Climate and vegetation are variables of the physical space that have a dynamic and interdependent relationship. Flora modifies climatic elements and gives rise to a microclimate whose characterization is a function of regional climatic conditions and vegetation structure. The objective of this work was to compare the climatic variations (inside and outside) of the Caldén Forest in the Parque Luro Provincial Reserve. Temperature, relative humidity, wind speed, wind direction and precipitation data from two meteorological stations for 2012 were analyzed and statistically compared. The influence of the forest on climatic parameters was demonstrated and it was found that the greatest variations were in wind speed, daily temperature and precipitation.

In order to explore the influence of the ferroelectric surface on the structure and properties of semiconductor oxides, the growth of CdS nanocrystals was regulated and controlled by taking single-crystal perovskite PbTiO₃ nanosheets as the substrate through a simple hydrothermal method. Through composition design, a series of PbTiO₃-CdS nanocomposite materials with different loading concentrations were prepared, and their microstructure and photocatalytic properties were systematically analyzed. Studies show that in the prepared product, CdS nanoparticles selectively grow on the surfaces of PbTiO₃ nanosheets, and their morphology is affected by the exposed surfaces of PbTiO₃ nanosheets. There is a clear interface between the PbTiO₃ substrate and CdS nanoparticles. The concentration of the initial reactant and the time of hydrothermal reaction also significantly affect the crystal morphology of CdS. Photocatalysis studies have shown that the prepared PbTiO₃-CdS nanocomposite material has a significant degradation effect on 10 mg/L of Rhodamine B aqueous solution. The degradation efficiency rises with the increase of CdS loading concentration. When degrading 10 mg/L Rhodamine B aqueous solution, the PbTiO₃-CdS sample with a mass fraction of 3% can reach a degradation rate of 72% within 120 min.

Four alloys based on niobium and containing about 33wt.%Cr, 0.4wt.C and, in atomic content equivalent to the carbon one, Ta, Ti, Hf or Zr, were elaborated by classical foundry under inert atmosphere. Their as-cast microstructures were characterized by X-ray diffraction, electron microscopy, energy dispersion spectrometry and while their room temperature hardness was specified by Vickers indentation. The microstructures are in the four cases composed of a dendritic Nb-based solid solution and of an interdendritic NbCr₂ Laves phase. Despite the MC-former behavior of Ta, Ti, Hf and Zr usually observed in nickel or cobalt-based alloys, none of the four alloys contain MC carbides. Carbon is essentially visible as graphite flakes. These alloys are brittle at room temperature and hard to machine. Indentation shows that the Vickers hardness is very high, close to 1000HV_10kg. Indentation lead to crack propagation through the niobium phase and the Laves areas. Obviously no niobium-based alloys microstructurally similar to high performance MC-strengthened nickel-based and cobalt-based can be expected. However the high temperature mechanical and chemical properties of these alloys remain to be investigated.

In this study, we utilized a convolutional neural network (CNN) trained on microscopic images encompassing the SARS-CoV-2 virus, the protozoan parasite “plasmodium falciparum” (causing of malaria in humans), the bacterium “vibrio cholerae” (which produces the cholera disease) and non-infected samples (healthy persons) to effectively classify and predict epidemics. The findings showed promising results in both classification and prediction tasks. We quantitatively compared the obtained results by using CNN with those attained employing the support vector machine. Notably, the accuracy in prediction reached 97.5% when using convolutional neural network algorithms.