Field Evaluation of High Modulus Asphalt Concrete Resistance to Low-Temperature Cracking

High-modulus asphalt concrete has numerous advantages in comparison to conventional asphalt concrete, including increased resistance to permanent deformations and increased pavement fatigue life. However, previous studies have shown that the construction of road pavements with High Modulus Asphalt Concrete (HMAC) may significantly increase the risk of low-temperature cracking. Those observations were the motivation for the research presented in this paper. Four test sections with HMAC used in base and binder courses were evaluated in the study. Field investigations of the number of low-temperature cracks were performed over several years. It was established that the number of new low-temperature cracks is susceptible to many random factors, and the statistical term “reversion to the mean” should be considered. A new factor named Increase in Cracking Index was developed to analyze the resistance of pavement to low-temperature cracking. For all the considered field sections, samples were cut from each asphalt layer, and Thermal Stress Restrained Specimen Tests were performed in the laboratory. Correlations of temperature at failure and cryogenic stresses with the cracking intensity observed in the field were analyzed. The paper provides practical suggestions for pavement designers. When the use of high modulus asphalt concrete is planned for binder course and asphalt base, which may result in lower resistance to low-temperature cracking of pavement than in the case of conventional asphalt concrete, it is advisable to apply a wearing course with improved resistance to low-temperature cracking. Such an approach may compensate for the adverse effects of usage of high modulus asphalt concrete.

Improving term candidates selection using terminological tokens

The identification of reliable terms from domain-specific corpora using computational methods is a task that has to be validated manually by specialists, which is a highly time-consuming activity. To reduce this effort and improve term candidate selection, we implemented the Token Slot Recognition method, a filtering method based on terminological tokens which is used to rank extracted term candidates from domain-specific corpora. This paper presents the implementation of the term candidates filtering method we developed in linguistic and statistical approaches applied for automatic term extraction using several domain-specific corpora in different languages. We observed that the filtering method outperforms term candidate selection by ranking a higher number of terms at the top of the term candidate list than raw frequency, and for statistical term extraction the improvement is between 15% and 25% both in precision and recall. Our analyses further revealed a reduction in the number of term candidates to be validated manually by specialists. In conclusion, the number of term candidates extracted automatically from domain-specific corpora has been reduced significantly using the Token Slot Recognition filtering method, so term candidates can be easily and quickly validated by specialists.

Bootstrapping and the Fossil Record

A new statistical term has been cropping up in the literature of paleobiological analysis: bootstrapping. This term, which refers to a relatively new general-purpose statistical method, has appeared in papers on subjects as diverse as rates of morphological change (Kitchell et al., 1987), patterns of morphological difference (between dextral and sinistral snail shells, for instance; Gould et al., 1985), survivorship analysis (Gilinsky, 1988), mass extinctions (Hubbard and Gilinsky, in press), the shapes of diversity paths (Gilinsky and Bambach, 1986), and periodicity of extinction (Connor, 1986). Some other papers do not explicitly mention the word bootstrapping, but nonetheless use methods that are quite similar (e.g., Raup and Sepkoski, 1984). Jennifer A. Kitchell convened an entire symposium on the subject at the Fourth North American Paleontological Convention in 1986. What is bootstrapping, and why is it being so widely applied in analytical paleobiology?

Analysis of the statistical S matrix generated in fitting 16O + 28Si elastic scattering

An S matrix, which gives very good fits for the elastic scattering of 16O + 28Si over the angular range 15° < θ < 180°, has been generated at six energies (21 MeV < E(centre of mass) < 35 MeV). The S matrix is composed of a parametric form plus a small statistical term for each partial wave. The properties of the S matrix have been examined in order to deduce the mechanisms involved in the reaction. The 180° excitation function has also been computed.