Non-linear Autoregressive Neural Networks to Forecast Short-Term Solar Radiation for Photovoltaic Energy Predictions

Nowadays, green energy is considered as a viable solution to hinder CO2 emissions and greenhouse effects. Indeed, it is expected that Renewable Energy Sources (RES) will cover 40% of the total energy request by 2040. This will move forward decentralized and cooperative power distribution systems also called smart grids. Among RES, solar energy will play a crucial role. However, reliable models and tools are needed to forecast and estimate with a good accuracy the renewable energy production in short-term time periods. These tools will unlock new services for smart grid management. In this paper, we propose an innovative methodology for implementing two different non-linear autoregressive neural networks to forecast Global Horizontal Solar Irradiance (GHI) in short-term time periods (i.e. from future 15 to 120min). Both neural networks have been implemented, trained and validated exploiting a dataset consisting of four years of solar radiation values collected by a real weather station. We also present the experimental results discussing and comparing the accuracy of both neural networks. Then, the resulting GHI forecast is given as input to a Photovoltaic simulator to predict energy production in short-term time periods. Finally, we present the results of this Photovoltaic energy estimation discussing also their accuracy

A new physical mapping approach refines the sex-determining gene positions on the Silene latifolia Y-chromosome

Sex chromosomes are particularly interesting regions of the genome for both molecular genetics and evolutionary studies; yet, for most species, we lack basic information, such as the gene order along the chromosome. Because they lack recombination, Y-linked genes cannot be mapped genetically, leaving physical mapping as the only option for establishing the extent of synteny and homology with the X chromosome. Here, we developed a novel and general method for deletion mapping of non-recombining regions by solving "the travelling salesman problem", and evaluate its accuracy using simulated datasets. Unlike the existing radiation hybrid approach, this method allows us to combine deletion mutants from different experiments and sources. We applied our method to a set of newly generated deletion mutants in the dioecious plant Silene latifolia and refined the locations of the sex-determining loci on its Y chromosome map

Rivers as integration devices in cities

Background: As dynamic systems rivers and cities have been in interaction under changing relations over time, and the morphology of many cities has risen through a long and steady struggle between the city functions and the river system flowing inside. This makes river cities an interesting case to study how the presence of geographical features interacts with spatial morphology in the formation of cities. Methods: The basis of this research is enabled by utilizing a novel model for cross-city comparison presented by Hillier in his Santiago keynote in 2012 called a “star model”. This is done on large samples of cities investigating concurrent configurations, as well as how the properties in this star model react to specific forms of disturbance. Results: Results illustrate that the foreground network as identified through maximum choice values in cities are more vital to the structure of cities than the bridges. The overall syntactic structure tends to retain its character (degree of distributedness) and the location of its foreground network (which street segments constitute the foreground network) even when bridges are targeted. Furthermore, counter to the initial hypothesis, river cities tend to change less than non-river cities after targeted disturbance of the systems. Finally, the results show that while there is a statistical morphological difference between river cities and non-river cities, this difference is not directly explained through the bridges. Conclusion: Integrating space syntax with statistical and geospatial analysis can throw light on the way in which the properties of city networks and urban structure reflect the relative effect of rivers on the morphology of river cities. The paper, finally, contributes through offering one piece of a better perception of the structure of river-cities that can support strategies of river-cities interaction as well as enhance our knowledge on the constraints and limits to that interaction.QC 20160309</p