Ground and excited states Gamow-Teller strength distributions of iron isotopes and associated capture rates for core-collapse simulations

This paper reports on the microscopic calculation of ground and excited states Gamow-Teller (GT) strength distributions, both in the electron capture and electron decay direction, for $^{54,55,56}$Fe. The associated electron and positron capture rates for these isotopes of iron are also calculated in stellar matter. These calculations were recently introduced and this paper is a follow-up which discusses in detail the GT strength distributions and stellar capture rates of key iron isotopes. The calculations are performed within the framework of the proton-neutron quasiparticle random phase approximation (pn-QRPA) theory. The pn-QRPA theory allows a microscopic \textit{state-by-state} calculation of GT strength functions and stellar capture rates which greatly increases the reliability of the results. For the first time experimental deformation of nuclei are taken into account. In the core of massive stars isotopes of iron, $^{54,55,56}$Fe, are considered to be key players in decreasing the electron-to-baryon ratio ($Y_{e}$) mainly via electron capture on these nuclide. The structure of the presupernova star is altered both by the changes in $Y_{e}$ and the entropy of the core material. Results are encouraging and are compared against measurements (where possible) and other calculations. The calculated electron capture rates are in overall good agreement with the shell model results. During the presupernova evolution of massive stars, from oxygen shell burning stages till around end of convective core silicon burning, the calculated electron capture rates on $^{54}$Fe are around three times bigger than the corresponding shell model rates. The calculated positron capture rates, however, are suppressed by two to five orders of magnitude.Comment: 18 pages, 12 figures, 10 table

In-vitro application of pentoxifylline preserved ultrastructure of spermatozoa after vitrification in asthenozoospermic patients

Abstract PURPOSE: To evaluate the effect of in vitro application of pentoxifylline (PX) on sperm parameters and ultrastructure after vitrification in asthenozoospermic patients. MATERIALS AND METHODS: A total of 30 asthenozoospermic semen samples (aged 25-45 years) were divided into four groups before vitrification, after vitrification, control (without PX) and experimental (with PX). In experimental group, each sample was exposed for 30 min to 3.6mmol/l PX and the control group without any treatment apposing in 370C for 30 min. After incubation, the samples were washed and analyzed again. Vitrification was done according to straw method. Eosin-nigrosin and Papanicolaou staining were applied for assessment of sperm viability and morphology, respectively. The samples without PX and post treatment with PX were assessed by transmission electron microscopy (TEM). RESULTS: A significant decrease in sperm motility (P ≤ .001), morphology (11.47 ± 2.9 versus 6.73 ± 2.01) and viability (73.37 ± 6.26 versus 54.67 ± 6.73) was observed post vitrification, but sperm motility (19.85 ± 4.75 versus 32.07 ± 5.58, P ≤ .001) was increased significantly following application of PX. This drug had no significant (P >.05) detrimental neither negative effect on ultrastructure acrosome, plasma membrane and coiled tail statues of spermatozoa. CONCLUSION: Vitrification had detrimental effects on sperm parameters, but PX reversed detrimental effects on sperm motility. However, PX had no alteration on ultrastructure morphology of human spermatozoa after vitrification

Deep learnability: using neural networks to quantify language similarity and learnability

Learning a second language (L2) usually progresses faster if a learner's L2 is similar to their first language (L1). Yet global similarity between languages is difficult to quantify, obscuring its precise effect on learnability. Further, the combinatorial explosion of possible L1 and L2 language pairs, combined with the difficulty of controlling for idiosyncratic differences across language pairs and language learners, limits the generalisability of the experimental approach. In this study, we present a different approach, employing artificial languages and artificial learners. We built a set of five artificial languages whose underlying grammars and vocabulary were manipulated to ensure a known degree of similarity between each pair of languages. We next built a series of neural network models for each language, and sequentially trained them on pairs of languages. These models thus represented L1 speakers learning L2s. By observing the change in activity of the cells between the L1-speaker model and the L2-learner model, we estimated how much change was needed for the model to learn the new language. We then compared the change for each L1/L2 bilingual model to the underlying similarity across each language pair. The results showed that this approach can not only recover the facilitative effect of similarity on L2 acquisition, but can also offer new insights into the differential effects across different domains of similarity. These findings serve as a proof of concept for a generalisable approach that can be applied to natural languages

Empirical Formulae Evaluation for Hydraulic Conductivity Determination Based on Grain Size Analysis

Seven empirical formulae to calculate hydraulic conductivity using grain size distribution of unconsolidated aquifer materials have been evaluated in this study. Four soil samples extracted from an injection or recharge well during borehole drilling aimed at recharging the ground water through rainwater harvesting in Lahore Pakistan. The sample testing and grading analysis were done in CEWRE, UET Lahore soil laboratory. Results showed that out of seven empirical formulae three formulae (Kozeny-Carman, Hazen and Breyer) reliably estimated hydraulic conductivities of the various soil samples well within the known ranges while the others four formulae Slitcher, Terzaghi, USBR, Alyamani & Sen methods underestimated the results as compared to constant head method results for all samples. Kozeny-Carman Equation proved to be the best estimator of most samples analyzed, and maybe, even for a wide range of other soil types. This best estimation is followed by Hazen and Breyer formula after Kozeny-Carman formula. Most importantly, all these empirical formulae are to be used strictly within their domains of applicability

Fine-Grid Calculations for Stellar Electron and Positron Capture Rates on Fe-Isotopes

The acquisition of precise and reliable nuclear data is a prerequisite to success for stellar evolution and nucleosynthesis studies. Core-collapse simulators find it challenging to generate an explosion from the collapse of the core of massive stars. It is believed that a better understanding of the microphysics of core-collapse can lead to successful results. The weak interaction processes are able to trigger the collapse and control the lepton-to-baryon ratio ($Y_{e}$) of the core material. It is suggested that the temporal variation of $Y_{e}$ within the core of a massive star has a pivotal role to play in the stellar evolution and a fine-tuning of this parameter at various stages of presupernova evolution is the key to generate an explosion. During the presupernova evolution of massive stars, isotopes of iron, mainly $^{54,55,56}$Fe, are considered to be key players in controlling $Y_{e}$ ratio via electron capture on these nuclide. Recently an improved microscopic calculation of weak interaction mediated rates for iron isotopes was introduced using the proton-neutron quasiparticle random phase approximation (pn-QRPA) theory. The pn-QRPA theory allows a microscopic \textit{state-by-state} calculation of stellar capture rates which greatly increases the reliability of calculated rates. The results were suggestive of some fine-tuning of the $Y_{e}$ ratio during various phases of stellar evolution. Here we present for the first time the fine-grid calculation of the electron and positron capture rates on $^{54,55,56}$Fe. Core-collapse simulators may find this calculation suitable for interpolation purposes and for necessary incorporation in the stellar evolution codes.Comment: 21 pages, 6 ps figures and 2 table

Dislocation dipoles and the nucleation of cracks in silicon nanopillars

To understand the brittle to ductile transtion at small scale in silicon nanopillars, plastic deformation of silicon nanopillars was investigated by atomistic simulations. Perfect dislocations were found to be nucleated from surfaces and nano cavities were evidenced resulting from dislocation dipoles annihilation. The formation of such cavities is consistent with previous atomistic calculations showing that the annihilation of dislocation vacancy dipole of perfect shuffle dislocations is associated to the formation of vacancy clusters in silicon and diamond [1]. In nanopillars such cavities contribute to the nucleation of cracks [2]. This mechanism of crack nucleation is relevant to single slip deformation and does not require any interactions between dislocations issued from intersecting glide planes as usually postulated for crack nucleation [3]. Incipient dipoles were also found nucleated on the glide plane swept by dislocations. These incipient dipoles result from bond flips and are similar to the Stone–Wales defects in graphene [4]. These defects could be similar and related to the “dislocations trails” found in the glide plane of dislocations in other deformation conditions, a long time and rather unsolved problem in silicon (see for example [5]). Under the applied stress those incipient dipoles appear to act as new nucleation centers for dislocations located in the glide plane. Those dislocations contribute to dislocation interactions in parallel slip planes and to the formation of nano cracks following the described above mechanism

Mendelian randomization case-control PheWAS in UK Biobank shows evidence of causality for smoking intensity in 28 distinct clinical conditions.

Background: Smoking is one of the greatest threats to public health worldwide. We integrated phenome-wide association study (PheWAS) and Mendelian randomization (MR) approaches to explore causal effects of genetically predicted smoking intensity across the human disease spectrum. Methods: We conducted PheWAS case-control analyses in 152,483 ever smokers of White-British ancestry, aged 39-73 years. Disease diagnoses were based on hospital inpatient and mortality registrations. Smoking intensity was instrumented by four genetic variants, and disease risks estimated for one cigarette per day heavier intakes. Associations passing the FDR threshold (p<0•0025) were assessed for causality using several complementary MR approaches. Findings: Genetically instrumented smoking intensity was associated with 48 conditions, with MR supporting a possible causal effect for 28 distinct outcomes. Each cigarette smoked per day elevated the odds of respiratory diseases by 5% to 33% (nine distinct diseases, including pneumonia, emphysema, obstructive chronic bronchitis, pleurisy, pulmonary collapse, respiratory failure) and the odds of circulatory disease by 5% to 23% (seven diseases, including atherosclerosis, myocardial infarction, congestive heart failure, arterial embolisms). Further effects were seen for cancer within the respiratory system and other neoplasms, renal failure, septicaemia, and retinal disorders. No associations were observed in sensitivity analyses on 185,002 never smokers. Interpretation: These genetic data demonstrate the substantial adverse health impacts by smoking intensity and suggest notable increases in the risks of several diseases. Public health initiatives should highlight the damage caused by smoking intensity and the potential benefits of reducing or ideally quitting smoking