Macroevolutionary dynamics of nectar spurs, a key evolutionary innovation.

Floral nectar spurs are widely considered a key innovation promoting diversification in angiosperms by means of pollinator shifts. We investigated the macroevolutionary dynamics of nectar spurs in the tribe Antirrhineae (Plantaginaceae), which contains 29 genera and 300-400 species (70-80% spurred). The effect of nectar spurs on diversification was tested, with special focus on Linaria, the genus with the highest number of species. We generated the most comprehensive phylogeny of Antirrhineae to date and reconstructed the evolution of nectar spurs. Diversification rate heterogeneity was investigated using trait-dependent and trait-independent methods, and accounting for taxonomic uncertainty. The association between changes in spur length and speciation was examined within Linaria using model testing and ancestral state reconstructions. We inferred four independent acquisitions of nectar spurs. Diversification analyses revealed that nectar spurs are loosely associated with increased diversification rates. Detected rate shifts were delayed by 5-15 Myr with respect to the acquisition of the trait. Active evolution of spur length, fitting a speciational model, was inferred in Linaria, which is consistent with a scenario of pollinator shifts driving diversification. Nectar spurs played a role in diversification of the Antirrhineae, but diversification dynamics can only be fully explained by the complex interaction of multiple biotic and abiotic factors.This work was supported by the Marie Curie Intra-European Fellowship LINARIA-SPECIATION (FP7-PEOPLE-2013-IEF, reference 624396), an Isaac Newton Trust Research Grant (Trinity College, Cambridge), a Juan de la Cierva fellowship to M.F.-M. (Spanish Ministry of Economy and Competitivity, reference IJCI-2015-23459) and a Generalitat Valenciana postdoctoral grant to A.J. (Ministry of Education, Culture and Sport, reference BEST/2014/264)

Introduction and evaluation of the ACS BCon basic course in Zaragoza, Spain

Background: The American College of Surgeons Bleeding Control Basic (BCon) course aimed at teaching hemorrhage control techniques in the USA had not yet been taught in Spain. The purpose of this study is to assess its implementation among students and healthcare employees in the Lozano Blesa University Hospital of Zaragoza, a middle-sized Spanish city. Methods: The study was conducted in a University Hospital and at the University of Zaragoza, scheduling four free B-Con sessions from 2017 to 2018. Two groups were identified as forming the population: healthcare employees and medical students. An anonymous questionnaire was completed at the end of the course regarding content, applicability, usefulness, relevance, and satisfaction. Study variables were ranked from 0 to 10: poor (when graded from 0 to 3), fair (4 to 6) and good (7 to 10). Results were compared between the groups, expressed in percentages and ¿ 2 tested to analyze significant differences if any. Results: Among the 83 individuals who completed the course, 46 were medical students and 37 healthcare employees; 61% women and 39% men; aged 21 years to 52 years. Attendees evaluated satisfaction with the highest grade (84%), followed by usefulness (73%), applicability (70%), and relevance (66%). There was no variable graded as poor. The comparison of perceptions between groups did not reveal statistical differences based on a 0.05 significance level. Conclusion: We concluded that the B-Con course was valued as good for relevance, usefulness, applicability, and satisfaction by the majority of the studied population. Level of Evidence: Level III

A robust procedure for damage detection from strain measurements based on principal component analysis

FBGs are excellent strain sensors, because of its low size and multiplexing capability. Tens to hundred of sensors may be embedded into a structure, as it has already been demonstrated. Nevertheless, they only afford strain measurements at local points, so unless the damage affects the strain readings in a distinguishable manner, damage will go undetected. This paper show the experimental results obtained on the wing of a UAV, instrumented with 32 FBGs, before and after small damages were introduced. The PCA algorithm was able to distinguish the damage cases, even for small cracks. Principal Component Analysis (PCA) is a technique of multivariable analysis to reduce a complex data set to a lower dimension and reveal some hidden patterns that underlie

Sensing the turbulent large-scale motions with their wall signature

This study assesses the capability of extended proper orthogonal decomposition (EPOD) and convolutional neural networks (CNNs) to reconstruct large-scale and very-large-scale motions (LSMs and VLSMs respectively) employing wall-shear-stress measurements in wall-bounded turbulent flows. Both techniques are used to reconstruct the instantaneous LSM evolution in the flow field as a combination of proper orthogonal decomposition (POD) modes, employing a limited set of instantaneous wall-shear-stress measurements. Due to the dominance of nonlinear effects, only CNNs provide satisfying results. Being able to account for nonlinearities in the flow, CNNs are shown to perform significantly better than EPOD in terms of both instantaneous flow-field estimation and turbulent-statistics reconstruction. CNNs are able to provide a more effective reconstruction performance employing more POD modes at larger distances from the wall and employing lower wall-measurement resolutions. Furthermore, the capability of tackling nonlinear features of CNNs results in estimation capabilities that are weakly dependent on the distance from the wall.This work has been partially supported by Grant No. DPI2016-79401-R funded by the Spanish State Research Agency (SRA) and the European Regional Development Fund (ERDF). A.G. acknowledges Dr. A. Sánchez for insightful discussions about CNN architecture. The authors acknowledge Dr. R. Vinuesa for insightful comments and discussions

Damage detection by using FBGs and strain field pattern recognition techniques

A novel methodology for damage detection and location in structures is proposed. The methodology is based on strain measurements and consists in the development of strain field pattern recognition techniques. The aforementioned are based on PCA (principal component analysis) and damage indices (T 2 and Q). We propose the use of fiber Bragg gratings (FBGs) as strain sensor

Liver tissue remodeling following ablation with irreversible electroporation in a porcine model

Irreversible electroporation (IRE) is a method of non-thermal focal tissue ablation characterized by irreversibly permeabilizing the cell membranes while preserving the extracellular matrix. This study aimed to investigate tissue remodeling after IRE in a porcine model, especially focusing on the extracellular matrix and hepatic stellate cells. IRE ablation was performed on 11 female pigs at 2,000 V/cm electric field strength using a versatile high-voltage generator and 3 cm diameter parallel-plate electrodes. The treated lobes were removed during surgery at 1, 3, 7, 14, and 21 days after IRE. Tissue remodeling and regeneration were assessed by histopathology and immunohistochemistry. Throughout the treated area, IRE led to extensive necrosis with intact collagenous structures evident until day 1. From then on, the necrosis progressively diminished while reparative tissue gradually increased. During this process, the reticulin framework and the septal fibrillar collagen remained in the necrotic foci until they were invaded by the reparative tissue. The reparative tissue was characterized by a massive proliferation of myofibroblast-like cells accompanied by a complete disorganization of the extracellular matrix with the disappearance of hepatic architecture. Hepatic stellate cell markers were associated with the proliferation of myofibroblast-like cells and the reorganization of the extracellular matrix. Between 2 and 3 weeks after IRE, the lobular architecture was almost completely regenerated. The events described in the present study show that IRE may be a valid model to study the mechanisms underlying liver regeneration after extensive acute injury