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A simplified model for mixed continuous antisolvent crystalliser
No full textAntisolvent crystallization is one of the key separation processes used in the pharmaceutical and other chemical industries for the purification and recovery of crystalline solid products. In this work, we present a simplified model to simulate steady state performance of a mixed continuous antisolvent crystalliser. A simplified model is derived and is shown to be able to mimic the behaviour of the full population balance model (PBM). The predictions of the simplified model are validated by comparing with the results of the recently published full PBM model. The model is further simplified to derive explicit expressions for estimating the steady state supersaturation and the Sauter mean diameter. The expressions are useful to understand interactions of key operating parameters (feed supersaturation and residence time) and crystallisation kinetics (nucleation and growth) and their influence on steady state supersaturation and the Sauter mean diameter. The presented model will be useful for design and optimisation of continuous anti-solvent crystallisers.</p
Methodological, practical, and ethical perspectives on music therapy research in pediatric neurorehabilitation
No full textThis commentary explores the complexities of advancing research in music therapy for pediatric neurorehabilitation following acquired brain injury. Despite the increasing clinical integration of music therapy in this field, robust evidence remains limited. This discussion explores methodological, practical, and ethical challenges that complicate research design and concludes with recommendations to address these challenges and strengthen the evidence base.</p
Threats, pressure and veiled coercion: decision-making about induction of labor in Ireland
No full textInduction of labor is an increasingly common routine intervention in most high resource maternity settings. This article focuses on the experiences of birthing people by asking to what extent they felt involved in the decision-making process to have an induction. We present qualitative findings from a national mixed methods survey, drawing on text responses from women who gave birth in Ireland between 2018 and 2023. The survey was part of a larger participatory research project on the medicalization of birth in Ireland. Our findings suggest that many women did not feel well informed, and that coercion and duress are commonplace.</p
The cervical microbiome of ewe breeds with known divergent fertility following artificial insemination with frozen-thawed semen
No full textThe use of artificial insemination (AI) with frozen-thawed semen in sheep is limited internationally due to low pregnancy rates. An exception is Norway, where high success rates routinely occur following vaginal deposition of frozen-thawed semen during natural estrus. Previous research suggests that breed-specific differences in pregnancy rates may result from impaired cervical sperm transport. This study compared cervical microbiomes among sheep breeds with known differences in pregnancy rates after AI. Cervical samples were collected from Suffolk (low fertility) and Belclare (medium fertility) breeds in Ireland, and Norwegian white sheep (NWS) and Fur breeds (both high fertility) in Norway, during the follicular phase of both natural and synchronized estruses, and the luteal phase of synchronized estrus. Amplicon sequencing revealed significantly higher bacterial abundance during the follicular phase in the low-fertility Suffolk breed compared to high-fertility breeds. Alpha diversity was higher in Suffolk and Belclare breeds, especially during the natural follicular phase, coinciding with pronounced beta diversity differences among breeds. Genus Histophilus was the top feature leading to microbial differences between ewe breeds and types of cycle. Ewe breed was the main driver of cervical microbial composition; increased microbial load in lower-fertility breeds may negatively impact sperm survival/transport, hampering AI success.</p
“You need to know that you are not alone”: the sustainability of community-based dance programs for people living with Parkinson’s disease
No full textPurposeTo identify factors contributing to the long-term sustainability of community-based dance programs for people living with Parkinson’s disease in order to inform the design and development of sustainable programs.MethodsMulti-site ethnographic fieldwork was conducted at four different preexisting dance programs for people living with Parkinson’s disease. Dancer, facilitator, and community stakeholder perspectives were gathered via semi-structured interviews in order to create a deeper understanding of how existing programs navigate challenges and maintain stability. Transcripts and field notes were analyzed via reflexive thematic analysis.ResultsInterviews were conducted with 18 participants (eight dancers with Parkinson’s disease, seven dance facilitators, one classroom assistant, and two community stakeholders). Four key areas for supporting program sustainability were identified: (1) finding an organizational structure that works, (2) balancing funding, fundraisers, and fees, (3) prioritizing dancer experience and satisfaction, and (4) recruiting and retaining committed, high-quality facilitators.ConclusionCultivating multiple funding sources; forging strategic connections with local Parkinson’s organizations and arts institutions; building a critical mass of facilitators and administrators with diverse skillsets; offering hybrid online delivery where possible; and ensuring that the dancer experience is low-pressure, varied, and enjoyable can support the long-term sustainability of dance programs for people living with Parkinson’s disease.</p
Exploring the frontier of bovine protein production within territorial net zero emission targets
No full textGlobal and national environmental targets for the Agriculture, Forestry and Other Land Use (AFOLU) sector need to be reconciled with increasing food and protein demands of a growing global population. Meeting climate targets in AFOLU is a tremendous challenge in countries with high ruminant livestock production and small forest carbon sinks. Using GOBLIN, an integrated assessment model that utilises a back-casting approach, 2187 future AFOLU configuration scenarios are explored to investigate whether current levels of bovine protein production in Ireland are compatible with net zero greenhouse gas (GHG) emissions by 2050. Seven proven GHG mitigation measures are combined at three levels of ambition and screened according to three definitions of net zero based on the GWP100 metric, with a focus on the integration of clover-based grasslands. Net zero was achieved in 19 % of scenarios when all GHGs require balancing by 2050. The current livestock herd configuration was incompatible with net zero, which required at least 1.5 million ha of grassland to be diverted from livestock production towards climate-positive land uses, including afforestation of close to 10 % of terrestrial land area by 2050. When applying less stringent net zero definitions based on a split gas approach, up to 63 % of explored scenarios achieved net zero. Independent of net zero definition (which must be internationally fair and transparent), results indicate that bovine protein production can only be maintained through very high deployment of ambitious technical abatement measures, alongside major land use transformation requiring large-scale structural changes in the agriculture sector.</p
Comprehensive machine learning approaches for modelling the state of charge of lithium-ion batteries
No full textThe advancement of lithium-ion batteries (LIBs) is vital for achieving net-zero emissions because it enables renewable energy integration, supports electric vehicle (EV) adoption, and promotes cost-effective and sustainable solutions. The growing demand for EVs and portable electronics has amplified the need for reliable battery management systems to ensure safety and performance. Machine learning (ML) methods for modelling the state of charge (SOC) in batteries are gaining traction owing to their adaptability to diverse datasets and lower computational demands. However, the challenge lies in selecting the most suitable ML architecture for a specific application. This study evaluates three ML approaches for SOC modelling in LIBs: multilayer perceptron (MLP), long short-term memory (LSTM), and nonlinear autoregressive with exogenous input (NARX) neural networks. The models were tested using an experimental dataset with multiple input variables, including electrochemical impedance spectroscopy data, voltage, and capacity from commercial LIB cells. The results show that MLP and LSTM perform effectively with smaller training datasets (14 samples), whereas the NARX model requires more extensive data (34 out of 67 samples) for accuracy. Additionally, the NARX model showed greater sensitivity to learning rate adjustments and hidden layer configurations, whereas MLP and LSTM maintained robust performance across varying parameters.</p
A mixed methods realist analysis of telehealth delivery of complex wheelchair assessment in Aotearoa New Zealand: contexts, mechanisms, and outcomes
No full textPurpose: This study examined telehealth delivery of complex wheelchair assessment in Aotearoa New Zealand, specifically: what works, for whom, and in which contexts, with exploration of culturally specific factors for indigenous Māori. Materials and Methods: A mixed methods realist evaluation was conducted with remote specialist assessors (physiotherapists and occupational therapists), on-site assistants, and wheelchair users. Interviews/focus groups, mobility goal achievement, satisfaction, and fidelity of tele-delivered assessment of wheelchair and seating (tAWS) contributed to Context-Mechanism-Outcome configurations (CMOc). Results: Four remote specialist assessors delivered tAWS, but it was declined by on-site assistants in 78% of cases in which specialist assessors perceived it could work. When tAWS was delivered to wheelchair users (N=5), the majority of goals were achieved, with high service satisfaction. CMOc’s highlight the influence of system design in the uptake of telehealth by health professionals. Conclusions: While therapists can navigate complexity for successful tAWS, therapist and system barriers limit its uptake, particularly confidence in conducting assessment and use of technology among the non-adopters. Telehealth specific training in culturally-responsive rehabilitation is recommended. This evaluation contributes to telehealth program theory and the mechanisms to be addressed for telehealth to meet its potential to enhance equity in health outcomes.</p
Modelling gender equity in the classroom: from teacher educators to pre-service teachers and what gets lost in translation
No full textGender-responsive pedagogies (GRP) are increasingly recognised as an essential factor in promoting gender equity in the classroom across all levels of education. This paper explores successes and challenges of using GRP to support more equitable gender relationships in Palestine, where equality of access to education between boys and girls has already been achieved but gendered dynamics in teaching and learning prevail. Our reflections are grounded in the lessons learned from a four-year project which explored how GRP and play-based learning (PBL) can be incorporated into teacher education programmes to enhance the educational experience of children in Palestine. We explore how teacher educators who participated in training on GRP and PBL shared their knowledge, practical skills and enthusiasm with the pre-service teachers who took their classes. We question why gender gets lost in translation and how playful approaches can better support the use of GRP in future teacher education initiatives.</p
Capturing mental workload through physiological sensors in human–robot collaboration: a systematic literature review
No full textHuman–robot collaboration (HRC) is increasingly prevalent across various industries, promising to boost productivity, efficiency, and safety. As robotics technology advances and takes on more complex tasks traditionally performed by humans, the nature of work and the demands on workers are evolving. This shift emphasizes the need to critically integrate human factors into these interactions, as the effectiveness and safety of these systems are highly dependent on how workers cooperate with and understand robots. A significant challenge in this domain is the lack of a consensus on the most efficient way to operationalize and assess mental workload, which is crucial for optimizing HRC. In this systematic literature review, we analyze the different psychophysiological measures that can reliably capture and differentiate varying degrees of mental workload in different HRC settings. The findings highlight the crucial need for standardized methodologies in workload assessment to enhance HRC models. Ultimately, this work aims to guide both theorists and practitioners in creating more sophisticated, safe, and efficient HRC frameworks by providing a comprehensive overview of the existing literature and pointing out areas for further study.</p