A Pyrrole-Based Triazolium-Phane with Nh and Cationic Ch Donor Groups as a Receptor for Tetrahedral Oxyanions that Functions in Polar Media

The pyrrole-based triazolium-phane 1(4+)center dot 4BF(4)(-) has been prepared via the tetraalkylation of a macrocycle originally prepared via click chemistry. It displays a high selectivity for tetrahedral oxyanions relative to various test monoanions and trigonal planar anions in mixed polar organic-aqueous media. This selectivity is solvent dependent and is less pronounced in acetonitrile. Theoretical calculations were carried out in with the chloride anion in an effort to understand the influence of solvent on the intrinsic hydrogen bonding ability of the donor groups (pyrrole N-H, benzene C-H and triazolium C-H). The host-guest interactions between receptor 1(4+)center dot 4BF(4)(-) and representative tetrahedral oxyanions were further analysed by H-1 NMR spectroscopy, and the findings proved consistent with the differences in the intrinsic strength of the various H-bond donor groups inferred from the electronic structure calculations carried out in methanol, namely that (CH)(+)-anion interactions are less important in an energetic sense than neutral CH-anion interactions in polar media. Single crystal X-ray diffraction analyses of the mixed salts 1(4+)center dot HP2O73-center dot BF4- and 31(4+)center dot 4H(2)PO(4)(-)center dot 8BF(4)(-) confirmed that receptor 1(4+) can bind the pyrophosphate and phosphate anions in the solid state.Cai, Jiajia, Benjamin P. Hay, Neil J. Young, Xiaoping Yang, and Jonathan L. Sessler. "A pyrrole-based triazolium-phane with NH and cationic CH donor groups as a receptor for tetrahedral oxyanions that functions in polar media." Chemical Science 4, no. 4 (Jan., 2013): 1560-1567.Chemistr

Turning a nickelate Fermi surface into a cuprate-like one through heterostructuring

Using the local density approximation and its combination with dynamical mean-field theory, we show that electronic correlations induce a single-sheet, cuprate-like Fermi surface for hole-doped 1/1 LaNiO3 /LaAlO3 heterostructures, even though both eg orbitals contribute to it. The Ni 3d 3z^2-1 orbital plays the role of the axial Cu 4s-like orbital in the cuprates. These two results indicate that "orbital engineering" by means of heterostructuring should be possible. As we also find strong antiferromagnetic correlations, the low-energy electronic and spin excitations in nickelate heterostructures resemble those of high-temperature cuprate superconductors.Comment: 4 pages, 3 figure

The Critical Rotation of Strange Stars and Rapidly Rotating Pulsars

We utilize the bulk viscosity of interacting strange quark matter to reevaluate the damping time scale. The presence of medium effect of bulk viscosity leads to a stronger damping of r-modes, which can be over an order of magnitude for realistic parameters. We find that the r-mode instability window is narrowed due to the medium effect, and hence when a pulsar reaches the instability window it will only slow down by gravitational wave emission to a period of 1.78msec instead of 2.5msec given by early estimate. As a theoretical upper rotation limit of pulsars, the period of 1.78msec is very close to the two most rapidly spinning pulsars known, with periods of about 1.6msec.Comment: 10pages,5figure

Finite-time trajectory tracking control for rigid 3-DOF manipulators with disturbances

This paper addresses the robust finite time trajectory tracking control problem for a rigid three-degrees-of-freedo

Optimal scheduling of microgrid with distributed power based on water cycle algorithm

Microgrid, taking advantage of distributed power generation technology, plays an important role in maximizing the utilization of renewable energy. Based on the problems of the energy crisis, environmental contamination and the high operating cost of the microgrid, the microgrid model can effectively ease energy pressure.We can dispatch the output of each part in the microgrid to obtain the optimal economy. Since many traditional optimization algorithms have limitations of local optimization, multiple iterations, and slow convergence speed, this paper proposes a method that applies the Water Cycle Algorithm (WCA) to optimize the dispatch of the microgrid to minimize the operating cost. The mathematical model of each distributed power is established. The interactive power between the microgrid and large grid is also considered. The lowest generation cost considering environmental benefits is taken as the objective function. Water cycle algorithm is implemented to obtain the optimal solution under various constraints. Some optimization algorithms such as Genetic Algorithm (GA), Interior Search Algorithm (ISA), and Differential Search Algorithm (DSA) were used for results evaluation. By comparing the results obtained from four different algorithms, a case study shows the WCA possesses the advancements of better convergence performance, faster calculation and higher precision compared to the other algorithms. The results demonstrate that the WCA applied to determine the optimal scheduling of the microgrid can achieve a better result than some other algorithms with an acceptable accuracy and efficiency

Point Primitives Based Virtual Surgery System

In order to achieve a high degree of visual realism in surgery simulation, we present a virtual surgery system framework, which is based on point primitives for the virtual surgery scene rendering and the biomechanical calculation of the soft tissue. To embody the superiority of this framework, two virtual surgery systems based on point primitives we developed are exhibited in this paper. Six critical functional modules were selected as representative of basic and advanced virtual surgery skill. These modules were: 1) point-based texture mapping; 2) deformation simulation; 3) cutting simulation; 4) tearing simulation; 5) dynamic texture mapping; and 6) 3-D display. These modules were elaborated by including working principle, execution process, and the performance of the algorithm. The experimental results have shown that point primitives-based virtual surgery systems obtained higher performance in terms of computational efficiency and rendering effect than traditional meshes-based virtual surgery system

An enhanced brain storm sine cosine algorithm for global optimization problems

The conventional sine cosine algorithm (SCA) does not appropriately balance exploration and exploitation, causing premature convergence, especially for complex optimization problems, such as the complex shifted or shifted rotated problems. To address this issue, this paper proposes an enhanced brain storm SCA (EBS-SCA), where an EBS strategy is employed to improve the population diversity, and by combining it with two different update equations, two new individual update strategies [individual update strategies (IUS): IUS-I and IUS-II] are developed to make effective balance between exploration and exploitation during the entire iterative search process. Double sets of benchmark suites involving 46 popular functions and two real-world problems are employed to compare the EBS-SCA with other metaheuristic algorithms. The experimental results validate that the proposed EBS-SCA achieves the overall best performance including the global search ability, convergence speed, and scalability

A Vector Grouping Learning Brain Storm Optimization Algorithm for Global Optimization Problems

The original brain storm optimization (BSO) method does not rationally compromise global exploration and local exploitation capability, which results in the premature convergence when solving complicated optimization problems like the shifted or shifted rotated functions. To address this problem, the paper develops a vector grouping learning BSO (VGLBSO) method. In VGLBSO, the individuals’ creation based on vector grouping learning (IC-VGL) scheme is first developed to improve the population diversity and compromise the global exploration and local exploitation capability. Moreover, a hybrid individuals’ update (H-IU) scheme is established by reasonably combing two different individuals’ update schemes, which further compromises the global exploration and local exploitation capability. Finally, the random grouping (RG) scheme, instead of K-means grouping is allowed to shrink the computational cost and maintain the diversity of the information exchange between different individuals. Twenty-eight popular benchmark functions are used to compare VGLBSO with 12 BSO and nine swarm intelligence methods. Experimental results present that VGLBSO achieves the best overall performance including the global search ability, convergence speed, and scalability amongst all the compared algorithms