DFT screened-exchange approach for investigating electronical properties of graphene-related materials

We present ab initio calculations of the bandstructure of graphene and of short zigzag graphene nanoribbons by the screened-exchange-LDA method (sX-LDA) within the framework of density functional theory (DFT). The inclusion of non-local electron-electron interactions in this approach results in a renormalization of the electronic bandstructure and the Fermi velocity compared to calculations within local density approximation (LDA) gives good agreement with experiment. Similarly, the band gaps in zigzag nanoribbons (ZGNR) are widened by more than 200%, being of similar magnitude than bandgaps from past studies based on quasiparticle bandstructures. We found a noticeable effect of non-local exchange on the spin-polarization of the electronic ground state of ZGNRs, compared to LDA and GGA-PW91 calculations.Comment: 5 pages, 3 figure

Hybrid functional calculations of the Al impurity in silica: Hole localization and electron paramagnetic resonance parameters

We performed first-principle calculations based on the supercell and cluster approaches to investigate the neutral Al impurity in smoky quartz. Electron paramagnetic resonance measurements suggest that the oxygens around the Al center undergo a polaronic distortion which localizes the hole being on one of the four oxygen atoms. We find that the screened exchange hybrid functional successfully describes this localization and improves on standard local density approaches or on hybrid functionals that do not include enough exact exchange such as B3LYP. We find a defect level at about 2.5 eV above the valence band maximum, corresponding to a localized hole in a O 2p orbital. The calculated values of the g tensor and the hyperfine splittings are in excellent agreement with experiment.Comment: 5 pages, 2 figures, 1 tabl

Frequentist Evaluation of Group Sequential Clinical Trial Designs

Group sequential stopping rules are often used as guidelines in the monitoring of clinical trials in order to address the ethical and efficiency issues inherent in human testing of a new treatment or preventive agent for disease. Such stopping rules have been proposed based on a variety of different criteria, both scientific (e.g., estimates of treatment effect) and statistical (e.g., frequentist type I error, Bayesian posterior probabilities, stochastic curtailment). It is easily shown, however, that a stopping rule based on one of those criteria induces a stopping rule on all other criteria. Thus the basis used to initially define a stopping rule is relatively unimportant so long as the operating characteristics of the stopping rule are fully investigated. In this paper we describe how the frequentist operating characteristics of a particular stopping rule might be evaluated in order to ensure that the selected clinical trial design satisfies the constraints imposed by the many different disciplines represented by the clinical trial collaborators

Bayesian Evaluation of Group Sequential Clinical Trial Designs

Clincal trial designs often incorporate a sequential stopping rule to serve as a guide in the early termination of a study. When choosing a particular stopping rule, it is most common to examine frequentist operating characteristics such as type I error, statistical power, and precision of confi- dence intervals (Emerson, et al. [1]). Increasingly, however, clinical trials are designed and analyzed in the Bayesian paradigm. In this paper we describe how the Bayesian operating characteristics of a particular stopping rule might be evaluated and communicated to the scientific community. In particular, we consider a choice of probability models and a family of prior distributions that allows concise presentation of Bayesian properties for a specified sampling plan

On the Use of Stochastic Curtailment in Group Sequential Clinical Trials

Many different criteria have been proposed for the selection of a stopping rule for group sequen- tial trials. These include both scientific (e.g., estimates of treatment effect) and statistical (e.g., frequentist type I error, Bayesian posterior probabilities, stochastic curtailment) measures of the evidence for or against beneficial treatment effects. Because a stopping rule based on one of those criteria induces a stopping rule on all other criteria, the utility of any particular scale relates to the ease with which it allows a clinical trialist to search for sequential sampling plans having de- sirable operating characteristics. In this paper we examine the use of such measures as conditional power and predictive power in the definition of stopping rules, especially as they apply to decisions to terminate a study early for “futility”. We illustrate that stopping criteria based on stochastic curtailment are relatively difficult to interpret on the scientifically relevant scale of estimated treat- ment effects, as well as with respect to commonly used statistical measures such as unconditional power. We further argue that neither conditional power nor predictive power adhere to the stan- dard optimality criteria within either the frequentist or Bayesian data analysis paradigms. Thus when choosing a stopping rule for “futility”, we recommend the definition of stopping rules based on other criteria and careful evaluation of the frequentist and Bayesian operating characteristics that are of greatest scientific and statistical relevance

Effects of digging by a native and introduced ecosystem engineer on soil physical and chemical properties in temperate grassy woodland

Temperate grasslands and woodlands are the focus of extensive restoration efforts worldwide. Reintroduction of locally extinct soil-foraging and burrowing animals has been suggested as a means to restore soil function in these ecosystems. Yet little is known about the physical and chemical effects of digging on soil over time and how these effects differ between species of digging animal, vegetation types or ecosystems. We compared foraging pits of a native reintroduced marsupial, the eastern bettong (Bettongia gaimardi) and that of the exotic European rabbit (Oryctolagus cuniculus). We simulated pits of these animals and measured pit dimensions and soil chemical properties over a period of 2 years. We showed that bettong and rabbit pits differed in their morphology and longevity, and that pits had a strong moderating effect on soil surface temperatures. Over 75% of the simulated pits were still visible after 2 years, and bettong pits infilled faster than rabbit pits. Bettong pits reduced diurnal temperature range by up to 25 ° C compared to the soil surface. We did not find any effects of digging on soil chemistry that were consistent across vegetation types, between bettong and rabbit pits, and with time since digging, which is contrary to studies conducted in arid biomes. Our findings show that animal foraging pits in temperate ecosystems cause physical alteration of the soil surface and microclimatic conditions rather than nutrient changes often observed in arid areas. © 2019 Ross et al. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Philip Barton” is provided in this record*

Breakthrough results in astrobiology: is ‘high risk’ research needed?

Astrobiology is a scientific endeavour involving great uncertainties. This could justify intellectual risk-taking associated with research that significantly deviates from the mainstream, to explore new avenues. However, little is known regarding the effect of such maverick endeavours. To better understand the need for more or less risk in astrobiology, we investigate to what extent high-risk / high-impact research contributes to breakthrough results in the discipline. We gathered a sample of the most impactful astrobiology papers of the past 20 years and explored the degree of risk of the research projects behind these papers via contact with the corresponding authors. We carried out interviews to explore how attitudes towards risk have played out in their work, and to ascertain their opinions on risk-taking in astrobiology. We show the majority of the selected breakthrough results derive from endeavours considered medium- or high-risk, risk is significantly correlated with impact, and most of the discussed projects adopt exploratory approaches. Overall, the researchers display a distribution of attitudes towards risk from the more cautious to the more audacious, and are divided on the need for more risk-taking in astrobiology. Our findings ultimately support the explicit implementation of a risk-balanced portfolio in astrobiology