Acute stress regulates vasotocinergic and isotocinergic systems in the gilthead sea bream (Sparus aurata L.).

The hypothalamus-pituitary-interrenal axis is involved in stress response regulation. In addition, arginine vasotocin (AVT) and isotocin (IT) are also considered as important players in this stress regulation. The present study assessed, using the teleost gilthead sea bream (Sparus aurata) as a biological model, hypothalamic mRNA expression changes of AVT and IT and their receptors at hepatic level after an acute stress situation. Specimens were submitted to air for 3 min and place back in their respective tanks after that, being sampled at different times (15 min, 30 min, 1, 2, 4 and 8 hours post-stress) in order to study the time course response. Plasma cortisol values increased after few minutes post-exposure, decreasing during the experimental time while a metabolic reorganization occurred in both plasmatic and hepatic levels. At hypothalamic level, acute stress affects mRNA expression of AVT and IT precursors, as well as hepatic expression of their receptors, suggesting the involvement of both vasotocinergic and isotocinergic systems in the acute stress response. Our results demonstrate the activation and involvement of both endocrine pathways in the regulation of metabolic and stress systems of Sparus aurata, which is stated, at least, through changes in mRNA expression levels of these genes analysed.

Near Real-Time Detection Of Pipe Bursts in Water Distribution Systems

The research work presented in the thesis describes a new methodology for the automated near real-time detection of pipe bursts in Water Distribution Systems (WDSs). The methodology analyses the pressure/flow data gathered by means of SCADA systems in order to extract useful informations that go beyond the simple and usual monitoring type activities and/or regulatory reporting , enabling the water company to proactively manage the WDSs sections. The work has an interdisciplinary nature covering AI techniques and WDSs management processes such as data collection, manipulation and analysis for event detection. Indeed, the methodology makes use of (i) Artificial Neural Network (ANN) for the short-term forecasting of future pressure/flow signal values and (ii) Rule-based Model for bursts detection at sensor and district level. The results of applying the new methodology to a District Metered Area in Emilia- Romagna’s region, Italy have also been reported in the thesis. The results gathered illustrate how the methodology is capable to detect the aforementioned failure events in fast and reliable manner. The methodology guarantees the water companies to save water, energy, money and therefore enhance them to achieve higher levels of operational efficiency, a compliance with the current regulations and, last but not least, an improvement of customer service.