Swinburne University of Technology

About: Swinburne University of Technology is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Galaxy & Population. The organization has 7223 authors who have published 25530 publications receiving 667955 citations. The organization is also known as: Swinburne Technical College & Swinburne College of Technology.

Nano-structured antimicrobial surfaces: From nature to synthetic analogues.

Abstract: The scientific and industrial interest in antimicrobial surfaces has significantly increased in recent times. This interest is largely in response to the persistent microbial contamination of industrial and, importantly, medical implant surfaces. Bacterial contamination of implant surfaces often leads to infection at the implant-tissue interface, and with the prevalence of increasing levels of antimicrobial resistance, the treatment of these infections is becoming far more challenging. Recently, many naturally occurring, high-aspect-ratio surface topographies have been discovered that exhibit high levels of biocidal efficacy. These include epicuticular lipid nano-architectures that are formed on the surfaces of insect wings, such as cicadae and dragonflies. The antimicrobial activity of such surfaces has been found to be a consequence of the physical interactions between the nanoscale topography of the substrate and the attaching pathogenic cells, meaning that the activity is independent of biochemical surface functionality. Importantly, these desirable surface properties can be translated to synthetic biomimetic surfaces, which, when mimicked, lead to a substantial increase in the antimicrobial properties of such surfaces. This paper reviews the recent advances in understanding the basis of these mechanical antimicrobial mechanisms, and discusses the progress being made towards the fabrication of optimised, biocompatible, synthetic analogues.

Semi-analytic galaxy evolution (sage): model calibration and basic results

Abstract: This paper describes a new publicly available codebase for modelling galaxy formation in a cosmological context, the "Semi-Analytic Galaxy Evolution" model, or SAGE for short. SAGE is a significant update to that used in Croton et al. (2006) and has been rebuilt to be modular and customisable. The model will run on any N-body simulation whose trees are organised in a supported format and contain a minimum set of basic halo properties. In this work we present the baryonic prescriptions implemented in SAGE to describe the formation and evolution of galaxies, and their calibration for three N-body simulations: Millennium, Bolshoi, and GiggleZ. Updated physics include: gas accretion, ejection due to feedback, and reincorporation via the galactic fountain; a new gas cooling--radio mode active galactic nucleus (AGN) heating cycle; AGN feedback in the quasar mode; a new treatment of gas in satellite galaxies; and galaxy mergers, disruption, and the build-up of intra-cluster stars. Throughout, we show the results of a common default parameterization on each simulation, with a focus on the local galaxy population.

Software Vulnerability Detection Using Deep Neural Networks: A Survey

Abstract: The constantly increasing number of disclosed security vulnerabilities have become an important concern in the software industry and in the field of cybersecurity, suggesting that the current approaches for vulnerability detection demand further improvement. The booming of the open-source software community has made vast amounts of software code available, which allows machine learning and data mining techniques to exploit abundant patterns within software code. Particularly, the recent breakthrough application of deep learning to speech recognition and machine translation has demonstrated the great potential of neural models’ capability of understanding natural languages. This has motivated researchers in the software engineering and cybersecurity communities to apply deep learning for learning and understanding vulnerable code patterns and semantics indicative of the characteristics of vulnerable code. In this survey, we review the current literature adopting deep-learning-/neural-network-based approaches for detecting software vulnerabilities, aiming at investigating how the state-of-the-art research leverages neural techniques for learning and understanding code semantics to facilitate vulnerability discovery. We also identify the challenges in this new field and share our views of potential research directions.

ALMA spectroscopic survey in the Hubble ultra deep field: survey description

Abstract: We present the rationale for and the observational description of ASPECS: the ALMA SPECtroscopic Survey in the Hubble Ultra-Deep Field (UDF), the cosmological deep field that has the deepest multi-wavelength data available. Our overarching goal is to obtain an unbiased census of molecular gas and dust continuum emission in high-redshift (z > 0.5) galaxies. The ~1' region covered within the UDF was chosen to overlap with the deepest available imaging from the Hubble Space Telescope. Our ALMA observations consist of full frequency scans in band 3 (84–115 GHz) and band 6 (212–272 GHz) at approximately uniform line sensitivity (L’_(CO) ~ 2 × 10^9 K km s^(−1) pc^2), and continuum noise levels of 3.8 μJy beam^(−1) and 12.7 μJy beam^(−1), respectively. The molecular surveys cover the different rotational transitions of the CO molecule, leading to essentially full redshift coverage. The [C II] emission line is also covered at redshifts 6.0 < z < 8.0. We present a customized algorithm to identify line candidates in the molecular line scans and quantify our ability to recover artificial sources from our data. Based on whether multiple CO lines are detected, and whether optical spectroscopic redshifts as well as optical counterparts exist, we constrain the most likely line identification. We report 10 (11) CO line candidates in the 3 mm (1 mm) band, and our statistical analysis shows that <4 of these (in each band) are likely spurious. Less than one-third of the total CO flux in the low-J CO line candidates are from sources that are not associated with an optical/NIR counterpart. We also present continuum maps of both the band 3 and band 6 observations. The data presented here form the basis of a number of dedicated studies that are presented in subsequent papers.