Electrically Driven Microcavity Exciton-Polariton Optomechanics at 20 GHz

Microcavity exciton polaritons enable the resonant coupling of excitons and photons to vibrations in the super-high-frequency (SHF, 3–30 GHz) domain. We introduce here a novel platform for coherent SHF optomechanics based on the coupling of polaritons and electrically driven SHF longitudinal acoustic phonons confined in a planar Bragg microcavity. The highly monochromatic phonons with tunable amplitudes are excited over a wide frequency range by piezoelectric transducers, which also act as efficient phonon detectors with a very large dynamical range. The microcavity platform exploits the long coherence time of polaritons as well as their efficient coupling to phonons. Furthermore, an intrinsic property of the platform is the backfeeding of phonons to the interaction region via reflections at the sample boundaries, which leads to quality factor × frequency products (Q×f) exceeding 1014  Hz as well as huge modulation amplitudes of the optical transition energies exceeding 8 meV. We show that the modulation is dominated by the phonon-induced energy shifts of the excitonic polariton component. Thus, the large modulation leads to a dynamical switching of light-matter nature of the particles from a mixed (i.e., polaritonic) one to photonlike and excitonlike states at frequencies up to 20 GHz. On the one hand, this work opens the way for electrically driven polariton optomechanics in the nonadiabatic, sideband-resolved regime of coherent control. Here, the bidirectionality of the transducers can be exploited for light-to-sound-to-rf conversion. On the other hand, the large phonon frequencies and Q×f products enable phonon control with optical readout down to the single-particle regime at relatively high temperatures (of 1 K)

A Population Dynamics Approach to Viral Marketing

Souto, P. C., Silva, L. V., Pinto, D. C., & Santos, F. C. (2020). A Population Dynamics Approach to Viral Marketing. In H. Cherifi, S. Gaito, J. F. Mendes, E. Moro, & L. M. Rocha (Eds.), Complex Networks and Their Applications VIII : Proceedings of the 8th International Conference on Complex Networks and Their Applications, COMPLEX NETWORKS 2019 (Vol. 1, pp. 399-411). (Studies in Computational Intelligence; Vol. 881 SCI). Springer. https://doi.org/10.1007/978-3-030-36687-2_33The symbiosis of Social Media and viral campaigns has recently become ubiquitous. In many recent phenomena (e.g., the Cambridge Analytica scandal), rumours in viral marketing programs are present without being even noticed by consumers. Yet, the study of population dynamics and its complex patterns of interaction remains largely elusive. Here, we propose an agent-based Marketing referral model to study the impact on firms’ dissemination and profitability of biased behavior in a population of opportunistic individuals. We show that those agents only interested in collecting rewards without any brand recognition are responsible for most of Marketing campaign success and dissemination, for a large range of different cost structures, network characteristics, and number of invites. This effect is further amplified whenever the difference between the cost of using the service and the reward collected after bringing a new customer is higher.authorsversionpublishe

Acoustically Driven Stark Effect in Transition Metal Dichalcogenide Monolayers

The Stark effect is one of the most efficient mechanisms to manipulate many-body states in nanostructured systems. In mono- and few-layer transition metal dichalcogenides, it has been successfully induced by optical and electric field means. Here, we tune the optical emission energies and dissociate excitonic states in MoSe2 monolayers employing the 220 MHz in-plane piezoelectric field carried by surface acoustic waves. We transfer the monolayers to high dielectric constant piezoelectric substrates, where the neutral exciton binding energy is reduced, allowing us to efficiently quench (above 90%) and red-shift the excitonic optical emissions. A model for the acoustically induced Stark effect yields neutral exciton and trion in-plane polarizabilities of 530 and 630 × 10-5 meV/(kV/cm)2, respectively, which are considerably larger than those reported for monolayers encapsulated in hexagonal boron nitride. Large in-plane polarizabilities are an attractive ingredient to manipulate and modulate multiexciton interactions in two-dimensional semiconductor nanostructures for optoelectronic applications. © 2021 The Authors. Published by American Chemical Society

Ecología y biodiversidad de un arrecife formado por Phragmatopoma caudata Krøyer in Mörch (Canalipalpata: Sabellariidae) en República Dominicana

Se evaluó un arrecife formado por Phragmatopoma caudata (Canalipalpata: Sabellariidae), ubicado en Barco Viejo o Playa Desembarco, provincia Samaná, República Dominicana. Este tipo de arrecife está compuesto por los restos de sedimentos y rocas que son gradualmente depositados a través del tiempo por estos gusanos sabeláridos. El arrecife tiene una longitud de 115 m en total, 1.59 m de altura máxima y 19.58 m de ancho máximo, formando dos peldaños. La arena colectada en el arrecife y la playa presentaba granulometría variada, en la que los granos de arena de la playa se encontraron más pequeños que los granos de la arena de arrecife. Los diámetros de los tubos de gusano no superaron los 4 mm de ancho y 5.5 cm de altura. Hubo una disminución en la población de gusanos durante el tiempo abarcado por este estudio. Se registraron 19 especies de diferentes filos en el arrecife. El índice de Margalef fue de 5.04, el cual está por encima del máximo común. El índice de Shannon fue valorado en 0.54, el cual se considera extremadamente bajo. En base a estos resultados se infiere que la morfología de este arrecife proporciona arena a la playa y la protege de las condiciones ambientales adversas. Este arrecife es un foco de biodiversidad en la zona

FIRST RECORD OF A NUCLEAR-FOLLOWER ASSOCIATION BETWEEN CORYDORAS VITTATUS (NIJSSEN, 1971), CORYDORAS CF. JULII (CALLICHTHYIDAE) AND KNODUS VICTORIAE (STEINDACHNER, 1907) (CHARACIDAE)

Nuclear-follower interactions are a particular type of interspecific foraging association which involves a nuclear species, which revolves or scans through the substrate, and follower species that access the food items made available by the nuclear species’ activity. This type of association was observed in a headwater stream at the Itapecuru basin, in the Maranhão cerrado, involving the catfishes Corydoras vittatus, Corydoras cf. julii as nuclear species and Knodus victoriae as its follower. Individuals of C. vittatus, Corydoras cf. julii revolved the substrate during their foraging, promoting sediment suspension. Their followers, in turn, moved through the “cloud” of particles in suspension, capturing food items. Food particles in suspension do not seem to be used by the catfishes but become available for K. victoriae. The follower behavior represents a feeding tactic for these species, reinforcing the general idea of behavioral plasticity between follower species

Predictive Maintenance Model Based on Anomaly Detection in Induction Motors: A Machine Learning Approach Using Real-Time IoT Data

With the support of Internet of Things (IoT) devices, it is possible to acquire data from degradation phenomena and design data-driven models to perform anomaly detection in industrial equipment. This approach not only identifies potential anomalies but can also serve as a first step toward building predictive maintenance policies. In this work, we demonstrate a novel anomaly detection system on induction motors used in pumps, compressors, fans, and other industrial machines. This work evaluates a combination of pre-processing techniques and machine learning (ML) models with a low computational cost. We use a combination of pre-processing techniques such as Fast Fourier Transform (FFT), Wavelet Transform (WT), and binning, which are well-known approaches for extracting features from raw data. We also aim to guarantee an optimal balance between multiple conflicting parameters, such as anomaly detection rate, false positive rate, and inference speed of the solution. To this end, multiobjective optimization and analysis are performed on the evaluated models. Pareto-optimal solutions are presented to select which models have the best results regarding classification metrics and computational effort. Differently from most works in this field that use publicly available datasets to validate their models, we propose an end-to-end solution combining low-cost and readily available IoT sensors. The approach is validated by acquiring a custom dataset from induction motors. Also, we fuse vibration, temperature, and noise data from these sensors as the input to the proposed ML model. Therefore, we aim to propose a methodology general enough to be applied in different industrial contexts in the future