One-pot Synthesis,Crystal Structures and Antimicrobial Activities of Two New 1,4-Disubstituted 1,2,3-Triazole-4-Carboxylates

Two new 1,4-disubstituted 1,2,3-triazoles-4-carboxylates were synthesized via click reaction. Compound 1a was synthesized by the interaction of 6-nitro-tetrazolo[1.5-a]-pyridine with ethyl propynoate at room temperature in the presence of Cu(OAc)2 as a catalyst and THF as solvent. Compound 1b was also synthesized by the same manner except that tert-butyl propionate, instead of ethyl propynoate, was used. The compounds were characterized by IR, 1H-NMR, 13C-NMR and single-crystal X-ray diffraction analysis. Compound 1a(C10H9N5O4) crystallizes in the triclinic system, space group P1 with a = 5.0894(9), b = 8.9834(13), c = 13.089(2) ?, α= 83.041(7), β= 80.256(7), γ=87.296(8)°, V = 585.24(16)?3, Z = 2, Mr = 263.22, crystal size(mm) = 0.37 × 0.20 ×0.18,(I 2σ(I)) = 8557, 2493, 1229, Rint = 0.057. Compound 1b(C12H13N5O4) crystallizes in the monoclinic system, space group P21/c with a = 6.8854(5), b = 21.783(2), c = 9.3986(8) ?,β = 93.239(4)°, V = 1407.4(2)?3, Z = 4, Mr = 291.27, crystal size(mm) = 0.38 × 0.22 × 0.20,(I 2σ(I)) = 11842, 3172, 1866, Rint = 0.047. Antimicrobial assay results showed that the title compounds display excellent activities to different bacterial and fungal strains.     

Eco‐friendly ionic liquid assisted capillary electrophoresis and α‐acid glycoprotein‐assisted liquid chromatography for simultaneous determination of anticancer drugs in human fluids

In the current work, two eco‐friendly analytical methods based on capillary electrophoresis (CE) and reversed phase liquid chromatography (RPLC) were developed for simultaneous determination of the most commonly used anticancer drugs for Hodgkin's disease: methotrexate (MTX), vinblastine, chlorambucil and dacarbazine. A background electrolyte (BGE) of 12.5 mmol/L phosphate buffer at pH 7.4 and 0.1 µmol/L 1‐butyl‐3‐methyl imidazolium bromide (BMImBr) ionic liquid (IL) was used for CE measurements at 250 nm detection wavelength, 20 kV applied voltage and 25 °C. The rinsing protocol was significantly improved to reduce the adsorption of IL on the interior surface of capillary. Moreover, RPLC method was developed on α‐1‐acid glycoprotein (AGP) column. Mobile phase was 10 mmol/L phosphate buffer at pH 6.0 (100% v/v) and flow rate at 0.1 mL/min. As AGP is a chiral column, it was successfully separated l ‐MTX from its enantiomer impurity d ‐MTX. Good linearity of quantitative analysis was achieved with coefficients of determinations (r²) >0.995. The stability of drugs measurements was investigated with adequate recoveries up to 24 h storage time under ambient temperature. The limits of detection were <50 and 90 ng/mL by CE and RPLC, respectively. The using of short‐chain IL as an additive in BGE achieved 600‐fold sensitivity enhancement compared with conventional Capillary Zone Electrophoresis (CZE). Therefore, for the first time, the proposed methods were successfully applied to determine simultaneously the analytes in human plasma and urine samples at clinically relevant concentrations with fast and simple pretreatments. Developed IL‐assisted CE and RPLC methods were also applied to measure MTX levels in patients’ samples over time. Copyright © 2014 John Wiley & Sons, Ltd.     

Path integral quantization corresponding to the deformed Heisenberg algebra

In this paper, the deformation of the Heisenberg algebra, consistent with both the generalized uncertainty principle and doubly special relativity, has been analyzed. It has been observed that, though this algebra can give rise to fractional derivative terms in the corresponding quantum mechanical Hamiltonian, a formal meaning can be given to them by using the theory of harmonic extensions of function. Depending on this argument, the expression of the propagator of the path integral corresponding to the deformed Heisenberg algebra, has been obtained. In particular, the consistent expression of the one dimensional free particle propagator has been evaluated explicitly. With this propagator in hand, it has been shown that, even in free particle case, normal generalized uncertainty principle and doubly special relativity show very much different result.     

Sampling with a String

Kramer's sampling theorem forms a bridge between the Whittaker-Shannon-Kotel'nikov sampling theorem and boundary-value problems. It has been shown that sampling expansions associated with Sturm-Liouville boundary-value problems are Lagrange-type sampling series, i.e., Lagrange series with infinitely many terms converging to entire functions. String theory as developed by Feller, Kac, and Krein, is a generalization of the Sturm-Liouville theory. We investigate sampling series associated with strings and compare them with those associated with Sturm-Liouville problems. We show that unlike sampling series associated with Sturm-Liouville problems, those associated with strings include not only Lagrange-type sampling series, but also Lagrange polynomial interpolation.     

On Quantum Team Games

Recently Liu and Simaan (2004) convex static multi-team classical games have been introduced. Here they are generalized to both nonconvex, dynamic and quantum games. Puu's incomplete information dynamical systems are modified and applied to Cournot team game. The replicator dynamics of the quantum prisoner's dilemma game is also studied.     

Synthèse de nouveaux dérivés tétrahydroquinoléines et quinoléines via la réaction d'aza-Diels-Alder suivie d'aromatisation

The Aza-Diels-Alder reaction of aldimines with isoeugenol is described. New 1,2,3,4-tetrahydroquinoline and quinoline structures are reported. The stereo- and regioselectivities of the [4+2] cycloaddition are discussed.     

The Sample Average Approximation Method Applied to Stochastic Routing Problems: A Computational Study

The sample average approximation (SAA) method is an approach for solving stochastic optimization problems by using Monte Carlo simulation. In this technique the expected objective function of the stochastic problem is approximated by a sample average estimate derived from a random sample. The resulting sample average approximating problem is then solved by deterministic optimization techniques. The process is repeated with different samples to obtain candidate solutions along with statistical estimates of their optimality gaps.We present a detailed computational study of the application of the SAA method to solve three classes of stochastic routing problems. These stochastic problems involve an extremely large number of scenarios and first-stage integer variables. For each of the three problem classes, we use decomposition and branch-and-cut to solve the approximating problem within the SAA scheme. Our computational results indicate that the proposed method is successful in solving problems with up to 2¹⁶⁹⁴ scenarios to within an estimated 1.0% of optimality. Furthermore, a surprising observation is that the number of optimality cuts required to solve the approximating problem to optimality does not significantly increase with the size of the sample. Therefore, the observed computation times needed to find optimal solutions to the approximating problems grow only linearly with the sample size. As a result, we are able to find provably near-optimal solutions to these difficult stochastic programs using only a moderate amount of computation time.