Modeling importance

A product can be a real product that is producible on a set of resources. A description for a process is stored as a product, because processes often produce a product. As an abstraction a product also represents a production step/step in a work flow in the optimization model. Important data are, for example ... 

Nash, H. A., Tobias, J. M. Phospholipid membrane model Importance of phosphatidyl serine and its cation exchanger nature. Proc. Nat. Acad. Sci. (Wash.) 51,476 (1964)... 

Kong, G., Anyarambhatla, G., Petros, W.P, et al. Efficacy of liposomes and hyperthermia in a human tumor xenograft model Importance of triggered drug release. Cancer Res. 60(24) 6950-6957. 2000. 

Well determined masses of nuclei which lie far from beta stability can provide very sensitive tests of atomic mass models While a single new mass measurement from one previously uncharacterized isotope carries with it only limited information about the quality of mass predictions from the models, important trends frequently become evident across isotopic sequences or when global comparisons of many new masses are made against the various mass models It is in this context that a comprehensive and critical assessment of the predictive properties of atomic mass models is presented with the aim of identifying both the successes and failures in the models A summary of a portion of this effort has been published earlier [HAU84] ... 

The technique of ANCOVA allows more than one covariate to be added to the analysis model. This means that a wide range of variables measured at baseline can potentially be used. While this possibility can initially appear advantageous, it raises a potential concern. Using all of the possible variables is neither practical nor desirable, and so a decision has to be made concerning which ones to include in the ANCOVA model. Importantly, if the covariate is not related to the primary variable of interest, including it in the ANCOVA model is of no benefit. 

P. O Brien, and A. Kortenkamp, Chemical models important in understanding the ways in which chromate can damage DNA. Environ. Health Perspect. 102(suppl. 3) 3, 1994. 

A limitation of off-line feedback mechanisms is an implicit assumption that a single iteration NWP-ACTM-NWP is sufficient to reflect the bulk of the impact of chemical composition onto meteorology. This assumption is fulfilled in almost all cases but larger number of iterations might be needed in case of very strong deviation of the atmospheric composition from the default values assumed in the NWP model. Importance of this limitation and reasonable number of iterations needed for e.g. a dust storm simulations need investigation. 

When a model has been obtained, it is necessary to evaluate the fit of the model, by comparing for each of the points the experimental value obtained for the response and the value predicted with the model. Important differences indicate that the model is not adequate and that a more complex model (see below) may be needed. To have still more confidence in the model, validation can be carried out. This requires that new chromatograms be obtained at different x-values from those obtained with the experimental design. Again the experimental and predicted response values are compared. 

Recently, OECD work has focused on exposure assessment including estimation of emission, monitoring, and modeling. Important products are the OECD Emission Scenario Documents (ESDs). 

In order to use sink models, important parameters must be available. For example, the Langmuir adsorption model requires information on the rates of adsorption and desorption. Diffusion models require information on the diffusion coefficients. These parameters are dependent upon the characteristics of both the VOC (or SVOC) and the sink material, and fundamental data are generally not available. Thus, experimental studies are required to determine the values of the important parameters of the sink models. 

Similarly, the core of the Document Model is self-contained. However, it relies on a product data model to describe the contents of documents (cf. Subsect. 2.3.4). Thus, the domain-specific extension of the Document Model imports OntoCAPE as a means to characterize the documents created or used in an engineering design project. 

Conceptually, for each bootstrap replication a selection method is used to identify the significant covariates and the deterministic model. Important predictive covariates should be included in most bootstrap replications, as it is assumed that each replication should reflect the underlying data structure. Therefore, an important covariate should be included in nearly all of the bootstrap replications. 

Once one or more postulated mechanisms have been formulated, we can begin identifying factors that may influence reaction rates. These factors would then be examined as part of an experimental program, and would also be a part of a complete reaction model. Important factors usually include concentrations of participating species, ionic strength, pH, temperature, and character and intensity of radiation (in the case of photochemical reactions). 

An adequate understanding of the mechanism of action of a biopharmaceutical facilitates the selection of relevant pre-clini-cal animal models. Important mechanism of action considerations for biopharmaceuticals include exact knowledge of the epitope target of mAbs, receptor binding and... 

A mass transfer model has been developed for the pulse plating of copper into high aspect ratio sub-0.25 micron trenches and vias. Surface and concentration overpotentials coupled with the shape change due to the deposition on the sidewalls and the bottom of the tiench/via with time have been explicitly accounted for in the model. Important parameters have been identified and their physical significance described. The resulting model equations have been solved numerically as a coupled non-linear free boundary problem. A complete parametric analysis has been performed to study the effect of the important parameters on the step coverage and deposition rate. In addition, a linear analytical model has also been developed to obtain key physical trends in the system. 

The studies of elementary films formed in inverse emulsions and stabilized by different synthetic and natural surfactants revealed that the membrane electric conductivity experiences a sharp increase upon the addition of some biologically active surfactants. For instance, membrane conductivity may increase by five orders of magnitude when trace amounts of valinomycin antibiotic are introduced into the outer aqueous medium of lipid membrane. At the same time the membrane becomes permeable to potassium and hydrogen ions but impermeable to sodium ions. A sharp decrease in electric resistance of synthetic membranes is observed when proteins and enzymes with suitable substrates are introduced into them. By studying the properties of such membranes one may model important biological processes, e.g. the transfer of neural impulses. 

Limited Number of Success Models Important to the success of any scientific field is the presence of success models which can serve as role models for further developments and which can serve as examples of the field s potential. These success models are particularly important if the field is to be taken seriously and to be funded adequately. They are also important for attracting researchers into the field, and for maintaining the morale of Aose who are already there. It is thus important that ITS have success models. What characteristics would such success models have An interesting analogy can be made with AI, which provides instructive lessons about the nature of success models, and how they are use l. 

The Ionic Bonding Model Importance of Lattice Energy How the Model Explains the Properties Polar Covalent Bonds and Bond Polarity... 

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