Mixed-ligand complexes of copper(I) with diimines and phosphines: Effective catalysts for the coupling of phenylacetylene with halobenzene

New copper(I) mixed-ligand complexes 1–4 of the formula Cu(N–N)PR₃X, where N–N = 1,10-phenanthroline (phen), 2,2′-bipyridine (bpy), 5,5′-dimethyl-2,2′-bipyridine (5,5′dimbpy) and PR₃ = tricyclohexylphosphine, tris(2-cyanoethyl)phosphine and isopropyldiphenylphosphine, have been synthesized. The complexes were characterized by EA, IR, NMR and single crystal X-ray diffraction. The solution fluorescence emission spectra were measured. The single crystal X-ray analysis showed that the copper(I) ion is four-coordinate with a distorted tetrahedral geometry. The complexes catalyze the formation of diphenylacetylene from the coupling of halobenzene with phenylacetylene. The complex Cu(5,5′-dimethylbpy)P{(cyhexyl)₃}I showed the highest catalytic activity. At room temperature all four complexes exhibit, in dichloromethane, emission maxima in the 329–344 nm range, corresponding to intra-ligand excited states.     

Albumin-conjugated corrole metal complexes: extremely simple yet very efficient biomimetic oxidation systems

An extremely simple biomimetic oxidation system, consisting of mixing metal complexes of amphiphilic corroles with serum albumins, utilizes hydrogen peroxide for asymmetric sulfoxidation in up to 74% ee. The albumin-conjugated manganese corroles also display catalase-like activity, and mechanistic evidence points toward oxidant-coordinated manganese(III) as the prime reaction intermediate.     

Inelastic scattering of electrons andE2 transition in6Li

A simple nucleon-nucleon correlation function has been included in the independent-particle shell-model (IPSM) wave functions of⁶Li. The reduced transition probability and the nuclear form factor of⁶Li as obtained from the inelastic scattering of electrons have been calculated using the correlated as well as the uncorrelated wave functions of the ground and the first excited states. The correlated transition probability and the form factor are considerably improved over the uncorrelated ones. The correlated form factor is more consistent with the experimental data than the uncorrelated one.     

DICE: exploiting <Emphasis Type="Italic">all</Emphasis> bivariate dependencies in binary and multary search spaces

Although some of the earliest Estimation of Distribution Algorithms (EDAs) utilized bivariate marginal distribution models, up to now, all discrete bivariate EDAs had one serious limitation: they were constrained to exploiting only a limited O(d) subset out of all possible \(O(d^{2})\) bivariate dependencies. As a first we present a family of discrete bivariate EDAs that can learn and exploit all \(O(d^{2})\) dependencies between variables, and yet have the same run-time complexity as their more limited counterparts. This family of algorithms, which we label DICE (DIscrete Correlated Estimation of distribution algorithms), is rigorously based on sound statistical principles, and particularly on a modelling technique from statistical physics: dichotomised multivariate Gaussian distributions. Initially (Lane et al. in European Conference on the Applications of Evolutionary Computation, Springer, 1999), DICE was trialled on a suite of combinatorial optimization problems over binary search spaces. Our proposed dichotomised Gaussian (DG) model in DICE significantly outperformed existing discrete bivariate EDAs; crucially, the performance gap increasingly widened as dimensionality of the problems increased. In this comprehensive treatment, we generalise DICE by successfully extending it to multary search spaces that also allow for categorical variables. Because correlation is not wholly meaningful for categorical variables, interactions between such variables cannot be fully modelled by correlation-based approaches such as in the original formulation of DICE. Therefore, here we extend our original DG model to deal with such situations. We test DICE on a challenging test suite of combinatorial optimization problems, which are defined mostly on multary search spaces. While the two versions of DICE outperform each other on different problem instances, they both outperform all the state-of-the-art bivariate EDAs on almost all of the problem instances. This further illustrates that these innovative DICE methods constitute a significant step change in the domain of discrete bivariate EDAs.     

A Min–Max Property of Chordal Bipartite Graphs with Applications

We show that if G is a bipartite graph with no induced cycles on exactly 6 vertices, then the minimum number of chain subgraphs of G needed to cover E(G) equals the chromatic number of the complement of the square of line graph of G. Using this, we establish that for a chordal bipartite graph G, the minimum number of chain subgraphs of G needed to cover E(G) equals the size of a largest induced matching in G, and also that a minimum chain subgraph cover can be computed in polynomial time. The problems of computing a minimum chain cover and a largest induced matching are NP-hard for general bipartite graphs. Finally, we show that our results can be used to efficiently compute a minimum chain subgraph cover when the input is an interval bigraph.     

Cycle Extensions in BIBD Block‐Intersection Graphs

A cycle C in a graph G is extendable if there is some other cycle in G that contains each vertex of C plus one additional vertex. A graph is cycle extendable if every non‐Hamilton cycle in the graph is extendable. A balanced incomplete block design, BIBD, consists of a set V of v elements and a block set of k‐subsets of V such that each 2‐subset of V occurs in exactly λ of the blocks of . The block‐intersection graph of a design is the graph having as its vertex set and such that two vertices of are adjacent if and only if their corresponding blocks have nonempty intersection. In this paper, we prove that the block‐intersection graph of any BIBD is cycle extendable. Furthermore, we present a polynomial time algorithm for constructing cycles of all possible lengths in a block‐intersection graph.     

Hybrid cross‐linked hydrogels as a technology platform for in vitro release of cephradine

Hydrogel‐based drug delivery systems can leverage therapeutically favorable upshots of drug release and found clinical uses. Hydrogels offer temporal and spatial control over the release of different therapeutic agents. Because of their tailor made controllable degradability, physical properties, and ability to prevent the labile drugs from degradation, hydrogels provide platform on which diverse physicochemical interactions with entrapped drugs cause to control drug release. Herein, we report the fabrication of novel vinyltrimethoxy silane (VTMS) cross‐linked chitosan/polyvinyl pyrrolidone hydrogels. Swelling in distilled water in conjunction with different buffer and electrolyte solutions was performed to assess the swellability of hydrogels. Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and X‐ray diffraction (XRD) analysis were further conducted to investigate the possible interactions between components, thermal stability, and crystallinity of as‐prepared hybrid hydrogels, respectively. In vitro time‐dependent biodegradability, antimicrobial study, and cytotoxicity were also carried out to evaluate their extensive biocompatibility and cytotoxic behavior. More interestingly, in vitro drug release study allowed for the controlled release of cephradine. Therefore, this facile strategy developed the novel biocompatible and biodegradable hybrid hydrogels, which could significantly expand the scope of these hydrogels in other biomedical applications like scaffolds, skin regeneration, tissue engineering, etc.     

Green Synthesis of CeO2 Nanoparticles from the Abelmoschus esculentus Extract: Evaluation of Antioxidant,Anticancer, Antibacterial,and Wound-Healing Activities

Metal oxide nanoparticles synthesized by the biological method represent the most recent research in nanotechnology. This study reports the rapid and ecofriendly approach for the synthesis of CeO₂ nanoparticles mediated using the Abelmoschus esculentus extract. The medicinal plant extract acts as both a reducing and stabilizing agent. The characterization of CeO₂ NPs was performed by scanning electron microscopy (SEM), X-ray diffraction (XRD), ultraviolet-visible spectroscopy (UV-Vis), and Fourier transform infrared spectroscopy (FTIR). The in vitro cytotoxicity of green synthesized CeO₂ was assessed against cervical cancerous cells (HeLa). The exposure of CeO₂ to HeLa cells at 10–125 µg/mL caused a loss in cellular viability against cervical cancerous cells in a dose-dependent manner. The antibacterial activity of the CeO₂ was assessed against S. aureus and K. pneumonia. A significant improvement in wound-healing progression was observed when cerium oxide nanoparticles were incorporated into the chitosan hydrogel membrane as a wound dressing.