Enhanced CO2/H2 separation by GO and PVA-GO embedded PVAm nanocomposite membranes

Membrane technology for CO2/H2 separation, especially when using CO2-selective membranes to keep H2 on the high-pressure retentate side, has been considered promising and energy-efficient for further H2 transport and utilization. This work prepared and optimized a CO2-selective membrane based on polyvinylamine (PVAm) with embedded graphene oxide (GO) and grafted GO for CO2/H2 separation. The facilitated transport effect of PVAm enhances CO2 transport, while the GO-based 2D nanosheets bring in a barrier effect to compensate for the high H2 diffusivity. The GO-modified surface with higher CO2 affinity also provides additional CO2 sorption sites. The membranes’ chemical structure, thermal stability, and morphology were characterized. The effects of GO and PVA-GO in the PVAm matrix and optimal loadings of GO or PVA-GO were investigated. Introducing GO into PVAm significantly increased CO2 permeance with a slight increase in CO2/H2 selectivity. While by adding 0.5 wt% PVA-GO, CO2/H2 selectivity significantly increased from 10 to 22. The selective layer thickness also greatly affects CO2/H2 separation. By increasing the coating layer thickness to approx. 11 μm, the CO2/H2 selectivity substantially increased. The separation performances of the studied membrane are far above the current CO2/H2 upper bound.publishedVersio

Metric-aligned Sample Selection and Critical Feature Sampling for Oriented Object Detection

Arbitrary-oriented object detection is a relatively emerging but challenging task. Although remarkable progress has been made, there still remain many unsolved issues due to the large diversity of patterns in orientation, scale, aspect ratio, and visual appearance of objects in aerial images. Most of the existing methods adopt a coarse-grained fixed label assignment strategy and suffer from the inconsistency between the classification score and localization accuracy. First, to align the metric inconsistency between sample selection and regression loss calculation caused by fixed IoU strategy, we introduce affine transformation to evaluate the quality of samples and propose a distance-based label assignment strategy. The proposed metric-aligned selection (MAS) strategy can dynamically select samples according to the shape and rotation characteristic of objects. Second, to further address the inconsistency between classification and localization, we propose a critical feature sampling (CFS) module, which performs localization refinement on the sampling location for classification task to extract critical features accurately. Third, we present a scale-controlled smooth $L_1$ loss (SC-Loss) to adaptively select high quality samples by changing the form of regression loss function based on the statistics of proposals during training. Extensive experiments are conducted on four challenging rotated object detection datasets DOTA, FAIR1M-1.0, HRSC2016, and UCAS-AOD. The results show the state-of-the-art accuracy of the proposed detector

Proteomic analyses reveal distinct chromatin-associated and soluble transcription factor complexes.

The current knowledge on how transcription factors (TFs), the ultimate targets and executors of cellular signalling pathways, are regulated by protein-protein interactions remains limited. Here, we performed proteomics analyses of soluble and chromatin-associated complexes of 56 TFs, including the targets of many signalling pathways involved in development and cancer, and 37 members of the Forkhead box (FOX) TF family. Using tandem affinity purification followed by mass spectrometry (TAP/MS), we performed 214 purifications and identified 2,156 high-confident protein-protein interactions. We found that most TFs form very distinct protein complexes on and off chromatin. Using this data set, we categorized the transcription-related or unrelated regulators for general or specific TFs. Our study offers a valuable resource of protein-protein interaction networks for a large number of TFs and underscores the general principle that TFs form distinct location-specific protein complexes that are associated with the different regulation and diverse functions of these TFs

The influence of different intensity of monsoon on typhoon precipitation: a comparative study of typhoons Soudelor and Maria

In this paper, multiple sets of reanalysis datasets are used to analyze the intensity of the Asian summer monsoon from 1979 to 2021. Typhoon Soudelor (No. 1513) and Typhoon Maria (No. 1808) were selected from the weak monsoon year 2015 and the strong monsoon year 2018, both of which were generated in the Northwest Pacific in July and made landfall in South China. The Weather Research and Forecasting Model (WRF) was used to simulate the two typhoons, starting 48 h prior to their landfall. The reasons for the differences in precipitation and how the monsoon affects typhoon precipitation in this process are analyzed from the aspects of monsoon background, ambient weather systems, typhoon thermodynamic structure, and water vapor conditions. The analysis shows that the circulation of Soudelor was stable and maintained for a long time. Despite existing in the background of a weak monsoon, the monsoon flow was able to reach the key area affecting typhoons and inject enough warm and moist flow to affect Soudelor. Combined with the analysis of typhoon structure, the strong water vapor transport of Soudelor and increased low-level convergence were conducive to the formation of typhoon-related rainstorms. The monsoon appeared to provide environmental conditions favorable for typhoon precipitation, resulting in a wide range of precipitation and heavy precipitation. Typhoon Maria developed and changed rapidly, moved rapidly, and the precipitation maintained itself for a relatively short time. The monsoon flow was not transported into Maria, resulting in insufficient water vapor inside Maria, which prevented the strengthening of typhoon precipitation. The precipitation of Maria mainly came from the dynamics of the typhoon itself and was not affected by the monsoon. In addition, this study defines an area on the southwest side of the typhoon moving with the center of the typhoon as the key area affecting typhoons. The characteristics of this area can be simply linked to typhoon precipitation, which can be considered an important research area for future analysis and prediction of typhoon precipitation

RSFNet: A White-Box Image Retouching Approach using Region-Specific Color Filters

Retouching images is an essential aspect of enhancing the visual appeal of photos. Although users often share common aesthetic preferences, their retouching methods may vary based on their individual preferences. Therefore, there is a need for white-box approaches that produce satisfying results and enable users to conveniently edit their images simultaneously. Recent white-box retouching methods rely on cascaded global filters that provide image-level filter arguments but cannot perform fine-grained retouching. In contrast, colorists typically employ a divide-and-conquer approach, performing a series of region-specific fine-grained enhancements when using traditional tools like Davinci Resolve. We draw on this insight to develop a white-box framework for photo retouching using parallel region-specific filters, called RSFNet. Our model generates filter arguments (e.g., saturation, contrast, hue) and attention maps of regions for each filter simultaneously. Instead of cascading filters, RSFNet employs linear summations of filters, allowing for a more diverse range of filter classes that can be trained more easily. Our experiments demonstrate that RSFNet achieves state-of-the-art results, offering satisfying aesthetic appeal and increased user convenience for editable white-box retouching.Comment: Accepted by ICCV 202