8,285 research outputs found
Wind loads analysis at the anchorages of the Talavera de la Reina cable stayed bridge
No full textThis paper describes wind tunnel tests performed on wind tunnel models of the Talavera de la Reina cable stayed bridge. The work describes the aeroelastic model construction and it is focused on the evaluation and analysis of the mean and peak wind loads at the tower foundation and the cable anchorages since these data can be very useful by the bridge manufacturer as a support for the bridge design. The work is part of a complete wind tunnel study carried out to analyze the aeroelastic stability of the bridge
Letter by Guazzi and Reina Regarding Article, "Aspirin Use and Outcomes in a Community-Based Cohort of 7352 Patients Discharged After First Hospitalization for Heart Failure"
No full textCross-Coupled Control for All-Terrain Rovers
No full textMobile robots are increasingly being used in challenging outdoor environments for applications that include construction, mining, agriculture, military and planetary exploration. In order to accomplish the planned task, it is critical that the motion control system ensure accuracy and robustness. The achievement of high performance on rough terrain is tightly connected with the minimization of vehicle-terrain dynamics effects such as slipping and skidding. This paper presents a cross-coupled controller for a 4-wheel-drive/4-wheel-steer robot, which optimizes the wheel motors’ control algorithm to reduce synchronization errors that would otherwise result in wheel slip with conventional controllers. Experimental results, obtained with an all-terrain rover operating on agricultural terrain, are presented to validate the system. It is shown that the proposed approach is effective in reducing slippage and vehicle posture errors
Fotografía UDBC029742
No full textFotografía del ejemplar Reina, G. 118, determinado como Anthurium sp
Fotografía UDBC029734
No full textFotografía del ejemplar Reina, G. 117, determinado como Anthurium sp
Eduardo G. Rico: María Cristina, la reina burguesa
No full textReview of: Eduardo G. Rico, María Cristina, la reina burguesa. Barcelona, Planeta, 1994, 200 pp
Epigenetic Modulation of Chromatin States and Gene Expression by G-Quadruplex Structures
No full textG-quadruplexes are four-stranded helical nucleic acid structures formed by guanine-rich sequences. A considerable number of studies have revealed that these noncanonical structural motifs are widespread throughout the genome and transcriptome of numerous organisms, including humans. In particular, G-quadruplexes occupy strategic locations in genomic DNA and both coding and noncoding RNA molecules, being involved in many essential cellular and organismal functions. In this review, we first outline the fundamental structural features of G-quadruplexes and then focus on the concept that these DNA and RNA structures convey a distinctive layer of epigenetic information that is critical for the complex regulation, either positive or negative, of biological activities in different contexts. In this framework, we summarize and discuss the proposed mechanisms underlying the functions of G-quadruplexes and their interacting factors. Furthermore, we give special emphasis to the interplay between G-quadruplex formation/disruption and other epigenetic marks, including biochemical modifications of DNA bases and histones, nucleosome positioning, and three-dimensional organization of chromatin. Finally, epigenetic roles of RNA G-quadruplexes in post-transcriptional regulation of gene expression are also discussed. Undoubtedly, the issues addressed in this review take on particular importance in the field of comparative epigenetics, as well as in translational research
Efficient Power-Split Powertrain for Full Electric Vehicles
No full textElectric vehicles are typically employed in highly-variable operating conditions, especially during city drive. The variability in speed and torque results in suboptimal efficiency of the drive motor. However, recent technological advances in new embedded processing units and power electronics open the way to the adoption of novel efficient control strategies of the electric powertrain. This paper proposes an architecture that in contrast to the use of a single drive electric motor employs two drive motors of smaller size combined through a planetary gear. This power-split full-electric architecture ensures both drive motors to operate in their optimal working range resulting in a higher overall efficiency. A parametric optimization is performed showing an increase in the average efficiency of about 7% with respect to a single motor for the Artemis urban cycle
Adaptive Multi-Sensor Perception for Driving Automation in Outdoor Contexts
No full textIn this research, adaptive perception for driving automation is discussed so as to enable a vehicle to automatically detect driveable areas and obstacles in the scene. It is especially designed for outdoor contexts where conventional perception systems that rely on a priori knowledge of the terrain's geometric properties, appearance properties, or both, is prone to fail, due to the variability in the terrain properties and environmental conditions. In contrast, the proposed framework uses a self-learning approach to build a model of the ground class that is continuously adjusted online to reflect the latest ground appearance. The system also features high flexibility, as it can work using a single sensor modality or a multi-sensor combination. In the context of this research, different embodiments have been demonstrated using range data coming from either a radar or a stereo camera, and adopting self-supervised strategies where monocular vision is automatically trained by radar or stereo vision. A comprehensive set of experimental results, obtained with different ground vehicles operating in the field, are presented to validate and assess the performance of the system
Towards Autonomous Agriculture: Automatic Ground Detection Using Trinocular Stereovision
No full textAutonomous driving is a challenging problem, particularly when the domain is unstructured, as in an outdoor agricultural setting. Thus, advanced perception systems are primarily required to sense and understand the surrounding environment recognizing artificial and natural structures, topology, vegetation and paths. In this paper, a self-learning framework is proposed to automatically train a ground classifier for scene interpretation and autonomous navigation based on multi-baseline stereovision. The use of rich 3D data is emphasized where the sensor output includes range and color information of the surrounding environment. Two distinct classifiers are presented, one based on geometric data that can detect the broad class of ground and one based on color data that can further segment ground into subclasses. The geometry-based classifier features two main stages: an adaptive training stage and a classification stage. During the training stage, the system automatically learns to associate geometric appearance of 3D stereo-generated data with class labels. Then, it makes predictions based on past observations. It serves as well to provide training labels to the color-based classifier. Once trained, the color-based classifier is able to recognize similar terrain classes in stereo imagery. The system is continuously updated online using the latest stereo readings, thus making it feasible for long range and long duration navigation, over changing environments. Experimental results, obtained with a tractor test platform operating in a rural environment, are presented to validate this approach, showing an average classification precision and recall of 91.0% and 77.3%, respectively
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