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A protocol for a scoping review of variations among psychedelic interventions for psychological suffering associated with the end-of-life
No full textPsychedelic substances are increasingly recognized for their therapeutic potential to ease psychological suffering linked to end-of-life issues. However, amid renewed scientific and public interest, policy remains restrictive. Existing reviews have made progress in synthesizing the results of studies of psychedelic interventions, especially psilocybin, and particularly with regard to their outcomes related to anxiety and depression, long-term effects and safety. Despite this progress, a wide range of both substances (such as ayahuasca, psilocybin, ketamine) and therapeutic approaches (such as psychedelics alone, or psychotherapy assisted with a psychedelic) in the use of psychedelic interventions specifically for end-of-life populations, has not been adequately covered by reviews to date. The aim of this scoping review is to identify and learn from the variety of psychedelic substances and therapeutic approaches that exists within the research on therapeutic psychedelic interventions reported in populations coping with psychological suffering associated with life-threatening illness and the end of life itself. We will follow Arksey and O’Malley’s (2005) framework for scoping reviews while incorporating updated methodological guidance. The Preferred Reporting Items for Systematic Review and Meta-Analyses extension for scoping reviews (PRISMA-ScR) guideline will be used to organize the search and identification of research focusing on psychedelic interventions, psychological suffering, and end-of-life issues. Health science databases such as Medline, Embase, APA PsychINFO, and CINAHL will be searched. The search will be limited to empirical published data on ‘end-of-life’, ‘psychedelics’, and ‘psychological suffering’. Data extracted from selected studies will cover intervention details, participant characteristics, measured outcomes, and theorised mechanisms. The insights gained from this review will be used to inform future research and discussions on how psychedelics can be integrated into care strategies for populations coping with end-of-life concerns. This scoping review does not require ethics approval
Induced Abortion After Previous Caesarean Section: A Scoping Review
No full textAims
To map and analyse existing literature on abortion safety, outcomes and management in those with previous CS.
Materials and Methods
Four databases were systematically searched from inception to July 2024. Primary human studies in English reporting on outcomes, safety or management of first- or second-trimester medical (MToP) or surgical (SToP) abortion in women with previous CS were included. Uterine rupture incidence was analysed cumulatively in the first and secondtrimesters by the number of CS and the type of prostaglandin used. Data on the efficacy and safety of MToP and SToP, including studies reporting on the management of abortion in the setting of abnormal placentation, were collected and analysed by theme.
Results
In total, 164 articles met inclusion criteria. Incidence of uterine rupture in first-trimester MToP was 0 of 2194 cases, in second-trimester misoprostol MToP in those with 1 previous CS was 0.5% (10/1910) and 2.2% (18/835) in women with ≥ 2 CS (p < 0.001). Mifepristone priming did not increase the rupture rate in second-trimester MToP (p = 0.77). Previous CS was a modest risk factor for retained products after MToP across both trimesters (OR 1.48, CI 1.29–1.70).
Conclusion
Medical and surgical abortion in the first and second trimester appears safe in women with prior CS; however, risks include uterine rupture, need for surgical intervention and haemorrhage from undiagnosed placenta accreta. Further research and guidance are needed on managing abortion after previous classical CS, ≥ 3 previous CS and those with abnormally invasive placenta
Towards an AI tutor for undergraduate geotechnical engineering: a comparative study of evaluating the efficiency of large language model application programming interfaces
No full textThis study investigates the efficiency of large language model (LLM) application programming interfaces (APIs)—specifically GPT-4 and Llama-3—as AI tutors for undergraduate Geotechnical Engineering education. As educational needs in specialised fields like Geotechnical Engineering become increasingly complex, innovative teaching tools that provide personalised learning experiences are essential. Unlike previous studies on AI-driven education, our research uniquely focuses on assessing the role of retrieval-augmented generation (RAG) in improving the accuracy of LLM-generated solutions to Geotechnical problems. A dataset of 391 questions from the related textbook written by Das and Sobhan (Das B, Sobhan K. Principles of Geotechnical engineering, Eight Edition. In: Cengage Learning. 2014) was used for evaluation, with solutions sourced from the textbook’s manual. Performance benchmarking focused on 20 challenging questions previously identified by Chen et al. (Chen et al. in Geotechnics 4:470–498, 2024) as problematic for GPT-4 in Zero Shot tasks. GPT-4 with API support demonstrated superior accuracy, achieving accuracy rates of 95% at a temperature setting of 0.1, 82.5% at 0.5, and 60% at 1. In comparison, Llama-3 achieved an accuracy of 25% in Zero Shot tasks and 45% with API support at a temperature setting of 0.1. The findings highlight GPT-4’s potential as an AI tutor for Geotechnical Engineering education while demonstrating the need for domain-specific optimisation and advanced formula integration techniques. This study contributes to the ongoing discourse on AI in education by providing empirical evidence supporting the deployment of LLMs as personalised, adaptive teaching aids in engineering disciplines. Future work should explore optimised formula integration strategies, expanded domain knowledge bases, and long-term student learning outcomes
Opportunistic sampling from the near-threatened Alexandrine parakeet uncovers genomes of a novel parvovirus and beak and feather disease virus
No full textBirds are known to harbour a wide range of pathogenic viruses, including the beak and feather disease virus (BFDV; species, Circovirus parrot), which poses a significant threat to the conservation of endangered avian species. This study reports the genomic identification and characterisation of a novel psittaciform chaphamaparvovirus (PsChPV-6) and BFDV, sequenced from the faecal samples of healthy Alexandrine parakeets (Psittacula eupatria). PsChPV-6 is a linear, single-stranded DNA virus consisting of 4232 nucleotides (nt) with a high A + T content and five predicted open reading frames (ORFs). Key proteins encoded by PsChPV-6, such as the nonstructural protein 1 (NS1) and major capsid protein VP1, demonstrate strong sequence similarities to other avian parvoviruses, with conserved motifs in NS1 crucial for viral replication. The presence of a previously uncharacterised ORF1 region suggests strain-specific viral features that warrant further exploration. BFDV is a circular single-stranded DNA virus in the Circoviridae family and was also identified in the samples. Phylogenetic analysis positioned PsChPV-6 within the Chaphamaparvovirus genus, closely related to parvoviruses from diverse avian species, whereas BFDV was grouped with strains from Australian cockatoos and other nonpsittacine birds, suggesting potential cross-species transmission. These findings contribute to a deeper understanding of the genetic diversity and evolutionary dynamics of these viral pathogens in bird populations, underscoring the importance of ongoing surveillance to evaluate their ecological and veterinary impacts
LEAVES: An open-source web-based tool for the scalable annotation and visualisation of large-scale ecoacoustic datasets using cluster analysis
No full textEcoacoustics has emerged as a pivotal discipline in the conservation and monitoring of ecosystems, offering insights into species’ behaviour and ecosystem health through soundscape analysis. Central to this is the need for accurate annotations of environmental audio recordings, which underpin the computational models used in ecological monitoring. However, due to the increasingly large scale of datasets, annotation using existing tools and techniques cannot be performed at feasible speeds or with the necessary accuracy required for real-world application. The LEAVES (Large-scale Ecoacoustics Annotation and Visualisation with Efficient Segmentation) platform addresses this gap by leveraging unsupervised clustering techniques optimised for the high-throughput annotation of large-scale ecoacoustics datasets. Our evaluation across six real-world datasets shows that LEAVES improves annotation efficiency by up to 7.12 times compared to manual annotation while maintaining 79%–90% label similarity to validated data. We expect that our proposed tool will greatly accelerate the annotation process when generating high-quality labelled datasets, supporting larger-scale studies with broader community engagement in ecoacoustics research
CRNet: Convolutive Recurrent Network for Suspect Face Identification
No full textIdentifying suspects in critical situations-particularly when they are wearing scarves, masks, or are in environments with light obstructions and concealed facial expressions-poses significant challenges. To address these issues, a method known as the Convolutive Recurrent Network (CRNet) for suspect face identification is proposed. CRNet utilises deep neural networks, specifically the Residual Network-50, leveraging a transfer learning approach for efficient feature extraction. In addition, Bidirectional Long Short-Term Memory (BiLSTM) layers are employed to capture spatial and recurrent features, with BiLSTM layers serving as the core component of the model. CRNet is designed to overcome the limitations of current models in managing complex situations, such as scarves, spectacles, high illumination, and varied expressions. CRNet fills this gap by integrating mechanisms that provide flexibility for ambiguous features and variable lighting conditions. Experimental and comparative analysis demonstrates that CRNet significantly outperforms existing methods, providing notable improvements in both accuracy and reliability. This approach introduces a rapid feature-learning method for precise suspect identification by integrating spatial dependencies, enhancing versatility across various computer vision domains. The model’s potential impact on criminal investigations is substantial due to its fast bidirectional feature processing. Experimental results demonstrate the robustness and adaptability of CRNet, achieving accuracy rates of 97.46% on the Extended Cohn-Kanade dataset, 98.08% on the Augmented Reality dataset, and 99.58% on the Extended Yale B dataset-substantially surpassing the baseline accuracy of 46.00%
Edits & Annotations: Season 1
No full textEdits & Annotations is a podcast from the Roderick Centre for Australian Literature and Creative Writing, featuring interviews with Australian and international authors about their craft, their process and their writing lives
Effects of solution ageing in compressive behaviour of SLM-In718 triply periodic minimal surfaces
No full textThis study aims to investigate the effect of heat treatment on the microstructure and mechanical properties of triply periodic
minimal surface (TPMS) structures manufactured by selective laser melting (SLM) from Inconel
® alloy 718 (In718).
Although many aspects of SLM-In718 have been studied, its as-built (AB) and heat treated (HT) performance under compression
has not been thoroughly investigated. To this end, sheet-based diamond, gyroid, and primitive morphologies along with
bulk specimens were manufactured and tested under AB and HT conditions. Standard solution ageing (solution treatment
+ two-step ageing) was carried out to improve some of the inherent deficiencies of SLM-In718 such as the development of
brittle Laves and � phases. It was found that the overall mechanical performance of the HT TPMS specimens were improved
in terms of stiffness, strength, and energy absorption among others. Furthermore, the geometry of the TPMS specimens
dictated the extent of enhancement such that the diamond geometry outperformed the others in many aspects. In contrast,
the primitive structure demonstrated the most stable plateau stage in both AB and HT conditions. Microstructural analysis
revealed occasional precipitation of second-phases carbide particles at grain boundaries. Moreover, niobium was made
available by dissolution of Laves phases during solution treatment which was later used in precipitation of strengthening ��
and ��� phases during ageing. Finally, a new scheme for analysing the energy absorption was devised which could provide
a new perspective towards studying energy efficiency of porous structures. Accordingly, it was found that heat treatment
improves the mechanical properties contributing the first two stages of energy absorption (initial and plateau) while limiting
the fraction of the final stage. In conclusion, it was demonstrated that although heat treatment could address issues like
residual stresses and microstructural shortcomings of SLM-In718, the extent of this rectification is further controlled by
cell topology of the TPMS structure
Dynamic capabilities-enabled servitization: the role of exploitative quality management
No full textLiterature is silent on whether the impact of dynamic capabilities (DCs) on transformative efforts towards servitization is hampered by manufacturers’ exploitative quality management (QM) employed to improve production efficiencies. Based on theoretical and empirical insights about 60 manufacturers this paper offers propositions on this question and a nuanced appreciation of the conflicts and barriers manufacturers face to effectively use DCs to servitize. It shows that DCs strengthen manufacturers’ customer solution capabilities and service resources. However, although directly improving their service resources, exploitative QM weakens the positive impact of DCs on such resources, yet without necessarily affecting customer solution capabilities. Hence, manufacturers’ use of exploitative QM can bolster their service resources yet concurrently reduce the impact of their transformative efforts towards servitization. The paper also delves into the tensions that can arise between the equipment and service parts of a manufacturing organisation and proposes managerial guidance on how to address them
Are the synergy of stable energy supply, robust financial service and strong economic growth achievable? Evidence from 134 countries
No full textPurpose: This study tests convergence in energy diversification, per-capita income and financial development and explores their interrelationships.
Design/methodology/approach: Club convergence tests, Granger tests and panel regressions are employed on 134 countries from 1995 to 2019.
Findings: While overall convergence is absent across the entire sample, countries have converged within specific clubs. Low- and lower-middle-income countries show convergence in energy diversification and per-capita income. Positive bidirectional relationships are found between energy diversification and per-capita income, and between financial development and per-capita income. A U-shaped relationship between oil prices and energy diversification is identified.
Research limitations/implications: The findings suggest that achieving a shared equilibrium in energy diversification, economic prosperity and financial development is feasible through technological progress within convergence clubs. Investments in human capital and technology are crucial prerequisites for sustainable development.
Originality/value: This study pioneers testing energy diversification, per-capita income and financial development convergence, investigating the tri-directional relationship between them, and exploring the U-shaped relationship between oil prices and energy diversification