Agri-food qualification and certification process as an interface between exchange marketing and reciprocity

Ce texte mobilise la théorie de la réciprocité en anthropologie économique pour analyser les processus de qualification des produits de l'agriculture familiale au Brésil. Tout processus de qualification qui garantit l'origine, la spécificité, la qualité d'un produit peut réduire les effets de concurrence et de spéculation spécifiques à l'échange capitaliste. Je fais l'hypothèse que les processus de qualification peuvent contribuer à établir une relation de réciprocité symétrique entre producteur et consommateur. Ils peuvent également concourir à engendrer une structure de partage (de la qualité) au sein d'un groupe de producteurs. Mais, les mécanismes de qualification et certification peuvent également introduire l'exclusion, car en dehors du groupe et des produits certifiés ce sont les lois de l'échange qui régulent le marché. C'est pourquoi on a besoin d'une forme d'interface ou d'articulation entre production et marché. L'interface offerte par les mécanismes de certification de la qualification permet de réintroduire la dimension de la réciprocité économique dans le système du marché d'échange capitaliste. Ce texte repose sur la comparaison de trois systèmes de certification de produits agro-écologiques au Brésil : la certification externe de groupes, la certification participative et la cocertification. (Résumé d'auteur

The Effects of Base Sheet Moisture Content on Size Penetration Characteristics

This thesis was designed to determine the effects of moisture on the penetration of size solution into a paper sample. The experiment involved use of laboratory equipment and procedures to accomplish the objectives of this experiment. Handsheets were conditioned, sized, cut, stained, and viewed under a laboratory microscope to obtain the desired results. The results from this procedure determined that the area of size deposition was dependant upon the moisture content of the paper sheet. As the moisture content of the samples increased, the size was retained more on the sample\u27s surface as opposed to penetration into the paper web. If the results obtained in this study can be reproduced on the machine scale, extensive capital benefits will be realized by the particular mill. The benefits will be in the form of increased production as well as a reduction in steam consumption. However, benefits obtained from this increase in moisture should be weighed against effects on strength as well as other problems associated with high moisture content utilization, such as moisture profile

Don\u27t get left behind: Moving library instruction online

With the growing number of online courses and programs across the higher education spectrum, the need to train faculty to effectively design and deliver online courses has become essential to many institutions. However, many professional development options do not include information or support in order to transition the same library services and resources faculty might use in their face-to-face classes to this new environment. The following case study describes professional development for faculty preparing to teach online at one small, private, doctoral-granting institution; how library resources and services were incorporated into the professional development experience; and the overall impressions from faculty who have participated

Learning the dependence structure of rare events: a non-asymptotic study

Assessing the probability of occurrence of extreme events is a crucial issue in various fields like finance, insurance, telecommunication or environmental sciences. In a multivariate framework, the tail dependence is characterized by the so-called stable tail dependence function (STDF). Learning this structure is the keystone of multivariate extremes. Although extensive studies have proved consistency and asymptotic normality for the empirical version of the STDF, non-asymptotic bounds are still missing. The main purpose of this paper is to fill this gap. Taking advantage of adapted VC-type concentration inequalities, upper bounds are derived with expected rate of convergence in O(k^-1/2). The concentration tools involved in this analysis rely on a more general study of maximal deviations in low probability regions, and thus directly apply to the classification of extreme data

Identifying groups of variables with the potential of being large simultaneously

Identifying groups of variables that may be large simultaneously amounts to finding out which joint tail dependence coefficients of a multivariate distribution are positive. The asymptotic distribution of a vector of nonparametric, rank-based estimators of these coefficients justifies a stopping criterion in an algorithm that searches the collection of all possible groups of variables in a systematic way, from smaller groups to larger ones. The issue that the tolerance level in the stopping criterion should depend on the size of the groups is circumvented by the use of a conditional tail dependence coefficient. Alternatively, such stopping criteria can be based on limit distributions of rank-based estimators of the coefficient of tail dependence, quantifying the speed of decay of joint survival functions. Numerical experiments indicate that the algorithm's effectiveness for detecting tail-dependent groups of variables is highest when paired with a criterion based on a Hill-type estimator of the coefficient of tail dependence.Comment: 23 pages, 2 table

On Anomaly Ranking and Excess-Mass Curves

Learning how to rank multivariate unlabeled observations depending on their degree of abnormality/novelty is a crucial problem in a wide range of applications. In practice, it generally consists in building a real valued "scoring" function on the feature space so as to quantify to which extent observations should be considered as abnormal. In the 1-d situation, measurements are generally considered as "abnormal" when they are remote from central measures such as the mean or the median. Anomaly detection then relies on tail analysis of the variable of interest. Extensions to the multivariate setting are far from straightforward and it is precisely the main purpose of this paper to introduce a novel and convenient (functional) criterion for measuring the performance of a scoring function regarding the anomaly ranking task, referred to as the Excess-Mass curve (EM curve). In addition, an adaptive algorithm for building a scoring function based on unlabeled data X1 , . . . , Xn with a nearly optimal EM is proposed and is analyzed from a statistical perspective