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Ethics and morality as objects of research remain important blind spots of geography. Despite their recent attempts to reconcile the discipline’s take on ethics, geographers hardly ever investigate the individual and social production of moral and ethical ...
Cloaking using complementary media was suggested by Lai et al. in [8]. The study of this problem faces two difficulties. Firstly, this problem is unstable since the equations describing the phenomenon have sign changing coefficients, hence the ellipticity ...
Susceptibility to obesity in today′s environment has a strong genetic component. Lower socioeconomic position (SEP) is associated with a higher risk of obesity but it is not known if it accentuates genetic susceptibility to obesity. We aimed to use up to 1 ...
In this thesis, we explore possible stabilisation methods for the reduce basis approximation of advection-diffusion problems, for which the advection term is dominating. The options we consider are mainly inspired by the Variational Multiscale method (VMS) ...
One of the actual goals in the field of macrocyclic research is to provide accessible chemically robust compounds with absorption in the NIR spectral region. This requirement can be fulfilled in the case of tetrapyrrolic derivatives such as porphyrins, pht ...
Protein kinase inhibitors are an increasingly important class of targeted anticancer therapeutics. More than two dozen new drugs of this class have entered routine clinical use over the past decade. This review article focuses on how the development of met ...
White Working Class Communities in Lyon explores the views and experiences of the majority population in the 8th arrondissement (borough) of Lyon, a diverse and dense area, and socially and economically one of the most challenged areas in the city. This st ...
We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of lowdimensional subspaces. To that end, the training posteriors are used for dictionary learning and sparse coding. Sparse representa ...
We propose to model the acoustic space of deep neural network (DNN) class-conditional posterior probabilities as a union of low- dimensional subspaces. To that end, the training posteriors are used for dictionary learning and sparse coding. Sparse represen ...
We study the problem of simultaneously reconstructing a polygonal room and a trajectory of a device equipped with a (nearly) collocated omnidirectional source and receiver. The device measures arrival times of echoes of pulses emitted by the source and pic ...
