Innovation Diffusion and Biostimulant knowledge in Moroccan agriculture

Our study focused on Morocco investigating the dissemination of PBs amongst farmers belonging to the first pillar of the GMP, located in the Fès-Meknès region. As well as to assess how innovation adoption is influenced by the network of relationships that various farmers are involved in. We adopted an “ego network” approach to identify the primary stakeholders responsible for the diffusion of PBs. We collected data through “face-to-face” interviews with 80 farmers in April and May 2021. The data were processed with the aim of: 1) analysing the total number of main and specific topics discussed between egos and egos’ alters regarding the variation of some egos attributes; 2) analysing egos’ network characteristics using E-Net software, and 3) identifying the significant variables that influence farmers to access knowledge, use and reuse of PBs a Binary Logistic Regression (LR) was applied. The first result disclosed that the main PBs topics discussed were technical positioning, the need to use PBs, knowledge of PBs, and organic PBs. We noted that farmers have specific features: they have a high school diploma and a bachelor's degree; they are specialised in fruits and cereals farming, and they are managers and members of a professional organisation. The second result showed results of SNA: 1) PBs seem to become generally a common argument for farmers who have already exchanged fertiliser information with their alters; 2) we disclosed a moderate heterogeneity in the networks, farmers have access to information mainly from acquaintances and professionals, and 3) we revealed that networks have a relatively low density and alters are not tightly connected to each other. Farmers have a brokerage position in the networks controlling the flow of information about the PBs. LR revealed that both the farmers’ attributes and the networks’ characteristics influence growers to know, use and reuse PBs.

New knowledge, diagnostic and control tools to limit the impact of viral nervous necrosis (VNN) in the Mediterranean aquaculture sector

The role of aquaculture in satisfying the global seafood demand is essential. The expansion of the aquaculture sector and the intensification of its activities have enhanced the circulation of infectious agents. Among these, the nervous necrosis virus (NNV) represents the most widespread in the Mediterranean basin. The NNV is responsible for a severe neuropathological condition named viral nervous necrosis (VNN), impacting hugely on fish farms due to the serious disease-associated losses. Therefore, it is fundamental to develop new strategies to limit the impact of VNN in this area, interconnecting several aspects of disease management, diagnosis and prevention. This PhD thesis project, focusing on aquatic animals’ health, deals with these topics. The first two chapters expand the knowledge on VNN epidemiology and distribution, showing the possibility of interspecies transmission, persistent infections and a potential carrier role for invertebrates. The third study expands the horizon of VNN diagnosis, by developing a quick and affordable multiplex RT-PCR able to detect and simultaneously discriminate between NNV variants, reducing considerably the time and costs of genotyping. The fourth study, with the development of a fluorescent in situ hybridization technique and its application to aquatic vertebrates and invertebrates’ tissues, contributes to expand the knowledge on NNV distribution at cellular level, localizing also the replication site of the virus. Finally, the last study dealing with an in vitro evaluation of the NNV susceptibility to a commercial biocide, stress the importance to implement proper disinfectant procedures in fish farms to prevent virus spread and disease outbreaks.

Knowledge management in intelligent tutoring systems

In the last years, Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation processes are difficult tasks because they require a specialised skills on computer programming and knowledge engineering. In this thesis we discuss a general framework for knowledge management in an Intelligent Tutoring System and propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition that have to be used in the ITS during the tutoring process. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor. We design and implement a part of the proposed architecture, mainly the module of knowledge acquisition from examples based on first order data mining. We then show that the algorithm can be applied at least two different domains: first order algebra equation and some topics of C programming language. Finally we discuss the limitation of current approach and the possible improvements of the whole framework.

Sustainability indicators for environmental management and decision making

The general objective of this research is to explore theories and methodologies of sustainability indicators, environmental management and decision making disciplines with the operational purpose of producing scientific, robust and relevant information for supporting system understanding and decision making in real case studies. Several tools have been applied in order to increase the understanding of socio-ecological systems as well as providing relevant information on the choice between alternatives. These tools have always been applied having in mind the complexity of the issues and the uncertainty tied to the partial knowledge of the systems under study. Two case studies with specific application to performances measurement (environmental performances in the case of the K8 approach and sustainable development performances in the case of the EU Sustainable Development Strategy) and a case study about the selection of sustainable development indicators amongst Municipalities in Scotland, are discussed in the first part of the work. In the second part of the work, the common denominator among subjects consists in the application of spatial indices and indicators to address operational problems in land use management within the territory of the Ravenna province (Italy). The main conclusion of the thesis is that a ‘perfect’ methodological approach which always produces the best results in assessing sustainability performances does not exist. Rather, there is a pool of correct approaches answering different evaluation questions, to be used when methodologies fit the purpose of the analysis. For this reason, methodological limits and conceptual assumptions as well as consistency and transparency of the assessment, become the key factors for assessing the quality of the analysis.

Reputation, VC funding, and innovation: Evidence from the UK Micro and Nanotechnology sector

Startups’ contributions on economic growth have been widely realized. However, the funding gap is often a problem limiting startups’ development. To some extent, VC can be a means to solve this problem. VC is one of the optimal financial intermediaries for startups. Two streams of VC studies are focused in this dissertation: the criteria used by venture capitalists to evaluate startups and the effect of VC on innovation. First, although many criteria have been analyzed, the empirical assessment of the effect of startup reputation on VC funding has not been investigated. However, reputation is usually positively related with firm performance, which may affect VC funding. By analyzing reputation from the generalized visibility dimension and the generalized favorability dimension using a sample of 200 startups founded from 1995 operating in the UK MNT sector, we show that both the two dimensions of reputation have positive influence on the likelihood of receiving VC funding. We also find that management team heterogeneity positively influence the likelihood of receiving VC funding. Second, studies investigating the effect of venture capital on innovation have frequently resorted to patent data. However, innovation is a process leading from invention to successful commercialization, and while patents capture the upstream side of innovative performance, they poorly describe its downstream one. By reflecting the introduction of new products or services trademarks can complete the picture, but empirical studies on trademarking in startups are rare. Analyzing a sample of 192 startups founded from 1996 operating in the UK MNT sector, we find that VC funding has positive effect on the propensity to register trademarks, as well as on the number and breadth of trademarks.

Data management and data analysis in the large European projects GEHA (GEnetics of Healthy Aging) and NU-AGE (NUtrition and AGEing): a bioinformatic approach

The aging process is characterized by the progressive fitness decline experienced at all the levels of physiological organization, from single molecules up to the whole organism. Studies confirmed inflammaging, a chronic low-level inflammation, as a deeply intertwined partner of the aging process, which may provide the “common soil” upon which age-related diseases develop and flourish. Thus, albeit inflammation per se represents a physiological process, it can rapidly become detrimental if it goes out of control causing an excess of local and systemic inflammatory response, a striking risk factor for the elderly population. Developing interventions to counteract the establishment of this state is thus a top priority. Diet, among other factors, represents a good candidate to regulate inflammation. Building on top of this consideration, the EU project NU-AGE is now trying to assess if a Mediterranean diet, fortified for the elderly population needs, may help in modulating inflammaging. To do so, NU-AGE enrolled a total of 1250 subjects, half of which followed a 1-year long diet, and characterized them by mean of the most advanced –omics and non –omics analyses. The aim of this thesis was the development of a solid data management pipeline able to efficiently cope with the results of these assays, which are now flowing inside a centralized database, ready to be used to test the most disparate scientific hypotheses. At the same time, the work hereby described encompasses the data analysis of the GEHA project, which was focused on identifying the genetic determinants of longevity, with a particular focus on developing and applying a method for detecting epistatic interactions in human mtDNA. Eventually, in an effort to propel the adoption of NGS technologies in everyday pipeline, we developed a NGS variant calling pipeline devoted to solve all the sequencing-related issues of the mtDNA.