Number analysis

Composite value refers to the average of all sample analyses. Number of replicate analyses appears in parentheses. A complete listing of the data for the individual... 

Database generated Diagnostic activity in the ares (number of TSH, T4, and T3 analyses) Number of subjects with abnormal blood test results Number of subjects with new biochemical hyper- or hypothyroidism ... 

Fuel and Energy Abstracts. Available via ScienceDirect, also published bi-monthly in paper copy. Provides summaries of world literature on scientific, technical, environmental, and commercial aspects of fuel and energy. Covers over 800 international publications, monographs, conference proceedings, reports, surveys, and statistical analyses. Number of abstracts per issue can vary from 500 to 800. The online indexing is inconsistent. Individual abstracts are indexed in most issues. However, in newer issues, the citations are buried under headings, such as Liquid Euels, Heat Pumps, and Fuel Science and Technology, and cannot be retrieved without a secondary keyword search of the actual subject index of a particular issue. 

Leren ce Limbe rs design s design s al designs ce designs situatio ns ns desig ns pages calculation s and analysis number of references leve emphas... 

Historical control data for fertility studies at Ricerca Biosciences with CrI Wistar sperm analysis—number in epididymis and motility... 

Page numbers in bold-faced type refer to experimental procedures. Numbers followed by an asterisk refer particularly to qualitative organic analysis. Numbers followed by a dagger t refer to apparatus with ground glass joints. Numbers followed by a double dagger refer to reaction mechanisms. 

Occasionally a species of whito lead is produced by tho Dutch method, which yields on analysis numbers corresponding to the formula 3 (Pb 0, COa) Pb 0, IIO that is, three equivalents of carbonate to one of oxide of lead. It has a loose friable texture when drawn from the heights, quite distinct from the hard cratos of whito lead obtained when the metal is almost wholly converted and is invariably the result of defective corrosion of tho motal. This kind of white lead does not cover so well as the hard lead. 

Figure 18. Analysis of the product spectrum in Figure 17. Asterisks indicate composite bands used for the product analysis. Numbers in parentheses represent ppm.

Figure E3.4.3 Representative chromatograms. (A) Acetic acid standard (0.4 mg). (B) Methanol standard (2.0 mg). (C) Pectin sample. The start of each recording begins 12 min into HPLC analysis. Numbers above each peak refer to minutes elapsed after start of recording. The additional peaks in (C) are presumably due to other alcohols and acids released by alkaline treatment.

Analysis Number Sample Description Styrene content (mg/kg)... 

Page, A. L., MiUer, R. H., and Keeney, D. R. (eds.). (1982). Methods of Soil Analysis, Number 9, Part 2. Soil Science Society of America, Madison, WI. 1159pp. 

COMPOUND LOT CODE DATA AVG S.D. UNITS METHOD NO. ANALYSIS NUMBER... 

LOT ITEM NUMBER NUMBER MATERIAL VENDOR INFORMATION SUBMITTER DEPT. GROUP DATE RECEIVED OF RELEASE ANALYSIS NUMBER... 

These waters are derived from both pristine and polluted carbonate systems. The analyses are ordered according to their increasing TDS contents. The freshest waters have a prevalent chemical character (PCC) of the calcium-bicarbonate type. As TDS values increase, the waters become relatively more enriched in Na, Cl, and/or SO4. The high Na and Cl content of analysis number 9 in Table 6.7 (TDS = 1269 mg/L) is derived from its pollution by sewage. The even higher Na and Cl concentrations of analysis number 10 reflect the fact that waters in the X-Can well, which is in coastal Yucatan, have been mixed with seawater. 

Fig. 10. Chondrite-normalized REE patterns of (A) siderite, ankerite and (B,C) calcite in the Oseberg Formation. The numbers in the key boxes refer to the analysis numbers in Table 4. In (C) a same symbol shape denotes different samples coming from a single calcite-cemented layer in a same well.

N Number of zones or sections in a numerical analysis, number of hypothetical... 

Fig. (14). A Experimental vs. calculated pIC o values from a QSAR model for inhibitory effect of 28 STLs on NF-kB activation (biological data from [59], structures see Fig. (12)). The model was generated by GA-PLS analysis (number of latent variables 3) from the 8 descriptors shown in the loading weights plot (B). This plot illustrates the impact of each descriptor on the first two latent variables (PCI and PC2) explaining 54 % and 27 % of the variance in the Y data (pIC o), respectively.

EDX analysis (number 1 and 2) of the relation of Si and O in the sample SHF is realized in TEM micrograph of Fig. lb. The same analysis is made on SAHMI (number 3) and SAHMII (number 4 and 5) samples and the results are shown in Table 2. EDX analysis corroborates the presence inside of silica framework of the two modifiers, which besides, are identified in particular form as it can be observed on micrographs and by EDX analysis. The presence of HS induces hydrophobic properties on the synthesized silicas so they seem to float on water when the HS quantities showed on Table 1 are used. It is important to emphasize that when ethanol is used to wet the tested silicas, they interact with their free surface OH groups and get wet. This behaviour could be due to the umbrella effect [7] which is produced by the AP that covered the surface OH. 

The molecular descriptors for a CoMFA analysis number in the hundreds or thousands, even for datasets of twenty or so compounds. A multiple regression equation cannot be fitted for such a dataset. In such cases. Partial Least Squares (PLS) is the appropriate method. PLS unravels the relationship between log (1/C) and molecular properties by extracting from the data matrix linear combinations (latent variables) of molecular properties that best explain log (1/C). Because the individual properties are correlated (for example, steric properties at adjacent lattice points), more than one contributes to each latent variable. The first latent variable extracted explains most of the variance in log (1/C) the second the next greatest degree of variance, etc. At each step iP and s are calculated to help one decide when enough variables have been extracted—the maximum number of extracted variables is found when extracting another does not decrease x substantially. Cross-validation, discussed in Section 3.5.3, is commonly used to decide how many latent variables are significant. For example, Table 3.5 summarizes the CoMFA PLS analysis... 

Regression Analysis number versus amount Regression Analysis number versus amount... 

---