways and REM sleep functions via gating of thalamocortical networks. A 66-year-old man with paroxysmal atrial fibrillation developed abrupt–onset complex visual hallucinations with preserved insight and violent dream enactment behavior. Brain MRI showed restricted diffusion in the left rostrodorsal pons suggestive of an acute ischemic stroke. REM sleep behavior disorder (RBD) was diagnosed on polysomnography. We investigated the integrity of ponto-geniculate-occipital circuits with seed-based resting-state functional connectivity MRI (rs-fcMRI) in this patient compared to 46 controls. Rs-fcMRI revealed significantly reduced functional connectivity between the lesion and lateral geniculate nuclei (LGN), and between LGN and visual association cortex compared to controls. Conversely, functional connectivity between brainstem and visual association cortex, and between visual association cortex and prefrontal cortex (PFC) was significantly increased in the patient. Focal damage to the rostrodorsal pons is sufficient to cause RBD and PH in humans, suggesting an overlapping mechanism in both syndromes. This lesion produced a pattern of altered functional connectivity consistent with disrupted visual cortex connectivity via de-afferentation of thalamocortical pathways

The contribution of diet and genotype to iron status in women:a classical twin study

This is the first published report examining the combined effect of diet and genotype on body iron content using a classical twin study design. The aim of this study was to determine the relative contribution of genetic and environmental factors in determining iron status. The population was comprised of 200 BMI- and age-matched pairs of MZ and DZ healthy twins, characterised for habitual diet and 15 iron-related candidate genetic markers. Variance components analysis demonstrated that the heritability of serum ferritin (SF) and soluble transferrin receptor was 44% and 54% respectively. Measured single nucleotide polymorphisms explained 5% and selected dietary factors 6% of the variance in iron status; there was a negative association between calcium intake and body iron (p = 0.02) and SF (p = 0.04)

Developing a model to estimate the potential impact of municipal investment on city health

This article summarizes a process which exemplifies the potential impact of municipal investment on the burden of cardiovascular disease (CVD) in city populations. We report on Developing an evidence-based approach to city public health planning and investment in Europe (DECiPHEr), a project part funded by the European Union. It had twin objectives: first, to develop and validate a vocational educational training package for policy makers and political decision takers; second, to use this opportunity to iterate a robust and user-friendly investment tool for maximizing the public health impact of 'mainstream' municipal policies, programs and investments. There were seven stages in the development process shared by an academic team from Sheffield Hallam University and partners from four cities drawn from the WHO European Healthy Cities Network. There were five iterations of the model resulting from this process. The initial focus was CVD as the biggest cause of death and disability in Europe. Our original prototype 'cost offset' model was confined to proximal determinants of CVD, utilizing modified 'Framingham' equations to estimate the impact of population level cardiovascular risk factor reduction on future demand for acute hospital admissions. The DECiPHEr iterations first extended the scope of the model to distal determinants and then focused progressively on practical interventions. Six key domains of local influence on population health were introduced into the model by the development process: education, housing, environment, public health, economy and security. Deploying a realist synthesis methodology, the model then connected distal with proximal determinants of CVD. Existing scientific evidence and cities' experiential knowledge were 'plugged-in' or 'triangulated' to elaborate the causal pathways from domain interventions to public health impacts. A key product is an enhanced version of the cost offset model, named Sheffield Health Effectiveness Framework Tool, incorporating both proximal and distal determinants in estimating the cost benefits of domain interventions. A key message is that the insights of the policy community are essential in developing and then utilising such a predictive tool