Default value, defined

Checkbox fields contain a definition of the size of the checkbox and a default value defining whether the box is checked or not. 

You can specify the number and values of visible contour lines. You specify the total number of contour lines to be shown by simple stating the number, n>0. You normally specify the values of the contour lines as default values. For this case, HyperChem computes the maximum and minimum values on the grid and then draws contours at these values plus n-2 contour lines evenly spaced in between these maximum and minimum values. If you need non-default values, you can specify the starting value and then an increment to define the other n-1 evenly spaced contour lines. If default values were computed previously, HyperChem suggests the starting value and increment of the previous default computation for the new non-default option. 

When first running SAPHIRE for Windows, after installation, the Define Constants dialog appears for assigning default values to various functions. After saving the defaults the S.APliIRr window appears for selecting a family. 

Define Constants - specify file locations, archive information, uncertainty analysis settings, cutset generation, transformations, quantification constants, and set default values for the graphical editors. 

The following variables are given default values if the user does not explicitly define them ... 

A Dutch smdy (Wilschut et al. 1998, as reviewed in Vermeire et al. 1999) has evaluated route-to-route extrapolation on the basis of absorption or acute toxicity data. Data were collected primarily on dermal and inhalation repeated dose toxicity. An extrapolation factor, defined as the factor that is applied in route-to-route extrapolation to account for differences in the expression of systemic toxicity between exposure routes, was determined for each substance by using data on absorption and acute toxicity data. As experimental data on absorption often were not available, default values for absorption were also used to determine an extrapolation factor. Despite a rather large overall database, relatively few data could be used for the evaluation and the selection criteria were modified in order to include data that initially were considered less suitable for data analysis interspecies extrapolation based on caloric demands was introduced, and a factor of 3 was applied in case a LOAEL instead of a NOAEL was available. The choice of NOAELs for different exposure routes known for a substance suitable for analysis was based primarily on the same effect, but this criterion could not be maintained. 

WHO/IPCS (1994, 1996, 1999) did not consider an extrapolation factor for duration of exposure specifically, but the uncertainty related to this element is included in a broader defined additional factor addressing the adequacy of the overall database (Section 5.9). The US-EPA (1993) has adopted the 10-fold factor to account for the uncertainty involved in extrapolating from less than chronic NOAELs to chronic NOAELs. This default value has later on been reconfirmed (US-EPA 2002) when only a subchronic duration smdy is available to develop a chronic reference value no chronic reference value is derived if neither a subchronic nor a chronic smdy is available. For systemic effects, ECETOC (2001) recommended a default assessment factor of 6 for extrapolation from subacute (28 days) to chronic exposure, and a factor of 2 from subchronic (90 days) to chronic exposure. For local effects, no additional assessment factor is needed for duration of exposure extrapolation for substances with a local effect below the threshold of cytotoxicity. KEMl (2003) suggested that extrapolation from subchronic to chronic exposure should be based on the distribution of NOAEL ratios reported by Vermeire et al. (2001) with an assessment factor of 16 covering 95% of the substances compared and for extrapolation from subacute to chronic exposure, with an assessment factor of 39 covering 95% of the substances. 

The value of resistor RL is now the value of the parameter RLj/Sl. We must now define the parameter and assign it a default value. Double-click the LEFT mouse button on the text PARAMETERS ... 

This attribute box is used to define parameters. We will define RLyal as a parameter and give it a default value of lk. Click the New Column button to create a new parameter ... 

A prediction model must define all of the possible results that may be obtained from the alternative method. This is important since there are many different types of data available from typical alternative methods. Examples of data types include quantitative data, censored data, qualitative data, descriptive data, default values, and nonqualified... 

The initial process in the application of toxicity (dose-response) data in risk assessment is the extrapolation of findings to establish acceptable levels (AL) of human exposure. These levels may be reference values (inhalation reference concentrations, RfC or oral reference doses, RfD), minimal risk levels (MRL) values, occupational exposure limits, and so on. When the toxicity data are derived from animals, the lowest dose representing the NOAEL (preferably) or the LOAEL defines the point of departure (POD). In setting human RfD, RfC, or MRL values, the POD requires several extrapolations (see [13] and revisions). Extrapolations are often made for interspecies differences, intraspecies variability, duration of exposure, and effect level. Each area is generally addressed by applying a respective uncertainty factor having a default value of 10 their multiplicative value is called the composite uncertainty factor (UF). The UF is mathematically combined with the dose at the POD to determine the reference value ... 

Tentative heat of formation was defined by MOPAC. Calculation was started from initially defaulted value of inter-atomic distance in each sample Value of gradient by root-mean-square method Microwave spectroscopy cited in [13]... 

Metadata are an important concept of the biotransformation system. They provide additional information abont data objects and can be customized. Metadata consist at least of a name and a value. They may additionally contain flags, which describe special conventions for processing of metadata with the software. Administrators of the biotransformation system may define a set of metadata for a series of data types by name and default value. In addition, the user is able to define lists of metadata that can be used in certain visible list fields, like dropdown lists. 

Numeric fields have a definable format including length of integer and fractional parts. In addition, the validation includes upper and lower limit and a default value. 

Available models include both binary ( yes or no predictions, reported as probability of yes ) and quantitative value models (e.g., for inhibition constants in pM). The range of values considered as a hit for the QSAR model (and therefore defining a compound-protein association for binding type models) is user selectable (Fig. 4). The default values are 0.5-1 for binary models (i.e., >50% probability of a positive match to the model) and 50 pM - the lowest limit of the training set activity for binding activity models. Other model types (e.g., % serum protein binding) have default values appropriate for the model and the training set see Note 1). 

We can apply values to the parameters and the values n. We use s to define the number of CSTRs rather than n per se in order to avoid a name clash that leads to an infinite loop. Before we try this, however, we shall set the RecursionLimit to 1000. The default value of 256 is not sufficient for us to go out to numbers as large as n = 1000 CSTRs. 

An object from the previous classes, as it is defined, automatically receives a default value for the tolerances of the absolute (1. e-10) and relative (1. e-6) errors on the variables y. ... 

We can also define the minimum and maximum number of sites for a variant. It ranges from three to seven. Care must be taken while defining the number of site points because less number of sites may not contain all the features and more sites may result in no pharmacophores. Usually, default value 5 is considered. The must-match-at-least box will display the total number of actives present in our data by default. We can reduce the number in order to widen the search (less number of actives will give more number of variant lists). The completion of job displays the maximum number of hypotheses found for each variant (Fig. 4.68). 

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