Semantic Image Synthesis via Adversarial Learning

In this paper, we propose a way of synthesizing realistic images directly with natural language description, which has many useful applications, e.g. intelligent image manipulation. We attempt to accomplish such synthesis: given a source image and a target text description, our model synthesizes images to meet two requirements: 1) being realistic while matching the target text description; 2) maintaining other image features that are irrelevant to the text description. The model should be able to disentangle the semantic information from the two modalities (image and text), and generate new images from the combined semantics. To achieve this, we proposed an end-to-end neural architecture that leverages adversarial learning to automatically learn implicit loss functions, which are optimized to fulfill the aforementioned two requirements. We have evaluated our model by conducting experiments on Caltech-200 bird dataset and Oxford-102 flower dataset, and have demonstrated that our model is capable of synthesizing realistic images that match the given descriptions, while still maintain other features of original images.Comment: Accepted to ICCV 201

TensorLayer: A Versatile Library for Efficient Deep Learning Development

Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduous and complex, as it involves constructing neural network architectures, managing training/trained models, tuning optimization process, preprocessing and organizing data, etc. TensorLayer is a versatile Python library that aims at helping researchers and engineers efficiently develop deep learning systems. It offers rich abstractions for neural networks, model and data management, and parallel workflow mechanism. While boosting efficiency, TensorLayer maintains both performance and scalability. TensorLayer was released in September 2016 on GitHub, and has helped people from academia and industry develop real-world applications of deep learning.Comment: ACM Multimedia 201

Overcoming Language Priors in Visual Question Answering via Distinguishing Superficially Similar Instances

Despite the great progress of Visual Question Answering (VQA), current VQA models heavily rely on the superficial correlation between the question type and its corresponding frequent answers (i.e., language priors) to make predictions, without really understanding the input. In this work, we define the training instances with the same question type but different answers as \textit{superficially similar instances}, and attribute the language priors to the confusion of VQA model on such instances. To solve this problem, we propose a novel training framework that explicitly encourages the VQA model to distinguish between the superficially similar instances. Specifically, for each training instance, we first construct a set that contains its superficially similar counterparts. Then we exploit the proposed distinguishing module to increase the distance between the instance and its counterparts in the answer space. In this way, the VQA model is forced to further focus on the other parts of the input beyond the question type, which helps to overcome the language priors. Experimental results show that our method achieves the state-of-the-art performance on VQA-CP v2. Codes are available at \href{https://github.com/wyk-nku/Distinguishing-VQA.git}{Distinguishing-VQA}.Comment: Published in COLING 202

DAGAN: deep de-aliasing generative adversarial networks for fast compressed sensing MRI reconstruction

Compressed Sensing Magnetic Resonance Imaging (CS-MRI) enables fast acquisition, which is highly desirable for numerous clinical applications. This can not only reduce the scanning cost and ease patient burden, but also potentially reduce motion artefacts and the effect of contrast washout, thus yielding better image quality. Different from parallel imaging based fast MRI, which utilises multiple coils to simultaneously receive MR signals, CS-MRI breaks the Nyquist-Shannon sampling barrier to reconstruct MRI images with much less required raw data. This paper provides a deep learning based strategy for reconstruction of CS-MRI, and bridges a substantial gap between conventional non-learning methods working only on data from a single image, and prior knowledge from large training datasets. In particular, a novel conditional Generative Adversarial Networks-based model (DAGAN) is proposed to reconstruct CS-MRI. In our DAGAN architecture, we have designed a refinement learning method to stabilise our U-Net based generator, which provides an endto-end network to reduce aliasing artefacts. To better preserve texture and edges in the reconstruction, we have coupled the adversarial loss with an innovative content loss. In addition, we incorporate frequency domain information to enforce similarity in both the image and frequency domains. We have performed comprehensive comparison studies with both conventional CSMRI reconstruction methods and newly investigated deep learning approaches. Compared to these methods, our DAGAN method provides superior reconstruction with preserved perceptual image details. Furthermore, each image is reconstructed in about 5 ms, which is suitable for real-time processing

Empagliflozin inhibits coronary microvascular dysfunction and reduces cardiac pericyte loss in db/db mice

BackgroundCoronary microvascular dysfunction (CMD) is a pathophysiological feature of diabetic heart disease. However, whether sodium-glucose cotransporter 2 (SGLT2) inhibitors protect the cardiovascular system by alleviating CMD is not known.ObjectiveWe observed the protective effects of empagliflozin (EMPA) on diabetic CMD.Materials and methodsThe mice were randomly divided into a db/db group and a db/db + EMPA group, and db/m mice served as controls. At 8 weeks of age, the db/db + EMPA group was given empagliflozin 10 mg/(kg⋅d) by gavage for 8 weeks. Body weight, fasting blood glucose and blood pressure were dynamically observed. Cardiac systolic and diastolic function and coronary flow reserve (CFR) were detected using echocardiography. The coronary microvascular structure and distribution of cardiac pericytes were observed using immunofluorescence staining. Picrosirius red staining was performed to evaluate cardiac fibrosis.ResultsEmpagliflozin lowered the increased fasting blood glucose levels of the db/db group. The left ventricular ejection fraction, left ventricular fractional shortening, E/A ratio and E/e′ ratio were not significantly different between the three groups. CFR was decreased in the db/db group, but EMPA significantly improved CFR. In contrast to the sparse and abnormal expansion of coronary microvessels observed in the db/db group, the number of coronary microvessels was increased, and the capillary diameter was decreased in the db/db + EMPA group. The number and microvascular coverage of cardiac pericytes were reduced in the db/db mice but were improved by EMPA. The cardiac fibrosis was increased in db/db group and may alleviate by EMPA.ConclusionEmpagliflozin inhibited CMD and reduced cardiac pericyte loss in diabetic mice

GmFT2a, a Soybean Homolog of FLOWERING LOCUS T, Is Involved in Flowering Transition and Maintenance

BACKGROUND: Flowering reversion can be induced in soybean (Glycine max L. Merr.), a typical short-day (SD) dicot, by switching from SD to long-day (LD) photoperiods. This process may involve florigen, putatively encoded by FLOWERING LOCUS T (FT) in Arabidopsis thaliana. However, little is known about the potential function of soybean FT homologs in flowering reversion. METHODS: A photoperiod-responsive FT homologue GmFT (renamed as GmFT2a hereafter) was cloned from the photoperiod-sensitive cultivar Zigongdongdou. GmFT2a gene expression under different photoperiods was analyzed by real-time quantitative PCR. In situ hybridization showed direct evidence for its expression during flowering-related processes. GmFT2a was shown to promote flowering using transgenic studies in Arabidopsis and soybean. The effects of photoperiod and temperature on GmFT2a expression were also analyzed in two cultivars with different photoperiod-sensitivities. RESULTS: GmFT2a expression is regulated by photoperiod. Analyses of GmFT2a transcripts revealed a strong correlation between GmFT2a expression and flowering maintenance. GmFT2a transcripts were observed continuously within the vascular tissue up to the shoot apex during flowering. By contrast, transcripts decreased to undetectable levels during flowering reversion. In grafting experiments, the early-flowering, photoperiod-insensitive stock Heihe27 promotes the appearance of GmFT2a transcripts in the shoot apex of scion Zigongdongdou under noninductive LD conditions. The photothermal effects of GmFT2a expression diversity in cultivars with different photoperiod-sensitivities and a hypothesis is proposed. CONCLUSION: GmFT2a expression is associated with flowering induction and maintenance. Therefore, GmFT2a is a potential target gene for soybean breeding, with the aim of increasing geographic adaptation of this crop

Anisotropic Hardy-Sobolev inequality in mixed Lorentz spaces with applications to the axisymmetric Navier-Stokes equations

In this paper, we establish several new anisotropic Hardy-Sobolev inequalities in mixed Lebesgue spaces and mixed Lorentz spaces, which covers many known corresponding results. As an application, this type of inequalities allows us to generalize some regularity criteria of the 3D axisymmetric Navier-Stokes equations.Comment: 18 page

Distribution of atmospheric corrosion grades in Southern Hebei Province

China has the largest and most complex power grid in the world. But at the same time, the power grid is also facing severe challenges from the natural environment, so its security and reliability are particularly important. In this paper, Q235 carbon steel was used for exposure test. 81 experimental sites were set up in five cities of Southern Hebei Province. And the data of two years were collected and sorted out, and the map of atmospheric corrosion grade in Southern Hebei Province was drawn