In this work, we present a method for unsupervised domain adaptation. Many adversarial learning methods train domain classifier networks to distinguish the features as either a source or target and train a feature generator network to mimic the discriminator. Two problems exist with these methods. First, the domain classifier only tries to distinguish the features as a source or target and thus does not consider task-specific decision boundaries between classes. Therefore, a trained generator can generate ambiguous features near class boundaries. Second, these methods aim to completely match the feature distributions between different domains, which is difficult because of each domain's characteristics.To solve these problems, we introduce a new approach that attempts to align distributions of source and target by utilizing the task-specific decision boundaries. We propose to maximize the discrepancy between two classifiers' outputs to detect target samples that are far from the support of the source. A feature generator learns to generate target features near the support to minimize the discrepancy. Our method outperforms other methods on several datasets of image classification and semantic segmentation. The codes are available at https

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PREdiction of NOn-LINear soil behavior (PRENOLIN) is an international benchmark aiming to test multiple numerical simulation codes that are capable of predicting nonlinear seismic site response with various constitutive models. One of the objectives of this project is the assessment of the uncertainties associated with nonlinear simulation of 1D site effects. A first verification phase (i.e., comparison between numerical codes on simple idealistic cases) will be followed by a validation phase, comparing the predictions of such numerical estimations with actual strongmotion recordings obtained at well-known sites. The benchmark presently involves 21 teams and 23 different computational codes.We present here the main results of the verification phase dealing with simple cases. Three different idealized soil profiles were tested over a wide range of shear strains with different input motions and different boundary conditions at the sediment/bedrock interface. A first iteration focusing on the elastic and viscoelastic cases was proved to be useful to ensure a common understanding and to identify numerical issues before pursuing the nonlinear modeling. Besides minor mistakes in the implementation of input parameters and output units, the initial discrepancies between the numerical results can be attributed to (1) different understanding of the expression "input motion" in different communities, and (2) different implementations of material damping and possible numerical energy dissipation. The second round of computations thus allowed a convergence of all teams to the Haskell-Thomson analytical solution in elastic and viscoelastic cases. For nonlinear computations, we investigate the epistemic uncertainties related only to wave propagation modeling using different nonlinear constitutive models. Such epistemic uncertainties are shown to increase with the strain level and to reach values around 0.2 (log 10 scale) for a peak ground acceleration of 5 m=s 2 at the base of the soil column, which may be reduced by almost 50% when the various constitutive models used the same shear strength and damping implementation.

BackgroundSuccessful delivery of compounds to the brain and retina is a challenge in the development of therapeutic drugs and imaging agents. This challenge arises because internalization of compounds into the brain and retina is restricted by the blood–brain barrier (BBB) and blood-retinal barrier (BRB), respectively. Simple and reliable in vivo assays are necessary to identify compounds that can easily cross the BBB and BRB.MethodsWe developed six fluorescent indoline derivatives (IDs) and examined their ability to cross the BBB and BRB in zebrafish by in vivo fluorescence imaging. These fluorescent IDs were administered to live zebrafish by immersing the zebrafish larvae at 7-8 days post fertilization in medium containing the ID, or by intracardiac injection. We also examined the effect of multidrug resistance proteins (MRPs) on the permeability of the BBB and BRB to the ID using MK571, a selective inhibitor of MRPs.ResultsThe permeability of these barriers to fluorescent IDs administered by simple immersion was comparable to when administered by intracardiac injection. Thus, this finding supports the validity of drug administration by simple immersion for the assessment of BBB and BRB permeability to fluorescent IDs. Using this zebrafish model, we demonstrated that the length of the methylene chain in these fluorescent IDs significantly affected their ability to cross the BBB and BRB via MRPs.ConclusionsWe demonstrated that in vivo assessment of the permeability of the BBB and BRB to fluorescent IDs could be simply and reliably performed using zebrafish. The structure of fluorescent IDs can be flexibly modified and, thus, the permeability of the BBB and BRB to a large number of IDs can be assessed using this zebrafish-based assay. The large amount of data acquired might be useful for in silico analysis to elucidate the precise mechanisms underlying the interactions between chemical structure and the efflux transporters at the BBB and BRB. In turn, understanding these mechanisms may lead to the efficient design of compounds targeting the brain and retina.