Approximation of Images via Generalized Higher Order Singular Value Decomposition over Finite-dimensional Commutative Semisimple Algebra

Low-rank approximation of images via singular value decomposition is well-received in the era of big data. However, singular value decomposition (SVD) is only for order-two data, i.e., matrices. It is necessary to flatten a higher order input into a matrix or break it into a series of order-two slices to tackle higher order data such as multispectral images and videos with the SVD. Higher order singular value decomposition (HOSVD) extends the SVD and can approximate higher order data using sums of a few rank-one components. We consider the problem of generalizing HOSVD over a finite dimensional commutative algebra. This algebra, referred to as a t-algebra, generalizes the field of complex numbers. The elements of the algebra, called t-scalars, are fix-sized arrays of complex numbers. One can generalize matrices and tensors over t-scalars and then extend many canonical matrix and tensor algorithms, including HOSVD, to obtain higher-performance versions. The generalization of HOSVD is called THOSVD. Its performance of approximating multi-way data can be further improved by an alternating algorithm. THOSVD also unifies a wide range of principal component analysis algorithms. To exploit the potential of generalized algorithms using t-scalars for approximating images, we use a pixel neighborhood strategy to convert each pixel to "deeper-order" t-scalar. Experiments on publicly available images show that the generalized algorithm over t-scalars, namely THOSVD, compares favorably with its canonical counterparts.Comment: 20 pages, several typos corrected, one appendix adde

Topographical and Biological Evidence Revealed FTY720-Mediated Anergy-Polarization of Mouse Bone Marrow-Derived Dendritic Cells In Vitro

Abnormal inflammations are central therapeutic targets in numerous infectious and autoimmune diseases. Dendritic cells (DCs) are involved in these inflammations, serving as both antigen presenters and proinflammatory cytokine providers. As an immuno-suppressor applied to the therapies of multiple sclerosis and allograft transplantation, fingolimod (FTY720) was shown to affect DC migration and its crosstalk with T cells. We posit FTY720 can induce an anergy-polarized phenotype switch on DCs in vitro, especially upon endotoxic activation. A lipopolysaccharide (LPS)-induced mouse bone marrow-derived dendritic cell (BMDC) activation model was employed to test FTY720-induced phenotypic changes on immature and mature DCs. Specifically, methods for morphology, nanostructure, cytokine production, phagocytosis, endocytosis and specific antigen presentation studies were used. FTY720 induced significant alterations of surface markers, as well as decline of shape indices, cell volume, surface roughness in LPS-activated mature BMDCs. These phenotypic, morphological and topographical changes were accompanied by FTY720-mediated down-regulation of proinflammatory cytokines, including IL-6, TNF-α, IL-12 and MCP-1. Together with suppressed nitric oxide (NO) production and CCR7 transcription in FTY720-treated BMDCs with or without LPS activation, an inhibitory mechanism of NO and cytokine reciprocal activation was suggested. This implication was supported by the impaired phagocytotic, endocytotic and specific antigen presentation abilities observed in the FTY720-treated BMDCs. In conclusion, we demonstrated FTY720 can induce anergy-polarization in both immature and LPS-activated mature BMDCs. A possible mechanism is FTY720-mediated reciprocal suppression on the intrinsic activation pathway and cytokine production with endpoint exhibitions on phagocytosis, endocytosis, antigen presentation as well as cellular morphology and topography

Bioinformatic prediction of possible targets and mechanisms of action of the green tea compound epigallocatechin-3-gallate against breast cancer

10.3389/fmolb.2017.00043Frontiers in Molecular Biosciences4JUN4

Green Tea (Camellia sinensis): A Review of Its Phytochemistry, Pharmacology, and Toxicology

Objectives Green tea (Camellia sinensis) is a kind of unfermented tea that retains the natural substance in fresh leaves to a great extent. It is regarded as the second most popular drink in the world besides water. In this paper, the phytochemistry, pharmacology, and toxicology of green tea are reviewed systematically and comprehensively. Key findings Green tea has been demonstrated to be good for human health. Nowadays, multiple pharmacologically active components have been isolated and identified from green tea, including tea polyphenols, alkaloids, amino acids, polysaccharides, and volatile components. Recent studies have demonstrated that green tea shows versatile pharmacological activities, such as antioxidant, anticancer, hypoglycemic, antibacterial, antiviral, and neuroprotective. Studies on the toxic effects of green tea extract and its main ingredients have also raised concerns including hepatotoxicity and DNA damage. Summary Green tea can be used to assist the treatment of diabetes, Alzheimer’s disease, oral cancer, and dermatitis. Consequently, green tea has shown promising practical prospects in health care and disease prevention

Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold Based on Integrated CatBoost-GA Model

Micro-electro-mechanical systems (MEMS) hemispherical resonant gyroscopes are used in a wide range of applications in defense technology, electronics, aerospace, etc. The surface roughness of the silicon micro-hemisphere concave molds (CMs) inside the MEMS hemispherical resonant gyroscope is the main factor affecting the performance of the gyroscope. Therefore, a new method for reducing the surface roughness of the micro-CM needs to be developed. Micro-ultrasonic machining (MUM) has proven to be an excellent method for machining micro-CMs; shear thickening fluids (STFs) have also been used in the ultra-precision polishing field due to their perfect processing performance. Ultimately, an STF-MUM polishing method that combines STF with MUM is proposed to improve the surface roughness of the micro-CM. In order to achieve the excellent processing performance of the new technology, a Categorical Boosting (CatBoost)-genetic algorithm (GA) optimization model was developed to optimize the processing parameters. The results of optimizing the processing parameters via the CatBoost-GA model were verified by five groups of independent repeated experiments. The maximum absolute error of CatBoost-GA is 7.21%, the average absolute error is 4.69%, and the minimum surface roughness is reduced by 28.72% compared to the minimum value of the experimental results without optimization

Clogging and Water Quality Change Effects of Typical Metal Pollutants under Intermittent Managed Aquifer Recharge Using Urban Stormwater

Managed aquifer recharge (MAR) using urban stormwater facilitates relieving water supply pressure, restoring the ecological environment, and developing sustainable water resources. However, compared to conventional water sources, such as river water and lake water, MAR using urban stormwater is a typically intermittent recharge mode. In order to study the clogging and water quality change effects of Fe, Zn, and Pb, the typical mental pollutants in urban stormwater, a series of intermittent MAR column experiments were performed. The results show that the type of pollutant, the particle size of the medium and the intermittent recharge mode have significant impacts on the pollutant retention and release, which has led to different clogging and water quality change effects. The metals that are easily retained in porous media have greater potential for clogging and less potential for groundwater pollution. The fine medium easily becomes clogged, but it is beneficial in preventing groundwater contamination. There is a higher risk of groundwater contamination for a shallow buried aquifer under intermittent MAR than continuous MAR, mainly because of the de-clogging effect of porous media during the intermittent period

A rational design of highly active and coke-resistant anode for methanol-fueled solid oxide fuel cells with Sn doped Ni-Ce0.8Sm0.2O2−δ

A crucial challenge in the commercialization of Ni-based materials as the anode of solid oxide fuel cell is the fast voltage drop due to carbon deposition and structural degradation during cell operation. Herein, Sn-doped Ce0.8Sm0.2O2−δ (SDC) supported Sn-Ni alloy anode is rationally designed and prepared, via a simple and convenient dual-modification strategy. The substitution of Sn of Ce in the oxide phase enhances the mobility of lattice oxygen in SDC. Meanwhile, Sn exsolves partially from the oxide phase and forms Ni3Sn and Ni3Sn2 intermetallic compounds with Ni after reduction. The composite anode thus formed achieves unprecedent activity in the electrochemical oxidation of H2 and CH3OH. The maximum power densities of a cell supported by 500 μm-thick Ce0.8Sm0.2O2−δ-carbonate electrolyte layer with the Ni-Ce0.7Sn0.1Sm0.2O2−δ (Ni-SSn10DC) anode reach 1.99 and 2.11 W cm−2 at 700 °C, respectively for using H2 and methanol as fuels. The doping of Sn also remarkably enhances the coking resistance of the anode.This work opens a path on the design of high-performance SOFC anode.Peer reviewe