Volcanic spreading forcing and feedback in geothermal reservoir development, Amiata Volcano, Italia

We made a stratigraphic, structural and morphologic study of Amiata Volcano in Italy. We find that the edifice is dissected by intersecting grabens that accommodate the collapse of the higher sectors of the volcano. In turn, a number of compressive structures and diapirs exist all around the margin of the volcano. These structures create an angular drainage pattern, with stream damming and captures, and a set of lakes within and around the volcano. We interpret these structures as the result of volcanic spreading of the edifice of Amiata onto its weak substratum, formed by the late Triassic evaporites (Anidriti of Burano) and the Middle-Jurassic to Early-Cretaceous clayey chaotic complexes (Ligurian Complex). Regional doming created a slope in the basement forcing the outward flow and spreading of the ductile layers below the volcano. We model the dynamics of spreading with a scaled lubrication approximation of the Navier Stokes equations, and numerically study a solution. In the model we include simple functions for volcanic deposition and surface erosion that change the topography over time. Scaling indicates that spreading at Amiata could still be active. The numerical solution shows that, as the central part of the edifice sinks into the weak basement, diapiric structures of the underlying formations form around the base of the volcano. Deposition of volcanic rocks within the volcano and surface erosion away from it both enhance spreading. In addition, a sloping basement may constitute a trigger for the formation of trains of adjacent diapirs. Finally, we observe that volcanic spreading has created ideal heat traps that constitute todays’ exploited geothermal fields at Amiata. Normal faults generated by volcanic spreading, volcanic conduits, and direct contact between volcanic rocks (which host an extensive fresh-water aquifer) and the rocks of the geothermal field, constitute ideal pathways for water recharge during vapour extraction for geothermal energy production. We think that volcanic spreading could maintain faults in a critically stressed state, facilitating the occurrence of triggered seismicity

Neural-powered unit disk graph embedding: qubits connectivity for some QUBO problems

Graph embedding is a recurrent problem in quantum computing, for instance, quantum annealers need to solve a minor graph embedding in order to map a given Quadratic Unconstrained Binary Optimization (QUBO) problem onto their internal connectivity pattern. This work presents a novel approach to constrained unit disk graph embedding, which is encountered when trying to solve combinatorial optimization problems in QUBO form, using quantum hardware based on neutral Rydberg atoms. The qubits, physically represented by the atoms, are excited to the Rydberg state through laser pulses. Whenever qubits pairs are closer together than the blockade radius, entanglement can be reached, thus preventing entangled qubits to be simultaneously in the excited state. Hence, the blockade radius determines the adjacency pattern among qubits, corresponding to a unit disk configuration. Although it is straight-forward to compute the adjacency pattern given the qubits' coordinates, identifying a feasible unit disk arrangement that matches the desired QUBO matrix is, on the other hand, a much harder task. In the context of quantum optimization, this issue translates into the physical placement of the qubits in the 2D/3D register to match the machine's Ising-like Hamiltonian with the QUBO formulation of the optimization problems. The proposed solution exploits the power of neural networks to transform an initial embedding configuration, which does not match the quantum hardware requirements or does not account for the unit disk property, into a feasible embedding properly representing the target optimization problems. Experimental results show that this new approach overcomes in performance Gurobi solver

Optimized culture conditions for tissue explants of uterine leiomyoma

Background: Uterine leiomyomas are the most common benign tumours in women, which arise from smooth muscle cells of the uterine myometrium and usually are multicentric. In spite of their frequency pathogenesis is widely unknown, mainly due to the absence of a suitable model system. We describe the systematic optimization of culturing leiomyoma tissue explants in an economical and effective ex vivo system. Methods: Different concentrations of oxygen, different media, sera, hormones, and growth factor supplements were tested. Immunohistochemical stainings with antibodies against hormone receptors as well as specifying proliferation and apoptotic indices and real-time PCR were performed. Results: Main parameters for culturing myoma tissue explants were tested for finding an optimal protocol. Standard medium D-MEM-F12 in combination with the use of horse serum in a reduced concentration of 1% turned out to be optimal for these tissue cultures as well as the addition of estradiol and epidermal growth factor EGF to media. Reduced oxygen content in the incubator air showed no positive effect. Conclusions: For culturing tissue explants of uterine leiomyoma several conditions were optimized. The established tissue culture model allows examining the effects of known and potential therapeutic substances and the influence of immune competent cells in the process of tumour formation to find new targets for medical treatmen

Accelerating legacy applications with spatial computing devices

Heterogeneous computing is the major driving factor in designing new energy-efficient high-performance computing systems. Despite the broad adoption of GPUs and other specialized architectures, the interest in spatial architectures like field-programmable gate arrays (FPGAs) has grown. While combining high performance, low power consumption and high adaptability constitute an advantage, these devices still suffer from a weak software ecosystem, which forces application developers to use tools requiring deep knowledge of the underlying system, often leaving legacy code (e.g., Fortran applications) unsupported. By realizing this, we describe a methodology for porting Fortran (legacy) code on modern FPGA architectures, with the target of preserving performance/power ratios. Aimed as an experience report, we considered an industrial computational fluid dynamics application to demonstrate that our methodology produces synthesizable OpenCL codes targeting Intel Arria10 and Stratix10 devices. Although performance gain is not far beyond that of the original CPU code (we obtained a relative speedup of x 0.59 and x 0.63, respectively, for a single optimized main kernel, while only on the Stratix10 we achieved x 2.56 by replicating the main optimized kernel 4 times), our results are quite encouraging to drawn the path for further investigations. This paper also reports some major criticalities in porting Fortran code on FPGA architectures

Reply to: Barazzuoli P., Bertini G., Brogi A., Capezzuoli E., Conticelli S., Doveri M., Ellero A., Gianelli G., La Felice S., Liotta D., Marroni M., Manzella A., Meccheri M., Montanari D., Pandeli E., Principe C., Ruggieri R., Sbrana A., Vaselli V., Vezzoli L., 2015. COMMENT ON: "Borgia, A., Mazzoldi, A., Brunori, C.A., Allocca, C., Delcroix, C., Micheli, L., Vercellino, A., Gr

The volcanic spreading model by Borgia et al. (2014) is accurate in describing the extensional structures found on the edifice and the radial compressional structures existing all around the base of Amiata Volcano. Volcanic conduits, extensional structures, and direct contact between the volcanic rocks and the Tuscan Units, constitute the hydraulic connection between the potable fresh-water aquifer contained in the volcanites and the underlying hydrothermal system. Therefore, gaseous phases tend to flow upward (particularly through faults) carrying pollutants into the freshwater aquifer, while the freshwater recharges (also through primary permeability) the exploited geothermal fields

The mycorrhizal root-shoot axis elicits Coffea arabica growth under low phosphate conditions

Coffee is one of the most traded commodities world-wide. As with 70% of land plants, coffee is associated with arbuscular mycorrhizal (AM) fungi, but the molecular bases of this interaction are unknown. We studied the mycorrhizal phenotype of two commercially important Coffea arabica cultivars (‘Typica National’ and ‘Catimor Amarillo’), upon Funnelliformis mosseae colonisation grown under phosphorus limitation, using an integrated functional approach based on multi-omics, physiology and biochemistry. The two cultivars revealed a strong biomass increase upon mycorrhization, even at low level of fungal colonisation, improving photosynthetic efficiency and plant nutrition. The more important iconic markers of AM symbiosis were activated: We detected two gene copies of AM-inducible phosphate (Pt4), ammonium (AM2) and nitrate (NPF4.5) transporters, which were identified as belonging to the C. arabica parental species (C. canephora and C. eugenioides) with both copies being upregulated. Transcriptomics data were confirmed by ions and metabolomics analyses, which highlighted an increased amount of glucose, fructose and flavonoid glycosides. In conclusion, both coffee cultivars revealed a high responsiveness to the AM fungus along their root-shoot axis, showing a clear-cut re-organisation of the major metabolic pathways, which involve nutrient acquisition, carbon fixation, and primary and secondary metabolism

Cd19 cell count at baseline predicts b cell repopulation at 6 and 12 months in multiple sclerosis patients treated with ocrelizumab

Background: The kinetics of B cell repopulation in MS patients treated with Ocrelizumab is highly variable, suggesting that a fixed dosage and time scheduling might be not optimal. We aimed to investigate whether B cell repopulation kinetics influences clinical and radiological outcomes and whether circulating immune asset at baseline affects B cell repopulation kinetics. Methods: 218 MS patients treated with Ocrelizumab were included. Every six months we collected data on clinical and magnetic resonance imaging (MRI) activity and lymphocyte subsets at baseline. According to B cell counts at six and twelve months, we identified two groups of patients, those with fast repopulation rate (FR) and those with slow repopulation rate (SR). Results: A significant reduction in clinical and radiological activity was found. One hundred fifty-five patients had complete data and received at least three treatment cycles (twelve-month follow-up). After six months, the FR patients were 41/155 (26.45%) and 10/41 (29.27%) remained non-depleted after twelve months. FR patients showed a significantly higher percentage of active MRI scan at twelve months (17.39% vs. 2.53%; p = 0,008). Furthermore, FR patients had a higher baseline B cell count compared to patients with an SR (p = 0.02 and p = 0.002, at the six-and twelve-month follow-ups, respectively). Conclusion: A considerable proportion of MS patients did not achieve a complete CD19 cell depletion and these patients had a higher baseline CD19 cell count. These findings, together with the higher MRI activity found in FR patients, suggest that the Ocrelizumab dosage could be tailored depending on CD19 cell counts at baseline in order to achieve complete disease control in all patients