The coronavirus disease 2019 (COVID-19) pandemic is considered a public health emergency of international concern. The 2019 novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused this pandemic has spread rapidly to over 200 countries, and has drastically affected public health and the economies of states at unprecedented levels. In this context, efforts around the world are focusing on solving this problem in several directions of research, by: (i) exploring the origin and evolution of the phylogeny of the SARS-CoV-2 viral genome; (ii) developing nanobiosensors that could be highly effective in detecting the new coronavirus; (iii) finding effective treatments for COVID-19; and (iv) working on vaccine development. In this paper, an overview of the progress made in the development of nanobiosensors for the detection of human coronaviruses (SARS-CoV, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV) is presented, along with specific techniques for modifying the surface of nanobiosensors. The newest detection methods of the influenza virus responsible for acute respiratory syndrome were compared with conventional methods, highlighting the newest trends in diagnostics, applications, and challenges of SARS-CoV-2 (COVID-19 causative virus) nanobiosensors.

This paper presents neural network based models for the prediction of propagation path loss in urban environment. The neural networks are designed separately for line-ofsight (LOS) and non-line-of-sight (NLOS) cases. The performance of the neural models is compared to that of the COST231-Walfisch-lkegami model, the WaGschBertoni model and the single regression model, based on the absolute mean error, standard deviation and the root mean squared error between predicted and measured values.

In this paper is studied the hot plastic deformability (plasticity and resistance to deformation) for the low-alloyed steel of heat treatment for mechanical engineering in two ways: compression and tension. Groups of low alloy steels is very important in terms of quality and quantity, the products of these steels have developed internal and external market. The plasticity variation were plotted with the temperature and it was established that the plasticity of the steel increases in the range 700-12000C, then decreases as a result of the firing of the grain boundaries, for the bars obtained from ingot and continuous cast blown it was noticed that the plasticity values are very close. Deformation resistance decreases as the temperature increases. The finest granulation was obtained for a final plastic deformation temperature of 8000C and a minimum degree of deformation of 45%.

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The application of plastic materials in various areas of contemporary technology can lead to improvements in the function, quality and performance of engineering components. When determining the field of use of these materials, it is necessary, in addition to knowing the physical and mechanical properties, information about their behavior in service under the influence of the operating and environment factors. Compared to metallic or ceramic materials, polymeric materials exhibit a wide range of scratching deformations in a narrow range of pressure, speed, temperature, lubrication etc.In this paper is proposed a penetration model of a flat surface (from polymeric material) with a rigid conical penetrator and the determination of the flat surface material response mode. The penetration method corresponds to the deformation produced by the asperities in practice.The comparison of the experimental and the theoretical results confirms the veracity of the model and corresponds with many of the experimental results obtained in the specialized works.Based on the proposed models, maps can be produced, that can illustrate the response of any polymeric surface in contact with an abrasive material.

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