Optimization of the Extraction Technology and Assessment of Antioxidant Activity of Chlorogenic Acid-Rich Extracts From Eucommia ulmoides Leaves

Chlorogenic acid has been proved to have cardiovascular protection, antibacterial, antiviral, hemostatic, and hypolipidemia effects. Modern scientific research on the bioactivity of chlorogenic acid has been extended to the fields of food, medicine, health care and daily-use chemical industry. The aim of this research was to optimize the extraction conditions for chlorogenic acid from Eucommia ulmoides (Eucommiaceae) leaves. The significant variables were screened and optimized by a combination of Plackett-Burman test and Box-Behnken design. Optimum extraction parameters with ethanol concentration of 50%, solvent pH value of 3, and particle size of 60 mesh were determined according to variance analysis and contour plots. Under these conditions, the yield of chlorogenic acid was up to 4.36 mg/g, which was basically consistent with the theoretical prediction value of 4.50 mg/g. This study also proved the potential antioxidant activity of E. ulmoides leaves. The optimal extract of E. ulmoides leaves rich in chlorogenic acid showed the highest antioxidant activity in the FRAP method, which was 219.8 μM Trolox equivalents (TE) per g extract weight (EW) (μM TE/g EW). The DPPH method gave a similar value (168 μM TE/g EW) to the ABTS method (152 μM TE/g EW). The established extraction process was efficient in the recovery of chlorogenic acid from E. ulmoides leaves, encouraging its valorization as a cheap and sustainable alternative for the isolation of chlorogenic acid.

AMFİ-DERSLİK ÖĞRENME ALANLARINDA İNSAN ODAKLI MİMARİ AYDINLATMA TASARIMI

By using artificial lighting in AMFI classrooms where there are architectural constraints and daylight cannot be adequately benefited from, it can contribute to the visual comfort and indirectly to the health of the students. In this study, point-based analysis of the Equivalent Melanopic Lux values of artificial lighting and learning environments in schools was made according to the criteria of WELL standards specified in the Human Centric Lighting concept. By using direct lighting, without changing the architectural design, optimum lighting suitable for human biology is provided with low-cost artificial lighting arrangements. According to the Human-Centered Lighting concept, an architectural lighting design was made in accordance with the WELL standards criteria. As a result of the improvement of visual comfort and optimum circadian effects in the learning environments of the students studying in AMFI classrooms, it is predicted that the success and participation of the students who use these learning areas will increase.

Optimum Design of Straight Circular Channels Incorporating Constant and Variable Roughness Scenarios: Assessment of Machine Learning Models

In this study, two machine learning (ML) models named as artificial neural network (ANN) and genetic programming (GP) were applied to design optimum canals with circular shapes. In this application, the earthwork and lining costs were considered as the objective function, while Manning’s equation was utilized as the hydraulic constraint. In this design problem, two different scenarios were considered for Manning’s coefficient: (1) constant Manning’s coefficient and (2) the experimentally proved variation of Manning’s coefficient with water depth. The defined design problem was solved for a wide range of different dimensionless variables involved to produce a large enough database. The first part of these data was used to train the ML models, while the second part was utilized to compare the performances of ANN and GP in optimum design of circular channels with those of explicit design relations available in the literature. The comparison obviously indicated that the ML models improved the accuracy of the circular channel design from 55% to 91% based on two performance evaluation criteria. Finally, application of the ML models to optimum design of circular channels demonstrates a considerable improvement over the explicit design equations available in the literature.

Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design optimization

In recent years, the use of machine learning-based surrogate models for computational fluid dynamics (CFD) simulations has emerged as a promising technique for reducing the computational cost associated with engine design optimization. However, such methods still suffer from drawbacks. One main disadvantage is that the default machine learning (ML) hyperparameters are often severely suboptimal for a given problem. This has often been addressed by manually trying out different hyperparameter settings, but this solution is ineffective in case of a high-dimensional hyperparameter space. Besides this problem, the amount of data needed for training is also not known a priori. In response to these issues that need to be addressed, the present work describes and validates an automated active learning approach, AutoML-GA, for surrogate-based optimization of internal combustion engines. In this approach, a Bayesian optimization technique is used to find the best machine learning hyperparameters based on an initial dataset obtained from a small number of CFD simulations. Subsequently, a genetic algorithm is employed to locate the design optimum on the ML surrogate surface. In the vicinity of the design optimum, the solution is refined by repeatedly running CFD simulations at the projected optima and adding the newly obtained data to the training dataset. It is demonstrated that AutoML-GA leads to a better optimum with a lower number of CFD simulations, compared to the use of default hyperparameters. The proposed framework offers the advantage of being a more hands-off approach that can be readily utilized by researchers and engineers in industry who do not have extensive machine learning expertise.

The Effect of Inlet Conditions on Turbine Endwall Loss

There can be significant variation and uncertainty in the flow conditions entering a blade row. This paper explores how this variability can affect endwall loss in axial turbines. A computational study of three cascades with collinear inlet boundary layers is conducted. Endwall loss varies by more than a factor of 3 depending on the inlet conditions. This variation is caused by dissipation of Secondary Kinetic Energy (SKE). The results can be understood by observing that the inlet conditions predominantly control how secondary vorticity is distributed within the blade passage. Modestly-thick inlet boundary layers with high shape factor tend to displace vorticity towards the center of the passage. This displacement reduces vorticity cancellation, increasing secondary velocities and SKE. A general method is formulated to estimate SKE in preliminary design. Optimum aspect ratio is shown to depend on the inlet boundary condition. Strategies to reduce endwall loss and minimize sensitivity to inlet conditions are then highlighted.

Test of AC - 20 asphalt mixture ratio on the runway of Da Lian Airport

After years of use, there’s oil loss on the asphalt pavement. the bond strength of aggregate decreases. Loose threshing is serious. In order to improve the pavement performance, Extend the service life of pavement, Improve the safety of aircraft operation. we test the AC-20 modified asphalt mixture on the runway of Da Lian Airport from many factors, including raw materials, admixtures, gradation design, optimum ratio of oil to stone, then we find the best ways to resolve it.

Test of SMA - 16 asphalt mixture ratio on the runway of Da Lian Airport

After years of use, there’s oil loss on the asphalt pavement. the bond strength of aggregate decreases. Loose threshing is serious. In order to improve the pavement performance, Extend the service life of pavement , Improve the safety of aircraft operation. we test the SMA-16 modified asphalt mixture on the runway of Da Lian Airport from many factors, including raw materials, admixtures, gradation design, optimum ratio of oil to stone, then we find the best ways to resolve it.

Organizing thematic search in open archive system

Problems of search organization in open archive system are specified and analyzed. The experience of thematic search in digital resources is generalized. The approaches to organizing open archive search interface oriented toward untrained and trained users are characterized. The pros and cons of single search window are discussed. Vectors to improve search instruments and performance are defined. The rubricator version to support thematic search adaptation is proposed. The choice of UDC as the rubricator foundation is substantiated provided that its correspondence with the State Rubricator of Scitech information and Library Bibliographic Classification is set up. The fragment of the suggested rubricator is given as an example. The main purpose of the analysis is to summarize on the problems related to thematic search and to propose approaches to design optimum close-knit rubricator, and to identify its application possibilities.

Optimization of methylene blue degradation by Aspergillus terreus YESM 3 using response surface methodology

Synthetic dyes released from many industries cause pollution problems in aquatic environments affecting public health. The present study aimed to explore the potentiality of Aspergillus terreus YESM 3 (accession number LM653117) for colour removal of three different dyes: methylene blue (MB), malachite green (MG) and safranin (S). Results showed that the tolerance index of the studied fungus against tested dyes decreased in the order: methylene blue, safranin and malachite green. Removal of methylene blue colour was improved by using Box–Behnken design. Optimum condition for methylene blue biodegradation in Czapek Dox broth was achieved at pH 6, of 31.41 mg/L dye concentration and an inoculum of 5.7778 × 104 (conidia/mL) with biodegradation of 89.41%. Thus, a novel and eco-friendly system for the biodegradation of dyes using Box–Behnken design has been efficiently developed. Accordingly, A. terreus YESM 3 can be professionally used for bioremediation of methylene blue dye in wastewater and removal of environmental pollution.