A new series of azomethine-functionalized compounds was synthesized from the condensation of 2-hydroxy-1,3-propanediamine and 2-thienylcarboxaldehydes in the presence of a drying agent. The derivatives were spectroscopically characterized by NMR, LC-MS, UV/Vis, IR and elemental analysis. Variable temperature 1H-NMR (−60 to +60 °C) was performed to investigate the effect of solvent polarity; the capability of solvent to form H-bond was found to dramatically influencing the tautomerization process of the desired structures. The calculated thermochemical parameters (ΔH298, ΔG298 and ΔS298) at DFT and MP2 levels of theory explained that 3 b exists in equilibrium with two tautomers. The basis of the electronic absorptions was pursued through Time-Dependent Density-Functional Theory (TD-DFT). Analysis of the structural surfaces was inspected and the molecular electrostatic potential (MEP) demonstrated that the three functionalized compounds were relatively analogous in the electronic distributions. Furthermore, the electrophilic and nucleophilic centers lying on the molecular surfaces were probably playing a key-role in stabilizing the compounds through the nonclassical C−H⋅⋅⋅π interactions and hydrogen bonding. The impact of solvent polarity on absorption spectra were investigated via solvatochromic shifts. For instance, compound 3 c displayed a gradual shift of the maximum absorption to the red area when the solvent polarity was increased, recording a 21 nm of bathochromic shift. In contrast, no significant solvent-effect on 3 a and 3 b was observed. The solvation relation was pursued between Gutmann's donicity numbers the experimental λmax; exhibited almost positive linear performance with a minor oscillation, that ascribe to the possible weak interface between the molecules of solute and designated solvents. The bandgap energy of all products were assessed experimentally using optical absorption spectra following Tauc approach, giving −4.050 ( 3 a ), −3.900 ( 3 b ) and −3.210 ( 3 c ) eV. However, the ΔE were computationally figured out from TD-DFT simulation to be −4.258 ( 3 a ), −4.022 ( 3 b ) and −3.390 ( 3 c ) eV. 相似文献
The machining process is primarily used to remove material using cutting tools. Any variation in tool state affects the quality of a finished job and causes disturbances. So, a tool monitoring scheme (TMS) for categorization and supervision of failures has become the utmost priority. To respond, traditional TMS followed by the machine learning (ML) analysis is advocated in this paper. Classification in ML is supervised based learning method wherein the ML algorithm learn from the training data input fed to it and then employ this model to categorize the new datasets for precise prediction of a class and observation. In the current study, investigation on the single point cutting tool is carried out while turning a stainless steel (SS) workpeice on the manual lathe trainer. The vibrations developed during this activity are examined for failure-free and various failure states of a tool. The statistical modeling is then incorporated to trace vital signs from vibration signals. The multiple-binary-rule-based model for categorization is designed using the decision tree. Lastly, various tree-based algorithms are used for the categorization of tool conditions. The Random Forest offered the highest classification accuracy, i.e., 92.6%.
One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity. 相似文献
In this paper, the problem of the uniform stability for a class of fuzzy fractional-order genetic regulatory networks with random discrete delays, distributed delays, and parameter uncertainties is studied. Although there is a portion of literature on using fixed point theorems to study the stability of fractional neural networks, most of them required the fractional order to be in . However, the case of the fractional-order belonging to has not been discussed. To solve it, this work proposes a novel idea of using fixed point theory to study the stability of fuzzy (0,1) order neural networks, the problem of the uniqueness of the solution of the considered genetic regulatory networks is resolved, and a novel sufficient condition to guarantee the uniform stability of above genetic regulatory networks is also derived. Eventually, an example is given to demonstrate that the obtained result is effective. 相似文献
Juglandis Mandshuricae Cortex is the bark of Juglans mandshurica Maxim., which has been used as a folk medicine plant in China and India. In this study, an ultra-high performance liquid chromatography–quadrupole/orbitrap high-resolution mass spectrometry method was developed to clarify and quantify the chemical profiling of Juglandis Mandshuricae Cortex rapidly. A total of 113 compounds were characterized. Among them, seven flavonoids were simultaneously quantified in 15 min, including myricetin, myricetrin, taxifolin, kaempferol, quercetin, quercitrin, and naringenin. The method was validated for accuracy, precision, and the limits of detection and quantification. All calibration curves showed a good linear relationship (r > 0.9990) within test ranges. The intra- and inter-day relative standard deviations were less than 2.16%. Accuracy validation showed that the recovery was between 95.6 and 101.3% with relative standard deviation values below 2.85%. The validated method was successfully applied to determine the contents of seven flavones in Juglandis Mandshuricae Cortex from seven sources and the contents of these places were calculated respectively. This method provides a theoretical basis for further developing the medicinal value of Juglandis Mandshuricae Cortex. 相似文献
Neighborhood preserving embedding (NPE) is an important linear dimensionality reduction technique that aims at preserving the local manifold structure. NPE contains three steps, i.e., finding the nearest neighbors of each data point, constructing the weight matrix, and obtaining the transformation matrix. Liang et al. proposed a variational quantum algorithm (VQA) for NPE [Phys. Rev. A101 032323 (2020)]. The algorithm consists of three quantum sub-algorithms, corresponding to the three steps of NPE, and was expected to have an exponential speedup on the dimensionality n. However, the algorithm has two disadvantages: (i) It is not known how to efficiently obtain the input of the third sub-algorithm from the output of the second one. (ii) Its complexity cannot be rigorously analyzed because the third sub-algorithm in it is a VQA. In this paper, we propose a complete quantum algorithm for NPE, in which we redesign the three sub-algorithms and give a rigorous complexity analysis. It is shown that our algorithm can achieve a polynomial speedup on the number of data points m and an exponential speedup on the dimensionality n under certain conditions over the classical NPE algorithm, and achieve a significant speedup compared to Liang et al.'s algorithm even without considering the complexity of the VQA. 相似文献
In this article, a way to employ the diffusion approximation to model interplay between TCP and UDP flows is presented. In order to control traffic congestion, an environment of IP routers applying AQM (Active Queue Management) algorithms has been introduced. Furthermore, the impact of the fractional controller and its parameters on the transport protocols is investigated. The controller has been elaborated in accordance with the control theory. The TCP and UDP flows are transmitted simultaneously and are mutually independent. Only the TCP is controlled by the AQM algorithm. Our diffusion model allows a single TCP or UDP flow to start or end at any time, which distinguishes it from those previously described in the literature. 相似文献