A Two-Stage Approach to First Order Default Reasoning

1996 ◽  
Vol 28 (3,4) ◽  
pp. 377-402 ◽  
Author(s):  
Karl Schlechta
Keyword(s):  
Default Reasoning ◽  
Two Stage ◽  
First Order

Evaluation of sampling alternatives to quantify tree leaf area

2003 ◽  
Vol 33 (1) ◽  
pp. 82-95 ◽  
Author(s):  
H Temesgen
Keyword(s):  
Leaf Area ◽  
Poor Performance ◽  
Tree Crown ◽  
Two Stage ◽  
Zero Bias ◽  
Probability Sampling ◽  
First Order ◽  
Unequal Probability Sampling ◽  
Unequal Probability ◽  
Tree Leaf

High within- and among-tree crown variation have contributed to the difficulty of tree-crown sampling and single-tree leaf area (area available for photosynthesis) estimation. Using reconstructed trees, simulations were used to compare five sampling designs for bias, mean square error (MSE), and distribution of the estimates. All sampling designs showed nearly zero bias. For most sample trees, stratified random sampling resulted in the lowest MSE values, followed by ellipsoidal, two-stage systematic, simple random, and then by two-stage unequal probability sampling. The poor performance of two-stage unequal probability sampling can be ascribed to the unequal probability of inclusion of first-order branches and twigs.

A Test of a Two-Stage Model of the Evaluation of Hypotheses from Quantified First-Order Predicate Logic in Information Use Tasks

1992 ◽  
Vol 71 (3_suppl) ◽  
pp. 1091-1104 ◽  
Author(s):  
Peter E. Langford ◽  
Robert Hunting
Keyword(s):  
Predicate Logic ◽  
Information Use ◽  
Stage Model ◽  
Two Stage ◽  
First Order ◽  
Alternative Hypotheses ◽  
Age Range ◽  
Hypothesis Evaluation ◽  
Universe Of Discourse ◽  
First Order Predicate Logic

480 adolescents and young adults between the ages of 12 and 29 years participated in an experiment in which they were asked to evaluate hypotheses from quantified first-order predicate logic specifying that certain classes of event were necessarily, possibly, or certainly not included within a universe of discourse. Results were used to test a two-stage model of performance on hypothesis evaluation tasks that originated in work on the evaluation of conditionals. The two-stage model, unlike others available, successfully predicted the range of patterns of reply observed. In dealing with very simple hypotheses subjects in this age range tended not to make use of alternative hypotheses unless these were explicitly or implicitly suggested to them by the task. This tells against complexity of hypothesis as an explanation of the reluctance to use alternative hypotheses in evaluating standard conditionals.

The kinetics and the mechanism of oxidative decarboxylation of benzilic acid by acidic permanganate (stopped-flow technique) — An autocatalytic study

2004 ◽  
Vol 82 (9) ◽  
pp. 1372-1380 ◽  
Author(s):  
Sairabanu A Farokhi ◽  
Sharanappa T Nandibewoor
Keyword(s):  
Activation Parameters ◽  
Oxidative Decarboxylation ◽  
Two Stage ◽  
First Order ◽  
First Order Kinetics ◽  
Stage Process ◽  
Benzilic Acid ◽  
Reaction Constants ◽  
Kinetics Of ◽  
Good Agreement

The kinetics of the oxidation of benzilic acid by potassium permanganate in an acidic medium were studied spectrophotometrically. The reaction followed a two-stage process, wherein both stages of the reaction followed first-order kinetics with respect to permanganate ion and benzilic acid. The rate of the reaction increased with an increase in acid concentration. Autocatalysis was observed by one of the products, i.e., manganese(II). A composite mechanism involving autocatalysis has been proposed. The activation parameters of the reaction were calculated and discussed and the reaction constants involved in the mechanisms were calculated. There is a good agreement between the observed and calculated rate constants under different experimental conditions.Key words: oxidation, autocatalysis, benzilic acid, two-stage kinetics.

First-order conditional logic for default reasoning revisited

2000 ◽  
Vol 1 (2) ◽  
pp. 175-207 ◽  
Author(s):  
Nir Friedman ◽  
Joseph Y. Halpern ◽  
Daphne Koller
Keyword(s):  
Default Reasoning ◽  
Conditional Logic ◽  
First Order

scholarly journals Pharmacodynamic Variability beyond That Explained by MICs

2013 ◽  
Vol 57 (4) ◽  
pp. 1730-1735 ◽  
Author(s):  
Rachel L. Soon ◽  
Neang S. Ly ◽  
Gauri Rao ◽  
Lance Wollenberg ◽  
Kuo Yang ◽  
...  
Keyword(s):  
Compartment Model ◽  
Free Drug ◽  
Maximum Effect ◽  
Bacterial Strains ◽  
Target Attainment ◽  
Two Stage ◽  
First Order ◽  
Drug Concentrations ◽  
Two Compartment Model ◽  
Separate Site

ABSTRACTMonte Carlo simulations (MCS) present a powerful tool to evaluate candidate regimens by determining the probability of target attainment. Although these assessments have traditionally incorporated variability in pharmacokinetic (PK) parameters and MICs, consideration of interstrain pharmacodynamic (PD) variability has been neglected. A population PK/PD model was developed for doripenem using murine thigh infection data based on 20 bacterial strains. PK data were fit to a linear two-compartment model with first-order input and elimination processes and an absorption lag time from a separate site (r2> 0.96). PK parameters were utilized to simulate free-drug profiles for various regimens in PD studies, from which the percentage of the dosing interval for which free-drug concentrations exceed the MIC of the targeted strain (%fT>MIC) was calculated. Doripenem PD was excellently described with Hill-type models (r2> 0.98); significant differences between mean PD estimates determined using a two-stage approach versus population analyses were not observed (P> 0.05); however, the variance in 50% effective concentration (EC50) and maximum effect (Emax) among strains was much greater using the two-stage approach. Even using the population approach, interstrain variability in EC50(coefficient of variation expressed as a percentage [CV%] = 29.2%) andH(CV% = 46.1%) parameters was substantive, while the variability inEmax(CV% = 19.7%) was modest. This resulted in extensive variability in the range of %fT>MIC targets associated with stasis to those associated with a 2-log10reduction in bacterial burden (CV% ∼ 50%). It appears that MCS, based on the assumption that PD variability is due to MIC alone, underestimates variability and may consequently underestimate treatment failures.

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