A case study on the impact of fixed input parameter values in the modelling of indoor overheating

Global efforts to reduce greenhouse gas emissions from buildings while also improving their environmental resilience have intensified. These efforts are often supported by building stock models which can inform policymakers on the impact of policies on energy consumption, greenhouse gas emissions and the indoor environment. The input values of such models are commonly informed by reference tables, which can result in inaccurate specification and incomplete representation of the distribution of possible values. In this modelling case study of a semi-detached dwelling archetype, the influence of using a reference U-value (2.1 W/(m2K)) for solid walls in England on heat-related mortality rate is compared to a probabilistic specification based on empirical evidence (median = 1.7W/(m2K)). Using the theoretical reference U-value generally resulted in a lower indoor overheating risk compared to the use of the empirically derived U-values pre-retrofit, but a larger increase in heat-related mortality rate following internal wall insulation (1.20%) than the use of the empirical median (0.94%, 95 % Confidence Interval = 0.87–0.99 %). This highlights the potentially significant implications of using fixed reference values. Future work will employ this probabilistic framework on multiple influential parameters

The effect of sampling techniques used in the multiconfigurational Ehrenfest method

In this paper, we compare and contrast basis set sampling techniques recently developed for use in the ab initio multiple cloning method, a direct dynamics extension to the multiconfigurational Ehrenfest approach, used recently for the quantum simulation of ultrafast photochemistry. We demonstrate that simultaneous use of basis set cloning and basis function trains can produce results which are converged to the exact quantum result. To demonstrate this, we employ these sampling methods in simulations of quantum dynamics in the spin boson model with a broad range of parameters and compare the results to accurate benchmarks

Identifying key experience-related differences in over-ground manual wheelchair propulsion biomechanics

OBJECTIVE: The purpose of this study was to investigate technique differences between expert and novice manual wheelchair users during over-ground wheelchair propulsion. METHOD: Seven experts (spinal cord injury level between T5 and L1) and six novices (non-wheelchair users) pushed a manual wheelchair over level ground, a 2.5% cross slope and up a 6.5% incline (7.2 m length) and 12% incline (1.5 m length). Push rim kinetics, trunk and shoulder kinematics and muscle activity level were measured. RESULTS: During the level and cross slope tasks, the experts completed the tasks with fewer pushes by applying a similar push rim moment over a greater push arc, demonstrating lower muscle activity. During the incline tasks, the experts required fewer pushes and maintained a greater average velocity, generating greater power by applying a similar push rim moment over a greater push arc with greater angular velocity, demonstrating greater trunk flexion and higher shoulder muscle activity. CONCLUSIONS: This study identifies experience-related differences during over-ground manual wheelchair propulsion. These differences are particularly evident during incline propulsion, with the experts generating significantly greater power to maintain a higher velocity

Modelling and monitoring tools to evaluate the Urban Heat Island's contribution to the risk of indoor overheating

The growth of cit ies increases urban surface areas and anthropogenic heat generation, causing an Urban Heat Island (UHI) effect. In the UK , UHI effects may cause positive (winter) and negative (summer) health , comfort and energy consumption consequences . With the increasing focus on climate change - related heat exposure and consequent increased mortality risk, there is a need to better investigate the UHI during hot seasons. This paper reviews the current literature regarding UHI characterisation using monitoring, modelling, and remote sensing approaches, their limitations, and applications in building simulation and population heat exposure models . Ongoing and future research is briefly introduced in which downscaling techniques are proposed that provide higher temporal and spatial information to assess and locate heat - associated health risk in London

Phase I/II Clinical Trials Using Gene-Modified Adult Hematopoietic Stem Cells for HIV: Lessons Learnt

Gene therapy for individuals infected with HIV has the potential to provide a once-only treatment that will act to reduce viral load, preserve the immune system, and mitigate cumulative toxicities associated with highly active antiretroviral therapy (HAART). The authors have been involved in two clinical trials (phase I and phase II) using gene-modified adult hematopoietic stem cells (HSCs), and these are discussed as prototypic trials within the general field of HSC gene therapy trials for HIV. Taken as a group these trials have shown (i) the safety of both the procedure and the anti-HIV agents themselves and (ii) the feasibility of the approach. They point to the requirement for (i) the ability to transduce and infuse as many as possible gene-containing HSC and/or (ii) high engraftment and in vivo expansion of these cells, (iii) potentially increased efficacy of the anti-HIV agent(s) and (iv) automation of the cell processing procedure

Modelling population exposure to high indoor temperatures under changing climates, housing conditions, and urban environments in England

: The exposure of an individual to heat during hot weather depends on several factors including local outdoor temperatures and possible Urban Heat Island (UHI) effects, the thermal performance of the building they inhabit, and any actions that they are able to take in order to modify the indoor thermal conditions. There is an increasing body of research that seeks to understand how housing, UHI, and occupant profiles may alter the risk of mortality during hot weather. Housing overheating models have been of particular interest due to the amount of time spent indoors and the need to improve the energy efficiency of the UK housing stock. A number of housing overheating models have been created in order to understand how changes to the building stock and climate may alter heat exposure and risks of heatrelated mortality. We briefly describe the development of a metamodel – a model derived from the outputs of EnergyPlus dynamic thermal simulation models of building variants – and its application to a housing stock model representative of the West Midlands, UK. We model the stock under a ‘current’ scenario, as described by the 2010-2011 English Housing Survey, and then following a full energy-efficient building fabric retrofit or the installation of external window shutters. Initial results indicate a wide range of overheating risks inside dwelling variants in Birmingham, with flats and bungalows most vulnerable to overheating, and detached dwellings least vulnerable. Modelling of the full retrofit of buildings indicated that the stock would experience an overall increase in overheating, while external shutters were able to decrease overheating significantly

A participatory process for modelling green infrastructure implementation in London

Cities face the interlinked challenges of transforming environmental quality, sustainability, population health and health equity. There is increasing interest in green infrastructure in connection with these challenges. In order to go beyond an understanding of the effects of green infrastructure and develop an understanding of how policymakers should think about it, we need to capture potential interactions and be aware of possible unintended consequences. In our research, we applied a systems-thinking approach: integrating participatory engagements, qualitative system dynamics modelling, and an assessment framework in order to address the challenge. This allowed us to see multiple dynamics between the prioritisation of policymakers, different types of green infrastructure, and environmental and health outcomes. It also made us ask different and more integrated questions, and suggested a methodology for addressing the challenge of transforming cities

IRF1 (interferon regulatory factor 1)

Review on IRF1 (interferon regulatory factor 1), with data on DNA, on the protein encoded, and where the gene is implicated

Modelling Long-Term Urban Temperatures with Less Training Data: A Comparative Study Using Neural Networks in the City of Madrid

In the last decades, urban climate researchers have highlighted the need for a reliable provision of meteorological data in the local urban context. Several efforts have been made in this direction using Artificial Neural Networks (ANN), demonstrating that they are an accurate alternative to numerical approaches when modelling large time series. However, existing approaches are varied, and it is unclear how much data are needed to train them. This study explores whether the need for training data can be reduced without overly compromising model accuracy, and if model reliability can be increased by selecting the UHI intensity as the main model output instead of air temperature. These two approaches were compared using a common ANN configuration and under different data availability scenarios. Results show that reducing the training dataset from 12 to 9 or even 6 months would still produce reliable results, particularly if the UHI intensity is used. The latter proved to be more effective than the temperature approach under most training scenarios, with an average RMSE improvement of 16.4% when using only 3 months of data. These findings have important implications for urban climate research as they can potentially reduce the duration and cost of field measurement campaigns