The implications of transporting architecture on human health

This is the author accepted manuscript.Where modern buildings are unable to maintain the internal environment to within comfort levels they often rely on mechanical systems to become habitable. This could be due to bad design or putting the building in an environment for which it is not suited. Due to climate change it is likely that all buildings will in effect and time be moved to an environment for which it is not suited. In this work the effects of changes in climate on the internal environment will be explored and an index to define how moveable a construction might be, will be developed.The authors would like to thank the EPSRC for their support [grant ref: EP/J002380/1

A comparison between Gaussian Process emulation and Genetic Algorithms for optimising energy use of buildings

Computing speed has increased greatly over recent years. Building designers can now simulate complex building models in a short time. However, even with short simulation times, building optimisation routines can still take too long for some applications. In this paper, we compare how well genetic algorithms (GAs) and Gaussian process emulation with sequential optimisation (GPESO) optimise a building to minimise the energy use. The GA approach performs a GA routine on an EnergyPlus model and the GPESO technique creates a Gaussian Process emulator (GPE) also based on the EnergyPlus model. The GPESO uses an expected improvement algorithm to sequentially improve the GPE. The results show that the GPESO technique outperforms the GA in terms of minimising the number of simulations required and the solution obtained.This work was supported by the Engineering and Physical Sciences Research Council [EPSRC grant number EP/J002380/1]

Emulating computer models with step-discontinuous outputs using Gaussian processes

In many real-world applications, we are interested in approximating functions that are analytically unknown. An emulator provides a "fast" approximation of such functions relying on a limited number of evaluations. Gaussian processes (GPs) are commonplace emulators due to their properties such as the ability to quantify uncertainty. GPs are essentially developed to emulate smooth, continuous functions. However, the assumptions of continuity and smoothness is unwarranted in many situations. For example, in computer models where bifurcation, tipping points occur in their systems of equations, the outputs can be discontinuous. This paper examines the capacity of GPs for emulating step-discontinuous functions using two approaches. The first approach is based on choosing covariance functions/kernels, namely neural network and Gibbs, that are most appropriate for modelling discontinuities. The predictive performance of these two kernels is illustrated using several examples. The results show that they have superior performance to standard covariance functions, such as the Mat\'ern family, in capturing sharp jumps. The second approach is to transform the input space such that in the new space a GP with a standard kernel is able to predict the function well. A parametric transformation function is used whose parameters are estimated by maximum likelihood.Engineering and Physical Sciences Research Council (EPSRC

Future proofing a building design using history matching inspired level‐set techniques

This is the final version. Available on open access from Wiley via the DOI in this record. How can one design a building that will be sufficiently protected against overheating and sufficiently energy efficient, whilst considering the expected increases in temperature due to climate change? We successfully manage to address this question—greatly reducing a large set of initial candidate building designs down to a small set of acceptable buildings. We do this using a complex computer model, statistical models of said computer model (emulators), and a modification to the history matching calibration technique. This modification tackles the problem of level‐set estimation (rather than calibration), where the goal is to find input settings which lead to the simulated output being below some threshold. The entire procedure allows us to present a practitioner with a set of acceptable building designs, with the final design chosen based on other requirements (subjective or otherwise).Engineering and Physical Sciences Research Council (EPSRC

Creating granular climate zones for future-proof building design in the UK

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Datasets related to this article can be found at https://catalogue.ceda.ac.uk, hosted at the CEDA archive.Climate zones play an important role in promoting climate responsive building design and implementing climate-specific prescriptions in national building standards and regulations. The existing studies on climate zoning are subject to several limitations, i.e. the incapability of distinguishing microclimates and the lack of consideration of climate change. In this research, we propose a two-tiered ensemble clustering method for the identification of granular climate zones using the projections of future climate. The first tier identifies primary climate zones using a combination of climatic features and geographical locations, whereas the second tier identifies distinct local variations within each primary climate zone using the temperature related features. The proposed ensemble clustering model is applied to the UK to create a mapping of granular climate zones for future proofing building design. The method identified 14 distinct primary zones and distinguished microclimates at a range of scales from large urban areas, such as the Greater London Area, to national parks, such as Dartmoor and the Pennines. The identified mapping resolves two major obstacles in the creation and usage of weather data for building performance assessment in the UK, i.e. the lack of guidance for selecting weather files, and the absence of scientific rationale for representing the UK climate using the current 14 locations.Innovate U

La pobreza en Cartagena: un análisis por barrios

En el presente documento se hace un análisis descriptivo de la pobreza urbana enCartagena. El tema se aborda desde dos perspectivas. En la primera, se analiza lapobreza desagregada por los barrios que conforman la cabecera municipal deCartagena. En la segunda, se realiza una comparación de la situaciónsocioeconómica de los habitantes de Cartagena con la de las principales ciudades deColombia. Vale la pena mencionar que este trabajo es pionero no sólo en Cartagenasino en Colombia, en cuanto al nivel de división por barrios al que se analizanindicadores socioeconómicos, tales como la pobreza, el ingreso, los logroseducativos, la migración y el autorreconocimiento racial. Dentro de los principalesresultados se comprobó una focalización espacial de la pobreza en sectoresespecíficos de la ciudad, tales como las laderas del Cerro de la Popa y los barriosaledaños a la Ciénaga de la Virgen. En estas zonas de la ciudad se concentra no sólola población más pobre sino la de menores logros educativos. Otro resultadointeresante, y que está acorde con la literatura internacional, es que en los barrioscartageneros de mayor pobreza existe también una alta proporción de habitantes quese autorreconocen de raza negra.Pobreza urbana, Cartagena, economía regional y urbana

‘Not dead … abandoned’ – a clinical case study of childhood and combat-related trauma

This clinical case study examines inter-subjective processes with a counselling client who presented with symptoms of complex trauma including severe anxiety, low mood, dissociation and suicidality. Therapy lasted 12 months and the ending was unplanned. Psychoanalytic and phenomenological hermeneutic frameworks are drawn on in theorizing the work. From this perspective, loss associated with trauma is conceptualized as relational, as traumatic states threaten psychological organization and the continuing experience of relational ties that are needed for survival. Dissociation is understood as a defensive state that changes the way that temporality is experienced. The client’s capacity for dissociation appeared to have developed in early childhood in response to physical abuse, predisposing him to further ongoing and severe trauma as an adult soldier. There will be a focus on the way that dissociation and enactment in the therapeutic relationship limited the therapist’s capacity to provide the client with inter-subjective regulation of disavowed affect. The client’s unconscious experience of unbearable affect led to a breakdown of the therapeutic relationship and the termination of therapy. Detailed session and supervision notes, and correspondence received from the client were used to evaluate theory and practice links, as well as some methodological aspects of case study research

Feeling at home in an experiential research group: reflections on the research process in collaborative pluralism

This paper presents a set of reflections on the process of conducting a qualitative pluralistic group research project. As our work progressed, we began to spend as much time discussing this group work process as we did focusing on our specific research topic. We begin by giving some background to how we got started and the research study itself as well as saying something about who the group is. We then describe our process and examine how we came to see that what we were doing shared a lot of similarities with forms of pluralistic research. We discuss some of the challenges and opportunities we faced along the way and end with some final thoughts on where we might go next. We argue that it is important to pay close attention to the research process as it plays a crucial role in shaping the insights that can be gained from a piece of research. This paper contributes to the growing literature on reflexivity in qualitative psychology in general and the exploration of the research process in in collaborative pluralistic research designs in particular

Continuous Structural Parameterization: A Proposed Method for Representing Different Model Parameterizations Within One Structure Demonstrated for Atmospheric Convection

Continuous structural parameterization (CSP) is a proposed method for approximating different numerical model parameterizations of the same process as functions of the same grid‐scale variables. This allows systematic comparison of parameterizations with each other and observations or resolved simulations of the same process. Using the example of two convection schemes running in the Met Office Unified Model (UM), we show that a CSP is able to capture concisely the broad behavior of the two schemes, and differences between the parameterizations and resolved convection simulated by a high resolution simulation. When the original convection schemes are replaced with their CSP emulators within the UM, basic features of the original model climate and some features of climate change are reproduced, demonstrating that CSP can capture much of the important behavior of the schemes. Our results open the possibility that future work will estimate uncertainty in model projections of climate change from estimates of uncertainty in simulation of the relevant physical processes. Plain Language Summary Numerical models are used to provide estimates of future weather and climate change. The models contain “parameterizations,” which are algorithms that simulate the effect of processes too small or poorly understood to represent using physical equations. Although they are based as much as possible on physics, parameterizations are a large source of modeling uncertainty because there can be large disagreements on how to best represent a given process. The method and even the variables used by two different parameterizations may differ. It is therefore very difficult to know how different parameterizations cause numerical models to produce different results and whether the parameterizations we have are adequate and span the range of uncertainty concerning our knowledge of the processes they represent. Using the example of small‐scale atmospheric convection linked to rain and thunderstorms, this paper describes a mathematical method for expressing different parameterizations within the same framework. This allows easy but formal mathematical comparison of different parameterizations and gives future work the potential to understand whether our parameterizations perform as they should in conjunction with future observations

What do measures of patient satisfaction with the doctor tell us?

Objective: To gain an understanding of how patient satisfaction (PS) with the doctor (PSD) is conceptualized through an empirical review of how it is currently being measured. The content of PS questionnaire items was examined to (a) determine the primary domains underlying PSD, and (b) summarize the specific doctor-related characteristics and behaviors, and patient-related perceptions, composing each domain. Methods: A scoping review of empirical articles that assessed PSD published from 2000 to November 2013. MEDLINE and PsycINFO databases were searched. Results: The literature search yielded 1726 articles, 316 of which fulfilled study inclusion criteria. PSD was realized in one of four health contexts, with questions being embedded in a larger questionnaire that assessed PS with either: (1) overall healthcare, (2) a specific medical encounter, or (3) the healthcare team. In the fourth context, PSD was the questionnaire's sole focus. Five broad domains underlying PSD were revealed: (1) Communication Attributes; (2) Relational Conduct; (3) Technical Skill/Knowledge; (4) Personal Qualities; and (5) Availability/Accessibility. Conclusions: Careful consideration of measurement goals and purposes is necessary when selecting a PSD measure. Practice implications: The five emergent domains underlying PSD point to potential key areas of physician training and foci for quality assessment