The Social and Local Dimensions of Governance of Energy Poverty: Adaptive Responses to State Remoteness

Energy poverty is a huge social problem. Academic and policy deliberations about energy poverty focus repeatedly on the same issues: the lack of a shared definition,who is responsible for the problem, and how best to measure it through indicators. We argue that debates at EU and national level do not address the daily reality of people living in energy poverty. The preliminary findings of our ESRC funded project suggest that local actors (e.g. NGOs) make a substantial contribution to bridging the gap between top-down policy and the energy poor. We argue that these actors represent an adaptive response to the inherent limitations of state and supra-national action and, therefore, play a key role in the governance of energy poverty. In presenting this argument, we suggest, as an avenue for future research, nodal governance as a lens through which to understand the role local actors play in the governing order for tackling energy poverty. The article provides an exploratory analysis of these issues, discussed through the selection of four illustrative examples in Italy, France, Catalonia, and England

GHG emissions of supply chains from different retail systems in Europe

An approach has been developed to collect data and measure energy use and GHG emissions from logistics activities for product supply chains. This approach has been used to assess the GHG efficiency of several supply chains of the same product marketed through different types of retail systems in Europe. The retail types considered are hyper and supermarkets, corner shops, open-air markets, producer's basket direct sale, farm shops and e-commerce; Their GHG efficiencies are quantified and compared for food products, considering whole supply chains from the farm gate where they are grown to the consumer's home. This supply chain efficiency approach highlights the importance of the various operations carried out within the supply chains, such as transport, warehousing, the shop itself, and even consumer behaviour for the last mile. While supermarkets in towns, shops included in a delivery system, or open air markets in town centre appears to be very efficient, rural area and independent shops with lower turnover are less favourable. Indeed, the outcomes of an online consumer survey show large differences amongst the GHG efficiency values for all these retail systems. Therefore, potential logistics choices for improving the supply chain performance could be identified

Energy efficiency and greenhouse gas emissions of different supply chains: a comparison of French, UK and Belgian cases

Freight transportation system is critical to economic activity but it carries significant environmental costs, notably GHG emissions and climate change : energy use and corresponding CO2 emissions is increasing faster in freight transport than in other sectors and this increase is primarily the result of increased trade. This paper compares the transport activities, associated energy consumption and CO2 emissions of different supply chains for a range of products in three countries: Belgium, France and United Kingdom. Among the products considered are furniture and ‘fruits & vegetables’. For each of these products, different supply chains, involving more or less transport activity and associated energy consumption are analysed in each country. The comparison highlights some of the main factors that influence GHG emissions for different supply chains and illustrates how they vary according to product and country of final distribution. In more detail, the paper addresses the main differences between the supply chains of these products namely, the origin of their sourcing, the logistical organisation between production and retail and different types of retail outlet. The origin of the sourcing impact is mainly related to distance. The impact of the logistical organisation between raw material and retail on GHG emissions is linked to the mode and vehicle choice and to the load factor. As for retail, the consumer trip emissions, between his home and the retail outlet, are also an important part of the whole supply chain emissions. It is worthwhile to notice that our goal in this project is to consider the whole supply chain, from production to consumption. Therefore a particular focus is put on the mobility behaviours of consumers purchasing the studied products during their shopping and dropping back home activities related to these products. Especially a web based survey has been conducted and the gathered results offer an opportunity for drawing a more detailed picture of the associated CO2 emissions. This paper uses the results of an ongoing research on supply chain energy efficiency, funded by ADEME (the French Energy Agency) through the French program on transport research (PREDIT). This research is based on a comprehensive review of the various approaches to quantifying the environmental impacts of supply chains together with data collection from a range of organisations including manufacturers, retailers and transport companies. We will first present the developed methodologies, then the results corresponding to each studied product will be described. A discussion of the potential application of the research approach to the wider debate about the environmental impact of freight transport and the scope for GHG emissions reduction targets to be achieved will be included

Accurate determination of elastic parameters for multi-component membranes

Heterogeneities in the cell membrane due to coexisting lipid phases have been conjectured to play a major functional role in cell signaling and membrane trafficking. Thereby the material properties of multiphase systems, such as the line tension and the bending moduli, are crucially involved in the kinetics and the asymptotic behavior of phase separation. In this Letter we present a combined analytical and experimental approach to determine the properties of phase-separated vesicle systems. First we develop an analytical model for the vesicle shape of weakly budded biphasic vesicles. Subsequently experimental data on vesicle shape and membrane fluctuations are taken and compared to the model. The combined approach allows for a reproducible and reliable determination of the physical parameters of complex vesicle systems. The parameters obtained set limits for the size and stability of nanodomains in the plasma membrane of living cells.Comment: (*) authors contributed equally, 6 pages, 3 figures, 1 table; added insets to figure

A New Approach to Fuzzy-Rough Nearest Neighbour Classification

In this paper; we present a new fuzzy-rough nearest neighbour (FRNN) classification algorithm, as an alternative to Sarkar's fuzzy-rough ownership function (FRNN-O) approach. By contrast to the latter, our method uses the nearest neighbours to construct lower and ripper approximations of decision classes; and classifies test instances based on their membership to these approximations. In the experimental analysis; we evaluate our approach with both classical fuzzy-rough approximations (based on an implicator and a t-norm), as well as with the recently introduced vaguely quantified rough sets. Preliminary results are very good, and in general FRNN outperforms both FRNN-O; as well as the traditional frizzy nearest neighbour (FNN) algorithm

Enhanced persistence and collective migration in cooperatively aligning cell clusters

Most cells possess the capacity to locomote. Alone or collectively, this allows them to adapt, to rearrange, and to explore their surroundings. The biophysical characterization of such motile processes, in health and disease, has so far focused mostly on two limiting cases: single-cell motility on the one hand, and the dynamics of confluent tissues such as the epithelium on the other. The in-between regime of clusters, composed of relatively few cells, moving as a coherent unit has received less attention. Such small clusters are, however, deeply relevant in development but also in cancer metastasis. In this work, we use cellular Potts models and analytical active matter theory to understand how the motility of small cell clusters changes with N, the number of cells in the cluster. Modeling and theory reveal our two main findings: Cluster persistence time increases with N while the intrinsic diffusivity decreases with N. We discuss a number of settings in which the motile properties of more complex clusters can be analytically understood, revealing that the focusing effects of small-scale cooperation and cell-cell alignment can overcome the increased bulkiness and internal disorder of multicellular clusters to enhance overall migrational efficacy. We demonstrate this enhancement for small-cluster collective durotaxis, which is shown to proceed more effectively than for single cells. Our results may provide some novel insights into the connection between single-cell and large-scale collective motion and may point the way to the biophysical origins of the enhanced metastatic potential of small tumor cell clusters

Comparing Brain Networks of Different Size and Connectivity Density Using Graph Theory

Graph theory is a valuable framework to study the organization of functional and anatomical connections in the brain. Its use for comparing network topologies, however, is not without difficulties. Graph measures may be influenced by the number of nodes (N) and the average degree (k) of the network. The explicit form of that influence depends on the type of network topology, which is usually unknown for experimental data. Direct comparisons of graph measures between empirical networks with different N and/or k can therefore yield spurious results. We list benefits and pitfalls of various approaches that intend to overcome these difficulties. We discuss the initial graph definition of unweighted graphs via fixed thresholds, average degrees or edge densities, and the use of weighted graphs. For instance, choosing a threshold to fix N and k does eliminate size and density effects but may lead to modifications of the network by enforcing (ignoring) non-significant (significant) connections. Opposed to fixing N and k, graph measures are often normalized via random surrogates but, in fact, this may even increase the sensitivity to differences in N and k for the commonly used clustering coefficient and small-world index. To avoid such a bias we tried to estimate the N,k-dependence for empirical networks, which can serve to correct for size effects, if successful. We also add a number of methods used in social sciences that build on statistics of local network structures including exponential random graph models and motif counting. We show that none of the here-investigated methods allows for a reliable and fully unbiased comparison, but some perform better than others

Modeling Spitzer observations of VV Ser. I. The circumstellar disk of a UX Orionis star

We present mid-infrared Spitzer-IRS spectra of the well-known UX Orionis star VV Ser. We combine the Spitzer data with interferometric and spectroscopic data from the literature covering UV to submillimeter wavelengths. The full set of data are modeled by a two-dimensional axisymmetric Monte Carlo radiative transfer code. The model is used to test the prediction of (Dullemond et al. 2003) that disks around UX Orionis stars must have a self-shadowed shape, and that these disks are seen nearly edge-on, looking just over the edge of a puffed-up inner rim, formed roughly at the dust sublimation radius. We find that a single, relatively simple model is consistent with all the available observational constraints spanning 4 orders of magnitude in wavelength and spatial scales, providing strong support for this interpretation of UX Orionis stars. The grains in the upper layers of the puffed-up inner rim must be small (0.01-0.4 micron) to reproduce the colors (R_V ~ 3.6) of the extinction events, while the shape and strength of the mid-infrared silicate emission features indicate that grains in the outer disk (> 1-2 AU) are somewhat larger (0.3-3.0 micron). From the model fit, the location of the puffed-up inner rim is estimated to be at a dust temperature of 1500 K or at 0.7-0.8 AU for small grains. This is almost twice the rim radius estimated from near-infrared interferometry. A best fitting model for the inner rim in which large grains in the disk mid-plane reach to within 0.25 AU of the star, while small grains in the disk surface create a puffed-up inner rim at ~0.7-0.8 AU, is able to reproduce all the data, including the near-infrared visibilities. [Abstract abridged]Comment: 12 pages, accepted for publication in Ap

Cloning characterisation and expression of a G-protein-couple receptor from Lymnaea stagnalis and identification of a leucokinin-like peptide PSFHSWSamide as its endogenous ligand

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Prenatal diagnosis of isovaleric acidaemia by enzyme and metabolite assay in the first and second trimesters

Isovaleric acidaemia (IVA) is caused by a deficiency of isovaleryl CoA dehydrogenase. The diagnosis can be established biochemically by the demonstration of increased levels of isovalerylglycine (IVG) and 3-hydroxyisovaleric acid in urine and by the deficiency of incorporation of radiolabel from [14C]isovaleric acid in macromolecules in cultured fibroblasts. This paper reports a consecutive series of 24 prenatal diagnoses in pregnancies at high risk, using both methods-metabolite and indirect enzyme assay. Affected fetuses were diagnosed in four pregnancies: three in the second trimester and one recent case in the first trimester. The latter represents the first reported case of a first-trimester diagnosis of IVA by direct analysis of chorionic villi. We also report the first demonstration of strongly accumulated IVG in the amniotic fluid in the 12th week of an affected pregnancy