Target mass, variability

Multivariate methods, on the other hand, resolve the major sources by analyzing the entire ambient data matrix. Factor analysis, for example, examines elemental and sample correlations in the ambient data matrix. This analysis yields the minimum number of factors required to reproduce the ambient data matrix, their relative chemical composition and their contribution to the mass variability. A major limitation in common and principal component factor analysis is the abstract nature of the factors and the difficulty these methods have in relating these factors to real world sources. Hopke, et al. (13.14) have improved the methods ability to associate these abstract factors with controllable sources by combining source data from the F matrix, with Malinowski s target transformation factor analysis program. (15) Hopke, et al. (13,14) as well as Klelnman, et al. (10) have used the results of factor analysis along with multiple regression to quantify the source contributions. Their approach is similar to the chemical mass balance approach except they use a least squares fit of the total mass on different filters Instead of a least squares fit of the chemicals on an individual filter. 

In on-mass mode, both Ql and Q2 are set to the same target mass. In this case, Ql controls which ions enter the collision/reaction cell. All masses except the analyte mass and any direct mass interferences are rejected by Ql only the analyte mass and any direct on-mass interferences pass into the collision/reaction cell. The ORS separates the analyte from interferences by neutralizing the interference or shifting it to a new mass. Q2 then rejects any cell-formed interferences except for the target analyte ion. The on-mass mode removes the variability seen in reaction cell systems caused by different samples (ions) changing the reaction processes and product ions. The on-mass mode is used when the analyte is not reactive, and the interferences are reactive with a particular cell gas. 

Gupta, A., and Manousiouthakis, V. (1993). Minimum utility cost of mass exchanger networks with variable single component supplies and targets. Ind. Eng. Chem. Res. 32(9). 1937-1950. 

In this paper the PLS method was introduced as a new tool in calculating statistical receptor models. It was compared with the two most popular methods currently applied to aerosol data Chemical Mass Balance Model and Target Transformation Factor Analysis. The characteristics of the PLS solution were discussed and its advantages over the other methods were pointed out. PLS is especially useful, when both the predictor and response variables are measured with noise and there is high correlation in both blocks. It has been proved in several other chemical applications, that its performance is equal to or better than multiple, stepwise, principal component and ridge regression. Our goal was to create a basis for its environmental chemical application. 

This paper describes a new reaction which may yield useful amounts of the product isotope following neutron capture by lanthanide or actinide elements. The trivalent target ion is exchanged into Linde X or Y zeolite, fixed in the structure by appropriate heat treatment, and irradiated in a nuclear realtor. The (n, y) product isotope, one mass unit heavier than the target, is ejected from its exchange site location by y recoil. It may then be selectively eluted from the zeolite. The reaction has been demonstrated with several rare earths, and with americium and curium. Products typically contain about 50% of the neutron capture isotope, accompanied by about 1% of the target isotope. The effect of experimental variables on enrichment is discussed. 

The selection of the volume-related and, therefore, intensively formulated variable kLa, this being the target quantity of the mass transfer process, implies the following consequences ... 

Fig. 11 RNA-targeted RBDCC. Cysteine position was encoded by resin size, while variable amino acids were selected to provide unique monomer mass...

---