École Normale Supérieure

About: École Normale Supérieure is a other organization based out in Paris, Île-de-France, France. It is known for research contribution in the topics: Population & Catalysis. The organization has 68439 authors who have published 99414 publications receiving 3092008 citations.

MicroRaman Spectral Study of the PO4 and CO3 Vibrational Modes in Synthetic and Biological Apatites

Abstract: The carbonate and phosphate vibrational modes of different synthetic and biological carbonated apatites were investigated by Raman microspectroscopy, and compared with those of hydroxyapatite. The ν1 phosphate band at 960 cm−1 shifts slightly due to carbonate substitution in both A and B sites. The spectrum of type A carbonated apatite exhibits two ν1 PO43− bands at 947 and 957 cm−1. No significant change was observed in the ν2 and ν4 phosphate mode regions in any carbonated samples. The ν3 PO43− region seems to be more affected by carbonation: two main bands were observed, as in the hydroxyapatite spectrum, but at lower wave numbers. The phosphate spectra of all biominerals apatite were consistent with type AB carbonated apatite. In the enamel spectrum, bands were observed at 3513 and at 3573 cm−1 presumably due to two different hydroxyl environments. Two different bands due to the carbonate ν1 mode were identified depending on the carbonate substitution site A or B, at 1107 and 1070 cm−1, respectively. Our results, compared with the infrared data already reported, suggest that even low levels of carbonate substitution induce modifications of the hydroxyapatite spectrum. Increasing substitution ratios, however, do not bring about any further alteration. The spectra of dentine and bone showed a strong similarity at a micrometric level. This study demonstrates the existence of acidic phosphate, observable by Raman microspectrometry, in mature biominerals. The HPO42− and CO32− contents increase from enamel to dentine and bone, however, these two phenomena do not seem to be correlated.

Immunology for physicists

Abstract: The immune system is a complex system of cells and molecules that can provide us with a basic defense against pathogenic organisms. Like the nervous system, the immune system performs pattern recognition tasks, learns, and retains a memory of the antigens that it has fought. The immune system contains more than 10{sup 7} different clones of cells that communicate via cell-cell contact and the secretion of molecules. Performing complex tasks such as learning and memory involves cooperation among large numbers of components of the immune system and hence there is interest in using methods and concepts from statistical physics. Furthermore, the immune response develops in time and the description of its time evolution is an interesting problem in dynamical systems. In this paper, the authors provide a brief introduction to the biology of the immune system and discuss a number of immunological problems in which the use of physical concepts and mathematical methods has increased our understanding. {copyright} {ital 1997} {ital The American Physical Society}

Multidimensional orientation estimation with applications to texture analysis and optical flow

Abstract: The problem of detection of orientation in finite dimensional Euclidean spaces is solved in the least squares sense. The theory is developed for the case when such orientation computations are necessary at all local neighborhoods of the n-dimensional Euclidean space. Detection of orientation is shown to correspond to fitting an axis or a plane to the Fourier transform of an n-dimensional structure. The solution of this problem is related to the solution of a well-known matrix eigenvalue problem. The computations can be performed in the spatial domain without actually doing a Fourier transformation. Along with the orientation estimate, a certainty measure, based on the error of the fit, is proposed. Two applications in image analysis are considered: texture segmentation and optical flow. The theory is verified by experiments which confirm accurate orientation estimates and reliable certainty measures in the presence of noise. The comparative results indicate that the theory produces algorithms computing robust texture features as well as optical flow. >

Monitoring training status with HR measures: do all roads lead to Rome?

Abstract: Monitoring an athlete's physiological status in response to various types and volumes of (aerobic-oriented) training can provide useful information for optimizing training programs. Measures of resting, exercise and recovery heart rate (HR) are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load 1) daily during specific training blocks and 2) throughout the competitive season. These measures are still not widely implemented to monitor athletes’ responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in HR, reflecting parasympathetic activity) and submaximal exercise (30- to 60-s average) HR are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker’s sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of HR cannot inform on all aspects of wellness, fatigue and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status

Gradient Response Maps for Real-Time Detection of Textureless Objects

Abstract: We present a method for real-time 3D object instance detection that does not require a time-consuming training stage, and can handle untextured objects. At its core, our approach is a novel image representation for template matching designed to be robust to small image transformations. This robustness is based on spread image gradient orientations and allows us to test only a small subset of all possible pixel locations when parsing the image, and to represent a 3D object with a limited set of templates. In addition, we demonstrate that if a dense depth sensor is available we can extend our approach for an even better performance also taking 3D surface normal orientations into account. We show how to take advantage of the architecture of modern computers to build an efficient but very discriminant representation of the input images that can be used to consider thousands of templates in real time. We demonstrate in many experiments on real data that our method is much faster and more robust with respect to background clutter than current state-of-the-art methods.