Controlling Excitations Inversion of a Cooper Pair Box Interacting with a Nanomechanical Resonator

We investigate the action of time dependent detunings upon the excitation inversion of a Cooper pair box interacting with a nanomechanical resonator. The method employs the Jaynes-Cummings model with damping, assuming different decay rates of the Cooper pair box and various fixed and t-dependent detunings. It is shown that while the presence of damping plus constant detunings destroy the collapse/revival effects, convenient choices of time dependent detunings allow one to reconstruct such events in a perfect way. It is also shown that the mean excitation of the nanomechanical resonator is more robust against damping of the Cooper pair box for convenient values of t-dependent detunings.Comment: 11 pages, 5 figure

A Rare Presentation of Invasive Tuberculosis of the Central Nervous System in an Immunocompetent Patient in a Nonendemic Country.

We herein report a rare case of a 25-year-old immunocompetent male patient with disseminated tuberculosis of central nervous system (CNS), first presenting as multiple cerebral lesions with no meningeal involvement. Subsequent diagnostic workup disclosed extensive peritoneal involvement. A broad differential diagnosis was considered, including neoplastic and infectious diseases. The diagnosis was confirmed with positive PCR result for Mycobacterium tuberculosis in the biopsied mesenteric tissue. The patient was started on tuberculostatic regimen with favorable outcome. No acquired or hereditary immunodeficiency was documented. Disseminated tuberculosis in immunocompetent individuals is extremely rare. Genetic susceptibility factors have been reported in individuals with extensive forms of the disease and a high index of suspicion is required, as observed in our case.info:eu-repo/semantics/publishedVersio

Genetic study in patients operated dentally and anesthetized with articaine-epinephrine

Aims: In this study we wanted to figure out if there was a correlation between OPRM1 N40D, TRPV1 I316M, TRPV1 I585V, NOS3 −786T>C and IL6 −174C>G polymorphisms and the response to locally applied articaine-epinephrine anesthetic. Methods: In this observational study, 114 oral cell samples of patients anesthetized with articaine-epinephrine (54 from men 60 from women), were collected from dental centers in Madrid (Spain). High molecular weight DNA was obtained from oral mucosa cells. The analysis of OPRM1 N40D (rs1799971), TRPV1 I316M (rs222747), TRPV1 I585V (rs8065080) and IL6 −174C>G polymorphism was performed through real-time PCR allelic discrimination using TaqMan probes. Polymorphism NOS3 −786T> C (rs2070744) was analyzed using RFLP-PCR. Results: The studied polymorphisms are involved neither in the response to the anesthetic, nor in the intensity of perceived dental pain. However, in a subset of female patients we found that TRPV1 I316M was associated with a delayed onset of anesthesia. Conclusions: There is no association among these polymorphisms and the time elapsed between the application of the anesthetic and the onset of its effect

Local Fermi gas in inclusive muon capture from nuclei

We compare local Fermi gas and shell model in muon capture in nuclei in order to estimate the effect of finite nuclear size in low energy weak reactions.Comment: 6 pages, 8 figures. To be published in the Proceedings of 20th Max Born Symposium, Wroclaw (Poland), December 7-10, 200

Sustainable growth in complex networks

Based on the empirical analysis of the dependency network in 18 Java projects, we develop a novel model of network growth which considers both: an attachment mechanism and the addition of new nodes with a heterogeneous distribution of their initial degree, $k_0$. Empirically we find that the cumulative degree distributions of initial degrees and of the final network, follow power-law behaviors: $P(k_{0}) \propto k_{0}^{1-\alpha}$, and $P(k)\propto k^{1-\gamma}$, respectively. For the total number of links as a function of the network size, we find empirically $K(N)\propto N^{\beta}$, where $\beta$ is (at the beginning of the network evolution) between 1.25 and 2, while converging to $\sim 1$ for large $N$. This indicates a transition from a growth regime with increasing network density towards a sustainable regime, which revents a collapse because of ever increasing dependencies. Our theoretical framework is able to predict relations between the exponents $\alpha$, $\beta$, $\gamma$, which also link issues of software engineering and developer activity. These relations are verified by means of computer simulations and empirical investigations. They indicate that the growth of real Open Source Software networks occurs on the edge between two regimes, which are either dominated by the initial degree distribution of added nodes, or by the preferential attachment mechanism. Hence, the heterogeneous degree distribution of newly added nodes, found empirically, is essential to describe the laws of sustainable growth in networks.Comment: 5 pages, 2 figures, 1 tabl