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Multi-drug resistant Klebsiella pneumoniae strains circulating in hospital setting
Carbapenems resistant Enterobacteriaceae infections are increasing worldwide representing an emerging public health problem. The application of phylogenetic and phylodynamic analyses to bacterial whole genome sequencing (WGS) data have become essential in epidemiological surveillance of MDR pathogens to discern outbreak from non-outbreak strains in both community and hospital settings. In this study, K. pneumoniae strains circulating within different wards of university hospital were collected and WGS applied. Moreover a microbiological surveillance on duedonoscopes was performed to evaluate their reprocessing. The aim was to infer the origin and the spread of K. pneumoniae nosocomial strains and to clarify the epidemiological transmission as so as the eventual reservoir in the hospital setting supporting the epidemiological surveillance and infections control strategies. Winner of the Competition “Prize for PhD Thesis 2020” arranged by Sapienza University Press.
Simulations of RF Beam Manipulations Including Intensity Effects for CERN PSB and SPS Upgrades
The LIU program at CERN is of paramount importance at international level. The program foresees a significant upgrade of the LHC injector chain to increase the luminosity of the LHC beam by a factor of ten after 2024, when the HL-LHC era will start. This thesis deals with longitudinal beam dynamics studies for two LHC injectors (PSB and SPS), the main goal being the analysis of beam instabilities in the HL-LHC scenario.
Towards Recognizing New Semantic Concepts in New Visual Domains
Despite being the leading paradigm in computer vision, deep neural networks are inherently limited by the visual and semantic information contained in their training set. In this thesis, we aim to design deep models operating with previously unseen visual domains and semantic concepts. We first describe different solutions for generalizing to new visual domains, applying variants of normalization layers to multiple challenging settings e.g. where new domain data is not available but arrives online or is described by metadata. In the second part, we incorporate new semantic concepts into pretrained deep models. We propose specific solutions for different problems such as multi-task/incremental learning and open-world recognition. Finally, we merge the two challenges: given images of multiple domains and categories, can we recognize unseen concepts in unseen domains? We propose an approach that is the first, promising step, towards solving this problem. Winner of the Competition “Prize for PhD Thesis 2020” arranged by Sapienza University Press.
Trauma Narratives in Italian and Transnational Women’s Writing
This edited volume is the first to propose new readings of Italian and transnational female-authored texts through the lens of Trauma Studies. Illuminating a space that has so far been left in the shadows, Trauma Narratives in Italian and Transnational Women’s Writing provides new insights into how the trope of trauma shapes the narrative, temporal and linguistic dimension of these works. The various contributions delineate a landscape of female-authored Italian and transnational trauma narratives and their complex textual negotiation of suffering and pathos, from the twentieth century to the present day. These zones of trauma engender a new aesthetics and a new reading of history and cultural memory as an articulation of female creativity and resistance against a dominant cultural and social order.
Fighting an Elusive Enemy: Staphylococcus aureus and its Antibiotic Resistance, Immune-Evasion and Toxic Mechanisms
Topic Editors Dr. Bagnoli and Dr. Phogat are employed by GlaxoSmithKline plc. The other Topic Editors Declare no conflict of interest in relation to the Research Topic theme
