Coleridge: A computer tool for assisting musical reflection and self‐explanation

This paper examines some of the problems involved when learning how to compose music. A prototype computer‐based music tool called Coleridge is described. Coleridge was used in a study that investigated the dialogues that took place when a mentor attempted to encourage creative reflection in students. Results of dialogue analysis suggested that because learners seem unable to make accurate predictions about how a musical phrase will sound, there is a real need for a computer‐based learning assistant. Finally, the paper reports on how these findings were used to motivate the design of a mentor's assistant in a new version of Coleridge

The Changing Face of Milk Production, Milk Quality and Milking Technology in Brazil

This introductory paper gives an overview of milk production in Brazil and discusses a series of recent regulations implemented to improve milk quality with the purpose of asserting the Brazilian dairy industry as a competitor on the international market. It also points out the economic advantage of setting design guidelines for milking machines that would be best suited to Brazilian crossbred cows.Brazilian Milk Quality, Brazil Dairy Industry, Brazilian Milk Production, Brazilian Milk Prices, Agribusiness, Farm Management, Food Consumption/Nutrition/Food Safety, Industrial Organization, International Development, Political Economy,

Real-time PCR-based methods for detection of Hepatitis E virus in pork products: a critical review

Standard methods for detection of hepatitis A virus and norovirus in at-risk foodstuffs are available, but currently there is no standard method for detection of hepatitis E virus (HEV) in pork products or other foods that can be contaminated with the virus. Detection assays for HEV are mainly based on nucleic acid amplification, particularly the reverse transcription polymerase chain reaction (RTPCR) in real-time format. RTPCR-based methods can be sensitive and specific, but they require a suite of controls to verify that they have performed correctly. There have been several RTPCR methods developed to detect HEV in pork products, varying in details of sample preparation and RTPCR target sequences. This review critically discusses published HEV detection methods, with emphasis on those that have been successfully used in subsequent studies and surveys. RTPCR assays have been used both qualitatively and quantitatively, although in the latter case the data acquired are only reliable if appropriate assay calibration has been performed. One particular RTPCR assay appears to be ideal for incorporation in a standard method, as it has been demonstrated to be highly specific and sensitive, and an appropriate control and calibration standard is available. The review focuses on the detection of HEV in pork products and similar foodstuffs (e.g., boar). The information may be useful to inform standardisation activities

Development of a disease-specific health utility score for Chronic Obstructive Pulmonary Disease from a Discrete Choice Experiment patient preference study

Acknowledgements; We wish to acknowledge the support of Katie Mycock, Tom Gardner, Phil Mellor, Pam Hallworth, Kate Sully, Sophi Tatlock, Beyza Klein, Gerard Criner, Pierre-Régis Burgel, Olivier Le Rouzic, Kip Adams, Kirsten Phillips, Mike McKevitt, and Kazuko Toyama for their involvement and contributions to the design, conduct and analysis of this patient preference study, and Kevin Marsh for comments and suggestions for further analyses based on a manuscript draft. Funding statement: The study was funded in full by Novartis Pharma AG. Byron Jones and Nigel Cook are employees of Novartis Pharma AG. At the time of writing, Florian Gutzwiller was an employee of Novartis Pharma AG.Peer reviewe

Exploratory analysis of multivariate drill core time series measurements

Demand for mineral resources is increasing, necessitating exploitation of lower grade and more heterogeneous orebodies. The high variability inherent in such orebodies leads to an increase in the cost, complexity and environmental footprint associated with mining and mineral processing. Enhanced knowledge of orebody characteristics is thus vital for mining companies to optimize profitability. We present a pilot study to investigate prediction of geometallurgical variables from drill sensor data. A comparison is made of the performance of multilayer perceptron (MLP) and multiple linear regression models (MLR) for predicting a geometallurgical variable. This comparison is based on simulated data that are physically realistic, having been derived from models fitted to the one available drill core. The comparison is made in terms of the mean and standard deviation (over repeated samples from the population) of the mean absolute error, root mean square error, and coefficient of determination. The best performing model depends on the form of the response variable and the sample size. The standard deviation of performance measures tends to be higher for the MLP, and MLR appears to offer a more consistent performance for the test cases considered. References R. M. Balabin and S. V. Smirnov. Interpolation and extrapolation problems of multivariate regression in analytical chemistry: Benchmarking the robustness on near-infrared (NIR) spectroscopy data”. Analyst 137.7 (2012), pp. 1604–1610. doi: 10.1039/c2an15972d C. M. Bishop. Pattern recognition and machine learning. Springer, 2006. url: https://link.springer.com/book/9780387310732 J. B. Boisvert, M. E. Rossi, K. Ehrig, and C. V. Deutsch. Geometallurgical modeling at Olympic dam mine, South Australia”. Math. Geosci. 45 (2013), pp. 901–925. doi: 10.1007/s11004-013-9462-5 T. Bollerslev. Generalized autoregressive conditional heteroskedasticity”. J. Economet. 31.3 (1986), pp. 307–327. doi: 10.1016/0304-4076(86)90063-1 C. Both and R. Dimitrakopoulos. Applied machine learning for geometallurgical throughput prediction—A case study using production data at the Tropicana Gold Mining Complex”. Minerals 11.11 (2021), p. 1257. doi: 10.3390/min11111257 J. Chen and G. Li. Tsallis wavelet entropy and its application in power signal analysis”. Entropy 16.6 (2014), pp. 3009–3025. doi: 10.3390/e16063009 S. Coward, J. Vann, S. Dunham, and M. Stewart. The primary-response framework for geometallurgical variables”. Seventh international mining geology conference. 2009, pp. 109–113. https://www.ausimm.com/publications/conference->url: https://www.ausimm.com/publications/conference- proceedings/seventh-international-mining-geology- conference-2009/the-primary-response-framework-for- geometallurgical-variables/ A. C. Davis and N. B. Christensen. Derivative analysis for layer selection of geophysical borehole logs”. Comput. Geosci. 60 (2013), pp. 34–40. doi: 10.1016/j.cageo.2013.06.015 C. Dritsaki. An empirical evaluation in GARCH volatility modeling: Evidence from the Stockholm stock exchange”. J. Math. Fin. 7.2 (2017), pp. 366–390. doi: 10.4236/jmf.2017.72020 R. F. Engle and T. Bollerslev. Modelling the persistence of conditional variances”. Econ. Rev. 5.1 (1986), pp. 1–50. doi: 10.1080/07474938608800095 A. S. Hadi and R. F. Ling. Some cautionary notes on the use of principal components regression”. Am. Statistician 52.4 (1998), pp. 15–19. doi: 10.2307/2685559 J. Hunt, T. Kojovic, and R. Berry. Estimating comminution indices from ore mineralogy, chemistry and drill core logging”. The Second AusIMM International Geometallurgy Conference (GeoMet) 2013. 2013, pp. 173–176. http://ecite.utas.edu.au/89773>url: http://ecite.utas.edu.au/89773 on p. C210). R. Hyndman, Y. Kang, P. Montero-Manso, T. Talagala, E. Wang, Y. Yang, M. O’Hara-Wild, S. Ben Taieb, H. Cao, D. K. Lake, N. Laptev, and J. R. Moorman. tsfeatures: Time series feature extraction. R package version 1.0.2. 2020. https://CRAN.R-project.org/package=tsfeatures>url: https://CRAN.R-project.org/package=tsfeatures on p. C222). C. L. Johnson, D. A. Browning, and N. E. Pendock. Hyperspectral imaging applications to geometallurgy: Utilizing blast hole mineralogy to predict Au-Cu recovery and throughput at the Phoenix mine, Nevada”. Econ. Geol. 114.8 (2019), pp. 1481–1494. doi: 10.5382/econgeo.4684 E. B. Martin and A. J. Morris. An overview of multivariate statistical process control in continuous and batch process performance monitoring”. Trans. Inst. Meas. Control 18.1 (1996), pp. 51–60. doi: 10.1177/014233129601800107 E. Sepulveda, P. A. Dowd, C. Xu, and E. Addo. Multivariate modelling of geometallurgical variables by projection pursuit”. Math. Geosci. 49.1 (2017), pp. 121–143. doi: 10.1007/s11004-016-9660-z S. J. Webb, G. R. J. Cooper, and L. D. Ashwal. Wavelet and statistical investigation of density and susceptibility data from the Bellevue drill core and Moordkopje borehole, Bushveld Complex, South Africa”. SEG Technical Program Expanded Abstracts 2008. Society of Exploration Geophysicists, 2008, pp. 1167–1171. doi: 10.1190/1.3059129 R. Zuo. Identifying geochemical anomalies associated with Cu and Pb–Zn skarn mineralization using principal component analysis and spectrum–area fractal modeling in the Gangdese Belt, Tibet (China)”. J. Geochem. Explor. 111.1-2 (2011), pp. 13–22. doi: 10.1016/J.GEXPLO.2011.06.01

Total or Partial Knee Arthroplasty Trial - TOPKAT : study protocol for a randomised controlled trial

Peer reviewedPublisher PD

A Rapid LAMP-Based Method for Screening Poultry Samples for Campylobacter Without Enrichment

Campylobacter is the most prominent bacterium associated with foodborne disease and the majority of human infection cases are attributed to chicken. Rapid methods capable of determining the Campylobacter status of poultry products in a short time are needed in today’s fast-paced food supply chain. In this study, we developed and evaluated an easy to perform, rapid and robust method for direct detection of Campylobacter in poultry carcasses based on loop-mediated isothermal DNA AMPlification (LAMP). The method does not require bacterial culture or DNA purification and generates results in just an hour. A total of 171 swabs from chicken and turkey slaughter houses were analyzed in parallel by both LAMP and conventional culture-based enumeration methods to evaluate the performance of the rapid method. Campylobacter was detected by LAMP in 100% of swabs with an enumeration result of ≥800 cfu/swab, and 98.6% (69 out of 70) of samples reported as negative by enumeration (≤10 cfu/swab) were also negative by LAMP. The method is also suitable for analysis of boot swabs from poultry houses, and therefore it represents a convenient screening tool that can be implemented on farm, at slaughter houses, processing plants or retail, to help with the control of Campylobacter contamination throughout the food supply chain. The inclusion of an internal amplification control prevents any potential false negative results due to DNA amplification inhibitors that might be present in the sample

Defining the needs and preferences of patients with dry eye disease

Objective Dry eye disease is a multifactorial chronic disease, leading to ocular discomfort and visual disturbance with a substantial impact on quality of life. Therefore, the patient's perspective should be taken into account early in the drug development process. We have developed a step-by-step methodology based on the self-explicated conjoint approach to assess the needs and preferences of patients with moderate-to-severe dry eye disease. Methods and Analysis Following a literature review and social media listening (step 0), qualitative phone call interviews were conducted with 12 patients (step 1). Patients' responses underwent content analysis and were coded, quantified and displayed as charts. Based on the emerging trends and attributes identified as relevant in steps 0 and 1, a quantitative online questionnaire was designed and conducted with 160 patients across four countries (step 2). Results The online questionnaire was rated as easy/very easy to understand by 60% of respondents, 62% rated the survey as easy/very easy to complete and 71% rated it as interesting/very interesting. Treatment satisfaction was the most important aspect for patients, and the three most relevant attributes were as follows (with the most important indexed to 100%): 'treatment effectiveness on symptoms of dry eyes' (100%), 'frequency of treatment use' (96%) and 'how the treatment works' (95%). Conclusion Our methodology was well received by patients, and the results will help inform future clinical trial development and discussions with health technology assessment bodies and regulators on unmet needs and product attributes that are of most value to patients with dry eye disease

Comparing the needs and preferences of patients with moderate and severe dry eye symptoms across four countries

Background/aims Understanding patients' perspectives of their disease can inform drug development and treatment decisions. In this study, we compared the preferences and needs of patients with moderate and severe dry eye symptoms from four different countries. Methods A quantitative questionnaire was developed based on the self-explicated conjoint methodology and was administered to 160 patients with moderate or severe dry eye disease (DED) from Australia, Germany, UK and the USA. Results Patients with moderate dry eye symptoms ranked 'treatment satisfaction' as the most important aspect, whereas 'symptom bother' was more relevant for those in the severe group. Both the moderate and severe groups classified treatment effectiveness as the most important treatment attribute. This result was consistent across the four countries, although US patients gave significantly higher scores than patients from other countries (p<0.001). Furthermore, patients from Australia ranked 'treatment experience' as significantly more important than the concern of side effects, whereas respondents from Germany exhibited the opposite trend (p<0.05 for both). The health burden of DED is reflected in the average European Quality of Life-5 Dimensions 5-level (EQ-5D) scores of 0.764 and 0.658 for patients with moderate and severe disease, respectively. Conclusion Our results confirm that across the countries in the study, moderate and severe DED has a major impact on patients' quality of life and daily activities. By providing insight into the patient perspective of DED, our study helps identify outcomes that are important to patients and may guide future drug development and clinical decision-making