Fluctuations of fitness distributions and the rate of Muller's ratchet

The accumulation of deleterious mutations is driven by rare fluctuations which lead to the loss of all mutation free individuals, a process known as Muller's ratchet. Even though Muller's ratchet is a paradigmatic process in population genetics, a quantitative understanding of its rate is still lacking. The difficulty lies in the nontrivial nature of fluctuations in the fitness distribution which control the rate of extinction of the fittest genotype. We address this problem using the simple but classic model of mutation selection balance with deleterious mutations all having the same effect on fitness. We show analytically how fluctuations among the fittest individuals propagate to individuals of lower fitness and have a dramatically amplified effects on the bulk of the population at a later time. If a reduction in the size of the fittest class reduces the mean fitness only after a delay, selection opposing this reduction is also delayed. This delayed restoring force speeds up Muller's ratchet. We show how the delayed response can be accounted for using a path integral formulation of the stochastic dynamics and provide an expression for the rate of the ratchet that is accurate across a broad range of parameters.Comment: Genetics 201

Optimal Dispatch of Aggregated HVAC Units for Demand Response::An Industry 4.0 Approach

Demand response (DR) involves economic incentives aimed at balancing energy demand during critical demand periods. In doing so DR offers the potential to assist with grid balancing, integrate renewable energy generation and improve energy network security. Buildings account for roughly 40% of global energy consumption. Therefore, the potential for DR using building stock offers a largely untapped resource. Heating, ventilation and air conditioning (HVAC) systems provide one of the largest possible sources for DR in buildings. However, coordinating the real-time aggregated response of multiple HVAC units across large numbers of buildings and stakeholders poses a challenging problem. Leveraging upon the concepts of Industry 4.0, this paper presents a large-scale decentralized discrete optimization framework to address this problem. Specifically, the paper first focuses upon the real-time dispatch problem for individual HVAC units in the presence of a tertiary DR program. The dispatch problem is formulated as a non-linear constrained predictive control problem, and an efficient dynamic programming (DP) algorithm with fixed memory and computation time overheads is developed for its efficient solution in real-time on individual HVAC units. Subsequently, in order to coordinate dispatch among multiple HVAC units in parallel by a DR aggregator, a flexible and efficient allocation/reallocation DP algorithm is developed to extract the cost-optimal solution and generate dispatch instructions for individual units. Accurate baselining at individual unit and aggregated levels for post-settlement is considered as an integrated component of the presented algorithms. A number of calibrated simulation studies and practical experimental tests are described to verify and illustrate the performance of the proposed schemes. The results illustrate that the distributed optimization algorithm enables a scalable, flexible solution helping to deliver the provision of aggregated tertiary DR for HVAC systems for both aggregators and individual customers. The paper concludes with a discussion of future work

Diagnosing coeliac disease: Out with the old and in with the new?

Coeliac disease (CD) is a complex condition resulting from an interplay between genetic and environmental factors. When diagnosing the condition, serological testing and genotyping are useful in excluding CD, although the gold standard of testing is currently histopathological examination of the small intestine. There are drawbacks associated with this form of testing however and because of this, novel forms of testing are currently under investigation. Before we develop completely novel tests though, it is important to ask whether or not we can simply use the data we gather from coeliac patients more effectively and build a more accurate snapshot of CD through statistical analysis of combined metrics. It is clear that not one single test can accurately diagnose CD and it is also clear that CD patients can no longer be defined by discrete classifications, the continuum of patient presentation needs to be recognised and correctly captured to improve diagnostic accuracy. This review will discuss the current diagnostics for CD and then outline novel diagnostics under investigation for the condition. Finally, improvements to current protocols will be discussed with the need for a holistic “snapshot” of CD using a number of metrics simultaneously

From 2-dimensional to 3-dimensional: Overcoming dilemmas in intestinal mucosal interpretation

The purpose of this review is to provide a definitive account of small intestinal mucosal structure and interpretation. The coeliac lesion has been well known, but not well described to date and this review aims to identify the interpretative difficulties which have arisen over time with the histological assessment of coeliac disease. In early coeliac interpretation, there were significant inaccuracies, particularly surrounding intraepithelial lymphocyte counts and the degree of villous flattening which occurred in the tissue. Many of these interpretive pitfalls are still encountered today, increasing the potential for diagnostic errors. These difficulties are mostly due to the fact that stained 2-dimensional sections can never truly represent the 3-dimensional framework of the intestinal tissue under investigation. Therefore, this review offers a critical account occasioned by these 2-dimensional interpretative errors and which, in our opinion, should in general be jettisoned. As a result, we leave a framework regarding the true 3-dimensional knowledge of mucosal structure accrued over the 70-year period of study, and one which is available for future reference

The changing health needs of the UK population

The demographics of the UK population are changing and so is the need for health care. In this Health Policy, we explore the current health of the population, the changing health needs, and future threats to health. Relative to other high-income countries, the UK is lagging on many health outcomes, such as life expectancy and infant mortality, and there is a growing burden of mental illness. Successes exist, such as the striking improvements in oral health, but inequalities in health persist as well. The growth of the ageing population relative to the working-age population, the rise of multimorbidity, and persistent health inequalities, particularly for preventable illness, are all issues that the National Health Service (NHS) will face in the years to come. Meeting the challenges of the future will require an increased focus on health promotion and disease prevention, involving a more concerted effort to understand and tackle the multiple social, environmental, and economic factors that lie at the heart of health inequalities. The immediate priority of the NHS will be to mitigate the wider and long-term health consequences of the COVID-19 pandemic, but it must also strengthen its resilience to reduce the impact of other threats to health, such as the UK leaving the EU, climate change, and antimicrobial resistance

A multi-energy system optimisation software for advance process control using hypernetworks and a micro-service architecture

This paper describes a multi-energy system optimisation software, “Sustainable Energy Management System” (SEMS), developed as part of a Siemens, Greater London Authority and Royal Borough of Greenwich partnership in collaboration with the University of Nottingham, Nottingham Trent University and Imperial College London. The software was developed for application at a social housing estate in Greenwich, London, as part of the Borough’s efforts to retrofit the energy systems and building fabric of its housing stock. Its purpose is to balance energy across vectors and networks through day-ahead forecasting and optimisations that can be interpreted as control outputs for energy plant such as a water source heat pump, district heating pumps and values, power switchgear, gas boilers, a thermal store, electric vehicle chargers and a photovoltaic array. The optimisation objectives are to minimise greenhouse gas emissions and operational cost. The tool uses Hypernetwork Theory based orchestration coupled with a microservice architecture. The distributed nature of the design ensures flexibility and scalability. Currently, microservices have been programmed to forecast domestic heating demand, domestic electricity demand, electric vehicle demand, solar photovoltaic generation, ground temperature, and to run a day-ahead energy balance optimisation. This paper presents the results from both domestic heat and electricity demand forecasting, as well as the overall design and integration of the software with a physical system. The works build on that of O’Dwyer, et al. (2020) who developed a preliminary energy management software and digital twin. Their work acts as a foundation for this real-world commercialisation-ready program that integrates with physical assets