Number of Primary Samples

Each sector has specific requirements in terms of the number of primary samples that should be taken. Simple empirical rules which have been used in the past to determine the number of samples to be taken from a lot include n = -JN and n = 3 x / N (in each case, N is the total number of items in the lot). In both cases, n is rounded to the nearest integer. 

In addition, published sampling plans for different sectors indicate the number of samples to be taken from a lot. For example, when carrying out acceptance sampling by attributes (see Section 3.3.2), as described in ISO 2859-1 [6], a number of factors have to be taken into account  

This needs to be known as it will influence the number of samples that need to be taken from the lot. 

Once the lot size and inspection level are known, Table 3.2 can be used to identify the appropriate sampling plan. For example, if the lot size is 4000 and inspection level II is required, then L is the appropriate code letter. The code letter relates to the number of items (samples) from the lot that needs to be examined, as shown in Table 3.2. 

Lot or batch size Special inspection levels General inspection levels  

---

Prevalency of screening tests probability that the analyte A is present in a given number of samples Number of primary samples (in sampling) ... 

The relationship between the estimated variances s2 has to consider the number of primary samples, p, subsamples, q, and test samples, q r... 

Raw materials are delivered to manufacturing facilities in containers of different nature, form and dimensions and there may be many of them in one batch. Steps should therefore be taken to take a sufficient number of primary samples in order to make sure of the quality and homogeneity of the batch received. Various appropriate utensils which can provide representative samples may be employed. The type of utensil and protocol to be used is that judged to be the most suitably adapted to the particular problem. 

Percentage of meteorites seen to fall. Chondrites. Over 90% of meteorites that are observed to fall out of the sky are classified as chondrites, samples that are distinguished from terrestrial rocks in many ways (3). One of the most fundamental is age. Like most meteorites, chondrites have formation ages close to 4.55 Gyr. Elemental composition is also a property that distinguishes chondrites from all other terrestrial and extraterrestrial samples. Chondrites basically have undifferentiated elemental compositions for most nonvolatile elements and match solar abundances except for moderately volatile elements. The most compositionaHy primitive chondrites are members of the type 1 carbonaceous (Cl) class. The analyses of the small number of existing samples of this rare class most closely match estimates of solar compositions (5) and in fact are primary source solar or cosmic abundances data for the elements that cannot be accurately determined by analysis of lines in the solar spectmm (Table 2). Table 2. Solar System Abundances of the Elements ... 

The sampling plan should specify the number and size of primary samples which need to be obtained from the lot/batch. It should also describe how the laboratory sample is to be obtained. These issues may well be outside of the analyst s control, but it is important to consider how the validity of any analysis will be affected. 

Note A good number of Standard Samples, including primary standards, such as arsenic trioxide, benzoic acid, potassium hydrogen phthalate, sodium oxalate, are available as ... 

Let us begin by looking at the parameters that make SIMS measurements difficult to quantify. First, the secondary ion yield (defined as the ratio of the number of secondary ions sputtered from the surface of a solid sample to the number of primary ions incident upon the specimen) varies over four orders of magnitude from element to element. Second, the yield of each ion is affected by the composition of the matrix. This is the well known SIMS "matrix effect . Third, instrumental effects and ion collection/detection efficiencies can vary from instrument to instrument and specimen to specimen. 

There are two primary difficulties in directly inverting equation (12.7). First, the system is usually underdetermined, which means there are more variables (e.g., wavelengths) than equations (e.g., number of calibration samples). Thus, direct inversion does not always yield a unique solution. Second, even if a pseudoinverse exists and results in a unique solution, the solution tends to be unstable because all measurements contain noise and error. That is, small variations in c or S can lead to large variations in b. Underdetermined and unstable models can be avoided by using data reduction methods, such as factor analysis, which reduce the dimensionality of the spectral data and much of the underlying noise within each spectrum. 

Cell culture technology can be a viable alternative to animal testing in many cases, with the possibility of increasing significantly the number of replicate samples and thus expanding the bioassay utility. Primary cell cultures have the advantage that they maintain most of the characteristics of the animal tissue from which the cells are derived. These would be ideal for bioassays except that they cannot be kept in culture indefinitely. They can be difficult and sometimes impossible to grow reproducibly, and are subject to the inherent variability of the animal they come from. 

Lawson (1994) examined levels of aromatic amine migration from a number of laminate samples. Specially prepared laminate pouches containing distilled water were boiled for one hour and tested for primary aromatic amine (PAA) migration using a diazotisation procedure. Olive oil migration data at the same temperature was also obtained. Results are shown in Table 16.5 (detection limit 0.3 t,g dm ). These results, if expressed using the conventional surface area to volume ratio of 6 dm per kg of food, would range between 3 and... 

The surface chemical properties of the carbon materials were characterized as follows measurement of pH of carbon slurries (in 0.1 M NaCl solution) [89] neutralization with bases of different strength and dilute HCl according to Boehm s method [63,66] determination of total oxygen/nitrogen content by elemental analysis (with an accuracy of 0.2%) [170] mass loss of carbon samples after heat treatment in a vacuum. Additionally, the number of primary adsorption centers (a,)) was determined from water vapor adsorption isotherms according to the Dubinin-Serpinsky method [171], as was the heat of immersion in water for selected samples [111,172]. The results of these operations are pre.sented in Table 3. For all samples transmission Fourier Transform Infrared (FTIR) spectra and X-ray photoelectron spectra (XPS) were recorded. 

Because the degree of coalescence was low and constant, the strength of the catalysts in this series of experiments was determined entirely from the number of primary contacts, as illustrated in Scheme 21. This average "coordination number" is a function of the pore volume of the silica but not of its surface area. In any two samples of equal pore volume, large primary particles have the same number of contacts with other particles, as do small primary particles. Consequently, the strength of the silica matrix is, in this experiment, a function of the pore volume only, and not of surface area. Indeed, the melt elasticity of these polymers was found to be dependent on pore volume only in this series [500,521],... 

The SIMS process, as it relates to polymers, is characterized by three important parameters ion yield, transformation probability, and disappearance cross section. The ion yield (Y) is the ratio of the number of secondary ions produced divided by the number of primary ions incident on the sample Y = N(si)/N(pi). SIMS bombardment of a surface covered by a monolayer or less results in an exponential decay of the measured signal intensity 1(f) = I° exp[-(7(x)ypf/e] where is the primary ion current density, X the species measured, and cthe disappearance cross section. Thus <7 can be calculated from SIMS intensity decay curves. The disappearance cross section is the damage area caused by the primary ion which leads to desorption of a polymer molecule. 

The requirement that samples be in the vapor phase used to be a limiting factor in the utility of mass spectrometry because it was frequently necessary to add heat to vaporize samples. Successful vaporization depends on the polarity and molecular mass of the analyte. For small molecules (<1 kDa) polarity is the most important factor, particularly the number of primary amino (-NH2), hydroxyl (-OH), and acidic (-COOH) groups present. When there are two or three of these groups present, heating will frequently destroy compounds before they vaporize, even at reduced pressures. Chemical derivatization, e.g., the conversion of an alcohol to its trimethylsilyl ether or the acetylation of an acid group, can be used to reduce the polarity and increase the volatility of analytes, thereby improving the chances of obtaining useful spectra. 

---