Contributors:Carla Lima, Roberto Gimenez, Wilson Bonifacio, Girland Amud, Sandra Regina Alouche, Cristiane Makida-Dyonisio, Edison Manoel
Background: This study investigated two approaches of sensory-motor stimulation for parents to perform to their preterm infants.
Objective: The aim of the present study was to investigate the effect of two different stimulation approaches in the development of preterm infants.
Method: One approach was directive, in which parents have performed a strict order of movements. The second approach was indirective, in which parents were oriented to provide a rich context for sensory-motor stimulation so that infants could experience the association between their movements and environmental consequences. Seventeen preterm infants accompanied by their caregivers were divided into two groups: Directive Group, n=10; and Indirective Group, n=7. Infants’ development was followed for over six months by the Alberta Scale.
Results: After the intervention, the indirective group reached more advanced stages of development than the directive group.
Daily Coronavirus Disease (Covid-19) prevalence data from 25th of January 2020 until 29th of April 2020 were collected from the records of the Ministry of Health Malaysia and Excel 2019 was used to build a time-series database. All fully-anonymized, laboratory-confirmed cases were abstracted on Covid-19 in which 5,945 cases represented Covid-19 infection in 16 states in Malaysia as recorded by the Ministry of Health Malaysia. The non-parametric Mann-Kendall Test (MK) statistical test has usually been used to assess the significance of a trend at a site. Meanwhile, the prediction model was developed based on Singular Spectrum Analysis (SSA) which called it as Recurrent Forecasting (RF-SSA) to predict the new daily confirmed Covid-19 cases for a short-term period.
This paper explored the coordination-like phenomena observed in collective dissipative structures. We observed the coordination of two self-organized electrical structures that oscillated together in a shared electrical field. The system is called the Electrical Self-Organized Foraging Implementation (E-SOFI). The structures are coupled by this field and settle into stable oscillatory regimes defined by their relative phase. We also observed the oscillatory dynamics of simulated electrical structures, using a computational model called the Charge Depletion Model (CDM; De Bari et al., 2019). We predicted that both in-phase (zero radians relative phase) and anti-phase (pi radians relative phase) would be stable oscillatory modes for the physical and simulated system. Previous work has demonstrated that this system self-selects for states of maximal current. We predicted that the model would demonstrate differential stability of in-phase and anti-phase modes, in accordance with whichever mode produced the greater current.
This data set includes the digitally tracked positions of the physical structures, gathered from video data. One data set demonstrated in-phase coordination, and another demonstrated anti-phase coordination. Also included are corresponding data from simulations of the physical model. Simulations tested the existence of the in-phase and anti-phase modes, and the current conducted during the coordination. Simulations were conducted across a parameter space that varied the stability of the in- and anti-phase coordination modes.
We demonstrated stability in the in-phase coordination mode, and potential meta-stability of the anti-phase mode in the physical system. Simulations suggested that within a reasonable parameter space the anti-phase mode can be made stable. Simulations also revealed that within a given parameter space, whichever mode produces greater current is also more stable.
An R Markdown file includes the code to compute the relative phase of both the physical and simulated data, as well as the code used to produce the plots in the published manuscript.
Contributors:John Palmieri, Kevin Spiegler, Kevin Pang, Catherine Myers
The purpose of this experiment was to compare between-strain differences regarding avoidance behavior. Active avoidance data were collected from 40 Wistar-Kyoto (WKY) and 40 Sprague Dawley (SD) rats during a foot-shock experiment. The experiment consisted of 12 sessions each composed of 25 trials. Each trial consisted of a warning period, a possible shock period (if avoidance did not occur), and an intertrial interval (ITI) representing a safety period. During warning periods, rats had an option to press a lever in order to avoid future shock. However, if a lever press did not occur, then a shock period began during which the rats could press the lever to escape the foot-shock. After an escape or an avoidance, a 180-second safe period began (ITI). The maximum time of a warning period and a shock were both 72-seconds each if the rat failed to lever press during both periods. Every session also began with a 60-second habituation period during which the rat could familiarize itself with the experimental cage.
Lever presses during ITI periods were classified as inter-trial responses (ITRs) whereas lever presses during the habituation periods were classified as anticipatory responses (ARs). Lever presses during shock periods were labeled as escapes “E” whereas lever presses during warning periods were labeled as avoidances “A”.
Lever press data were discretized to 12-second periods. Frequency counts for lever presses during each 12-second timestep can be found in the raw data files (located in the “ratRL_datafiles_Model_InputOutput” folder). An example name of this file is “S09.csv” representing an SD rat or “W09.csv” representing a WKY rat.
A reinforcement learning, actor-critic model was applied to this raw data to determine different learning parameters for each rat. The code for this model fitting can be found in the folder titled “ratRL_ModelFitting_Code”.
Based on learning parameters determined from the reinforcement learning model code, a simulation of theoretical rats running through the experimental protocol was created. This simulation can be found in the “ratRL_Simulation_Code” folder. Inputs to this simulation are found in the “ratRL_codedTrials_Sim_InputOutput” folder. The summaries for each experimental rat’s performance during the foot-shock avoidance experiment are labeled “Sum” files (ie S09sum.csv) and the learning parameters for each rat are stored in the file called “parm_listfile.csv”. Output files are labeled “out” (ie S09out.csv) and represent the performance of a theoretical simulated rat.
The differences in learning parameters between the two rat strains can provide insight into anxiety-disorders as the WKY rats have been used as an animal model for anxiety. Learning parameters can also be mapped to certain brain regions in order to explore possible neurological differences in the two strains in future experiments.
The high sensitivity of COVID-19 and the need for high accuracy calculations necessitate collecting the required data sets from reliable sources. Thus, all information was collected and categorized from reputable sources such as WHO (World Health Organization) and worldometers site (www.worldometers.info). The worldometers site contains information such as daily mortality statistics, recovery, and newly confirmed cases.
Research data including observation data is obtained from a collection of Iranian samples’ reports in three parts (i.e. death, confirmed and recovered). This countrywide daily information is confirmed by the WHO. It should be noted that the relevant data was collected between February 19 and May 16, 2020.