Post-Subsidy Solar PV Business Models to Tackle Fuel Poverty in Multi-Occupancy Social Housing

Feed-in Tariffs created a vibrant business ecosystem for the deployment of decentralised renewable energy technologies while constituting a regressive tax and increasing inequality. Business model innovation spurred by their withdrawal is providing valuable lessons for progressive policy design. Using the case study of solar PV deployment on multi-occupancy social housing, this paper reveals policy, business and organisational challenges that need to be overcome to address fuel poverty and reduce inequality. Suitable ‘export’ and ‘local’ business models were identified through a workshop and subsequently evaluated through qualitative thematic interview analysis. The ‘local’ model compares favourably in terms of production costs and benefits for fuel poor tenants but unfavourably in terms of transaction costs. Both models are considered equally susceptible to changes in policy. Their success hinges upon third party intermediaries, peer-to-peer learning and a supportive policy environment. This paper concludes with a policy recommendation to ensure that energy justice lies at the heart of the UK’s transition to net-zero carbon through the fair distribution of costs and benefits by including specific provisions to protect low-income groups

Validity of the Cauchy-Born rule applied to discrete cellular-scale models of biological tissues.

The development of new models of biological tissues that consider cells in a discrete manner is becoming increasingly popular as an alternative to continuum methods based on partial differential equations, although formal relationships between the discrete and continuum frameworks remain to be established. For crystal mechanics, the discrete-to-continuum bridge is often made by assuming that local atom displacements can be mapped homogeneously from the mesoscale deformation gradient, an assumption known as the Cauchy-Born rule (CBR). Although the CBR does not hold exactly for noncrystalline materials, it may still be used as a first-order approximation for analytic calculations of effective stresses or strain energies. In this work, our goal is to investigate numerically the applicability of the CBR to two-dimensional cellular-scale models by assessing the mechanical behavior of model biological tissues, including crystalline (honeycomb) and noncrystalline reference states. The numerical procedure involves applying an affine deformation to the boundary cells and computing the quasistatic position of internal cells. The position of internal cells is then compared with the prediction of the CBR and an average deviation is calculated in the strain domain. For center-based cell models, we show that the CBR holds exactly when the deformation gradient is relatively small and the reference stress-free configuration is defined by a honeycomb lattice. We show further that the CBR may be used approximately when the reference state is perturbed from the honeycomb configuration. By contrast, for vertex-based cell models, a similar analysis reveals that the CBR does not provide a good representation of the tissue mechanics, even when the reference configuration is defined by a honeycomb lattice. The paper concludes with a discussion of the implications of these results for concurrent discrete and continuous modeling, adaptation of atom-to-continuum techniques to biological tissues, and model classification

The acquisition of reading skills in English by coloured primary school children whose home language is Afrikaans : a developmental study conducted in a specific South African community

This research studies the acquisition and development of specific reading skills in English by "Coloured" primary school children for whom English is a second language. This study involves both oral and silent reading research. Developmental trends in both modes of reading are compared with those established for reading in Afrikaans in order to ascertain whether any transfer takes place from Afrikaans to English. For analysis of data obtained from oral reading, this researcher adopted an error analysis method devised by Kenneth Goodman (1973), viz. Miscue Analysis (MA). Readers read a passage and their miscues were recorded. From the miscues this researcher established, for the different standards: the frequencies of miscues; readers' ability to associate sound and symbol; sensitivity to grammar; meaning access; and correction strategies. In the silent reading research, readers' performances in a test battery of eight sub-tests provide insights into the presence or absence of information processing skills. Readability levels (Singer and Donlan (1980), discrimination index and facility value (Heaton 1975), and Chi-Square Statistics (Roscoe 1969) determine the development of specific reading skills, viz.: utilization of textual cues; understanding cause and effect relationships and sequence; previewing and anticipation; scanning, referring and synthesizing; understanding text structure and coherence; understanding propositional development; understanding synonymy and antonimy; and understanding communicative value. Grellet (1981), Kennedy (1981), and Harri-Augstein (1982), inter alia, regard these skills as crucial to efficient text processing. Analyses of data show there are developmental patterns, but skills emerge 1 - 3 years late when compared with results obtained by Kennedy (1981 ) and develop at a retarded and erratic pace. The readers in all the standards have not mastered the skills sufficiently to process text efficiently. This research shows that Std 3 is a cut-off level where a transition takes place from lower-order to higher-order skills processing. In addition, Chi-Square Statistics show little transfer from Afrikaans to English; the skills develop independently in the two languages. Enquiry has identified various factors that influence skills deficiencies, viz.: syllabus prescriptions and problems of interpretation; teachers' understanding of the reading process and the methods employed; teacher-training progresses; materials prescribed for reading; and reading in the society. This research recommends ways in which short comings can be remedie

Using a probabilistic approach to derive a two-phase model of flow-induced cell migration

Interstitial fluid flow is a feature of many solid tumors. In vitro experiments have shown that such fluid flow can direct tumor cell movement upstream or downstream depending on the balance between the competing mechanisms of tensotaxis (cell migration up stress gradients) and autologous chemotaxis (downstream cell movement in response to flow-induced gradients of self-secreted chemoattractants). In this work we develop a probabilistic-continuum, two-phase model for cell migration in response to interstitial flow. We use a kinetic description for the cell velocity probability density function, and model the flow-dependent mechanical and chemical stimuli as forcing terms that bias cell migration upstream and downstream. Using velocity-space averaging, we reformulate the model as a system of continuum equations for the spatiotemporal evolution of the cell volume fraction and flux in response to forcing terms that depend on the local direction and magnitude of the mechanochemical cues. We specialize our model to describe a one-dimensional cell layer subject to fluid flow. Using a combination of numerical simulations and asymptotic analysis, we delineate the parameter regime where transitions from downstream to upstream cell migration occur. As has been observed experimentally, the model predicts downstream-oriented chemotactic migration at low cell volume fractions, and upstream-oriented tensotactic migration at larger volume fractions. We show that the locus of the critical volume fraction, at which the system transitions from downstream to upstream migration, is dominated by the ratio of the rate of chemokine secretion and advection. Our model also predicts that, because the tensotactic stimulus depends strongly on the cell volume fraction, upstream, tensotaxis-dominated migration occurs only transiently when the cells are initially seeded, and transitions to downstream, chemotaxis-dominated migration occur at later times due to the dispersive effect of cell diffusion

Using a probabilistic approach to derive a two-phase model of flow-induced cell migration

Interstitial fluid flow is a feature of many solid tumours. In vitro experiments have shown that such fluid flow can direct tumour cell movement upstream or downstream depending on the balance between the competing mechanisms of tensotaxis and autologous chemotaxis. In this work we develop a probabilistic-continuum, two-phase model for cell migration in response to interstitial flow. We use a Fokker-Planck type equation for the cell-velocity probability density function, and model the flow-dependent mechanochemical stimulus as a forcing term which biases cell migration upstream and downstream. Using velocity-space averaging, we reformulate the model as a system of continuum equations for the spatio-temporal evolution of the cell volume fraction and flux, in response to forcing terms which depend on the local direction and magnitude of the mechanochemical cues. We specialise our model to describe a one-dimensional cell layer subject to fluid flow. Using a combination of numerical simulations and asymptotic analysis, we delineate the parameter regime where transitions from downstream to upstream cell migration occur. As has been observed experimentally, the model predicts downstream-oriented, chemotactic migration at low cell volume fractions, and upstream-oriented, tensotactic migration at larger volume fractions. We show that the locus of the critical volume fraction, at which the system transitions from downstream to upstream migration, is dominated by the ratio of the rate of chemokine secretion and advection. Our model predicts that, because the tensotactic stimulus depends strongly on the cell volume fraction, upstream migration occurs only transiently when the cells are initially seeded, and transitions to downstream migration occur at later times due to the dispersive effect of cell diffusion.Comment: 20 pages, 6 figures. Submitted to Biophysical Journa

Cell morphology drives spatial patterning in microbial communities

The clearest phenotypic characteristic of microbial cells is their shape, but we do not understand how cell shape affects the dense communities, known as biofilms, where many microbes live. Here, we use individual-based modeling to systematically vary cell shape and study its impact in simulated communities. We compete cells with different cell morphologies under a range of conditions and ask how shape affects the patterning and evolutionary fitness of cells within a community. Our models predict that cell shape will strongly influence the fate of a cell lineage: we describe a mechanism through which coccal (round) cells rise to the upper surface of a community, leading to a strong spatial structuring that can be critical for fitness. We test our predictions experimentally using strains of Escherichia coli that grow at a similar rate but differ in cell shape due to single amino acid changes in the actin homolog MreB. As predicted by our model, cell types strongly sort by shape, with round cells at the top of the colony and rod cells dominating the basal surface and edges. Our work suggests that cell morphology has a strong impact within microbial communities and may offer new ways to engineer the structure of synthetic communities

Enhanced perfusion following exposure to radiotherapy: a theoretical investigation

Tumour angiogenesis leads to the formation of blood vessels that are structurally and spatially heterogeneous. Poor blood perfusion, in conjunction with increased hypoxia and oxygen heterogeneity, impairs a tumour’s response to radiotherapy. The optimal strategy for enhancing tumour perfusion remains unclear, preventing its regular deployment in combination therapies. In this work, we first identify vascular architectural features that correlate with enhanced perfusion following radiotherapy, using in vivo imaging data from vascular tumours. Then, we present a novel computational model to determine the relationship between these architectural features and blood perfusion in silico. If perfusion is defined to be the proportion of vessels that support blood flow, we find that vascular networks with small mean diameters and large numbers of angiogenic sprouts show the largest increases in perfusion post-irradiation for both biological and synthetic tumours. We also identify cases where perfusion increases due to the pruning of hypoperfused vessels, rather than blood being rerouted. These results indicate the importance of considering network composition when determining the optimal irradiation strategy. In the future, we aim to use our findings to identify tumours that are good candidates for perfusion enhancement and to improve the efficacy of combination therapies

CoGNaC: A Chaste Plugin for the Multiscale Simulation of Gene Regulatory Networks Driving the Spatial Dynamics of Tissues and Cancer

We introduce a Chaste plugin for the generation and the simulation of Gene Regulatory Networks (GRNs) in multiscale models of multicellular systems. Chaste is a widely used and versatile computational framework for the multiscale modeling and simulation of mul- ticellular biological systems. The plugin, named CoGNaC (Chaste and Gene Networks for Cancer), allows the linking of the regulatory dynamics to key properties of the cell cycle and of the differentiation process in populations of cells, which can subsequently be modeled us- ing different spatial modeling scenarios. The approach of CoGNaC focuses on the emergent dynamical behaviour of gene networks, in terms of gene activation patterns characterizing the different cellular phenotypes of real cells and, especially, on the overall robustness to perturbations and biological noise. The integration of this approach within Chaste\u2019s modu- lar simulation framework provides a powerful tool to model multicellular systems, possibly allowing for the formulation of novel hypotheses on gene regulation, cell differentiation and, in particular, cancer emergence and development. In order to demonstrate the usefulness of CoGNaC over a range of modelling paradigms, two example applications are presented. The first of these concerns the characterization of the gene activation patterns of human T-helper cells. The second example is a multiscale simulation of a simplified intestinal crypt, in which, given certain conditions, tumor cells can emerge and colonize the tissue

Abnormal morphology biases haematocrit distribution in tumour vasculature and contributes to heterogeneity in tissue oxygenation

Oxygen heterogeneity in solid tumors is recognized as a limiting factor for therapeutic efficacy. This heterogeneity arises from the abnormal vascular structure of the tumor, but the precise mechanisms linking abnormal structure and compromised oxygen transport are only partially understood. In this paper, we investigate the role that red blood cell (RBC) transport plays in establishing oxygen heterogeneity in tumor tissue. We focus on heterogeneity driven by network effects, which are challenging to observe experimentally due to the reduced fields of view typically considered. Motivated by our findings of abnormal vascular patterns linked to deviations from current RBC transport theory, we calculated average vessel lengths L⎯⎯ and diameters d⎯⎯ from tumor allografts of three cancer cell lines and observed a substantial reduction in the ratio λ=L⎯⎯/d⎯⎯ compared to physiological conditions. Mathematical modeling reveals that small values of the ratio λ (i.e., λ<6 ) can bias hematocrit distribution in tumor vascular networks and drive heterogeneous oxygenation of tumor tissue. Finally, we show an increase in the value of λ in tumor vascular networks following treatment with the antiangiogenic cancer agent DC101. Based on our findings, we propose λ as an effective way of monitoring the efficacy of antiangiogenic agents and as a proxy measure of perfusion and oxygenation in tumor tissue undergoing antiangiogenic treatment

Megacity and local contributions to regional air pollution : An aircraft case study over London

In July 2017 three research flights circumnavigating the megacity of London were conducted as a part of the STANCO training school for students and early career researchers organised by EUFAR (European Facility for Airborne Research). Measurements were made from the UK's Facility for Airborne Atmospheric Measurements (FAAM) BAe-146-301 atmospheric research aircraft with the aim to sample, characterise and quantify the impact of megacity outflow pollution on air quality in the surrounding region. Conditions were extremely favourable for airborne measurements, and all three flights were able to observe clear pollution events along the flight path. A small change in wind direction provided sufficiently different air mass origins over the 2 d such that a distinct pollution plume from London, attributable marine emissions and a double-peaked dispersed area of pollution resulting from a combination of local and transported emissions were measured. We were able to analyse the effect of London emissions on air quality in the wider region and the extent to which local sources contribute to pollution events. The background air upwind of London was relatively clean during both days; concentrations of CO were 88-95 ppbv, total (measured) volatile organic compounds (VOCs) were 1.6-1.8 ppbv and NOx was 0.7- 0.8 ppbv. Downwind of London, we encountered elevations in all species with CO>100 ppbv, VOCs 2.8-3.8 ppbv, CH4>2080 ppbv and NOx>4 ppbv, and peak concentrations in individual pollution events were higher still. Levels of O3 were inversely correlated with NOx during the first flight, with O3 concentrations of 37 ppbv upwind falling to 26 ppbv in the well-defined London plume. Total pollutant fluxes from London were estimated through a vertical plane downwind of the city. Our calculated CO2 fluxes are within the combined uncertainty of those estimated previously, but there was a greater disparity in our estimates of CH4 and CO. On the second day, winds were lighter and downwind O3 concentrations were elevated to 39-43 ppbv (from 32 to 35 ppbv upwind), reflecting the contribution of more aged pollution to the regional background. Elevations in pollutant concentrations were dispersed over a wider area than the first day, although we also encountered a number of clear transient enhancements from local sources. This series of flights demonstrated that even in a region of megacity outflow, such as the south-east of the UK, local fresh emissions and more distant UK sources of pollution can all contribute substantially to pollution events. In the highly complex atmosphere around a megacity where a high background level of pollution mixes with a variety of local sources at a range of spatial and temporal scales and atmospheric dynamics are further complicated by the urban heat island, the use of pollutant ratios to track and determine the ageing of air masses may not be valid. The individual sources must therefore all be well-characterised and constrained to understand air quality around megacities such as London. Research aircraft offer that capability through targeted sampling of specific sources and longitudinal studies monitoring trends in emission strength and profiles over time