To gain a deep understanding of maintenance and repair planning, investigate the weak points of the distribution network, and discover unusual events, it is necessary to trace the shutdowns that occurred in the network. Many incidents happened due to the failure of thermal equipment in schools. On the other hand, the most important task of electricity distribution companies is to provide reliable and stable electricity, which minimal blackouts and standard voltage should accompany. This research uses seasonal time series and artificial neural network approaches to provide models to predict the failure rate of one of the equipment used in two areas covered by the greater Tehran electricity distribution company. These data were extracted weekly from April 2019 to March 2021 from the ENOX incident registration software. For this purpose, after pre-processing the data, the appropriate final model was presented with the help of Minitab and MATLAB software. Also, average air temperature, rainfall, and wind speed were selected as input variables for the neural network. The mean square error has been used to evaluate the proposed models’ error rate. The results show that the time series models performed better than the multi-layer perceptron neural network in predicting the failure rate of the target equipment and can be used to predict future periods.

The agronomic and oenological behavior of the Pinot noir grape variety was studied in relation to different rootstocks on the Agroscope estate in Leytron (VS): 3309 C, 5 BB, Fercal, 41 BMGt, Riparia Gloire, 420 AMGt, 101-14 MGt and 161-49 C. Rootstock primarily influenced vigor, speed of vine establishment, and mineral nutrition of the graft. Riparia Gloire, 41 BMGt, 420 AMGt and 161-49 C rootstocks were less vigorous and, for the last three, induced a lower nitrogen and potassium supply leading to the production of slightly more acidic wines. The less vigorous rootstocks and 101-14 MGt were slightly more sensitive to water stress.

Imaging technology plays a key role in guiding endovascular treatment of aortic aneurysm, especially in the complex thoracoabdominal aorta. The combination of high quality images with a sterile and functional environment in the surgical suite can reduce contrast and radiation exposure for both patient and operator, in addition to better outcomes. This presentation aims to describe the current use of this technique, combining angiotomography and intraoperative cone beam computed tomography, image “fusion” and intravascular ultrasound, to guide procedures and thus improve the intraoperative success rate and reduce the need for reoperation. On the other hand, a procedure is described to create customized 3D templates with the high-definition images of the patient’s arterial anatomy, which serve as specific guides for making fenestrated stents in the operating room. These customized fenestration templates could expand the number of patients with complex aneurysms treated minimally invasively.

Agroforestry holds the key in providing alternative economically viable livelihood development and to support mountainous farmers to adapt to climate change. Innovative agroforestry interventions integrating animal production, horticulture etc into cropping systems exist that can help farmers improve yields and build resilience for supporting livelihoods particularly among marginal communities. But, the lack of knowledge, technical know-how and other information among the farmers are major barriers in adoption of agroforestry. Millions of the farmers of mountainous regions are already wrestling with water scarcity, which would be more severe in climate change scenario. The Himalayan regions are have been considered to be highly sensitive to climate change. Indeed, Innovative agroforestry interventions have the potential to conserve natural resources, improve productivity and provide resilience to climate change. The present paper highlights the need for developing innovative agroforestry interventions to promote various alternate livelihood options through diversification, adoption of high yielding varieties and development of innovative products from forest resources.  Of these spice based agroforetry, silvi-medicinal systems, Van silk cultivation, bamboo and ringal cultivation  and development and use of farm resources based products like  bamboo based composite structures, Seabuckthorn herbal tea, Ghingaroo juice  (Crataegus crenulata) and incense products etc holds a promising potential to be explored as better options for future scenario.

It increased the demands on ground-water supplies that prolonged drought and improper maintenance of water resources. So it is necessary to evaluate ground-water resources in the hard rock terrain. In recent years, Remote-Sensing methods have been increasingly recognized as a means of obtaining crucial geoscientific data for both regional and site-specific investigations. This work aims to develop and apply integrated methods combining the information obtained by geo-hydrological field mapping and those obtained by analyzing multi-source remotely sensed data in a GIS environment for better understanding the Groundwater condition in hard rock terrain. In this study, digitally enhanced Landsat ETM+ data was used to extract information on geology, geomorphology. The Hill-Shading techniques are applied to SRTM DEM data to enhance terrain perspective views, and extract Geomorphological features and morphologically defined structures through the means of lineament analysis. A combination of Spectral information from Landsat ETM+ data plus spatial information from SRTM-DEM data is used to address the groundwater potential of alluvium, colluvium, and fractured crystalline rocks in the study area. The spatial distribution of groundwater potential zones shows regional patterns related to lithologies, lineaments, drainage systems, and landforms. High-yielding wells and springs are often related to large lineaments and corresponding structural features such as dykes. The results show that the combination of remote sensing, GIS, traditional fieldwork, and models provide a powerful tool for water resources assessment and management, and groundwater exploration planning.

Marine geological maps of the Campania region have been constructed both to a 1:25.000 and to a 1:10.000 scale in the frame of the research projects financed by the Italian National Geological Survey, focusing, in particular, on the Gulf of Naples (Southern Tyrrhenian Sea), a complex volcanic area where volcanic and sedimentary processes strongly interacted during the Late Quaternary and on the Cilento Promontory offshore. In this paper, the examples of the geological sheets n. 464 “Isola di Ischia” and n. 502 “Agropoli” have been studied. The integration of the geological maps with the seismo-stratigraphic setting of the study areas has also been performed based on the realization of interpreted seismic profiles, providing interesting data on the geological setting of the subsurface. The coastal geological sedimentation in the Ischia and Agropoli offshore has been studied in detail. The mapped geological units are represented by: i) the rocky units of the acoustic basement (volcanic and/or sedimentary); ii) the deposits of the littoral environment, including the deposits of submerged beach and the deposits of toe of coastal cliff; iii) the deposits of the inner shelf environment, including the inner shelf deposits and the bioclastic deposits; iv) the deposits of the outer shelf environment, including the clastic deposits and the bioclastic deposits; v) the lowstand system tract; vi) the Pleistocene relict marine units; vii) different volcanic units in Pleistocene age. The seismo-stratigraphic data, coupled with the sedimentological and environmental data provided by the geological maps, provided us with new insights on the geologic evolution of this area during the Late Quaternary.