Production Control of Gold and Rhodium Plating Thickness on Very Small Samples by X-Ray Spectroscopy

1967 ◽  
Vol 11 ◽  
pp. 185-190
Author(s):  
George H. Glade

AbstractManufacture of reed switches, critical components in present-day dataprocessing support devices, requires a means of accurate, rapid analysis of elements used in plating tlie levers of the switch. Because of gready reduced feedback time, X-ray spectroscopy has replaced metallographic sectioning and optical measurement as a plating-thickness control method. While 6 hr were required to obtain thickness data for a given sample size by sectioning, X-ray spectroscopy requires only 2 hr, which permits better control of the plating operating. X-ray spectroscopy is now used routinely to control both gold and rhodium plating thicknesses in the 20- to 100μin. (1 × 10−6) thickness range. The large number of samples prevents long count duration, while the small sample size (0.110 by 0.033 in.) reduces the precision of the analysis. However, the precision of the X-ray and optical methods is approximately the same, 8% variance. X-ray accuracy is comparable to that of sectioning since the standards are obtained by sectioning. Simplicity of operation is required since relatively untrained operators are used. An aperture system is used to reduce background. The rhodium thickness measurement is obtained from gross rhodium intensity. Attenuation of gross nickel intensity from the base material was found to be a better measure of gold thickness intensity. Calibration for hoth gold and rhodium is performed by using the same wide detector conditions. The choice of analysis is made by changing only the 2θ angle, thus avoiding the time required for recalibration when changing analysis.

PEDIATRICS ◽  
1989 ◽  
Vol 83 (3) ◽  
pp. A72-A72
Author(s):  
Student

The believer in the law of small numbers practices science as follows: 1. He gambles his research hypotheses on small samples without realizing that the odds against him are unreasonably high. He overestimates power. 2. He has undue confidence in early trends (e.g., the data of the first few subjects) and in the stability of observed patterns (e.g., the number and identity of significant results). He overestimates significance. 3. In evaluating replications, his or others', he has unreasonably high expectations about the replicability of significant results. He underestimates the breadth of confidence intervals. 4. He rarely attributes a deviation of results from expectations to sampling variability, because he finds a causal "explanation" for any discrepancy. Thus, he has little opportunity to recognize sampling variation in action. His belief in the law of small numbers, therefore, will forever remain intact.


Author(s):  
J. Mullaert ◽  
M. Bouaziz ◽  
Y. Seeleuthner ◽  
B. Bigio ◽  
J-L. Casanova ◽  
...  

AbstractMany methods for rare variant association studies require permutations to assess the significance of tests. Standard permutations assume that all individuals are exchangeable and do not take population stratification (PS), a known confounding factor in genetic studies, into account. We propose a novel strategy, LocPerm, in which individuals are permuted only with their closest ancestry-based neighbors. We performed a simulation study, focusing on small samples, to evaluate and compare LocPerm with standard permutations and classical adjustment on first principal components. Under the null hypothesis, LocPerm was the only method providing an acceptable type I error, regardless of sample size and level of stratification. The power of LocPerm was similar to that of standard permutation in the absence of PS, and remained stable in different PS scenarios. We conclude that LocPerm is a method of choice for taking PS and/or small sample size into account in rare variant association studies.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Vahid Ebrahimi ◽  
Zahra Bagheri ◽  
Zahra Shayan ◽  
Peyman Jafari

Assessing differential item functioning (DIF) using the ordinal logistic regression (OLR) model highly depends on the asymptotic sampling distribution of the maximum likelihood (ML) estimators. The ML estimation method, which is often used to estimate the parameters of the OLR model for DIF detection, may be substantially biased with small samples. This study is aimed at proposing a new application of the elastic net regularized OLR model, as a special type of machine learning method, for assessing DIF between two groups with small samples. Accordingly, a simulation study was conducted to compare the powers and type I error rates of the regularized and nonregularized OLR models in detecting DIF under various conditions including moderate and severe magnitudes of DIF ( DIF = 0.4   and   0.8 ), sample size ( N ), sample size ratio ( R ), scale length ( I ), and weighting parameter ( w ). The simulation results revealed that for I = 5 and regardless of R , the elastic net regularized OLR model with w = 0.1 , as compared with the nonregularized OLR model, increased the power of detecting moderate uniform DIF ( DIF = 0.4 ) approximately 35% and 21% for N = 100   and   150 , respectively. Moreover, for I = 10 and severe uniform DIF ( DIF = 0.8 ), the average power of the elastic net regularized OLR model with 0.03 ≤ w ≤ 0.06 , as compared with the nonregularized OLR model, increased approximately 29.3% and 11.2% for N = 100   and   150 , respectively. In these cases, the type I error rates of the regularized and nonregularized OLR models were below or close to the nominal level of 0.05. In general, this simulation study showed that the elastic net regularized OLR model outperformed the nonregularized OLR model especially in extremely small sample size groups. Furthermore, the present research provided a guideline and some recommendations for researchers who conduct DIF studies with small sample sizes.


2020 ◽  
Vol 21 ◽  
Author(s):  
Roberto Gabbiadini ◽  
Eirini Zacharopoulou ◽  
Federica Furfaro ◽  
Vincenzo Craviotto ◽  
Alessandra Zilli ◽  
...  

Background: Intestinal fibrosis and subsequent strictures represent an important burden in inflammatory bowel disease (IBD). The detection and evaluation of the degree of fibrosis in stricturing Crohn’s disease (CD) is important to address the best therapeutic strategy (medical anti-inflammatory therapy, endoscopic dilation, surgery). Ultrasound elastography (USE) is a non-invasive technique that has been proposed in the field of IBD for evaluating intestinal stiffness as a biomarker of intestinal fibrosis. Objective: The aim of this review is to discuss the ability and current role of ultrasound elastography in the assessment of intestinal fibrosis. Results and Conclusion: Data on USE in IBD are provided by pilot and proof-of-concept studies with small sample size. The first type of USE investigated was strain elastography, while shear wave elastography has been introduced lately. Despite the heterogeneity of the methods of the studies, USE has been proven to be able to assess intestinal fibrosis in patients with stricturing CD. However, before introducing this technique in current practice, further studies with larger sample size and homogeneous parameters, testing reproducibility, and identification of validated cut-off values are needed.


Author(s):  
Jonah T Hansen ◽  
Luca Casagrande ◽  
Michael J Ireland ◽  
Jane Lin

Abstract Statistical studies of exoplanets and the properties of their host stars have been critical to informing models of planet formation. Numerous trends have arisen in particular from the rich Kepler dataset, including that exoplanets are more likely to be found around stars with a high metallicity and the presence of a “gap” in the distribution of planetary radii at 1.9 R⊕. Here we present a new analysis on the Kepler field, using the APOGEE spectroscopic survey to build a metallicity calibration based on Gaia, 2MASS and Strömgren photometry. This calibration, along with masses and radii derived from a Bayesian isochrone fitting algorithm, is used to test a number of these trends with unbiased, photometrically derived parameters, albeit with a smaller sample size in comparison to recent studies. We recover that planets are more frequently found around higher metallicity stars; over the entire sample, planetary frequencies are 0.88 ± 0.12 percent for [Fe/H] < 0 and 1.37 ± 0.16 percent for [Fe/H] ≥ 0 but at two sigma we find that the size of exoplanets influences the strength of this trend. We also recover the planet radius gap, along with a slight positive correlation with stellar mass. We conclude that this method shows promise to derive robust statistics of exoplanets. We also remark that spectrophotometry from Gaia DR3 will have an effective resolution similar to narrow band filters and allow to overcome the small sample size inherent in this study.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shinya Hosokawa ◽  
Kyosuke Momota ◽  
Anthony A. Chariton ◽  
Ryoji Naito ◽  
Yoshiyuki Nakamura

AbstractDiversity indices are commonly used to measure changes in marine benthic communities. However, the reliability (and therefore suitability) of these indices for detecting environmental change is often unclear because of small sample size and the inappropriate choice of communities for analysis. This study explored uncertainties in taxonomic density and two indices of community structure in our target region, Japan, and in two local areas within this region, and explored potential solutions. Our analysis of the Japanese regional dataset showed a decrease in family density and a dominance of a few species as sediment conditions become degraded. Local case studies showed that species density is affected by sediment degradation at sites where multiple communities coexist. However, two indices of community structure could become insensitive because of masking by community variability, and small sample size sometimes caused misleading or inaccurate estimates of these indices. We conclude that species density is a sensitive indicator of change in marine benthic communities, and emphasise that indices of community structure should only be used when the community structure of the target community is distinguishable from other coexisting communities and there is sufficient sample size.


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