Institution
University of Udine
Education•Udine, Italy•
About: University of Udine is a education organization based out in Udine, Italy. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 6745 authors who have published 20530 publications receiving 669088 citations. The organization is also known as: Università degli Studi di Udine & Universita degli Studi di Udine.
Topics: Population, Large Hadron Collider, Transplantation, Lepton, Higgs boson
Papers published on a yearly basis
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TL;DR: This paper reports on the first attempts to combine crowdsourcing and TREC: the aim is to validate the use of crowdsourcing for relevance assessment, using the Amazon Mechanical Turk crowdsourcing platform to run experiments on TREC data, evaluate the outcomes, and discuss the results.
Abstract: Crowdsourcing has recently gained a lot of attention as a tool for conducting different kinds of relevance evaluations At a very high level, crowdsourcing describes outsourcing of tasks to a large group of people instead of assigning such tasks to an in-house employee This crowdsourcing approach makes possible to conduct information retrieval experiments extremely fast, with good results at a low cost This paper reports on the first attempts to combine crowdsourcing and TREC: our aim is to validate the use of crowdsourcing for relevance assessment To this aim, we use the Amazon Mechanical Turk crowdsourcing platform to run experiments on TREC data, evaluate the outcomes, and discuss the results We make emphasis on the experiment design, execution, and quality control to gather useful results, with particular attention to the issue of agreement among assessors Our position, supported by the experimental results, is that crowdsourcing is a cheap, quick, and reliable alternative for relevance assessment
159 citations
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TL;DR: Fluoxetine compared to other ADs had more activating and gastrointestinal adverse effects, which often require additional pharmacotherapy or other managements strategies, leading to discontinuation and non-compliance and increasing the costs.
Abstract: Background In the last ten years, SSRIs have increasingly replaced TCAs as comparators of newer antidepressants (ADs), because of their better tolerability profile. In particular, fluoxetine has become a reference drug for the treatment of depression, but the occurrence of individual side effects in depressed subjects treated with fluoxetine and each comparator AD have not been systematically investigated. Methods This meta-analysis investigated the frequency of side effects induced by fluoxetine or alternative ADs and compared the occurrence of individual side effects in depressed subjects. All randomised clinical trials (RCTs) comparing fluoxetine with any other AD drug in patients with major depression were located by searching the Cochrane Collaboration Depression, Anxiety and Neurosis Controlled Trials Register and the Cochrane Controlled Trials Register. Two reviewers independently extracted information. Results Significantly less percentage of patients treated with fluoxetine experienced any side effects in comparison with TCAs (50.9 % vs 60.3 %, 29 RCTs; RR = 0.84, p = 0.003), but not in comparison with other SSRIs (59.4 % vs 59.3 %, 15 RCTs; RR = 1.00, p = 0.902). In addition, fluoxetine was better tolerated in comparison with TCAs and related ADs (RR 0.61, 95 % CI 0.52, 0.71), but not in comparison with other SSRIs. Regard to individual side effects, activating (insomnia, agitation, tremor and anxiety) and gastrointestinal adverse events (nausea, vomiting, diarrhoea, weight loss and anorexia) were significantly more frequent in fluoxetine-treated patients, whereas cholinergic side effects were significantly less frequent. Conclusions Fluoxetine compared to other ADs had more activating and gastrointestinal adverse effects, which often require additional pharmacotherapy or other managements strategies, leading to discontinuation and non-compliance and increasing the costs. This information is relevant to base on evidence the prescription of ADs in everyday clinical practice.
159 citations
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TL;DR: An analysis of the results of an algorithm for optimal trajectory planning of robot manipulators is described, which allows to set constraints on the robot motion, expressed as upper bounds on the absolute values of velocity, acceleration and jerk.
158 citations
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TL;DR: The effects, as a whole, depict this compound as a drug candidate for diseases in which peroxidative damage is associated with the induction of inflammatory responses and specifically with activation of a respiratory burst of leucocytes.
158 citations
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University of Ljubljana1, University of Birmingham2, Czech Technical University in Prague3, Linköping University4, Austrian Institute of Technology5, Vienna University of Technology6, ETH Zurich7, Beijing Institute of Technology8, Carnegie Mellon University9, University of Isfahan10, Autonomous University of Madrid11, National Technical University12, Eskişehir Osmangazi University13, Dalian University of Technology14, Chinese Academy of Sciences15, Tamkang University16, University of Udine17, Southeast University18, Uppsala University19, Stony Brook University20, Sichuan University21, Indian Institutes of Technology22, Yazd University23, University of Science and Technology of China24, Microsoft25, Jiangnan University26, University of Alberta27, Samsung28, University of Surrey29, Korea University30, Renmin University of China31, Nanjing University of Information Science and Technology32, University of Oxford33, KAIST34, Sharif University of Technology35, Fuzhou University36, University of Electronic Science and Technology of China37
TL;DR: A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in theVDT challenges.
Abstract: The Visual Object Tracking challenge VOT2020 is the eighth annual tracker benchmarking activity organized by the VOT initiative. Results of 58 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The VOT2020 challenge was composed of five sub-challenges focusing on different tracking domains: (i) VOT-ST2020 challenge focused on short-term tracking in RGB, (ii) VOT-RT2020 challenge focused on “real-time” short-term tracking in RGB, (iii) VOT-LT2020 focused on long-term tracking namely coping with target disappearance and reappearance, (iv) VOT-RGBT2020 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2020 challenge focused on long-term tracking in RGB and depth imagery. Only the VOT-ST2020 datasets were refreshed. A significant novelty is introduction of a new VOT short-term tracking evaluation methodology, and introduction of segmentation ground truth in the VOT-ST2020 challenge – bounding boxes will no longer be used in the VOT-ST challenges. A new VOT Python toolkit that implements all these novelites was introduced. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website (http://votchallenge.net).
158 citations
Authors
Showing all 6857 results
Name | H-index | Papers | Citations |
---|---|---|---|
M.-Marsel Mesulam | 150 | 558 | 90772 |
Francesco Longo | 142 | 745 | 89859 |
Georges Aad | 135 | 1121 | 88811 |
Bobby Samir Acharya | 133 | 1121 | 100545 |
G. Della Ricca | 133 | 1598 | 92678 |
Marina Cobal | 132 | 1078 | 85437 |
Fernando Barreiro | 130 | 1082 | 83413 |
Saverio D'Auria | 129 | 1142 | 83684 |
Jean-Francois Grivaz | 128 | 1322 | 97758 |
Evgeny Starchenko | 128 | 864 | 75913 |
Muhammad Alhroob | 127 | 880 | 71982 |
Michele Pinamonti | 126 | 846 | 69328 |
Reisaburo Tanaka | 126 | 967 | 69849 |
Kerim Suruliz | 126 | 795 | 69456 |
Kate Shaw | 125 | 841 | 70087 |