In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.

If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. deleted from all document vectors. If term m is a good discriminator, valuable for content identification, then Q m > Q, that is, the document space after removal of term m will be more compact (because upon addition of that term, the documents will resemble each other less and the space spreads out). Thus for good discriminators Q m -Q>O. The reverse obtains for poor discriminators for which Q m -Q

A good deal of work has been done over the years in an attempt to use statistical or probabilistic techniques as a basis for automatic indexing and content analysis. (1–10) Unfortunately, many of these methods are lacking in effectiveness, and the more refined procedures are computationally unattractive. A new technique, known as discrimination value analysis, ranks the text words in accordance with how well they are able to discriminate the documents of a collection from each other; that is, the value of a term depends on how much the average separation between individual documents changes when the given term is assigned for content identification. The best words are those which achieve the greatest separation. The discrimination value analysis is computationally simple, and it assigns a specific role in content analysis to single words, juxtaposed words and phrases, and word groups or thesaurus categories. Experimental results are given showing the effectiveness of the technique.

In recent years, human pathogenic microorganisms have developed multiple drug resistance and caused serious nosocomial infections. In this study, we identified four new antimicrobial compounds from the Chinese herbal medicine Illicium verum and assessed their antibacterial efficacies. The supercritical CO₂ and ethanol extracts of Illicium verum showed substantial antibacterial activity against 67 clinical drug-resistant isolates, including 27 Acinetobacter baumannii, 20 Pseudomonas aeruginosa, and 20 methicillin-resistant Staphylococcus aureus. The diethyl ether (EE) fraction obtained from partition extraction and supercritical CO₂ extracts revealed an antibacterial activity with a minimum inhibitory concentration value of 0.15-0.70 mg/mL and 0.11 mg/mL, respectively. The EE fraction of I. verum showed synergetic effects with some commercial antibiotics. The antimicrobial mechanism was investigated with killing curves and scanning electron microscopy observation. The chemical components of the extracts were analyzed by spectrophotometry; (E)-anethole, anisyl acetone, anisyl alcohol, and anisyl aldehyde exhibited antibacterial activity against different clinical isolates. These extracts from I. verum can be further developed into antibiotic medicines due to their proven antibacterial activity.

NPs are a valuable resource, and the healthcare system demand is growing. Reasonable NP staffing, working hours, proper promotion systems, the causes of job stress, job content clarification and practical work shift scheduling need to be considered. The occupational safety and physical and psychological health of NPs are strongly associated with the quality of patient care.