Framboid Sizes

2021 ◽  
pp. 21-46
Author(s):  
David Rickard
Keyword(s):  
Water Column ◽  
Marine Sediments ◽  
Geometric Mean ◽  
Atomic Clusters ◽  
Normal Distributions ◽  
Nanoparticle Clusters ◽  
Mean Diameter ◽  
The Mean ◽  
Framboid Formation ◽  
Log Normal

Framboid size-frequency plots show log-normal distributions with a geometric mean diameter of 6.0 μ‎m and with 95% of framboids ranging between 2.9 and 12.3 μ‎m. The largest framboids may be 250 μ‎m in diameter, although spherical aggregates of framboids, known as polyframboids, may range up to 900 μ‎m in diameter. Various spherical clusters of nanoparticles have been described which are less than 0.2 μ‎m in diameter. These do not form a continuum with framboids. There is no evidence for any significant change in framboid diameters with geologic time, and the differences in mean sizes between hydrothermal and sedimentary framboids do not, at present, appear to be statistically significant. By contrast, it appears that the mean diameters of framboids from non-marine sediments are significantly larger (7.6 μ‎m) than marine framboids (5.7 μ‎m). There is some evidence that framboids formed in the water column are smaller than those formed in sediments, but the non-critical use of this possible difference as a proxy for paleoenvironmental reconstructions is not robust. So-called microframboids and nanoframboids are discrete entities which are distinct from framboids. They are nanoparticle clusters and are not produced by the same processes as those involved in framboid formation, nor do they behave in the same way. They are more akin to atomic clusters, which form similar constructs.

Modeling of engineering properties for predicting the mass of acid lime fruit (Citrus aurantifolia Swingle)

2020 ◽  
Vol 44 (01) ◽  
pp. 20-28
Author(s):  
V. S. Sonone ◽  
D. A. Pawar ◽  
V. P. Kad ◽  
P. A. Unde
Keyword(s):  
Surface Area ◽  
Geometric Mean ◽  
Engineering Properties ◽  
Mean Values ◽  
Mean Diameter ◽  
Multiple Variable ◽  
Acid Lime ◽  
The Mean ◽  
Packaging Industry ◽  
Area And Volume

Engineering properties and their relationships with mass for Phule Sharbati acid lime cultivar were investigated. Relationship between physical properties of fruits and its mass will create tremendous change in the packaging industry. The mean values of engineering properties such as minor diameter, intermediate diameter, major diameter, geometric mean diameter, sphericity, aspect ratio, mass, surface area, volume and true density were found to be 42.55 mm, 41.20 mm, 40.41 mm, 0.94, 0.94, 38.17g, 49997 mm2, 33322.8 mm3 and 1 g/cc, respectively. Regression models were used to predict the effect of mass of acid lime and classified into two: 1–Single and multiple variable regressions of acid lime mass and dimensional characteristics and 2- Single variable regression for geometric mean diameter, sphericity, surface area and volume. Results indicated that mass modeling of acid lime based on minor diameter was found most appropriate in the first classification. In the second classification, the power-law model was noticed best on the basis of the geometric mean diameter, surface area and the volume.

Uncertainty of Design Parameters From Viewpoint of Extreme Statistics

1992 ◽  
Vol 114 (2) ◽  
pp. 76-82 ◽  
Author(s):  
Y. Goda
Keyword(s):  
Distribution Function ◽  
Standard Deviation ◽  
Sample Size ◽  
Design Parameters ◽  
Empirical Formulas ◽  
Extreme Statistics ◽  
Normal Distributions ◽  
The Mean ◽  
Log Normal ◽  
Return Value

Statistical variability of a sample of extreme data has been examined by means of Monte Carlo simulations. The Fisher-Tippett types I and II, the Weibull, and the log-normal distributions were chosen for the examination. The sample size covered from 10 to 400, and 10,000 runs were carried out for each combination of sample size, censoring rate, and distribution function. Empirical formulas and tables are presented for the mean and the coefficient of variation of the standard deviation of a sample, the standard deviation of return value, and the confidence interval of return period.

Particle Size Analysis of Inorganic Dirt in Raw Wool

1988 ◽  
Vol 58 (9) ◽  
pp. 526-530 ◽  
Author(s):  
Franco Ferrero ◽  
Franco Marchese ◽  
Giorgio Fornaro
Keyword(s):  
Particle Size ◽  
Geometric Mean ◽  
Particle Size Analysis ◽  
Ash Content ◽  
Size Analysis ◽  
Normal Model ◽  
Mean Diameter ◽  
Distribution Parameters ◽  
Log Normal ◽  
Different Origin

A method of analyzing the particle size of inorganic dirt in raw wool is described. This method was applied to 25 raw wool samples of different origin, type, fineness, and grease and ash content. The results show that the particle size distribution of inorganic dirt is monomodal and approaches a log-normal model. The distribution parameters such as geometric mean diameter and standard deviation were also evaluated. In all samples, the geometric mean diameter was in the range of 9 to 28 micrometers without any correlation with other raw wool characteristics.

A Unified Approach to Economic Dominance and Inequality Measures using a General Transformation Function

2009 ◽  
pp. 42
Author(s):  
Subir Ghosh
Keyword(s):  
Income Distribution ◽  
Geometric Mean ◽  
Economic Inequality ◽  
Transformation Function ◽  
Unified Approach ◽  
General Transformation ◽  
Inequality Measures ◽  
Pareto Distributions ◽  
The Mean ◽  
Log Normal

We present three generalized, empirical, economic inequality definitions for the empirical dominance of the income distribution of Population 1 over that of Population 2 with respect to their n-person economy in terms of a general transformation function G. These definitions are based on the generalized gaps using the general G function instead of the standard gaps, to achieve greater flexibility and higher generality in performing many comparisions between Populations 1 and 2, in terms of the mean as well as the variance, geometric mean, median, and range. This article provides a unified approach to various dominance concepts and inequality measures. This unification is achieved through the transformation function G. We study the effects of the economic inequality definitions on location and dispersion of the income distribution. Log-normal, log-skew-normal, and Pareto distributions are considered in this study.

Colloidal molybdoantimonic acids as ion exchangers

1991 ◽  
Vol 69 (2) ◽  
pp. 293-299 ◽  
Author(s):  
M. Koné ◽  
P. Courtin ◽  
J. Lemerle
Keyword(s):  
Colloidal Particles ◽  
Polymerization Process ◽  
Exchange Reactions ◽  
Aqueous Dispersions ◽  
Normal Distributions ◽  
Mean Size ◽  
The Mean ◽  
Mo Content ◽  
The Stability ◽  
Log Normal

Colloidal particles with a c.c.p. structure were obtained from mixtures of antimonic and molybdic acids through a polymerization process. These particles were octahedral and their sizes fits the log-normal distributions. The mean size decreases and the polydispersity increases with increasing Mo content in the particles. The stability of the aqueous dispersions was due to the surface charge density of the particles which was enhanced when increasing the Mo content. Ion exchange reactions can occur with the dispersions. Two different routes lead to Ag+ fixation: substitution of core H+ without flocculation of the dispersion or cancellation of external charges with flocculation. Key words: inorganic exchangers, colloids, antimonic acid, molybdic acid.

scholarly journals Measurement of Indoor Thoron Gas Concentrations Using a Radon-Thoron Discriminative Passive Type Monitor: Nationwide Survey in Japan

2021 ◽  
Vol 18 (3) ◽  
pp. 1299
Author(s):  
Tetsuya Sanada
Keyword(s):  
Geometric Mean ◽  
Nationwide Survey ◽  
Wall Material ◽  
Living Room ◽  
The Mean ◽  
Wall Construction ◽  
Materials Used ◽  
One Year ◽  
Log Normal ◽  
Log Normal Distribution

As part of a nationwide survey of thoron (220Rn) in Japan, the indoor 220Rn gas concentrations in 940 dwellings were measured throughout one year, from 1993 to 1996, using a passive type 222Rn-220Rn discriminative monitor. The monitor was placed in a bedroom or a living room in each house for four successive three-month periods. The mean annual indoor 220Rn concentration was estimated from the four measurements in each house. The arithmetic mean, the median and the geometric mean for indoor 220Rn concentrations in 899 dwellings were 20.1, 9.6 and 10.0 Bq m−3, respectively. The 220Rn concentrations exhibited a log-normal distribution. It was found that the 220Rn concentrations were dependent on the nature of the materials used for wall construction and also on the distance of measurement from the wall. Significant seasonal variations in the 220Rn concentration were not observed. It would seem that the nature of the wall material contributed to the increased indoor 220Rn concentrations.

scholarly journals Impact of engineering properties of grass seeds in developing post-harvest operations and machineries

2021 ◽  
Vol 22 (3) ◽  
pp. 395-399
Author(s):  
Sanjay Kumar Singh ◽  
Sheshrao Kautkar ◽  
Amit Patil
Keyword(s):  
Geometric Mean ◽  
Seed Mass ◽  
Seed Storage ◽  
Arithmetic Mean ◽  
Engineering Properties ◽  
Mean Values ◽  
Post Harvest ◽  
Mean Diameter ◽  
Length Width ◽  
The Mean

Engineering properties of grass seeds are most important for the development of post-harvest mechanization and operations. Therefore engineering properties of fluffy as well as true seeds were determined in view of its important in development of post-harvest mechanization. The mean values of length, width, thickness, arithmetic mean diameter, geometric mean diameter, sphericity, surface area, volume, thousands seed mass and bulk density of fluffy Deenanath grass seed were observed in the range of 5.23-7.17 mm, 2.10-3.44 mm, 1.17-2.49 mm, 3.07- 4.13 mm, 2.53- 3.69 mm,  41.01-60.13 %, 19.12-43.70 mm2, 3.70-18.24 mm3, 0.789-0.849 g and 7.41-7.89 kg/m3 respectively. However, for true seeds of Deenanath grass, the range of these values varied from 2.23-2.65 mm, 0.69-0.95 mm, 0.47-0.69 mm, 1.16-1.40 mm, 0.93-1.17 mm,  38.69-47.33 %, 2.67-4.31 mm2, 3.60-9.64 mm3, 0.468-0.488 g and 602.97-624.29 kg/m3 respectively moisture level of 9 % db. Determined properties of fluffy as well as true seeds of Deenanath would be utilized to develop threshing, cleaning, grading, seed storage and packaging operations and machineries.

DMSA-scintigraphy in paediatrics: Is the evaluation of the geometric mean necessary for the calculation of the differential renal function?

2001 ◽  
Vol 40 (04) ◽  
pp. 107-110 ◽  
Author(s):  
B. Roßmüller ◽  
S. Alalp ◽  
S. Fischer ◽  
S. Dresel ◽  
K. Hahn ◽  
...  
Keyword(s):  
Renal Function ◽  
Geometric Mean ◽  
Region Of Interest ◽  
Posterior View ◽  
Renal Abnormality ◽  
Anterior View ◽  
Differential Renal Function ◽  
The Mean ◽  
The Right ◽  
To Receive

SummaryFor assessment of differential renal function (PF) by means of static renal scintigraphy with Tc-99m-dimer-captosuccinic acid (DMSA) the calculation of the geometric mean of counts from the anterior and posterior view is recommended. Aim of this retrospective study was to find out, if the anterior view is necessary to receive an accurate differential renal function by calculating the geometric mean compared to calculating PF using the counts of the posterior view only. Methods: 164 DMSA-scans of 151 children (86 f, 65 m) aged 16 d to 16 a (4.7 ± 3.9 a) were reviewed. The scans were performed using a dual head gamma camera (Picker Prism 2000 XP, low energy ultra high resolution collimator, matrix 256 x 256,300 kcts/view, Zoom: 1.6-2.0). Background corrected values from both kidneys anterior and posterior were obtained. Using region of interest technique PF was calculated using the counts of the dorsal view and compared with the calculated geometric mean [SQR(Ctsdors x Ctsventr]. Results: The differential function of the right kidney was significantly less when compared to the calculation of the geometric mean (p<0.01). The mean difference between the PFgeom and the PFdors was 1.5 ± 1.4%. A difference > 5% (5.0-9.5%) was obtained in only 6/164 scans (3.7%). Three of 6 patients presented with an underestimated PFdors due to dystopic kidneys on the left side in 2 patients and on the right side in one patient. The other 3 patients with a difference >5% did not show any renal abnormality. Conclusion: The calculation of the PF from the posterior view only will give an underestimated value of the right kidney compared to the calculation of the geometric mean. This effect is not relevant for the calculation of the differntial renal function in orthotopic kidneys, so that in these cases the anterior view is not necesssary. However, geometric mean calculation to obtain reliable values for differential renal function should be applied in cases with an obvious anatomical abnormality.

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