Revista Cubana de Física

The great complexity of the human connectome motivates the study of a simpler neural network. For that purpose, the Ising Model was applied on experimental data on the synaptic connectivity of Caenorhabditis elegans (C. elegans) in resting-state, assigning a binary variable (representing active or inactive states) to each neuron in the network. The dynamics of this system is postulated as a message passing network, encoded by the Belief Propagation algorithm (BP) in its criticality region. The inferences of neuronal activity maps were obtained for different times of the nematode’s life cycle. We determined the network susceptibilities as a measure of correlations in the system through the Susceptibility Propagation algorithm (SP). Finally, we applied clustering methods to obtain functional clusters and analyze similarities between them and the real functional clusters (sensory, interneurons and motor). All this contributed to the analysis of structure-function relationship in the C. elegans neural network.

This paper aims at introducing the Kalman’s filter to science and engineering undergraduate students by means of a simple experiment. It consists in the free fall of an umbrella equipped with a mobile phone from a height of a few-meters. Using the data provided by the accelerometer embedded in the phone, it is shown that the use of the Kalman filter allows determining the terminal velocity without the need of performing multiple repetitions of the experiment. Three methods for finding the covariance matrix of the control vector are tested, and their results are compared.

We analyzed amber samples from the Baltic region (Mexico) and imitation amber, in order to develop an analytical method allowing to discriminate between different samples causing little or no damage. We propose a two-step method that involves the use of Laser Induced Breakdown Spectroscopy (LIBS) to obtain spectra, and Discriminant Analysis to analyze the resulting data. We studied the damage caused to the samples using confocal optical microscopy.

The main objective of this research is to create a signal processing simulation using Javascript programming language on acoustic waves. Signal processing uses Fourier Transform to convert signals from the time domain to the frequency domain. Acoustic wave samples were obtained from a Javanese musical instrument called Gamelan. Acoustic wave signals from Gamelan are chosen because there is still little research on Gamelan signal processing. This research has successfully created a simulation using Javascript programming language. The simulation can show the waveform in function of time and its wave spectrum. The convenience of this tools for distant learning is substantiated.

This study aims at simulating the energy dispersion of graphene using Spreadsheet as a distance (online) learning as a solution for physics learning, especially for undergraduate students. Here we compare the simulation results of graphene’s dispersion energy from various literatures and then discussed them from the educational point of view. The Spreadsheet is used to visualize the energy dispersions of graphene having hexagonal honeycomb lattice structure. The results obtained are graphene’s energy dispersion simulations from various literature sources, especially from 2010 to 2019. Moreover, although the mathematical formulas are different, the graphene’s energy dispersion profiles are mostly similar in wireframe and 3D surface patterns. These simulation results can be used in teaching undergraduate students in making simple simulations using Spreadsheet.