Augmented Arnoldi-Tikhonov Regularization Methods for Solving Large-Scale Linear Ill-Posed Systems

We propose an augmented Arnoldi-Tikhonov regularization method for the solution of large-scale linear ill-posed systems. This method augments the Krylov subspace by a user-supplied low-dimensional subspace, which contains a rough approximation of the desired solution. The augmentation is implemented by a modified Arnoldi process. Some useful results are also presented. Numerical experiments illustrate that the augmented method outperforms the corresponding method without augmentation on some real-world examples

CM-CASL: Comparison-based Performance Modeling of Software Systems via Collaborative Active and Semisupervised Learning

Configuration tuning for large software systems is generally challenging due to the complex configuration space and expensive performance evaluation. Most existing approaches follow a two-phase process, first learning a regression-based performance prediction model on available samples and then searching for the configurations with satisfactory performance using the learned model. Such regression-based models often suffer from the scarcity of samples due to the enormous time and resources required to run a large software system with a specific configuration. Moreover, previous studies have shown that even a highly accurate regression-based model may fail to discern the relative merit between two configurations, whereas performance comparison is actually one fundamental strategy for configuration tuning. To address these issues, this paper proposes CM-CASL, a Comparison-based performance Modeling approach for software systems via Collaborative Active and Semisupervised Learning. CM-CASL learns a classification model that compares the performance of two given configurations, and enhances the samples through a collaborative labeling process by both human experts and classifiers using an integration of active and semisupervised learning. Experimental results demonstrate that CM-CASL outperforms two state-of-the-art performance modeling approaches in terms of both classification accuracy and rank accuracy, and thus provides a better performance model for the subsequent work of configuration tuning

A Three-Dimensional Tight-Binding Model and Magnetic Instability of KFe2e2

For a newly discovered iron-based high T_c superconducting parent material KFe2Se2, we present an effective three-dimensional five-orbital tight-binding model by fitting the band structures. The three t2g-symmetry orbitals of the five Fe 3d orbitals mainly contribute to the electron-like Fermi surface, in agreement with recent angle-resolved photoemission spectroscopy experiments. To understand the groundstate magnetic structure, the two- and three-dimensional dynamical spin susceptibilities within the random phase approximation are investigated. It obviously shows a sharp peak at wave vector $\mathbf{Q}$ $\thicksim$ ($\pi$, $\pi$), indicating the magnetic instability of {\it N$\acute{e}$el}-type antiferromagnetic rather than ($\pi$/2, $\pi$/2)-type antiferromagnetic ordering. While along \emph{c} axis, it exhibits a ferromagnetic coupling between the nearest neighboring FeSe layers. The difference between the present results and the experimental observation in KxFe2-ySe2 is attributed to the presence of Fe vacancy in the latter.Comment: 14 pages, 8 figure

Experimental Investigation of Forchheimer Coefficients for Non-Darcy Flow in Conglomerate-Confined Aquifer

The research is financially supported by the National Key Research and Development Program of China (No. 2016YFC0801401 and No. 2016YFC0600708), Major Consulting Project of Chinese Academy of Engineering (No. 2017-ZD-2), Yue Qi Distinguished Scholar Project of China University of Mining & Technology (Beijing), and Fundamental Research Funds for the Central Universities (No. 2009QM01).Peer reviewedPublisher PD

Bis{μ-1,3-bis­[(benzimidazol-1-yl)meth­yl]benzene-κ2 N 3:N 3′}bis­[dichloridozinc(II)] dimethyl­formamide disolvate

In the title compound, [Zn2Cl4(C22H18N4)2]·2C3H7NO, the 1,3-bis­[(benzimidazol-1-yl)meth­yl]benzene ligand bridges two ZnCl2 units, forming a centrosymmetric dinuclear mol­ecule. The ZnII atom shows a distorted tetra­hedral coordination within a Cl2N2 donor set

Poly[[μ4-tartrato-cadmium(II)] 0.167-hydrate]

The title compound, {[Cd(C4H4O6)]·0.167H2O}n, adopts a three-dimensional network structure in which each CdII ion is chelated by two pairs of carboxyl­ate and hydroxyl O atoms from two tartrate anions, and is additionally linked to two O atoms of two carboxyl­ate groups that are not involved in chelation. The asymmetric unit has four independent cadmium atoms, two of which lie on special positions of 2 site symmetry. The tartrate anions all lie on general positions. All hydroxyl groups are engaged in O—H⋯O hydrogen-bonds, one of which is also bifurcated. The non-coordinating water molecule is situated on a site with half-occupation

Genetic characterization of H1N2 influenza a virus isolated from sick pigs in Southern China in 2010

In China H3N2 and H1N1 swine influenza viruses have been circulating for many years. In January 2010, before swine were infected with foot and mouth disease in Guangdong, some pigs have shown flu-like symptoms: cough, sneeze, runny nose and fever. We collected the nasopharyngeal swab of all sick pigs as much as possible. One subtype H1N2 influenza viruses were isolated from the pig population. The complete genome of one isolate, designated A/swine/Guangdong/1/2010(H1N2), was sequenced and compared with sequences available in GenBank. The nucleotide sequences of all eight viral RNA segments were determined, and then phylogenetic analysis was performed using the neighbor-joining method. HA, NP, M and NS were shown to be closely to swine origin. PB2 and PA were close to avian origin, but NA and PB1were close to human origin. It is a result of a multiple reassortment event. In conclusion, our finding provides further evidence about the interspecies transmission of avian influenza viruses to pigs and emphasizes the importance of reinforcing swine influenza virus (SIV) surveillance, especially before the emergence of highly pathogenic FMDs in pigs in Guangdong

Amniotic fluid-derived mesenchymal stem cells as a novel therapeutic approach in the treatment of fulminant hepatic failure in rats

As a potential alternative treatment for terminal liver diseases, amniotic fluid derived mesenchymal stem cells (AFMSCs) have many advantages over other stem cells: avoiding much ethical controversy and decrease in both quantity and differentiation potential with age. However, the therapeutic role of AFMSC for fulminant hepatic failure (FHF) has not yet been clearly elucidated. Therefore, we investigated the reparation effects of transplanted AFMSCs in rats with FHF. AFMSCs were transplanted into injured liver via the portal vein in the rat FHF model. Therapeutic effect was evaluated after cell transfusion by histologic pathology, hepatic enzyme levels and animal survival. Cryostat sections were prepared and directly assessed for green fluorescent protein (GFP) expression and localization, and in vivo differentiation of AFMSC was confirmed by double-immunostaining analyses. Our results show that AFMSCs prevented liver failure and reduced mortality in rats with FHF. These animals also exhibited improved liver function and animals survival after injection with AFMSCs using GFP, we demonstrated that the engrafted cells and their progeny incorporated into injured livers and produced albumin. We found that AFMSCs transplantation modestly promoted the repair of FHF in rats. AFMSCs implanted in the injured liver may be a novel therapeutic approach in the treatment of FHF.Key words: Amniotic fluid-derived mesenchymal stem cells, fulminant hepatic failure, cell transplantation, treatment, hepatogenic differentiation

Hippocampal Subregion and Gene Detection in Alzheimer’s Disease Based on Genetic Clustering Random Forest

The distinguishable subregions that compose the hippocampus are differently involved in functions associated with Alzheimer's disease (AD). Thus, the identification of hippocampal subregions and genes that classify AD and healthy control (HC) groups with high accuracy is meaningful. In this study, by jointly analyzing the multimodal data, we propose a novel method to construct fusion features and a classification method based on the random forest for identifying the important features. Specifically, we construct the fusion features using the gene sequence and subregions correlation to reduce the diversity in same group. Moreover, samples and features are selected randomly to construct a random forest, and genetic algorithm and clustering evolutionary are used to amplify the difference in initial decision trees and evolve the trees. The features in resulting decision trees that reach the peak classification are the important "subregion gene pairs". The findings verify that our method outperforms well in classification performance and generalization. Particularly, we identified some significant subregions and genes, such as hippocampus amygdala transition area (HATA), fimbria, parasubiculum and genes included RYR3 and PRKCE. These discoveries provide some new candidate genes for AD and demonstrate the contribution of hippocampal subregions and genes to AD