Normal maps vs. visible images: Comparing classifiers and combining modalities

This work investigates face recognition based on normal maps, and the performance improvement that can be obtained when exploiting it within a multimodal system, where a further independent module processes visible images. We first propose a technique to align two 3D models of a face by means of normal maps, which is very fast while providing an accuracy comparable to well-known and more general techniques such as Iterative Closest Point (ICP). Moreover, we propose a matching criterion based on a technique which exploits difference maps. It does not reduce the dimension of the feature space, but performs a weighted matching between two normal maps. In the second place, we explore the range of performances offered by different linear and nonlinear classifiers, when applied to the normal maps generated from the above aligned models. Such experiments highlight the added value of chromatic information contained in normal maps. We analyse a solid list of classifiers which were selected due to their historical reference value (e.g. Principal Component Analysis) or to their good performances in the bidimensional setting (Linear Discriminant Analysis, Partitioned Iterated Function Systems). Last but not least, we perform experiments to measure how different ways of combining normal maps and visible images can enhance the results obtained by the single recognition systems, given that specific characteristics of the images are taken into account. For these last experiments we only consider the classifier giving the best average results in the preceding ones, namely the PIFS-based one.     

A gender analysis of top scientists’ collaboration behavior: evidence from Italy

Scientometrics - This work analyzes the differences in collaboration behavior between males and females among a particular type of scholars: top scientists, and as compared to non top scientists....     

The effect of multidisciplinary collaborations on research diversification

This work verifies whether research diversification by a scientist is in some measure related to their collaboration with multidisciplinary teams. The analysis considers the publications achieved by 5300 Italian academics in the sciences over the period 2004–2008. The findings show that a scientist’s outputs resulting from research diversification are more often than not the result of collaborations with multidisciplinary teams. The effect becomes more pronounced with larger and particularly with more diversified teams. This phenomenon is observed both at the overall level and for the disciplinary macro-areas.     

Embryonic diapause and its regulation

Embryonic diapause, a condition of temporary suspension of development of the mammalian embryo, occurs due to suppression of cell proliferation at the blastocyst stage. It is an evolutionary strategy to ensure the survival of neonates. Obligate diapause occurs in every gestation of some species, while facultative diapause ensues in others, associated with metabolic stress, usually lactation. The onset, maintenance and escape from diapause are regulated by cascades of environmental, hypophyseal, ovarian and uterine mechanisms that vary among species and between the obligate and facultative condition. In the best-known models, the rodents, the uterine environment maintains the embryo in diapause, while estrogens, in combination with growth factors, reinitiate development. Mitotic arrest in the mammalian embryo occurs at the G0 or G1 phase of the cell cycle, and may be due to expression of a specific cell cycle inhibitor. Regulation of proliferation in non- mammalian models of diapause provide clues to orthologous genes whose expression may regulate the reprise of proliferation in the mammalian context.     

Diversity of stress tolerance in Lactobacillus plantarum, Lactobacillus pentosus and Lactobacillus paraplantarum: A multivariate screening study

Sixty-three strains of the taxonomically related species Lactobacillus plantarum subsp. plantarum, L. plantarum subsp. argentoratensis, L. paraplantarum and L. pentosus isolated from sourdoughs and other food and non-food sources and 14 strains of other members of the genus Lactobacillus were screened for their tolerance of acid, alkaline, heat, oxidative, osmotic, detergent and starvation stresses in order to evaluate the diversity of stress response. Most strains of the L. plantarum group were highly tolerant of acid, alkaline and osmotic stress and highly sensitive to detergent stress, while a larger diversity was found for other stress. Multivariate analysis allowed grouping the strains in clusters with similar response patterns. Stress response patterns in the L. plantarum group were similar to those of species of the L. casei/L. paracasei group but clearly different from those of other mesophilic Lactobacillus. No relationship was found between grouping obtained on the basis of stress response patterns and by genotypic fingerprinting (rep-PCR), nor with the taxonomic position or isolation source of the strains. Further experiments with selected strains showed that exponential phase cells were generally but not always more sensitive than stationary phase cells. The ability to grow under stressful conditions showed a slightly better correlation with the ecological conditions prevailing in the isolation niches of the strains.This study will be the basis for further investigations to identify and exploit the basis of diversity in the stress response of lactic acid bacteria.     

Generalized Discrete Radon Transforms and Their Use in the Ridgelet Transform

We introduce and study a new class of Radon transforms in a discrete setting for the purpose of applying them to the ridgelet and curvelet transforms. We give a detailed analysis of the p-adic case and provide a closed-form formula for an inverse of the p-adic Radon transform. We give conditions for a scaled version of the generalized discrete Radon transform to yield a tight frame, and discuss a direct Radon matrix method for the implementation of a local ridgelet transform. We then study the effectiveness of some types of the generalized Radon transforms in reducing a type of noise known as speckle that is present in synthetic aperture radar (SAR) imagery. Flavia Colonna received the M.A. degree and the Ph.D degree in mathematics from the University of Maryland (College Park) in 1980 and 1985, respectively. She was an assistant professor at the University of Bari (Italy) until she joined the faculty of George Mason University in 1986, where she is currently professor of mathematics. Her research interests include discrete harmonic analysis, integral geometry, potential theory, and classical complex function theory. Glenn R. Easley received the B.S. degree (with honors) and the M.A. degree in mathematics from the University of Maryland, College Park, in 1993 and 1996, respectively, and the Ph.D. degree in computational science and informatics from George Mason University in 2000. Since 2000, he has been working for System Planning Corporation in signal and image processing. His research interests include computational harmonic analysis, wavelet analysis, synthetic aperture radar, deconvolution and computer vision.This revised version was published online in June 2005 with correction to CoverDate