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P. Silva

Publications and source records attributed to P. Silva.

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Studying stellar populations in Omega Centauri with phylogenetics

The nature and formation history of our Galaxy's largest and most enigmatic stellar cluster, known as Omega Centauri (ocen) remains debated. Here, we offer a novel approach to disentangling the complex stellar populations within ocen based on phylogenetics methodologies from evolutionary biology. These include the Gaussian Mixture Model and Neighbor-Joining clustering algorithms applied to a set of chemical abundances of ocen stellar members. Instead of using the classical approach in astronomy of grouping them into separate populations, we focused on how the stars are related to each other. In this way, we could identify stars that likely formed in globular clusters versus those originating from prolonged in-situ star formation and how these stars interconnect. Our analysis supports the hypothesis that ocen might be a nuclear star cluster of a galaxy accreted by the Milky Way with a mass of about 10^9M_sun. Furthermore, we revealed the existence of a previously unidentified in-situ stellar population with a distinct chemical pattern unlike any known population found in the Milky Way to date. Our analysis of ocen is an example of the success of cross-disciplinary research and shows the vast potential of applying evolutionary biology tools to astronomical datasets, opening new avenues for understanding the chemical evolution of complex stellar systems.

astro-ph.GA

The AEROS ocean observation mission and its CubeSat pathfinder

AEROS aims to develop a nanosatellite as a precursor of a future system of systems, which will include assets and capabilities of both new and existing platforms operating in the Ocean and Space, equipped with state-of-the-art sensors and technologies, all connected through a communication network linked to a data gathering, processing and dissemination system. This constellation leverages scientific and economic synergies emerging from New Space and the opportunities in prospecting, monitoring, and valuing the Ocean in a sustainable manner, addressing the demand for improved spatial, temporal, and spectral coverage in areas such as coastal ecosystems management and climate change assessment and mitigation. Currently, novel sensors and systems, including a miniaturized hyperspectral imager and a flexible software-defined communication system, are being developed and integrated into a new versatile satellite structure, supported by an innovative on-board software. Additional sensors, like the LoRaWAN protocol and a wider field of view RGB camera, are under study. To cope with data needs, a Data Analysis Centre, including a cloud-based data and telemetry dashboard and a back-end layer, to receive and process acquired and ingested data, is being implemented to provide tailored-to-use remote sensing products for a wide range of applications for private and institutional stakeholders.

physics.ao-ph

Valley notch filter in a graphene strain superlattice: Green's function and machine learning approach

The valley transport properties of a superlattice of out-of-plane Gaussians deformations are calculated using a Green's function and a Machine Learning approach. Our results show that periodicity significantly improves the valley filter capabilities of a single Gaussian deformation, these manifest themselves in the conductance as a sequence by valley filter plateaus. We establish that the physical effect behind the observed valley notch filter is the coupling between counter-propagating transverse modes; the complex relationship between the design parameters of the superlattice and the valley filter effect make difficult to estimate in advance the valley filter potentialities of a given superlattice. With this in mind, we show that a Deep Neural Network can be trained to predict valley polarization with a precision similar to the Green's function but with much less computational effort.

cond-mat.mes-hall

A Customized System to Assess Foot Plantar Pressure: A Case Study on Calloused and Normal Feet

Foot plantar pressure monitoring is an important tool for biomechanical assessment of posture, foot complications due to callus formation and wounds and for sports applications. The pronounced cost associated with commercial plantar pressure monitoring systems and inflexibility of custom analyzing data in such systems prompted the development of a versatile system with minimized cost. This study focuses on the development of such a system with high speed data acquisition providing analysis tools for assessing plantar pressure variations of diabetic patients with calloused feet. The new system is capable of achieving a frame rate of 155 Hz which is ideal for pressure monitoring during both standing and walking. The system was verified using 10 normal subjects and 5 diabetic subjects with calluses on in their feet. Results indicate significantly high mechanical stresses on skin beneath callus and postural disorders during standing, in subjects with calluses.

eess.SP