Approccio multi-scala per la definizione delle caratteristiche idrogeologiche degli acquiferi fessurati

This works aims at applying a methodology to characterize the fracture network in granitic rocks in a pilot area on the South of Sardinia. The fracture network has been characterized through a multiscale approach using digital photogrammetry and field measurements of fracture parameters. The digital photogrammetry allowed to generate a digital elevation model (DEM) of high resolution (5m), orthophotos and then the digitalization of over 900 lineaments. The orientation and the length were calculated for the lineaments. The fractures field survey provided complementary information regarding to the orientation, the aperture, the spacing and the roughness of the fractures

Deep learning based pipelines for Alzheimer's disease diagnosis: A comparative study and a novel deep-ensemble method

Background: Alzheimer's disease is a chronic neurodegenerative disease that destroys brain cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are not yet fully understood, and there is no curative treatment. However, neuroimaging tools currently offer help in clinical diagnosis, and, recently, deep learning methods have rapidly become a key methodology applied to these tools. The reason is that they require little or no image preprocessing and can automatically infer an optimal representation of the data from raw images without requiring prior feature selection, resulting in a more objective and less biased process. However, training a reliable model is challenging due to the significant differences in brain image types. Methods: We aim to contribute to the research and study of Alzheimer's disease through computer-aided diagnosis (CAD) by comparing different deep learning models. In this work, there are three main objectives: i) to present a fully automated deep-ensemble approach for dementia-level classification from brain images, ii) to compare different deep learning architectures to obtain the most suitable one for the task, and (iii) evaluate the robustness of the proposed strategy in a deep learning framework to detect Alzheimer's disease and recognise different levels of dementia. The proposed approach is specifically designed to be potential support for clinical care based on patients' brain images. Results: Our strategy was developed and tested on three MRI and one fMRI public datasets with heterogeneous characteristics. By performing a comprehensive analysis of binary classification (Alzheimer's disease status or not) and multiclass classification (recognising different levels of dementia), the proposed approach can exceed state of the art in both tasks, reaching an accuracy of 98.51% in the binary case, and 98.67% in the multiclass case averaged over the four different data sets. Conclusion: We strongly believe that integrating the proposed deep-ensemble approach will result in robust and reliable CAD systems, considering the numerous cross-dataset experiments performed. Being tested on MRIs and fMRIs, our strategy can be easily extended to other imaging techniques. In conclusion, we found that our deep-ensemble strategy could be efficiently applied for this task with a considerable potential benefit for patient management

Structural geological study for hydrogeological survey of the area consisting between the regions of Batna and Biskra (NE Algeria) [Studio geologico strutturale per indagini idrogeologiche dell'area compresa tra le regioni di Batna e Biskra (NE Algeria)]

To infer the hydrogeological features of an area about 300 square km wide in the Alpine Nappe, we present a 3D geological model of a zone in Alpine Nappe in NE Algeria (between the "Wilaya" of Batna and "Wilaya" of Biskra), where field mapping is nowadays impossible. Therefore a preliminary geological model was built based on previous maps (both geological and hydrogeological), subsurface data (well-logs), photo-interpretation and remote sensing. The area is characterized by the superposition of several folding events from Middle Eocene to Pleistocene that strongly influence the geometry of the main aquifers

Geological 3D model for the design of artificial recharge facilities into the Oued Biskra inféro-flux aquifer (NE Algeria)

North Africa arid regions of Maghreb suffers of dry climatic conditions with erratic behaviour of rainfall in which most part of available superficial waters is lost, providing scarce benefits for households living in villages of such semidesertic areas. Oued Biskra watershed (NE Algeria) is one of two study areas implemented in WADIS-MAR demonstration project (www.wadis-mar.eu) founded by European Commission through SWIM Programme (www.swim-sm.eu). North to the city of Biskra the river bed is imposed on Mio-Plio-Quaternary deposits and the alluvial sediments constitute a phreatic aquifer called inféro-flux (AA.VV., 1980). The aquifer is overexploited for drinking water and irrigation purposes, therefore the aquifer artificial recharge systems were designed in order to increase the sustainable yield of the aquifer and to store water underground when available and to employ it when needed. Using the software Move (Midland Valley Exploration Ltd.) a preliminary 3D hydro-geological model, based on geological, hydro-geological and sub-surface data, a 30 meters Aster DEM and photo-interpretation, was made to better understand the hydro-geological setting of the inféro-flux aquifer. This study investigated 4 kilometres of the oued Biskra. Through 28 geological cross sections orthogonal to the river bed the 3D model of the alluvial aquifer was reconstructed. It is made up by alluvial deposits, mainly sand and gravel, with thickness that increases from 20 metres in the North to 80 metres in the South. In order to estimate the storativity, from sub-surface data we inferred an effective porosity value of 30%. Based on the hydro-geological model an aquifer artificial recharge system was designed, consists by: · 6 dry recharge wells: they will have a diameter ranging from 2 to 3 meters and a depth from 5 to 10, according to local setting of wadi bed and alluvial aquifer. From each well, three buried drainage pipes will depart to maximize the infiltration rates; · 6 recharge trenches: they will be arrange perpendicular to the flow direction in cascade in a v-shape manner; · 3 recharge basin: they will permit the infiltration of excess water conducted by buried pipes from the recharge wells. Its shape will be built as an inverted pyramid and built in slightly higher areas of the wadi bed to be sure to not being affected by superficial flow. Groundwater pollution will be prevent using a “reactive layer”, a palm leaves compost with clay and sand to improve the quality of infiltrating water, that will work as a filter. The evaluation of the artificial recharge yield according the above described system, considering the occurrence of water along the oued for 20 days per year, is 1.5 million cubic metres per year