Perceptual Image Compression with Cooperative Cross-Modal Side Information

The explosion of data has resulted in more and more associated text being transmitted along with images. Inspired by from distributed source coding, many works utilize image side information to enhance image compression. However, existing methods generally do not consider using text as side information to enhance perceptual compression of images, even though the benefits of multimodal synergy have been widely demonstrated in research. This begs the following question: How can we effectively transfer text-level semantic dependencies to help image compression, which is only available to the decoder? In this work, we propose a novel deep image compression method with text-guided side information to achieve a better rate-perception-distortion tradeoff. Specifically, we employ the CLIP text encoder and an effective Semantic-Spatial Aware block to fuse the text and image features. This is done by predicting a semantic mask to guide the learned text-adaptive affine transformation at the pixel level. Furthermore, we design a text-conditional generative adversarial networks to improve the perceptual quality of reconstructed images. Extensive experiments involving four datasets and ten image quality assessment metrics demonstrate that the proposed approach achieves superior results in terms of rate-perception trade-off and semantic distortion

MB-RACS: Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network

Conventional compressed sensing (CS) algorithms typically apply a uniform sampling rate to different image blocks. A more strategic approach could be to allocate the number of measurements adaptively, based on each image block's complexity. In this paper, we propose a Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network (MB-RACS) framework, which aims to adaptively determine the sampling rate for each image block in accordance with traditional measurement bounds theory. Moreover, since in real-world scenarios statistical information about the original image cannot be directly obtained, we suggest a multi-stage rate-adaptive sampling strategy. This strategy sequentially adjusts the sampling ratio allocation based on the information gathered from previous samplings. We formulate the multi-stage rate-adaptive sampling as a convex optimization problem and address it using a combination of Newton's method and binary search techniques. Additionally, we enhance our decoding process by incorporating skip connections between successive iterations to facilitate a richer transmission of feature information across iterations. Our experiments demonstrate that the proposed MB-RACS method surpasses current leading methods, with experimental evidence also underscoring the effectiveness of each module within our proposed framework

A Hierarchical Hybrid Learning Framework for Multi-agent Trajectory Prediction

Accurate and robust trajectory prediction of neighboring agents is critical for autonomous vehicles traversing in complex scenes. Most methods proposed in recent years are deep learning-based due to their strength in encoding complex interactions. However, unplausible predictions are often generated since they rely heavily on past observations and cannot effectively capture the transient and contingency interactions from sparse samples. In this paper, we propose a hierarchical hybrid framework of deep learning (DL) and reinforcement learning (RL) for multi-agent trajectory prediction, to cope with the challenge of predicting motions shaped by multi-scale interactions. In the DL stage, the traffic scene is divided into multiple intermediate-scale heterogenous graphs based on which Transformer-style GNNs are adopted to encode heterogenous interactions at intermediate and global levels. In the RL stage, we divide the traffic scene into local sub-scenes utilizing the key future points predicted in the DL stage. To emulate the motion planning procedure so as to produce trajectory predictions, a Transformer-based Proximal Policy Optimization (PPO) incorporated with a vehicle kinematics model is devised to plan motions under the dominant influence of microscopic interactions. A multi-objective reward is designed to balance between agent-centric accuracy and scene-wise compatibility. Experimental results show that our proposal matches the state-of-the-arts on the Argoverse forecasting benchmark. It's also revealed by the visualized results that the hierarchical learning framework captures the multi-scale interactions and improves the feasibility and compliance of the predicted trajectories

Single-cell analyses reveal the dynamic functions of Itgb2+ microglia subclusters at different stages of cerebral ischemia-reperfusion injury in transient middle cerebral occlusion mice model

IntroductionThe underlying pathophysiological mechanisms of cerebral ischemia reperfusion injury (CIRI) is intricate, and current studies suggest that neuron, astrocyte, microglia, endothelial cell, and pericyte all have different phenotypic changes of specific cell types after ischemic stroke. And microglia account for the largest proportion after CIRI. Previous transcriptomic studies of ischemic stroke have typically focused on the 24 hours after CIRI, obscuring the dynamics of cellular subclusters throughout the disease process. Therefore, traditional methods for identifying cell types and their subclusters may not be sufficient to fully unveil the complexity of single-cell transcriptional profile dynamics caused by an ischemic stroke.MethodsIn this study, to explore the dynamic transcriptional profile of single cells after CIRI, we used single-cell State Transition Across-samples of RNA-seq data (scSTAR), a new bioinformatics method, to analyze the single-cell transcriptional profile of day 1, 3, and 7 of transient middle cerebral artery occlusion (tMCAO) mice. Combining our bulk RNA sequences and proteomics data, we found the importance of the integrin beta 2 (Itgb2) gene in post-modeling. And microglia of Itgb2+ and Itgb2- were clustered by the scSTAR method. Finally, the functions of the subpopulations were defined by Matescape, and three different time points after tMCAO were found to exhibit specific functions.ResultsOur analysis revealed a dynamic transcriptional profile of single cells in microglia after tMCAO and explored the important role of Itgb2 contributed to microglia by combined transcriptomics and proteomics analysis after modeling. Our further analysis revealed that the Itgb2+ microglia subcluster was mainly involved in energy metabolism, cell cycle, angiogenesis, neuronal myelin formation, and repair at 1, 3, and 7 days after tMCAO, respectively.DiscussionOur results suggested that Itgb2+ microglia act as a time-specific multifunctional immunomodulatory subcluster during CIRI, and the underlying mechanisms remain to be further investigated

The role of ERK1/2 in colitis through regulation of NADPH oxidase and mitochondrial fission

Objective To investigate the role of extracellular signal regulated kinase 1/2 （ERK1/2） in colitis through the regulation of NADPH oxidase and mitochondrial fission. Methods Mice models of acute colitis were induced by 3% dextran sulfate sodium （DSS）. Thirty C57BL/6J mice were randomly divided into six groups by random number table method： control group， 3%DSS group，1% dimethyl sulfoxide （DMSO） group， ERK1/2 inhibitor（PD98059） group， 3%DSS+1%DMSO group and 3%DSS+PD98059 group， with five mice in each group. The changes of body weight， colonic length， disease activity index and colonic histopathological changes of mice in the control and 3%DSS groups were evaluated， and the expression levels of ERK1/2， p-ERK1/2， Nicotinamide adenine dinucleotide phosphate oxidase 1 （Nox1） and Nox2 in colonic mucosa of mice were detected. Mice in 1%DMSO and 3%DSS+1%DMSO groups were intraperitoneally injected with 1%DMSO. Mice in the PD98059 and 3%DSS+PD98059 groups were intraperitoneally injected with PD98059. The colonic histopathological changes were evaluated among four groups， and the expression levels of Nox1， Nox2， Dynamin related protein 1 （DRP1）， p-DRP1-S616 and p-DRP1-S637 mitochondrial fission related proteins were detected. Mitochondrial fission of colonic epithelial cells in the control and 3%DSS groups was observed by transmission electron microscopy. The co-localization of Nox2 and mitochondrial outer membrane translocator enzyme TOM complex （TOMM20） in colonic mucosa of mice in two groups was analyzed by double-immunofluorescence staining. The correlation between relative expression levels of DRP1 and Nox2 mRNA in mouse colonic mucosa was analyzed in two groups. Results Compared with the control group， mice in the 3%DSS group exhibited body weight loss， shortened colonic length， increased disease activity index and increased colonic histopathological score. The expression levels of p-ERK1/2， Nox1， Nox2 in colonic mucosa of mice were significantly up-regulated in the 3%DSS group （all P < 0.05）. In mice with colitis， mitochondrial fission in colonic epithelial cells was increased， and the colonic mucosa co-localization of DRP1 and Nox2 was elevated， and the relative mRNA expression levels of both target genes were positively correlated （r = 0.678， P < 0.05）. ERK1/2 inhibitor PD98059 improved colonic histopathological changes in mice with colitis， and down-regulated the expression levels of Nox1， Nox2， DRP1， p-DRP1-S616 in colonic mucosa. Conclusion Inhibition of ERK1/2 may ameliorate colitis by down-regulating NADPH oxidase expression and alleviating mitochondrial fission

A Fixed-Dose Combination, QXOH/Levobupivacaine, Produces Long-Acting Local Anesthesia in Rats Without Additional Toxicity

QXOH, a QX314 derivative with longer duration and lesser local toxicity, is a novel local anesthetic in preclinical drug development. Previous studies demonstrated that bupivacaine can prolong the effects of QX314. So, we attempted to combine QXOH with levobupivacaine to shorten the onset time and lengthen the duration. In this study, we investigated the efficacy, local and systemic toxicity in rats. In subcutaneous infiltration anesthesia, the inhibition of cutaneous trunci muscle reflex for QXOH-LB was greater than QXOH and levobupivacaine in the first 8 h (QXOH-LB vs. QXOH, P = 0.004; QXOH-LB vs. LB, P = 0.004). The completely recovery time for QXOH-LB (17.5 ± 2.5 h) was significantly longer than levobupivacaine (9.0 ± 1.3 h, P = 0.034) and QXOH (9.8 ± 0.9 h, P = 0.049). In sciatic nerve block, QXOH-LB produced a rapid onset time, which was obviously shorter than QXOH. For sensory, the time to recovery for QXOH-LB was 17.3 ± 2.6 h, which was statistically longer than 6.0 ± 1.8 h for QXOH (P = 0.027), and 4 h for levobupivacaine (P = 0.001). Meanwhile, the time to motor recovery for QXOH-LB was 7.9 ± 2.8 h, significantly longer than 4 h for levobupivacaine (P = 0.003) but similar to 6.0 ± 1.7 h for QXOH (P = 0.061). In local toxicity, there was no significant difference of histological score regarding muscle and sciatic nerve in QXOH-LB, QXOH, levobupivacaine and saline (P < 0.01). In the combination, the interaction index of LD50 was 1.39, indicating antagonistic interaction between QXOH and levobupivacaine in terms of systemic toxicity. In this study, we demonstrated that QXOH-LB produced cutaneous anesthesia which was 2-fold greater than that produced by QXOH or LB alone, and elicited sciatic nerve block with a potency that was 5- and 3-fold that of LB and QXOH, respectively. Local tissue inflammation by QXOH-LB was mild, similar to that induced by LB. This fixed-dose combination led to an antagonistic interaction between QXOH and LB in terms of systemic toxicity. These results suggested that QXOH-LB induced a long-lasting local anesthesia, likely, avoiding clinically important local and systemic toxicities

No evidence for persistent natural plague reservoirs in historical and modern Europe

Caused by Yersinia pestis, plague ravaged the world through three known pandemics: the First or the Justinianic (6th–8th century); the Second (beginning with the Black Death during c.1338–1353 and lasting until the 19th century); and the Third (which became global in 1894). It is debatable whether Y. pestis persisted in European wildlife reservoirs or was repeatedly introduced from outside Europe (as covered by European Union and the British Isles). Here, we analyze environmental data (soil characteristics and climate) from active Chinese plague reservoirs to assess whether such environmental conditions in Europe had ever supported “natural plague reservoirs”. We have used new statistical methods which are validated through predicting the presence of modern plague reservoirs in the western United States. We find no support for persistent natural plague reservoirs in either historical or modern Europe. Two factors make Europe unfavorable for long-term plague reservoirs: 1) Soil texture and biochemistry and 2) low rodent diversity. By comparing rodent communities in Europe with those in China and the United States, we conclude that a lack of suitable host species might be the main reason for the absence of plague reservoirs in Europe today. These findings support the hypothesis that long-term plague reservoirs did not exist in Europe and therefore question the importance of wildlife rodent species as the primary plague hosts in Europe

Universal scaling of the critical temperature and the strange-metal scattering rate in unconventional superconductors

Dramatic evolution of properties with minute change in the doping level is a hallmark of the complex chemistry which governs cuprate superconductivity as manifested in the celebrated superconducting domes as well as quantum criticality taking place at precise compositions. The strange metal state, where the resistivity varies linearly with temperature, has emerged as a central feature in the normal state of cuprate superconductors. The ubiquity of this behavior signals an intimate link between the scattering mechanism and superconductivity. However, a clear quantitative picture of the correlation has been lacking. Here, we report observation of quantitative scaling laws between the superconducting transition temperature $T_{\rm c}$ and the scattering rate associated with the strange metal state in electron-doped cuprate $\rm La_{2-x}Ce_xCuO_4$ (LCCO) as a precise function of the doping level. High-resolution characterization of epitaxial composition-spread films, which encompass the entire overdoped range of LCCO has allowed us to systematically map its structural and transport properties with unprecedented accuracy and increment of $\Delta x = 0.0015$. We have uncovered the relations $T_{\rm c}\sim(x_{\rm c}-x)^{0.5}\sim(A_1^\square)^{0.5}$, where $x_c$ is the critical doping where superconductivity disappears on the overdoped side and $A_1^\square$ is the scattering rate of perfect $T$-linear resistivity per CuO$_2$ plane. We argue that the striking similarity of the $T_{\rm c}$ vs $A_1^\square$ relation among cuprates, iron-based and organic superconductors is an indication of a common mechanism of the strange metal behavior and unconventional superconductivity in these systems.Comment: 15 pages, 3 figure