Quantum pumping with adiabatically modulated barriers in three-band pseudospin-1 Dirac-Weyl systems

In this work, pumped currents of the adiabatically-driven double-barrier structure based on the pseudospin-1 Dirac-Weyl fermions are studied. As a result of the three-band dispersion and hence the unique properties of pseudospin-1 Dirac-Weyl quasiparticles, sharp current-direction reversal is found at certain parameter settings especially at the Dirac point of the band structure, where apexes of the two cones touches at the flat band. Such a behavior can be interpreted consistently by the Berry phase of the scattering matrix and the classical turnstile mechanism

The spectral rigidity of Ricci soliton and Einstein-type manifolds

We are concerned in this article with a classical topic in spectral geometry dating back to McKean-Singer, Patodi and Tanno: whether or not the constancy of sectional curvature (resp. holomorphic sectional curvature) of a compact Riemannian manifold (resp. K\"{a}hler manifold) can be completely determined by the eigenvalues of its $p$-Laplacian for a \emph{single} integer $p$? We treat this question under two conditions: gradient shrinking Ricci soliton for Riemannian manifolds and cohomologically Einstein for K\"{a}hler manifolds. We show that, with some sporadic unknown cases, this is true for each $p$. Furthermore, we show that the condition of being isospectral can be relaxed to a suitable almost-isospectral version.Comment: 21 pages. arXiv admin note: text overlap with arXiv:1804.0051

Prediction of yeast protein–protein interaction network: insights from the Gene Ontology and annotations

A map of protein–protein interactions provides valuable insight into the cellular function and machinery of a proteome. By measuring the similarity between two Gene Ontology (GO) terms with a relative specificity semantic relation, here, we proposed a new method of reconstructing a yeast protein–protein interaction map that is solely based on the GO annotations. The method was validated using high-quality interaction datasets for its effectiveness. Based on a Z-score analysis, a positive dataset and a negative dataset for protein–protein interactions were derived. Moreover, a gold standard positive (GSP) dataset with the highest level of confidence that covered 78% of the high-quality interaction dataset and a gold standard negative (GSN) dataset with the lowest level of confidence were derived. In addition, we assessed four high-throughput experimental interaction datasets using the positives and the negatives as well as GSPs and GSNs. Our predicted network reconstructed from GSPs consists of 40 753 interactions among 2259 proteins, and forms 16 connected components. We mapped all of the MIPS complexes except for homodimers onto the predicted network. As a result, ∼35% of complexes were identified interconnected. For seven complexes, we also identified some nonmember proteins that may be functionally related to the complexes concerned. This analysis is expected to provide a new approach for predicting the protein–protein interaction maps from other completely sequenced genomes with high-quality GO-based annotations

Responsive aqueous foams stabilized by silica nanoparticles hydrophobized in situ with a conventional surfactant

In the recent past, switchable surfactants and switchable/stimulus-responsive surface-active particles have been of great interest. Both can be transformed between surface-active and surface-inactive states via several triggers, making them recoverable and reusable afterward. However, the synthesis of these materials is complicated. In this paper we report a facile protocol to obtain responsive surface-active nanoparticles and their use in preparing responsive particle-stabilized foams. Hydrophilic silica nanoparticles are initially hydrophobized in situ with a trace amount of a conventional cationic surfactant in water, rendering them surface-active such that they stabilize aqueous foams. The latter can then be destabilized by adding equal moles of an anionic surfactant, and restabilized by adding another trace amount of the cationic surfactant followed by shaking. The stabilization–destabilization of the foams can be cycled many times at room temperature. The trigger is the stronger electrostatic interaction between the oppositely charged surfactants than that between the cationic surfactant and the negatively charged particles. The added anionic surfactant tends to form ion pairs with the cationic surfactant, leading to desorption of the latter from particle surfaces and dehydrophobization of the particles. Upon addition of another trace amount of cationic surfactant, the particles are rehydrophobized in situ and can then stabilize foams again. This principle makes it possible to obtain responsive surface-active particles using commercially available inorganic nanoparticles and conventional surfactants

Integrated energy storage and CO2 conversion using an aqueous battery with tamed asymmetric reactions

Developing a CO2-utilization and energy-storage integrated system possesses great advantages for carbon- and energy-intensive industries. Efforts have been made to developing the Zn-CO2 batteries, but access to long cycling life and low charging voltage remains a grand challenge. Here we unambiguously show such inefficiencies originate from the high-barrier oxygen evolution reaction on charge, and by recharging the battery via oxidation of reducing molecules, Faradaic efficiency-enhanced CO2 reduction and low-overpotential battery regeneration can be simultaneously achieved. Showcased by using hydrazine oxidation, our battery demonstrates a long life over 1000 hours with a charging voltage as low as 1.2 V. The low charging voltage and formation of gaseous product upon hydrazine oxidation are the key to stabilize the catalyst over cycling. Our findings suggest that by fundamentally taming the asymmetric reactions, aqueous batteries are viable tools to achieve integrated energy storage and CO2 conversion that is economical, highly energy efficient, and scalable

Topology, Vorticity and Limit Cycle in a Stabilized Kuramoto-Sivashinsky Equation

A noisy stabilized Kuramoto-Sivashinsky equation is analyzed by stochastic decomposition. For values of control parameter for which periodic stationary patterns exist, the dynamics can be decomposed into diffusive and transverse parts which act on a stochastic potential. The relative positions of stationary states in the stochastic global potential landscape can be obtained from the topology spanned by the low-lying eigenmodes which inter-connect them. Numerical simulations confirm the predicted landscape. The transverse component also predicts a universal class of vortex like circulations around fixed points. These drive nonlinear drifting and limit cycle motion of the underlying periodic structure in certain regions of parameter space. Our findings might be relevant in studies of other nonlinear systems such as deep learning neural networks.Comment: Main body: 16 pages, 3 figures; Supplementary: 14 pages, 6 figure

Elucidation of the mechanisms and molecular targets of Yiqi Shexue formula for treatment of primary immune thrombocytopenia based on network pharmacology

Yiqi Shexue formula (YQSX) is traditionally used to treat primary immune thrombocytopenia (ITP) in clinical practice of traditional Chinese medicine. However, its mechanisms of action and molecular targets for treatment of ITP are not clear. The active compounds of YQSX were collected and their targets were identified. ITP-related targets were obtained by analyzing the differential expressed genes between ITP patients and healthy individuals. Protein-protein interaction (PPI) data were then obtained and PPI networks of YQSX putative targets and ITP-related targets were visualized and merged to identify the candidate targets for YQSX against ITP. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out. The gene-pathway network was constructed to screen the key target genes. In total, 177 active compounds and 251 targets of YQSX were identified. Two hundred and thirty differential expressed genes with an P value 1 were identified between ITP patient and control groups. One hundred and eighty-three target genes associated with ITP were finally identified. The functional annotations of target genes were found to be related to transcription, cytosol, protein binding, and so on. Twenty-four pathways including cell cycle, estrogen signaling pathway, and MAPK signaling pathway were significantly enriched. MDM2 was the core gene and other several genes including TP53, MAPK1, CDKN1A, MYC, and DDX5 were the key gens in the gene-pathway network of YQSX for treatment of ITP. The results indicated that YQSX's effects against ITP may relate to regulation of immunological function through the specific biological processes and the related pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of complex herbal formulations