Microscopic Abrams-Strogatz model of language competition

The differential equations of Abrams and Strogatz for the competition between two languages are compared with agent-based Monte Carlo simulations for fully connected networks as well as for lattices in one, two and three dimensions, with up to 10^9 agents.Comment: 10 pages, 7 figure

Le briofite della Grotta dell\u2019Orso (33-7VG, Carso triestino, NE Italia)

Vengono presentati i risultati di uno studio sulla flora briologica della Grotta dell\u2019Orso (33-7VG), situata sul Carso triestino. Sono state rinvenute 42 specie di briofite (33 specie di muschi e 9 epatiche); per ogni specie sono indicati l\u2019elemento corologico, la distribuzione nell\u2019area e note ecologico-stazionali. Aspetti floristici, biogeografici e conservazionistici della componente briologica dell\u2019area vengono discussi. Viene riportata una nuova specie per la Regione Friuli Venezia Giulia, l\u2019epatica Cololejeunea rossettiana; 2 altre specie di muschi sono segnalate come nuove per il Carso. La flora briologica aggiornata della cavit\ue0 comprende 46 specie

Modeling the Yield Curve of BRICS Countries: Parametric vs. Machine Learning Techniques

We compare parametric and machine learning techniques (namely: Neural Networks) for in\u2013sample modeling of the yield curve of the BRICS countries (Brazil, Russia, India, China, South Africa). To such aim, we applied the Dynamic De Rezende\u2013Ferreira five\u2013factor model with time\u2013varying decay parameters and a Feed\u2013Forward Neural Network to the bond market data of the BRICS countries. To enhance the flexibility of the parametric model, we also introduce a new procedure to estimate the time varying parameters that significantly improve its performance. Our contribution spans towards two directions. First, we offer a comprehensive investigation of the bond market in the BRICS countries examined both by time and maturity; working on five countries at once we also ensure that our results are not specific to a particular data\u2013set; second we make recommendations concerning modelling and estimation choices of the yield curve. In this respect, although comparing highly flexible estimation methods, we highlight superior in\u2013sample capabilities of the neural network in all the examined markets and then suggest that machine learning techniques can be a valid alternative to more traditional methods also in presence of marked turbulence

2016 field monitoring report

Compiled June 2019.Colorado Forestry Best Management Practices

2018 field monitoring report

Compiled August 2020.Colorado Forestry Best Management Practices

Second-order odd-harmonic repetitive control and its application to active filter control

High order repetitive control has been introduced toovercomeperformance decay of repetitive control systems undervarying frequency of the signals to be tracked/rejected orimproving the interhamonic behavior. However, most highorder repetitive internal models used to improve frequencyuncertainty are unstable, as a consequence practicalimplementations are more difficult. In this work a stable,second order odd-harmonic repetitive control system ispresented and studied.The proposed internal model has been implemented andvalidated in a shunt active filter current controller. Thishigh order controller allows dealing with the gridfrequency variations without using adaptive schemes

Familiarity Facilitates Detection of Angry Expressions

Personal familiarity facilitates rapid and optimized detection of faces. In this study, we investigated whether familiarity associated with faces can also facilitate the detection of facial expressions. Models of face processing propose that face identity and face expression detection are mediated by distinct pathways. We used a visual search paradigm to assess if facial expressions of emotion (anger and happiness) were detected more rapidly when produced by familiar as compared to unfamiliar faces. We found that participants detected an angry expression 11% more accurately and 135 ms faster when produced by familiar as compared to unfamiliar faces while happy expressions were detected with equivalent accuracies and at equivalent speeds for familiar and unfamiliar faces. These results suggest that detectors in the visual system dedicated to processing features of angry expressions are optimized for familiar faces