A 2‐year randomized blinded controlled trial of a conditionally licensed Moraxella bovoculi vaccine to aid in prevention of infectious bovine keratoconjunctivitis in Angus beef calves

Background Infectious bovine keratoconjunctivitis (IBK) in beef cattle has major welfare and production implications. Effective vaccination against IBK would also reduce antibiotic use in beef production. Objective/Hypothesis To evaluate the efficacy of a conditionally licensed commercial IBK vaccine containing Moraxella bovoculi bacterin. Primary working hypothesis was that animals vaccinated with 2 doses of the commercial M. bovoculi vaccine would have a lower risk of disease. Animals Spring born calves at a university cow‐calf herd. After excluding animals with ocular lesions, calves eligible for prevention assessment in 2017 and 2018 were 163 (81 vaccinated, 82 unvaccinated) and 207 (105 vaccinated, 102 unvaccinated). One hundred sixty two and two hundred and six calves completed the follow‐up period in 2017 and 2018, respectively. Methods A randomized controlled trial. The trial design was a 2‐arm parallel trial with a 1:1 allocation ratio. Results In both years, calves receiving the vaccine had more IBK. This effect was small. The pooled risk ratio was 1.30 (95% confidence interval 0.84–2.01). The pooled unadjusted difference in mean weight (kg) at weaning was −0.88 (95% confidence interval—7.2‐5.43). Conclusions and Clinical Importance We were unable to document that the M. bovoculi bacterin vaccine had a protective effect for the incidence of IBK in our single herd in a 2‐year study

Utilizing unsupervised learning to improve sward content prediction and herbage mass estimation

Sward species composition estimation is a tedious one. Herbage must be collected in the field, manually separated into components, dried and weighed to estimate species composition. Deep learning approaches using neural networks have been used in previous work to propose faster and more cost efficient alternatives to this process by estimating the biomass information from a picture of an area of pasture alone. Deep learning approaches have, however, struggled to generalize to distant geographical locations and necessitated further data collection to retrain and perform optimally in different climates. In this work, we enhance the deep learning solution by reducing the need for ground-truthed (GT) images when training the neural network. We demonstrate how unsupervised contrastive learning can be used in the sward composition prediction problem and compare with the state-of-the-art on the publicly available GrassClover dataset collected in Denmark as well as a more recent dataset from Ireland where we tackle herbage mass and height estimation.Comment: 3 pages. Accepted at the 29th EGF General Meeting 202

Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation

Herbage mass yield and composition estimation is an important tool for dairy farmers to ensure an adequate supply of high quality herbage for grazing and subsequently milk production. By accurately estimating herbage mass and composition, targeted nitrogen fertiliser application strategies can be deployed to improve localised regions in a herbage field, effectively reducing the negative impacts of over-fertilization on biodiversity and the environment. In this context, deep learning algorithms offer a tempting alternative to the usual means of sward composition estimation, which involves the destructive process of cutting a sample from the herbage field and sorting by hand all plant species in the herbage. The process is labour intensive and time consuming and so not utilised by farmers. Deep learning has been successfully applied in this context on images collected by high-resolution cameras on the ground. Moving the deep learning solution to drone imaging, however, has the potential to further improve the herbage mass yield and composition estimation task by extending the ground-level estimation to the large surfaces occupied by fields/paddocks. Drone images come at the cost of lower resolution views of the fields taken from a high altitude and requires further herbage ground-truth collection from the large surfaces covered by drone images. This paper proposes to transfer knowledge learned on ground-level images to raw drone images in an unsupervised manner. To do so, we use unpaired image style translation to enhance the resolution of drone images by a factor of eight and modify them to appear closer to their ground-level counterparts. We then ... ~\url{www.github.com/PaulAlbert31/Clover_SSL}.Comment: 11 pages, 5 figures. Accepted at the Agriculture-Vision CVPR 2022 Worksho

Semi-supervised dry herbage mass estimation using automatic data and synthetic images

Monitoring species-specific dry herbage biomass is an important aspect of pasture-based milk production systems. Being aware of the herbage biomass in the field enables farmers to manage surpluses and deficits in herbage supply, as well as using targeted nitrogen fertilization when necessary. Deep learning for computer vision is a powerful tool in this context as it can accurately estimate the dry biomass of a herbage parcel using images of the grass canopy taken using a portable device. However, the performance of deep learning comes at the cost of an extensive, and in this case destructive, data gathering process. Since accurate species-specific biomass estimation is labor intensive and destructive for the herbage parcel, we propose in this paper to study low supervision approaches to dry biomass estimation using computer vision. Our contributions include: a synthetic data generation algorithm to generate data for a herbage height aware semantic segmentation task, an automatic pro- cess to label data using semantic segmentation maps, and a robust regression network trained to predict dry biomass using approximate biomass labels and a small trusted dataset with gold standard labels. We design our approach on a herbage mass estimation dataset collected in Ireland and also report state-of-the-art results on the publicly released Grass-Clover biomass estimation dataset from Denmark. Our code is available at https://git.io/J0L2a

Irish women in the diaspora: exclusions and inclusions

Irish women have a long history of emigration which provides parallels with the experiences of women now moving to settle in Ireland. In both cases, women migrants have been needed to fill the massive deficit of paid domestic labor in rapidly industrialising economies. Over the last two centuries, these destinations for Irish women have included the USA, Britain and Australia, as well as Canada, New Zealand, South Africa and Argentina. Some of the complexities in the positioning of migrant Irish women within the “diaspora spaces” they occupy are explored in this article. I identify ongoing disadvantage for certain groups of Irish-born women, drawing on evidence primarily from Britain, which has the largest contemporary diasporic Irish population. Comparisons are made with Irish women's experiences in the USA and Australia, using Census and survey data generated by and for the 2002 Task Force on Policy regarding Emigrants. The concept of diaspora explicitly includes those identifying themselves as Irish over several generations. I use qualitative findings from the Irish 2 Project, a recent study of the large second-generation Irish population in Britain, to examine narratives of women living in Manchester who grew up in “Irish” households and are subsequently negotiating hybrid identities in adulthood. These offer insights into longitudinal dimensions of migrant experience and the continuing significance of ethnic difference

The tyranny of transnational discourse: ‘authenticity’ and Irish diasporic identity in Ireland and England

This is the peer reviewed version of the following article: SCULLY, M., 2012. The tyranny of transnational discourse: 'authenticity' and Irish diasporic identity in Ireland and England. Nations and Nationalism, 18 (2), pp.191-209, which has been published in final form at: http://dx.doi.org/10.1111/j.1469-8129.2011.00534.x. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Through the prism of current state discourses in Ireland on engagement with the Irish diaspora, this article examines the empirical merit of the related concepts of 'diaspora' and 'transnationalism'. Drawing on recent research on how Irish identity is articulated and negotiated by Irish people in England, this study suggests a worked distinction between the concepts of 'diaspora' and 'transnationalism'. Two separate discourses of authenticity are compared and contrasted: they rest on a conceptualisation of Irish identity as transnational and diasporic, respectively. I argue that knowledge of contemporary Ireland is constructed as sufficiently important that claims on diasporic Irishness are constrained by the discourse of authentic Irishness as transnational. I discuss how this affects the identity claims of second-generation Irish people, the relationship between conceptualisations of Irishness as diasporic within Ireland and 'lived' diasporic Irish identities, and implications for state discourses of diaspora engagement

When People Die:Stories from Young People

When People Die: Stories from Young People is a comic that tells numerous stories about death and resilience from a group of young people. The comic helps readers gain different and better perspectives on grief and what grieving means for young people. These stories and scenarios have been written by a group of young people selected from Children’s Hospices Across Scotland (Robin House), HMYOI Polmont, and Richmond’s Hope, and put together by the team at the Dundee Comics Creative Space. This comic will help people such as school teachers, guidance counsellors and anyone who reads it to learn more about how it feels to be in the position of a grieving young person, and how to act in situations that may come up with a grieving child

Multimodal surface-based morphometry reveals diffuse cortical atrophy in traumatic brain injury.

<p>Abstract</p> <p>Background</p> <p>Patients with traumatic brain injury (TBI) often present with significant cognitive deficits without corresponding evidence of cortical damage on neuroradiological examinations. One explanation for this puzzling observation is that the diffuse cortical abnormalities that characterize TBI are difficult to detect with standard imaging procedures. Here we investigated a patient with severe TBI-related cognitive impairments whose scan was interpreted as normal by a board-certified radiologist in order to determine if quantitative neuroimaging could detect cortical abnormalities not evident with standard neuroimaging procedures.</p> <p>Methods</p> <p>Cortical abnormalities were quantified using multimodal surfaced-based morphometry (MSBM) that statistically combined information from high-resolution structural MRI and diffusion tensor imaging (DTI). Normal values of cortical anatomy and cortical and pericortical DTI properties were quantified in a population of 43 healthy control subjects. Corresponding measures from the patient were obtained in two independent imaging sessions. These data were quantified using both the average values for each lobe and the measurements from each point on the cortical surface. The results were statistically analyzed as z-scores from the mean with a p < 0.05 criterion, corrected for multiple comparisons. False positive rates were verified by comparing the data from each control subject with the data from the remaining control population using identical statistical procedures.</p> <p>Results</p> <p>The TBI patient showed significant regional abnormalities in cortical thickness, gray matter diffusivity and pericortical white matter integrity that replicated across imaging sessions. Consistent with the patient's impaired performance on neuropsychological tests of executive function, cortical abnormalities were most pronounced in the frontal lobes.</p> <p>Conclusions</p> <p>MSBM is a promising tool for detecting subtle cortical abnormalities with high sensitivity and selectivity. MSBM may be particularly useful in evaluating cortical structure in TBI and other neurological conditions that produce diffuse abnormalities in both cortical structure and tissue properties.</p

The gendering of global citizenship: findings from a large-scale quantitative study on global citizenship education experiences

The growing literature on the gendering of citizenship and citizenship education highlights that western notions of ‘citizenship’ have often been framed in a way that implicitly excludes women. At the same time, insofar as feminist writers have addressed citizenship, they have tended to see it in largely local and national terms. While feminist literature has laid the groundwork for understanding how schools have shaped and structured a gendered citizenry, there is a lack of large-scale quantitative data which might allow us to explore the intersection between gender and global citizenship education. Drawing on a large-scale quantitative study on development education/global citizenship education in second-level schools, the data presented here suggest that emergent notions of global citizenship are being gendered in schools. The data suggest that girls’ schools are more likely than other types of schools to emphasise a sense of responsibility for, and an analysis of, global inequalities, while differences also emerge between boys’ schools and co-educational schools

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Background: Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. // Methods: We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung's disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. // Findings: We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung's disease) from 264 hospitals (89 in high-income countries, 166 in middle-income countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in low-income countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. // Interpretation: Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between low-income, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030