Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration

Recent work on discrete generative priors, in the form of codebooks, has shown exciting performance for image reconstruction and restoration, as the discrete prior space spanned by the codebooks increases the robustness against diverse image degradations. Nevertheless, these methods require separate training of codebooks for different image categories, which limits their use to specific image categories only (e.g. face, architecture, etc.), and fail to handle arbitrary natural images. In this paper, we propose AdaCode for learning image-adaptive codebooks for class-agnostic image restoration. Instead of learning a single codebook for each image category, we learn a set of basis codebooks. For a given input image, AdaCode learns a weight map with which we compute a weighted combination of these basis codebooks for adaptive image restoration. Intuitively, AdaCode is a more flexible and expressive discrete generative prior than previous work. Experimental results demonstrate that AdaCode achieves state-of-the-art performance on image reconstruction and restoration tasks, including image super-resolution and inpainting

DeepDPM: Dynamic Population Mapping via Deep Neural Network

Dynamic high resolution data on human population distribution is of great importance for a wide spectrum of activities and real-life applications, but is too difficult and expensive to obtain directly. Therefore, generating fine-scaled population distributions from coarse population data is of great significance. However, there are three major challenges: 1) the complexity in spatial relations between high and low resolution population; 2) the dependence of population distributions on other external information; 3) the difficulty in retrieving temporal distribution patterns. In this paper, we first propose the idea to generate dynamic population distributions in full-time series, then we design dynamic population mapping via deep neural network(DeepDPM), a model that describes both spatial and temporal patterns using coarse data and point of interest information. In DeepDPM, we utilize super-resolution convolutional neural network(SRCNN) based model to directly map coarse data into higher resolution data, and a time-embedded long short-term memory model to effectively capture the periodicity nature to smooth the finer-scaled results from the previous static SRCNN model. We perform extensive experiments on a real-life mobile dataset collected from Shanghai. Our results demonstrate that DeepDPM outperforms previous state-of-the-art methods and a suite of frequent data-mining approaches. Moreover, DeepDPM breaks through the limitation from previous works in time dimension so that dynamic predictions in all-day time slots can be obtained.Comment: AAAI201

Protective Effect of Chlorogenic Acid and Its Analogues on Lead-Induced Developmental Neurotoxicity Through Modulating Oxidative Stress and Autophagy

Lead (Pb) is among the deleterious heavy metal and has caused global health concerns due to its tendency to cause a detrimental effect on the development of the central nervous system (CNS). Despite being a serious health concern, treatment of Pb poisoning is not yet available, reflecting the pressing need for compounds that can relieve Pb-induced toxicity, especially neurotoxicity. In the quest of exploring protective strategies against Pb-induced developmental neurotoxicity, compounds from natural resources have gained increased attention. Chlorogenic acid (CGA) and its analogues neochlorogenic acid (NCGA) and cryptochlorogenic acid (CCGA) are the important phenolic compounds widely distributed in plants. Herein, utilizing zebrafish as a model organism, we modeled Pb-induced developmental neurotoxicity and investigated the protective effect of CGA, NCGA, and CCGA co-treatment. In zebrafish, Pb exposure (1,000 μg/L) for 5 days causes developmental malformation, loss of dopaminergic (DA) neurons, and brain vasculature, as well as disrupted neuron differentiation in the CNS. Additionally, Pb-treated zebrafish exhibited abnormal locomotion. Notably, co-treatment with CGA (100 µM), NCGA (100 µM), and CCGA (50 µM) alleviated these developmental malformation and neurotoxicity induced by Pb. Further underlying mechanism investigation revealed that these dietary phenolic acid compounds may ameliorate Pb-induced oxidative stress and autophagy in zebrafish, therefore protecting against Pb-induced developmental neurotoxicity. In general, our study indicates that CGA, NCGA, and CCGA could be promising agents for treating neurotoxicity induced by Pb, and CCGA shows the strongest detoxifying activity

Psoralen Induces Developmental Toxicity in Zebrafish Embryos/Larvae Through Oxidative Stress, Apoptosis, and Energy Metabolism Disorder

Psoralen toxicity is an issue of wide concern. However, an assay for psoralen-induced developmental toxicity has not been reported to date. Moreover, the underlying mechanism of psoralen-induced developmental toxicity is unclear. Therefore, this study attempted to develop a psoralen-induced developmental toxicity assay in zebrafish embryos/larvae. Psoralen treatment caused a decrease in the hatching rate and body length and a significant increase in the malformation rate of zebrafish. Yolk retention, pericardial edema, swim-bladder deficiency, and curved body shape were also observed after psoralen treatment. Yolk retention might have been caused by an abnormality in lipid metabolism. Further experiments indicated that psoralen exerted toxic effects on the developing heart, liver, phagocytes, and nervous system. Increased generation of reactive oxygen species, inhibition of total superoxide dismutase activity, and increased malondialdehyde concentrations indicated inhibition of antioxidant capacity and the presence of oxidative stress. A greater number of apoptotic cells were observed after psoralen exposure, relative to the control. Furthermore, the results of gene-expression analysis showed that psoralen induced developmental toxicity by means of oxidative stress, apoptosis, and energy metabolism abnormalities. These findings will be helpful in understanding psoralen-induced toxicity

Image enhancement suggestions based on machine learning

Images in image libraries are sometimes oriented incorrectly. For example, a photograph taken with a camera held vertically may be displayed horizontally, or vice-versa. Further, users often capture images of documents; however, the resultant image can include distortions due to camera angle, poor lighting, etc. The captured image of a document often also includes objects outside the document boundary, e.g., a surface on which the document is placed. For some photos, automatic enhancements can enhance the quality of the image. This disclosure applies machine learning techniques to detect if an image is that of a document, if the image is mis-rotated, if the image can benefit from automatic enhancement, etc. When such images are detected, enhancements such correction of rotation, cropping, distortion-removal, etc., are automatically suggested to the user, e.g., when the image is displayed. With user permission, an acceptance or dismissal of the suggestion is used as a training signal for the machine learning model. Enhancement suggestions are surfaced, e.g., as tappable or clickable buttons, when an image is being viewed and are applied upon user selection of the suggestion

Xiaoaiping Induces Developmental Toxicity in Zebrafish Embryos Through Activation of ER Stress, Apoptosis and the Wnt Pathway

The aim of the study was to determine the developmental toxicity of the traditional Chinese medicine Xiaoaiping (XAP) and to investigate its underlying mechanism of action. Zebrafish embryos were incubated with 0.4, 0.8, 1.2, and 1.6 mg/mL XAP. Endpoints such as mortality, hatching rate, malformation, body length, morphology score, swimming behavior, histological changes, reactive oxygen species (ROS) production, total superoxide dismutase (T-SOD) activity, and the mRNA expression of genes related to oxidative stress, endoplasmic reticulum (ER) stress, apoptosis, and the Wnt pathway were evaluated. Our results demonstrated that XAP exposure increased mortality and malformation and reduced the hatching rate. XAP resulted in severe malformation, including swim bladder deficiency, yolk retention, pericardial edema, and tail curvature. Histopathological analysis showed that XAP induced liver, heart and muscle injury. High doses (≥1.2 mg/mL) of XAP notably decreased the locomotor capacity of zebrafish. ROS generation was remarkably increased and T-SOD activity was decreased, confirming that oxidative stress was induced by XAP. The mRNA expression levels of ER stress-related genes (chop, hspa5, hsp90b1, and perk), apoptosis-related genes (caspase-3, bax, and p53) and wnt11 were significantly upregulated by XAP exposure. The expression levels of the oxidative stress-related genes (cat, sod1, and gstp2), Wnt pathway-related genes (β-catenin, wnt3a, and wnt8a) and bcl-2 initially increased and then decreased as the XAP exposure dose increased. In conclusion, we provide evidence for the first time that XAP can induce dose-related developmental toxicity, and ER stress, apoptosis and the Wnt pathway participate in the toxicity regulation