Strategy-proof preference aggregation

An aggregation rule maps each profile of individual strict preference orderings over a set of alternatives into a social ordering over that set. We call such a rule strategyproof if misreporting one’s preference never produces a social ordering that is strictly between the original ordering and one’s own preference. After describing a few examples of manipulable rules, we study in some detail three classes of strategy-proof rules: (i)rules based on a monotonic alteration of the majority relation generated by the preference profile; (ii)rules improving upon a fixed status-quo; and (iii) rules generalizing the Condorcet-Kemeny aggregation method.

Voyage en pays normatif. Le droit : une variable dépendante

"Le sous-titre des Mélanges consacrés à Andrée Lajoie – Ledroit : une variable dépendante – n’est pas neutre : d’abord, parce qu’elle en est elle-même l’auteure ; ensuite, parce qu’elle a travaillé à traquer, dans la réalité phénoménale tout autant que discursive, toute prétention à la neutralité. Le concept de variable est intimement lié à la formulation d’une hypothèse dont on sait qu’elle se définit comme le pivot de l’élaboration d’un projet de recherche quand, une fois abreuvée d’un cadre théorique qui la surdétermine, elle bascule vers les efforts de démonstration et les stratégies de vérification appelés à l’infirmer définitivement ou à la confirmer toujours temporairement. Les variables, entre dimensions théoriques et indicateurs empiriques, obéissent à une structure interactionnelle dans une relation de causalité, de covariance, d’imputation, etc. Ces rapports soumettent l’observation à une dynamique présupposée entre des données inertes (variable indépendante) et des données mutantes (variable dépendante), souvent sous l’effet de facteurs de changements (variable intermédiaire). On parlera donc de variations impulsées par des combinaisons, des séquençages, des coordinations entre des concepts d’abord, puis entre des faits (incluant les faits discursifs) qui rendront compte plus adéquatement de la réalité et qui enrichiront les connaissances."

Recension systématique et critique des études portant sur l'utilisation de la variable motivationnelle dans les inerventions auprès d'adolescent(e)s atteint(e)s d'anorexie mentale

Essai doctoral présenté à la Faculté des arts et des sciences en vue de l'obtention du grade de Doctorat (D.Psy) en psychologie option psychologie clinique.

Étude in vivo de la relation entre la structure et la fonction de la boucle variable de l'ARN de transfert de la sélénocystéine d'E. coli

La sélénocystéine est le 21e acide aminé encodé génétiquement et on la retrouve à travers les trois domaines de la vie. Elle est synthétisée sur l'ARNtSec par un processus unique. L'ARNtSec se distingue également au niveau structural. La tige acceptrice possède 8 (procaryotes) et 9 (eucaryotes) paires de bases, contrairement aux ARNt canoniques qui ont invariablement 7 paires de bases dans la tige acceptrice. De plus, la tige D a 2 paires de bases additionnelles qui remplacent les interactions tertiaires universelles 8-14, 15-48 qui sont absentes chez l'ARNtSec. D'autre part, la longueur de la boucle variable de l'ARNtSec est plus longue que la majorité des ARNt de type II. Dans ce mémoire, on se concentre sur la région de la boucle variable de l'ARNtSec . La recherche consiste à distinguer les paires de bases de la boucle variable qui sont essentielles à la biosynthèse et l’insertion de la sélénocystéine. De plus, on regarde si la paire de base additionnelle de la tige acceptrice de l'ARNtSec (procaryote) est essentielle pour l'insertion de la sélénocystéine. Pour répondre à ces questions, on a utilisé l'approche expérimentale Évolution Instantanée qui consiste au criblage in vivo d'ARNtSec fonctionnels chez E. coli. Dans ce travail, on montre que l'insertion de la sélénocystéine ne nécessite pas une spécificité de la longueur ou de la séquence de l'ARNtSec. On montre aussi que ni la longueur de la tige acceptrice ou du domaine tige acceptrice/tige T n'est essentielle pour avoir un ARNtSec fonctionnel.

L’impact de la rémunération variable sur l’intention de rester via l’engagement organisationnel : étude longitudinale dans le secteur des TIC.

Notre mémoire a pour objectif d’étudier l’impact différencié de la rémunération variable individuelle et collective sur l’intention de rester. De plus, nous nous intéressons au rôle de l’engagement organisationnel dans la relation entre la rémunération variable et l’intention de rester. Pour ce faire, nous avons formulé quatre hypothèses basées sur la littérature et certaines théories. La première hypothèse avance que la rémunération variable individuelle fait accroître l’intention de rester des travailleurs. La deuxième stipule que la rémunération variable collective fait accroître l’intention de rester. La troisième indique que la rémunération variable individuelle fait accroître davantage l’intention de rester que la rémunération variable collective sur l’intention de rester. Enfin, la quatrième hypothèse suggère que l’engagement organisationnel agit à titre de variable médiatrice dans la relation entre la rémunération variable et l’intention de rester. Notre étude s’appuie sur des données longitudinales colligées dans le cadre d’une enquête portant sur « les liens entre la rémunération, la formation et le développement des compétences avec l’attraction et la rétention des employés clés ». L’enquête a été réalisée auprès de nouveaux travailleurs d’une entreprise internationale du secteur des technologies de l’information et des communications (TIC) à Montréal. Les données ont été colligées en trois temps entre le 1er avril 2009 et le 30 septembre 2010. Nos résultats soutiennent qu’effectivement la rémunération variable individuelle et collective font augmenter l’intention de rester des travailleurs. De plus, nous trouvons que la rémunération variable individuelle et la rémunération variable collective ont un impact équivalent sur l’intention de rester. Enfin, bien que l’engagement organisationnel soit un prédicteur important de l’intention de rester, celui-ci n’agit pas à titre de variable médiatrice dans la relation entre la rémunération variable et l’intention de rester. Finalement, notre étude permet d’élaborer certaines pistes pour améliorer l’intention de rester des travailleurs.

Investigation of nonlinear absorption and aggregation in aqueous solutions of rhodamine B using thermal lens technique

Thermal lensing effect was studied in aqueous solutions of rhodamine B using 532 nm, 9 ns pulses from a Nd:YAG laser. A low intensity He-Ne laser beam was used for probing the thermal lens. Results obtained show that it is appropriate to use this technique for studying nonlinear absorption processes like two photon absorption or excited state absorption and for analyzing dimerization equilibria.

Studies of nonlinear absorption and aggregation in aqueous solutions of rhodamine 6G using a transient thermal lens technique

Dual-beam transient thermal lens studies were carried out in aqueous solutions of rhodamine 6G using 532 nm pulses from a frequency-doubled Nd:YAG laser. The analysis of the observed data showed that the thermal lens method can effectively be utilized to study the nonlinear absorption and aggregation which are taking place in a dye medium.

Study on period search methods of variable stars: Application to ASAS and CRTS databases

Study on variable stars is an important topic of modern astrophysics. After the invention of powerful telescopes and high resolving powered CCD’s, the variable star data is accumulating in the order of peta-bytes. The huge amount of data need lot of automated methods as well as human experts. This thesis is devoted to the data analysis on variable star’s astronomical time series data and hence belong to the inter-disciplinary topic, Astrostatistics. For an observer on earth, stars that have a change in apparent brightness over time are called variable stars. The variation in brightness may be regular (periodic), quasi periodic (semi-periodic) or irregular manner (aperiodic) and are caused by various reasons. In some cases, the variation is due to some internal thermo-nuclear processes, which are generally known as intrinsic vari- ables and in some other cases, it is due to some external processes, like eclipse or rotation, which are known as extrinsic variables. Intrinsic variables can be further grouped into pulsating variables, eruptive variables and flare stars. Extrinsic variables are grouped into eclipsing binary stars and chromospheri- cal stars. Pulsating variables can again classified into Cepheid, RR Lyrae, RV Tauri, Delta Scuti, Mira etc. The eruptive or cataclysmic variables are novae, supernovae, etc., which rarely occurs and are not periodic phenomena. Most of the other variations are periodic in nature. Variable stars can be observed through many ways such as photometry, spectrophotometry and spectroscopy. The sequence of photometric observa- xiv tions on variable stars produces time series data, which contains time, magni- tude and error. The plot between variable star’s apparent magnitude and time are known as light curve. If the time series data is folded on a period, the plot between apparent magnitude and phase is known as phased light curve. The unique shape of phased light curve is a characteristic of each type of variable star. One way to identify the type of variable star and to classify them is by visually looking at the phased light curve by an expert. For last several years, automated algorithms are used to classify a group of variable stars, with the help of computers. Research on variable stars can be divided into different stages like observa- tion, data reduction, data analysis, modeling and classification. The modeling on variable stars helps to determine the short-term and long-term behaviour and to construct theoretical models (for eg:- Wilson-Devinney model for eclips- ing binaries) and to derive stellar properties like mass, radius, luminosity, tem- perature, internal and external structure, chemical composition and evolution. The classification requires the determination of the basic parameters like pe- riod, amplitude and phase and also some other derived parameters. Out of these, period is the most important parameter since the wrong periods can lead to sparse light curves and misleading information. Time series analysis is a method of applying mathematical and statistical tests to data, to quantify the variation, understand the nature of time-varying phenomena, to gain physical understanding of the system and to predict future behavior of the system. Astronomical time series usually suffer from unevenly spaced time instants, varying error conditions and possibility of big gaps. This is due to daily varying daylight and the weather conditions for ground based observations and observations from space may suffer from the impact of cosmic ray particles. Many large scale astronomical surveys such as MACHO, OGLE, EROS, xv ROTSE, PLANET, Hipparcos, MISAO, NSVS, ASAS, Pan-STARRS, Ke- pler,ESA, Gaia, LSST, CRTS provide variable star’s time series data, even though their primary intention is not variable star observation. Center for Astrostatistics, Pennsylvania State University is established to help the astro- nomical community with the aid of statistical tools for harvesting and analysing archival data. Most of these surveys releases the data to the public for further analysis. There exist many period search algorithms through astronomical time se- ries analysis, which can be classified into parametric (assume some underlying distribution for data) and non-parametric (do not assume any statistical model like Gaussian etc.,) methods. Many of the parametric methods are based on variations of discrete Fourier transforms like Generalised Lomb-Scargle peri- odogram (GLSP) by Zechmeister(2009), Significant Spectrum (SigSpec) by Reegen(2007) etc. Non-parametric methods include Phase Dispersion Minimi- sation (PDM) by Stellingwerf(1978) and Cubic spline method by Akerlof(1994) etc. Even though most of the methods can be brought under automation, any of the method stated above could not fully recover the true periods. The wrong detection of period can be due to several reasons such as power leakage to other frequencies which is due to finite total interval, finite sampling interval and finite amount of data. Another problem is aliasing, which is due to the influence of regular sampling. Also spurious periods appear due to long gaps and power flow to harmonic frequencies is an inherent problem of Fourier methods. Hence obtaining the exact period of variable star from it’s time series data is still a difficult problem, in case of huge databases, when subjected to automation. As Matthew Templeton, AAVSO, states “Variable star data analysis is not always straightforward; large-scale, automated analysis design is non-trivial”. Derekas et al. 2007, Deb et.al. 2010 states “The processing of xvi huge amount of data in these databases is quite challenging, even when looking at seemingly small issues such as period determination and classification”. It will be beneficial for the variable star astronomical community, if basic parameters, such as period, amplitude and phase are obtained more accurately, when huge time series databases are subjected to automation. In the present thesis work, the theories of four popular period search methods are studied, the strength and weakness of these methods are evaluated by applying it on two survey databases and finally a modified form of cubic spline method is intro- duced to confirm the exact period of variable star. For the classification of new variable stars discovered and entering them in the “General Catalogue of Vari- able Stars” or other databases like “Variable Star Index“, the characteristics of the variability has to be quantified in term of variable star parameters.

Content aggregation on knowledge bases using graph clustering

Recently, research projects such as PADLR and SWAP have developed tools like Edutella or Bibster, which are targeted at establishing peer-to-peer knowledge management (P2PKM) systems. In such a system, it is necessary to obtain provide brief semantic descriptions of peers, so that routing algorithms or matchmaking processes can make decisions about which communities peers should belong to, or to which peers a given query should be forwarded. This paper proposes the use of graph clustering techniques on knowledge bases for that purpose. Using this clustering, we can show that our strategy requires up to 58% fewer queries than the baselines to yield full recall in a bibliographic P2PKM scenario.

La atenci??n a la diversidad de nuestro alumnado como variable de disminuci??n del fracaso escolar : una propuesta pr??ctica

Se pretende paliar el absentismo y el abandono escolar prematuro y poner al alcance de todo el alumnado los elementos del curriculum de forma que, desde la integraci??n, todas y todos vivan su tiempo de escolarizaci??n como un tiempo ??til, sin desesperanza y con las perspectivas de obtener el Graduado de ESO.

Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders

Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, regarding (1) dissemination of information from informed to uninformed traders, and (2) aggregation of information spread over different traders.

Estimating Dependency Structure as a Hidden Variable

This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EMand the Minimum Spanning Tree algorithm to find the ML and MAP mixtureof trees for a variety of priors, including the Dirichlet and the MDL priors.

Estimating Dependency Structure as a Hidden Variable

This paper introduces a probability model, the mixture of trees that can account for sparse, dynamically changing dependence relationships. We present a family of efficient algorithms that use EM and the Minimum Spanning Tree algorithm to find the ML and MAP mixture of trees for a variety of priors, including the Dirichlet and the MDL priors. We also show that the single tree classifier acts like an implicit feature selector, thus making the classification performance insensitive to irrelevant attributes. Experimental results demonstrate the excellent performance of the new model both in density estimation and in classification.

Synthesis and Aggregation Behavior of Pluronic F87/Poly(acrylic acid) Block Copolymer with Doxorubicin

Poly(acrylic acid) (PAA) was grafted onto both termini of Pluronic F87 (PEO₆₇-PPO₃₉-PEO₆₇) via atom transfer radical polymerization to produce a novel muco-adhesive block copolymer PAA₈₀-b-F₈₇-b-PAA₈₀. It was observed that PAA₈₀-F₈₇-PAA₈₀ forms stable complexes with weakly basic anti-cancer drug, Doxorubicin. Thermodynamic changes due to the drug binding to the copolymer were assessed at different pH by isothermal titration calorimetry (ITC). The formation of the polymer/drug complexes was studied by turbidimetric titration and dynamic light scattering. Doxorubicin and PAA-b-F87-b-PAA block copolymer are found to interact strongly in aqueous solution via non-covalent interactions over a wide pH range. At pH>4.35, drug binding is due to electrostatic interactions. Hydrogen-bond also plays a role in the stabilization of the PAA₈₀-F₈₇-PAA₈₀/DOX complex. At pH 7.4 (α=0.8), the size and stability of polymer/drug complex depend strongly on the doxorubicin concentration. When CDOX <0.13mM, the PAA₈₀-F₈₇-PAA₈₀ copolymer forms stable inter-chain complexes with DOX (110 ~ 150 nm). When CDOX >0.13mM, as suggested by the light scattering result, the reorganization of the polymer/drug complex is believed to occur. With further addition of DOX (CDOX >0.34mM), sharp increase in the turbidity indicates the formation of large aggregates, followed by phase separation. The onset of a sharp enthalpy increase corresponds to the formation of a stoichiometric complex.