Multi-outputs Gaussian process for predicting Burkina Faso COVID-19 spread using correlations from the weather parameters.

The novel coronavirus has affected all regions of the world, but each country has experienced different rates of infection. In West Africa, in particular, infection rates remain low as compared to other parts of the world. This heterogeneity in the spread of COVID-19 raises a lot of questions that are still unanswered. However, some studies point out that people's mobility, size of gatherings, rate of testing, and weather have a great impact on the COVID-19 spread. In this work, we first evaluate the correlation between meteorological parameters and COVID-19 cases using Spearman's rank correlation. Secondly, multi-output Gaussian processes (MOGP) are used to predict the daily confirmed COVID-19 cases by exploring its relationships with meteorological parameters. The number of daily reported COVID-19 cases, as well as, weather variables collected from March 9, 2020, to October 18, 2021, were used in the analysis. The weather variables considered in the analysis are the mean temperature, relative humidity, wind direction, insolation, precipitation, and wind speed. The predicting model was constructed exploiting the correlation between the data of the daily confirmed COVID-19 cases and data of the weather variables. The results show that a significant correlation between the daily confirmed COVID-19 cases was found with humidity, wind direction, wind speed, and insolation. These parameters are used to construct the predictive model using the Multi-Output Gaussian process (MOGP). Different combinations of the data of meteorological parameters together with the data of daily reported COVID-19 cases were used to derive different models. We found that the best predictor is obtained using the combination of Humidity and insolation. This model is then used to predict the daily confirmed COVID-19 cases knowing the humidity and Insolation.

Density measurement of liquid 22MnB5 by aerodynamic levitation.

This study is part of the general context of thermophysical characterization of liquid metals with an aerodynamic levitation device and laser heating. The density measurements vs temperature of pure and alloyed metals are determined during cooling of the sample. The temperature and shape of the sample are measured, respectively, with a bichromatic pyrometer and filmed by a high-speed camera. The sample visualization is performed by backlighting, which has been preferred to self-illumination. The post-treatment process consists in a binarisation of each recorded image, and then, an ellipse is fitted on the detected edge. The density is directly calculated with the ellipse volume and the sample weight. The good agreement of experimental results on pure metals with the literature validates the method. Then, an industrial steel of unknown liquid density is characterized from 1750 K to 2250 K.

Computational fluid dynamic analysis of physical forces playing a role in brain organoid cultures in two different multiplex platforms.

BACKGROUND: Organoid cultivation in suspension culture requires agitation at low shear stress to allow for nutrient diffusion, which preserves tissue structure. Multiplex systems for organoid cultivation have been proposed, but whether they meet similar shear stress parameters as the regularly used spinner flask and its correlation with the successful generation of brain organoids has not been determined. RESULTS: Here we used computational fluid dynamics (CFD) to simulate two multiplex culture conditions: steering plates on an orbital shaker and the use of a previously described bioreactor. The bioreactor had low speed and high shear stress regions that may affect cell aggregate growth, depending on volume, whereas the computed variables of the steering plates were closer to those of the spinning flask. CONCLUSION: Our protocol improves the initial steps of the standard brain organoid formation, and the produced organoids displayed regionalized brain structures, including retinal pigmented cells. Overall, we conclude that suspension culture on orbital steering plates is a cost-effective practical alternative to previously described platforms for the cultivation of brain organoids for research and multiplex testing.

Estimation of the temperature field in laser-induced hyperthermia experiments with a phantom.

BACKGROUND: One of the challenges faced during the hyperthermia treatment of cancer is to monitor the temperature distribution in the region of interest. The main objective of this work was to accurately estimate the transient temperature distribution in the heated region, by using a stochastic heat transfer model and temperature measurements. METHODS: Experiments involved the laser heating of a cylindrical phantom, partially loaded with iron oxide nanoparticles. The nanoparticles were manufactured and characterized in this work. The solution of the state estimation problem was obtained with an algorithm of the Particle Filter method, which allowed for simultaneous estimation of state variables and model parameters. Measurements of one single sensor were used for the estimation procedure, which is highly desirable for practical applications in order to avoid patient discomfort. RESULTS: Despite the large uncertainties assumed for the model parameters and for the coupled radiation-conduction model, discrepancies between estimated temperatures and internal measurements were smaller than 0.7 °C. In addition, the estimated fluence rate distribution was physically meaningful. Maximum discrepancies between the prior means and the estimated means were of 2% for thermal conductivity and heat transfer coefficient, 4% for the volumetric heat capacity and 3% for the irradiance. CONCLUSIONS: This article demonstrated that the Particle Filter method can be used to accurately predict the temperatures in regions where measurements are not available. The present technique has potential applications in hyperthermia treatments as an observer for active control strategies, as well as to plan personalized heating protocols.