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This work proposes a modification of a compartmental-type model based on the Susceptible-Exposed-Infected-Recovered (SEIR) scheme to describe the dynamics of contagion by Covid-19 in any part of the world, including also the numerical and analytical calculation of the mantissa and the resolution of a partial differential equation system. As an example, the different incidents that occurred in Singapore, Spain and Venezuela are analyzed to demonstrate the usefulness of the methodology developed in this work that can be seamlessly extended to other regions.

The goal of this paper is to show that it is possible to obtainan analytical solution of the life cycle of SARS-CoV-2 based on a deterministic model. To do this, this work solved a system of twelve differential equations where we obtained two points of equilibrium. The first critical point corresponds to the initial conditions regarding the virus entry into the cell without replication in the cell, and the second involved one is the process of the transcription and replication of the virus in the infected cell.

Open Science is the movement to make scientific research (including publications, data, physical samples, and software) and its dissemination accessible to all levels of society, be they researchers, amateurs, or professionals. [1] As a working model for scientific activity, Open Science has the potential to promote greater economic and social development in Latin America, favouring the efficient and safe utilization of the resources dedicated to funding science and facilitating the processes for knowledge transfer and dissemination in a region rife with challenges and inequities. The incorporation of transparent, collaborative, and open scientific practices also improves the quality of results, their impact, and their reproducibility. This transparency and accessibility strengthen the ability to translate scientific advances into innovations and allow the interaction of the scientific world with open innovation systems that need to be strengthened to facilitate the creation of wealth and strengthen productivity and the accumulation of human capital in our society. The draft text of the UNESCO Recommendation on Open Science highlights the five key pillars on which it is supported: open scientific knowledge, open science infrastructure, scientific communication, open engagement of societal actors, and open dialogue with other knowledge systems. [2] The current dimensions and characteristics of scientific activity are such that its productivity is contingent on certain key factors such as access to global collaboration networks, the effective management of data and scientific publications (e.g., the possibility of searching, accessing, interacting with, and reusing these data and the related scientific publications), computing power, connection speed, and the availability of shared research infrastructures. This collection of necessary infrastructures serves as the base for the digital ecosystem needed to support and promote Open Science. Latin America has a long tradition in this area that can provide the foundations to develop important leadership in the deployment and strengthening of these ecosystems, increasing our ability to incorporate ourselves into existing collaborations and to promote the development of new scientific collaborations. This document proposes a vision for this digital Open Science ecosystem that we must finish building in an orderly manner, analysing its components and interactions, while suggesting possible courses of action for its achievement.

Since its establishment in 1951, CIEMAT has been continuously boosting the use of computation as a research method, deploying innovative computing facilities. Hence, Vectorial, MPP, NUMA, and distributed architectures have been managed at CIEMAT, resultingin an extensive expertise on HPC maintainability as well as on the computational needs of the community related to international projects. Nowadays, the evolution of HPC hardware and software is progressively faster and implies a continuous challenge to increase their availability for the greater number of different initiatives supported. To address this task, the ICT team has been changing towards a flexible management model, with a look toward future acquisitions

The Latin American Giant Observatory (LAGO) is a distributed cosmic ray observatory at a regional scale in Latin America, by deploying a large network of Water Cherenkov detectors (WCD) and other astroparticle detectors in a wide range of latitudes from Antarctica to M\'exico, and altitudes from sea level to more than 5500 m a.s.l. Detectors telemetry, atmospherics conditions and flux of secondary particles at the ground are measured with extreme detail at each LAGO site by using our own-designed hardware and firmware (ACQUA). To combine and analyse all these data, LAGO developed ANNA, our data analysis framework. Additionally, ARTI, a complete framework of simulations designed to simulate the expected signals at our detectors coming from primary cosmic rays entering the Earth atmosphere, allowing a precise characterization of the sites in realistic atmospheric, geomagnetic and detector conditions. As the measured and synthetic data started to flow, we are facing challenging scenarios given a large amount of data emerging, performed on a diversity of detectors and computing architectures and e-infrastructures. These data need to be transferred, analyzed, catalogued, preserved, and provided for internal and public access and data-mining under an open e-science environment. In this work, we present the implementation of ARTI at the EOSC-Synergy cloud-based services as the first example of LAGO' frameworks that will follow the FAIR principles for provenance, data curation and re-using of data. For this, we calculate the flux of secondary particles expected in up to 1 week at detector level for all the 26 LAGO, and the 1-year flux of high energy secondaries expected at the ANDES Underground Laboratory and other sites. Therefore, we show how this development can help not only LAGO but other data-intensive cosmic rays observatories, muography experiments and underground laboratories., Comment: [30Dic21. No changes in the paper. Corrected mistake in ArXiv' metadata: swapping given name order: Juan Antonio Rubio-Montero -> Antonio Juan Rubio-Montero]

In March 2019 a Space Weather Laboratory was deployed at Marambio base in the Antarctic Peninsula. The main instrument installed was a cosmic ray detector based on water Cherenkov radiation. This detector is the first permanent Antarctic node of LAGO Collaboration (Latin American Giant Observatory). LAGO Project is an extended Astroparticle Observatory and it is mainly oriented to basic research in three branches of Astroparticle physics: the Extreme Universe,Space Weather phenomena, and Atmospheric Radiation at ground level. LAGO Space Weather program is directed towards the study of how the variations of the flux of secondary cosmic rays at ground level are linked with the heliospheric and geomagnetic modulations. Observations made during 2019 and 2020 are presented here. We analyze the effect of barometric pressure and local temperature in the count rate. The corrected count rate observed with the water Cherenkov detector is compared with observations of Oulu neutron monitor which has similar rigidity cut-off than the Marambio site.