Frequency planning optimisation in real mobile networks

Due to the annual increase of cellular subscribers, there is a growing interest by the network operators, in how to deploy the network infrastructure to achieve maximum capacity. A key point is the channel or frequency assignment, which implies efficiently assigning frequencies from a limited set, to each cell, while satisfying the electromagnetic compatibility constraints.Peer ReviewedPostprint (published version

Improved tabu search and simulated annealing methods for nonlinear data assimilation

Nonlinear data assimilation can be a very challenging task. Four local search methods are proposed for nonlinear data assimilation in this paper. The methods work as follows: At each iteration, the observation operator is linearized around the current solution, and a gradient approximation of the three dimensional variational (3D-Var) cost function is obtained. Then, samples along potential steepest descent directions of the 3D-Var cost function are generated, and the acceptance/rejection criteria for such samples are similar to those proposed by the Tabu Search and the Simulated Annealing framework. In addition, such samples can be drawn within certain sub-spaces so as to reduce the computational effort of computing search directions. Once a posterior mode is estimated, matrix-free ensemble Kalman filter approaches can be implemented to estimate posterior members. Furthermore, the convergence of the proposed methods is theoretically proven based on the necessary assumptions and conditions. Numerical experiments have been performed by using the Lorenz-96 model. The numerical results show that the cost function values on average can be reduced by several orders of magnitudes by using the proposed methods. Even more, the proposed methods can converge faster to posterior modes when sub-space approximations are employed to reduce the computational efforts among iterations

The Microbially Extended Phenotype of Plants, a Keystone against Abiotic Stress

[EN] Background: Climate change affects every region across the globe with heterogeneous effects on local temperatures and precipitation patterns. In plants, sessile organisms, climate change imposes more drastic effects leading to loss of yield or even death. However, plants establish mutualistic interactions with microorganisms that boost plant tolerance against abiotic stresses or strengthen the plant immune system against pathogens, thus, enhancing their survival and fitness. Moreover, in the wild, microbial endophytes provide important ecosystem services. Purpose and scope: Little we know about the mechanisms of response against the adverse effects of climate change on natural populations of wild plants and even less about the potential role played by microbial biostimulants. In this article, we review the effects of biostimulants on plant responses against abiotic stresses, with a particular focus on the role of mycorrhizas and leaf endophytes. Results: We have reviewed the effects of the main abiotic stresses in plants, the mechanisms that plants use to face these abiotic challenges, and the interaction plant-biostimulant-abiotic stress, highlighting the primary responses and parameters to evaluate different plant responses. Conclusion: Abiotic stresses can check the phenotypic plasticity of plants and also trigger a complex and heterogeneous array of responses to face different abiotic stresses, and beneficial microorganisms do play an essential role in enhancing such responses. Our laboratory has initiated a project to characterise microbial populations associated with plants from wild areas and analyse their potential role in aiding the plants to cope with abiotic stresses.This study was supported by a Maria Zambrano distinguished researcher contract to MXR-G, and funded by both the Ministerio de Universidades (Gobierno de Espana) and the Next generation EU. The authors have no competing financial interests.Ruiz-González, MX.; Vicente, O. (2022). The Microbially Extended Phenotype of Plants, a Keystone against Abiotic Stress. The Eurobiotech Journal. 6(4):174-182. https://doi.org/10.2478/ebtj-2022-00171741826