Perceiving meaningful activities in a long video sequence is a challenging problem due to ambiguous definition of 'meaningfulness' as well as clutters in the scene. We approach this problem by learning a generative model for regular motion patterns (termed as regularity) using multiple sources with very limited supervision. Specifically, we propose two methods that are built upon the autoencoders for their ability to work with little to no supervision. We first leverage the conventional handcrafted spatio-temporal local features and learn a fully connected autoencoder on them. Second, we build a fully convolutional feed-forward autoencoder to learn both the local features and the classifiers as an end-to-end learning framework. Our model can capture the regularities from multiple datasets. We evaluate our methods in both qualitative and quantitative waysshowing the learned regularity of videos in various aspects and demonstrating competitive performance on anomaly detection datasets as an application.

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Cartilage loss is irreversible, and to date, no effective pharmacotherapies are available to protect or regenerate cartilage. Quantitative prestructural/compositional MR imaging techniques have been developed to characterize the cartilage matrix quality at a stage where abnormal findings are early and potentially reversible, allowing intervention to halt disease progression. The goal of this article is to critically review currently available technologies, present the basic concept behind these techniques, but also to investigate their suitability as imaging biomarkers including their validity, reproducibility, risk prediction and monitoring of therapy. Moreover, we highlighted important clinical applications. This review article focuses on the currently most relevant and clinically applicable technologies, such as T2 mapping, T2*, T1ρ, delayed gadolinium enhanced MRI of cartilage (dGEMRIC), sodium imaging and glycosaminoglycan chemical exchange saturation transfer (gagCEST). To date, most information is available for T2 and T1ρ mapping. dGEMRIC has also been used in multiple clinical studies, although it requires Gd contrast administration. Sodium imaging and gagCEST are promising technologies but are dependent on high field strength and sophisticated software and hardware. Level of Evidence: 5 J. Magn. Reson. Imaging 2017;45:949–965

We characterize the double-faced nature of hydrogen bonding in hydroxy-functionalized ionic liquids by means of neutron diffraction with isotopic substitution (NDIS), molecular dynamics (MD) simulations,and quantum chemical calculations.N DIS data are fit using the empirical potential structure refinement technique (EPSR) to elucidate the nearest neighbor H···O and O···O pair distribution functions for hydrogen bonds between ions of opposite charge and the same charge.D espite the presence of repulsive Coulomb forces,t he cation-cation interaction is stronger than the cation-anion interaction. We compare the hydrogen-bond geometries of both "doubly charged hydrogen bonds" with those reported for molecular liquids,such as water and alcohols.Incombination, the NDIS measurements and MD simulations reveal the subtle balance between the two types of hydrogen bonds:T he small transition enthalpysuggests that the elusive like-charge attraction is almost competitive with conventional ion-pair formation.

We study ionic liquids composed of 1-alkyl-3-methylimidazolium cations and bis(trifluoromethyl-sulfonyl)imide anions ([CnMIm][NTf2]) with varying chain-length n = 2, 4, 6, 8 by using molecular dynamics simulations. We show that a reparametrization of the dihedral potentials as well as charges of the [NTf2] anion leads to an improvement of the force field model introduced by Köddermann, Paschek, and Ludwig [ChemPhysChem 8, 2464 (2007)] (KPL-force field). A crucial advantage of the new parameter set is that the minimum energy conformations of the anion (trans and gauche), as deduced from ab initio calculations and Raman experiments, are now both well represented by our model. In addition, the results for [CnMIm][NTf2] show that this modification leads to an even better agreement between experiment and molecular dynamics simulation as demonstrated for densities, diffusion coefficients, vaporization enthalpies, reorientational correlation times, and viscosities. Even though we focused on a better representation of the anion conformation, also the alkyl chain-length dependence of the cation behaves closer to the experiment. We strongly encourage to use the new NGOLP (Neumann, Golub, Odebrecht, Ludwig, Paschek) force field for the [NTf2] anion instead of the earlier KPL parameter set for computer simulations aiming to describe the thermodynamics, dynamics, and also structure of imidazolium-based ionic liquids.