Short term traffic congestion forecasting using hybrid metaheuristics and rule based methods a comparative study

In this paper, a comparative study between a hybrid technique that combines a Genetic Algorithm with a Cross Entropy method to optimize Fuzzy Rule-Based Systems, and literature techniques is presented. These techniques are applied to traffic congestion datasets in order to determine their performance in this area. Different types of datasets have been chosen. The used time horizons are 5, 15 and 30 min. Results show that the hybrid technique improves those results obtained by the techniques of the state of the art. In this way, the performed experimentation shows the competitiveness of the proposal in this area of application. Document type: Part of book or chapter of boo

Cytoneme-Mediated Delivery of Hedgehog Regulates the Expression of Bone Morphogenetic Proteins to Maintain Germline Stem Cells in Drosophila

Genetic manipulation of the germline stem cell niche in Drosophila ovaries reveals that support cells ensure the maintenance of stem cells by modulating the spread of Hedgehog within the niche

STAT Is an Essential Activator of the Zygotic Genome in the Early Drosophila Embryo

In many organisms, transcription of the zygotic genome begins during the maternal-to-zygotic transition (MZT), which is characterized by a dramatic increase in global transcriptional activities and coincides with embryonic stem cell differentiation. In Drosophila, it has been shown that maternal morphogen gradients and ubiquitously distributed general transcription factors may cooperate to upregulate zygotic genes that are essential for pattern formation in the early embryo. Here, we show that Drosophila STAT (STAT92E) functions as a general transcription factor that, together with the transcription factor Zelda, induces transcription of a large number of early-transcribed zygotic genes during the MZT. STAT92E is present in the early embryo as a maternal product and is active around the MZT. DNA–binding motifs for STAT and Zelda are highly enriched in promoters of early zygotic genes but not in housekeeping genes. Loss of Stat92E in the early embryo, similarly to loss of zelda, preferentially down-regulates early zygotic genes important for pattern formation. We further show that STAT92E and Zelda synergistically regulate transcription. We conclude that STAT92E, in conjunction with Zelda, plays an important role in transcription of the zygotic genome at the onset of embryonic development

Drosophila TIEG Is a Modulator of Different Signalling Pathways Involved in Wing Patterning and Cell Proliferation

Acquisition of a final shape and size during organ development requires a regulated program of growth and patterning controlled by a complex genetic network of signalling molecules that must be coordinated to provide positional information to each cell within the corresponding organ or tissue. The mechanism by which all these signals are coordinated to yield a final response is not well understood. Here, I have characterized the Drosophila ortholog of the human TGF-β Inducible Early Gene 1 (dTIEG). TIEG are zinc-finger proteins that belong to the Krüppel-like factor (KLF) family and were initially identified in human osteoblasts and pancreatic tumor cells for the ability to enhance TGF-β response. Using the developing wing of Drosophila as “in vivo” model, the dTIEG function has been studied in the control of cell proliferation and patterning. These results show that dTIEG can modulate Dpp signalling. Furthermore, dTIEG also regulates the activity of JAK/STAT pathway suggesting a conserved role of TIEG proteins as positive regulators of TGF-β signalling and as mediators of the crosstalk between signalling pathways acting in a same cellular context

Application of Artificial Intelligence Techniques to Traffic Prediction and Route Planning, the vision of TIMON project

TIMON is an European research project under the Horizon 2020 programme. The main objective of this project is to provide real-time services through a web based platform and a mobile APP for drivers, Vulnerable Road Users (VRUs) and businesses. These services will contribute to increasing drivers and VRUs assistance and safety. To provide these services, one of the core technologies developed inside TIMON will be the design and development of Artificial Intelligence (AI) techniques for traffic prediction and route planning. The DeustoTech-Mobility research group is in charge of this part of the project. The objective of this technical paper is to describe the approach followed in TIMON to develop traffic congestion prediction and route planning services based on AI techniques and the progress done so far. Additionally, the deployment and the result obtained in the first test done is also detailed in this study