University of Iceland

About: University of Iceland is a education organization based out in Reykjavik, Suðurnes, Iceland. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 5423 authors who have published 16199 publications receiving 694762 citations. The organization is also known as: Háskóli Íslands.

Changes in groundwater chemistry before two consecutive earthquakes in Iceland

Abstract: Precursor events to earthquakes are rarely reproduced. Measurement of groundwater chemistry in Iceland between 2008 and 2013 reveals distinct changes prior to two consecutive >M5 earthquakes.

Hyperspectral Image Classification via Multiple-Feature-Based Adaptive Sparse Representation

Abstract: A multiple-feature-based adaptive sparse representation (MFASR) method is proposed for the classification of hyperspectral images (HSIs). The proposed method mainly includes the following steps. First, four different features are separately extracted from the original HSI and they reflect different kinds of spectral and spatial information. Second, for each pixel, a shape adaptive (SA) spatial region is extracted. Third, an adaptive sparse representation algorithm is introduced to obtain the sparse coefficients for the multiple-feature matrix set of pixels in each SA region. Finally, these obtained coefficients are jointly used to determine the class label of each test pixel. Experimental results demonstrated that the proposed MFASR method can outperform several well-known classifiers in terms of both qualitative and quantitative results.

Eight centuries of periodic volcanism at the center of the Iceland hotspot revealed by glacier tephrostratigraphy

Abstract: A record of volcanic activity within the Vatnajokull ice cap has been obtained by combining data from three sources: tephrostratigraphic studies of two outlet glaciers, a 415-m-long ice core from northwestern Vatnajokull, and written records. The record extends back to a.d. 1200 and shows that the volcanic activity has a 130–140 yr period. Intervals of frequent eruptions with recurrence times of three to seven years alternate with intervals of similar duration having much lower eruption frequency. In comparison with other parts of the plate boundary in Iceland, eruption frequency is greater, episodes of unrest are longer, and intervals of low activity are shorter. The high eruption frequency may be the result of a more sustained supply of magma, owing to the area's location above the center of the Iceland mantle plume. When combined with historical data on eruptions and earthquakes, our data indicate that rifting-related activity in Iceland as a whole is periodic and broadly in phase with the volcanic activity within Vatnajokull.

Breast and ovarian cancer risks to carriers of the BRCA1 5382insC and 185delAG and BRCA2 6174delT mutations: a combined analysis of 22 population based studies

Abstract: A recent report estimated the breast cancer risks in carriers of the three Ashkenazi founder mutations to be higher than previously published estimates derived from population based studies. In an attempt to confirm this, the breast and ovarian cancer risks associated with the three Ashkenazi founder mutations were estimated using families included in a previous meta-analysis of populatrion based studies. The estimated breast cancer risks for each of the founder BRCA1 and BRCA2 mutations were similar to the corresponding estimates based on all BRCA1 or BRCA2 mutations in the meta-analysis. These estimates appear to be consistent with the observed prevalence of the mutations in the Ashkenazi Jewish population.

A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods

Abstract: Pansharpening refers to the fusion of a multispectral (MS) image and panchromatic (PAN) data aimed at generating an outcome with the same spatial resolution of the PAN data and the spectral resolution of the MS image. In the last 30 years, several approaches to deal with this issue have been proposed. However, the reproducibility of these methods is often limited, making the comparison with the state of the art hard to achieve. Thus, to fill this gap, we propose a new benchmark consisting of recent advances in MS pansharpening. In particular, optimized classical approaches [multiresolution analysis (MRA) and component substitution (CS)] are compared with methods belonging to the third generation of pansharpening, represented by variational optimization-based (VO) and machine learning (ML) techniques. The benchmark is tested on different scenarios (from urban to rural areas) acquired by different commercial sensors [i.e., IKONOS (IK), GeoEye-1 (GE-1), and WorldView-3 (WV-3)]. Both quantitative and qualitative assessments and the computational burden are analyzed in this article, and all of the implementations have been collected in a MATLAB toolbox that is made available to the community.