GPU Accelerated Color Correction and Frame Warping for Real-time Video Stitching

Traditional image stitching focuses on a single panorama frame without considering the spatial-temporal consistency in videos. The straightforward image stitching approach will cause temporal flicking and color inconstancy when it is applied to the video stitching task. Besides, inaccurate camera parameters will cause artifacts in the image warping. In this paper, we propose a real-time system to stitch multiple video sequences into a panoramic video, which is based on GPU accelerated color correction and frame warping without accurate camera parameters. We extend the traditional 2D-Matrix (2D-M) color correction approach and a present spatio-temporal 3D-Matrix (3D-M) color correction method for the overlap local regions with online color balancing using a piecewise function on global frames. Furthermore, we use pairwise homography matrices given by coarse camera calibration for global warping followed by accurate local warping based on the optical flow. Experimental results show that our system can generate highquality panorama videos in real time

Surface-exposed loops L7 and L8 of Haemophilus (Glaesserella) parasuis OmpP2 contribute to the expression of proinflammatory cytokines in porcine alveolar macrophages

International audienceOuter membrane protein P2 (OmpP2) of the virulent Haemophilus (Glaesserella) parasuis has been shown to induce the release of proinflammatory cytokines. The OmpP2 protein is composed of eight or nine surface-exposed loops, but it is unclear which of them participates in the OmpP2-induced inflammatory response. In this study, we synthesized linear peptides corresponding to surface-exposed loops L1–L8 of OmpP2 from the virulent H. parasuis SC096 strain to stimulate porcine alveolar macrophages (PAMs) in vitro. We found that both L7 and L8 significantly upregulated the mRNA expression of interleukin (IL)-1α, IL-1β, IL-6, IL-8, IL-17, and IL-23 and the chemokines CCL-4 and CCL-5 in a time- and dose-dependent manner. Additionally, we constructed ompP2ΔLoop7 and ompP2ΔLoop8 mutant SC096 strains and extracted their native OmpP2 proteins to stimulate PAMs. These mutant proteins induced significantly less mRNA expression of inflammatory cytokines than SC096 OmpP2. Next, the amino acid sequences of L7 and L8 from 15 serovars of H. parasuis OmpP2 were aligned. These sequences were relatively conserved among the most virulent reference strains, suggesting that L7 and L8 are the most active peptides of the OmpP2 protein. Furthermore, L7 and L8 significantly upregulated the NF-κB and AP-1 activity levels based on luciferase reporter assays in a dose-dependent manner. Therefore, our results demonstrated that both surface-exposed loops L7 and L8 of H. parasuis OmpP2 induced the expression of proinflammatory cytokines possibly by activating the NF-κB and MAPK signalling pathways in cells infected by H. parasuis

Phylogenetic signal in gut microbial community rather than in rodent metabolic traits

This work was supported by the National Natural Science Foundation of China (32090020, 32271575, 32070449, 31872232, and 32270508) and the Strategic Priority Research Program of the Chinese Academy of Sciences (XDPB16).Peer reviewedPublisher PD

Analysis of internal flow characteristics and entropy generation of low head bulb tubular pump

To study the internal flow characteristics and energy characteristics of a large bulb perfusion pump. Based on the CFX software of the ANSYS platform, the steady calculation of the three-dimensional model of the pump device is carried out. The numerical simulation results obtained by SST k-ω and RNG k-ε turbulence models are compared with the experimental results. Finally, SST k-ω is selected for subsequent calculation. With the help of the flow line diagram and turbulent kinetic energy table of the whole flow channel of the pump device, the flow components of the pump device under different working conditions are analyzed, and the pressure and velocity distribution at the impeller and guide vane are analyzed by pressure cloud diagram and velocity cloud diagram. It is found that there are three high-pressure areas in the impeller and guide vane section, and the high-pressure regions are mainly distributed in the middle of the impeller channel. As the head decreases, the pressure at the impeller and guide vane positions decreases gradually, and the flow rate increases. Based on the entropy production principle, the wall entropy production and the distribution of mainstream entropy production at the impeller and guide vane parts are analyzed

Expression quantitative trait locus studies in the era of single-cell omics

Genome-wide association studies have revealed that the regulation of gene expression bridges genetic variants and complex phenotypes. Profiling of the bulk transcriptome coupled with linkage analysis (expression quantitative trait locus (eQTL) mapping) has advanced our understanding of the relationship between genetic variants and gene regulation in the context of complex phenotypes. However, bulk transcriptomics has inherited limitations as the regulation of gene expression tends to be cell-type-specific. The advent of single-cell RNA-seq technology now enables the identification of the cell-type-specific regulation of gene expression through a single-cell eQTL (sc-eQTL). In this review, we first provide an overview of sc-eQTL studies, including data processing and the mapping procedure of the sc-eQTL. We then discuss the benefits and limitations of sc-eQTL analyses. Finally, we present an overview of the current and future applications of sc-eQTL discoveries

SiRA: Sparse Mixture of Low Rank Adaptation

Parameter Efficient Tuning has been an prominent approach to adapt the Large Language Model to downstream tasks. Most previous works considers adding the dense trainable parameters, where all parameters are used to adapt certain task. We found this less effective empirically using the example of LoRA that introducing more trainable parameters does not help. Motivated by this we investigate the importance of leveraging "sparse" computation and propose SiRA: sparse mixture of low rank adaption. SiRA leverages the Sparse Mixture of Expert(SMoE) to boost the performance of LoRA. Specifically it enforces the top $k$ experts routing with a capacity limit restricting the maximum number of tokens each expert can process. We propose a novel and simple expert dropout on top of gating network to reduce the over-fitting issue. Through extensive experiments, we verify SiRA performs better than LoRA and other mixture of expert approaches across different single tasks and multitask settings