Synthesis and optical properties of composite films from P3HT and sandwich-like Ag-C-Ag nanoparticles

This document is the Accepted Manuscript of the following article: Lingpeng Yan, Yamin Hao, Xiaoting Feng, Yongzhen Yang, Xuguang Liu, Yongkang Chen, and Bingshe Xu, ‘Synthesis and optical properties of composite films from P3HT and sandwich-like Ag–C–Ag nanoparticles’, RSC Advances, Vol. 5(97): 79860-79867, 2015, DOI: https://doi.org/10.1039/C5RA16854F. Content in the UH Research Archive is made available for personal research, educational, and non-commercial purposes only. Unless otherwise stated, all content is protected by copyright, and in the absence of an open license, permissions for further re-use should be sought from the publisher, the author, or other copyright holder.Sandwich-like Ag-C-Ag nanoparticles (Ag-C-Ag NPs) were synthesized under mild hydrothermal conditions in a one-step method. With this approach, Ag was not only encapsulated in the centre of an individual carbon nanosphere, but was also uniformly dispersed within the carbon matrix up to the sphere's shell. Then, poly(3-hexylthiophene):Ag-C-Ag NPs (P3HT:Ag-C-Ag NPs) composite films were prepared by a spin coating method with a chlorobenzene solution of Ag-C-Ag NPs and P3HT. Both morphology and microstructure of Ag-C-Ag NPs were investigated by field emission scanning electron microscopy and high resolution transmission electron microscopy. The possible formation mechanism was proposed. The results have indicated that the Ag-C-Ag NPs present many functional groups and their energy levels match with those of P3HT. It has been observed that an introduction of Ag-C-Ag NPs to P3HT can induce broad and high-absorbing spectra as well as great photoluminescence quenching of P3HT. It is evident that sandwich-like Ag-C-Ag NPs have a great potential to be a new acceptor material in photovoltaic devices.Peer reviewe

FlowLens: Seeing Beyond the FoV via Flow-guided Clip-Recurrent Transformer

Limited by hardware cost and system size, camera's Field-of-View (FoV) is not always satisfactory. However, from a spatio-temporal perspective, information beyond the camera's physical FoV is off-the-shelf and can actually be obtained "for free" from the past. In this paper, we propose a novel task termed Beyond-FoV Estimation, aiming to exploit past visual cues and bidirectional break through the physical FoV of a camera. We put forward a FlowLens architecture to expand the FoV by achieving feature propagation explicitly by optical flow and implicitly by a novel clip-recurrent transformer, which has two appealing features: 1) FlowLens comprises a newly proposed Clip-Recurrent Hub with 3D-Decoupled Cross Attention (DDCA) to progressively process global information accumulated in the temporal dimension. 2) A multi-branch Mix Fusion Feed Forward Network (MixF3N) is integrated to enhance the spatially-precise flow of local features. To foster training and evaluation, we establish KITTI360-EX, a dataset for outer- and inner FoV expansion. Extensive experiments on both video inpainting and beyond-FoV estimation tasks show that FlowLens achieves state-of-the-art performance. Code will be made publicly available at https://github.com/MasterHow/FlowLens.Comment: Code will be made publicly available at https://github.com/MasterHow/FlowLen

Towards Anytime Optical Flow Estimation with Event Cameras

Event cameras are capable of responding to log-brightness changes in microseconds. Its characteristic of producing responses only to the changing region is particularly suitable for optical flow estimation. In contrast to the super low-latency response speed of event cameras, existing datasets collected via event cameras, however, only provide limited frame rate optical flow ground truth, (e.g., at 10Hz), greatly restricting the potential of event-driven optical flow. To address this challenge, we put forward a high-frame-rate, low-latency event representation Unified Voxel Grid, sequentially fed into the network bin by bin. We then propose EVA-Flow, an EVent-based Anytime Flow estimation network to produce high-frame-rate event optical flow with only low-frame-rate optical flow ground truth for supervision. The key component of our EVA-Flow is the stacked Spatiotemporal Motion Refinement (SMR) module, which predicts temporally-dense optical flow and enhances the accuracy via spatial-temporal motion refinement. The time-dense feature warping utilized in the SMR module provides implicit supervision for the intermediate optical flow. Additionally, we introduce the Rectified Flow Warp Loss (RFWL) for the unsupervised evaluation of intermediate optical flow in the absence of ground truth. This is, to the best of our knowledge, the first work focusing on anytime optical flow estimation via event cameras. A comprehensive variety of experiments on MVSEC, DESC, and our EVA-FlowSet demonstrates that EVA-Flow achieves competitive performance, super-low-latency (5ms), fastest inference (9.2ms), time-dense motion estimation (200Hz), and strong generalization. Our code will be available at https://github.com/Yaozhuwa/EVA-Flow.Comment: Code will be available at https://github.com/Yaozhuwa/EVA-Flo

TinyKG: Memory-Efficient Training Framework for Knowledge Graph Neural Recommender Systems

There has been an explosion of interest in designing various Knowledge Graph Neural Networks (KGNNs), which achieve state-of-the-art performance and provide great explainability for recommendation. The promising performance is mainly resulting from their capability of capturing high-order proximity messages over the knowledge graphs. However, training KGNNs at scale is challenging due to the high memory usage. In the forward pass, the automatic differentiation engines (\textsl{e.g.}, TensorFlow/PyTorch) generally need to cache all intermediate activation maps in order to compute gradients in the backward pass, which leads to a large GPU memory footprint. Existing work solves this problem by utilizing multi-GPU distributed frameworks. Nonetheless, this poses a practical challenge when seeking to deploy KGNNs in memory-constrained environments, especially for industry-scale graphs. Here we present TinyKG, a memory-efficient GPU-based training framework for KGNNs for the tasks of recommendation. Specifically, TinyKG uses exact activations in the forward pass while storing a quantized version of activations in the GPU buffers. During the backward pass, these low-precision activations are dequantized back to full-precision tensors, in order to compute gradients. To reduce the quantization errors, TinyKG applies a simple yet effective quantization algorithm to compress the activations, which ensures unbiasedness with low variance. As such, the training memory footprint of KGNNs is largely reduced with negligible accuracy loss. To evaluate the performance of our TinyKG, we conduct comprehensive experiments on real-world datasets. We found that our TinyKG with INT2 quantization aggressively reduces the memory footprint of activation maps with $7 \times$, only with $2\%$ loss in accuracy, allowing us to deploy KGNNs on memory-constrained devices

MicroRNA: role in macrophage polarization and the pathogenesis of the liver fibrosis

Macrophages, as central components of innate immunity, feature significant heterogeneity. Numerus studies have revealed the pivotal roles of macrophages in the pathogenesis of liver fibrosis induced by various factors. Hepatic macrophages function to trigger inflammation in response to injury. They induce liver fibrosis by activating hepatic stellate cells (HSCs), and then inflammation and fibrosis are alleviated by the degradation of the extracellular matrix and release of anti-inflammatory cytokines. MicroRNAs (miRNAs), a class of small non-coding endogenous RNA molecules that regulate gene expression through translation repression or mRNA degradation, have distinct roles in modulating macrophage activation, polarization, tissue infiltration, and inflammation regression. Considering the complex etiology and pathogenesis of liver diseases, the role and mechanism of miRNAs and macrophages in liver fibrosis need to be further clarified. We first summarized the origin, phenotypes and functions of hepatic macrophages, then clarified the role of miRNAs in the polarization of macrophages. Finally, we comprehensively discussed the role of miRNAs and macrophages in the pathogenesis of liver fibrotic disease. Understanding the mechanism of hepatic macrophage heterogeneity in various types of liver fibrosis and the role of miRNAs on macrophage polarization provides a useful reference for further research on miRNA-mediated macrophage polarization in liver fibrosis, and also contributes to the development of new therapies targeting miRNA and macrophage subsets for liver fibrosis

Logistic Regression Analysis of Factors Influencing the Effectiveness of Intensive Sound Masking Therapy in Patients with Tinnitus

Objectives: To investigate factors influencing the effectiveness intensive sound masking therapy on tinnitus using Logistic Regression Analysis. Design: The study used a retrospective cross-section analysis. Participants: 102 patients with tinnitus were recruited at the Sun Yat-sen Memorial Hospital of Sun Yat-sen University, China. Intervention: Intensive sound masking therapy was used as an intervention approach for patients with tinnitus. Primary and secondary outcome measures: participants underwent audiological investigations and tinnitus pitch and loudness matching measurements, followed by intensive sound masking therapy. The Tinnitus Handicap Inventory (THI) was used as the outcome measure pre- and post-treatment. Multivariate logistic regression was performed to investigate the association of demographic and audiological factors with effective therapy. Results: According to the THI score changes pre-and post-sound masking intervention, fifty-one participants were categorised into an effective group, the remaining 51 participants were placed in a non-effective group. Those in the effective group were significantly younger than those in the non-effective group (p=0.012). Significantly more participants had flat audiogram configurations in the effective group (p=0.04). Multivariable logistic regression analysis showed that age (OR=0.96, 95% CI: 0.93, 0.99, p=0.007), audiometric configuration (p=0.027) and THI score pre-treatment (OR=1.04, 95% CI: 1.02, 1.07, p<0.001) were significantly associated with therapeutic effectiveness. Further analysis showed that patients with flat audiometric configurations were 5.45 times more likely to respond to intervention than those with high-frequency steeply sloping audiograms (OR=5.45, 95% CI: 1.67, 17.86, p=0.005). Conclusion: Audiometric configuration, age and THI scores appear to be predictive for the effectiveness of sound masking treatment. Gender, tinnitus characteristics and hearing threshold measures seem not to be related to treatment effectiveness. Further randomized control study is needed to provide further evidence of the effectiveness of prognostic factors in tinnitus interventions

The first comprehensive Milky Way stellar mock catalogue for the Chinese Space Station Telescope Survey Camera

The Chinese Space Station Telescope (CSST) is a cutting-edge two-meter astronomical space telescope currently under construction. Its primary Survey Camera (SC) is designed to conduct large-area imaging sky surveys using a sophisticated seven-band photometric system. The resulting data will provide unprecedented data for studying the structure and stellar populations of the Milky Way. To support the CSST development and scientific projects related to its survey data, we generate the first comprehensive Milky Way stellar mock catalogue for the CSST SC photometric system using the TRILEGAL stellar population synthesis tool. The catalogue includes approximately 12.6 billion stars, covering a wide range of stellar parameters, photometry, astrometry, and kinematics, with magnitude reaching down to g=27.5 mag in the AB magnitude system. The catalogue represents our benchmark understanding of the stellar populations in the Milky Way, enabling a direct comparison with the future CSST survey data. Particularly, it sheds light on faint stars that are hidden from current sky surveys. Our crowding limit analysis based on this catalogue provides compelling evidence for the extension of the CSST Optical Survey (OS) to cover low Galactic latitude regions. The strategic extension of the CSST-OS coverage, combined with this comprehensive mock catalogue, will enable transformative science with the CSST

Global distribution and evolutionary transitions of angiosperm sexual systems

Angiosperm sexual systems are fundamental to the evolution and distribution of plant diversity, yet spatiotemporal patterns in angiosperm sexual systems and their drivers remain poorly known. Using data on sexual systems and distributions of 68453 angiosperm species, we present the first global maps of sexual system frequencies and evaluate sexual system evolution during the Cenozoic. Frequencies of dioecy and monoecy increase with latitude, while hermaphrodites are more frequent in warm and arid regions. Transitions to dioecy from other states were higher than to hermaphroditism, but transitions away from dioecy increased since the Cenozoic, suggesting that dioecy is not an evolutionary end point. Transitions between hermaphroditism and dioecy increased, while transitions to monoecy decreased with paleo-temperature when paleo-temperature >0℃. Our study demonstrates the biogeography of angiosperm sexual systems from a macroecological perspective, and enhances our understanding of plant diversity patterns and their response to climate change.acceptedVersio

Cytoplasmic Localization Isoform of Cyclin Y Enhanced the Metastatic Ability of Lung Cancer via Regulating Tropomyosin 4

Cyclin Y (CCNY) is a novel cyclin and highly conserved in metazoan species. Previous studies from our and other laboratory indicate that CCNY play a crucial role in tumor progression. There are two CCNY isoform which has different subcellular distributions, with cytoplasmic isoform (CCNYc) and membrane distribution isoform (CCNYm). However, the expression and function of CCNY isoforms is still unclear. We firstly found CCNYc was expressed in natural lung cancer tissue and cells through the subcellular distribution. Co-IP and immunofluorescence showed that both CCNYm and CCNYc could interact with PFTK1. Further studies illustrated that CCNYc but not CCNYm enhanced cell migration and invasion activity both in vivo and vitro. The function of CCNYc could be inhibited by suppression of PFTK1 expression. In addition, our data indicated that tropomyosin 4 (TPM4), a kind of actin-binding proteins, was down-regulated by suppression of CCNY. F-actin assembly could be controlled by CCNYc as well as PFTK1 and TPM4. As a result, CCNY was mainly expressed in lung cancer. CCNYc could promote cell motility and invasion. It indicated that CCNYc/PFTK1 complex could promote cell metastasis by regulating the formation of F-actin via TPM4