Interdisciplinary approaches to understanding and preserving mudbrick architecture in regional and diachronic contexts

Mudbrick is a challenging material to interpret, maintain, and preserve in terms of planning and treatment decision-making – especially when recovered during archaeological excavation. Further challenges exist where mudbrick remains have been exposed and abandoned, as interactions with the environment (especially water and wind) introduce additional dissolution and damage of the resource. In this paper, we present multidisciplinary research focused on the interpretation and preservation of ancient and vernacular mudbrick architecture in the Marmara Lake Basin in western Turkey. Of interest is the preservation of mudbrick and stone foundations at Kaymakçı, a Middle to Late Bronze Age, ridge-top citadel. We demonstrate that utilizing multiples lines of evidence, including macromorphological, mineralogical, and chemical studies interpreted within the context of extant vernacular traditions in the region, produces a nuanced understanding of the archaeological evidence. Further, ethnographic and experimental archaeological research with local stakeholders allowed for the development of a robust template for testing and implementing sustainable site-preservation strategies for in situ architecture with immediate communities

Made from mud: functional categorization and analyses of Bronze Age earthen materials from Western Turkey

This contribution presents the results of a pilot study of earthen materials excavated at the Middle to Late Bronze Age site of Kaymakçı, located in western Anatolia. It argues that systematic collection and analysis of fragmentary and difficult-to-identify earthen materials is challenging, yet crucial. These materials inform on activities of which traces are preserved in the archaeological record but which have been largely under-researched. Flourishing studies on earthen findings foreground architectural materials, such as mudbrick, and well-preserved features and objects. However, earthen objects and architectural features were utilized more widely than in building architecture and only a small portion of excavated sites has good preservation. We, therefore, present the different categories of earthen materials discovered at Kaymakçı, specifically architecture, installations, and portable items. Our work demonstrates that by incorporating new knowledge of archaeological remains at the site and re-studying the earthen assemblage it is possible to gain a better understanding of the morphological, functional, and social aspects of this dataset

Made from Mud: Functional Categorization and Analyses of Bronze Age Earthen Materials from Western Turkey

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Low accuracy of Bayesian latent class analysis for estimation of herd-level true prevalence under certain disease characteristics—An analysis using simulated data

Estimation of the true prevalence of infected individuals involves the application of a diagnostic test to a population and adjusting according to test performance, sensitivity and specificity. Bayesian latent class analysis for the estimation of herd and animal-level true prevalence, has become increasingly used in veterinary epidemiology and is particularly useful in incorporating uncertainty and variability into analyses in a flexible framework. However, the approach has not yet been evaluated using simulated data where the true prevalence is known. Furthermore, using this approach, the within-herd true prevalence is often assumed to follow a beta distribution, the parameters of which may be modelled using hyperpriors to incorporate both uncertainty and variability associated with this parameter. Recently however, the authors of the current study highlighted a potential issue with this approach, in particular, with fitting the distributions and a tendency for the resulting distribution to invert and become clustered at zero. Therefore, the objective of the present study was to evaluate commonly specified models using simulated datasets where the herd-level true prevalence was known. The specific purpose was to compare findings from models using hyperpriors to those using a simple beta distribution to model within-herd prevalence. A second objective was to investigate sources of error by varying characteristics of the simulated dataset. Mycobacterium avium subspecies paratuberculosis infection was used as an example for the baseline dataset. Data were simulated for 1000 herds across a range of herd-level true prevalence scenarios, and models were fitted using priors from recently published studies. The results demonstrated poor performance of these latent class models for diseases characterised by poor diagnostic test sensitivity and low within-herd true prevalence. All variations of the model appeared to be sensitive to the prior and tended to overestimate herd-level true prevalence. Estimates were substantially improved in different infection scenarios by increasing test sensitivity and within-herd true prevalence. The results of this study raise questions about the accuracy of published estimates for the herd-level true prevalence of paratuberculosis based on serological testing, using latent class analysis. This study highlights the importance of conducting more rigorous sensitivity analyses than have been carried out in previous analyses published to date

Using examination performance data and focus groups to inform teaching – a case study from final year students of veterinary medicine

Background: Student feedback has played an important role in the maintenance of quality and standards in higher education. Perhaps the most commonly used method to capture feedback is a series of questions or statements where students indicate their degree of satisfaction or agreement. Focus groups offer an alternative means of capturing ‘richer’ qualitative data relating to students’ thoughts on course structure. Aside from student evaluations, student examination performance has been used as a method to evaluate the efficacy of curriculum changes at programme level. However, this data is utilised less so at a ‘finer detail’ level to identify specific issues with the delivery of teaching. Case presentation: The purpose of this report was to outline the approach taken using qualitative and quantitative data to identify problems with a specific area of teaching, inform a new teaching approach and to assess the impact of those changes. Following quantitative and qualitative analysis, a practical class on dairy herd fertility performance was highlighted as an area for improvement. After the introduction of the newly formatted practical class with a greater focus on self-directed learning, there was a significant increase in the average score (p < 0.001) and a decrease in the proportion of students failing (p < 0.001) the question that assessed the analysis of dairy herd fertility data. In addition, the R-squared value between students’ performance in the fertility question and their performance in the overall examination increased from 0.06 to 0.11. Conclusions: The combination of qualitative focus group data and quantitative analysis of examination performance data represent robust methods for identifying problems associated with specific aspects of veterinary teaching

A review of paratuberculosis in dairy herds — Part 2: On-farm control

Bovine paratuberculosis is a chronic infectious disease of cattle, caused by Mycobacterium avium subspecies paratuberculosis (MAP). This is the second in a two-part review of the epidemiology and control of paratuberculosis in dairy herds. Several negative production effects associated with MAP infection have been described, but perhaps the most significant concern in relation to the importance of paratuberculosis as a disease of dairy cattle is the potential link with Crohn’s disease in humans. Milk is considered a potential transmission route to humans and it is recognised that pasteurisation does not necessarily eliminate the bacterium. Therefore, control must also include reduction of the levels of MAP in bulk milk supplied from dairy farms. There is little field evidence in support of specific control measures, although several studies seem to show a decreased prevalence associated with the implementation of a combined management and test-and-cull programme. Improvements in vaccination efficacy and reduced tuberculosis (TB) test interference may increase uptake of vaccination as a control option. Farmer adoption of best practice recommendations at farm level for the control of endemic diseases can be challenging. Improved understanding of farmer behaviour and decision making will help in developing improved communication strategies which may be more efficacious in affecting behavioural change on farm

A review of paratuberculosis in dairy herds — Part 1: Epidemiology

Bovine paratuberculosis is a chronic infectious disease of cattle caused by Mycobacterium avium subspecies paratuberculosis (MAP). This is the first in a two-part review of the epidemiology and control of paratuberculosis in dairy herds. Paratuberculosis was originally described in 1895 and is now considered endemic among farmed cattle worldwide. MAP has been isolated from a wide range of non-ruminant wildlife as well as humans and non-human primates. In dairy herds, MAP is assumed to be introduced predominantly through the purchase of infected stock with additional factors modulating the risk of persistence or fade-out once an infected animal is introduced. Faecal shedding may vary widely between individuals and recent modelling work has shed some light on the role of super-shedding animals in the transmission of MAP within herds. Recent experimental work has revisited many of the assumptions around age susceptibility, faecal shedding in calves and calf-to-calf transmission. Further efforts to elucidate the relative contributions of different transmission routes to the dissemination of infection in endemic herds will aid in the prioritisation of efforts for control on farm

Predictive modelling of deviation from expected milk yield in transition cows on automatic milking systems

The transition period is a pivotal time in the production cycle of the dairy cow. It is estimated that between 30% and 50% of all cows experience metabolic or infectious disease during this time. One of the most common and economically consequential effects of disease during the transition period is a reduction in early lactation milk production. This has led to the utilisation of deviation from expected milk yield in early lactation as a proxy measure for transition health. However, to date, this analysis has been used exclusively for the retrospective assessment of transition cow health. Statistical models capable of predicting deviations from expected milk yield may allow producers to proactively manage animals predicted to suffer negative deviations in early lactation milk production. The objective of this retrospective cohort study was first, to explore the accuracy with which cow-level production and behaviour data collected on automatic milking systems (AMS) from 1–3 days in milk (DIM) can predict deviation from expected 30-day cumulative milk yield in multiparous cows. And second, to assess the accuracy with which predicted yield deviations can classify cows into groups which may facilitate improved transition management. Production, rumination, and physical activity data from 31 commercial AMS were accessed. A 3-step analytical procedure was then conducted. In Step 1, expected cumulative yield for 1–30 DIM for each individual cow-lactation was calculated using a mixed effect linear model. In Step 2, 30-Day Yield Deviation (YD) was calculated as the difference between observed and expected cumulative yield. Lactations were then assigned to one of three groups based on their YD, RED Group (0% YD). In Step 3, yield, rumination, and physical activity data from days 1–3 in lactation were used to predict YD using machine learning models. Following external validation, YD was predicted across the test data set with a mean absolute error of 9%. Categorisation of animals suffering large negative deviations (RED group) was achieved with a specificity of 99%, sensitivity of 35%, and balanced accuracy of 67%. Our results suggest that milk yield, rumination and physical activity patterns expressed by dairy cows from 1–3 DIM have utility in the prediction of deviation from expected 30-day cumulative yield. However, these predictions currently lack the sensitivity required to classify cows reliably and completely into groups which may facilitate improved transition cow management

The contribution of geogenic particulate matter to lung disease in indigenous children

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Indigenous children have much higher rates of ear and lung disease than non-Indigenous children, which may be related to exposure to high levels of geogenic (earth-derived) particulate matter (PM). The aim of this study was to assess the relationship between dust levels and health in Indigenous children in Western Australia (W.A.). Data were from a population-based sample of 1077 Indigenous children living in 66 remote communities of W.A. (>2,000,000 km2), with information on health outcomes derived from carer reports and hospitalisation records. Associations between dust levels and health outcomes were assessed by multivariate logistic regression in a multi-level framework. We assessed the effect of exposure to community sampled PM on epithelial cell (NuLi-1) responses to non-typeable Haemophilus influenzae (NTHi) in vitro. High dust levels were associated with increased odds of hospitalisation for upper (OR 1.77 95% CI [1.02–3.06]) and lower (OR 1.99 95% CI [1.08–3.68]) respiratory tract infections and ear disease (OR 3.06 95% CI [1.20–7.80]). Exposure to PM enhanced NTHi adhesion and invasion of epithelial cells and impaired IL-8 production. Exposure to geogenic PM may be contributing to the poor respiratory health of disadvantaged communities in arid environments where geogenic PM levels are high

Bayesian estimation of prevalence of paratuberculosis in dairy herds enrolled in a voluntary Johne’s Disease Control Programme in Ireland

Bovine paratuberculosis is a disease characterised by chronic granulomatous enteritis which manifests clinically as a protein-losing enteropathy causing diarrhoea, hypoproteinaemia, emaciation and, eventually death. Some evidence exists to suggest a possible zoonotic link and a national voluntary Johne’s Disease Control Programme was initiated by Animal Health Ireland in 2013. The objective of this study was to estimate herd-level true prevalence (HTP) and animal-level true prevalence (ATP) of paratuberculosis in Irish herds enrolled in the national voluntary JD control programme during 2013–14. Two datasets were used in this study. The first dataset had been collected in Ireland during 2005 (5822 animals from 119 herds), and was used to construct model priors. Model priors were updated with a primary (2013–14) dataset which included test records from 99,101 animals in 1039 dairy herds and was generated as part of the national voluntary JD control programme. The posterior estimate of HTP from the final Bayesian model was 0.23–0.34 with a 95% probability. Across all herds, the median ATP was found to be 0.032 (0.009, 0.145). This study represents the first use of Bayesian methodology to estimate the prevalence of paratuberculosis in Irish dairy herds. The HTP estimate was higher than previous Irish estimates but still lower than estimates from other major dairy producing countries