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Campylobacter hepaticus and Spotty Liver Disease in Poultry
No full textSpotty liver disease is an economically important, emerging disease that primarily impacts the cage-free poultry layer industry. While this disease remains understudied, several important findings have been reported in the last 5 yr that warrant an updated review of the field. These include updated cost estimates of disease, insights into the molecular biology of the causative agent, the identification of a second bacterium responsible for disease production, insights into disease epidemiology and interventions, and the generation of new molecular tools for further study.</p
Development of Reactive and Self-Cleaning Layered Double Hydroxide Membranes for Advanced Water Treatment
No full textMicropollutants are synthetic chemicals or naturally occurring compounds found in the environment at very low concentrations, often in the microgram or nano-gram per litre range, which create trouble for their persistence, bioaccumulation, and potential toxicity. The presence of micropollutants in water and wastewater has emerged as a major public health concern, particularly due to their frequent detection in wastewater treatment plant effluents. Ranitidine, a competitive inhibitor of histamine H2 receptors, has been identified as an emerging micropollutant in water and wastewater, raising concerns about its potential impact on the environment and human health. In addition to micropollutants, conventional WWTPs face challenges in managing microplastics (MPs). While MPs are partially removed, WWTPs often release smaller-sized plastics, contributing to the fragmentation of MPs into nanoplastics (NPs). These NPs (This study also developed a CoFe layered double hydroxide (CoFeLDH) catalytic membrane for PMS activation to achieve efficient micropollutant removal with improved mass transfer rate and reaction kinetics. The CoFeLDH membrane/PMS system achieved an impressive degradation efficiency above 98% degradation of the probe chemical ranitidine at 0.1 mM of PMS including five more micropollutants (Sulfamethoxazole, Ciprofloxacin, Carbamazepine, Acetaminophen and Bisphenol A) at satisfactory level (above 80%). Moreover, significant improvements in water flux and antifouling properties were observed, marking the membrane as a specific advancement in the removal of membrane fouling in water purification technology. The membrane demonstrated consistent degradation efficiency for several micropollutants and across a range of pH (4–9) as well as different anionic environments, thereby showing it suitability for scale-up application. The key role of reactive species such as SO4•–, and O2•− radicals in the degradation process was elucidated. This is followed by the confirmation of the occurrence of redox cycling between Co and Fe, and the presence of CoOH+ that promotes PMS activation. Over the ten cycles, the membrane could be operated with a flux recovery of up to 99.8% and maintained efficient performance over 24 h continuous operation. The efficiency in degrading micropollutants, was coupled with reduced metal leaching for this membrane. Furthermore, a CoFe layered double hydroxide (CoFeLDH) membrane incorporating the metal–organic framework (MOF) MIL(1 0 0)Fe, was tailored for a PMS based system. Among various combinations of MOF and LDH nanosheets on a PVDF substrate, the highest water flux, reaching 1900 L/m2/hr/bar, was achieved with an LDH/MOF ratio of 5:1 and an MOF concentration of 0.025 M. The optimized membrane exhibited exceptional performance, achieving 99 % degradation of ranitidine at 0.1 mM PMS. The LDH MOF catalytic membrane exhibited excellent treatment performance in real water matrices and demonstrated long-term operational efficiency. The effective removal of ranitidine by this catalytic membrane was attributed to a synergistic combination of radical (SO4•– and •OH) and non-radical (singlet 1O2 and electron transfer O2) oxidation pathways, with SO4•– and singlet 1O2 playing a predominant role. Post-activation, 40 % of surface Co2+ and 65 % of Fe2+ in the LDH MOF membrane were found in the + III oxidation state, highlighting the significance of metal catalytic sites and the reusability potential of the membrane. The durability of the membrane was evident through 10 cycles, achieving a flux recovery ratio of 95 % in the first cycle and sustaining efficient performance across pH variations (3 to 9) and exposure to various anions. Importantly, negligible metal leaching was observed for the real water samples, ensuring suitability for large-scale applications. After that, a novel hybrid CoFe layered metal oxide (CoFeLMO) membrane was developed by integrating MIL(100)Fe and polyethylene glycol (PEG), designed specifically for peroxymonosulfate (PMS)-based advanced oxidation processes. The uniqueness of this research lies in the innovative incorporation of LMO, MOF, and PEG nanosheets onto a polyethersulfone (PES) substrate, creating a highly efficient catalytic membrane for the simultaneous removal of pharmaceutical micropollutants and nanoplastics (NPs).Among various configurations, the LMO-MOF-PEG membrane, with 20% MOF (0.025 M) and 0.5 g of PEG, demonstrated superior performance, achieving remarkable removal efficiencies of 99.5% for ranitidine and 98.5% for NPs. This membrane also exhibited outstanding operational efficiency, achieving a flux of 1600 L/m²/hr/bar at a low PMS concentration of 0.2 mM. The degradation of ranitidine was driven by both reactive species (SO4•–, •OH and O2•-) and non-reactive species (singlet 1O2), with SO4•– playing a dominant role. Post-activation analysis revealed the presence of Co²⁺ and Fe²⁺ in both +II and +III oxidation, indicating the active participation of metal plots in the degradation process and confirming the membrane's reusability. The membrane demonstrated exceptional durability, maintaining a flux recovery ratio of 97-99% across 10 filtration cycles, even under harsh chemical conditions and across a wide pH range (2-12). Furthermore, Co leaching was minimal (2-21 µg/L) over a broad pH spectrum, even after 15 days of immersion in water. Lastly, the addition of covalent organic framework (COF) with LMO improved the membrane separation capabilities (100% for ranitidine) and durability. Overall, the findings suggest that this membrane proves to be a suitable choice for attaining high degradation efficiency and good stability in the remediation of micropollutants and NPs from wastewater. In summary, these studies present groundbreaking and innovative strategies for wastewater treatment, introducing new nanomaterials and membranes that significantly enhance the removal of various micropollutants and NPs. These advancements play a vital role in addressing key issues related to environmental pollution and water resource management. Various novel membranes have been developed through combining different nanomaterials, specifically designed to interact more effectively with oxidant and the types of the micropollutants. This approach leads to substantial improvements in both the removal efficiency and fouling resistance of the membrane.</p
Structural Variations Arrangement
No full textResearch background Presented at the George Paton Gallery, University of Melbourne, and curated by Channon Goodwin and Sandra Bridie, the exhibition transformed the gallery into a reading room combining contemporary submissions with archival material from earlier GPG book shows. Cruickshank exhibited Structural Variations Arrangement, a collection of book forms testing size and binding types, utilising coloured binding glue, various paper stocks and reflexive covers featuring the production processes.Research contribution Extends Cruickshank’s publishing‑as‑method by situating book structures within a public, reading environment, testing how display conventions, access and perusal shape reception and meaning. The GPG brief explicitly foregrounded books as artworks to be browsed, although these examples contained no text but could nevertheless be 'read' as objects.Research significance GPG is a long‑standing, institutionally supported experimental space (est. 1974) with a documented history in artists’ books; inclusion in the curated #4 iteration places the work within that lineage and a large cross‑section of Australian practitioners.</p
Variations between, and within, jurisdictions in the use of community treatment orders and other compulsory community treatment: study of 402 060 people across four Australian states
No full textBackground The use of compulsory community treatment (CCT) in Australia is some of the highest worldwide despite limited evidence of effectiveness. Even within Australia, use varies widely across jurisdictions despite general similarities in legislation and health services. However, there is much less information on whether variation occurs within the same jurisdiction. Aims To measure variations in the use of CCT in a standardised way across the following four Australian jurisdictions: Queensland, South Australia, New South Wales (NSW) and Victoria. We also investigated associated sociodemographic variables. Methods We used aggregated administrative data from the Australian Institute of Health and Welfare. Results There were data on 402 060 individuals who were in contact with specialist mental health services, of whom 51 351 (12.8%) were receiving CCT. Percentages varied from 8% in NSW to 17.6% in South Australia. There were also wide variations within jurisdictions. In NSW, prevalence ranged from 2% to 13%, in Victoria from 6% to 24%, in Queensland from 11% to 25% and in South Australia from 6% to 36%. People in contact with services who were male, single and aged between 25 and 44 years old were significantly more likely to be subject to CCT, as were people living in metropolitan areas or those born outside Oceania. Conclusions There are marked variations in the use of CCT both within and between Australian jurisdictions. It is unclear how much of this variation is determined by clinical need and these findings may be of relevance to jurisdictions with similar clinician-initiated orders.</p
Anti-Violence Human Resource Management and Workplace Violence: Perspectives From Australian Aged Care Managers and Employees
No full textIncidents of workplace violence are commonplace against nurses and personal care assistants (PCAs) employed in aged care facilities. This article examines ways in which managers and human resource (HR) departments manage workplace violence. In this context, understanding anti-violence human resource management (HRM) practices and other ways in which incidents of violence are managed may have important implications for workforce sustainability. Greenwood and Freeman's [Greenwood, M., & Freeman, R. E. (2011). Ethics and HRM: The Contribution of Stakeholder Theory. Business & Professional Ethics Journal, 269–292.] conceptual model of employee engagement and “ethical” HRM underpins this study by focusing on stakeholder engagement and stakeholder agency. We take a qualitative approach to examine workplace violence in aged care facilities in Australia by conducting semi-structured interviews with 60 participants. We report on narratives of participants highlighting the unethical use of HRM as evidenced by a lack of anti-violence HRM in aged care facilities. To encourage greater workforce sustainability, we argue that HR departments and managers need to behave ethically and better support the management and mitigation of workplace violence against workers in aged care facilities. Our paper provides new theoretical and practical insights into understanding the role of stakeholder engagement and stakeholder agency, and the moral treatment of employees through the development of anti-violence HRM within the aged care context.</p
Artificial Intelligence in Demand Planning for German Electric Vehicle Supply Chains
No full textDemand planning (DP) is a core function in supply chain management that involves forecasting market demand, preparing the supply chain to meet that demand, and enhancing overall performance. In recent years, artificial intelligence (AI) technologies have received considerable attention in academic and management literature for their utility in DP for innovative products. Enigmatically however, the industry adoption rate of AI in DP is still low in supply chains. Hence, this research investigates AI adoption in DP in the context of manufacturing SMEs (MSMEs) in the electric vehicle (EV) industry, manufacturing highly innovative products. This study aims to develop a framework to investigate drivers and enablers for AI implementation in DP for innovative products with limited historical data, like EV and their components. Set in Germany, the study is underpinned by resource orchestration theory (ROT) to explain how structuring, assembling and utilising firm resources impact AI adoption. We posit that AI adoption in DP creates value in supply chain and thus increases firm performance. This research employs a deductive-inductive approach developing an a priori conceptual framework through in-depth literature review. The framework is then expanded and explored through empirical investigation from 11 case studies in 25 semi-structured interviews. Analysis of findings reveal four key themes (orchestration of AI resources, catalyst for AI adoption, performance gains and value creation through AI adoption, and supply chain orientation in EV manufacturing) with 13 second order elements of AI adoption in DP. Furthermore, the findings were validated using three groups of respondents that are instrumental in shaping decision making in EV SC: manufacturing SME, specialised consultants, and industry organisations.Findings suggest that acquiring and accumulating relevant resources such as AI knowledge, cloud platforms, and integrated data platforms allows MSMEs to create AI capabilities. Acquisition of resources through external AI consultants and AI platform providers is the dominant form to structure resources. However, we find concurrent accumulation through industry networks and training is essential to internalise resources and create permanent capabilities. Supported by a management focus on supply chain orientation, acquisition and accumulation of resources leads to performance gains along financial, operational, supply chain structural, and digital transformation elements. Our findings also suggest that AI adoption needs a catalyst, amid competing investment alternatives for MSME. This catalyst can be external or internal to the firm and materialises as supply chain-specific, data-specific, or planning process-specific elements.This research contributes to theory by investigating factors – including factors that may explain the relationship between digitised technology adoption and value creation through application of supply chain orientation concepts in resources orchestration. It expands ROT by identifying a new theme that may drive the resource orchestration process as catalyst in the context of AI technology adoption. For practitioners and industry, by developing a framework for AI adoption in DP, this research provides a structured approach to resource allocation in developing digitised capabilities that enable the implementation of AI-based DP into their existing systems and thus overcome the barriers that lead to low AI adoption currently observed in the industry. This research as several limitations which provide an opportunity for future research. Findings are developed in the context of MSME in German EV supply chains, which might limit their applicability to these context parameters. Whilst we have addressed transferability concerns in the research design, future research could test our findings, also empirically, in the context of other countries or industries. Further, this research largely ignores cognitive constructs like trust in DP, opening an opportunity for further research. Trust concepts are of particular interest in the context of AI applications in DP and the explainability of machine generated planning outcomes.</p
System and Method for Predicting the Future
No full textWork created under pseudonym Antoinette J. Citizen.Over six months, Citizen systematically documented her activities, emotional states, location, and social interactions at 15-minute intervals. This dataset forms the foundation for an algorithmic system that generates predictions about her future behaviour.The installation, exhibited at the Gallery of Modern Art, Brisbane, comprises an automated x-y plotting system that continuously inscribes predictions for Citizen throughout the exhibition period. The system typically forecasts events 30-60 minutes in advance of their predicted occurrence.</p
Covert Policing and Coerced Confessions: Australia Needs a New Test for the Admissibility of ‘Mr Big Confessions’
No full textIn 2007, the High Court examined the use of the so-called ‘Mr Big Method’ in Australia. The Mr Big Method is a covert policing method where police officers establish a fictitious criminal enterprise. The aim of this operation is to induce a confession from a suspect. To achieve this, undercover officers groom the suspect into becoming a member of their ‘gang’. The undercover officers offer inducements such as money and fictitious job opportunities, causing the suspect to believe that a membership of the ‘gang’ would provide safety and a financially secure future. Although the High Court permitted the use of this method, concerns have been raised by scholars and foreign courts over the last decade. This article will discuss the Mr Big Method, criticisms of this method and its application in Australia. It is argued that the admissibility of these confessions should be subject to a new test to minimise the risk of coerced confessions and consequential wrongful convictions.</p
I need husband: AI beauty standards, fascism and the proliferation of bot driven content
No full textGenerative AI is proliferating on social media at an alarming rate. Images are generated and disseminated with political agendas, particularly in right-wing spheres. These AI-generated images often depict soldiers, sad children, or interior designs. Of particular note are the catfishing-style “I need husband” posts featuring women with impossible proportions, ostensibly seeking partners. These chimeric creations are bot-driven posts designed to farm engagement, but they also hint at something more sinister. These posts reflect a mechanical view of the male gaze. However, an AI cannot truly comprehend the male gaze, and in its attempt to mimic it, it creates beings beyond understanding. This research aims to analyze the patterns in these images, explore posting methods and engagement, and examine the meaning behind the images. It culminates in an artistic piece in progress critiquing both the images and their creation and dissemination methods. By rendering these AI-generated images as classical Greek statues through Gaussian splatting and 3D printing, I aim to create a visual commentary on the intersection of AI, the male gaze and fascism. This artistic approach not only highlights the absurdity of these digital constructs but also invites viewers to critically examine AI’s role in shaping contemporary perceptions of beauty and gender roles.</p
A sensor for fresh food and less waste
No full textThe reports from Food Bank Australia reveal that, in 2024 alone, 3.4 million households ran out of food. At the same time, food wastage in the country is approximately 7.6 million tonnes per year. Unfortunately,70% of this wasted food is actually edible. One of the main reasons is food packets past their expiry date, especially meat packets, are tossed even when they are perfectly safe. This food wastage also leads to emission of 17.6 million tonnes of carbon dioxide annually. Currently researchers are focusing on finding a reliable alternative to expiry dates. As a part of my PhD project, I am trying to fabricate a sensor to track meat spoilage. When meat begins to spoil, some gases like ammonia, hydrogen sulphide, are released due to microbial reactions. A sensor attached to the meat packet detects these gases and changes colour, indicating that it is unsafe to eat.</p