Organocatalyzed Michael Addition of Aldehydes to Nitro Alkenes – Generally Accepted Mechanism Revisited and Revised

The amine‐catalyzed enantioselective Michael addition of aldehydes to nitro alkenes (Scheme 1) is known to be acid‐catalyzed (Fig. 1). A mechanistic investigation of this reaction, catalyzed by diphenylprolinol trimethylsilyl ether is described. Of the 13 acids tested, 4‐NO₂? C₆H₄OH turned out to be the most effective additive, with which the amount of catalyst could be reduced to 1 mol‐% (Tables 2–5). Fast formation of an amino‐nitro‐cyclobutane 12 was discovered by in situ NMR analysis of a reaction mixture. Enamines, preformed from the prolinol ether and aldehydes (benzene/molecular sieves), and nitroolefins underwent a stoichiometric reaction to give single all‐trans‐isomers of cyclobutanes (Fig. 3) in a [2+2] cycloaddition. This reaction was shown, in one case, to be acid‐catalyzed (Fig. 4) and, in another case, to be thermally reversible (Fig. 5). Treatment of benzene solutions of the isolated amino‐nitro‐cyclobutanes with H₂O led to mixtures of 4‐nitro aldehydes (the products 7 of overall Michael addition) and enamines 13 derived thereof (Figs. 6–9). From the results obtained with specific examples, the following tentative, general conclusions are drawn for the mechanism of the reaction (Schemes 2 and 3): enamine and cyclobutane formation are fast, as compared to product formation; the zwitterionic primary product 5 of C,C‐bond formation is in equilibrium with the product of its collapse (the cyclobutane) and with its precursors (enamine and nitro alkene); when protonated at its nitronate anion moiety the zwitterion gives rise to an iminium ion 6 , which is hydrolyzed to the desired nitro aldehyde 7 or deprotonated to an enamine 13 . While the enantioselectivity of the reaction is generally very high (>97% ee), the diastereoselectivity depends upon the conditions, under which the reaction is carried out (Fig. 10 and Tables 1–5). Various acid‐catalyzed steps have been identified. The cyclobutanes 12 may be considered an off‐cycle ‘reservoir’ of catalyst, and the zwitterions 5 the ‘key players’ of the process (bottom part of Scheme 2 and Scheme 3).     

In silico evaluation of potential inhibitory activity of remdesivir,favipiravir, ribavirin and galidesivir active forms on SARS-CoV-2 RNA polymerase

Molecular Diversity - Since the outbreak emerged in November 2019, no effective drug has yet been found against SARS-CoV-2. Repositioning studies of existing drug molecules or candidates are...     

Existence of weak solutions of the g-Kelvin–Voight equation

The 2D $g$-Navier–Stokes equations have the form $\frac{?u}{?t}?\nu \Delta u+u.?u+?p=f\text{in }\Omega$ with the continuity equation $?.\left(gu\right)=0\text{in }\Omega$ in a bounded domain $\Omega ?{\mathbb{R}}^2$ where $g=g\left(x_{1,}{x}_2\right)$ is a smooth real valued function defined on $\Omega$. We use the method described by Roh [J. Roh, $g$-Navier Stokes equations, Ph.D. Thesis, University of Minnesota, 2001] for the derivation of $g$-Kelvin–Voight equations represented by $\frac{?u}{?t}?\nu {\Delta }_{g}u+\frac{\nu }{g}(?g??)u?\alpha {\Delta }_g{u}_t+\frac{\alpha }{g}(?g??)u_t+u??u+?p=f\left(x\right)\text{ in }\Omega$$?.\left(gu\right)=0\text{in }\Omega$ We discuss the existence and uniqueness of weak solutions of $g$-Kelvin–Voight equations by the use of the well known Feado–Galerkin method.     

On the Strong Solutions and the Structural Stability of the g-Bénard Problem

In this paper, we study a type of modified Boussinesq equations which is called g-Bénard problem. We show the existence and uniqueness of strong solutions of the problem in two dimensions, and then, we investigate the continuous dependence of the solutions on the viscosity parameter.     

Characterization and ethylene adsorption of natural and modified clinoptilolites

The ethylene adsorption of Turkey clinoptilolite-rich tuff from Gordes and Bigadic region of western of Anatolia and their exchanged forms (K⁺, Na⁺ and Ca²⁺) were investigated. The clinoptilolite samples were characterized using XRD, TG-DTA and nitrogen adsorption methods. Adsorption isotherms for ethylene on natural and modified forms of both adsorbents at 277 K and 293 K were obtained at pressures up to 38 kPa. Uptake of ethylene increased as Na-CLN < Ca-CLN < K-CLN < Natural CLN for Gordes zeolite at 277 K, 293 K and for Bigadic zeolite at 277 K. For Bigadic zeolites at 293 K, uptake of ethylene increased in the order Ca-CLN < Na-CLN < K-CLN < Natural CLN. It was found that ethylene adsorption capacity of Bigadic clinoptilolite samples was much greater than Gordes clinoptilolite samples except K⁺ modified forms at both temperatures. These results show that both natural clinoptilolites have a considerable potential for the removal of ethylene.     

DNA multiblock copolymers

Single stranded (ss) DNA block copolymers were applied to synthesize DNA multiblock architectures by hybridization; these polymeric bioorganic hybrids were characterized by gel electrophoresis and MALDI-TOF mass spectrometry.     

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors, Multiscale Permutation Entropy (MPE) is a suitable tool for capturing useful information from the ordinal patterns of sEMG time series. In a previous work, a theoretical comparison in terms of bias and variance of two MPE variants—namely, the refined composite MPE (rcMPE) and the refined composite downsampling (rcDPE), was addressed. In the current paper, we assess the superiority of rcDPE over MPE and rcMPE, when applied to real sEMG signals. Moreover, we demonstrate the capacity of rcDPE in quantifying fatigue levels by using sEMG data recorded during a fatiguing exercise. The processing of four consecutive temporal segments, during biceps brachii exercise maintained at 70% of maximal voluntary contraction until exhaustion, shows that the 10th-scale of rcDPE was capable of better differentiation of the fatigue segments. This scale actually brings the raw sEMG data, initially sampled at 10 kHz, to the specific 0–500 Hz sEMG spectral band of interest, which finally reveals the inner complexity of the data. This study promotes good practices in the use of MPE complexity measures on real data.     

On the Genuine Relevance of the Data-Driven Signal Decomposition-Based Multiscale Permutation Entropy

Ordinal pattern-based approaches have great potential to capture intrinsic structures of dynamical systems, and therefore, they continue to be developed in various research fields. Among these, the permutation entropy (PE), defined as the Shannon entropy of ordinal probabilities, is an attractive time series complexity measure. Several multiscale variants (MPE) have been proposed in order to bring out hidden structures at different time scales. Multiscaling is achieved by combining linear or nonlinear preprocessing with PE calculation. However, the impact of such a preprocessing on the PE values is not fully characterized. In a previous study, we have theoretically decoupled the contribution of specific signal models to the PE values from that induced by the inner correlations of linear preprocessing filters. A variety of linear filters such as the autoregressive moving average (ARMA), Butterworth, and Chebyshev were tested. The current work is an extension to nonlinear preprocessing and especially to data-driven signal decomposition-based MPE. The empirical mode decomposition, variational mode decomposition, singular spectrum analysis-based decomposition and empirical wavelet transform are considered. We identify possible pitfalls in the interpretation of PE values induced by these nonlinear preprocessing, and hence, we contribute to improving the PE interpretation. The simulated dataset of representative processes such as white Gaussian noise, fractional Gaussian processes, ARMA models and synthetic sEMG signals as well as real-life sEMG signals are tested.     

Effect of pressure and space between electrodes on the deposition of SiN_xH_y films in a capacitively coupled plasma reactor

The fluid model, also called the macroscopic model, is commonly used to simulate low temperature and low pressure radiofrequency plasma discharges. By varying the parameters of the model, numerical simulation allows us to study several cases, providing us the physico-chemical information that is often difficult to obtain experimentally. In this work, using the fluid model, we employ numerical simulation to show the effect of pressure and space between the reactor electrodes on the fundamental properties of silicon plasma diluted with ammonia and hydrogen. The results show the evolution of the fundamental characteristics of the plasma discharge as a function of the variation of the pressure and the distance between the electrodes. By examining the pressure-distance product in a range between 0.3 Torr 2.7 cm and 0.7 Torr 4 cm, we have determined the optimal pressure-distance product that allows better deposition of hydrogenated silicon nitride(Si N_x H_y)films which is 0.7 Torr 2.7 cm.