Gaussian Process Morphable Models

Statistical shape models (SSMs) represent a class of shapes as a normal distribution of point variations, whose parameters are estimated from example shapes. Principal component analysis (PCA) is applied to obtain a low-dimensional representation of the shape variation in terms of the leading principal components. In this paper, we propose a generalization of SSMs, called Gaussian Process Morphable Models (GPMMs). We model the shape variations with a Gaussian process, which we represent using the leading components of its Karhunen-Loeve expansion. To compute the expansion, we make use of an approximation scheme based on the Nystrom method. The resulting model can be seen as a continuous analogon of an SSM. However, while for SSMs the shape variation is restricted to the span of the example data, with GPMMs we can define the shape variation using any Gaussian process. For example, we can build shape models that correspond to classical spline models, and thus do not require any example data. Furthermore, Gaussian processes make it possible to combine different models. For example, an SSM can be extended with a spline model, to obtain a model that incorporates learned shape characteristics, but is flexible enough to explain shapes that cannot be represented by the SSM. We introduce a simple algorithm for fitting a GPMM to a surface or image. This results in a non-rigid registration approach, whose regularization properties are defined by a GPMM. We show how we can obtain different registration schemes,including methods for multi-scale, spatially-varying or hybrid registration, by constructing an appropriate GPMM. As our approach strictly separates modelling from the fitting process, this is all achieved without changes to the fitting algorithm. We show the applicability and versatility of GPMMs on a clinical use case, where the goal is the model-based segmentation of 3D forearm images

Towards Sustainable Sanitation in an Urbanising World

Urban sanitation in low‐ and middle‐income countries is at an inflection point. It is increasingly acknowledged that conventional sewer‐based sanitation cannot be the only solution for expanding urban areas. There are other objective reasons apart from the lack of capital. The lack of stable energy supplies, of spare parts and of human resources for reliable operation, and the increasing water scarcity are factors that seriously limit the expansion of centralised systems. This chapter argues that a new paradigm for urban sanitation is possible, if the heterogeneity within developing cities is reflected in the implementation of different sanitation systems, adapted to each urban context and integrated under one institutional roof. This new paradigm entails: (1) innovative management arrangements; (2) increased participation and the integration of individual, community and private sector initiatives; (3) thinking at scale to open new opportunities; (4) improved analysis of the situation and awareness raising. Moving beyond conventional approaches towards sustainable urbanisation needs to follow both a top‐down and a bottom‐up approach, with proper incentives and a variety of sanitation systems which, in a future perspective, will become part of the ‘urban ecosystem’

Bayesian multi-model projection of climate: bias assumptions and interannual variability

Current climate change projections are based on comprehensive multi-model ensembles of global and regional climate simulations. Application of this information to impact studies requires a combined probabilistic estimate taking into account the different models and their performance under current climatic conditions. Here we present a Bayesian statistical model for the distribution of seasonal mean surface temperatures for control and scenario periods. The model combines observational data for the control period with the output of regional climate models (RCMs) driven by different global climate models (GCMs). The proposed Bayesian methodology addresses seasonal mean temperatures and considers both changes in mean temperature and interannual variability. In addition, unlike previous studies, our methodology explicitly considers model biases that are allowed to be time-dependent (i.e. change between control and scenario period). More specifically, the model considers additive and multiplicative model biases for each RCM and introduces two plausible assumptions ("constant bias” and "constant relationship”) about extrapolating the biases from the control to the scenario period. The resulting identifiability problem is resolved by using informative priors for the bias changes. A sensitivity analysis illustrates the role of the informative prior. As an example, we present results for Alpine winter and summer temperatures for control (1961-1990) and scenario periods (2071-2100) under the SRES A2 greenhouse gas scenario. For winter, both bias assumptions yield a comparable mean warming of 3.5-3.6°C. For summer, the two different assumptions have a strong influence on the probabilistic prediction of mean warming, which amounts to 5.4°C and 3.4°C for the "constant bias” and "constant relation” assumptions, respectively. Analysis shows that the underlying reason for this large uncertainty is due to the overestimation of summer interannual variability in all models considered. Our results show the necessity to consider potential bias changes when projecting climate under an emission scenario. Further work is needed to determine how bias information can be exploited for this tas

Resistance of αAI-1 transgenic chickpea (Cicer arietinum) and cowpea (Vigna unguiculata) dry grains to bruchid beetles (Coleoptera: Chrysomelidae)

Dry grain legume seeds possessing αAI-1, an α-amylase inhibitor from common bean (Phaseolus vulgaris), under the control of a cotyledon-specific promoter have been shown to be highly resistant to several important bruchid pest species. One transgenic chickpea and four cowpea lines expressing αAI-1, their respective controls, as well as nine conventional chickpea cultivars were assessed for their resistance to the bruchids Acanthoscelides obtectus (Say), Callosobruchus chinensis L. and Callosobruchus maculatus F. All transgenic lines were highly resistant to both Callosobruchus species. A. obtectus, known to be tolerant to αAI-1, was able to develop in all transgenic lines. While the cotyledons of all non-transgenic cultivars were highly susceptible to all bruchids, C. chinensis and C. maculatus larvae suffered from significantly increased mortality rates inside transgenic seeds. The main factor responsible for the partial resistance in the non-transgenic cultivars was deduced to reside in the seed coat. The αAI-1 present in seeds of transgenic chickpea and cowpea lines significantly increases their resistance to two important bruchid pest species (C. chinensis and C. maculatus) essentially to immunity. To control αAI-1 tolerant bruchid species such as A. obtectus and to avoid the development of resistance to αAI-1, varieties carrying this transgene should be protected with additional control measure

The role of institutional logics during participation in urban processes and projects: Insights from a comparative analysis of upgrading fifteen informal settlements in Kenya

The academic literature largely acknowledges participation as a key condition for the successful upgrading of informal settlements. However, how individual participative actions of different actor groups and reactions of dwellers combine to influence project outcomes of upgrading processes has not been studied. This article posits that different combinations of presence or absence of collaborative interactions between dwellers and other actors will decisively predict the success and failure of projects. Specifically, we argue that interactions between different groups of implementers and dwellers are conditioned by distinctive value systems—institutional logics—, which provide specific challenges to establishing collaborative interactions with dwellers as the actors conduct their roles. We identify sufficient combinations of participative actions that may lead to successful upgrading using qualitative comparative analysis (QCA) on 15 informal settlements in Kenya's secondary towns that were recently upgraded. Our findings indicate that participation has to consider a multiplicity of actors, who are guided by different logics; it has to span over the whole implementation cycle. It also has to deal reflexively with the issue of representation of the community. This extends the understanding of participation to a perspective that emphasizes the capabilities of implementers to enact collaborative relationships by bridging between their own and the community's institutional logic

Variational Image Registration Using Inhomogeneous Regularization

We present a generalization of the convolution-based variational image registration approach, in which different regularizers can be implemented by conveniently exchanging the convolution kernel, even if it is nonseparable or nonstationary. Nonseparable kernels pose a challenge because they cannot be efficiently implemented by separate 1D convolutions. We propose to use a low-rank tensor decomposition to efficiently approximate nonseparable convolution. Nonstationary kernels pose an even greater challenge because the convolution kernel depends on, and needs to be evaluated for, every point in the image. We propose to pre-compute the local kernels and efficiently store them in memory using the Tucker tensor decomposition model. In our experiments we use the nonseparable exponential kernel and a nonstationary landmark kernel. The exponential kernel replicates desirable properties of elastic image registration, while the landmark kernel incorporates local prior knowledge about corresponding points in the images. We examine the trade-off between the computational resources needed and the approximation accuracy of the tensor decomposition methods. Furthermore, we obtain very smooth displacement fields even in the presence of large landmark displacements

Where do Kampala’s poor “go”? - Urban sanitation conditions in Kampala’s low-income areas

Results of a representative survey conducted with 1’500 poor households in Uganda’s capital during November 2010 show that the majority of Kampala’s urban poor have access to on-site sanitation facilities. Despite the widespread accessibility to sanitation, the conditions of many facilities are unsatisfactory due to the generally large number of users per stance. This leads to low hygienic standards and waiting times for toilet users. As a result, “flying toilets” is (at least occasionally) still a common practice among the urban poor, and many toilets are abandoned after a relatively short time - thus questioning the true level of sanitation access in Kampala’s low-income areas. Household investment in good-quality on-site facilities is discouraged by the lack of property rights and high prices, often exceeding the average annual per capita income in Kampala’s poor settlements

Characterization of Digestive Enzymes of Bruchid Parasitoids–Initial Steps for Environmental Risk Assessment of Genetically Modified Legumes

Genetically modified (GM) legumes expressing the α-amylase inhibitor 1 (αAI-1) from Phaseolus vulgaris L. or cysteine protease inhibitors are resistant to several bruchid pests (Coleoptera: Chrysomelidae). In addition, the combination of plant resistance factors together with hymenopteran parasitoids can substantially increase the bruchid control provided by the resistance alone. If the strategy of combining a bruchid-resistant GM legume and biological control is to be effective, the insecticidal trait must not adversely affect bruchid antagonists. The environmental risk assessment of such GM legumes includes the characterization of the targeted enzymes in the beneficial species and the assessment of the in vitro susceptibility to the resistance factor. The digestive physiology of bruchid parasitoids remain relatively unknown, and their susceptibility to αAI-1 has never been investigated. We have detected α-amylase and serine protease activities in all five bruchid parasitoid species tested. Thus, the deployment of GM legumes expressing cysteine protease inhibitors to control bruchids should be compatible with the use of parasitoids. In vitro inhibition studies showed that sensitivity of α-amylase activity to αAI-1 in the parasitoids was comparable to that in the target species. Direct feeding assays revealed that harmful effects of α-amylase inhibitors on bruchid parasitoids cannot be discounted and need further evaluation