Assessment of multi-temporal, multi-sensor radar and ancillary spatial data for grasslands monitoring in Ireland using machine learning approaches

Accurate inventories of grasslands are important for studies of carbon dynamics, biodiversity conservation and agricultural management. For regions with persistent cloud cover the use of multi-temporal synthetic aperture radar (SAR) data provides an attractive solution for generating up-to-date inventories of grasslands. This is even more appealing considering the data that will be available from upcoming missions such as Sentinel-1 and ALOS-2. In this study, the performance of three machine learning algorithms; Random Forests (RF), Support Vector Machines (SVM) and the relatively underused Extremely Randomised Trees (ERT) is evaluated for discriminating between grassland types over two large heterogeneous areas of Ireland using multi-temporal, multi-sensor radar and ancillary spatial datasets. A detailed accuracy assessment shows the efficacy of the three algorithms to classify different types of grasslands. Overall accuracies ≥ 88.7% (with kappa coefficient of 0.87) were achieved for the single frequency classifications and maximum accuracies of 97.9% (kappa coefficient of 0.98) for the combined frequency classifications. For most datasets, the ERT classifier outperforms SVM and RF

Alopecia areata: a multifactorial autoimmune condition

Alopecia areata is an autoimmune disease that results in non-scarring hair loss, and it is clinically characterised by small patches of baldness on the scalp and/or around the body. It can later progress to total loss of scalp hair (Alopecia totalis) and/or total loss of all body hair (Alopecia universalis). The rapid rate of hair loss and disfiguration caused by the condition causes anxiety on patients and increases the risks of developing psychological and psychiatric complications. Hair loss in alopecia areata is caused by lymphocytic infiltrations around the hair follicles and IFN-γ. IgG antibodies against the hair follicle cells are also found in alopecia areata sufferers. In addition, the disease coexists with other autoimmune disorders and can come secondary to infections or inflammation. However, despite the growing knowledge about alopecia areata, the aetiology and pathophysiology of disease are not well defined. In this review we discuss various genetic and environmental factors that cause autoimmunity and describe the immune mechanisms that lead to hair loss in alopecia areata patients

TaLAM: Mapping Land Cover in Lowlands and Uplands with Satellite Imagery

End-of-Project ReportThe Towards Land Cover Accounting and Monitoring (TaLAM) project is part of Ireland’s response to creating a national land cover mapping programme. Its aims are to demonstrate how the new digital map of Ireland, Prime2, from Ordnance Survey Ireland (OSI), can be combined with satellite imagery to produce land cover maps

Radiocarbon dating of burials from the Teouma Lapita cemetery, Efate, Vanuatu

The discovery of a cemetery at Teouma on the island of Efate in Vanuatu dated to c. 3000 years ago increased the number of early Pacific human remains available for study by nearly an order of magnitude and provided for the first time the ability to study the population dynamics of these early colonizers. The cemetery also provided an opportunity to investigate the chronological development of such a unique site. Although identified short-lived plant materials are favoured for dating archaeological sites, the reality of research in the Pacific region is that such materials are often rare, difficult to identify to species because of an absence of suitable reference collections, and dates on other materials often have greater potential to refine and focus ¹⁴C chronologies that deal with specific research questions. At Teouma, dates on the burial remains themselves are the best means to answer questions about the age and duration of the burial ground. Human bone, however, is one of the most complicated materials to date reliably because of dietary ¹⁴C offsets and bone preservation. One commonly used methodology for calibrating dates on human bone from Pacific human skeletal remains, based on linear interpolation between δ¹³C endpoints and δ¹⁵N values, is complicated by the wide range of foods available (marine, reef, C₄ and C₃), and remains largely untested in Pacific contexts. Radiocarbon dating of the Teouma site, including 36 Lapita-age burials, 5 dates on Conus sp. ring artefacts, and dates from the associated midden deposit, has enabled further evaluation of ¹⁴C dietary offsets and the reliability of calibrated radiocarbon ages on human bone. Bayesian evaluation of the ¹⁴C dates suggests the burial ground was in regular use by c. 2940-2880 cal BP, with the last interments occurring c. 2770-2710 cal BP. A number of burials could indicate possible earlier use, perhaps as early as 3110-2930 cal BP as indicated by the calibrated age range of Burial 57. This cannot be independently substantiated using other radiocarbon dates or context at the present time. Overall, these results suggest the burial ground was in use over a possible 150 to 240 years during the formative phase of Lapita expansion into Remote Oceania

The influence of socio-economic deprivation on mobility, participation and quality of life following major lower extremity amputation in the West of Scotland

Objective: Lower extremity amputation (LEA) is more common in people from lower socio-economic groups. This study examined this further by investigating the influence of socio-economic status on mobility, participation, and quality of life (QoL) after LEA. Methods: Prospective data were gathered for all LEAs performed in one year in one Scottish Health Board, commencing March 2014. A postcode derived Scottish Index of Multiple Deprivation (SIMD) was applied by quintile (SIMD 1 = most deprived). Routine data were collected on the cohort of 171 patients; 101 participants consented and received postal questionnaires on QoL (EQ-5D-5L), participation (Reintegration to Normal Living Index [RNLI]), and mobility (Prosthetic Limb User Survey of Mobility), six (n = 67) and 12 months (n = 50) after LEA. Results: The mean ± SD age of the cohort was 66.2 ± 11.4 years; 75% were male and 53% had diabetes. In total, 67% lived in SIMD 1 and 2 and 11.1% in SIMD 5. Sixty per cent had a transtibial amputation. Mortality was 6% at 30 days 17% at six, and 29% at 12 months. Those in SIMD 1 were significantly younger (62.9 years) than those in SIMD 5 (76.3 years). Significantly more participants with a transfemoral amputation (TFA) lived in SIMD 1 (44%) compared with SIMD 5 (11%) (p = .004). Participation was low (RNLI scores: 6 months = 55.7; 12 months = 56.6) and PLUS M scores suggested mobility was poor overall at six (39.1) and 12 months (38.9). Mean QoL was 0.37 at 6 months and 0.33 at 12 months. Conclusion: Although this study observed more LEAs in those from low socio-economic areas, it is impossible to conclude whether QoL after LEA is truly influenced by socio-economic status. There was an association between the disproportionately high rate of LEAs in SIMD groups 1 and 2 and the high prevalence of smoking, 61% vs. only 21% of those in the least deprived areas (SIMD 3, 4, and 5) being current smokers

Regional anti-corruption effort, political connections and firm innovation effort: Evidence from China

This paper examines how firm characteristics and local anti‐corruption effort moderate the influence of political connections on enterprises’ private R&D investment using data from 2,587 Chinese A‐share listed enterprises. Our results show that the local anti‐corruption institutional environment significantly moderates the strong relationship between political connections and enterprises’ private R&D investment. Firm characteristics (i.e., firm size and firm age) also show a moderating effect on the relationship between political connection and enterprises’ private R&D investment; larger and older enterprises are more likely to have innovative resources and business cooperation partners, and thus are able to reduce their degree of reliance on political connections and government funding. The results of our study suggest the importance of having a transparent and fair institutional environment for enterprise innovation activities

Upland vegetation mapping using Random Forests with optical and radar satellite data

Uplands represent unique landscapes that provide a range of vital benefits to society, but are under increasing pressure from the management needs of a diverse number of stakeholders (e.g. farmers, conservationists, foresters, government agencies and recreational users). Mapping the spatial distribution of upland vegetation could benefit management and conservation programmes and allow for the impacts of environmental change (natural and anthropogenic) in these areas to be reliably estimated. The aim of this study was to evaluate the use of medium spatial resolution optical and radar satellite data, together with ancillary soil and topographic data, for identifying and mapping upland vegetation using the Random Forests (RF) algorithm. Intensive field survey data collected at three study sites in Ireland as part of the National Parks and Wildlife Service (NPWS) funded survey of upland habitats was used in the calibration and validation of different RF models. Eight different datasets were analysed for each site to compare the change in classification accuracy depending on the input variables. The overall accuracy values varied from 59.8% to 94.3% across the three study locations and the inclusion of ancillary datasets containing information on the soil and elevation further improved the classification accuracies (between 5 and 27%, depending on the input classification dataset). The classification results were consistent across the three different study areas, confirming the applicability of the approach under different environmental contexts

The emergence of resistance to the benzimidazole anthlemintics in parasitic nematodes of livestock is characterised by multiple independent hard and soft selective sweeps

Anthelmintic resistance is a major problem for the control of parasitic nematodes of livestock and of growing concern for human parasite control. However, there is little understanding of how resistance arises and spreads or of the “genetic signature” of selection for this group of important pathogens. We have investigated these questions in the system for which anthelmintic resistance is most advanced; benzimidazole resistance in the sheep parasites Haemonchus contortus and Teladorsagia circumcincta. Population genetic analysis with neutral microsatellite markers reveals that T. circumcincta has higher genetic diversity but lower genetic differentiation between farms than H. contortus in the UK. We propose that this is due to epidemiological differences between the two parasites resulting in greater seasonal bottlenecking of H. contortus. There is a remarkably high level of resistance haplotype diversity in both parasites compared with drug resistance studies in other eukaryotic systems. Our analysis suggests a minimum of four independent origins of resistance mutations on just seven farms for H. contortus, and even more for T. circumincta. Both hard and soft selective sweeps have occurred with striking differences between individual farms. The sweeps are generally softer for T. circumcincta than H. contortus, consistent with its higher level of genetic diversity and consequent greater availability of new mutations. We propose a model in which multiple independent resistance mutations recurrently arise and spread by migration to explain the widespread occurrence of resistance in these parasites. Finally, in spite of the complex haplotypic diversity, we show that selection can be detected at the target locus using simple measures of genetic diversity and departures from neutrality. This work has important implications for the application of genome-wide approaches to identify new anthelmintic resistance loci and the likelihood of anthelmintic resistance emerging as selection pressure is increased in human soil-transmitted nematodes by community wide treatment programs