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

Supplementary data for article: O’Connor, S.; Szwej, E.; Nikodinović-Runić, J.; O’Connor, A.; Byrne, A. T.; Devocelle, M.; O’Donovan, N.; Gallagher, W. M.; Babu, R. P.; Kenny, S. T.; et al. The Anti-Cancer Activity of a Cationic Anti-Microbial Peptide Derived from Monomers of Polyhydroxyalkanoate. Biomaterials 2013, 34 (11), 2710–2718. https://doi.org/10.1016/j.biomaterials.2012.12.032

Supplementary material for: [https://doi.org/10.1016/j.biomaterials.2012.12.032]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/1609

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

Venous thromboembolism - risk assessment tool and thromboprophylaxis policy: a national survey

Venous Thromboembolic (VTE) events in hospitalised patients are associated with significant mortality and morbidity and a major economic burden on the health service. It is well established in the literature that active implementation of a mandatory risk assessment tool and thromboprophylaxis policy reduces the incidence of hospital associated thrombosis (HAT). This study examines the utilization of a VTE risk assessment tool and thromboprophylaxis (TP) policy in Irish hospitals that manage acute admissions. A national survey was distributed to forty acute hospitals throughout Ireland. The response rate was 78% (31/40). The results showed that only 26% (n=8/31) of acute hospitals in Ireland have a local implemented TP policy. Six (75%) of these eight had a risk assessment tool in conjunction with the TP policy. All respondents who did not report to have a TP policy and risk assessment tool agreed that they should implement VTE prevention policy at their hospital. Based on the data from this survey and evidence from the effectiveness of the VTE prevention programme introduced in the United Kingdom, there is a need for a national risk assessment and thromboprophylaxis policy in Ireland. This change in practice would have the potential to prevent or reduce the morbidity and mortality associated with hospital acquired thrombosis

The Hydroxylase Inhibitor Dimethyloxallyl Glycine Attenuates Endotoxic Shock Via Alternative Activation of Macrophages and IL-10 Production by B1 Cells

Localized tissue hypoxia is a feature of infection and inflammation, resulting in the upregulation of the transcription factors HIF-1α and NF-κB via inhibition of oxygen sensing hydroxylase enzymes. Previous studies have demonstrated a beneficial role for the hydroxylase inhibitor dimethyloxallyl glycine (DMOG) in inflammatory conditions, including experimental colitis, by regulating the activity of HIF-1 and NF-κB. We have demonstrated in vivo that pre-treatment with DMOG attenuates systemic LPS-induced activation of the NF-κB pathway. Furthermore, mice treated with DMOG had significantly increased survival in LPS-induced shock. Conversely, in models of polymicrobial sepsis, DMOG exacerbates disease severity. DMOG treatment of mice promotes M2 polarization in macrophages within the peritoneal cavity, resulting in the downregulation of pro-inflammatory cytokines such as TNFα. In addition, in vivo DMOG treatment upregulates IL-10 expression, specifically in the peritoneal B-1 cell population. This study demonstrates cell type specific roles for hydroxylase inhibition in vivo and provides insight into the mechanism underlying the protection conveyed by DMOG in models of endotoxic shock

Supplementary data for article: O’Connor, S.; Szwej, E.; Nikodinović-Runić, J.; O’Connor, A.; Byrne, A. T.; Devocelle, M.; O’Donovan, N.; Gallagher, W. M.; Babu, R. P.; Kenny, S. T.; et al. The Anti-Cancer Activity of a Cationic Anti-Microbial Peptide Derived from Monomers of Polyhydroxyalkanoate. Biomaterials 2013, 34 (11), 2710–2718. https://doi.org/10.1016/j.biomaterials.2012.12.032

Supplementary material for: [https://doi.org/10.1016/j.biomaterials.2012.12.032]Related to published version: [http://cherry.chem.bg.ac.rs/handle/123456789/1609

Benefits and Harms of Conservative, Pharmacological, and Surgical Management Options for Women with Bladder Outlet Obstruction : A Systematic Review from the European Association of Urology Non-neurogenic Female LUTS Guidelines Panel

Peer reviewedPostprin

Development and implementation of an ultralow-dose CT protocol for the assessment of cerebrospinal shunts in adult hydrocephalus

Background: Cerebrospinal fluid shunts in the treatment of hydrocephalus, although associated with clinical benefit, have a high failure rate with repeat computed tomography (CT) imaging resulting in a substantial cumulative radiation dose. Therefore, we sought to develop a whole-body ultralow-dose (ULD) CT protocol for the investigation of shunt malfunction and compare it with the reference standard, plain radiographic shunt series (PRSS). Methods: Following ethical approval, using an anthropomorphic phantom and a human cadaveric ventriculoperitoneal shunt model, a whole-body ULD-CT protocol incorporating two iterative reconstruction (IR) algorithms, pure IR and hybrid IR, including 60% filtered back projection and 40% IR was evaluated in 18 adult patients post new shunt implantation or where shunt malfunction was suspected. Effective dose (ED) and image quality were analysed. Results: ULD-CT permitted a 36% radiation dose reduction (median ED 0.16 mSv, range 0.07–0.17, versus 0.25 mSv (0.06–1.69 mSv) for PRSS (p = 0.002). Shunt visualisation in the thoracoabdominal cavities was improved with ULD-CT with pure IR (p = 0.004 and p = 0.031, respectively) and, in contrast to PRSS, permitted visualisation of the entire shunt course (p < 0.001), the distal shunt entry point and location of the shunt tip in all cases. For shunt complications, ULD-CT had a perfect specificity. False positives (3/22, 13.6%) were observed with PRSS. Conclusions: At a significantly reduced radiation dose, whole body ULD-CT with pure IR demonstrated diagnostic superiority over PRSS in the evaluation of cerebrospinal fluid shunt malfunction

Diagnostic Tests for Female Bladder Outlet Obstruction : A Systematic Review from the European Association of Urology Non-neurogenic Female LUTS Guidelines Panel

Acknowledgements Jae Hung Jung, Murat Gul, Ege Can Serefoglu (translation of foreign language articles) and Karin Plass for administrative support.Peer reviewedPostprin

Falls and falls efficacy: the role of sustained attention in older adults

<p>Abstract</p> <p>Background</p> <p>Previous evidence indicates that older people allocate more of their attentional resources toward their gait and that the attention-related changes that occur during aging increase the risk of falls. The aim of this study was to investigate whether performance and variability in sustained attention is associated with falls and falls efficacy in older adults.</p> <p>Methods</p> <p>458 community-dwelling adults aged ≥ 60 years underwent a comprehensive geriatric assessment. Mean and variability of reaction time (RT), commission errors and omission errors were recorded during a fixed version of the Sustained Attention to Response Task (SART). RT variability was decomposed using the Fast Fourier Transform (FFT) procedure, to help characterise variability associated with the arousal and vigilance aspects of sustained attention.</p> <p>The number of self-reported falls in the previous twelve months, and falls efficacy (Modified Falls Efficacy Scale) were also recorded.</p> <p>Results</p> <p>Significant increases in the mean and variability of reaction time on the SART were significantly associated with both falls (p < 0.01) and reduced falls efficacy (p < 0.05) in older adults. An increase in omission errors was also associated with falls (p < 0.01) and reduced falls efficacy (p < 0.05). Upon controlling for age and gender affects, logistic regression modelling revealed that increasing variability associated with the vigilance (top-down) aspect of sustained attention was a retrospective predictor of falling (p < 0.01, OR = 1.14, 95% CI: 1.03 - 1.26) in the previous year and was weakly correlated with reduced falls efficacy in non-fallers (p = 0.07).</p> <p>Conclusions</p> <p>Greater variability in sustained attention is strongly correlated with retrospective falls and to a lesser degree with reduced falls efficacy. This cognitive measure may provide a novel and valuable biomarker for falls in older adults, potentially allowing for early detection and the implementation of preventative intervention strategies.</p