Characterization of the Log-Normal Model for Received Signal Strength

Using the classical received signal strength (RSS)-distance log-normal model in wireless sensor network (WSN) applications poses a series of characteristic challenges derived from (a) the model’s structural limitations when it comes to explaining real observations, (b) the inherent hardware (HW) variability typically encountered in the low-cost nodes of WSNs, and (c) the inhomogeneity of the deployment environment. The main goal of this article is to better characterize how these factors impact the model parameters, an issue that has received little attention in the literature. For that matter, I qualitatively elaborate on their effects and interplay, and present the results of two quantitative empirical studies showing how much the parameters can vary depending on (a) the nodes used in the model identification and their position in the environment, and (b) the antenna directionality. I further show that the path loss exponent and the reference power can be highly correlated. In view of all this, I argue that real WSN deployments are better represented by random model parameters jointly accounting for HW and local environmental characteristics, rather than by deterministic independent ones. I further argue that taking this variability into account results in more realistic models and plausible results derived from their usage. The article contains example values of the mean and standard deviation of the model parameters, and of the correlation between the path loss exponent and the reference power. These can be used as a guideline in other studies. Given the sensitivity of localization algorithms to the proper model selection and identification demonstrated in the literature, the structural limitations of the log-normal model, the variability of its parameters and their interrelation are all relevant aspects that practitioners need to be aware of when devising optimal localization algorithms for real WSNs that rely on this popular model

Innocampus Explora: Nuevas formas de comunicar ciencia

[EN] Innocampus Explora aims to show the students of the Burjassot-Paterna campus of the Universitat de València how the different scientific degrees are interrelated. To do this we propose activities in which students and teachers work together to cover the interdisciplinary nature of science, both in everyday and professional issues. Throughout this course the activities developed relate to new ways to communicate science. With the development of this project we contribute to a transversal quality education for all the participating students.[ES] Innocampus Explora tiene por objetivo mostrar a los estudiantes del campus de Burjassot-Paterna de la Universitat de València cómo los diferentes grados científicos están interrelacionados. Para ello proponemos actividades en las que estudiantes y profesores trabajen conjuntamente para abarcar la interdisciplinariedad de la ciencia, tanto en temas cotidianos como profesionales. A lo largo de este curso las actividades desarrolladas se relacionan con las nuevas formas de comunicar ciencia. Con el desarrollo de este proyecto contribuimos a una formación transversal de calidad para todos los estudiantes participantes.Moros Gregorio, J.; Rodrigo Martínez, P.; Torres Piedras, C.; Montoya Martínez, L.; Peña Peña, J.; Pla Díaz, M.; Galarza Jiménez, P.... (2019). Innocampus Explora: Nuevas formas de comunicar ciencia. En IN-RED 2019. V Congreso de Innovación Educativa y Docencia en Red. Editorial Universitat Politècnica de València. 814-823. https://doi.org/10.4995/INRED2019.2019.10449OCS81482

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19

BackgroundWe previously reported that impaired type I IFN activity, due to inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity or to autoantibodies against type I IFN, account for 15-20% of cases of life-threatening COVID-19 in unvaccinated patients. Therefore, the determinants of life-threatening COVID-19 remain to be identified in similar to 80% of cases.MethodsWe report here a genome-wide rare variant burden association analysis in 3269 unvaccinated patients with life-threatening COVID-19, and 1373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. Among the 928 patients tested for autoantibodies against type I IFN, a quarter (234) were positive and were excluded.ResultsNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI 1.5-528.7, P=1.1x10(-4)) for biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70[95%CI 1.3-8.2], P=2.1x10(-4)). This enrichment was further strengthened by (1) adding the recently reported TYK2 and TLR7 COVID-19 loci, particularly under a recessive model (OR=19.65[95%CI 2.1-2635.4], P=3.4x10(-3)), and (2) considering as pLOF branchpoint variants with potentially strong impacts on splicing among the 15 loci (OR=4.40[9%CI 2.3-8.4], P=7.7x10(-8)). Finally, the patients with pLOF/bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10(-5)).ConclusionsRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old