Attribute profile

There are four main types of data that frequently occur in sensory analysis pair-wise differences, attribute profiling, time-intensity recordings and preference data. We will discuss in what situations such data arise and how they can be analyzed. Especially the analysis of profiling data and the comparison of such data with chemical information calls for a multivariate approach. Here, we can apply some of the techniques treated before, particularly those of Chapters 35 and 36. 

The results from Table 5 illustrate the most acceptable product, from the point of view of purchase intent. Note that the product models in Table 4 also allow the product developer to estimate the likely sensory attribute profile of the optimum product, which also appears in Table 5. Thus, it becomes possible to rapidly achieve an optimum product, whilst at the same time predict its profile on sensory and image characteristics. 

Attribute profile or pattern-. If the order of attributes is fixed then the sequence of attribute values for a given object x can be thought of as visualized by a bar diagram. This we have in mind when we are speaking of a profile or pattern. 

Anti-chain Subset of the ground set, where all elements are mutually incomparable. An example is the anti-chain ( f, a, d, q1 q2, q, ). Any other element of the ground set added to the set f, a, d would introduce a comparability. Therefore f, a, d is a maximal anti-chain. Attribute profiles being results of monotonous variations as seen in chains are not considered as essentially different. Contrary, attribute profiles through anti-chains are essentially different. Hence the width, Wd(A ), of the poset is considered as a measure of diversity. 

As the sampling sites with high responses of the test-battery are of most interest, the maximal elements are taken as priority elements, i.e. the equivalence classes 27, 33, 46, 47, 31, 95, 32, 9, 18. From this we conclude that a) the sites 27, 33, 46, 47, 31, 95, 32, 9, 18 are of specific importance, and b) the set of sites 27, 33, 46, 47 has the same profile of scores, thus, they may be remedied by the same methods, whereas the attribute profiles differ among all other priority objects. 

The analysis by linear extensions is very attractive as it helps to derive a linear ranking, without any subjective preferences. The data lead to a poset, the poset may be analyzed with respect to its structure, this is a combinatorial problem, and finally a ranking probability can be derived. Crucially in this procedure is that very different attribute profiles may lead to the same Hasse diagram and thus to the same set of linear extensions and therefore finally to the same probability characteristics Thus, the attribute profiles a) (0,0), (1,0), (0,1), (1,1) and b) (0,0), (1,0), (0,5), (4,7) lead to identical Hasse diagrams. 

A priori this is fine as the first attribute definitely should compensate the second one. However, the sites, which belong to (1,0),(0,1) on the one side and (1,0), (0,5) on the other side will get the same averaged rank Thus, the analysis by linear extensions alone should be carried out with appropriate care. We continue the analysis of the poset and discuss the attribute profiles. 

Construct validity was tested by factor analyses of databases containing 3700 and 2200 jobs, which estabhshed 45 factors. Thiity-two of these fit neatly into the original six-division framework, with the remaining 13 being classified as overall dimensions. Further proof of construct vahdity was based on 76 human attributes derived from the PAQ, rated by industrial psychologists and the ratings subjected to principal components analysis to develop dimensions which had reasonably similar attribute profiles (McCormick 1979, p. 204). Interrehabihty, as noted above, was 0.79, based on another sample of 62 jobs. 

A number of friction studies have been carried out on organic polymers in recent years. Coefficients of friction are for the most part in the normal range, with values about as expected from Eq. XII-5. The detailed results show some serious complications, however. First, n is very dependent on load, as illustrated in Fig. XlI-5, for a copolymer of hexafluoroethylene and hexafluoropropylene [31], and evidently the area of contact is determined more by elastic than by plastic deformation. The difference between static and kinetic coefficients of friction was attributed to transfer of an oriented film of polymer to the steel rider during sliding and to low adhesion between this film and the polymer surface. Tetrafluoroethylene (Telfon) has a low coefficient of friction, around 0.1, and in a detailed study, this lower coefficient and other differences were attributed to the rather smooth molecular profile of the Teflon molecule [32]. 

PTFE is outstanding in this group. In thin films it provides the lowest coefficient of friction (0.03—0.1) of any polymer, is effective from —200 to 250°C, and is generally unreactive chemically. The low friction is attributed to the smooth molecular profile of PTFE chains which allows easy sliding (57). Typical apphcations include chemical and food processing equipment, electrical components, and as a component to provide improved friction and wear in other resin systems. 

Part of a 15-nm long, 10 A tube, is given in Fig. 1. Its surface atomic structure is displayed[14], A periodic lattice is clearly seen. The cross-sectional profile was also taken, showing the atomically resolved curved surface of the tube (inset in Fig. 1). Asymmetry variations in the unit cell and other distortions in the image are attributed to electronic or mechanical tip-surface interactions[15,16]. From the helical arrangement of the tube, we find that it has zigzag configuration. 

Fig. 17 shows the adsorption isotherms of all (undimerized and dimerized) particles. Except for a very fast increase of adsorption connected with filling of the first adlayer, the adsorption isotherm for the system A3 is quite smooth. The step at p/k T 0.28 corresponds to building up of the multilayer structure. The most significant change in the shape of the adsorption isotherm for the system 10, in comparison with the system A3, is the presence of a jump discontinuity at p/k T = 0.0099. Inspection of the density profiles attributes this jump to the prewetting transition in the... 

Fig. 6-6. Overload elution profiles of D,L-PA injected on a column (125 4 mm) packed with the L-PA imprinted stationary phase used in Fig. 6-5. Mobile phase MeCN TFA (0.01 %) FI O (2.5 %). The tendency for fronting and the increase in retention with sample load is attributed in part to saturation of the mobile phase modifier.

In typical rotating machinery, the vibration profile generated by a normal machine contains lower amplitudes in the vertical plane. In most cases, this lower profile can be directly attributed to the difference in stiffness of the vertical plane when compared to the horizontal plane. 

Morishima et al. [75, 76] have shown a remarkable effect of the polyelectrolyte surface potential on photoinduced ET in the laser photolysis of APh-x (8) and QPh-x (12) with viologens as electron acceptors. Decay profiles for the SPV (14) radical anion (SPV- ) generated by the photoinduced ET following a 347.1-nm laser excitation were monitored at 602 nm (Fig. 13) [75], For APh-9, the SPV- transient absorption persisted for several hundred microseconds after the laser pulse. The second-order rate constant (kb) for the back ET from SPV- to the oxidized Phen residue (Phen+) was estimated to be 8.7 x 107 M 1 s-1 for the APh-9-SPV system. For the monomer model system (AM(15)-SPV), on the other hand, kb was 2.8 x 109 M-1 s-1. This marked retardation of the back ET in the APh-9-SPV system is attributed to the electrostatic repulsion of SPV- by the electric field on the molecular surface of APh-9. The addition of NaCl decreases the electrostatic interaction. In fact, it increased the back ET rate. For example, at NaCl concentrations of 0.025 and 0.2 M, the value of kb increased to 2.5 x 108 and... 

Assume that the reaction occurs between the two uncharged species, MNNG and Am, with a rate constant kN. Express ks as a function of tN, K m, Kan, and [H. Sketch the anticipated pH profile. Actually, this situation is further complicated because kN, although constant over some pH range, shows a further variation that can be attributed to an acidic intermediate. Derive an expression for kN as a function of [H + ] from the scheme shown, denoting the acid ionization constant of the steady-state intermediate as Knl. 

There was a discrepancy between water salinity limits for the three locations, which may be attributed to factors related to difference in soil texture and stmcture. This affects soil infiltration capacity and water retention. These soil hydrologic characteristics influence salt development in the soil profile, which affects plant... 

The selective flux maximization from the FOIST scheme shown in Fig. 2 is achieved by altering the spatial profile of the initial state to be subjected to the photolysis pulse and since changes in flux are due to the flow of probability density, it is useful to examine the attributes of the probability density profiles from the field optimized initial states. 

Like enzymes, whole cells are sometime immobilized by attachment to a surface or by entrapment within a carrier material. One motivation for this is similar to the motivation for using biomass recycle in a continuous process. The cells are grown under optimal conditions for cell growth but are used at conditions optimized for transformation of substrate. A great variety of reactor types have been proposed including packed beds, fluidized and spouted beds, and air-lift reactors. A semicommercial process for beer used an air-lift reactor to achieve reaction times of 1 day compared with 5-7 days for the normal batch process. Unfortunately, the beer suffered from a mismatched flavour profile that was attributed to mass transfer limitations. 

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