Selectivity optimization evaluation

Current research in LHASA is focused on developing new methods assisting users in choosing the most appropriate strategy for their target structures. Furthermore, the development of criteria for the evaluation of synthesis routes and/or algorithms for selecting optimal synthesis routes within the tree are discussed [34]. 

The early in vivo evaluation of compounds that demonstrate acceptable in vitro potency and selectivity requires evaluation of each compound alone in order to demonstrate antithrombotic efficacy. The antithrombotic landscape is becoming complicated by so many agents from which to choose that it will become increasingly difficult to design preclinical experiments that mimic the clinical setting in which poly-antithrombotic therapy is required for optimal efficacy and safety. Consequently, secondary and tertiary preclinical experiments will need to be carefully designed in order to answer these specific, important questions. 

Anderson, R.P., Lew, D., Peterson, A.T. 2003. Evaluating predictive models of species distributions criteria for selecting optimal models. Ecol. Model. 162 211-232. 

Once a mathematical model has been formulated, the researcher has the means to test his ideas and evaluate his concept of the system. In addition, different experimental situations can be simulated to select optimal protocol for experiments. 

The optimal set among all possible sets of given variables can, in principle, be characterized by the minimal probability of error calculated from F. Commonly, stepwise procedures are used to search for optimal sets in that either the variable causing the largest increase of P is added or that affecting the lowest decrease is eliminated in each step. Another F-test can then be used to calculate the contribution of each added (eUminated) variable to the class separation and, by this, to evaluate its indispensability or redundancy, respectively. With the intention to get well-interpretable results, the selected optimal set should contain only indispensable variables rather than reflect the absolnte minimum of the critical probability of error. 

A method is discussed here, which is based on OSBL conditions. This method can have a profound influence on evaluating project economics and thus determining the project selection. Improper project evaluation could lead to bad investment decisions bad projects are selected and good projects are discarded, which, regrettably, is common in energy optimization evaluations. To avoid the bad investment decisions and determine the true benefits for energy-saving projects, the effects on incremental steam, power, boiler feed water (BFW), and fuel balances must be assessed. A practical example is provided the next to illustrate how this method is applied. 

When carrying out an optimization based on the AHP, a correct optimization model including the selection of evaluation parameters and the determination of their weighting factors is significant for the accuracy of the analysis results since it is a decision-aiding method. To simplify calculations, only one kind of seismic input (longitudinal + vertical input) which could lead to the most adverse internal responses is employed. 

In GA-SVM, the quality of SVM for regression depends on several parameters namely, kernel type k, which determines the sample distribution in the mapping space, and its corresponding parameter o, capacity parameter C, and s-insensitive loss function. The three parameters were optimized in a systematic grid search-way and the final optimal model was determined. Six general statistical parameters were selected to evaluate the prediction ability of the constructed model. These parameters are root mean square error of prediction... 

When the objects to be differentiated are very different in chemical composition, a small number ofwavelengths are sufficient. For instance, HSl was evaluated for discriminating potato tubers from clods in the field and under varying humidity conditions [106]. The objective was to select optimal wavelengths to implement... 

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