Natural Metric for Quantum Information Theory

We study in detail a very natural metric for quantum states. This new proposal has two basic ingredients: entropy and purification. The metric for two mixed states is defined as the square root of the entropy of the average of representative purifications of those states. Some basic properties are analyzed and its relation with other distances is investigated. As an illustrative application, the proposed metric is evaluated for 1-qubit mixed states.Comment: v2: enlarged; presented at ISIT 2008 (Toronto

Evaluation of near-surface groundwater aquifers through integrated geophysical and geodetic measurements

Abstract Extensive geophysical and geodetic measurements were carried out to evaluate the groundwater aquifer, trace the basement relief, as well as detect the igneous intrusions and structural elements (mainly faults) that affect the occurrence of groundwater in the study area. The fieldwork included resistivity sounding, a geomagnetic survey, and Global Positioning System measurements. The magnetic results showed the presence of a group of main faults in East-west trend at the western part of the area and major fault at the northern part of the area of NW-SW trend. The findings also showed the presence of two igneous rock intrusions located in the middle of the eastern part of the valley. Pronounced differences in the depths of basement rocks have been identified, ranging between 0 and 900 m from the surface. Both high horizontal movements and high shear strain rates have been found to be concentrated at the southeast of the study area and it was noted that high stress was accumulated along the main observed faults and at the main groundwater aquifers. The geoelectrical results confirmed the presence of two aquifers; a shallow aquifer (Quaternary aquifer) that narrows northwards and a Nubian sandstone aquifer, which considered the main aquifer. The Nubian sandstone aquifer carries groundwater in the region, which overlies the last geoelectric unit represented by the basement complex layer and geological structures affecting the potential availability of groundwater in the study area, as proved by the geomagnetic survey and stress accumulation

Validation of a sectional soot model based on a constant pressure tabulated chemistry approach for PM, PN and PSDF estimation in a GDI research engine

Findings from the International Agency for Research on Cancer (IARC) classified particulate matter (PM) as carcinogenic to humans. While being a promising solution to reduce greenhouse gases (GHG) emissions and increase engine fuel economy, Gasoline Direct Injected (GDI) engines produce a number of particles (PN) of fine size higher than Port Fuel Injected (PFI) ones. As a consequence, the EU commission significantly tightened the emission standards for passenger cars, following which all gasoline engines will have to meet the euro-6d regulation coming into force in 2020. Efforts are made by the research community to understand the root causes leading to soot formation and possibly identify technical solutions to lower it. An important piece of the puzzle is the investigation of soot formation via 3D-CFD. To this aim, relevant efforts have been and are still being paid to adapt soot emissions models, originally developed for Diesel combustion, for GDI units. Among the many available models, one of the most advanced is the so-called Sectional Method. So far, studies presented in literature were not able to formulate a methodology to quantitatively match experimental PM, PN and PSDF without a dedicated soot model tuning. In the present work, a Sectional Method-based methodology to quantitatively predict GDI soot is presented and validated against PM, PN and PSDF measurements on a optically accessible GDI research unit. While adapting the model to GDI soot, attention is devoted to the modelling of soot precursor chemistry: a customized version of a pre-existing chemical kinetics mechanism, used to predict the formation of the key PAH (Polycyclic Aromatic Hydrocarbons) species, is presented and validated via 1D numerical simulations on a premixed flat flame burner dataset available in literature. The present work demonstrates that a Sectional Method-based approach can be a powerful tool to quantitatively predict engine-out soot emissions

Effect of the microtubule-associated protein tau on dynamics of single-headed motor proteins KIF1A

Intracellular transport based on molecular motors and its regulation are crucial to the functioning of cells. Filamentary tracks of the cells are abundantly decorated with nonmotile microtubule-associated proteins, such as tau. Motivated by experiments on kinesin-tau interactions [Dixit et al., Science 319, 1086 (2008)] we developed a stochastic model of interacting single-headed motor proteins KIF1A that also takes into account the interactions between motor proteins and tau molecules. Our model reproduces experimental observations and predicts significant effects of tau on bound time and run length which suggest an important role of tau in regulation of kinesin-based transport.publishedVersionFil: Sparacino, Javier. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Sparacino, Javier. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Farias, María Gimena. Universidad Nacional de Córdoba. Instituto de Investigación Médica Mercedes y Martín Ferreyra; Argentina.Fil: Farias, María Gimena. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigación Médica Mercedes y Martín Ferreyra; Argentina.Fil: Farias, María Gimena. Ministerio de Ciencia, Tecnología e Innovación. Agencia Nacional de Promoción de la Investigación, el Desarrollo Tecnológico y la Innovación. Fondo para la Investigación Científica y Tecnológica; Argentina.Fil: Lamberti, Pedro Walter. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía y Física; Argentina.Fil: Lamberti, Pedro Walter. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Otras Ciencias Física

Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring.

Background and Aims: Continuous glucose monitoring (CGM) devices could be useful for real-time management of diabetes therapy. In particular, CGM information could be used in real time to predict future glucose levels in order to prevent hypo-/hyperglycemic events. This article proposes a new online method for predicting future glucose concentration levels from CGM data. Methods: The predictor is implemented with an artificial neural network model (NNM). The inputs of the NNM are the values provided by the CGM sensor during the preceding 20 min, while the output is the prediction of glucose concentration at the chosen prediction horizon (PH) time. The method performance is assessed using datasets from two different CGM systems (nine subjects using the Medtronic [Northridge, CA] Guardian® and six subjects using the Abbott [Abbott Park, IL] Navigator®). Three different PHs are used: 15, 30, and 45 min. The NNM accuracy has been estimated by using the root mean square error (RMSE) and prediction delay. Results: The RMSE is around 10, 18, and 27 mg/dL for 15, 30, and 45 min of PH, respectively. The prediction delay is around 4, 9, and 14 min for upward trends and 5, 15, and 26 min for downward trends, respectively. A comparison with a previously published technique, based on an autoregressive model (ARM), has been performed. The comparison shows that the proposed NNM is more accurate than the ARM, with no significant deterioration in the prediction delay

Shewanella algae infection in Italy: report of 3 years' evaluation along the coast of the northern Adriatic Sea

Shewanella algae are Gram-negative, nonfermentative, motile bacilli, classified in the genus Shewanella in 1985. These environmental bacteria are occasionally identified in human infections, with a relatively strong association with exposure to seawater during warm seasons. This report describes a case series of 17 patients with infection correlated to S. algae in the coastal area of Romagna, Italy, from 2013 to 2016. The types of infection included otitis, pneumonia, sepsis and soft tissue (wound). Exposure to the marine environment during hot months was confirmed in 12 of 17 patients. An apparent correlation between increased severity of infection and patient age was also observed

Orientamento dei Centri Trapianto Italiani in tema di HCV e Trapianto Renale

Abstract non disponibil

Determinants of enhanced thromboxane biosynthesis in renal transplantation

Background. Despite great improvement in patient and graft survival, the long-term morbidity and mortality in renal transplant recipients (RTRs) are still significant, with a high incidence of cardiovascular disease-related deaths. Methods. We investigated thromboxane (TXA2) biosynthesis and endothelial and coagulative activation in 65 patients who received a renal transplant. Results. The rate of TXA2 biosynthesis (urinary 11-dehydro-TXB2 excretion largely reflects platelet TXA2 production in vivo) was significantly (P < 0.0001) higher in RTRs than in healthy subjects. Plasma von Willebrand factor (vWF) and thrombin-antithrombin (TAT) complexes were significantly higher (P < 0.001) in RTRs compared with controls. Urinary 11-dehydro-TXB2 directly correlated with plasma vWF and cholesterol. We next examined the relative influence of cyclosporine A (CsA) on TXA2 biosynthesis and endothelial activation, comparing a group of RTRs not receiving CsA with an age- and sex-matched group of patients treated with CsA. Urinary excretion of 11-dehydro-TXB2 and plasma levels of vWF were significantly increased in RTRs who received CsA compared with those who did not. After an overall follow-up of 120 months, RTRs who experienced cardiovascular events had a higher frequency of abnormal plasma levels of vWF than patients who remained event free. Conclusion. Renal transplantation is associated with in vivo platelet activation highly related to endothelial activation. This is particularly evident in CsA-treated patients. Administration of drugs that are able to reduce or eliminate thromboxane-dependent platelet activation in vivo may be beneficial to reduce the risk of cardiovascular events in RTRs