Intermittent and Scale-Invariant Intensity Fluctuations in Hot Coronal Loops

ABSTRACT BODY: To resolve outstanding questions on heating of coronal loops, we study intensity fluctuations in inter-moss portions of active region core loops as observed with AIA/SDO. The 94Å fluctuations (Figure 1) have structure on timescales shorter than radiative and conductive cooling times. Each of several strong 94Å brightenings is followed after ~8 min by a broader peak in the cooler 335Å emission. This indicates that we see emission from the hot component of the 94Å contribution function. No hotter contributions appear, and we conclude that the 94Å intensity can be used as a proxy for energy injection into the loop plasma. The probability density function of the observed 94Å intensity has 'heavy tails' that approach zero more slowly than the tails of a normal distribution. Hence, large fluctuations dominate the behavior of the system. The resulting 'intermittence' is associated with power-law or exponential scaling of the related variables, and these in turn are associated with turbulent phenomena. The intensity plots in Figure 1 resemble multifractal time series, which are common to various forms of turbulent energy dissipation. In these systems a single fractal dimension is insufficient to describe the dynamics and instead there is a spectrum of fractal dimensions that quantify the self-similar properties. Figure 2 shows the multifractal spectrum from our data to be invariant over timescales from 24 s to 6.4 min. We compare these results to outputs from theoretical energy dissipation models based on MHD turbulence, and in some cases we find substantial agreement, in terms of intermittence, multifractality and scale invariance. Figure 1. Time traces of 94A intensity in the inter-moss portions of four AR core loops. Figure 2. Multifractal spectra showing timescale invariance. The four cases of Figure 1 are included.

Evolution of Hot Loops in an Active Region Core Observed with the SDO Atmospheric Image Assembly

Evidence has accumulated of high temperature (> 4 MK) coronal emission in active region cores that corresponds to structures in equilibrium. Other studies have found evidence of evolving loops. We investigate the EUV intensity and temperature variations of short coronal loops observed in the core of NOAA Active Region 11250 on 13 July 2011. The loops, which run directly between the AR opposite polarities, are first detectable in the 94Å band of Fe XVIII, implying an effective temperature ~ 7 MK. The low temperature component of the 94 Å signal is modeled in terms of a linear superposition of the 193 Å and 171 Å signals in order to separate the hot component. After identifying the loops we have used contemporaneous HMI observations to identify the corresponding inter-moss regions, and we have investigated their time evolution in six AIA EUV channels. The results can be separated into two classes. Group 1 (94Å, 335Å, 211Å) is characterized by hotter temperatures (~2-7 MK), and Group 2 (193Å, 171Å, 131Å) by cooler temperatures (0.4 - 1.6 MK). For Group 1 the intensity peaks in the 94Å channel are followed by maxima in the 335 Å channel with a time lag of ~8 min, suggestive of a cooling pattern with an exponential decay. While the 211Å maxima follow those in the 335 Å channel, there is no systematic relation which would indicate a progressive cooling process through the lower temperatures, as has been observed in other investigations. In Group 2 the signals in the 171 and 131Å channels track each other closely, and lag behind the 193Å. In the inter-moss region of the loop the peak temperature and peak emission measure have opposite trends. The hot 94Å brightenings occur in the central part of the loops with maximum temperatures ~7 MK. Subsequently the loops appear to fill with plasma with an emission measure compatible with the 193 Å signal and temperature in the range ~ 1.5-2 MK. Although the exact details of the time evolution are still under investigation, these non static loops show high levels of intermittency in the 94Å signal (please see poster "Intermittent and Scale-Invariant Intensity Fluctuations in Hot Coronal Loops," by Lawrence et al. in this session).

Analysis of the respiratory dynamics during normal breathing by means of pseudo phase plots and pressure-volume loops

This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure–volume curves and the pseudophaseplane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

Analysis of the Respiratory Dynamics During Normal Breathing by Means of Pseudophase Plots and Pressure–Volume Loops

This paper reports on the analysis of tidal breathing patterns measured during noninvasive forced oscillation lung function tests in six individual groups. The three adult groups were healthy, with prediagnosed chronic obstructive pulmonary disease, and with prediagnosed kyphoscoliosis, respectively. The three children groups were healthy, with prediagnosed asthma, and with prediagnosed cystic fibrosis, respectively. The analysis is applied to the pressure-volume curves and the pseudophase-plane loop by means of the box-counting method, which gives a measure of the area within each loop. The objective was to verify if there exists a link between the area of the loops, power-law patterns, and alterations in the respiratory structure with disease. We obtained statistically significant variations between the data sets corresponding to the six groups of patients, showing also the existence of power-law patterns. Our findings support the idea that the respiratory system changes with disease in terms of airway geometry and tissue parameters, leading, in turn, to variations in the fractal dimension of the respiratory tree and its dynamics.

24/12/19 Vel d'Hiv' départ du Bol d'or [les pistards : Georget, Van Neh, Deruyter, Godivier, Bartelemy, Léonard et Steux] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57305

25-12-19 Vel d'Hiv', Bol d'or [les pistards au repos] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57307

Vel d'Hiv' 25/12/19, [Léon] Georget vainqueur du Bol d'or : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57311

[25-12-19 Vel d'Hiv'] Barthelemy 4e, Georget vainqueur du Bol d'or, Godivier 2e : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 57313

Les R-loops et leurs conséquences sur l'expression génique chez Escherichia coli.

Des variations importantes du surenroulement de l’ADN peuvent être générées durant la phase d’élongation de la transcription selon le modèle du « twin supercoiled domain ». Selon ce modèle, le déplacement du complexe de transcription génère du surenroulement positif à l’avant, et du surenroulement négatif à l’arrière de l’ARN polymérase. Le rôle essentiel de la topoisomérase I chez Escherichia coli est de prévenir l’accumulation de ce surenroulement négatif générée durant la transcription. En absence de topoisomérase I, l’accumulation de ce surenroulement négatif favorise la formation de R-loops qui ont pour conséquence d’inhiber la croissance bactérienne. Les R-loops sont des hybrides ARN-ADN qui se forment entre l’ARN nouvellement synthétisé et le simple brin d’ADN complémentaire. Dans les cellules déficientes en topoisomérase I, des mutations compensatoires s’accumulent dans les gènes qui codent pour la gyrase, réduisant le niveau de surenroulement négatif du chromosome et favorisant la croissance. Une des ces mutations est une gyrase thermosensible qui s’exprime à 37 °C. La RNase HI, une enzyme qui dégrade la partie ARN d’un R-loop, peut aussi restaurer la croissance en absence de topoisomérase I lorsqu’elle est produite en très grande quantité par rapport à sa concentration physiologique. En présence de topoisomérase I, des R-loops peuvent aussi se former lorsque la RNase HI est inactive. Dans ces souches mutantes, les R-loops induisent la réponse SOS et la réplication constitutive de l’ADN (cSDR). Dans notre étude, nous montrons comment les R-loops formés en absence de topoisomérase I ou RNase HI peuvent affecter négativement la croissance des cellules. Lorsque la topoisomérase I est inactivée, l’accumulation d’hypersurenroulement négatif conduit à la formation de nombreux R-loops, ce qui déclenche la dégradation de l’ARN synthétisé. Issus de la dégradation de l’ARNm de pleine longueur, des ARNm incomplets et traductibles s’accumulent et causent l’inhibition de la synthèse protéique et de la croissance. Le processus par lequel l’ARN est dégradé n’est pas encore complètement élucidé, mais nos résultats soutiennent fortement que la RNase HI présente en concentration physiologique est responsable de ce phénotype. Chose importante, la RNase E qui est l’endoribonuclease majeure de la cellule n’est pas impliquée dans ce processus, et la dégradation de l’ARN survient avant son action. Nous montrons aussi qu’une corrélation parfaite existe entre la concentration de RNase HI, l’accumulation d’hypersurenroulement négatif et l’inhibition de la croissance bactérienne. Lorsque la RNase HI est en excès, l’accumulation de surenroulement négatif est inhibée et la croissance n’est pas affectée. L’inverse se produit Lorsque la RNase HI est en concentration physiologique. En limitant l’accumulation d’hypersurenroulement négatif, la surproduction de la RNase HI prévient alors la dégradation de l’ARN et permet la croissance. Quand la RNase HI est inactivée en présence de topoisomérase I, les R-loops réduisent le niveau d’expression de nombreux gènes, incluant des gènes de résistance aux stress comme rpoH et grpE. Cette inhibition de l’expression génique n’est pas accompagnée de la dégradation de l’ARN contrairement à ce qui se produit en absence de topoisomérase I. Dans le mutant déficient en RNase HI, la diminution de l’expression génique réduit la concentration cellulaire de différentes protéines, ce qui altère négativement le taux de croissance et affecte dramatiquement la survie des cellules exposées aux stress de hautes températures et oxydatifs. Une inactivation de RecA, le facteur essentiel qui déclenche la réponse SOS et le cSDR, ne restaure pas l’expression génique. Ceci démontre que la réponse SOS et le cSDR ne sont pas impliqués dans l’inhibition de l’expression génique en absence de RNase HI. La croissance bactérienne qui est inhibée en absence de topoisomérase I, reprend lorsque l’excès de surenroulement négatif est éliminé. En absence de RNase HI et de topoisomérase I, le surenroulement négatif est très relaxé. Il semble que la réponse cellulaire suite à la formation de R-loops, soit la relaxation du surenroulement négatif. Selon le même principe, des mutations compensatoires dans la gyrase apparaissent en absence de topoisomérase I et réduisent l’accumulation de surenroulement négatif. Ceci supporte fortement l’idée que le surenroulement négatif joue un rôle primordial dans la formation de R-loop. La régulation du surenroulement négatif de l’ADN est donc une tâche essentielle pour la cellule. Elle favorise notamment l’expression génique optimale durant la croissance et l’exposition aux stress, en limitant la formation de R-loops. La topoisomérase I et la RNase HI jouent un rôle important et complémentaire dans ce processus.

Interaction entre la RNase HI et la RNase E dans le métabolisme des R-loops et la dégradation des ARNms chez Escherichia coli.

Chez la bactérie Escherichia coli, la topoisomérase I et la gyrase représentent deux topoisomérases majeures qui participent à la régulation du surenroulement de l’ADN. Celles-ci sont codées respectivement par les gènes topA et par gyrA et gyrB. Chez les mutants topA, l’excès de surenroulement négatif qui est généré en amont de la polymérase ARN lors de la phase d’élongation de la transcription de l’ADN, entraine la formation de R-loops. Les R-loops sont des hybrides ARN-ADN qui in vivo sont formés lorsque l’ARN nouvellement transcrit forme un hybride avec le brin d’ADN matrice, le brin d’ADN complémentaire demeurant sous forme simple brin. La RNase HI est une endoribonucléase codée par le gène rnhA. Elle dégrade l’ARN de R-loops, entre autres, pour empêcher l’initiation de la réplication à des sites autres que l’origine normale, oriC. Chez les mutants rnhA, on observe une réplication indépendante de l’origine oriC. Ce type de réplication appelé cSDR, pourrait donc expliquer, du moins en partie, l’inhibition de la croissance de doubles mutants topA rnhA. A l’aide de la mutagenèse au transposon Tn5, il a été possible d’isoler des suppresseurs extragéniques qui permettaient la croissance des doubles mutants topA rnhA. Plusieurs de ces suppresseurs ont le transposon inséré dans le gène codant pour la RNase E, l’endoribonucléase principale impliquée dans la dégradation des ARNms chez E. coli. La majorité des insertions se retrouvent dans la partie C-terminale de la protéine qui est impliquée dans l’assemblage d’un complexe multiprotéique appelé l’ARN dégradosome. Les résultats obtenus démontrent que ces suppresseurs diminuent le cSDR ainsi que la réponse SOS induite constitutivement en l’absence de la RNase HI. Sachant que la RNase HI est une endoribonucléase tout comme la RNase E, une collaboration entre les deux enzymes suggère que la RNase E pourrait également jouer un rôle potentiel dans le contrôle de la formation des R-loops et bien évidemment de leur retrait au sein de la cellule. À l’opposé, il est possible que la RNase HI puisse avoir comme autre fonction la prise en charge de la maturation et de la dégradation des molécules d’ARNs.

Belief Propagation and Revision in Networks with Loops

Local belief propagation rules of the sort proposed by Pearl(1988) are guaranteed to converge to the optimal beliefs for singly connected networks. Recently, a number of researchers have empirically demonstrated good performance of these same algorithms on networks with loops, but a theoretical understanding of this performance has yet to be achieved. Here we lay the foundation for an understanding of belief propagation in networks with loops. For networks with a single loop, we derive ananalytical relationship between the steady state beliefs in the loopy network and the true posterior probability. Using this relationship we show a category of networks for which the MAP estimate obtained by belief update and by belief revision can be proven to be optimal (although the beliefs will be incorrect). We show how nodes can use local information in the messages they receive in order to correct the steady state beliefs. Furthermore we prove that for all networks with a single loop, the MAP estimate obtained by belief revisionat convergence is guaranteed to give the globally optimal sequence of states. The result is independent of the length of the cycle and the size of the statespace. For networks with multiple loops, we introduce the concept of a "balanced network" and show simulati.

Programming Principles: Loops and Arrays

In this session we look at the different types of loop in the Java language, and see how they can be used to iterate over Arrays.

Analysis of the antigen combining site: Correlations between length and sequence composition of the hypervariable loops and the nature of the antigen

It has long been suggested that the overall shape of the antigen combining site (ACS) of antibodies is correlated with the nature of the antigen. For example, deep pockets are characteristic of antibodies that bind haptens, grooves indicate peptide binders, while antibodies that bind to proteins have relatively flat combining sites. In. 1996, MacCallum, Martin and Thornton used a fractal shape descriptor and showed a strong correlation of the shape of the binding region with the general nature of the antigen. However, the shape of the ACS is determined primarily by the lengths of the six complementarity-determining regions (CDRs). Here, we make a direct correlation between the lengths of the CDRs and the nature of the antigen. In addition, we show significant differences in the residue composition of the CDRs of antibodies that bind to different antigen classes. As well as helping us to understand the process of antigen recognition, autoimmune disease and cross-reactivity these results are of direct application in the design of antibody phage libraries and modification of affinity. (C) 2003 Elsevier Science Ltd. All rights reserved.

Differential recognition of Staphylococcus aureus quorum-sensing signals depends on both extracellular loops 1 and 2 of the transmembrane sensor AgrC.

Virulence in Staphylococcus aureus is regulated via agr-dependent quorum sensing in which an autoinducing peptide (AIP) activates AgrC, a histidine protein kinase. AIPs are usually thiolactones containing seven to nine amino acid residues in which the thiol of the central cysteine is linked to the alpha-carboxyl of the C-terminal amino acid residue. The staphylococcal agr locus has diverged such that the AIPs of the four different S. aureus agr groups self-activate but cross-inhibit. Consequently, although the agr system is conserved among the staphylococci, it has undergone significant evolutionary divergence whereby to retain functionality, any changes in the AIP-encoding gene (agrD) that modifies AIP structure must be accompanied by corresponding changes in the AgrC receptor. Since AIP-1 and AIP-4 only differ by a single amino acid, we compared the transmembrane topology of AgrC1 and AgrC4 to identify amino acid residues involved in AIP recognition. As only two of the three predicted extracellular loops exhibited amino acid differences, site-specific mutagenesis was used to exchange the key AgrC1 and AgrC4 amino acid residues in each loop either singly or in combination. A novel lux-based agrP3 reporter gene fusion was constructed to evaluate the response of the mutated AgrC receptors. The data obtained revealed that while differential recognition of AIP-1 and AIP-4 depends primarily on three amino acid residues in loop 2, loop 1 is essential for receptor activation by the cognate AIP. Furthermore, a single mutation in the AgrC1 loop 2 resulted in conversion of (Ala5)AIP-1 from a potent antagonist to an activator, essentially resulting in the forced evolution of a new AIP group. Taken together, our data indicate that loop 2 constitutes the predicted hydrophobic pocket that binds the AIP thiolactone ring while the exocyclic amino acid tail interacts with loop 1 to facilitate receptor activation.