Letter to the Editor: 1H, 15N, and 13C chemical shift assignments of the resuscitation promoting factor domain of Rv1009 from Mycobacterium tuberculosis

International audienceNo abstract availabl

Study of the optimal conditions for NV- center formation in type 1b diamond, using photoluminescence and positron annihilation spectroscopies

We studied the parameters to optimize the production of negatively-charged nitrogen-vacancy color centers (NV-) in type~1b single crystal diamond using proton irradiation followed by thermal annealing under vacuum. Several samples were treated under different irradiation and annealing conditions and characterized by slow positron beam Doppler-broadening and photoluminescence (PL) spectroscopies. At high proton fluences another complex vacancy defect appears limiting the formation of NV-. Concentrations as high as 2.3 x 10^18 cm^-3 of NV- have been estimated from PL measurements. Furthermore, we inferred the trapping coefficient of positrons by NV-. This study brings insight into the production of a high concentration of NV- in diamond, which is of utmost importance in ultra-sensitive magnetometry and quantum hybrid systems applications

Stochastic Invariants for Probabilistic Termination

Termination is one of the basic liveness properties, and we study the termination problem for probabilistic programs with real-valued variables. Previous works focused on the qualitative problem that asks whether an input program terminates with probability~1 (almost-sure termination). A powerful approach for this qualitative problem is the notion of ranking supermartingales with respect to a given set of invariants. The quantitative problem (probabilistic termination) asks for bounds on the termination probability. A fundamental and conceptual drawback of the existing approaches to address probabilistic termination is that even though the supermartingales consider the probabilistic behavior of the programs, the invariants are obtained completely ignoring the probabilistic aspect. In this work we address the probabilistic termination problem for linear-arithmetic probabilistic programs with nondeterminism. We define the notion of {\em stochastic invariants}, which are constraints along with a probability bound that the constraints hold. We introduce a concept of {\em repulsing supermartingales}. First, we show that repulsing supermartingales can be used to obtain bounds on the probability of the stochastic invariants. Second, we show the effectiveness of repulsing supermartingales in the following three ways: (1)~With a combination of ranking and repulsing supermartingales we can compute lower bounds on the probability of termination; (2)~repulsing supermartingales provide witnesses for refutation of almost-sure termination; and (3)~with a combination of ranking and repulsing supermartingales we can establish persistence properties of probabilistic programs. We also present results on related computational problems and an experimental evaluation of our approach on academic examples.Comment: Full version of a paper published at POPL 2017. 20 page

A formally verified compiler back-end

This article describes the development and formal verification (proof of semantic preservation) of a compiler back-end from Cminor (a simple imperative intermediate language) to PowerPC assembly code, using the Coq proof assistant both for programming the compiler and for proving its correctness. Such a verified compiler is useful in the context of formal methods applied to the certification of critical software: the verification of the compiler guarantees that the safety properties proved on the source code hold for the executable compiled code as well

Protein kinase B controls Mycobacterium tuberculosis growth via phosphorylation of the transcriptional regulator Lsr2 at threonine 112.

Mycobacterium tuberculosis (Mtb) is able to persist in the body through months of multi-drug therapy. Mycobacteria possess a wide range of regulatory proteins, including the protein kinase B (PknB) which controls peptidoglycan biosynthesis during growth. Here, we observed that depletion of PknB resulted in specific transcriptional changes that are likely caused by reduced phosphorylation of the H-NS-like regulator Lsr2 at threonine 112. The activity of PknB towards this phosphosite was confirmed with purified proteins, and this site was required for adaptation of Mtb to hypoxic conditions, and growth on solid media. Like H-NS, Lsr2 binds DNA in sequence-dependent and non-specific modes. PknB phosphorylation of Lsr2 reduced DNA binding, measured by fluorescence anisotropy and electrophoretic mobility shift assays, and our NMR structure of phosphomimetic T112D Lsr2 suggests that this may be due to increased dynamics of the DNA-binding domain. Conversely, the phosphoablative T112A Lsr2 had increased binding to certain DNA sites in ChIP-sequencing, and Mtb containing this variant showed transcriptional changes that correspond with the change in DNA binding. In summary, PknB controls Mtb growth and adaptations to the changing host environment by phosphorylating the global transcriptional regulator Lsr2

Model for initiation of quality factor degradation at high accelerating fields in superconducting radio-frequency cavities

A model for the onset of the reduction in SRF cavity quality factor, the so-called Q-drop, at high accelerating electric fields is presented. Breakdown of the surface barrier against magnetic flux penetration at the cavity equator is considered to be the critical event that determines the onset of Q-drop. The worst case of triangular grooves with low field of first flux penetration Hp, as analyzed previously by Buzdin and Daumens, [1998 Physica C 294: 257], was adapted. This approach incorporates both the geometry of the groove and local contamination via the Ginzburg-Landau parameter kappa, so the proposed model allows new comparisons of one effect in relation to the other. The model predicts equivalent reduction of Hp when either roughness or contamination were varied alone, so smooth but dirty surfaces limit cavity performance about as much as rough but clean surfaces do. When in combination, contamination exacerbates the negative effects of roughness and vice-versa. To test the model with actual data, coupons were prepared by buffered chemical polishing and electropolishing, and stylus profilometry was used to obtain distributions of angles. From these data, curves for surface resistance generated by simple flux flow as a function of magnetic field were generated by integrating over the distribution of angles for reasonable values of kappa. This showed that combined effects of roughness and contamination indeed reduce the Q-drop onset field by ~30%, and that that contamination contributes to Q-drop as much as roughness. The latter point may be overlooked by SRF cavity research, since access to the cavity interior by spectroscopy tools is very difficult, whereas optical images have become commonplace. The model was extended to fit cavity test data, which indicated that reduction of the superconducting gap by contaminants may also play a role in Q-drop.Comment: 15 pages with 7 figure