Good secrets, bad secrets : disclosure in children’s picture books about sexual child abuse

Well over 50 picture books have been published for children on the topic of sexual child abuse (Lampert & Walsh, 2010) many with the aim of teaching their very young readers how to tell the difference between good and bad secrets. This paper looks at three recent picture books for how they focus on disclosure as an end point.

On robust face recognition via sparse encoding : the good, the bad, and the ugly

In the field of face recognition, Sparse Representation (SR) has received considerable attention during the past few years. Most of the relevant literature focuses on holistic descriptors in closed-set identification applications. The underlying assumption in SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such assumption is easily violated in the more challenging face verification scenario, where an algorithm is required to determine if two faces (where one or both have not been seen before) belong to the same person. In this paper, we first discuss why previous attempts with SR might not be applicable to verification problems. We then propose an alternative approach to face verification via SR. Specifically, we propose to use explicit SR encoding on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which are then concatenated to form an overall face descriptor. Due to the deliberate loss spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment & various image deformations. Within the proposed framework, we evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN), and an implicit probabilistic technique based on Gaussian Mixture Models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the proposed local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, in both verification and closed-set identification problems. The experiments also show that l1-minimisation based encoding has a considerably higher computational than the other techniques, but leads to higher recognition rates.

Why new media reforms are bad news for Australian content

Two of the government’s six media reform bills passed in the House of Representatives with multi-party support on Tuesday 19 March. While most attention and debate has focused on the regulation of the news media and ownership, the changes approved on 19 March are both significant and far-reaching.

Privacy : bad for your health?

TO THE EDITOR: In Australia, personal and health information that identifies an individual cannot be used or disclosed for research without specific requirements being met.1 Even if these requirements are met, data custodians may still refuse access if their views are discordant with those of the relevant human research ethics committee (HREC). It is now evident that there are adverse consequences of this well-meaning legislation...

The Good, the Bad and the Efficient : Productivity, efficiency and technical change in the Airline Industry, 2004:2008

This study models the joint production of desirable and undesirable output production (that is, CO2 emissions) of airlines. The Malmquist-Luenberger productivity index is employed to measure productivity growth when undesirable output production is regulated and unregulated. The results show that pollution abatement activities of airlines lowers productivity growth which suggests the traditional approach of measuring productivity growth, which ignores CO2 emissions, overstate "true" productivity growth.

Bad apples, bad barrel: Exploring institutional responses to child sexual abuse by Catholic clergy in Australia

This paper considers constructions of institutional culture and power in the cover-up of child sexual abuse (CSA) by clergy in the Roman Catholic Church of Australia. The issue of cover-up has previously been considered in international inquiries as an institutional failing that has caused significant harm to victims of CSA by Catholic Clergy. Evidence given by select representatives of the Catholic Church in two government inquiries into institutional abuse carried out in Australia is considered here. This evidence suggests that, where cover-up has occurred, it has been reliant on the abuse of institutional power and resulted in direct emotional, psychological and spiritual harm to victims of abuse. Despite international recognition of cover-up as institutional abuse, evidence presented by Roman Catholic Representatives to the Victorian Inquiry denied there was an institutionalised cover-up. Responding to this evidence, this paper queries whether the primary foundation of cover-up conforms to the ‘bad apple theory’ in that it relates only to a few individuals, or the ‘bad barrel theory’ of institutional structure and culture.

Chemotherapeutic compounds targeting the DNA double-strand break repair pathways : the good, the bad, and the promising

The repair of DNA double-strand breaks (DSBs) is a critical cellular mechanism that exists to ensure genomic stability. DNA DSBs are the most deleterious type of insult to a cell’s genetic material and can lead to genomic instability, apoptosis, or senescence. Incorrectly repaired DNA DSBs have the potential to produce chromosomal translocations and genomic instability, potentially leading to cancer. The prevalence of DNA DSBs in cancer due to unregulated growth and errors in repair opens up a potential therapeutic window in the treatment of cancers. The cellular response to DNA DSBs is comprised of two pathways to ensure DNA breaks are repaired: homologous recombination and non-homologous end joining. Identifying chemotherapeutic compounds targeting proteins involved in these DNA repair pathways has shown promise as a cancer therapy for patients, either as a monotherapy or in combination with genotoxic drugs. From the beginning, there have been a number of chemotherapeutic compounds that have yielded successful responses in the clinic, a number that have failed (CGK-733 and iniparib), and a number of promising targets for future studies identified. This review looks in detail at how the cell responds to these DNA DSBs and investigates the chemotherapeutic avenues that have been and are currently being explored to target this repair process.

Governing prostitution: Differentiating the bad from the bad

Accounts of the governance of prostitution have typically argued that prostitutes are, in one way or another, stigmatised social outcasts. There is a persistent claim that power has operated to dislocate or banish the prostitute from the community in order to silence, isolate, hide, restrict, or punish. I argue that another position may be tenable; that is, power has operated to locate prostitution within the social. Power does not operate to 'desocialise' prostitution, but has in recent times operated increasingly to normalise it. Power does not demarcate prostitutes from the social according to some binary mechanics of difference, but works instead according to a principle of differentiation which seeks to connect, include, circulate and enable specific prostitute populations within the social. In this paper I examine how prostitution has been singled out for public attention as a sociopolitical problem and governed accordingly. The concept of governmentality is used to think through such issues, providing, as it does, a non-totalising and non-reductionist account of rule. It is argued that a combination of self-regulatory and punitive practices developed during modernity to manage socially problematic prostitute populations.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Bad Eggs

Synopsis and review of the Australian feature film Bad Eggs, directed by Tony Martin.

Videogames: Dispelling myths and tabloid headlines that videogames are bad

Videogamers are often portrayed as adolescent overweight males eating fast food in their bedroom, and videogames often blamed in the media for violent crime, obesity, social isolation and depression. However videogaming is a mainstream activity. In Australia 65% of the population play videogames (Digital Australia 2014), and humanity as a species play about 3 billion hours of videogames a week. This paper dispels the myths and sensationalised negative tabloid headlines that videogames are bad by presenting the latest research showing that videogames can help fight depression, improve brain function and stimulate creativity; that gamers have higher levels of family closeness and better attachment to school; and that videogames help boys and young men to relax, cope and socialise. Children and adolescents deliberately choose to play videogames in the knowledge that they will feel better as a result, and videogame play allow players to express themselves in ways they may not feel comfortable doing in real life because of their appearance, gender, sexuality, and/or age. The potential benefits of videogames to the individual and to society are yet to be fully realised. However already videogames are helping many gamers to flourish in life.

The good, the bad, and the efficient: Productivity, efficiency, and technical change in the airline industry, 2004–11

This study models the joint production of desirable and undesirable output production (that is, CO2 emissions) of airlines. The Malmquist–Luenberger productivity index is employed to measure productivity growth when undesirable output production is incorporated into the production model. The results show that pollution abatement activities of airlines lowers productivity growth, which suggests that the traditional approach of measuring productivity growth, which ignores CO2 emissions, overstates ‘true’ productivity growth. The reliability of the results is also tested and verified using confidence intervals based on bootstrapping.

Automatic surveillance in transportation hubs: No Longer just about catching the bad guy

As critical infrastructure such as transportation hubs continue to grow in complexity, greater importance is placed on monitoring these facilities to ensure their secure and efficient operation. In order to achieve these goals, technology continues to evolve in response to the needs of various infrastructure. To date, however, the focus of technology for surveillance has been primarily concerned with security, and little attention has been placed on assisting operations and monitoring performance in real-time. Consequently, solutions have emerged to provide real-time measurements of queues and crowding in spaces, but have been installed as system add-ons (rather than making better use of existing infrastructure), resulting in expensive infrastructure outlay for the owner/operator, and an overload of surveillance systems which in itself creates further complexity. Given many critical infrastructure already have camera networks installed, it is much more desirable to better utilise these networks to address operational monitoring as well as security needs. Recently, a growing number of approaches have been proposed to monitor operational aspects such as pedestrian throughput, crowd size and dwell times. In this paper, we explore how these techniques relate to and complement the more commonly seen security analytics, and demonstrate the value that can be added by operational analytics by demonstrating their performance on airport surveillance data. We explore how multiple analytics and systems can be combined to better leverage the large amount of data that is available, and we discuss the applicability and resulting benefits of the proposed framework for the ongoing operation of airports and airport networks.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.