Nuevos métodos de verificación de las predicciones numéricas de precipitación: el método SAL aplicado en la mesoescala

Ponencia presentada en: XXXII Jornadas Científicas de la AME y el XIII Encuentro Hispano Luso de Meteorología celebrado en Alcobendas (Madrid), del 28 al 30 de mayo de 2012

A semantic autonomous video surveillance system for dense camera networks in smart cities

Producción CientíficaThis paper presents a proposal of an intelligent video surveillance system able to detect and identify abnormal and alarming situations by analyzing object movement. The system is designed to minimize video processing and transmission, thus allowing a large number of cameras to be deployed on the system, and therefore making it suitable for its usage as an integrated safety and security solution in Smart Cities. Alarm detection is performed on the basis of parameters of the moving objects and their trajectories, and is performed using semantic reasoning and ontologies. This means that the system employs a high-level conceptual language easy to understand for human operators, capable of raising enriched alarms with descriptions of what is happening on the image, and to automate reactions to them such as alerting the appropriate emergency services using the Smart City safety network

Specification of the Drosophila Orcokinin A neurons by combinatorial coding

This is a post-peer-review, pre-copyedit version of an article published in Cell and Tissue Research. The final authenticated version is available online at: http://dx.doi.org10.1007/s00441-022-03721-xThe central nervous system contains a daunting number of different cell types. Understanding how each cell acquires its fate remains a major challenge for neurobiology. The developing embryonic ventral nerve cord (VNC) of Drosophila melanogaster has been a powerful model system for unraveling the basic principles of cell fate specification. This pertains specifically to neuropeptide neurons, which typically are stereotypically generated in discrete subsets, allowing for unambiguous single-cell resolution in different genetic contexts. Here, we study the specification of the OrcoA-LA neurons, characterized by the expression of the neuropeptide Orcokinin A and located laterally in the A1-A5 abdominal segments of the VNC. We identified the progenitor neuroblast (NB; NB5-3) and the temporal window (castor/grainyhead) that generate the OrcoA-LA neurons. We also describe the role of the Ubx, abd-A, and Abd-B Hox genes in the segment-specific generation of these neurons. Additionally, our results indicate that the OrcoA-LA neurons are “Notch Off” cells, and neither programmed cell death nor the BMP pathway appears to be involved in their specification. Finally, we performed a targeted genetic screen of 485 genes known to be expressed in the CNS and identified nab, vg, and tsh as crucial determinists for OrcoA-LA neurons. This work provides a new neuropeptidergic model that will allow for addressing new questions related to neuronal specification mechanisms in the futureThis work was supported by a grant from the MINECO (BFU2016-78327-P) to J.B-S and The University of Queensland, Australia, to S

A User-Centric Service Creation Approach for Next Generation Networks

The architecture and technologies for the Next Generation Networks are well known. The service provision approach is not so clear though. While the Telecommunications killer application still remains to be found, new competitors in the new all-IP world threaten the traditional business models of telcos by providing their services directly to the operators' customers. An innovative paradigm has recently come about in the Internet which allows users to create and share their own services from the composition of other services. User-centric service creation environments improve the service offering with profitable, value-added services faster and cheaper than ever before. This paper presents the initial results of a research project that applies the user-centric approach to the creative combination of Web and network services over Next Generation Networks

Temperature and relative humidity estimation and prediction in the tobacco drying process using artificial neural networks

Producción CientíficaThis paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.Centro para el Desarrollo Tecnológico Industrial (CDTI), proyecto "Mejora de la competitividad del sector del tabaco en Extremadura: nuevos procesos y productos" (under project IDI-20100986)Junta de Castilla y León, financiado por el Plan Regional de Proyectos de Investigación (proyecto VA034A10-2

Application of mixed reality to ultrasound-guided femoral arterial cannulation during real-time practice in cardiac interventions

Producción CientíficaMixed reality opens interesting possibilities as it allows physicians to interact with both, the real physical and the virtual computer-generated environment and objects, in a powerful way. A mixed reality system, based in the HoloLens 2 glasses, has been developed to assist cardiologists in a quite complex interventional procedure: the ultrasound-guided femoral arterial cannulations, during real-time practice in interventional cardiology. The system is divided into two modules, the transmitter module, responsible for sending medical images to HoloLens 2 glasses, and the receiver module, hosted in the HoloLens 2, which renders those medical images, allowing the practitioner to watch and manage them in a 3D environment. The system has been successfully used, between November 2021 and August 2022, in up to 9 interventions by 2 different practitioners, in a large public hospital in central Spain. The practitioners using the system confirmed it as easy to use, reliable, real-time, reachable, and cost-effective, allowing a reduction of operating times, a better control of typical errors associated to the interventional procedure, and opening the possibility to use the medical imagery produced in ubiquitous e-learning. These strengths and opportunities were only nuanced by the risk of potential medical complications emerging from system malfunction or operator errors when using the system (e.g., unexpected momentary lag). In summary, the proposed system can be taken as a realistic proof of concept of how mixed reality technologies can support practitioners when performing interventional and surgical procedures during real-time daily practice.Junta de Castilla y León - Gerencia Regional de Salud (SACyL) (grant number GRS 2275/A/2020)Instituto de Salud Carlos III (grant number DTS21/00158)Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

Dachshund acts with Abdominal-B to trigger programmed cell death in the Drosophila central nervous system at the frontiers of Abd-B expression

A striking feature of the nervous system pertains to the appearance of different neural cell subtypes at different axial levels. Studies in the Drosophila central nervous system reveal that one mechanism underlying such segmental differences pertains to the segment-specific removal of cells by programmed cell death (PCD). One group of genes involved in segment-specific PCD is the Hox homeotic genes. However, while segment-specific PCD is highly precise, Hox gene expression is evident in gradients, raising the issue of how the Hox gene function is precisely gated to trigger PCD in specific segments at the outer limits of Hox expression. The Drosophila Va neurons are initially generated in all nerve cord segments but removed by PCD in posterior segments. Va PCD is triggered by the posteriorly expressed Hox gene Abdominal-B (Abd-B). However, Va PCD is highly reproducible despite exceedingly weak Abd-B expression in the anterior frontiers of its expression. Here, we found that the transcriptional cofactor Dachshund supports Abd-B-mediated PCD in its anterior domain. In vivo bimolecular fluorescence complementation analysis lends support to the idea that the Dachshund/Abd-B interplay may involve physical interactions. These findings provide an example of how combinatorial codes of transcription factors ensure precision in Hox-mediated PCD in specific segments at the outer limits of Hox expressionMinisterio de Ciencia y Educación, Grant/Award Number: PID2019-110952GB-I0

A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants

[EN] Recent technological advances in the power generation and information technologies areas are helping to change the modern electricity supply system in order to comply with higher energy efficiency and sustainability standards. Smart grids are an emerging trend that introduce intelligence in the power grid to optimize resource usage. In order for this intelligence to be effective, it is necessary to retrieve enough information about the grid operation together with other context data such as environmental variables, and intelligently modify the behavior of the network elements accordingly. This article presents a multi-agent system model for virtual power plants, a new power plant concept in which generation no longer occurs in big installations, but is the result of the cooperation of smaller and more intelligent elements. The proposed model is not only focused on the management of the different elements, but includes a set of agents embedded with artificial neural networks for collaborative forecasting of disaggregated energy demand of domestic end users, the results of which are also shown in this article.We would like to express our thanks to the coordinators of the project OptimaGrid for the information provided on MAS-based micro-grids, and the creators of a MAS INGENIAS methodology. This article has been partially funded by the project SociAAL (Social Ambient Assisted Living), supported by Spanish Ministry for Economy and Competitiveness, with grant TIN2011-28335-C02-01, by the Programa de Creacion y Consolidacion de Grupos de Investigacion UCM-Banco Santander for the group number 921354 (GRASIA group).Hernández, L.; Baladrón Zorita, C.; Aguiar Pérez, JM.; Carro, B.; Sanchez-Esguevillas, A.; Lloret, J.; Chinarro, D.... (2013). A Multi-Agent System Architecture for Smart Grid Management and Forecasting of Energy Demand in Virtual Power Plants. IEEE Communications Magazine. 51(1):106-113. https://doi.org/10.1109/MCOM.2013.6400446S10611351

An intelligent surveillance platform for large metropolitan areas with dense sensor deployment

Producción CientíficaThis paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units while keeping monetary and resource/bandwidth costs at a minimum, the surveillance platform is based on the usage of inexpensive visual sensors which apply efficient motion detection and tracking algorithms to transform the video signal in a set of motion parameters. In order to automate the analysis of the myriad of data streams generated by the visual sensors, the platform’s control center includes an alarm detection engine which comprises three components applying three different Artificial Intelligence strategies in parallel. These strategies are generic, domain-independent approaches which are able to operate in several domains (traffic surveillance, vandalism prevention, perimeter security, etc.). The architecture is completed with a versatile communication network which facilitates data collection from the visual sensors and alarm and video stream distribution towards the emergency teams. The resulting surveillance system is extremely suitable for its deployment in metropolitan areas, smart cities, and large facilities, mainly because cheap visual sensors and autonomous alarm detection facilitate dense sensor network deployments for wide and detailed coveraMinisterio de Industria, Turismo y Comercio and the Fondo de Desarrollo Regional (FEDER) and the Israeli Chief Scientist Research Grant 43660 inside the European Eureka Celtic project HuSIMS (TSI-020400-2010-102)

Service Discovery Suite for User-Centric Service Creation

Two emerging trends are impacting the CIT world: service orientation and user centricity. The OPUCE project aims at developing a platform to mix together both philosophies into an environment where end-users are capable of building highly personalized services integrating Information Technologies and communication capabilities. Such a platform has the potential to become an open marketplace in order for telco operators to implement innovative business models, and as such imposes specific requirements over the discovery mechanisms to help users locate services fitting their needs. This paper presents the discovery suite implemented in the OPUCE platform