Quantitative Prediction of Yield in Transglycosylation Reaction Catalyzed by Nucleoside Phosphorylases

2018 ◽  
Vol 360 (16) ◽  
pp. 3090-3096 ◽  
Author(s):  
Cyril S. Alexeev ◽  
Irina V. Kulikova ◽  
Sergei Gavryushov ◽  
Vitali I. Tararov ◽  
Sergey N. Mikhailov
Keyword(s):  
Quantitative Prediction ◽  
Transglycosylation Reaction ◽  
Nucleoside Phosphorylases

Calculating Energy Release Rate as a Function of Crack Length Using a Multiple-Step Crack Closure Technique in Tire Finite Element Models

2018 ◽  
Vol 46 (3) ◽  
pp. 130-152
Author(s):  
Dennis S. Kelliher
Keyword(s):  
Finite Element ◽  
Energy Release Rate ◽  
Crack Length ◽  
Energy Release ◽  
Crack Closure ◽  
Release Rate ◽  
Fatigue Behavior ◽  
Three Dimensions ◽  
Quantitative Prediction ◽  
Closure Technique

ABSTRACT When performing predictive durability analyses on tires using finite element methods, it is generally recognized that energy release rate (ERR) is the best measure by which to characterize the fatigue behavior of rubber. By addressing actual cracks in a simulation geometry, ERR provides a more appropriate durability criterion than the strain energy density (SED) of geometries without cracks. If determined as a function of crack length and loading history, and augmented with material crack growth properties, ERR allows for a quantitative prediction of fatigue life. Complications arise, however, from extra steps required to implement the calculation of ERR within the analysis process. This article presents an overview and some details of a method to perform such analyses. The method involves a preprocessing step that automates the creation of a ribbon crack within an axisymmetric-geometry finite element model at a predetermined location. After inflating and expanding to three dimensions to fully load the tire against a surface, full ribbon sections of the crack are then incrementally closed through multiple solution steps, finally achieving complete closure. A postprocessing step is developed to determine ERR as a function of crack length from this enforced crack closure technique. This includes an innovative approach to calculating ERR as the crack length approaches zero.

Quantitative prediction of flow dynamics and mechanical retention of surface-altered red blood cells through a splenic slit

2021 ◽  
Vol 33 (5) ◽  
pp. 051902
Author(s):  
Xiaojing Qi ◽  
Shuo Wang ◽  
Shuhao Ma ◽  
Keqin Han ◽  
Xuejin Li
Keyword(s):  
Red Blood Cells ◽  
Blood Cells ◽  
Flow Dynamics ◽  
Quantitative Prediction

scholarly journals A predictable smoothing evolution model for computer-controlled polishing

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Jing Hou ◽  
Pengli Lei ◽  
Shiwei Liu ◽  
Xianhua Chen ◽  
Jian Wang ◽  
...  
Keyword(s):  
Evolution Model ◽  
Quantitative Prediction ◽  
Theoretical Support ◽  
Model Combining ◽  
Process Guidance ◽  
Dependent Model ◽  
Computer Controlled Optical Surfacing ◽  
Computer Controlled ◽  
Time Dependent Model ◽  
Selection Of

AbstractQuantitative prediction of the smoothing of mid-spatial frequency errors (MSFE) is urgently needed to realize process guidance for computer controlled optical surfacing (CCOS) rather than a qualitative analysis of the processing results. Consequently, a predictable time-dependent model combining process parameters and an error decreasing factor (EDF) were presented in this paper. The basic smoothing theory, solution method and modification of this model were expounded separately and verified by experiments. The experimental results show that the theoretical predicted curve agrees well with the actual smoothing effect. The smoothing evolution model provides certain theoretical support and guidance for the quantitative prediction and parameter selection of the smoothing of MSFE.

Quantitative prediction of a functional ingredient in apple using Raman spectroscopy and multivariate calibration analysis

2021 ◽  
Vol 127 (6) ◽  
Author(s):  
Shinsaku Tsuyama ◽  
Akinori Taketani ◽  
Takeharu Murakami ◽  
Michio Sakashita ◽  
Saki Miyajima ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Calibration ◽  
Quantitative Prediction ◽  
Functional Ingredient

scholarly journals A Novel Quantitative Prediction Approach for Pungency Level of Chinese Liquor (Baijiu) Based on Infrared Thermal Imager

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1107
Author(s):  
Yingxia He ◽  
Shuang Chen ◽  
Ke Tang ◽  
Yan Xu ◽  
Xiaowei Yu
Keyword(s):  
Aqueous Solution ◽  
Surface Temperature ◽  
Sensory Analysis ◽  
Alcoholic Beverages ◽  
Quantitative Prediction ◽  
Thermal Imager ◽  
Surface Temperatures ◽  
Tongue Surface ◽  
Ethanol Aqueous Solution ◽  
Prediction Approach

Pungency is a crucial sensory feature that influences consumers’ appreciation and preferences toward alcoholic beverages. However, the quantitation of pungency is challenging to achieve using sensory analysis because of persistence, accumulation, and desensitization to the pungency perception. This study aimed to design a novel pungency evaluation method based on the measurement of tongue surface temperature. An infrared thermal (IRT) imager technique for measuring tongue surface temperature was established. To validate its feasibility, the IRT technique was used to measure tongue surface temperatures after the tongue was stimulated by (1) water and Baijiu, (2) different concentrations of ethanol aqueous solution (10, 20, 30, 40, and 50%, v/v), (3) ethanol aqueous solution and Baijiu samples with the same ethanol content, and (4) 26 Baijiu samples with different pungency level. For all cases, tongue surface temperatures showed large differences as a result of the different stimulation. The results showed that the tongue surface temperature correlated with the pungency intensity obtained by the sensory analysis. The relationship between tongue surface temperature and pungency intensity was established by multiple linear regression analysis. The IRT technique was able to be a useful support tool to quantitatively predict the pungency of alcoholic beverages, based on the measurement of tongue surface temperature.

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