1,721,104 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Structure-activity relationships for metabolism and toxicity
No full textPrédire à l’avance quels composés seront toxiques chez l’homme ou non représente un réel challenge dans le monde pharmaceutique. En effet, les mécanismes à l’origine de la toxicité ne sont pas toujours bien connus, et à cela s’ajoute le fait qu’un composé peut devenir néfaste seulement après qu’il ait été métabolisé. Nous proposons ici une approche originale utilisant les graphes condensés de réactions afin de modéliser les réactions métaboliques et prédire le devenir des xénobiotiques dans l’organisme humain. Différentes formes de toxicité sont aussi prédites : la mutagénicité et l’hépatotoxicité. Pour cette seconde toxicité, l’approche utilisée est la première à notre connaissance à prédire avec succès les molécules toxiques décrites par des données autres que résultant d’observations in vivo.Predict in advance which compounds will be toxic in humans or not is a real challenge in the pharmaceutical world. Indeed, the mechanisms responsible for toxicity are not always well known, and in some case a compound become toxic only after it has been metabolized. We propose here a novel approach using condensed graphs of reactions to model and predict the metabolic fate of xenobiotics in the human body. Various forms of toxicity are also predicted : mutagenicity and hepatotoxicity. For this second toxicity, the approach proposed is the first to our knowledge to successfully predict the toxic molecules described by data other than resulting from observations in vivo
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Structure-property modeling with advanced machine learning techniques
No full textCette thèse est consacrée au développement de techniques avancées d'apprentissage automa-tique pour la modélisation des propriétés des molécules et des réactions. Le couplage de la méthode d'apprentissage automatique multi-instances (MIL) avec les descripteurs 3D phar-macophoriques a permis de construire des modèles prédictifs prenant en compte l'ensemble des conformations moléculaires. Cette approche 3D ne nécessite pas de sélection et d'alignement de conformères et a été validée dans les études de (i) la bioactivité des compo-sés et (ii) l'énantiosélectivité des catalyseurs organiques chiraux. Dans de nombreux cas, les modèles MIL multi-conformationnelles 3D ont surpassé les approches classiques impliquant des descripteurs 2D populaires. Dans la deuxième partie, un concept d'apprentissage automa-tique conjugué a été introduit et appliqué à la modélisation des caractéristiques thermody-namiques et cinétiques des réactions chimiques. L'apprentissage automatique conjugué intègre des équations fondamentales avec des algorithmes d'apprentissage automatique, ce qui le distingue de l'apprentissage multitâche traditionnel ne capturant que la relation statis-tique entre les tâches.This Ph.D. thesis is devoted to the development of advanced machine learning techniques for the modeling of properties of molecules and reactions. Coupling the Multi-Instance machine Learning (MIL) method with the pharmacophoric 3D descriptors enabled the construction of predictive models accounting for an ensemble of molecular conformations. This 3D approach does not require the selection and alignment of conformers and was validated in the case studies of (i) the bioactivity of compounds and (ii) the enantioselectivity of chiral organic catalysts. In many cases, 3D multi-conformation MIL models overperformed classical ap-proaches involving popular 2D descriptors. In the second part, a concept of conjugated ma-chine learning was introduced and applied to the modeling of thermodynamic and kinetic characteristics of reactions. Conjugated machine learning integrates fundamental equations with machine learning algorithms, which distinguishes it from traditional multi-task learning capturing only the statistical relationship between the tasks
QSPR modeling of non-additive binary mixtures : application to the azeotropic behaviour
No full textGénéralement les modèles QSPR ne sont utilisés que pour prédire des propriétés des corps purs. Dans cette thèse nous avons développé une approche QSPR permettant de prédire des propriétés non additives de mélanges binaires, plus précisément leur caractère azéotropique/zéotropique. Pour parvenir à ce résultat, plusieurs types de modèles quantitatifs et qualitatifs ont été développés. L’approche est originale pour deux raisons. Premièrement, peu de travaux de recherche ont été publiés sur des mélanges dont les propriétés sont non-additives. Deuxièmement, plusieurs nouveaux aspects méthodologiques ont été introduits dans ce travail. Tout d'abord des descripteurs "spéciaux", capables de décrire des mélanges ont été proposés. De plus, un protocole robuste d'obtention et de validation des modèles a été utilisé, et un domaine d'applicabilité des modèles fiable a été proposé. La méthodologie développée pendant cette thèse démontre la fiabilité d'un nouveau concept – les modèles QSPR pour les mélanges. Elle est comparable à d'autres méthodes classiques, quoique n'utilisant qu'un faible nombre de données en comparaison.Generally, QSPR models are limited to individual compounds. In this thesis we have developed a QSPR approach to predict non-additive properties of binary mixtures, more explicitly their azeotropic behavior. To achieve this, several types of quantitative and qualitative models have been developed. This approach is original for two reasons. First, little research has been published on mixtures whose properties are no additive. Second, several new methodological aspects have been introduced in this work. First of all "special" descriptors able to describe mixtures have been proposed. In addition, a robust protocol for obtaining and validating models was used, and a reliable models applicability domain was proposed. The methodology developed during this thesis demonstrates the consistency of a new concept - the QSPR models for mixtures. It is comparable to other conventional methods, though using only limited data
QSPR modelling of technologically interesting solvents : the ionic liquids and the electrolytes for Li-ion batteries
No full textCette thèse a pour but de modéliser les liquides ioniques et les électrolytes pour batteries Li-ion. Nous avons développé des modèles SVR afin de prédire 9 propriétés d’intérêt pour ces solvants. Les modèles construits pour les liquides ioniques ont permis la détection de divers problèmes, et sont accessibles sur le site web du laboratoire : infochim.u-strasbg.fr/webserv/VSEngine.html. Les modèles construits pour les électrolytes ont permis la modélisation de candidats testés expérimentalement par nos collaborateurs. Le nombre de données étant limité pour ces solvants, nous avons également testé l’approche transductive par le biais de la TRR (Transductive Ridge Regression). Nous avons mis en place un protocole d’optimisation des paramètres de la méthode et appliqué la TRR aux solvants étudiés. Les résultats obtenus par la TRR sont légèrement meilleurs que ceux de la Régression Ridge, mais restent modestes si on veut éviter une détérioration accidentelle du modèle.This thesis is dedicated to the modelling of ionic liquids and electrolytes of Li-ion batteries. We developed several SVR models in order to predict 9 interesting properties of these solvents. The models built for the ionic liquids allowed us to detect several problems, and are freely available on the laboratory’s website: infochim.u-strasbg.fr/webserv/VSEngine.html. The models built for the electrolytes were used to model some candidates tested experimentally by our colleagues. As the amount of data is quite small for these solvents, we also tested the transductive approach with the help of the TRR (Transductive Ridge Regression). We have developed an optimization procedure for the method’s parameters, and applied the TRR to the studied solvents. The results obtained with the TRR are slightly better than of the Ridge Regression but stay modest if we want to avoid any accidental damage of the model
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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