Synthesis of 3,3′-methylenebis(4-hydroxyquinolin-2(1H)-ones) of prospective anti-COVID-19 drugs

Molecular Diversity - During formylation of 2-quinolones by DMF/Et3N mixture, the unexpected 3,3′-methylenebis(4-hydroxyquinolin-2(1H)-ones) were formed. The discussed mechanism was proved as...     

ChemInform Abstract: Structure,Ionization, and Fragmentation of Hydrogenated Aluminoboron Clusters: Al2B2H2n (n = 0—6).

Energetic and structural stability of Al₂B₂H_2n (n = 0—6) clusters is investigated by DFT calculations and a stochastic search algorithm.     

Influence of the counteranion on silver(I)–dithioether coordination polymers

In order to rationalize the effect of the size and coordinating ability of counteranions upon the structure of Ag(I)–dithioether coordination polymers, a series of such polymers has been synthesized by the combination of the 1,3-bis(methylthio)propane building block and AgX silver salts (X = ClO₄⁻ (1), BF₄⁻ (2), CF₃SO₃⁻ (3), SbF₆⁻ (4), C₆H₅COO⁻ (5), CF₃COO⁻ (6), CF₃CF₂CF₂COO⁻ (7) and ⁻OOCCF₂CF₂COO⁻ (8)). Except in two cases, all complexes form 1D-coordination polymers.     

Exact solutions of the Korteweg-de Vries equation with space and time dependent coefficients by the extended unified method

Recently the unified method for finding traveling wave solutions of nonlinear evolution equations was proposed by one of the authors. It was shown that, this method unifies all the methods being used to find these solutions. In this paper, we extend this method to find a class of formal exact solutions to Korteweg-de Vries equation with space-time dependent coefficients.     

Dynamic compensation temperature in the kinetic spin-1 Ising model in an oscillating external magnetic field on alternate layers of a hexagonal lattice

The dynamic behavior of a two-sublattice spin-1 Ising model with a crystal-field interaction (D) in the presence of a time-varying magnetic field on a hexagonal lattice is studied by using the Glauber-type stochastic dynamics. The lattice is formed by alternate layers of spins σ=1 and S=1. For this spin arrangement, any spin at one lattice site has two nearest-neighbor spins on the same sublattice, and four on the other sublattice. The intersublattice interaction is antiferromagnetic. We employ the Glauber transition rates to construct the mean-field dynamical equations. Firstly, we study time variations of the average magnetizations in order to find the phases in the system, and the temperature dependence of the average magnetizations in a period, which is also called the dynamic magnetizations, to obtain the dynamic phase transition (DPT) points as well as to characterize the nature (continuous and discontinuous) of transitions. Then, the behavior of the total dynamic magnetization as a function of the temperature is investigated to find the types of the compensation behavior. Dynamic phase diagrams are calculated for both DPT points and dynamic compensation effect. Phase diagrams contain the paramagnetic (p) and antiferromagnetic (af) phases, the p+af and nm+p mixed phases, nm is the non-magnetic phase, and the compensation temperature or the L-type behavior that strongly depend on the interaction parameters. For D<2.835 and H₀>3.8275, H₀ is the magnetic field amplitude, the compensation effect does not appear in the system.     

Modeling and optimizing a vendor managed replenishment system using machine learning and genetic algorithms

Using a supply chain network, we demonstrate the feasibility, viability, and robustness of applying machine learning and genetic algorithms to respectively model, understand, and optimize such data intensive environments. Deployment of these algorithms, which learn from and optimize data, can obviate the need to perform more complex, expensive, and time consuming design of experiments (DOE), which usually disrupt system operations. We apply and compare the behavior and performance of the proposed machine learning algorithms to that obtained via DOE in a simulated Vendor Managed Replenishment system, developed for an actual firm. The results show that the models resulting from the proposed algorithms had strong explanatory and predictive power, comparable to that of DOE. The optimal system settings and profit were also similar to that obtained from DOE. The virtues of using machine learning and evolutionary algorithms to model and optimize data rich environments thus seem promising because they are automatic, involving little human intervention and expertise. We believe and are exploring how they can be made adaptive to improve parameter estimates with increasing data, as well as seamlessly detecting system (and therefore model) changes, thus being capable of recursively updating and reoptimizing a modified or new model.     

Density Based Problem Space Search for the Capacitated Clustering p-Median Problem

In the Capacitated Clustering Problem (CCP), a given set of n weighted points is to be partitioned into p clusters such that, the total weight of the points in each cluster does not exceed a given cluster capacity. The objective is to find a set of p centers that minimises total scatter of points allocated to them. In this paper a new constructive method, a general framework to improve the performance of greedy constructive heuristics, and a problem space search procedure for the CCP are proposed. The constructive heuristic finds patterns of natural subgrouping in the input data using concept of density of points. Elements of adaptive computation and periodic construction–deconstruction concepts are implemented within the constructive heuristic to develop a general framework for building efficient heuristics. The problem-space search procedure is based on perturbations of input data for which a controlled perturbation strategy, intensification and diversification strategies are developed. The implemented algorithms are compared with existing methods on a standard set of bench-marks and on new sets of large-sized instances. The results illustrate the strengths of our algorithms in terms of solution quality and computational efficiency.     

Phase switching and quantum interference in a 3-level Λ-shape bistable model

The steady state bistable behaviour of a three-level Λ-shape is examined in the presence of a control field $({\rm \Omega} +\chi \left( t\right) e^{i\varphi})$({\rm \Omega} +\chi \left( t\right) e^{i\varphi}) : Ω is the strong Rabi component, $\chi \left( t\right) $\chi \left( t\right) is the stochastic part with relative phase ϕ; with quantum interference between decay channels taken into account. One- and two-way phase switching effect for the transmitted field against the phase are predicted at fixed values for the incident input field. Also cooperative switching effect shows multistable/bistable behaviour. Quantum interference tends to diminish the dispersive effects responsible for multistable behaviour (in the input-output relation and the cooperative switching diagram) and asymmetry (in the phase switching diagram). Equivalence of the role of the stochastic part of the control field with that of the “classically” squeezed field is shown to occur only in the absence of quantum interference.     

Effect of substitution of blast-furnace slag by fired drinking water sludge on the properties of pozzolanic cement pastes

Journal of Thermal Analysis and Calorimetry - The effect of fired drinking water sludge (FDWS) as a mineral admixture on the physico-mechanical properties and the fire resistance of pozzolanic...     

Product and Mechanism of Gas‐phase Pyrolysis of 2‐arylidinehydrazinopyrimidines: Interesting Route to Condensed Heterocycles[1]

Gas‐phase pyrolysis of N‐arylidine‐N′‐pyrimidin‐2‐yl‐hydrazine derivatives 1a , 1b , 1c , 1d , 1e gave the corresponding arylnitriles 2a , 2b , 2c , 2d , 2e , 2‐aminopyrimidine 3 , 3‐phenyl‐1,2,4‐triazolo[4,3‐a]pyrimidines 4 , 2‐phenyl‐1,2,4‐triazolo[1,5‐a]pyrimidines 5 , 2,4,5‐triphenyl‐1H‐imidazole 6 , and 2,3‐diphenylquinoline 7 . The analyses of the reaction products are reported and used to elucidate the mechanism of the pyrolytic process.