Enzyme immobilization strategies for the design of robust and efficient biocatalysts

Different strategies for the preparation of efficient and robust immobilized biocatalysts are here reviewed. Different physico-chemical approaches are discussed.i.- The stabilization of enzyme by any kind of immobilization on pre-existing porous supports.ii.- The stabilization of enzymes by multipoint covalent attachment on support surfaces.iii.- Additional stabilization of immobilized-stabilized enzyme by physical or chemical modification with polymers.These three strategies can be easily developed when enzymes are immobilized in pre-existing porous supports. In addition to that, these immobilized-stabilized derivatives are optimal to develop enzyme reaction engineering and reactor engineering. Stabilizations ranging between 1000 and 100,000 folds regarding diluted soluble enzymes are here reported.     

石英晶体板非线性高频振动的拓展伽辽金法分析

针对考虑几何和材料非线性的石英晶体板厚度剪切振动和弯曲振动的方程组,利用扩展伽辽金法对该方程组进行转化和求解,分别获得了强烈耦合的厚度剪切振动模态和弯曲振动模态的频率响应关系,绘制了不同振幅比和不同驱动电压影响下的频率响应曲线图。数值计算结果表明可以选取石英晶片的最佳长厚比尺寸来避免两种模态的强烈耦合。驱动电压的变化将引起石英晶体谐振器厚度剪切振动频率的明显改变,必须将振动频率的漂移值控制在常用压电声波器件的允许值之内。扩展伽辽金法对石英晶体板非线性振动方程组的求解为非线性有限元分析和偏场效应分析奠定了基础。     

Solvent Influence on Absorption Spectra and Tautomeric Equilibria of Symmetric Azomethine-Functionalized Derivatives: Structural Elucidation and Computational Studies

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 λ_max; 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.     

The use of untargeted and widely targeted metabolomics to distinguish between asphyxia and sudden cardiac death as the cause of death in rats: A preliminary study

It is important to determine the cause of death in the case of asphyxia. However, it is difficult to conclude death by asphyxia, especially when the deceased has underlying heart disease, because there are often no specific and representative corpse signs for both asphyxia and sudden cardiac death (SCD). The aim of the present work was to investigate the potential of metabolomics to discriminate asphyxia from SCD as the cause of death. A total of thirty male Sprague–Dawley rats were used to construct models of asphyxia, SCD (interfering cause of death), and cervical dislocation (control). Untargeted and widely targeted metabolomics approaches were used to obtain rat pulmonary metabolic profiles in this study. First, the metabolic alterations resulting from asphyxia were explored. There were significant changes found in carbohydrate metabolism, the endocrine system, and the sensory system. Second, we screened potential biomarkers and built classification models to determine the cause of death. Moreover, some biomarkers remained differentiated at 24 h and 48 h postmortem, so the cause of death could still be determined after death. This study showed the application potential of metabolomics to investigate the metabolic changes occurring in the process of death, as well as to determine the cause of death on the basis of metabolic differences even after death.     

单层MXene纳米片Ti2N电磁特性的过渡金属(Sc、V、Zr)掺杂效应

二维材料MXene纳米片由于具有较大的比表面积和较高的电子迁移率而受到广泛的关注。本文采用基于密度泛函理论的第一性原理计算,对单层MXene纳米片Ti₂N电磁特性的过渡金属(Sc、V、Zr)掺杂效应进行了系统研究。结果表明,所有过渡金属掺杂体系结合能均为负值,结构均稳定;其中Ti₂N-Sc体系的形成能为-2.242 eV,结构更易形成,且保持稳定;掺杂后Ti₂N-Sc、Ti₂N-Zr体系磁矩增大;此外,Ti₂N-Sc体系中保留了较高的自旋极化率,达到84.9%,可预测该体系在自旋电子学中具有潜在的应用价值。     

Multivariate optimization and comparison between conventional extraction (CE) and ultrasonic-assisted extraction (UAE) of carotenoid extraction from cashew apple

Carotenoids are an essential component of cashew and can be used in pharmaceuticals, cosmetics, natural pigment, food additives, among other applications. The present work focuses on optimizing and comparing conventional and ultrasound-assisted extraction methods. Every optimization step took place with a 1:1 (w:w) mixture of yellow and red cashew apples lyophilized and ground in a cryogenic mill. A Simplex-centroid design was applied for both methods, and the solvents acetone, methanol, ethanol, and petroleum ether were evaluated. After choosing the extractor solvent, a central composite design was applied to optimize the sample mass (59–201 mg) and extraction time (6–34 min). The optimum conditions for the extractor solvent were 38% acetone, 30% ethanol, and 32% petroleum ether for CE and a mixture of 44% acetone and 56% methanol for UAE. The best experimental conditions for UAE were a sonication time of 19 min and a sample mass of 153 mg, while the CE was 23 min and 136 mg. Comparing red and yellow cashews, red cashews showed a higher carotenoid content in both methodologies. The UAE methodology was ca. 21% faster, presented a more straightforward composition of extracting solution, showed an average yield of superior carotenoid content in all samples compared to CE. Therefore, UAE has demonstrated a simple, efficient, fast, low-cost adjustment methodology and a reliable alternative for other applications involving these bioactive compounds in the studied or similar matrix.     

Application of Machine Learning for Tool Condition Monitoring in Turning

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%.

     

A lightweight cell switching and traffic offloading scheme for energy optimization in ultra-dense heterogeneous networks

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.