SEARCH TEXT derivatives

The revolution dans la maniere de traduire called for by Chateaubriand may partly be attributed to the impact of the Romantic movement, which, in its focus on individuality and original creation gave more importance to the source text, derivative writing receiving less priority.46 In addition, the Romantic taste and search for the new in content and form gave close translation a privileged role as it chal-... 

Web in the life of the medicinal chemist. One may see the development of alerting services for the primary medicinal chemistry journals. The Web-based information search process could be replaced by a much more structured one based on metadata, derived by automated processing of the original full-text article. To discover new and potentially interesting articles, the user subscribes to the RSS feeds of relevant publishers and can simply search the latest items that appear automatically for keywords of interest. The article download is still necessary, but it may be possible for the client software to automatically invoke bibliographic tools to store the found references. Another application of the Chemical Semantic Web may be as alerting services for new additions to chemical databases where users get alerts for the new additions of structures or reactions. 

All chemical shift data presented in this book come either from the primary literature or from spectra obtained in the author s laboratory. All spectra actually depicted in the book derive from spectra obtained by the author at the University of Florida. All data from the literature were obtained via searches using MDL Crossfire Commander or SciFinder Scholar. Persons interested in accessing such primary literature can do so readily via these databases by simply searching for the specific compound mentioned in the text. 

The name of the function is Voh. It has 2 input arguments (1,2). The first input will be the derivative of the trace, and the second input will be the trace itself. To use this function we would type Voh(d(V(Vo)), V(Vo)), where d(V(Vo)) is the derivative of the output trace and V(Vo) is the output trace. 1 search forward level means search the first input forward and find a level. The level we are looking for is -1. When the point is found, the text 1 designates its coordinates as xl and yl. Since the first input is the derivative of the trace, 11 search forward level (-1) 11 finds where the slope of the trace is -1. 2 search forward xvalue(xl) 2 searches the second input forward and finds the point when the x-coordinate is equal to x1. This point is where the slope of the transfer curve is -1. 12 marks the coordinates of this point as x2 and y2. The function returns the y-coordinate of this point Voh(1,2)=y2, which is equal to V0h-A second function is ... 

Deriving electrical energy from nuclear fission produces almost no atmospheric pollutants, such as carbon dioxide, sulfur oxides, nitrogen oxides, heavy metals, and airborne particulates. Although not discussed in the text, there is also an abundant supply of fuel for nuclear fission reactors in the form of plutonium-239, which can be manufactured from uranium-238. Use the keyword Breeder Reactor on your Internet search engine to learn about how this is so. 

The vector on the left is not the same as the vector (D ) on which the matrix S acts. Hence, the action of S on a vector is not equivalent to taking the derivative of this vector as required by Eq. (11) of text. The above matrices S and D, however, are used in establishing the required transformation. Let us search for the required transformation by a different route. 

Books and I blications. Some of the general references that should not be overlooked in a search of this sort designed to yield information on sulfur compounds is that material that can be obtained from some of the standard encyclopedias and reference texts, for example, The Science of Petroleum 182), Ellis, The Chemistry of Petroleum Derivatives 184), Sachanen, The Chemical Constituents of Petroleum ... 

Several computational methods for generating large databases of chemically reasonable structures (virtual libraries) have been developed. They employ strategies such as the mutation of text strings representing chemical structures, the expansion of Markush structural representations, or virtual combinatorial libraries derived by exhaustive enumeration of all substituent variations at specific points on a core scaffold. An example of these large virtual libraries is the ChemSpace database, containing approx 10 trillion chemical structures for use in similarity and pharmacophore searches, approx 500,000 times more than all the compounds in Chemical Abstracts. 

---