Utilizzo di una rete protesica in polipropilene in supporto all'erniorrafia perineale tradizionale nel cane

Scopo del progetto di dottorato è stato quello di mettere a punto l’utilizzo di una tecnica alternativa, rispetto a quelle riportate in letteratura, per la risoluzione dell’ernia perineale nel cane. Tale tecnica si propone di risolvere il difetto mediante l’ausilio di una rete protesica in polipropilene in supporto all’erniorrafia perineale tradizionale, mediante sutura a punti staccati dei muscoli che costituiscono il diaframma pelvico. Questa procedura risulta meno invasiva per l’animale rispetto alla tecnica che in letteratura viene definita il gold standard, ovvero la trasposizione del muscolo otturatore interno (Shaughnessy and Monnet, 2015), ed altre tecniche traspositive, quali la trasposizione del muscolo semitendinoso (Morello et al., 2015) e del gluteo superficiale (Bellenger & Canfield, 2002), con tempi di recupero postoperatori più rapidi e una gestione più semplice da parte del proprietario, pur mantenendo eccellenti outcomes. La messa a punto di questa procedura nasce dalla necessità di trovare una tecnica semplice da eseguire, che determini una chiusura del diaframma pelvico tale da evitare la comparsa di recidive e minimizzare le complicazioni post-operatorie. L’intento del progetto è stato di combinare l’erniorrafia perineale tradizionale con l’utilizzo di reti protesiche così da ricostruire il diaframma pelvico con i muscoli deputati a svolgere tale compito e fornire, tramite la rete, un maggiore supporto alla rafia, evitando le trasposizioni muscolari che comporterebbero un intervento più demolitivo e un recupero più lento da parte del paziente. Sono stati inclusi nello studio 30 cani portatori di ernia perineale, per un totale di 50 ernie, trattati con l’intervento proposto dal progetto. Di ogni caso sono stati raccolti il segnalamento, l’anamnesi, le indagini diagnostiche e i successivi follow up post-operatori considerando le eventuali complicazioni o la comparsa di recidiva dell’ernia.

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management

Apple latent infection caused by Neofabraea alba: host-pathogen interaction and disease management Bull’s eye rot (BER) caused by Neofabraea alba is one of the most frequent and damaging latent infection occurring in stored pome fruits worldwide. Fruit infection occurs in the orchard, but disease symptoms appear only 3 months after harvest, during refrigerated storage. In Italy BER is particularly serious for late harvest apple cultivar as ‘Pink Lady™’. The purposes of this thesis were: i) Evaluate the influence of ‘Pink Lady™’ apple primary metabolites in N. alba quiescence ii) Evaluate the influence of pH in five different apple cultivars on BER susceptibility iii) To find out not chemical method to control N. alba infection iv) Identify some fungal volatile compounds in order to use them as N. alba infections markers. Results regarding the role of primary metabolites showed that chlorogenic, quinic and malic acid inhibit N. alba development. The study based on the evaluation of cultivar susceptibility, showed that Granny Smith was the most resistant apple cultivar among the varieties analyzed. Moreover, Granny Smith showed the lowest pH value from harvest until the end of storage, supporting the thesis that ambient pH could be involved in the interaction between N. alba and apple. In order to find out new technologies able to improve lenticel rot management, the application of a non-destructive device for the determination of chlorophyll content was applied. Results showed that fruit with higher chlorophyll content are less susceptible to BER, and molecular analyses comforted this result. Fruits with higher chlorophyll content showed up-regulation of PGIP and HCT, genes involved in plant defence. Through the application of PTR-MS and SPME GC-MS, 25 volatile organic compounds emitted by N. alba were identified. Among them, 16 molecules were identified as potential biomarkers.

Development of predictive energy management strategies for hybrid electric vehicles supported by connectivity

Nowadays, the spreading of the air pollution crisis enhanced by greenhouse gases emission is leading to the worsening of the global warming. In this context, the transportation sector plays a vital role, since it is responsible for a large part of carbon dioxide production. In order to address these issues, the present thesis deals with the development of advanced control strategies for the energy efficiency optimization of plug-in hybrid electric vehicles (PHEVs), supported by the prediction of future working conditions of the powertrain. In particular, a Dynamic Programming algorithm has been developed for the combined optimization of vehicle energy and battery thermal management. At this aim, the battery temperature and the battery cooling circuit control signal have been considered as an additional state and control variables, respectively. Moreover, an adaptive equivalent consumption minimization strategy (A-ECMS) has been modified to handle zero-emission zones, where engine propulsion is not allowed. Navigation data represent an essential element in the achievement of these tasks. With this aim, a novel simulation and testing environment has been developed during the PhD research activity, as an effective tool to retrieve routing information from map service providers via vehicle-to-everything connectivity. Comparisons between the developed and the reference strategies are made, as well, in order to assess their impact on the vehicle energy consumption. All the activities presented in this doctoral dissertation have been carried out at the Green Mobility Research Lab} (GMRL), a research center resulting from the partnership between the University of Bologna and FEV Italia s.r.l., which represents the industrial partner of the research project.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.