Institution
University of Siena
Education•Siena, Italy•
About: University of Siena is a education organization based out in Siena, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 12179 authors who have published 33334 publications receiving 1008287 citations. The organization is also known as: Università degli studi di Siena & Universita degli studi di Siena.
Topics: Population, Cancer, Large Hadron Collider, Sperm, Oxidative stress
Papers published on a yearly basis
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Emory University1, University of California, Los Angeles2, University of Siena3, California Institute of Technology4, University of Zurich5, Central European University6, University of California, Davis7, Texas A&M University8, University of Oxford9, University of New Mexico10, University of Pennsylvania11, University of California, Santa Barbara12, Harvard University13, California State University, Fullerton14, University of Colorado Denver15
TL;DR: A cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions found the canonical model – based on self-interest – fails in all of the societies studied.
Abstract: Researchers from across the social sciences have found consistent deviations from the predictions of the canonical model of self-interest in hundreds of experiments from around the world. This research, however, cannot determine whether the uniformity re- sults from universal patterns of human behavior or from the limited cultural variation available among the university students used in virtually all prior experimental work. To address this, we undertook a cross-cultural study of behavior in ultimatum, public goods, and dictator games in a range of small-scale societies exhibiting a wide variety of economic and cultural conditions. We found, first, that the canonical model - based on self-interest - fails in all of the societies studied. Second, our data reveal substantially more behavioral vari- ability across social groups than has been found in previous research. Third, group-level differences in economic organization and the structure of social interactions explain a substantial portion of the behavioral variation across societies: the higher the degree of market integration and the higher the payoffs to cooperation in everyday life, the greater the level of prosociality expressed in experimental games. Fourth, the available individual-level economic and demographic variables do not consistently explain game behavior, either within or across groups. Fifth, in many cases experimental play appears to reflect the common interactional patterns of everyday life.
1,589 citations
Utrecht University1, University of Alabama at Birmingham2, Pennsylvania State University3, Columbia University4, University of Palermo5, University of California, San Diego6, Hacettepe University7, Erasmus University Medical Center8, Cardiff University9, University of Siena10, University of Colombo11, University of Adelaide12, Northwestern University13, Imperial College London14, University of Oklahoma15, University of California, Los Angeles16, University of Pennsylvania17
TL;DR: Relevant topics addressed-all dealt with in a systematic fashion-include adolescence, hirsutism and acne, contraception, menstrual cycle abnormalities, quality of life, ethnicity, pregnancy complications, long-term metabolic and cardiovascular health, and finally cancer risk.
1,585 citations
TL;DR: Some of the more commonly used biomarkers of oxidative/nitrosative damage are discussed and selected examples of human studies are included.
Abstract: Oxidative/nitrosative stress, a pervasive condition of increased amounts of reactive oxygen/nitrogen species, is now recognized to be a prominent feature of many acute and chronic diseases and even of the normal aging process. However, definitive evidence for this association has often been lacking because of recognized shortcomings with biomarkers and/or methods available to assess oxidative stress status in humans. Emphasis is now being placed on biomarkers of oxidative stress, which are objectively measured and evaluated as indicators of normal biological processes, pathogenic processes, or pharmacologic responses to therapeutic intervention. To be a predictor of disease, a biomarker must be validated. Validation criteria include intrinsic qualities such as specificity, sensitivity, degree of inter- and intraindividual variability, and knowledge of the confounding and modifying factors. In addition, characteristics of the sampling and analytical procedures are of relevance, including constraints and noninvasiveness of sampling, stability of potential biomarkers, and the simplicity, sensitivity, specificity, and speed of the analytical method. Here we discuss some of the more commonly used biomarkers of oxidative/nitrosative damage and include selected examples of human studies.
1,575 citations
27 Dec 2005
TL;DR: A new neural model, called graph neural network (GNN), capable of directly processing graphs, which extends recursive neural networks and can be applied on most of the practically useful kinds of graphs, including directed, undirected, labelled and cyclic graphs.
Abstract: In several applications the information is naturally represented by graphs. Traditional approaches cope with graphical data structures using a preprocessing phase which transforms the graphs into a set of flat vectors. However, in this way, important topological information may be lost and the achieved results may heavily depend on the preprocessing stage. This paper presents a new neural model, called graph neural network (GNN), capable of directly processing graphs. GNNs extends recursive neural networks and can be applied on most of the practically useful kinds of graphs, including directed, undirected, labelled and cyclic graphs. A learning algorithm for GNNs is proposed and some experiments are discussed which assess the properties of the model.
1,569 citations
Paris 12 Val de Marne University1, French Institute of Health and Medical Research2, University of Göttingen3, Ghent University4, University Hospital of Lausanne5, University of Lisbon6, university of lille7, Università Campus Bio-Medico8, University of Belgrade9, University of Hamburg10, Turku University Hospital11, Aristotle University of Thessaloniki12, University of Regensburg13, University of Bern14, Ludwig Maximilian University of Munich15, University of Siena16, The Catholic University of America17, University College London18, University of Ulm19, Copenhagen University Hospital20, University of Oxford21, University of Barcelona22, University of Tübingen23
TL;DR: There is a sufficient body of evidence to accept with level A (definite efficacy) the analgesic effect of high-frequency rTMS of the primary motor cortex (M1) contralateral to the pain and the antidepressant effect of HF-rT MS of the left dorsolateral prefrontal cortex (DLPFC).
1,554 citations
Authors
Showing all 12352 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Johan Auwerx | 158 | 653 | 95779 |
| I. V. Gorelov | 139 | 1916 | 103133 |
| Roberto Tenchini | 133 | 1390 | 94541 |
| Francesco Fabozzi | 133 | 1561 | 93364 |
| M. Davier | 132 | 1449 | 107642 |
| Roberto Dell'Orso | 132 | 1412 | 92792 |
| Rino Rappuoli | 132 | 816 | 64660 |
| Teimuraz Lomtadze | 129 | 893 | 80314 |
| Manas Maity | 129 | 1309 | 87465 |
| Dezso Horvath | 128 | 1283 | 88111 |
| Paolo Azzurri | 126 | 1058 | 81651 |
| Vincenzo Di Marzo | 126 | 659 | 60240 |
| Igor Katkov | 125 | 972 | 71845 |
| Ying Lu | 123 | 708 | 62645 |
| Thomas Schwarz | 123 | 701 | 54560 |