Tableau des distributions de pain, fourrage et bois a bruler qui seront faites pendant trente jours dans le courant des mois d'aoust et septembre 1754 aux troupes du camp de Gray

Ancien possesseur : Argenson, Antoine-René de Voyer (1722-1787 ; marquis de Paulmy d')

Extracting Ramachandran torsional angle distributions from 2D NMR data using Tikhonov regularization /

Solid state nuclear magnetic resonance (NMR) spectroscopy is a powerful technique for studying structural and dynamical properties of disordered and partially ordered materials, such as glasses, polymers, liquid crystals, and biological materials. In particular, twodimensional( 2D) NMR methods such as ^^C-^^C correlation spectroscopy under the magicangle- spinning (MAS) conditions have been used to measure structural constraints on the secondary structure of proteins and polypeptides. Amyloid fibrils implicated in a broad class of diseases such as Alzheimer's are known to contain a particular repeating structural motif, called a /5-sheet. However, the details of such structures are poorly understood, primarily because the structural constraints extracted from the 2D NMR data in the form of the so-called Ramachandran (backbone torsion) angle distributions, g{^,'4)), are strongly model-dependent. Inverse theory methods are used to extract Ramachandran angle distributions from a set of 2D MAS and constant-time double-quantum-filtered dipolar recoupling (CTDQFD) data. This is a vastly underdetermined problem, and the stability of the inverse mapping is problematic. Tikhonov regularization is a well-known method of improving the stability of the inverse; in this work it is extended to use a new regularization functional based on the Laplacian rather than on the norm of the function itself. In this way, one makes use of the inherently two-dimensional nature of the underlying Ramachandran maps. In addition, a modification of the existing numerical procedure is performed, as appropriate for an underdetermined inverse problem. Stability of the algorithm with respect to the signal-to-noise (S/N) ratio is examined using a simulated data set. The results show excellent convergence to the true angle distribution function g{(j),ii) for the S/N ratio above 100.

Unveiling Shi’i Religious Identities: Case Studies of Hijab in Culturally Homogeneous Canadian Schools

This qualitative case study explored 10 young female Shi’i Muslim Arabic-Canadian students’ experiences associated with wearing the Hijab (headscarf) within their home, community, and predominantly White Canadian public elementary school environments. The study integrated several bodies of scholarly theories in order to examine the data under a set of comprehensive lenses that more fully articulates and theorizes on the diversity of female Shi’i Muslim Canadian students’ experiences. These theories are: identity theories with a focus on religious identity and negative stereotypes associated with Muslims; feminism and the Hijab discourses; research pertaining to Muslims in school settings; and critical race theory. In order to readdress the dearth of information about Shi’is’ experiences in schools, this study provides an in-depth case study analysis in which the methodology strategies included 10 semi-structured in-depth interviews, 2 focus-group meetings, and the incorporation of the researcher’s fieldnotes. Data analysis revealed the following themes corresponding to participants’ experiences and values in their social worlds of home, community, and schools: (a) martyrdom and self-sacrifice as a means for social justice; (b) transformational meaning of the Hijab; (c) intersectionality between culture, religion, and gender; and (d) effects of visits “back home” on participants’ religious identities. Additional themes related to participants’ school experiences included: (a) “us versus them” mentality; (b) religious and complex secular dialogues; (c) absence of Muslim representations in monocultural schools; (d) discrimination; (e) remaining silent versus speaking out; and (f) participants’ strategies for preserving their identities. Recommendations are made to integrate Shi’i Muslim females’ identity within the context of Islam and the West, most notably in relation to: (a) the role of Muslim community in nondiverse settings as a space that advances and nurtures Shi’i Muslim identity; and (b) holistic and culturally responsive teaching that fosters respect of others’ religiosity and spirituality. This study makes new inroads into feminist theorizing by drawing conceptual links between these previously unknown connections such as the impact of the historical female exemplary role model and the ritual stories on the experiences of Muslim females wearing the Hijab.

Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions.

In this paper, we study several tests for the equality of two unknown distributions. Two are based on empirical distribution functions, three others on nonparametric probability density estimates, and the last ones on differences between sample moments. We suggest controlling the size of such tests (under nonparametric assumptions) by using permutational versions of the tests jointly with the method of Monte Carlo tests properly adjusted to deal with discrete distributions. We also propose a combined test procedure, whose level is again perfectly controlled through the Monte Carlo test technique and has better power properties than the individual tests that are combined. Finally, in a simulation experiment, we show that the technique suggested provides perfect control of test size and that the new tests proposed can yield sizeable power improvements.

Rank Regressions, Wage Distributions and the Gender Gap.

In this paper, we model the interactions between the distribution of male and female wages under the assumption that any change in the wage distribution of women must be offset by an opposite change in the wage distribution of men.

Exact Multivariate Tests of Asset Pricing Models with Stable Asymmetric Distributions

In this paper, we propose exact inference procedures for asset pricing models that can be formulated in the framework of a multivariate linear regression (CAPM), allowing for stable error distributions. The normality assumption on the distribution of stock returns is usually rejected in empirical studies, due to excess kurtosis and asymmetry. To model such data, we propose a comprehensive statistical approach which allows for alternative - possibly asymmetric - heavy tailed distributions without the use of large-sample approximations. The methods suggested are based on Monte Carlo test techniques. Goodness-of-fit tests are formally incorporated to ensure that the error distributions considered are empirically sustainable, from which exact confidence sets for the unknown tail area and asymmetry parameters of the stable error distribution are derived. Tests for the efficiency of the market portfolio (zero intercepts) which explicitly allow for the presence of (unknown) nuisance parameter in the stable error distribution are derived. The methods proposed are applied to monthly returns on 12 portfolios of the New York Stock Exchange over the period 1926-1995 (5 year subperiods). We find that stable possibly skewed distributions provide statistically significant improvement in goodness-of-fit and lead to fewer rejections of the efficiency hypothesis.

Distributions de salaire et participation au marché du travail.

Rapport de recherche

Rank Regressions, Wage Distributions and the Gender Gap.

In this paper, we model the interactions between the distribution of male and female wages under the assumption that any change in the wage distribution of women must be offset by an opposite change in the wage distribution of men.