186,210 research outputs found
Dataset of Last Interglacial climate from publication "Modeled storm surge changes in a warmer world: the Last Interglacial" by P. Scussolini et al.
No full textResults from the simulation of Last Interglacial (Eemian) climate with climate model CESM1.2. Variables are: sea-level pressure (PSL); meridional wind (V), and zonal wind (U). Time step is 6-hourly.
Detailed description of the methods are in the original publication:
Scussolini, P., Dullaart, J., Muis, S., Rovere, A., Bakker, P., Coumou, D., Renssen, H., Ward, P. J., and Aerts, J. C. J. H.: Modelled storm surge changes in a warmer world: the Last Interglacial, EGUsphere, 2022, 1-20, 10.5194/egusphere-2022-101, 2022
Building typological classification in Switzerland using deep learning methods for seismic assessment
Full text linkNatural disasters, such as earthquakes, have always represented a danger to human life. Seismic risk assessment consists of the evaluation of existing buildings and their expected response in case of an earthquake; the exposure model of buildings plays a key role in risk calculations. With this respect, in recent years, advanced techniques have been developed to speed up and automatize the processes of data acquisition to data interpretation, although it is worth mentioning that the visual survey is essential to train and validate Machine Learning (ML) methods. In the present study, the identification of building types is conducted by exploiting the traditional visual survey to implement a Deep Learning (DL) classification model. As a first step, city mapping schemes are obtained by classifying buildings according to the main features (i.e., construction period and height classes). Then, Random Forest (RF), a supervised learning algorithm, is applied to classify different building types by exploiting all their attributes. The RF model is trained and tested on the cities of Neuchatel and Yverdon-Les-Bains. The decent accuracy of the results encourages the application of the method to different cities, with proper adjustments in datasets, features and algorithms
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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
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
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
Dr. Edward P. Wimberly, ITC, July 2011
No full textThis video is a conversation with Dr. Edward P. Wimberly. Dr. Wimberly talks about his book, "No Shame in Wesley's Gospel: A Twenty-First Century Pastoral Gospel". Brad Ost, AUC Woodruff Library, is the interviewer
Author Rights and Scholarly Publishing
Full text linkOriginally posted at
http://blog.library.gsu.edu/2014/10/24/author-rights-and-scholarly-publishing/</p
Megafauna diversity and functional declines in Europe from the Last Interglacial to the present
Full text linkAim: Reconstructing megafauna diversity in the past before anthropogenic impacts is crucial for developing targeted restoration strategies. We estimated the diversity and functional decline of European megafauna in the present compared with the nearest in-time climate period analogue to the present but prior to the worldwide diffusion of Homo sapiens. Location: Europe. Time Period: Last Interglacial (LIG; ca. 127,000 years ago) to present. Major Taxa Studied: Wild, large (≥10 kg) terrestrial mammals. Methods: We assessed the distribution of 48 European megafauna species during the LIG using hindcasting modelling and fossil records. Then, we estimated the decline in megafauna community diversity and potential trait-based functional effects from the LIG to the present, accounting for climate differences between the two periods. Results: Species richness and community biomass dropped by 70.8% (±11.7%) and by 94.5% (±9.9%). Functional diversity dropped by 80.3% (±15.3%) for herbivores and by 64.9% (±29.1%) for carnivores, while trait-informed potential vegetation and meat consumptions dropped by 82.3% (±13.4%) and 60.5% (±26.0%). The loss in megafauna diversity and associated ecological processes were high everywhere, but particularly in western Europe for carnivores and in the East European Plain for herbivores. Potential megafauna richness in the two periods was similar if only climate-driven differences were considered. Main Conclusions: Severe, size-biased defaunation has degraded megafauna assemblages and megafauna-mediated ecological processes across Europe from the LIG to the present. These patterns cannot be explained by climate differences between the two periods, thus were likely driven by prehistoric Homo sapiens. The results suggest that the structure of wild ecosystems of the present strongly deviates from the evolutionary norm, with decreased functional heterogeneity and decreased fluxes of biogeochemical compounds across the trophic networks, highlighting the importance of ambitious policies of megafauna community restoration to support ecosystem functioning
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