Unfolding and refolding of cytochrome c driven by the interaction with lipid micelles

Binding of native cyt c to L-PG micelles leads to a partially unfolded conformation of cyt c. This micelle-bound state has no stable tertiary structure, but remains as -helical as native cyt c in solution. In contrast, binding of the acid-unfolded cyt c to L-PG micelles induces folding of the polypeptide, resulting in a similar helical state to that originated from the binding of native cyt c to L-PG micelles. Far-ultraviolet (UV) circular dichroism (CD) spectra showed that this common micelle-associated helical state (HL) has a native-like -helix content, but is highly expanded without a tightly packed hydrophobic core, as revealed by tryptophan fluorescence, near-UV, and Soret CD spectroscopy. The kinetics of the interaction of native and acid-unfolded cyt c was investigated by stopped-flow tryptophan fluorescence. Formation of HL from the native state requires the disruption of the tightly packed hydrophobic core in the native protein. This micelle-induced unfolding of cyt c occurs at a rate 0.1 s1, which is remarkably faster in the lipid environment compared with the expected rate of unfolding in solution. Refolding of acid-unfolded cyt c with L-PG micelles involves an early highly helical collapsed state formed during the burst phase (<3 ms), and the observed main kinetic event reports on the opening of this early compact intermediate prior to insertion into the lipid micelle

Predicting Future Instance Segmentation by Forecasting Convolutional Features

Anticipating future events is an important prerequisite towards intelligent behavior. Video forecasting has been studied as a proxy task towards this goal. Recent work has shown that to predict semantic segmentation of future frames, forecasting at the semantic level is more effective than forecasting RGB frames and then segmenting these. In this paper we consider the more challenging problem of future instance segmentation, which additionally segments out individual objects. To deal with a varying number of output labels per image, we develop a predictive model in the space of fixed-sized convolutional features of the Mask R-CNN instance segmentation model. We apply the "detection head'" of Mask R-CNN on the predicted features to produce the instance segmentation of future frames. Experiments show that this approach significantly improves over strong baselines based on optical flow and repurposed instance segmentation architectures

Constraints of a pulsation frequency on stellar parameters in the eclipsing spectroscopic binary system: V577 Oph

We present a preliminary spectroscopic analysis of the binary system V577Oph, observed during the summer of 2007 on the 2.6m NOT telescope on La Palma. We have obtained time series spectroscopic observations, which show clear binary motion as well as radial velocity variations due to pulsation in the primary star. By modelling the radial velocities we determine a full orbital solution of the system, which yields M_A sin^3 i = 1.562 +/- 0.012 M_solar and M_B sin^3 i = 1.461 +/- 0.020 M_solar. An estimate of inclination from photometry yields a primary mass of 1.6 M_solar. Using this derived mass, and the known pulsation frequency we can impose a lower limit of 1 Gyr on the age of the system, and constrain the parameters of the oscillation mode. We show that with further analysis of the spectra (extracting the atmospheric parameters), tighter constraints could be imposed on the age, metallicity and the mode parameters. This work emphasizes the power that a single pulsation frequency can have for constraining stellar parameters in an eclipsing binary system.Comment: Accepted by A

A model for the interpretation of biofouling

The formation of biofilms on heat exchange surfaces was studied using water with Pseudomonas fluorescens as a contaminant and also a mixture of these bacteria and kaolin particles. In every case increasing the fluid velocity resulted in a decrease in the final amount of deposit and in the deposition rate . The effect of the fluid velocity was interpreted using a mathematical model and it was found that cell adhesion and reproduction were the fundamental processes controlling the deposition rate . The presence of inorganic particles in the deposit enhanced the biofilm growth rate . This result was explained by the differences in the structure of the fouling layers

Separation by thermal diffusion in a rotary column

A rotary thermal diffusion column with the inner cylinder rotating and the outer cylinder static was used to separate n-heptane-benzene mixtures at different speeds of rotation. The results show that the column efficiency depends on the speed of rotation. For the optimum speed the increase in efficiency relative to the static column was of the order of 8%. The role of the geometric irregularities in the annulus width on performance of the rotary column is also discussed.Calouste Gulbenkian Foundatio

Liquid thermal diffusion in a batch rotary column

Experimental observations of separation by thermal diffusion in rotary columns have been published, but no adequate theory to explain the column performance has been given. By consideration of the hydrodynamics within the annular space an approximate theory has been developed which shows that for a geometrically perfect column the relevant parameters affecting separation can be simply related to the corresponding static column. The relaxation-time and separation are virtually independent of the speed of rotation and separation values are more favourable for the rotary column. The application of the theory to non-perfect practical columns requires the consideration of the "equivalent annulus width" concept similar to the static case. Experimental tests conducted at different speeds of rotation in two geometrically different columns whose inner cylinder rotates and the outer is static, showed that the rotation at moderate speeds increased the equilibrium separation by about 7%, reducing, simultaneously the relaxation time by an average of 3%. These results are in good agreement with the theoretical predictions

Application of Neural Networks to the study of stellar model solutions

Artificial neural networks (ANN) have different applications in Astronomy, including data reduction and data mining. In this work we propose the use ANNs in the identification of stellar model solutions. We illustrate this method, by applying an ANN to the 0.8M$_\odot$ star CG Cyg B. Our ANN was trained using 60,000 different 0.8M$_\odot$ stellar models. With this approach we identify the models which reproduce CG Cyg B's position in the HR diagram. We observe a correlation between the model's initial metal and helium abundance which, in most cases, does not agree with a helium to metal enrichment ratio $\Delta$Y/$\Delta$Z=2. Moreover, we identify a correlation between the model's initial helium/metal abundance and both its age and mixing-length parameter. Additionally, every model found has a mixing-length parameter below 1.3. This means that CG Cyg B's mixing-length parameter is clearly smaller than the solar one. From this study we conclude that ANNs are well suited to deal with the degeneracy of model solutions of solar type stars.Comment: Accepted for publication in New Astronom

Information-theoretic determination of ponderomotive forces

From the equilibrium condition $\delta S=0$ applied to an isolated thermodynamic system of electrically charged particles and the fundamental equation of thermodynamics ($dU = T dS-(\mathbf{f}\cdot d\mathbf{r})$) subject to a new procedure, it is obtained the Lorentz's force together with non-inertial terms of mechanical nature. Other well known ponderomotive forces, like the Stern-Gerlach's force and a force term related to the Einstein-de Haas's effect are also obtained. In addition, a new force term appears, possibly related to a change in weight when a system of charged particles is accelerated.Comment: 10 page