An Apparatus for Non Destructive Study of Atom Transport in Liquids

1970 ◽  
Vol 25 (10) ◽  
pp. 1472-1476 ◽  
Author(s):  
S. Larsson ◽  
L. Broman ◽  
C. Roxbergh ◽  
A. Lodding
Keyword(s):  
Diffusion Coefficients ◽  
Experimental Results ◽  
Self Diffusion ◽  
Present Apparatus ◽  
Non Destructive ◽  
Better Than

Abstract A description is given of a method developed for diffusion and electrotransport measurements in liquids, which permits several successive readings on a sample in uninterrupted anneal. Errors from solidification and sectioning are avoided, and the reproducibility of measured diffusion coefficients is better than two percent. Experimental results are given for gallium self-diffusion. The present apparatus can be conveniently applied to many liquids solidifying below some 280 °C utilizing gamma tracers with energies in the range 0.2 - 2.0 MeV. The design can be modified for higher temperatures.

Application of the Hard Sphere Theory to the Diffusion of Binary Liquid Alloy Systems

1981 ◽  
Vol 36 (11) ◽  
pp. 1225-1232 ◽  
Author(s):  
G. Schwitzgebel ◽  
G. Langen
Keyword(s):  
Melting Temperature ◽  
Liquid Alloy ◽  
Diffusion Coefficients ◽  
Hard Sphere ◽  
Liquid Alloys ◽  
Particle Interactions ◽  
Self Diffusion ◽  
Binary Liquid ◽  
Pure Metals ◽  
Better Than

On the basis of the van der Waals concept of Ascarelli and Paskin the hard sphere theory of self diffusion is extended to binary liquid alloys. Using only the melting temperature of the pure metals and the densities, component self-diffusion coefficients and, with the help of Darken’s equation, mutual diffusion coefficients were calculated. Agreement with experimental results is good in (Bi, Sn), and excellent in (Sn, Zn) and (Li, Ag). Impurity diffusion in liquid Cu, Sn and Pb is predicted better than by the theory of Protopapas et al. Deviations in (Hg, Zn) and (Li, Pb) are tentatively attributed to strong particle interactions in one component (Hg) or in the alloy (Li, Pb).

THE SOURCES OF AUXIN HORMONE TO GROWTH OF SHOOT PINEAPPLE STEM CUTTING (Ananascomosus.L. Merr.)

2016 ◽  
Vol 1 (1) ◽  
pp. 45-52
Author(s):  
Palupi Puspitorini
Keyword(s):  
Water Concentration ◽  
Urine Concentration ◽  
Experimental Results ◽  
Stem Cuttings ◽  
Randomized Design ◽  
Natural Hormone ◽  
Cow Urine ◽  
Urine Concentrations ◽  
Completely Randomized Design ◽  
Better Than

The aim of this study was to select the best sources of auxin of which it can stimulate the growth of shoots Pineapple plant cuttings. This research is compiled in a completely randomized design (CRD) with 4 treatments and 6 replications. The Data were statistically Analyzed by the DMRT. Level of treatment given proves that no treatment 0%, cow urine concentration of 25%, young coconut water concentration of 25% and Rootone F 100 mg / cuttings. The results showed that cow urine concentrations of 25% and Rootone F 100 mg give the best results in stimulating the growth of shoots pineapple stem cuttings. Experimental results concluded that the effect of this natural hormone were better than the shoots without given hormone.           

Advanced Fault Isolation Technique Using Electro-Optical Terahertz Pulse Reflectometry (EOTPR) for 2D and 2.5D Flip-Chip Package

2012 ◽  
Author(s):  
Lihong Cao ◽  
Manasa Venkata ◽  
Meng Yeow Tay ◽  
Wen Qiu ◽  
J. Alton ◽  
...  
Keyword(s):  
Time Domain ◽  
Flip Chip ◽  
Time Domain Reflectometry ◽  
Fault Isolation ◽  
Experimental Results ◽  
Terahertz Pulse ◽  
Isolation And Identification ◽  
Isolation Technique ◽  
Non Destructive

Abstract Electro-optical terahertz pulse reflectometry (EOTPR) was introduced last year to isolate faults in advanced IC packages. The EOTPR system provides 10μm accuracy that can be used to non-destructively localize a package-level failure. In this paper, an EOTPR system is used for non-destructive fault isolation and identification for both 2D and 2.5D with TSV structure of flip-chip packages. The experimental results demonstrate higher accuracy of the EOTPR system in determining the distance to defect compared to the traditional time-domain reflectometry (TDR) systems.

A Computational Method for the Identification of Endolysins and Autolysins

2020 ◽  
Vol 27 (4) ◽  
pp. 329-336 ◽  
Author(s):  
Lei Xu ◽  
Guangmin Liang ◽  
Baowen Chen ◽  
Xu Tan ◽  
Huaikun Xiang ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Cell Wall ◽  
Experimental Results ◽  
Computational Method ◽  
Lytic Enzyme ◽  
Support Vector ◽  
Lytic Enzymes ◽  
Data Set ◽  
Optimal Feature ◽  
Better Than

Background: Cell lytic enzyme is a kind of highly evolved protein, which can destroy the cell structure and kill the bacteria. Compared with antibiotics, cell lytic enzyme will not cause serious problem of drug resistance of pathogenic bacteria. Thus, the study of cell wall lytic enzymes aims at finding an efficient way for curing bacteria infectious. Compared with using antibiotics, the problem of drug resistance becomes more serious. Therefore, it is a good choice for curing bacterial infections by using cell lytic enzymes. Cell lytic enzyme includes endolysin and autolysin and the difference between them is the purpose of the break of cell wall. The identification of the type of cell lytic enzymes is meaningful for the study of cell wall enzymes. Objective: In this article, our motivation is to predict the type of cell lytic enzyme. Cell lytic enzyme is helpful for killing bacteria, so it is meaningful for study the type of cell lytic enzyme. However, it is time consuming to detect the type of cell lytic enzyme by experimental methods. Thus, an efficient computational method for the type of cell lytic enzyme prediction is proposed in our work. Method: We propose a computational method for the prediction of endolysin and autolysin. First, a data set containing 27 endolysins and 41 autolysins is built. Then the protein is represented by tripeptides composition. The features are selected with larger confidence degree. At last, the classifier is trained by the labeled vectors based on support vector machine. The learned classifier is used to predict the type of cell lytic enzyme. Results: Following the proposed method, the experimental results show that the overall accuracy can attain 97.06%, when 44 features are selected. Compared with Ding's method, our method improves the overall accuracy by nearly 4.5% ((97.06-92.9)/92.9%). The performance of our proposed method is stable, when the selected feature number is from 40 to 70. The overall accuracy of tripeptides optimal feature set is 94.12%, and the overall accuracy of Chou's amphiphilic PseAAC method is 76.2%. The experimental results also demonstrate that the overall accuracy is improved by nearly 18% when using the tripeptides optimal feature set. Conclusion: The paper proposed an efficient method for identifying endolysin and autolysin. In this paper, support vector machine is used to predict the type of cell lytic enzyme. The experimental results show that the overall accuracy of the proposed method is 94.12%, which is better than some existing methods. In conclusion, the selected 44 features can improve the overall accuracy for identification of the type of cell lytic enzyme. Support vector machine performs better than other classifiers when using the selected feature set on the benchmark data set.

scholarly journals Theoretical Modelling of Ion Exchange Processes in Glass: Advances and Challenges

2021 ◽  
Vol 11 (11) ◽  
pp. 5070
Author(s):  
Xesús Prieto-Blanco ◽  
Carlos Montero-Orille
Keyword(s):  
Ion Exchange ◽  
Diffusion Coefficients ◽  
Molten Salts ◽  
Theoretical Modelling ◽  
Copper Films ◽  
Theoretical Frameworks ◽  
Self Diffusion ◽  
Exchange Processes ◽  
The One ◽  
Made In

In the last few years, some advances have been made in the theoretical modelling of ion exchange processes in glass. On the one hand, the equations that describe the evolution of the cation concentration were rewritten in a more rigorous manner. This was made into two theoretical frameworks. In the first one, the self-diffusion coefficients were assumed to be constant, whereas, in the second one, a more realistic cation behaviour was considered by taking into account the so-called mixed ion effect. Along with these equations, the boundary conditions for the usual ion exchange processes from molten salts, silver and copper films and metallic cathodes were accordingly established. On the other hand, the modelling of some ion exchange processes that have attracted a great deal of attention in recent years, including glass poling, electro-diffusion of multivalent metals and the formation/dissolution of silver nanoparticles, has been addressed. In such processes, the usual approximations that are made in ion exchange modelling are not always valid. An overview of the progress made and the remaining challenges in the modelling of these unique processes is provided at the end of this review.

scholarly journals Self-Diffusion Coefficients, Aggregation Numbers and the Range of Existence of Spherical Micelles of Oxyethylated Alkylphenols

2021 ◽  
Author(s):  
Victor P. Arkhipov ◽  
Natalia A. Kuzina ◽  
Andrei Filippov
Keyword(s):  
Aqueous Solutions ◽  
Diffusion Coefficients ◽  
The Self ◽  
Self Diffusion ◽  
Aggregation Numbers ◽  
Temperature Ranges ◽  
Spherical Micelles ◽  
Limiting Values

AbstractAggregation numbers were calculated based on measurements of the self-diffusion coefficients, the effective hydrodynamic radii of micelles and aggregates of oxyethylated alkylphenols in aqueous solutions. On the assumption that the radii of spherical micelles are equal to the lengths of fully extended neonol molecules, the limiting values of aggregation numbers corresponding to spherically shaped neonol micelles were calculated. The concentration and temperature ranges under which spherical micelles of neonols are formed were determined.

scholarly journals Effect of Modification on the Fluid Diffusion Coefficient in Silica Nanochannels

Molecules ◽  
2021 ◽  
Vol 26 (13) ◽  
pp. 4030
Author(s):  
Gengbiao Chen ◽  
Zhiwen Liu
Keyword(s):  
Diffusion Coefficient ◽  
Diffusion Coefficients ◽  
Surface Effect ◽  
Bulk Water ◽  
Self Diffusion ◽  
Average Diffusion Coefficient ◽  
Average Diffusion ◽  
Chain Lengths ◽  
Fluid Diffusion ◽  
Self Diffusion Coefficient

The diffusion behavior of fluid water in nanochannels with hydroxylation of silica gel and silanization of different modified chain lengths was simulated by the equilibrium molecular dynamics method. The diffusion coefficient of fluid water was calculated by the Einstein method and the Green–Kubo method, so as to analyze the change rule between the modification degree of nanochannels and the diffusion coefficient of fluid water. The results showed that the diffusion coefficient of fluid water increased with the length of the modified chain. The average diffusion coefficient of fluid water in the hydroxylated nanochannels was 8.01% of the bulk water diffusion coefficient, and the diffusion coefficients of fluid water in the –(CH2)3CH3, –(CH2)7CH3, and –(CH2)11CH3 nanochannels were 44.10%, 49.72%, and 53.80% of the diffusion coefficients of bulk water, respectively. In the above four wall characteristic models, the diffusion coefficients in the z direction were smaller than those in the other directions. However, with an increase in the silylation degree, the increased self-diffusion coefficient due to the surface effect could basically offset the decreased self-diffusion coefficient owing to the scale effect. In the four nanochannels, when the local diffusion coefficient of fluid water was in the range of 8 Å close to the wall, Dz was greater than Dxy, and beyond the range of 8 Å of the wall, the Dz was smaller than Dxy.

Devanagari Text Detection From Natural Scene Images

2020 ◽  
Vol 10 (3) ◽  
pp. 44-59
Author(s):  
Sankirti Sandeep Shiravale ◽  
R. Jayadevan ◽  
Sanjeev S. Sannakki
Keyword(s):  
Edge Detection ◽  
Image Understanding ◽  
Text Detection ◽  
Experimental Results ◽  
Combined Approach ◽  
Natural Scene ◽  
Light Conditions ◽  
The Individual ◽  
Natural Scene Images ◽  
Better Than

Text present in a camera captured scene images is semantically rich and can be used for image understanding. Automatic detection, extraction, and recognition of text are crucial in image understanding applications. Text detection from natural scene images is a tedious task due to complex background, uneven light conditions, multi-coloured and multi-sized font. Two techniques, namely ‘edge detection' and ‘colour-based clustering', are combined in this paper to detect text in scene images. Region properties are used for elimination of falsely generated annotations. A dataset of 1250 images is created and used for experimentation. Experimental results show that the combined approach performs better than the individual approaches.

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