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Leveraging metatranscriptomics for the characterisation of bovine blood viromes.
Full text linkUnderstanding the diversity of the bovine virome is essential for assessing their potential impact on cattle health and transmission risks. Viruses present in the blood comprise both those that establish persistent infections in blood cells and those present during transient viremia. Farm management practices, such as the reuse of syringes for treatments, vaccinations, and supplements, may inadvertently contribute to the spread of blood-borne pathogens, emphasizing the need for improved biosecurity measures. Herein, we used a metatranscriptomic approach to analyse 20 bovine blood transcriptomes from dairy cows in New South Wales, Australia, along with 577 publicly available blood transcriptomes from studies in Australia and Kenya. Our analysis identified several viruses that are known to infect blood cells, transmitted either by direct contact or by vectors, including bovine viral diarrhea virus, bovine gammaherpesvirus 6, hepacivirus, foamy virus, ephemeroviruses and a new species of a coltivirus. Our findings highlight the complexity of the bovine blood virome and underscore the importance of sustained surveillance to identify emerging pathogens and assess their potential role in cattle health. This study provides a framework for integrating transcriptomic data into disease monitoring efforts, ultimately contributing to improved cattle management and biosecurity practices
Clinical evaluation of an artificial intelligence (AI) model for rare sperm detection in testis biopsies and azoospermic semen for ICSI
No full textAbstract Study question Does an artificial intelligence (AI)-based image detection model improve the speed and accuracy of identifying rare sperm in testis biopsies and azoospermic semen for ICSI? Summary answer AI sperm detection aids embryologists in finding more sperm in a shorter period. What is known already Non-obstructive azoospermia (NOA) is a form of severe male-factor infertility, affecting nearly 5% of infertile couples seeking treatment. Isolating sperm from macerated testicular tissue for intracytoplasmic sperm injection (ICSI) has changed marginally in the last two decades and requires embryologists to manually search through a background of obstructing collateral cells including red blood cells (RBC’s), white blood cells (WBC’s), leydig, sertoli and epithelial cells, causing fatigue and reducing sample coverage. Image analysis using AI presents itself as a candidate to dramatically reduce processing times in both surgical and non-surgical sperm cases. Study design, size, duration This multi-site, pilot clinical study consists of side-by-side testing of sperm searching with and without the aid of AI for rare sperm detection from a live-camera feed beside an inverted ICSI microscope over 12 months. The AI model was trained on a wide spectrum of sample types, and testing was performed to observe the effect of a reduction in search time on the clinical outcomes of severe male-factor cases. Participants/materials, setting, methods Azoospermic patients (N = 22) at two clinics attending for surgical sperm collection or extended sperm search of their ejaculate, consented to the use of the AI model for their treatment, including using the sperm found by both the AI-assisted embryologist and the unassisted embryologist for ICSI. Time taken per dish and number of live (usable) sperm was recorded as well as all subsequent embryology data. Main results and the role of chance AI-assisted sperm searching significantly reduced the time required to locate individual sperm and complete dish searches. The AI group required less time per sperm found compared to unassisted embryologists (2.8 ± 1.7 mins vs. 7.5 ± 4.0 mins, P = 0.0025). Similarly, the time per dish searched was significantly shorter with AI assistance (21.8 ± 8.6 mins vs. 35.7 ± 16.0 mins, P < 0.0001). Although more sperm were identified with AI assistance, the difference was not statistically significant (4.4 ± 1.4 sperm vs. 2.5 ± 0.8 sperm, P = 0.25). Notably, in three cases, embryos were created exclusively from AI-detected sperm (with no embryos resulting from embryologist-identified sperm), achieving a recent live-birth. Limitations, reasons for caution This is a pilot study to test the clinical utility of a novel sperm AI detection tool, which is undergoing continuous optimization. The highest quality sperm were selected for injection irrespective of which method they were found by. A larger number of samples across multiple indications is required. Wider implications of the findings AI-powered image analysis has the potential for seamless integration into laboratory workflows to reduce time to identify and isolate sperm from azoospermic samples by at least 50%, and do this with improved accuracy, thus reducing physical burden on embryologists, logistical burden on clinics and emotional burden on patients. Trial registration number N
Quantum Coherent Systems for Ground-State Problems
No full textThis paper offers a perspective on solving groundstate problems in quantum chemistry using a quantum coherent system Typically such issues are addressed with Variational Quantum Algorithms VQAs which rely on classical optimization to update the parameters iteratively Using the Quantum Stochastic Differential Equations QSDEs framework we design a quantum system that evolves toward a steady state solution corresponding to the ground state of the Hamiltonian Unlike VQAs this approach eliminates the reliance on classical optimization Moreover our method naturally expresses Hamiltonians in terms of annihilation and creation operators solving the problem directly without requiring a transformation into the Ising model This approach is further validated in our numerical simulations which demonstrate the feasibility of the QSDE based approach providing a promising solution for ground state preparatio
Electronic Wastes and Circular Economy A Path towards Sustainable Management
No full textThis chapter discusses the complex relationship between circular economy principles and electronic waste (e-waste) management. In the past decades, the electronics industry has grown fast. E-waste from many consumer electronic products adversely impacts human health, the environment, and an animal's well-being. This chapter discusses all the detrimental effects of e-waste, focusing primarily on pollution caused by inappropriate elimination methods. The primary focus of this chapter is how the circular economy is transforming traditional ideas regarding e-waste management. Fundamental principles of the circular economy, such as design for longevity, repairability, and recyclability, are scrutinized in the context of electronics. Drawing on case studies from diverse global initiatives, the chapter highlights successful models that have embraced circular practices, offering tangible solutions to mitigate the negative externalities associated with e-waste. Furthermore, the chapter addresses the challenges impeding the widespread adoption of circular practices in the electronics sector, examining both economic and environmental considerations. It underscores the critical roles of policymakers, manufacturers, and consumers in surmounting these challenges and fostering a paradigm shift toward circularity. The conclusion of the study consolidates the primary discoveries, highlighting the imperative nature of transitioning towards a circular economy in order to guarantee sustainable management of e-trash. The chapter finishes by making a persuasive appeal for collective action, encouraging individuals, businesses, and politicians to actively participate in fostering a more sustainable and healthier future through the adoption of circular practices within the electronics industry. This chapter offers a thorough examination of e-trash, presenting a guide for stakeholders to traverse the intricate aspects of this issue effectively. The chapter offers valuable perspectives on adopting a more sustainable and resilient strategy within e-waste management
Unusual Distal Leg Presentation of Morel-Lavallée Lesion: Case Report with Review of Diagnostic and Management Strategies
No full textA Morel-Lavallée lesion is a rare post-traumatic closed degloving injury defined by chronic fluid collection between subcutaneous tissue and fascia. We report a case involving a 42-year-old immunocompromised man with persistent swelling of the right leg after a fall 18 months earlier. The lesion was fluctuant and mildly tender, with no skin changes. Ultrasound revealed a complex cystic mass (6.6 × 4.2 × 1.0 cm) in the deep subcutaneous plane, raising suspicion for a Morel-Lavallée lesion. MRI confirmed a fluid collection overlying the fascia near the ankle. Orthopedic evaluation recommended percutaneous aspiration and compressive bandaging for 4–6 weeks to close the dead space, with surgery reserved for refractory cases. This report highlights the need to recognize Morel-Lavallée lesions long after trauma, as early identification prevents mismanagement. We also review the prevalence, diagnostic challenges, and management options for this condition
ENTANGLEMENTS: EMPLACED, TRANSNATIONAL AND TRANSCULTURAL TRAJECTORIES IN LIFE-WRITING BY ITALIAN-AUSTRALIAN WOMEN
Full text linkIn this study, I explore how engaging with autobiographical writings by Italian-Australian women has allowed me to reflect on my own emplaced, transnational and transcultural trajectory. Through a combination of archival research, textual analysis and personal narrative, I trace my encounter with a rich, though often overlooked, corpus of autobiographical writings that emerged in community contexts – particularly through literary contests organized by the National Italian-Australian Women’s Association – which resulted in the publication of two books of short stories: Give Me Strength (1989) and Growing up Italian in Australia (1993). Drawing on concepts such as ‘locational feminism’ and ‘transduction’, particularly as examined by Jasmina Lukic (2023), I consider how these texts speak across time and place, and how they resonate with my own experience as a scholar, writer and Italian-Australian woman and mother. I analyse these stories in search not of a fixed historical truth, but of what Nina Lykke foregrounds as ‘poetic truth’: a form of knowing that reverberates across subjectivities in the form of a resonance. This essay merges creative and academic writing and is grounded in a desire to read, share and amplify the vibrant, collective voices of translingual and migrant women
Spatio-Temporal Multivariate Probabilistic Modeling for Traffic Prediction
No full textTraffic prediction is an essential task in intelligent transportation systems dealing with complex and dynamic spatio-temporal correlations. To date, most work is focused on point estimation models, which only output a single value w.r.t an attribute of traffic data at a time, falling short of depicting diverse situations and uncertainty in future. Besides, most methods are not flexible enough to handle real complex traffic scenarios, involving missing values and non-uniformly sampled data. The interactions among different attributes of traffic data are also rarely explored explicitly. In this paper, we focus on probabilistic estimation in traffic prediction tasks, proposing a spatio-temporal multivariate probabilistic predictive model to estimate the distributions of traffic data. Specifically, we devise a multivariate spatio-temporal fusion graph block to extract spatio-temporal correlations of multiple traffic attributes at different locations. A multi-graph fusion module is designed to capture time-varying spatial relationships. We estimate the joint distributions of missing traffic data using copulas. The proposed model can simultaneously perform traffic forecasting and interpolation tasks with non-uniformly sampled data. Our experiments on two real-world traffic datasets demonstrate the advantages of our model over the state-of-the-art1</sup
Multi-objective optimization of an ammonia-fueled micro planar combustor with a secondary oxygen injection for thermophotovoltaic applications
No full textIn order to address the issue about the multi-objective optimization of an ammonia-fueled micro planar combustor with a secondary oxygen injection for thermophotovoltaic applications, in this work, response surface methodology (RSM), non-dominated sorting genetic algorithm II (NSGA-II), entropy weight method (EWM) and technique for order preference by similarity to an ideal solution (TOPSIS) are combined. Firstly, the volumetric flow rate (VNH3), secondary oxygen injection ratio (Φ) and secondary oxygen injection position (L6) are selected as the design variables, and the total energy output of MTPV system (Qtot), total energy output efficiency of MTPV system (ηMTPV) and NO mole fraction at the outlet (γNO) are chosen as objection functions. Subsequently, the Box-Behnken design is utilized to arrange numerical investigations. With the obtained results, RSM and NSGA-II is combined to obtain Pareto frontier solutions. Finally, TOPSIS with EWM is used to select the optimal solution from the Pareto frontier solutions. The optimal Qtot, ηMTPV and γNO is 8.83 W, 7.17 % and 0.0139, respectively, and the corresponding design variable VNH3, Φ and L6 are 582.43 mL/min, 15.14 % and 11.68 mm, respectively
Ethical AI for sustainable development: User perceptions across the United Nations Sustainable Development Goals
Full text linkArtificial intelligence is rapidly transforming technology in society and is increasingly seen as a critical tool for addressing complex global challenges, including the United Nations Sustainable Development Goals. These seventeen goals, grouped into societal, economic, and environmental domains, present both opportunities and risks when intersecting with artificial intelligence. While artificial intelligence has the capacity to accelerate sustainable development, it may also exacerbate inequalities, environmental degradation, or other unintended harms if ethical concerns are not adequately addressed. Despite a growing body of research on ethical frameworks for artificial intelligence, there remains a lack of empirical understanding of how users perceive its potential, its ethical implications, and the principles that should guide its deployment in sustainable development contexts. It is natural to raise the questions: How do Sustainable Development Goals and goal groups affect these user perceptions? To answer these questions, we conducted a comprehensive human-subject study examining variations in user perceptions across 17 Sustainable Development Goals and three overarching goal groups. Our findings reveal substantial variation in perceived potential and ethical priorities depending on the specific goal, while the perceived importance of ethical considerations remains consistent across goal groups. The novelty of this study lies in combining the AI–SDG context with empirical and perception-based evidence, and our results highlight the necessity of incorporating user perspectives into the design and governance of artificial intelligence systems to ensure ethically aligned and socially accepted progress toward sustainable development
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