AHL/Fe-CNF nanocomposites were effective in increasing germination rate and plant growth as well as developing resistance towards biotic and abiotic stresses.
Image-based virtual try-on for fashion has gained considerable attention recently. The task requires trying on a clothing item on a target model image. An efficient framework for this is composed of two stages: (1) warping (transforming) the try-on cloth to align with the pose and shape of the target model, and (2) a texture transfer module to seamlessly integrate the warped try-on cloth onto the target model image. Existing methods suffer from artifacts and distortions in their try-on output. In this work, we present SieveNet, a framework for robust image-based virtual tryon. Firstly, we introduce a multi-stage coarse-to-fine warping network to better model fine grained intricacies (while transforming the try-on cloth) and train it with a novel perceptual geometric matching loss. Next, we introduce a tryon cloth conditioned segmentation mask prior to improvethe texture transfer network. Finally, we also introduce a duelling triplet loss strategy for training the texture translation network which further improves the quality of generated try-on result. We present extensive qualitative and quantitative evaluations of each component of the proposed pipeline and show significant performance improvements against the current state-of-the-art method.
Herein, we investigate whether curcumin nanoparticles (Cur NPs) are effective for the treatment of monocrotaline (MCT)-induced pulmonary arterial hypertension in Sprague Dawley rat. Echocardiography was performed at the start of the study and 28 days after MCT injection. Compared to MCT only animals, Cur NP administration was associated with reduced right ventricular (RV) wall thickness and a decreased right ventricle weight/body weight ratio. Cur NPs also attenuated MCT induced increase in RV mRNA expression of TNF-α and IL-1β. These changes were also associated with decreased RV expression of nitrotyrosine, fibronectin and myosin heavy chain-β.
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