Recombination activity of iron-gallium and iron-indium pairs in silicon

The recombination activity of iron-gallium (FeGa) and iron-indium (FeIn) pairs in crystalline silicon is studied by means of injection-dependent carrier lifetime measurements on Fe-implanted, Ga- and In-doped p-type silicon wafers of different resistivities (0.3–15Ωcm). Compared to FeB pairs, FeGa and FeIn pairs are found to be much more effective recombination centers in p-type silicon. Using Shockley–Read–Hall statistics we determine the energy level Et of the FeGa-related center to be 0.20eV above the valence-band edge Eν. The strong recombination activity of FeGa is assigned to its large electron-capture cross section σn of 4×10⁻¹⁴cm². The hole-capture cross section σp is 2×10⁻¹⁴cm². For the FeIn-related recombination center, our measurements show that Et=Eν+0.15eV, σn=3.5×10⁻¹³cm², and σp=1.5×10⁻¹⁴cm². Strong illumination with white light is found to dissociate both types of pairs. Storage of the samples in the dark leads to a full repairing of FeGa and FeIn pairs. Lifetime changes measured before and after illumination can be used to determine the interstitialiron concentration in Ga- and In-doped silicon using calibration factors determined from the measured defect parameters.J.S. thanks A. Cuevas and A. Blakers for their hospitality during his research stay at ANU and acknowledges the financial support of the Alexander von Humboldt Foundation. D.M. acknowledges the financial support of the Australian Research Council

Issues affecting Security Design Pattern engineering

Security Design Patterns present the tried and tested design decisions made by security engineers within a well documented format. Patterns allow for complex security concepts, and mechanisms, to be expressed such that non domain experts can make use of them. Our research is concerned with the development of pattern languages for advanced crypto-systems. From our experience developing pattern languages we have encountered several recurring issues within security design pattern engineering. These issues, if not addressed, will affect the adoption of security design patterns. This paper describes these issues and discusses how they could be addressed.Publisher PD

Security pattern evaluation

Current Security Pattern evaluation techniques are demonstrated to be incomplete with respect to quantitative measurement and comparison. A proposal for a dynamic testbed system is presented as a potential mechanism for evaluating patterns within a constrained environment.Postprin

What's the PREMES behind your pattern?

Design patterns are supposed to be the well documented, tried and tested solutions to recurrent problems. Current evaluation techniques do not provide a demonstrable and holistic means to evaluate pattern quality. This paper introduces Pattern Report Cards an evaluation process for software design patterns that is demonstrable, measurable, and reproducible. A set of quality indicators for determining pattern quality has been identified, and a set of qualitative and quantitative evaluation techniques assembled to determine the quality of adherence to these indicators. Further, management and execution of the evaluation process is controlled by the PREMES framework. This framework describes a management cycle that facilitates the construction of bespoke evaluation systems for design patterns. Process tailoring is achieved by providing guidance over the selection and construction of the techniques used to assess pattern quality. Use of these techniques will help bolster existing evaluation processes, and lead to the improvement of design pattern evaluation techniques.Postprin

Physical activity in the lives of young women and men: embodied identies

The purpose of this paper is to explore the complex and diverse positions particular young women and men take up in relation to the moral imperatives of the healthism discourse. We do this through a discussion of the ways in which they talk about their own and others’ bodies, in the context of a number of in-depth interviews conducted with them over the course of a year. These interviews were conducted as the major component of a longitudinal qualitative study, funded by the Australian Research Council, which investigates the place and meaning of physical activity and physical culture in young people’s lives

Hydrodynamic Simulations of the Interaction between an AGB Star and a Main Sequence Companion in Eccentric Orbits

The Rotten Egg Nebula has at its core a binary composed of a Mira star and an A-type companion at a separation >10 au. It has been hypothesized to have formed by strong binary interactions between the Mira and a companion in an eccentric orbit during periastron passage ~800 years ago. We have performed hydrodynamic simulations of an asymptotic giant branch star interacting with companions with a range of masses in orbits with a range of initial eccentricities and periastron separations. For reasonable values of the eccentricity, we find that Roche lobe overflow can take place only if the periods are <<100 years. Moreover, mass transfer causes the system to enter a common envelope phase within several orbits. Since the central star of the Rotten Egg nebula is an AGB star, we conclude that such a common envelope phase must have lead to a merger, so the observed companion must have been a tertiary companion of a binary that merged at the time of nebula ejection. Based on the mass and timescale of the simulated disc formed around the companion before the common envelope phase, we analytically estimate the properties of jets that could be launched. Allowing for super-Eddington accretion rates, we find that jets similar to those observed are plausible, provided that the putative lost companion was relatively massive.Comment: accepted for publication in MNRA

Let's Enhance: A Deep Learning Approach to Extreme Deblurring of Text Images

This work presents a novel deep-learning-based pipeline for the inverse problem of image deblurring, leveraging augmentation and pre-training with synthetic data. Our results build on our winning submission to the recent Helsinki Deblur Challenge 2021, whose goal was to explore the limits of state-of-the-art deblurring algorithms in a real-world data setting. The task of the challenge was to deblur out-of-focus images of random text, thereby in a downstream task, maximizing an optical-character-recognition-based score function. A key step of our solution is the data-driven estimation of the physical forward model describing the blur process. This enables a stream of synthetic data, generating pairs of ground-truth and blurry images on-the-fly, which is used for an extensive augmentation of the small amount of challenge data provided. The actual deblurring pipeline consists of an approximate inversion of the radial lens distortion (determined by the estimated forward model) and a U-Net architecture, which is trained end-to-end. Our algorithm was the only one passing the hardest challenge level, achieving over $70\%$ character recognition accuracy. Our findings are well in line with the paradigm of data-centric machine learning, and we demonstrate its effectiveness in the context of inverse problems. Apart from a detailed presentation of our methodology, we also analyze the importance of several design choices in a series of ablation studies. The code of our challenge submission is available under https://github.com/theophil-trippe/HDC_TUBerlin_version_1.Comment: This article has been published in a revised form in Inverse Problems and Imagin