The white dwarf cooling sequence of NGC 6791: a unique tool for stellar evolution

NGC 6791 is a well-studied, metal-rich open cluster that is so close to us that can be imaged down to luminosities fainter than that of the termination of its white dwarf cooling sequence, thus allowing for an in-depth study of its white dwarf population. We use a Monte Carlo simulator that employs up-to-date evolutionary cooling sequences for white dwarfs with hydrogen-rich and hydrogen-deficient atmospheres, with carbon-oxygen and helium cores. The cooling sequences for carbon-oxygen cores account for the delays introduced by both Ne^22 sedimentation in the liquid phase and by carbon-oxygen phase separation upon crystallization. We do not find evidence for a substantial fraction of helium-core white dwarfs, and hence our results support the suggestion that the origin of the bright peak of the white dwarf luminosity function can only be attributed to a population of unresolved binary white dwarfs. Moreover, our results indicate that the number distribution of secondary masses of the population of unresolved binaries has to increase with increasing mass ratio between the secondary and primary components of the progenitor system. We also find that the observed cooling sequence appears to be able to constrain the presence of progenitor sub-populations with different chemical compositions and the fraction of non-DA white dwarfs. Our simulations place interesting constraints on important characteristics of the stellar populations of NGC 6791. In particular, we find that the fraction of single helium-core white dwarfs must be smaller than 5%, that a sub-population of stars with zero metallicity must be <12%, while if the adopted metallicity of the sub-population is solar the upper limit is ~8%. Finally, we also find that the fraction of non-DA white dwarfs in this particular cluster is surprinsingly small <6%.Comment: 9 pages, 14 figures, accepted for publication in Astronomy & Astrophysic

Outer boundary conditions for evolving cool white dwarfs

White dwarf evolution is essentially a gravothermal cooling process, which,for cool white dwarfs, sensitively depends on the treatment of the outer boundary conditions. We provide detailed outer boundary conditions appropriate for computing the evolution of cool white dwarfs employing detailed non-gray model atmospheres for pure H composition. We also explore the impact on the white dwarf cooling times of different assumptions for energy transfer in the atmosphere of cool white dwarfs. Detailed non-gray model atmospheres are computed taken into account non-ideal effects in the gas equation of state and chemical equilibrium, collision-induced absorption from molecules, and the Lyman alpha quasi-molecular opacity. Our results show that the use of detailed outer boundary conditions becomes relevant for effective temperatures lower than 5800 and 6100K for sequences with 0.60 and 0.90 M_sun, respectively. Detailed model atmospheres predict ages that are up to approx 10% shorter at log L/L_sun=-4 when compared with the ages derived using Eddington-like approximations at tau_Ross=2/3. We also analyze the effects of various assumptions and physical processes of relevance in the calculation of outer boundary conditions. In particular, we find that the Ly_alpha red wing absorption does not affect substantially the evolution of white dwarfs. White dwarf cooling timescales are sensitive to the surface boundary conditions for T_eff < 6000K. Interestingly enough, non-gray effects have little consequences on these cooling times at observable luminosities. In fact, collision-induced absorption processes, which significantly affect the spectra and colors of old white dwarfs with hydrogen-rich atmospheres, have not noticeable effects in their cooling rates, except throughout the Rosseland mean opacity.Comment: 6 pages, 9 figures, to be published in Astronomy and Astrophysic

Communication: Site-selective bond excision of adenine upon electron transfer

This work demonstrates that selective excision of hydrogen atoms at a particular site of the DNA base adenine can be achieved in collisions with electronegative atoms by controlling the impact energy. The result is based on analysing the time-of-flight mass spectra yields of potassium collisions with a series of labeled adenine derivatives. The production of dehydrogenated parent anions is consistent with neutral H loss either from selective breaking of C–H or N–H bonds. These unprecedented results open up a new methodology in charge transfer collisions that can initiate selective reactivity as a key process in chemical reactions that are dominant in different areas of science and technology

Size determination and quantification of engineered cerium oxide nanoparticles by flow field-flow fractionation coupled to inductively coupled plasma mass spectrometry

Facing the lack of studies on characterization and quantification of cerium oxide nanoparticles (CeO2 NPs), whose consumption and release is greatly increasing, this work proposes a method for their sizing and quantification by Flow Field-flow Fractionation (FFFF) coupled to Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Two modalities of FFFF (Asymmetric Flow- and Hollow Fiber-Flow Field Flow Fractionation, AF4 and HF5, respectively) are compared, and their advantages and limitations discussed. Experimental conditions (carrier composition, pH, ionic strength, crossflow and carrier flow rates) are studied in detail in terms of NP separation, recovery, and repeatability. Size characterization of CeO2 NPs was addressed by different approaches. In the absence of feasible size standards of CeO2 NPs, suspensions of Ag, Au, and SiO2 NPs of known size were investigated. Ag and Au NPs failed to show a comparable behavior to that of the CeO2 NPs, whereas the use of SiO2 NPs provided size estimations in agreement to those predicted by the theory. The latter approach was thus used for characterizing the size of CeO2 NPs in a commercial suspension. Results were in adequate concordance with those achieved by transmission electron microscopy, X-ray diffraction and dynamic light scattering. The quantification of CeO2 NPs in the commercial suspension by AF4-ICP-MS required the use of a CeO2 NPs standards, since the use of ionic cerium resulted in low recoveries (99 ± 9% vs. 73 ± 7%, respectively). A limit of detection of 0.9 µg L-1 CeO2 corresponding to a number concentration of 1.8 × 1012 L-1 for NPs of 5 nm was achieved for an injection volume of 100 µL

Time-to-birth prediction models and the influence of expert opinions

Preterm birth is the leading cause of death among children under five years old. The pathophysiology and etiology of preterm labor are not yet fully understood. This causes a large number of unnecessary hospitalizations due to high--sensitivity clinical policies, which has a significant psychological and economic impact. In this study, we present a predictive model, based on a new dataset containing information of 1,243 admissions, that predicts whether a patient will give birth within a given time after admission. Such a model could provide support in the clinical decision-making process. Predictions for birth within 48 h or 7 days after admission yield an Area Under the Curve of the Receiver Operating Characteristic (AUC) of 0.72 for both tasks. Furthermore, we show that by incorporating predictions made by experts at admission, which introduces a potential bias, the prediction effectiveness increases to an AUC score of 0.83 and 0.81 for these respective tasks

Induced molecular dissociations as a radiation damage descriptor: nanodosimetry

Conferencia invitada; IBER 2015, 6-9th September, Aveiro – Portugal; http://iber2015.web.ua.pt/Traditional dosimetry is based on the proportionality between the energy absorbed by the medium (absorbed dose) and the induced damage. This assumption applies for relatively high irradiated volumes and requires some equilibrium conditions. However, for small volumes being relatively far from the central irradiated areas these conditions are not observed and radiation damage is mainly driven by low energy secondary species (electrons and radicals) which induce molecular dissociations via electronic and vibrational excitations, electron attachment and chemical reactions. We will present here an integrated modelling procedure to simulate particle radiation tracks including those of all generated secondary species and their further interactions with the molecular constituent of the medium. For any selected volume of interest, this model provides not only the total energy transferred to that area but also the number and type of interactions taking place in it [1].Peer Reviewe

A critical look at studies applying over-sampling on the TPEHGDB dataset

Preterm birth is the leading cause of death among young children and has a large prevalence globally. Machine learning models, based on features extracted from clinical sources such as electronic patient files, yield promising results. In this study, we review similar studies that constructed predictive models based on a publicly available dataset, called the Term-Preterm EHG Database (TPEHGDB), which contains electrohysterogram signals on top of clinical data. These studies often report near-perfect prediction results, by applying over-sampling as a means of data augmentation. We reconstruct these results to show that they can only be achieved when data augmentation is applied on the entire dataset prior to partitioning into training and testing set. This results in (i) samples that are highly correlated to data points from the test set are introduced and added to the training set, and (ii) artificial samples that are highly correlated to points from the training set being added to the test set. Many previously reported results therefore carry little meaning in terms of the actual effectiveness of the model in making predictions on unseen data in a real-world setting. After focusing on the danger of applying over-sampling strategies before data partitioning, we present a realistic baseline for the TPEHGDB dataset and show how the predictive performance and clinical use can be improved by incorporating features from electrohysterogram sensors and by applying over-sampling on the training set