Provably Learning Diverse Features in Multi-View Data with Midpoint Mixup

Mixup is a data augmentation technique that relies on training using random convex combinations of data points and their labels. In recent years, Mixup has become a standard primitive used in the training of state-of-the-art image classification models due to its demonstrated benefits over empirical risk minimization with regards to generalization and robustness. In this work, we try to explain some of this success from a feature learning perspective. We focus our attention on classification problems in which each class may have multiple associated features (or views) that can be used to predict the class correctly. Our main theoretical results demonstrate that, for a non-trivial class of data distributions with two features per class, training a 2-layer convolutional network using empirical risk minimization can lead to learning only one feature for almost all classes while training with a specific instantiation of Mixup succeeds in learning both features for every class. We also show empirically that these theoretical insights extend to the practical settings of image benchmarks modified to have multiple features.Comment: 37 pages, 2 figures, ICML 202

Oxytocin protects neurons from hypoxic-ischemic brain injury by enhancing inhibitory neurotransmission in neonatal rats

Purpose: To study the protective effect of oxytocin on hypoxic-ischemic brain neuron injury in neonatal rats, and the mechanism of action involved.Methods: Hippocampal slices from neonatal SD rats were cultured in oxygen/glucose-deprived (OGD) solution, leading to establishment of hypoxic-ischemic model of hippocampal slices in vitro. The slices were assigned to 3 groups: control (ACSF solution), model (OGD solution), and oxytocin (OGD solution + 1 μM oxytocin). The effect of oxytocin on vertebral neurons in hippocampal CA1 region of HIBD rats was determined using TOPRO-3 staining, while the effects of oxytocin on hypoxic depolarization (AD) and inhibitory postsynaptic currents (iPSCs) were measured by cell patch clamp technique.Results: The fluorescence intensity of vertebral lamina in hippocampal CA1 area of model group was significantly higher than that of control group, while the corresponding value for oxytocin group was significantly lower than that of model group (p < 0.05). The time lapse before occurrence of AD in hippocampal CA1 area was significantly longer in oxytocin group than in model group, while the time lapse before neuronal AD in oxytocin receptor antagonist group was lower than that in oxytocin group. The frequency and amplitude of iPSCs in oxytocin group were markedly higher than the corresponding control values.Conclusion: Oxytocin exerts protective effect against hypoxic-ischemic brain neuronal damage in neonatal rats by regulating the activation of oxytocin receptor and GABA receptor, and inhibiting nerve transmission. These findings may be of benefit in the development of a suitable therapy for HIBD

Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

High accuracy video label prediction (classification) models are attributed to large scale data. These data could be frame feature sequences extracted by a pre-trained convolutional-neural-network, which promote the efficiency for creating models. Unsupervised solutions such as feature average pooling, as a simple label-independent parameter-free based method, has limited ability to represent the video. While the supervised methods, like RNN, can greatly improve the recognition accuracy. However, the video length is usually long, and there are hierarchical relationships between frames across events in the video, the performance of RNN based models are decreased. In this paper, we proposes a novel video classification method based on a deep convolutional graph neural network(DCGN). The proposed method utilize the characteristics of the hierarchical structure of the video, and performed multi-level feature extraction on the video frame sequence through the graph network, obtained a video representation re ecting the event semantics hierarchically. We test our model on YouTube-8M Large-Scale Video Understanding dataset, and the result outperforms RNN based benchmarks.Comment: ECCV 201

6-Amino-8-(2-bromo­phen­yl)-1,7,8,8a-tetrahydro-3H-isothio­chromene-5,7,7-tricarbonitrile dimethyl­formamide solvate

In the title compound, C18H13BrN4S·C3H7NO, the thio­pyran ring and the adjacent six-numbered ring adopt distorted boat conformations. The mol­ecules, lying about inversion centers, form hydrogen-bonded dimers involving one of the H atoms on the amino group with the N atom of a cyano group of an adjacent mol­ecule, resulting in a 12-membered ring system [R 2 2(12) ring motif]. The other H atom of the amino group forms an inter­molecular hydrogen bond with the O atom of the dimethyl­formamide (DMF) mol­ecule. Another lone pair of electrons on the same carbonyl O atom of DMF mol­ecule forms a non-classical C—H⋯O inter­molecular hydrogen bond, resulting in a chain of mol­ecules

Testing and Data Reduction of the Chinese Small Telescope Array (CSTAR) for Dome A, Antarctica

The Chinese Small Telescope ARray (hereinafter CSTAR) is the first Chinese astronomical instrument on the Antarctic ice cap. The low temperature and low pressure testing of the data acquisition system was carried out in a laboratory refrigerator and on the 4500m Pamirs high plateau, respectively. The results from the final four nights of test observations demonstrated that CSTAR was ready for operation at Dome A, Antarctica. In this paper we present a description of CSTAR and the performance derived from the test observations.Comment: Accepted Research in Astronomy and Astrophysics (RAA) 1 Latex file and 20 figure

(Z)-2-[(2,4-Dimethyl­phen­yl)imino]-1,3-thia­zinan-4-one

In the title compound, C12H14N2OS, the 1,3-thia­zinane ring displays a screw-boat conformation. In the crystal, pairs of centrosymmetrically related mol­ecules are linked by pairs of N—H⋯O hydrogen bonds into dimers. C—H⋯π inter­actions occur between adjacent dimers