Impact of HF radar current gap-filling methodologies on the Lagrangian assessment of coastal dynamics

High-frequency radar, HFR, is a cost-effective monitoring technique that allows us to obtain high-resolution continuous surface currents, providing new insights for understanding small-scale transport processes in the coastal ocean. In the last years, the use of Lagrangian metrics to study mixing and transport properties has been growing in importance. A common condition among all the Lagrangian techniques is that complete spatial and temporal velocity data are required to compute trajectories of virtual particles in the flow. However, hardware or software failures in the HFR system can compromise the availability of data, resulting in incomplete spatial coverage fields or periods without data. In this regard, several methods have been widely used to fill spatiotemporal gaps in HFR measurements. Despite the growing relevance of these systems there are still many open questions concerning the reliability of gap-filling methods for the Lagrangian assessment of coastal ocean dynamics. In this paper, we first develop a new methodology to reconstruct HFR velocity fields based on self-organizing maps (SOMs). Then, a comparative analysis of this method with other available gap-filling techniques is performed, i.e., open-boundary modal analysis (OMA) and data interpolating empirical orthogonal functions (DINEOFs). The performance of each approach is quantified in the Lagrangian frame through the computation of finite-size Lyapunov exponents, Lagrangian coherent structures and residence times. We determine the limit of applicability of each method regarding four experiments based on the typical temporal and spatial gap distributions observed in HFR systems unveiled by a K-means clustering analysis. Our results show that even when a large number of data are missing, the Lagrangian diagnoses still give an accurate description of oceanic transport properties.</p

Synchrony-induced modes of oscillation of a neural field model

We investigate the modes of oscillation of heterogeneous ring-networks of quadratic integrate-and-fire (QIF) neurons with non-local, space-dependent coupling. Perturbations of the equilibrium state with a particular wave number produce transient standing waves with a specific temporal frequency, analogous to those in a tense string. In the neuronal network, the equilibrium corresponds to a spatially homogeneous, asynchronous state. Perturbations of this state excite the network’s oscillatory modes, which reflect the interplay of episodes of synchronous spiking with the excitatory-inhibitory spatial interactions. In the thermodynamic limit, an exact low-dimensional neural field model (QIF-NFM) describing the macroscopic dynamics of the network is derived. This allows us to obtain formulas for the Turing eigenvalues of the spatially-homogeneous state, and hence to obtain its stability boundary. We find that the frequency of each Turing mode depends on the corresponding Fourier coefficient of the synaptic pattern of connectivity. The decay rate instead, is identical for all oscillation modes as a consequence of the heterogeneity-induced desynchronization of the neurons. Finally, we numerically compute the spectrum of spatially-inhomogeneous solutions branching from the Turing bifurcation, showing that similar oscillatory modes operate in neural bump states, and are maintained away from onset

Fortalecimiento de gestiones a través del Centro de Información de Actividades Porcinas (CIAP) para el desarrollo sustentable de pequeños y medianos productores porcinos familiares de la zona de influencia de la Facultad de Ciencias Agrarias de la Universidad Nacional de Rosario

Fortalecimiento de gestiones a través del Centro de Información de Actividades Porcinas (CIAP) para el desarrollo sustentable de pequeños y medianos productores porcinos familiares de la zona de influencia de la Facultad de Ciencias Agrarias de la Universidad Nacional de RosarioFil: Silva, Patricia. Universidad Nacional de Rosario. Facultad de Ciencias Agrarias; Argentin

Young men’s body dissatisfaction: A qualitative analysis of anonymous online accounts

Associated with numerous adverse health outcomes, body dissatisfaction in young men requires close examination. This study explores online accounts relating to male body image, including young men’s personal disclosures within one online newspaper article, and posts responding to this topic. Discursively informed thematic analysis indicated that non-disclosure was considered a problematic social expectation by the young men featured in the article. Also, reader posts variously constructed body dissatisfaction as a symptom of adolescence, a lack of self-care and an incapacity to capitalise on compensatory qualities. Our analysis suggests young men may welcome safe opportunities to critically discuss prevailing body image ideals

Variability in the air-sea interaction patterns and timescales within the south-eastern Bay of Biscay, as observed by HF radar data

Two high-frequency (HF) radar stations were installed on the coast of the south-eastern Bay of Biscay in 2009, providing high spatial and temporal resolution and large spatial coverage of currents in the area for the first time. This has made it possible to quantitatively assess the air-sea interaction patterns and timescales for the period 2009-2010. The analysis was conducted using the Barnett-Preisendorfer approach to canonical correlation analysis (CCA) of reanalysis surface winds and HF radar-derived surface currents. The CCA yields two canonical patterns: the first wind-current interaction pattern corresponds to the classical Ekman drift at the sea surface, whilst the second describes an anticyclonic/cyclonic surface circulation. The results obtained demonstrate that local winds play an important role in driving the upper water circulation. The wind-current interaction timescales are mainly related to diurnal breezes and synoptic variability. In particular, the breezes force diurnal currents in waters of the continental shelf and slope of the south-eastern Bay. It is concluded that the breezes may force diurnal currents over considerably wider areas than that covered by the HF radar, considering that the northern and southern continental shelves of the Bay exhibit stronger diurnal than annual wind amplitudes.The authors thank two anonymous reviewers and, particularly, the editor Mike Kosro for their very constructive comments, which have led to an improved version of the manuscript. The authors thank the Directorate of Emergency Attention and Meteorology of the Basque Government for establishing the operational data acquisition system. The authors acknowledge financial support from the ETORTEK Strategic Research Programme (Department of Industry, Trade and Tourism and Department of Transport and Civil Works of the Basque Government) through the ITSASEUS II project. The Basque Government (Department of Agriculture, Fisheries and Food) has funded the project "VARIACIONES". We thank Qualitas Remos for the work performed on HF radar data processing and also L. Solabarrieta for her enthusiasm and interest in the HF radar measurements. Jon Saenz is grateful for financial support from projects CGL2008-03321 (Spanish National R+D+I Programme) and CTP10-03 PYNATEO (Basque Government). He also acknowledges funding provided by the University of the Basque Country (UFI 11/55, GIU 11/01 and PPM12/01). The wind data for this study are from the Research Data Archive (RDA), which is maintained by the Computational and Information Systems Laboratory (CISL) at the National Center for Atmospheric Research (NCAR). NCAR is sponsored by the National Science Foundation (NSF). The original data are available from the RDA (http://dss.ucar.edu) in dataset number ds093.1. G. Esnaola is supported by a research grant from the Fundacion Centros Tecnologicos, Inaki Goenaga. This is contribution number 618, of the Marine Research Division of AZTI-Tecnalia

Empirical risk minimization with relative entropy regularization

The empirical risk minimization (ERM) problem with relative entropy regularization (ERM-RER) is investigated under the assumption that the reference measure is a σ-finite measure, and not necessarily a probability measure. Under this assumption, which leads to a generalization of the ERM-RER problem allowing a larger degree of flexibility for incorporating prior knowledge, numerous relevant properties are stated. Among these properties, the solution to this problem, if it exists, is shown to be a unique probability measure, mutually absolutely continuous with the reference measure. Such a solution exhibits a probably-approximately-correct guarantee for the ERM problem independently of whether the latter possesses a solution. For a fixed dataset and under a specific condition, the empirical risk is shown to be a sub-Gaussian random variable when the models are sampled from the solution to the ERM-RER problem. The generalization capabilities of the solution to the ERM-RER problem (the Gibbs algorithm) are studied via the sensitivity of the expected empirical risk to deviations from such a solution towards alternative probability measures. Finally, an interesting connection between sensitivity, generalization error, and lautum information is established