228 research outputs found

    MBA: A market-based approach to data allocation and migration for cloud database

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    With the coming shift to cloud computing, cloud database is emerging to provide database service over the Internet. In the cloud-based environment, data are distributed at internet scale and the system needs to handle a huge number of user queries simultaneously without delay. How data are distributed among the servers has a crucial impact on the query load distribution and the system response time. In this paper, we propose a market-based control method, called MBA, to achieve query load balance via reasonable data distribution. In MBA, database nodes are treated as traders in a market, and certain market rules are used to intelligently decide data allocation and migration. We built a prototype system and conducted extensive experiments. Experimental results show that the MBA method signicantly improves system performance in terms of average query response time and fairness

    Learning a Condensed Frame for Memory-Efficient Video Class-Incremental Learning

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    Recent incremental learning for action recognition usually stores representative videos to mitigate catastrophic forgetting. However, only a few bulky videos can be stored due to the limited memory. To address this problem, we propose FrameMaker, a memory-efficient video class-incremental learning approach that learns to produce a condensed frame for each selected video. Specifically, FrameMaker is mainly composed of two crucial components: Frame Condensing and Instance-Specific Prompt. The former is to reduce the memory cost by preserving only one condensed frame instead of the whole video, while the latter aims to compensate the lost spatio-temporal details in the Frame Condensing stage. By this means, FrameMaker enables a remarkable reduction in memory but keep enough information that can be applied to following incremental tasks. Experimental results on multiple challenging benchmarks, i.e., HMDB51, UCF101 and Something-Something V2, demonstrate that FrameMaker can achieve better performance to recent advanced methods while consuming only 20% memory. Additionally, under the same memory consumption conditions, FrameMaker significantly outperforms existing state-of-the-arts by a convincing margin.Comment: NeurIPS 202

    DWT1/DWL2 act together with OsPIP5K1 to regulate plant uniform growth in rice

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    •Uniform growth of the main shoot and tillers significantly influences rice plant architecture and grain yield. The WUSCHEL‐related homeobox transcription factor DWT1 is a key regulator of this important agronomic trait, disruption of which causes enhanced main shoot dominance and tiller dwarfism by an unknown mechanism. •Here, we have used yeast‐two‐hybrid screening to identify OsPIP5K1, a member of the rice phosphatidylinositol‐4‐phosphate 5‐kinase family, as a protein that interacts with DWT1. Cytological analyses confirmed that DWT1 induces accumulation of OsPIP5K1 and its product PI(4,5)P2, a phosphoinositide secondary messenger, in nuclear bodies. •Mutation of OsPIP5K1 compounds the dwarf dwt1 phenotype but abolishes the main shoot dominance. Conversely, overexpression of OsPIP5K1 partially rescues dwt1 developmental defects. Furthermore, we showed that DWL2, the homologue of DWT1, is also able to interact with OsPIP5K1 and shares partial functional redundancy with DWT1 in controlling rice uniformity. •Overall, our data suggest that nuclear localised OsPIP5K1 acts with DWT1 and/or DWL2 to coordinate the uniform growth of rice shoots, likely to be through nuclear phosphoinositide signals, and provides insights into the regulation of rice uniformity via a largely unexplored plant nuclear signalling pathway

    Dexmedetomidine Ameliorates the Neurotoxicity of Sevoflurane on the Immature Brain Through the BMP/SMAD Signaling Pathway

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    Numerous studies have demonstrated that general anesthetics might damage the nervous system, thus, the effect of general anesthetics on the developing brain has attracted much attention. Dexmedetomidine (Dex) exhibits a certain neuroprotective effect, but the mechanism is obscure. In our study, pregnant rats on gestational day 20 (G20) were exposed to 3% sevoflurane for 2 h or 4 h, and the neuronal apoptosis in hippocampal CA1 region of the offspring rats was detected by quantification of TUNEL positive cells and cleaved-caspase3 (cl-caspase3). Different doses of Dex were intraperitoneally injected before sevoflurane anesthesia; then, the expression of apoptotic-related proteins including BCL-2, BAX and cl-caspase3 as well as amyloid precursor protein (APP, a marker of axonal injury), p-CRMP-2 and CRMP-2 were measured at postnatal days 0, 1and 3 (P0, P1, and P3, respectively). As an antagonist of the bone morphgenetic proteins (BMP) receptor, DMH1 was co-administered with sevoflurane plus Dex to investigate whether BMP/SMAD is associated with the neuroprotective effects of Dex. The results showed that prenatal sevoflurane anesthesia for 4 h activated apoptosis transiently, as manifested by the caspase3 activity peaked on P1 and disappeared on P3. In addition, the expressions of APP and p-CRMP-2/CRMP-2 in postnatal rat hippocampus were significantly increased, which revealed that prenatal sevoflurane anesthesia caused axonal injury of offspring. The long-term learning and memory ability of offspring rats was also impaired after prenatal sevoflurane anesthesia. These damaging effects of sevoflurane could be mitigated by Dex and DMH1 reversed the neuroprotective effect of Dex. Our results indicated that prenatal exposure to 3% sevoflurane for 4 h increased apoptosis and axonal injury, even caused long-term learning and memory dysfunction in the offspring rats. Dex dose-dependently reduced sevoflurane- anesthesia-induced the neurotoxicity by activating the BMP/SMAD signaling pathway
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