University of Extremadura

About: University of Extremadura is a education organization based out in Badajoz, Spain. It is known for research contribution in the topics: Population & Hyperspectral imaging. The organization has 7856 authors who have published 18299 publications receiving 396126 citations. The organization is also known as: Universidad de Extremadura.

Fusion of Hyperspectral and LiDAR Remote Sensing Data Using Multiple Feature Learning

Abstract: Hyperspectral image classification has been an active topic of research. In recent years, it has been found that light detection and ranging (LiDAR) data provide a source of complementary information that can greatly assist in the classification of hyperspectral data, in particular when it is difficult to separate complex classes. This is because, in addition to the spatial and the spectral information provided by hyperspectral data, LiDAR can provide very valuable information about the height of the surveyed area that can help with the discrimination of classes and their separability. In the past, several efforts have been investigated for fusion of hyperspectral and LiDAR data, with some efforts driven by the morphological information that can be derived from both data sources. However, a main challenge for the learning approaches is how to exploit the information coming from multiple features. Specifically, it has been found that simple concatenation or stacking of features such as morphological attribute profiles (APs) may contain redundant information. In addition, a significant increase in the number of features may lead to very high-dimensional input features. This is in contrast with the limited number of training samples often available in remote-sensing applications, which may lead to the Hughes effect. In this work, we develop a new efficient strategy for fusion and classification of hyperspectral and LiDAR data. Our approach has been designed to integrate multiple types of features extracted from these data. An important characteristic of the presented approach is that it does not require any regularization parameters, so that different types of features can be efficiently exploited and integrated in a collaborative and flexible way. Our experimental results, conducted using a hyperspectral image and a LiDAR-derived digital surface model (DSM) collected over the University of Houston campus and the neighboring urban area, indicate that the proposed framework for multiple feature learning provides state-of-the-art classification results.

Mitochondria in Mammalian Sperm Physiology and Pathology: A Review

Abstract: While, for a long time, the role of mitochondria in sperm physiology and pathology has been largely ignored, recent research points out the mitochondria as a major organelle with key roles in sperm function both under physiological and biotechnological conditions. This paper briefly reviews these novel findings regarding the role of mitochondria in sperm, paying special attention to the most practical, readily applicable, aspects of the topic such as their role as a major source of the sublethal damage that sperm experiments after cryopreservation.

The Maunder minimum (1645--1715) was indeed a Grand minimum: A reassessment of multiple datasets

Abstract: Aims: Although the time of the Maunder minimum (1645--1715) is widely known as a period of extremely low solar activity, claims are still debated that solar activity during that period might still have been moderate, even higher than the current solar cycle #24. We have revisited all the existing pieces of evidence and datasets, both direct and indirect, to assess the level of solar activity during the Maunder minimum. Methods: We discuss the East Asian naked-eye sunspot observations, the telescopic solar observations, the fraction of sunspot active days, the latitudinal extent of sunspot positions, auroral sightings at high latitudes, cosmogenic radionuclide data as well as solar eclipse observations for that period. We also consider peculiar features of the Sun (very strong hemispheric asymmetry of sunspot location, unusual differential rotation and the lack of the K-corona) that imply a special mode of solar activity during the Maunder minimum. Results: The level of solar activity during the Maunder minimum is reassessed on the basis of all available data sets. Conclusions: We conclude that solar activity was indeed at an exceptionally low level during the Maunder minimum. Although the exact level is still unclear, it was definitely below that during the Dalton minimum around 1800 and significantly below that of the current solar cycle #24. Claims of a moderate-to-high level of solar activity during the Maunder minimum are rejected at a high confidence level.