Deductive automated pollen classification in environmental samples via exploratory deep learning and imaging flow cytometry.

Pollen and tracheophyte spores are ubiquitous environmental indicators at local and global scales. Palynology is typically performed manually by microscopic analysis; a specialised and time-consuming task limited in taxonomical precision and sampling frequency, therefore restricting data quality used to inform climate change and pollen forecasting models. We build on the growing work using AI (artificial intelligence) for automated pollen classification to design a flexible network that can deal with the uncertainty of broad-scale environmental applications. We combined imaging flow cytometry with Guided Deep Learning to identify and accurately categorise pollen in environmental samples; here, pollen grains captured within c. 5500 Cal yr BP old lake sediments. Our network discriminates not only pollen included in training libraries to the species level but, depending on the sample, can classify previously unseen pollen to the likely phylogenetic order, family and even genus. Our approach offers valuable insights into the development of a widely transferable, rapid and accurate exploratory tool for pollen classification in 'real-world' environmental samples with improved accuracy over pure deep learning techniques. This work has the potential to revolutionise many aspects of palynology, allowing a more detailed spatial and temporal understanding of pollen in the environment with improved taxonomical resolution.

The practice reality of ward based midwifery care: An exploration of aspirations and restrictions.

BACKGROUND: This paper reports on research that explores the experience of the ward based midwife, as research suggests workplace balance is problematic. AIM: To explore the processes and practices around ward based clinical engagement and its impact in an Australian public tertiary obstetric unit. METHODS: A qualitative descriptive study was undertaken. Focus groups were used to gather data. Groups were audio recorded and transcribed verbatim. Thematic analysis was continued until data saturation was achieved. FINDINGS: Seven focus groups involving 40 midwives were conducted. Midwives' voices suggested tensions arose when their aspirations around core professional values and camaraderie were compromised by the practice realism of the ward. Furthermore, they described frustration with imposed restrictions which governed their working environment. These occurred outside the ward, had a direct impact on how it functioned, and were perceived to be out of the midwives' control. Midwives experiencing emotional distress revealed they were carrying a burden. Two burdens were described: disengagement and what have I missed? CONCLUSION: Thought must be given to how the art of midwifery is practiced on the ward. Ignoring the growing body of literature on this subject will be problematic for both midwives and women, as midwives will be disempowered to foster women's capabilities through tailored, supportive and respectful care.