Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Predictions effect

W. Majewski and D. C. Miller, eds.. Predicting Effects of Power Plant Once-Through Cooling on Aquatic Systems, Technical Papers in Hydrology 20, United Nations Educational, Scientific and Cultural Organization (Unesco), Paris, 1979. [Pg.480]

Many sophisticated models and correlations have been developed for consequence analysis. Millions of dollars have been spent researching the effects of exposure to toxic materials on the health of animals the effects are extrapolated to predict effects on human health. A considerable empirical database exists on the effects of fires and explosions on structures and equipment. And large, sophisticated experiments are sometimes performed to validate computer algorithms for predicting the atmospheric dispersion of toxic materials. All of these resources can be used to help predict the consequences of accidents. But, you should only perform those consequence analysis steps needed to provide the information required for decision making. [Pg.34]

TABLE 3A. PREDICTED EFFECT OF PRESSURE ON BOILING POINT ... [Pg.32]

N. Harbor Blvd. Database for 30 hazardous substances. 13 Suite 800 mathematical models that predict effects of release... [Pg.309]

FIGURE 10.79 Typical streamlines for the flow near the exhaust hood when there is (o) only suction. (b) some exhaust Bow, and (cl a large exhaust flow. (The flow is symmetrical about X = 0.) The shaded area represents the predicted effective capture region. [Pg.958]

TABLE 8.3.3 Predicted Effects on Human Health of Exposure to Various Conccnti-ations of Anhydrous Ainmoiiia" ... [Pg.259]

Using dose-response information from animal studies to predict effects in humans... [Pg.341]

Effect of chemical state on line Negligible except for predictable effects Often marked... [Pg.238]

In this equation, Summerfield has shown that the parameter b1 should be very sensitive to the flame temperature of the propellant. At the same time, the factor b2 should be strongly dependent on oxidizer particle size. To check these predictions, Summerfield prepared four propellants using 120 and 16 oxidizer particles at 75 and 80% loadings. Correlation of the burning-rate data with Eq. (39) yields the values for the parameters given in Table I. The experimentally observed trends are consistent with predicted effects. [Pg.45]

The results of calculations showing the size of the predicted effects are shown in Table 9-5. It gives the calculated quotient of k/kn for different charge types over a range of ionic strengths, 0-0.3 M. The effects are very sizable, because ions are much less ideal than nonelectrolytes. [Pg.207]

Respiration of organic matter and dissolution of CaCOs are the main controls of the distribution of deep ocean Total CO2 and alkalinity. These reactions (and their predicted effects on DIC and alkalinity) can be represented schematically as... [Pg.264]

In making the reasonable assumption that browser diets should have remained consistent through time, it was also assumed that C7 C ratios of their C3 foliage diets would not have changed. This is not the case environmental parameters such as aridity, osmotic stress, temperature, pCOi and irra-diance have predictable effects on ratios of C3 plants (summarized in... [Pg.96]

Based on the predicted effects on HIV-1 and T cell dynamics, antiviral genes have been grouped into three classes (Fig. 1) (von Laer et al. 2006b). Early inhibitors are classified as class 1, inhibitors of intracellular reproduction of the viral genome and production of viral gene product are class II, and late inhibitors are considered class 111. A comprehensive list of types of antiviral genes reported to date for each class is found in Table 1 (von Laer et al. 2006a). [Pg.272]

To summarize this section, we have seen that the possibility of quanmm tunneling between structurally close states in glass does have a predictable effect on the spectrum and must be taken into account when computing the density of low (and not so low) energy structural excitations in these materials. [Pg.178]

The combination of hydrophilic and hydrophobic parts of a molecule defines its amphiphilicity. A program has been described to calculate this property and calibrated against experimental values obtained from surface activity measurements [133]. These values can possibly be used to predict effect on membranes leading to cytotoxicity or phospholipidosis, but may also contain information, not yet unraveled, on permeability. Surface activity measurements have also been used to make eshmates of oral absorphon [126]. [Pg.40]

Models must be both realistic and also robust. A model which predicts effects which are quite contrary to common sense or to normal experience is unlikely to be met with confidence. To accord with this, some use of empirical adjustment factors in the model may be needed, in order to represent combinations of relatively unknown unknown factors. [Pg.3]

Parenteral administration of drugs by intravenous (IV), intramuscular (IM), or subcutaneous (SC) routes is now an established and essential part of medical practice. Advantages for parenterally administered drugs include the following rapid onset, predictable effect, predictable and nearly complete bioavailability, and avoidance of the gastrointestinal (GI) tract and, hence, the problems of variable absorption, drug inactivation, and GI distress. In addition, the parenteral route provides reliable drug administration in very ill or comatose patients. [Pg.384]

F. O. Clements, March 30, 1937. Source for predicted effects of TEL and doubts that TEL would increase car ownership. [Pg.217]

FIGURE 1.16 The predicted effect of three concentrations of a reversible competitive antagonist, B, on the log concentration-response relationship for an agonist. The calculation of the concentration ratio (r3) for the highest concentration of antagonist, [B]3, is illustrated. [Pg.43]


See other pages where Predictions effect is mentioned: [Pg.2478]    [Pg.151]    [Pg.258]    [Pg.342]    [Pg.87]    [Pg.365]    [Pg.1397]    [Pg.65]    [Pg.226]    [Pg.230]    [Pg.252]    [Pg.252]    [Pg.272]    [Pg.277]    [Pg.29]    [Pg.175]    [Pg.54]    [Pg.157]    [Pg.156]    [Pg.218]    [Pg.195]    [Pg.194]    [Pg.30]    [Pg.122]    [Pg.248]    [Pg.84]   
See also in sourсe #XX -- [ Pg.95 , Pg.96 , Pg.97 ]




SEARCH



A Predicting the Effect of Solids Loading on Cyclone Efficiency

B Predicting the Effect of Loading on Cyclone Pressure Drop

Branching effects, long chain prediction

Carcinogenic effect, prediction

Directing effects predicting products

Effect on predictivity

Effective concentration prediction

Effective prediction domain

Effectiveness of the Predictions

General Predictions on Kinetic Isotope Effects

General kinetic model and prediction of critical effects

Hall effect theoretical predictions

High Effectiveness of an HCA Cell Model in Predictive Toxicology

Hydrocarbon predicted values, effect

PNEC (Predicted no-effect

PREDICTED EFFECT OF PRESSURE ON BOILING POINT

PREDICTED NO-EFFECT

Plasma biological effect prediction

Predicted No-Effect Level

Predicted no effect concentration

Predicted no effect concentration PNEC)

Predicting Ecotoxicological Effects

Predicting Medication Effects

Predicting and Exploiting Steric Effects

Predicting the Clinical Efficacy of Asthma Drugs from Their Inhibitory Effect on Allergen Bronchoprovocation

Prediction of Clinical Effects from Pharmacological Data

Prediction of clinical effect

Prediction of explosive effects

Prediction of salt effect

Prediction of the adverse effects

Predictive methods effectiveness

Subject predicted effects

Teratogenic effects prediction

The Effect of Annealing-Case Studies and Predictability

Toxicity testing potential human adverse effects predicted

Understanding and predicting clinical drug effects

© 2024 chempedia.info