CCD photometric study of the W UMa-type binary II CMa in the field of Berkeley 33

The CCD photometric data of the EW-type binary, II CMa, which is a contact star in the field of the middle-aged open cluster Berkeley 33, are presented. The complete R light curve was obtained. In the present paper, using the five CCD epochs of light minimum (three of them are calculated from Mazur et al. (1993)'s data and two from our new data), the orbital period P was revised to 0.22919704 days. The complete R light curve was analyzed by using the 2003 version of W-D (Wilson-Devinney) program. It is found that this is a contact system with a mass ratio $q=0.9$ and a contact factor $f=4.1$. The high mass ratio ($q=0.9$) and the low contact factor ($f=4.1$) indicate that the system just evolved into the marginal contact stage

Contrasting response of coexisting plant's water-use patterns to experimental precipitation manipulation in an alpine grassland community of Qinghai Lake watershed, China

Understanding species-specific changes in water-use patterns under recent climate scenarios is necessary to predict accurately the responses of seasonally dry ecosystems to future climate. In this study, we conducted a precipitation manipulation experiment to investigate the changes in water-use patterns of two coexisting species (Achnatherum splendens and Allium tanguticum) to alterations in soil water content (SWC) resulting from increased and decreased rainfall treatments. The results showed that the leaf water potential (Psi) of A. splendens and A. tanguticum responded to changes in shallow and middle SWC at both the control and treatment plots. However, A. splendens proportionally extracted water from the shallow soil layer (0-10cm) when it was available but shifted to absorbing deep soil water (30-60 cm) during drought. By contrast, the A. tanguticum did not differ significantly in uptake depth between treatment and control plots but entirely depended on water from shallow soil layers. The flexible water-use patterns of A. splendens may be a key factor facilitating its dominance and it better acclimates the recent climate change in the alpine grassland community around Qinghai Lake

Approximate Equivalence of the Hybrid Automata with Taylor Theory

Hybrid automaton is a formal model for precisely describing a hybrid system in which the computational processes interact with the physical ones. The reachability analysis of the polynomial hybrid automaton is decidable, which makes the Taylor approximation of a hybrid automaton applicable and valuable. In this paper, we studied the simulation relation among the hybrid automaton and its Taylor approximation, as well as the approximate equivalence relation. We also proved that the Taylor approximation simulates its original hybrid automaton, and similar hybrid automata could be compared quantitatively, for example, the approximate equivalence we proposed in the paper

Automata-Based Analysis of Stage Suspended Boom Systems

A stage suspended boom system is an automatic steeve system orchestrated by the PLC (programmable logic controller). Security and fault-recovering are two important properties. In this paper, we analyze and verify the boom system formally. We adopt the hybrid automaton to model the boom system. The forward reachability is used to verify the properties with the reachable states. We also present a case study to illustrate the feasibility of the proposed verification

Ganoderma triterpenes Protect Against Hyperhomocysteinemia Induced Endothelial-Mesenchymal Transition via TGF-β Signaling Inhibition

Endothelial dysfunction is one of the most important pathological status in hyperhomocysteinemia (HHcy) related cardiovascular diseases. Whereas, the underlying mechanisms have not been fully elucidated yet, concomitant with the absence of effective treatment. The purpose of this study was to explore the main mechanisms involved in HHcy-induced endothelial injury and identify the protective effect of Ganoderma triterpenes (GT). Bovine aortic endothelial cells (BAECs) were applied as in vitro experimental model. The small molecular inhibitors were used to explore the signalings involved in HHcy-induced endothelial injury. The experimental results provided initial evidence that HHcy led to endothelial-mesenchymal transition (EndMT). Meanwhile, TGF-β/Smad, PI3K/AKT and MAPK pathways were activated in this process, which was demonstrated by pretreatment with TGF-β RI kinase inhibitor VI SB431542, PI3K inhibitor LY294002, p38 inhibitor SB203580, and ERK inhibitor PD98059. Furthermore, it was found that GT restrained the process of HHcy-induced EndMT via reducing oxidative stress and suppressing fore mentioned pathways with further inhibiting the activity of Snail. These results implicate that there is an untapped potential for GT as a novel therapeutic candidate for HHcy-induced EndMT through alleviating oxidative stress and canonical TGF-β/Smad and non-Smad dependent signaling pathways

Experimental quantum computational chemistry with optimised unitary coupled cluster ansatz

Simulation of quantum chemistry is one of the most promising applications of quantum computing. While recent experimental works have demonstrated the potential of solving electronic structures with variational quantum eigensolver (VQE), the implementations are either restricted to nonscalable (hardware efficient) or classically simulable (Hartree-Fock) ansatz, or limited to a few qubits with large errors for the more accurate unitary coupled cluster (UCC) ansatz. Here, integrating experimental and theoretical advancements of improved operations and dedicated algorithm optimisations, we demonstrate an implementation of VQE with UCC for H_2, LiH, F_2 from 4 to 12 qubits. Combining error mitigation, we produce high-precision results of the ground-state energy with error suppression by around two orders of magnitude. For the first time, we achieve chemical accuracy for H_2 at all bond distances and LiH at small bond distances in the experiment. Our work demonstrates a feasible path towards a scalable solution to electronic structure calculation, validating the key technological features and identifying future challenges for this goal.Comment: 8 pages, 4 figures in the main text, and 29 pages supplementary materials with 16 figure

Aquaporins in Renal Diseases

Aquaporins (AQPs) are a family of highly selective transmembrane channels that mainly transport water across the cell and some facilitate low-molecular-weight solutes. Eight AQPs, including AQP1, AQP2, AQP3, AQP4, AQP5, AQP6, AQP7, and AQP11, are expressed in different segments and various cells in the kidney to maintain normal urine concentration function. AQP2 is critical in regulating urine concentrating ability. The expression and function of AQP2 are regulated by a series of transcriptional factors and post-transcriptional phosphorylation, ubiquitination, and glycosylation. Mutation or functional deficiency of AQP2 leads to severe nephrogenic diabetes insipidus. Studies with animal models show AQPs are related to acute kidney injury and various chronic kidney diseases, such as diabetic nephropathy, polycystic kidney disease, and renal cell carcinoma. Experimental data suggest ideal prospects for AQPs as biomarkers and therapeutic targets in clinic. This review article mainly focuses on recent advances in studying AQPs in renal diseases

Hybrid coevolutionary glowworm swarm optimization algorithm with simplex search method for system of nonlinear equations

In this paper, the problem of solving system of nonlinear equations is equivalently transformed into the problem of function optimization, a hybrid coevolutionary glowworm swarm optimization algorithm with simplex search method for system of nonlinear equations (HCGSOSSM) is proposed, where simplex search method is embedded to GSO, it is a local search operator, and combined with GSO to speed up the local search and then the more accurate solution can be obtained. The hybrid optimization algorithm sufficiently exerts the advantages such as group search, strong robustness and it satisfies the parallelism requests. For the problem that system of nonlinear equations has multi-solutions, it can also solve multisolutions at a time. Several numerical simulation results show that the algorithm offers an effective way to solve system of nonlinear equations, high convergence rate, high accuracy and robustness.Project supported by the National Natural Science Foundation of China(No.60873118 and 60973147), the Doctoral Fund of Ministry of Education of China(20090009110006), the Key Natural Science Foundation of Guangxi University for Nationalities (No.2010ZD008) and the Natural Science Foundation of Guangxi of China (No.2010GXNSFB013052)

Hybrid Coevolutionary Glowworm Swarm Optimization Algorithm with Simplex Search Method for System of Nonlinear Equations.

Abstract In this paper, the problem of solving system of nonlinear equations is equivalently transformed into the problem of function optimization, a hybrid coevolutionary glowworm swarm optimization algorithm with simplex search method for system of nonlinear equations (HCGSOSSM) is proposed, where simplex search method is embedded to GSO, it is a local search operator, and combined with GSO to speed up the local search and then the more accurate solution can be obtained. The hybrid optimization algorithm sufficiently exerts the advantages such as group search, strong robustness and it satisfies the parallelism requests. For the problem that system of nonlinear equations has multi-solutions, it can also solve multisolutions at a time. Several numerical simulation results show that the algorithm offers an effective way to solve system of nonlinear equations, high convergence rate, high accuracy and robustness

Hybrid coevolutionary population migration algorithm for integer programming and its application in neural network

For integer programming, there exist some difficulties and problems for the direct applications of population migration algorithm (PMA) due to the variables belonging to the set of integers. In this paper, a novel hybrid coevlutionary PMA is proposed for integer programming which evolves on the set of integer space. Several functions and its application problem simulation results show that the proposed algorithm is significantly superior to other algorithms