86 research outputs found

    Priority-Based Synchronization of Distributed Data

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    We consider the general problem of synchronizing the data on two devices using a minimum amount of communication, a core infrastructural requirement for a large variety of distributed systems. Our approach considers the interactive synchronization of prioritized data, where, for example, certain information is more time-sensitive than other information. We propose and analyze a new scheme for efficient priority-based synchronization, which promises benefits over conventional synchronization

    Prioritized data synchronization with applications

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    We are interested on the problem of synchronizing data on two distinct devices with differed priorities using minimum communication. A variety of distributed sys- tems require communication efficient and prioritized synchronization, for example, where the bandwidth is limited or certain information is more time sensitive than others. Our particular approach, P-CPI, involving the interactive synchronization of prioritized data, is efficient both in communication and computation. This protocol sports some desirable features, including (i) communication and computational com- plexity primarily tied to the number of di erences between the hosts rather than the amount of the data overall and (ii) a memoryless fast restart after interruption. We provide a novel analysis of this protocol, with proved high-probability performance bound and fast-restart in logarithmic time. We also provide an empirical model for predicting the probability of complete synchronization as a function of time and symmetric differences. We then consider two applications of our core algorithm. The first is a string reconciliation protocol, for which we propose a novel algorithm with online time com- plexity that is linear in the size of the string. Our experimental results show that our string reconciliation protocol can potentially outperform existing synchroniza- tion tools such like rsync in some cases. We also look into the benefit brought by our algorithm to delay-tolerant networks(DTNs). We propose an optimized DTN routing protocol with P-CPI implemented as middleware. As a proof of concept, we demonstrate improved delivery rate, reduced metadata and reduced average delay

    Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

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    The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality

    Resveratrol reduces inflammatory response and detrimental effects in chronic cerebral hypoperfusion by down-regulating stimulator of interferon genes/TANK-binding kinase 1/interferon regulatory factor 3 signaling

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    Inflammatory responses induced by chronic cerebral hypoperfusion (CCH) play a critical role in the progression of vascular dementia. Stimulator of interferon genes (STING) signaling function as a key mediator of inflammation and immunological responses in the central nervous system (CNS), and resveratrol (RES) exerts potent anti-inflammatory effects. However, the role of STING signaling and the relationship between RES and STING signaling in persistent hypoperfusion-induced cerebral inflammation remain unclear. In this study, Sprague–Dawley rats were subjected to either Sham or bilateral common carotid artery occlusion (2VO) surgery and received RES or vehicle daily by intraperitoneal injection for 4 or 8 weeks. Morris’s water maze was used for the analysis of cognitive function. The neuroinflammatory responses in white matter and hippocampus of the rat brain were assessed by Western blot, Immunofluorescence staining, and qRT-PCR analyses. Myelin integrity, neutrophil infiltration, and microglia proliferation were assessed by Immunohistochemistry and histologic analysis. We demonstrated that after CCH, neurons, microglia, and astrocyte under endoplasmic reticulum (ER) stress upregulated the expression of STING, TANK-binding kinase 1 (TBK1), and the transcription factor interferon regulatory factor 3 (IRF3), as well as translocation of IRF3 into the nucleus. These were accompanied by infiltration of neutrophils, activation of microglia, and overproduction of proinflammatory mediators. Improvements in cognitive deficits were related to reduced hippocampal neuronal cell death and increased myelin integrity in RES-treated rats. The neuroprotective effects of RES were associated with suppression of the expression of tumor necrosis factor-alpha (TNF-α), intercellular adhesion molecule 1 (ICAM-1), VCAM-1, interferon-β (IFN-β), and IL-1β, likely through mitigation of the STING/TBK1/IRF3 pathway. These inhibitory effects exerted by RES also inhibited the levels of myeloperoxidase, reduced excess expression of reactive astrocytes, and activated microglia. In conclusion, the STING/TBK1/IRF3 axis may be critical for proinflammatory responses in cerebral tissue with persistent hypoperfusion, and RES exerts its anti-inflammatory effects by suppressing STING/TBK1/IRF3 signaling

    Towards Predicting Equilibrium Distributions for Molecular Systems with Deep Learning

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    Advances in deep learning have greatly improved structure prediction of molecules. However, many macroscopic observations that are important for real-world applications are not functions of a single molecular structure, but rather determined from the equilibrium distribution of structures. Traditional methods for obtaining these distributions, such as molecular dynamics simulation, are computationally expensive and often intractable. In this paper, we introduce a novel deep learning framework, called Distributional Graphormer (DiG), in an attempt to predict the equilibrium distribution of molecular systems. Inspired by the annealing process in thermodynamics, DiG employs deep neural networks to transform a simple distribution towards the equilibrium distribution, conditioned on a descriptor of a molecular system, such as a chemical graph or a protein sequence. This framework enables efficient generation of diverse conformations and provides estimations of state densities. We demonstrate the performance of DiG on several molecular tasks, including protein conformation sampling, ligand structure sampling, catalyst-adsorbate sampling, and property-guided structure generation. DiG presents a significant advancement in methodology for statistically understanding molecular systems, opening up new research opportunities in molecular science.Comment: 80 pages, 11 figure

    The north–south shift of the ridge location of the western Pacific subtropical high and its influence on the July precipitation in the Jianghuai region from 1978 to 2021

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    The Jianghuai region is the area between the Yangtze River and the Huai River in China and is a densely populated agriculture region therefore, the economics and human activity there are significantly affected by the precipitation changes, particularly during the summer when extreme storms and droughts normally occur. It will be helpful if the summer precipitation changes can be predicted. The monthly ERA5 atmospheric reanalysis data from 1978 to 2021 are used in this study to investigate the relationship between the ridge latitudinal location of the western Pacific subtropical high (WPSH) and the precipitation in July over the Jianghuai region. The results show that the WPSH ridge location has an important impact on the amount and spatial distribution of the precipitation in this region. When the ridge was northward, an anomalous anticyclonic circulation will appear over the western Pacific, leading to the weakening of the summer monsoon and the reduction of moisture transport from the Indian Ocean, therefore decreasing precipitation in the Jianghuai region, while the situation is opposite when the ridge was southward. The Niño 3.4 index in March and the India–Burma trough intensity index in June have significant correlations with the July WPSH ridge location, and both can be used as precursors to predict the WPSH ridge location and, therefore, the precipitation in this region

    Overview to the Hard X-ray Modulation Telescope (Insight-HXMT) Satellite

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    As China's first X-ray astronomical satellite, the Hard X-ray Modulation Telescope (HXMT), which was dubbed as Insight-HXMT after the launch on June 15, 2017, is a wide-band (1-250 keV) slat-collimator-based X-ray astronomy satellite with the capability of all-sky monitoring in 0.2-3 MeV. It was designed to perform pointing, scanning and gamma-ray burst (GRB) observations and, based on the Direct Demodulation Method (DDM), the image of the scanned sky region can be reconstructed. Here we give an overview of the mission and its progresses, including payload, core sciences, ground calibration/facility, ground segment, data archive, software, in-orbit performance, calibration, background model, observations and some preliminary results.Comment: 29 pages, 40 figures, 6 tables, to appear in Sci. China-Phys. Mech. Astron. arXiv admin note: text overlap with arXiv:1910.0443

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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