Localizing the Common Action Among a Few Videos

This paper strives to localize the temporal extent of an action in a long untrimmed video. Where existing work leverages many examples with their start, their ending, and/or the class of the action during training time, we propose few-shot common action localization. The start and end of an action in a long untrimmed video is determined based on just a hand-full of trimmed video examples containing the same action, without knowing their common class label. To address this task, we introduce a new 3D convolutional network architecture able to align representations from the support videos with the relevant query video segments. The network contains: (\textit{i}) a mutual enhancement module to simultaneously complement the representation of the few trimmed support videos and the untrimmed query video; (\textit{ii}) a progressive alignment module that iteratively fuses the support videos into the query branch; and (\textit{iii}) a pairwise matching module to weigh the importance of different support videos. Evaluation of few-shot common action localization in untrimmed videos containing a single or multiple action instances demonstrates the effectiveness and general applicability of our proposal.Comment: ECCV 202

Satellite-based trends of solar radiation and cloud parameters in Europe

Solar radiation is the main driver of the Earth\u2019s climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990\u2019s is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out

COVID-19 therapy target discovery with context-aware literature mining

The abundance of literature related to the widespread COVID-19 pandemic is beyond manual inspection of a single expert. Development of systems, capable of automatically processing tens of thousands of scientific publications with the aim to enrich existing empirical evidence with literature-based associations is challenging and relevant. We propose a system for contextualization of empirical expression data by approximating relations between entities, for which representations were learned from one of the largest COVID-19-related literature corpora. In order to exploit a larger scientific context by transfer learning, we propose a novel embedding generation technique that leverages SciBERT language model pretrained on a large multi-domain corpus of scientific publications and fine-tuned for domain adaptation on the CORD-19 dataset. The conducted manual evaluation by the medical expert and the quantitative evaluation based on therapy targets identified in the related work suggest that the proposed method can be successfully employed for COVID-19 therapy target discovery and that it outperforms the baseline FastText method by a large margin.Comment: Accepted to the 23rd International Conference on Discovery Science (DS 2020

Detecting Machine-obfuscated Plagiarism

Related dataset is at https://doi.org/10.7302/bewj-qx93 and also listed in the dc.relation field of the full item record.Research on academic integrity has identified online paraphrasing tools as a severe threat to the effectiveness of plagiarism detection systems. To enable the automated identification of machine-paraphrased text, we make three contributions. First, we evaluate the effectiveness of six prominent word embedding models in combination with five classifiers for distinguishing human-written from machine-paraphrased text. The best performing classification approach achieves an accuracy of 99.0% for documents and 83.4% for paragraphs. Second, we show that the best approach outperforms human experts and established plagiarism detection systems for these classification tasks. Third, we provide a Web application that uses the best performing classification approach to indicate whether a text underwent machine-paraphrasing. The data and code of our study are openly available.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/152346/1/Foltynek2020_Paraphrase_Detection.pdfDescription of Foltynek2020_Paraphrase_Detection.pdf : Foltynek2020_Paraphrase_Detectio

Effects of climate change on exposure to coastal flooding in Latin America and the Caribbean

This study considers and compares several of the most important factors contributing to coastal flooding in Latin American and the Caribbean (LAC) while accounting for the variations of these factors with location and time. The study assesses the populations, the land areas and the built capital exposed at present and at the middle and end of the 21st century for a set of scenarios that include both climatic and non-climatic drivers. Climatic drivers include global mean sea level, natural modes of climate variability such as El Niño, natural subsidence, and extreme sea levels resulting from the combination of projected local sea-level rise, storm surges and wave setup. Population is the only human-related driver accounted for in the future. Without adaptation, more than 4 million inhabitants will be exposed to flooding from relative sea-level rise by the end of the century, assuming the 8.5 W m−2 trajectory of the Representative Concentration Pathways (RCPs), or RCP8.5. However, the contributions from El Niño events substantially raise the threat in several Pacific-coast countries of the region and sooner than previously anticipated. At the tropical Pacific coastlines, the exposure by the mid-century for an event similar to El Niño 1998 would be comparable to that of the RCP4.5 relative sea-level rise by the end of the century. Furthermore, more than 7.5 million inhabitants, 42,600 km2 and built capital valued at 334 billion USD are currently situated at elevations below the 100-year extreme sea level. With sea levels rising and the population increasing, it is estimated that more than 9 million inhabitants will be exposed by the end of the century for either of the RCPs considered. The spatial distribution of exposure and the comparison of scenarios and timeframes can serve as a guide in future adaptation and risk reduction policies in the region

Reference material for radionuclides in sediment IAEA-384 (Fangataufa Lagoon sediment)

Author Posting. © Springer, 2007. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Journal of Radioanalytical and Nuclear Chemistry 273 (2007): 383-393, doi:10.1007/s10967-007-6898-4.A reference material designed for the determination of anthropogenic and natural radionuclides in sediment, IAEA-384 (Fangataufa Lagoon sediment), is described and the results of certification are presented. The material has been certified for 8 radionuclides (40K, 60Co, 155Eu, 230Th, 238U, 238Pu, 239+240Pu and 241Am). Information values are given for 12 radionuclides (90Sr, 137Cs, 210Pb (210Po), 226Ra, 228Ra, 232Th, 234U, 235U, 239Pu, 240Pu and 241Pu). Less reported radionuclides include 228Th, 236U, 239Np and 242Pu. The reference material may be used for quality management of radioanalytical laboratories engaged in the analysis of radionuclides in the environment, as well as for the development and validation of analytical methods and for training purposes. The material is available from IAEA in 100 g units