Special issue : Computational intelligence models for image processing and information reasoning

Computational Intelligence (CI) models comprise robust computing methodologies with a high level of machine learning quotient. CI models, in general, are useful for designing computerized intelligent systems/machines that possess useful characteristics mimicking human behaviors and capabilities in solving complex tasks, e.g., learning, adaptation, and evolution. Examples of some popular CI models include fuzzy systems, artificial neural networks, evolutionary algorithms, multi-agent systems, decision trees, rough set theory, knowledge-based systems, and hybrid of these models. This special issue highlights how different computational intelligence models, coupled with other complementary techniques, can be used to handle problems encountered in image processing and information reasoning.

Putting families of origin into the queer picture : introducing this special issue

In undertaking our own separate research projects and in our crosscontinental comparative analyses of those projects, we became aware of the gaps between the richness of research on GLBT lives, including experiences of intimacy and parenthood, and the paucity of research on their relations with their families of origin. Still marginal is, in particular, research on the perspectives of the families of origin themselves: parents, but also siblings, grandparents, and other members of extended families. For the purposes of this special issue, we are deploying the term families of origin to mean heterosexual-identifying family members (at least as they publicly perform and display their sexualities), living within a heteronormative socio-politicocultural system. As we will argue in this introduction, however, there is a need to document and research, and thereby historically situate, family diversity, including the increasing shifting discourses and lived experiences of same-sex and other queer families of origin.

Application of the reporting entity concept and lodgement of special purpose financial statements

This Research Report analyses the application of the reporting entity concept and the adoption of special purpose financial reporting, particularly by entities lodging financial statements with the Australian Securities and Investments Commission (ASIC) and with state-based regulators in Australia’s three most populous states, namely, Consumer Affairs Victoria, NSW Fair Trading and Queensland Office of Fair Trading. This Report does not cover entities that have their equity interests traded in a public market, such as listed companies, and some other entities with ‘public accountability’.

Affective, linguistic and topic patterns in online autism communities

Online communities offer a platform to support and discuss health issues. They provide a more accessible way to bring people of the same concerns or interests. This paper aims to study the characteristics of online autism communities (called Clinical) in comparison with other online communities (called Control) using data from 110 Live Journal weblog communities. Using machine learning techniques, we comprehensively analyze these online autism communities. We study three key aspects expressed in the blog posts made by members of the communities: sentiment, topics and language style. Sentiment analysis shows that the sentiment of the clinical group has lower valence, indicative of poorer moods than people in control. Topics and language styles are shown to be good predictors of autism posts. The result shows the potential of social media in medical studies for a broad range of purposes such as screening, monitoring and subsequently providing supports for online communities of individuals with special needs.

Collaborating differently on different topics: a multi-relational approach to multi-task learning

Multi-task learning offers a way to benefit from synergy of multiple related prediction tasks via their joint modeling. Current multi-task techniques model related tasks jointly, assuming that the tasks share the same relationship across features uniformly. This assumption is seldom true as tasks may be related across some features but not others. Addressing this problem, we propose a new multi-task learning model that learns separate task relationships along different features. This added flexibility allows our model to have a finer and differential level of control in joint modeling of tasks along different features. We formulate the model as an optimization problem and provide an efficient, iterative solution. We illustrate the behavior of the proposed model using a synthetic dataset where we induce varied feature-dependent task relationships: positive relationship, negative relationship, no relationship. Using four real datasets, we evaluate the effectiveness of the proposed model for many multi-task regression and classification problems, and demonstrate its superiority over other state-of-the-art multi-task learning models

Sport consumer behavior research: improving our game

Sport consumer behavior (SCB) research continues to grow in both popularity and sophistication. A guiding principle in much of this research has focused on the nature of sport-related experiences and the benefits sport consumers derive from these experiences. This emphasis has generated new knowledge and insights into the needs and wants of sport consumers. Although these efforts have contributed to the field's understanding of SCB, the vast majority of this research has centered on psychological phenomena and the evaluative and affective components of these sport experiences. Approaches to this work have also narrowed, with SCB research predominately relying on cross-sectional studies and attitudinal surveys to collect information. This has resulted in limited findings that seldom account for how various situational or environmental factors might influence attitudinal data patterns at the individual and group level. This special issues seeks to deepen our understanding of SCB by providing seven papers that demonstrate or validate findings using multiple studies or data collections.

Atomically thin boron nitride: unique properties and applications

Atomically thin boron nitride (BN) is an important 2D nanomaterial, with many properties distinct from graphene. In this feature article, these unique properties and associated applications, often not feasible with graphene, are outlined. The article starts with characterization and identification of atomically thin BN. It is followed by demonstrating their strong oxidation resistance at high temperatures and applications in protecting metals from oxidation and corrosion. As flat insulators, BN nanosheets are ideal dielectric substrates for surface enhanced Raman spectroscopy (SERS) and electronic devices based on 2D heterostructures. The light emission of BN nanosheets in the deep ultraviolet (DUV) and ultraviolet (UV) regions is also included for its scientific and technological importance. The last part is dedicated to synthesis, characterization, and optical properties of BN nanoribbons, a special form of nanosheets.

Description of a new special of penicillate millipede from the genus monographis (diplopoda: polyxenidae) found in Vietnam

A new species of penicillate millipede, from genus Monographis (Diplopoda: Polyxenidae), was collected from Trang Bom and Dinh Quan, within the Dong Nai province, southern Vietnam. Taxonomic characteristics of the genus Monographis Attems, 1907, were used to formally describe this new species. Sensilla of the 6th antennal article and claw structures of Monographis dongnaiensis were compared with those of M. tamoyoensis, M. yunnanensis and M. queenslandicus. Genomic DNA of M. dongnaiensis was compared with the DNA of other species within the genus Monographis. Monographis dongnaiensis is confirmed as the ninth member of the genus Monographis and named Monographis dongnaiensis after the collection site Dong Nai province in Vietnam.

A prospective cohort study of antipsychotic medications in pregnancy: the first 147 pregnancies and 100 one year old babies

BACKGROUND: Many women diagnosed with varying psychiatric disorders take antipsychotic medications during pregnancy. The safety of antipsychotic medications in pregnancy is largely unknown.

METHODS: We established the National Register of Antipsychotic Medications in Pregnancy in 2005. Women who are pregnant and taking an antipsychotic medication are interviewed every 6 weeks during pregnancy and then followed until their babies are one year old. The baby's progress is closely followed for the first year of life.

FINDINGS: As of April 18 2012, 147 pregnancies had been followed through to completion. There were 142 live births and data is available for 100 one year old babies. 18% of babies were born preterm, with a higher dose of antipsychotic medication correlating to an increased likelihood of premature delivery; 43% of babies required special care nursery or intensive care after birth; 37% had any degree of respiratory distress and 15% of babies developed withdrawal symptoms. Congenital anomalies were seen in eight babies. Most pregnancies resulted in the birth of live, healthy babies. The use of mood stabilisers or higher doses of antipsychotics during pregnancy increased the likelihood of babies experiencing respiratory distress or admission to Special Care Nursery or Neonatal Intensive Care Units.

CONCLUSION: There is a great need for safety and efficacy information about the use of antipsychotic medications in pregnancy. Live, healthy babies are the most common outcome following the use of antipsychotic medication in pregnancy, but clinicians should be particularly mindful of neonatal problems such as respiratory distress.

Religion, sustainable development and policy: principles to practice

The nexus between religion and development is now well recognized in scholarship but the implications for development policies are relatively unexplored. The challenge with analysing religion as a policy construct is to ensure that its rich anthropological dimensions are not lost, but rather that these inform the conception and implementation of development planning, especially in diverse, multireligious societies. The aim of this special issue is to unpack the complex anthropological, sociological and even theological dimensions of religion that can enable development policymakers to identify the ways in which religion shapes the society, the environment and the economy. Therein also lie the opportunities to articulate policies that are truly responsive to serious structural issues of inequalities and oppressions. The authors address five foci that are central to sustainable development policymaking – urbanization and spatial equality; gender justice; environment and human/animal tensions; economic growth; and postsecularity and governance.

Influence of fuel-borne oxygen on European stationary cycle: diesel engine performance and emissions with a special emphasis on particulate and NO emissions

Exploration of sustainable fuels and their influence on reductions in diesel emissions are nowadays a challenge for the engine and fuel researchers. This study investigates the role of fuel-borne oxygen on engine performance and exhaust emissions with a special emphasis on diesel particulate and nitric oxide (NO) emissions. A number of oxygenated-blends were prepared with waste cooking biodiesel as a base oxygenated fuel. Triacetin, a derivative from transesterified biodiesel was chosen for its high oxygen content and superior fuel properties. The experimental campaign was conducted with a 6-cylinder, common rail turbocharged diesel engine equipped with highly precise instruments for nano and other size particles and other emissions. All experiments were performed in accordance with European Stationary Cycle (ESC 13-mode). A commercial diesel was chosen as a reference fuel with 0% oxygen and five other oxygenated blends having a range of 6.02–14.2% oxygen were prepared. The experimental results revealed that the oxygenated blends having higher a percentage of fuel-borne oxygen reduced particulate matter (PM), particle number (PN), unburned hydrocarbon (UBHC) and carbon monoxide (CO) emissions to a significantly low level with a slight penalty of NO emissions. The main target of this study was to effectively utilise triacetin as an additive for waste cooking biodiesel and suppress emissions without deteriorating engine performance. The key finding of this investigation is the significant reductions in both particle mass and number emissions simultaneously without worsening engine performance with triacetin-biodiesel blends. Reductions in both particle mass and number emissions with a cost-effective additive would be a new dimension for the fuel and engine researchers to effectively use triacetin as an emission suppressor in the future.

Queer pedagogies out of place and time: redrawing the boundaries of youth, sexual and gender difference, and education

For this contribution to the "Cartographies" section of the special issue on "Mapping Queer Bioethics," the author focuses on the concept of spatialized time as made material in the location of historical places, in particular as it relates to a reconsideration of approaches to Australian queer/LGBT youth education. Accordingly, the author employs historical maps as illustrative examples of spatialized time, reflecting on the relationships between historical knowledge and queer youth education.

Editorial for IEEE access special section on theoretical foundations for big data applications : challenges and opportunities

Big data is one of the hottest research topics in science and technology communities, and it possesses a great application potential in every sector for our society, such as climate, economy, health, social science, and so on. Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, and manage. We can conclude that big data is still in its infancy stage, and we will face many unprecedented problems and challenges along the way of this unfolding chapter of human history.