Carbonate conical mounds of the eastern Anti-Atlas(Morocco) and their relationship with potential analogues on Mars

Longstanding debates concerning the origin of the Kess Kess Emsian carbonate mounds exposed at Hamar Laghdad Ridge (eastern Anti-Atlas, Morocco) centre around the processes that induced precipitation of carbonate mud and the preservation of steep morphologies. Although in the last years an origin related to hydrothermalism seemed to be more likely, to date the Kess Kess are still considered controversial vent deposits. This study combines in updated research review information from previous work and new detailed field observations coupled with new analytical results to define a consistent framework and some new insight of current knowledge about the origin of these mounds. We obtain a complete minero-petrographic and palaeobiological data set and a detailed geochemical characterization of the different lithologies and facies of the Hamar Laghdad stratigraphic succession, including mounds, and we compared the results with the data from Maïder Basin mounds (Anti-Atlas, Morocco). Our data support the hydrothermal model proposed for the genesis and development of the Kess Kess mounds. The mechanisms linked to the mounds formation and growth are discussed in the light of the new finding of fluid-sediment interaction within a scenario driven by late magmatic fluids circulation. Conical mounds and other fluids related morphologies were also reported from Crommelin crater area (Arabia Terra, Mars). These mounds consist in meter-sized conical buildups hosted in the Equatorial Layered Deposits (ELDs) deposed during a regional groundwater fluid upwelling. Geometries and geological conditions that might have controlled the development of such morphologies were discussed. According to our data the morphological and stratigraphical characteristics of Crommelin area mounds are most consistent with a formation by fluids advection. Then we compare terrestrial and Martian data and examine the geological settings of hydrothermal mound occurrences on Earth in order to describe potential target areas for hydrothermal structures on Mars.

The human gut microbiome in disease: Role in chemotherapy treatments and relationship with clinical outcomes

The gut microbiome (GM) is a plastic entity, capable of adapting in response to intrinsic and extrinsic factors. However, several circumstances can disrupt this homeostatic balance, forcing the GM to shift from a health-associated mutualistic configuration to a disease-associated profile. Nowadays, a new frontier of microbiome research is understanding the GM role in chemo-immunotherapies and clinical outcomes. Here, the role of the genotoxin‐producing pathogen Salmonella in colorectal carcinogenesis was characterized by in-vitro models. A synergistic effect of Salmonella and the CRC-associated mutation (APC gene) promoted a tumorigenic microenvironment by increasing cellular genomic instability. Subsequently, the GM involvement in anti-cancer therapies was investigated via next-generation sequencing in different patient cohorts. The GM trajectory during treatments was characterized for women with epithelial ovarian cancer and pediatric patients undergoing hematopoietic stem cell transplantation (HSCT). The results highlighted the loss of GM homeostasis, with diversity reduction, decrease in health-associated microorganisms and pathobiont bloom. Interestingly, a distinctive GM profile was identified in ovarian cancer patients with a poor response to chemotherapy compared to patients in remission. Moreover, maintenance of GM homeostasis through enteral feeding in pediatric HSCT patients highlighted a better prognosis, with reduced risk of clinical complications. In this context, the gut resistome – the pattern of GM antibiotic-resistance genes (ARGs) – was evaluated longitudinally in HSCT patients. The results showed new acquisitions and consolidation of ARGs already present in patients developing clinical complications. Antibiotic exposure was also evaluated in infants under low-dose antibiotic prophylaxis for vesico-ureteral reflux showing an impairment of the GM configuration with possible long-term health implications. Dramatic GM dysbiosis was finally observed in critically ill patients with COVID-19 (undergoing multiple drug therapies) and correlated with increased risk of bloodstream infection. All these findings pointed out the importance of maintaining GM homeostasis during chemotherapy treatments for improving patients’ clinical outcomes.

Mode-I fracture parameters of quasi-brittle materials: direct evaluation using DIC and relationship with Mode-II interfacial parameters

The objective of this thesis is the investigation of the Mode-I fracture mechanics parameters of quasi-brittle materials to shed light onto the influence of the width and size of the specimen on the fracture response of notched beams. To further the knowledge on the fracture process, 3D digital image correlation (DIC) was employed. A new method is proposed to determine experimentally the critical value of the crack opening, which is then used to determine the size of the fracture process zone (FPZ). In addition, the Mode-I fracture mechanics parameters are compared with the Mode-II interfacial properties of composites materials that feature as matrices the quasi-brittle materials studied in Mode-I conditions. To investigate the Mode II fracture parameters, single-lap direct shear tests are performed. Notched concrete beams with six cross-sections has been tested using a three-point bending (TPB) test set-up (Mode-I fracture mechanics). Two depths and three widths of the beam are considered. In addition to concrete beams, alkali-activated mortar beams (AAMs) that differ by the type and size of the aggregates have been tested using the same TPB set-up. Two dimensions of AAMs are considered. The load-deflection response obtained from DIC is compared with the load-deflection response obtained from the readings of two linear variable displacement transformers (LVDT). Load responses, peak loads, strain profiles along the ligament from DIC, fracture energy and failure modes of TPB tests are discussed. The Mode-II problem is investigated by testing steel reinforced grout (SRG) composites bonded to masonry and concrete elements under single-lap direct shear tests. Two types of anchorage systems are proposed for SRG reinforced masonry and concrete element to study their effectiveness. An indirect method is proposed to find the interfacial properties, compare them with the Mode-I fracture properties of the matrix and to model the effect of the anchorage.

Applied deep learning and data science with a human-centric and data-centric approach

The term Artificial intelligence acquired a lot of baggage since its introduction and in its current incarnation is synonymous with Deep Learning. The sudden availability of data and computing resources has opened the gates to myriads of applications. Not all are created equal though, and problems might arise especially for fields not closely related to the tasks that pertain tech companies that spearheaded DL. The perspective of practitioners seems to be changing, however. Human-Centric AI emerged in the last few years as a new way of thinking DL and AI applications from the ground up, with a special attention at their relationship with humans. The goal is designing a system that can gracefully integrate in already established workflows, as in many real-world scenarios AI may not be good enough to completely replace its humans. Often this replacement may even be unneeded or undesirable. Another important perspective comes from, Andrew Ng, a DL pioneer, who recently started shifting the focus of development from “better models” towards better, and smaller, data. He defined his approach Data-Centric AI. Without downplaying the importance of pushing the state of the art in DL, we must recognize that if the goal is creating a tool for humans to use, more raw performance may not align with more utility for the final user. A Human-Centric approach is compatible with a Data-Centric one, and we find that the two overlap nicely when human expertise is used as the driving force behind data quality. This thesis documents a series of case-studies where these approaches were employed, to different extents, to guide the design and implementation of intelligent systems. We found human expertise proved crucial in improving datasets and models. The last chapter includes a slight deviation, with studies on the pandemic, still preserving the human and data centric perspective.