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The term ‘obsolescence’ occurs frequently in the literature of librarianship and information science. In numerous papers we are told how most published literature becomes obsolete within a measurable time, and that an item receives half the uses it will ever receive (‘half‐life’) in a few years. ‘Obsolescence’ is however very rarely defined, and its validity, interest, and practical value are often assumed rather than explained. Before reviewing studies on ‘obsolescence’, therefore, it is necessary to look at the concept and to identify the reasons why it should be of interest.

Sets out to provide a selected bibliography or recent resources on library instruction and information literacy.

Introduces and annotates periodical articles, monographs, and exhibition catalogues examining library instruction and information literacy.

Provides information about each source, discusses the characteristics of current scholarship, and describes sources that contain unique scholarly contributions and quality reproductions.

The information may be used by librarians and interested parties as a quick reference to literature on library instruction and information literacy.

A lot of triaxial compressive models for different concrete types and different concrete strength classes were proposed to be used in structural analyses. The existence of so many models creates conflicts and confusions during the selection of the models. In this study, reliability analyses were carried out to prevent such conflicts and confusions and to determine the most reliable model for normal- and high-strength concrete (NSC and HSC) under combined triaxial compressions. The paper aims to discuss these issues.

An analytical model was proposed to estimate the strength of NSC and HSC under different triaxial loadings. After verifying the validity of the model by making comparisons with the models in the literature, reliabilities of all models were investigated. The Monte Carlo simulation method was used in the reliability studies. Artificial experimental data required for the Monte Carlo simulation method were generated by using artificial neural networks.

The validity of the proposed model was verified. Reliability indexes of triaxial compressive models were obtained for the limit states, different concrete strengths and different lateral compressions. Finally, the reliability indexes were tabulated to be able to choose the best model for NSC and HSC under different triaxial compressions.

Concrete compressive strength and lateral compression were taken as variables in the model.

The reliability indexes were tabulated to be able to choose the best model for NSC and HSC under different triaxial compressions.

A new analytical model was proposed to estimate the strength of NSC and HSC under different triaxial loadings. Reliability indexes of triaxial compressive models were obtained for the limit states, different concrete strengths and different lateral compressions. Artificial experimental data were obtained by using artificial neural networks. Four different artificial neural networks were developed to generate artificial experimental data. They can also be used in the estimations of the strength of NSC and HSC under different triaxial loadings.