Secondary metabolites with ecologic and medicinal implications in Anthemis cretica subsp. petraea from Majella National Park

Anthemis cretica subsp. petraea (Ten.) Greuter is a plant belonging to the Asteraceae family and endemic of central Italy. In this paper, the first analysisof the ethanolic fraction of samples collected in the Majella National Park is reported. Seven compounds were isolated and identified namely parthenolide (1), 9α-acetoxyparthenolide (2), tamarixetin (3), 7-hydroxycoumarin (4), 4'-hydroxyacetophenone (5), leucanthemitol (conduritol F) (6),and proto-quercitol (7). Isolation of the compounds was achieved by means ofcolumn chromatography (CC), while their identification was achieved through spectroscopic and spectrometric techniques. The presence of these compounds is of great relevance. Compounds 1 and 2 are chemosystematic markers of the family, thus confirming the correct botanical classification of the species. Conversely, compounds 3, 5,and 7 were identified for the first time in the species and, instead, confirm the tendency of endemic entities to develop characteristic metabolite patterns in respect to cosmopolite species. Moreover, the presence of compounds 6 and 7 has ecologic implications and may be linked to this taxon’s adaption to dry environments. The production of these osmolytes may, in fact, represent the reason why this species is able to survive in extreme conditions of aridity. Lastly, from a medicinal standpoint, the isolated compounds are endowed with interesting biological activities and may justify, on a molecular base, the widespread traditional uses of the Anthemis species, as well as a basis for the use ofthe subspecies petraea

Isoflavones and other compounds from the roots of Iris marsica I. Ricci E Colas. Collected from Majella National Park, Italy

In this study, a phytochemical analysis was performed, for the first time, on Iris marsica I. Ricci e Colas. In particular, the attention was focused on the constituents of the roots. Twenty-one compounds were isolated by column chromatography and were analyzed/identified by NMR spectroscopy and mass spectrometry. They all own chemotaxonomic, ethno-pharmacological and nutraceutical relevance which allowed us to provide a phytochemical rationale, for the correct botanical classification of this species, for the employment of its roots in folk medicine like for all the other species belonging to the Iris genus and, lastly, for their further uses as food with important healthy benefits. All of these parts were broadly discussed about within the text

Understanding biodiversity responses to global change: Populations, communities, and species distributions

Human influence on global ecosystems is pervasive. To mitigate the effects of climate change and land use change, there is a need for developing a predictive understanding of how global biodiversity has been impacted. Identifying ecological traits of species associated with species that are vulnerable to, tolerant of, or benefitting from anthropogenic change can help predict ecological communities of the future. In this dissertation, I investigated the ecological impacts of global change at three levels: populations, communities, and range distributions.Population responses to anthropogenic change may be context dependent: climate change effects may be exacerbated by simultaneous land use changes, or intraspecific population response to climate change may depend on whether the population is in a warmer or colder portion of the species’ range. To address these questions, I modeled how forest fragmentation and climate change predict changes in population trends of 67 forest breeding bird species throughout the United States and Canada. Secondly, I determined whether ecological traits such as migratory strategy, habitat specialization, and thermal niche width can predict the susceptibility of species to the impacts of forest fragmentation and climate change. As a result of ongoing anthropogenic change, ecological communities have reshuffled. Understanding how communities are changing requires consideration of compositional shifts in species identity and abundance and how they are related to global change. I examined the compositional change in bird communities, comparing the relative contribution of land use and climate change variables from local to regional scales over the past 25 years in the United States and Canada. Additionally, I measured how species traits may explain turnover in response to climate and land use change. Impacts from local climate and land use change on populations and communities ultimately scale up to impact species range distributions. In response, species may undergo shifts in population size, sites occupied within their range, and shifts in range extent. Niche breadth on various axes may influence the direction and magnitude of these responses. Using annual survey data on breeding birds over forty years, I characterized the relative importance of niche breadth in explaining changes in species range responses.Doctor of Philosoph

GloNets: Globally Connected Neural Networks

Deep learning architectures suffer from depth-related performance degradation, limiting the effective depth of neural networks. Approaches like ResNet are able to mitigate this, but they do not completely eliminate the problem. We introduce Globally Connected Neural Networks (GloNet), a novel architecture overcoming depth-related issues, designed to be superimposed on any model, enhancing its depth without increasing complexity or reducing performance. With GloNet, the network's head uniformly receives information from all parts of the network, regardless of their level of abstraction. This enables GloNet to self-regulate information flow during training, reducing the influence of less effective deeper layers, and allowing for stable training irrespective of network depth. This paper details GloNet's design, its theoretical basis, and a comparison with existing similar architectures. Experiments show GloNet's self-regulation ability and resilience to depth-related learning challenges, like performance degradation. Our findings suggest GloNet as a strong alternative to traditional architectures like ResNets