•A nonlinear attachment-detachment model with hysteresis is proposed.•Introducing scanning desorption isotherms to model the deposition effect.•Static deposition and pulse injection tests are ...utilized to calibrate the parameters.
In this study, we propose a nonlinear attachment-detachment model with hysteresis for the transport of suspension-colloidal particles (SPs) in porous media. The proposed model uses an adsorption function and scanning desorption isotherms to model the deposition process of SPs. This model shows that increasing or decreasing the seepage velocity results in substantial changes in the penetration concentration of SPs, which is closely related to the adsorption hysteresis and the deposition dynamics of SPs. Studies show that previous linear attachment-detachment models probably result in an overestimation of the adsorption capacity of porous media. Static deposition tests and dynamic transport experiments using pulse injection were performed to calibrate the transport parameters. The effects of the seepage velocity, injection concentration and particle size on the transport parameters and reaction rate constant were investigated. Experiments were also performed under variable injection concentrations and seepage velocities. The results show that there is good agreement between the simulated and experimental breakthrough curves (BTCs).
Geo-environmental disturbances refer to the significant changes in physical, mechanical, and even chemical properties of soils; are closely related to interrelated multi-physical field coupling ...systems of solid particles, water, and gas in the shallow stratum; and are caused by underground engineering construction ...
Mice are widely used as experimental models for gut microbiome (GM) studies, yet the majority of mouse GM members remain uncharacterized. Here, we report the construction of a mouse gut microbial ...biobank (mGMB) that contains 126 species, represented by 244 strains that have been deposited in the China General Microorganism Culture Collection. We sequence and phenotypically characterize 77 potential new species and propose their nomenclatures. The mGMB includes 22 and 17 species that are significantly enriched in ob/ob and wild-type C57BL/6J mouse cecal samples, respectively. The genomes of the 126 species in the mGMB cover 52% of the metagenomic nonredundant gene catalog (sequence identity ≥ 60%) and represent 93-95% of the KEGG-Orthology-annotated functions of the sampled mouse GMs. The microbial and genome data assembled in the mGMB enlarges the taxonomic characterization of mouse GMs and represents a useful resource for studies of host-microbe interactions and of GM functions associated with host health and diseases.
Soil pollution and disposal technology is currently a hot topic in geo-environmental engineering that involves the interaction mechanisms, migration processes, and treatment measures of various types ...of pollutants (e ...
The aberrancy of U1 small nuclear ribonucleoprotein (snRNP) complex and RNA splicing has been demonstrated in Alzheimer's disease (AD). Importantly, the U1 proteopathy is AD-specific, widespread and ...early-occurring, thus providing a very unique clue to the AD pathogenesis. The prominent feature of U1 histopathology is its nuclear depletion and redistribution in the neuronal cytoplasm. According to the preliminary data, the initial U1 cytoplasmic distribution pattern is similar to the subcellular translocation of the spliceosome in cells undergoing mitosis. This implies that the U1 mislocalization might reflect the neuronal cell cycle-reentry (CCR) which has been extensively evidenced in AD brains. The CCR phenomenon explains the major molecular and cellular events in AD brains, such as Tau and amyloid precursor protein (APP) phosphorylation, and the possible neuronal death through mitotic catastrophe (MC). Furthermore, the CCR might be mechanistically linked to inflammation, a critical factor in the AD etiology according to the genetic evidence. Therefore, the discovery of U1 aberrancy might strengthen the involvement of CCR in the AD neuronal degeneration.
The smoothed particle hydrodynamics (SPH) method was employed to simulate the heat transfer process in porous media at the pore scale. The effective thermal conductivity of a porous medium can be ...predicted through a simulation experiment of SPH. The accuracy of the SPH simulation experiment was verified by comparing the predicted values with reference values for ideal homogeneous media and multiphase layered media. 3D simulation experiments were implemented in granular media generated by the PFC method. Based on the SPH framework, a concise method was proposed to produce unsaturated media by simulating the wetting process in dry media. This approach approximates the formation of liquid bridges and water films on granules. Through simulation experiments, the empirical formula of the variation in thermal conductivity with the degree of saturation was tested. The results showed that the reciprocal of the normalized thermal conductivity and the reciprocal of the saturation are linearly related, which is in line with the empirical formula proposed by Cote and Konrad.
A class-agnostic tracker typically consists of three key components, i.e., its motion model, its target appearance model, and its updating strategy. However, most recent top-performing trackers ...mainly focus on constructing complicated appearance models and updating strategies, while using comparatively simple and heuristic motion models that may result in an inefficient search and degrade the tracking performance. To address this issue, we propose a hierarchical tracker that learns to move and track based on the combination of data-driven search at the coarse level and coarse-to-fine verification at the fine level. At the coarse level, a data-driven motion model learned from deep recurrent reinforcement learning provides our tracker with coarse localization of an object. By formulating motion search as an action-decision problem in reinforcement learning, our tracker utilizes a recurrent convolutional neural network-based deep Q-network to effectively learn data-driven searching policies. The learned motion model can not only significantly reduce the search space but also provide more reliable interested regions for further verifying. At the fine level, a kernelized correlation filter (KCF)-based appearance model is adopted to densely yet efficiently verify a local region centered on the predicted location from the motion model. Through use of circulant matrices and fast Fourier transformation, a large number of candidate samples in the local region can be efficiently and effectively evaluated by the KCF-based appearance model. Finally, a simple yet robust estimator is designed to analyze possible tracking failure. The experiments on OTB50 and OTB100 illustrate that our tracker achieves better performance than the state-of-the-art trackers.
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Pyroptosis is a form of programmed cell death activated by various stimuli and is characterized by inflammasome assembly, membrane pore formation, and the secretion of inflammatory ...cytokines (IL-1β and IL-18). Atherosclerosis-related risk factors, including oxidized low-density lipoprotein (ox-LDL) and cholesterol crystals, have been shown to promote pyroptosis through several mechanisms that involve ion flux, ROS, endoplasmic reticulum stress, mitochondrial dysfunction, lysosomal rupture, Golgi function, autophagy, noncoding RNAs, post-translational modifications, and the expression of related molecules. Pyroptosis of endothelial cells, macrophages, and smooth muscle cells in the vascular wall can induce plaque instability and accelerate atherosclerosis progression. In this review, we focus on the pathogenesis, influence, and therapy of pyroptosis in atherosclerosis and provide novel ideas for suppressing pyroptosis and the progression of atherosclerosis.
•Extract both the mean and trend features based on Symbolic Aggregate approXimation.•Design single classifier based on both the mean and trend features.•Construct ensemble classifier by multi-feature ...dictionary and ensemble learning.•Experiments on real datasets verify effectiveness of our proposal.
Time series classification is an important task for mining time series data, and many high level representations of time series have been proposed to address it. Symbolic Aggregate approXimation (SAX) is a classic high level symbolic representation method which can effectively reduce the dimensionality of time series. However, SAX-based methods for time series classification cannot achieve promising results, because SAX only extracts the mean feature of subsequence to make symbolization. In this paper, we present a novel ensemble method based on SAX called TBOPE, which is based on multi-feature dictionary representation and ensemble learning. Specifically, we first extract both the mean feature and trend feature of time series. Second, we create the histograms of two kinds of feature based on the Bag-of-Feature mode and construct multiple single classifiers. Finally, we build an ensemble classifier to improve the classification performance. Experimental results on various time series datasets have shown that the proposed method is competitive to state-of-the-art methods.
The main purpose of this study is to experimentally investigate the effect of temperature on the seepage transport of suspended particles (SP) with a median diameter of 10–47 μm in a porous medium ...for various seepage velocities. The results show that the rise of temperature accelerates the irregular movements of SPs in the porous medium and reduces their migration velocity. As a result, the pore volume corresponding to the peak value of the breakthrough curves is apparently delayed, and the peak value in the effluent is decreased. The migration velocity of SPs decreases with increasing particle size, regardless of the Darcy velocity and temperature. The longitudinal dispersivity of SPs decreases slightly with increasing temperature and then remains almost unchanged. Larger particles experience more irregular movements induced by the limit of pore size, which leads to a larger dispersivity. The deposition coefficient increases with increasing temperature, especially in the case of a high seepage velocity, and then tends to be stable. The deposition coefficient for large‐sized particles is higher than that for small‐sized particles, which can be attributed to the restriction of large‐sized particles by the narrow pores in the porous medium. The recovery rate decreases slightly with the increase of temperature until a critical value is reached, beyond which it remains almost unchanged. In summary, temperature is a significant factor affecting the transport and deposition of SPs in the porous medium, and the transport parameters such as particle velocity, dispersivity, and deposition coefficient.
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