Exploring the effectiveness of the “Go-Along” in promoting citizen engagement Case Study: Resident participation in a social housing complex in Trondheim, Norway

Community participation is an integral part of decision-making processes as it presents clear understandings of the shared perceptions that every stakeholder has of their environment be it social or physical. To ensure maximum citizen engagement various qualitative methods have been implemented amongst which the go-along method has emerged as an immersive method of enquiry. This thesis investigates how the go-along method can engage citizens in planning processes by carrying out a systematic literature review and fieldwork focusing on the go-along method. The review showed that the go-along methods can be beneficial when applied to applied in health and wellbeing studies, student’s behavior in educational institutions, neighborhood studies, area redevelopment plans, etc.; however, few research gaps were identified: no application with a social housing context; recent advanced technology is not fully used; and, no semi-quantitative approach to evaluate the added value of the go-along method. Hence, this study applied the go-along method to investigate how it can engage social housing dwellers in planning processes of Boligstiftelsen. A multi-method approach was used in this study to provide a more comprehensive understanding of the context and to complement other method’s limitations. Four go-alongs, in-situ observations, a sit-down group interview, a focus group and a go-virtually-along were applied. Insta360 EVO, a 360° video camera, was used to film the go-alongs and focus group. The study concludes that the go-along method can engage social housing dwellers in providing basis to translate their desires and insights into valuable input that can support urban planning processes. An essential benefit of applying the go-along method is to gather a wide variety and significant volume of data by engaging even a small sample of participants as shown from the results of the semi-quantitative approach used in this study. The go-along method’s potential is better exploited when used complemented to other traditional methods, such as in conjunction to focus group, in order to overcome its limitations in regard to the exclusion of participants with low or no mobility abilities. The case study demonstrated that technology, such as 360° video cameras, can overcome the method’s limitation of the need to simultaneously take notes and pictures while moving and focusing on the conversation with the participant. The case study demonstrated that the go-along method enhances the interaction researcher-citizens in the planning process by involving the researcher more in the community and making residents more interested in the ongoing research

Physical modelling of epithelia: reverse engineering cell competition in silico

Cell competition is a phenomenon in which less fit cells are removed from a tissue for optimal survival of the host. Competition has been observed in many physiological and pathophysiological conditions, especially in the prevention of tumor development. While there have been extensive population-scale experimental studies of competition, the competitive strategies and their underlying mechanisms in single cells are poorly understood. To date, two main mechanisms of cell competition have been described. Mechanical competition arises when the two competing cell types have different sensitivities to crowding. In contrast, during biochemical competition, signaling occurs at the interface between cell types leading to apoptosis of the loser cells. However, rigorously testing these hypotheses remains challenging due to the difficulty of obtaining sufficient single cell level information to bridge scales to the whole tissue. In this thesis, I present metrics aimed at characterising competition at the single cell level. Then, I demonstrate the development of a multi-layered, cell-scale computational model that I use to gain understanding on the single cell mechanisms that govern mechanical competition and decipher the "rules of the cellular game". After benchmarking cell growth and homeostasis in pure populations, I show that competition emerges when both cell types are included in simulations. I then investigate the impact of each computational parameter on the outcome of cell competition. Intriguingly, the outcome of biochemical competition is controlled by topological entropy between cell types, whereas the outcome of mechanical cell competition is exclusively controlled by differences in energetic potential between cell types. As 90% of cancers arise from epithelia and a number of genetic diseases present symptoms of epithelial fragility, I anticipate that my model of realistic implementation of epithelia will be of use to the biophysics and computational modelling community

Local cellular neighbourhood controls proliferation in cell competition

Cell competition is a quality control mechanism through which tissues eliminate unfit cells. Cell competition can result from short-range biochemical inductions or long-range mechanical cues. However, little is known about how cell-scale interactions give rise to population shifts in tissues, due to the lack of experimental and computational tools to efficiently characterise interactions at the single-cell level. Here, we address these challenges by combining long-term automated microscopy with deep learning image analysis to decipher how single-cell behaviour determines tissue make-up during competition. Using our high-throughput analysis pipeline, we show that competitive interactions between MDCK wild-type cells and cells depleted of the polarity protein scribble are governed by differential sensitivity to local density and the cell-type of each cell's neighbours. We find that local density has a dramatic effect on the rate of division and apoptosis under competitive conditions. Strikingly, our analysis reveals that proliferation of the winner cells is upregulated in neighbourhoods mostly populated by loser cells. These data suggest that tissue-scale population shifts are strongly affected by cellular-scale tissue organisation. We present a quantitative mathematical model that demonstrates the effect of neighbour cell-type dependence of apoptosis and division in determining the fitness of competing cell lines

A probabilistic-based methodology for evaluation of timber facade constructions - The Performance to withstand biodeterioration

Mould and decay are biodeterioration phenomena that jeopardize the integrity, functionality and durability of timber façade constructions. Accounting for them during the design stage is crucial for the prevention of social problems and financial loss, and to ensure a healthy, safe and comfortable interior environment. The design of façade constructions is replete with uncertainties. They are mainly related to the representation of the outdoor and indoor climate, physical parameters of the materials properties and geometries, and modelling of complex physical phenomena. Current design approaches fail to account for these uncertainties, especially in representing the outdoor climate and microbial growth. The aim of this work is to develop and apply a probabilistic-based methodology, which evaluates the performance of timber façade constructions to withstand biodeterioration and accounts for the involved uncertainties. The time series analysis according to autoregressive-moving-average models is applied to develop the stochastic model representing the outdoor climate. This technique identifies mathematical expressions that can generate probable patterns of the weather data in a time series containing plausible sequences, frequencies and correlations, future trends of the climate and can be long enough to resemble the expected service life. The temperature-dependent thermal conductivity of the insulation material is investigated by carrying out lab measurements, and subsequently, a stochastic model is developed to represent this property. Deficiencies, considering penetration of wind-driven rain, are accounted for and represented by different moisture sources. Moreover, the development of criteria and models representing mould growth in wood-based materials are investigated by carrying out a systematic literature review. Subsequently, three mould models are selected to derive the mould growth outcome as a mixture of their distribution to account for their competencies and diminishing their limitations in representing mould. This outline derives the likelihoods of potential levels of mould growth; hence, facilitates their association to the corresponding consequences adapted from the case study at hand. Uncertainty and sensitivity analysis methods are performed to quantify the ranges of the output, the likelihood of each outcome and to evaluate the significance of key contributors to output uncertainty. The methodology is applied to evaluate traditional and modern façade constructions. The results prove that the probabilistic-based methodology enables a more systematic approach to the evaluation of façade constructions. It accounts for the involved uncertainties, provides a clear association of microbial growth and its likelihood, and enables the identification and significance of the dominant parameters; hence, it delivers a more comprehensive representation to evaluate construction performance. The methodology can facilitate the development of cost-optimisation and risk-based inspection planning methodologies, and enable the upgrading of current codes and standards. Keywords: mould; decay; façade; probabilistic; uncertainty; sensitivity analysis.Digital full text not availabl

Performance evaluation of a highly insulated wall to withstand mould

In this paper, the performance to withstand mould growth of a highly insulated wall is evaluated by applying a probabilistic-based methodology that accounts for the involved uncertainties and investigates their significance. A sensitivity analysis according to the Morris method is conducted to understand the influence of each parameter and simplify the system representation. Deficiencies in terms of moisture and air leakages are accounted for. The mould growth outcome is evaluated by integrating different mould models and assessment criteria. The study demonstrates that a probabilistic-based methodology enables a more systematic approach to evaluate wall constructions since it accounts for the involved uncertainties, provides a clear association of the microbial growth to its likelihood, and enables the identification and significance of the dominant parameters; hence, it delivers a more comprehensive assessment of a building envelope

Montana Kaimin, September 17, 2003

Student newspaper of the University of Montana, Missoula.https://scholarworks.umt.edu/studentnewspaper/5781/thumbnail.jp

Design for Disassembly: A systematic scoping review and analysis of built structures Designed for Disassembly

A systematic scoping review was performed to map literature in the field of Design for Disassembly (DfD) in the Architecture, Engineering, and Construction industry and identify existing built DfD structures to compare the current DfD practice and research front. Online scientific databases and architecture magazines were searched and almost 470 journal and conference articles, grey literature, and online magazine articles were selected for scope mapping and case study analysis. Based on the gathered literature the key research focus areas were identified as follows: analysis (barriers identification, standard development, literature review, feasibility study, ethical issues), frameworks, Building Information Modelling (BIM), tool development (indicator, method, technology), and case study analysis (concepts, structures, connections). Qualitative and quantitative data for 151 built DfD structure examples identified in the literature were collected and analysed to give an overview of the current practices and trends in the AEC industry. The DfD building was found to have various definitions and implementations and 50% of the built DfD structures have area below 300 m . The structure in 75% of the identified existing DfD buildings is made of timber while research literature into enabling technology is dominated by the development of the connections for reinforced concrete and hybrid concrete–steel structures.publishedVersio

Single-cell approaches to cell competition: high-throughput imaging, machine learning and simulations

Cell competition is a quality control mechanism in tissues that results in the elimination of less fit cells. Over the past decade, the phenomenon of cell competition has been identified in many physiological and pathological contexts, driven either by biochemical signaling or by mechanical forces within the tissue. In both cases, competition has generally been characterized based on the elimination of loser cells at the population level, but significantly less attention has been focused on determining how single-cell dynamics and interactions regulate population-wide changes. In this review, we describe quantitative strategies and outline the outstanding challenges in understanding the single cell rules governing tissue-scale competition dynamics. We propose quantitative metrics to characterize single cell behaviors in competition and use them to distinguish the types and outcomes of competition. We describe how such metrics can be measured experimentally using a novel combination of high-throughput imaging and machine learning algorithms. We outline the experimental challenges to quantify cell fate dynamics with high-statistical precision, and describe the utility of computational modeling in testing hypotheses not easily accessible in experiments. In particular, cell-based modeling approaches that combine mechanical interaction of cells with decision-making rules for cell fate choices provide a powerful framework to understand and reverse-engineer the diverse rules of cell competition

Cell-scale biophysical determinants of cell competition in epithelia

How cells with different genetic makeups compete in tissues is an outstanding question in developmental biology and cancer research. Studies in recent years have revealed that cell competition can either be driven by short-range biochemical signalling or by long-range mechanical stresses in the tissue. To date, cell competition has generally been characterised at the population scale, leaving the single-cell-level mechanisms of competition elusive. Here, we use high time-resolution experimental data to construct a multi-scale agent-based model for epithelial cell competition and use it to gain a conceptual understanding of the cellular factors that governs competition in cell populations within tissues. We find that a key determinant of mechanical competition is the difference in homeostatic density between winners and losers, while differences in growth rates and tissue organisation do not affect competition end result. In contrast, the outcome and kinetics of biochemical competition is strongly influenced by local tissue organisation. Indeed, when loser cells are homogenously mixed with winners at the onset of competition, they are eradicated; however, when they are spatially separated, winner and loser cells coexist for long times. These findings suggest distinct biophysical origins for mechanical and biochemical modes of cell competition