Problems in prediction

One of the problems in predicting efficiency and required pressure drop of a venturi is the chemical nature or wettability of the particulate, which on 0.5-pm-size particles can make up to a threefold difference in required pressure drop for its efficient coUection. Calvert... 

The problem in predicting the yield characteristics of a grass/white clover sward is that the relationship between yield and proportion of white clover in the sward is not linear. Grass/white clover swards yield more dry matter than either grass or white clover swards on their own, but the point where increasing the amount of white clover in the sward actually decreases total yield has not been defined experimentally. 

A major problem in predicting protein structure is the computational intractability. A short, 100-residue protein will contain at least 100 side-chain-to-side-chain or side-chain-to-solvent interactions. The orientation of each of these interactions will lead to cascading effects throughout the protein. Comparative modeling, threading algorithms, and de novo predictions seek to predict protein structure in reasonable execution times. 

Transferability to different temperatures is a particularly difficult task for polarizable water models. This statement is illustrated by the problems in predicting the PVT and phase coexistence properties. There are a handful of polarizable water models— including both dipole- and EE-based models— that are reasonably successful in predicting some of the structural and energetic changes in liquid water over a range of several hundred degrees. 

Although much is known about the reactive oxygen species, there are problems in predicting the probable extent of oxidation because it is often not known whether initiators are present. 

Some ecosy.stem processes are carbon neutral on a landscape scale because of disturbance-related variability but show distinct trends (positive and negative) at plot within landscapes. Relatively few types of direct measurements are possible at the landscape. scale and so the differences in plot and landscape behavior will be a major problem in predicting the effects of the implementation of the Kyoto protocol with respect to mitigation of the increase in atmospheric CO,. 

Wrinn MC. Whitehead MA. PCILO problems in predicting valid structure. Theochem 1986 30 197-205. 

However, there remain two major problems in predicting the Fg from in vitro or animal data. The first problem is the species differences in intestinal... 

All of the factors listed in Fig. 9.4 (and many more) could, potentially, influence the spread and biouptake of a metal. A central problem in predictive modeling is to quantitatively rank the importance of such factors and derive models that enable predictions of the y-variable, which in this example represents the metal content in top predator, from as few as easily obtainable and as relevant x-vari-ables as possible. 

Several recent Zero-Power Reactor (ZPR) cores that are suggested for future benchmarks are listed in Table I. these cores have been the subject of detaUed experimental and analytical investigations, tlie last two represent several essential features of a 3S0-MW(e) heterogeneous core and a 700-MW(e) homogeneous core. In addition to their usefulness for testing design-level methods and codes, the latter two cores have indicated problems in prediction of spatially varying parameters that are related to cross-section data. 

Inadequate understanding of product barrier requirements poses a package-design problem in predicting adequate shelf life from gas-transmission data. 

In optimizing planar chromatography, peak capacity in 2-D TLC far exceeds HPLC (13). PRISMA has also been very helpful by developing computerized and statistical choices for solvents. Demixing remains a major problem in predicting Rys and the ultimate experimental outcome vs. predicted. Again, 20 chromatograms define experimental variables for optimum Rf. Solvent selectivity (14) has been discussed based on proton donation, acceptance, or dipole interactions (IS). 

We suspect some variance between calculated and measured data Is due to Inconsistencies between various sets of data. This is shown in Tables 16 to 19 where calculated second vlrial coefficients are compared with literature data from various sources on water, CO2, hydrogen, and methane respectively. Calculated data in all four tables appear to agree with the experimental data almost within the scatter of the data. This demonstrates two things. One is that the comparison depends on whose data you compare with and the other is that predictability almost within experimental accuracy has been made without fitting virial coefficient data directly for both polar and non-polar compounds. One problem in predicting values at 3000 F is the lack of experimental data. This means that theoretical models for the second virial coefficient will have to be used in order to extend to these higher temperatures. 

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