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. 相似文献
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. 相似文献
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. 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%.
Large amounts of flowback and produced water (FPW) have been generated from hydraulic fracturing process for the production of unconventional gas such as shale gas. Complex organic pollutants are abundantly present in FPW with revealed toxicity to aquatic organisms and these contaminants may transfer into surrounding aquatic environment. Characterization and determination of complicated organic pollutants in FPW remains a challenge due to its complex composition and high salinity matrix. This review article covers the progress of recent 5 years regarding the sample preparation and instrumental analysis methods and thus summarizes the advantages and disadvantages of these methods for critical analysis of organic contaminants in FPW samples. Furthermore, the natural distribution of detected organic compounds and their transformation were reviewed and discussed to enhance the understanding of spatial and temporal behaviors of these organic pollutants in natural environment, paving the way for future development of pollution control policies and strategies. Enlightened by the studies of FPW contamination in the US, the investigations of FPW contamination in China continued to grow due to rapidly growing production of shale gas in China and resulted pollution. 相似文献
We investigate theoretically Rabi-like splitting and Fano resonance in absorption spectra of quantum dots(QDs)based on a hybrid QD-semiconducting nanowire/superconductor(SNW/SC)device mediated by Majorana fermions(MFs).Under the condition of pump on-resonance and off-resonance,the absorption spectrum experiences the conversion from Fano resonance to Rabi-like splitting in different parametric regimes.In addition,the Fano resonances are accompanied by the rapid normal phase dispersion,which will indicate the coherent optical propagation.The results indicate that the group velocity index is tunable with controlling the interaction between the QD and MFs,which can reach the conversion between the fast-and slow-light.Fano resonance will be another method to detect MFs and our research may indicate prospective applications in quantum information processing based on the hybrid QD-SNW/SC devices. 相似文献