Assessing the efficiency of maintenance operators: a case study of turning railway wheelsets on an under-floor wheel lathe

The present paper assesses the technical efficiency of different operators turning railway wheelsets on a under-floor wheel lathe. This type of lathe is a Computer Numerical Control (CNC) machine used to turn wheelsets in-situ on the train. As railway wheels are turned, a certain amount of the wheel diameter is lost to restore the tread profile and full flange thickness of the wheel. The technical efficiencies of the different wheel lathe operators are assessed using a Stochastic Frontier Analysis (SFA), whilst controlling for other explaining variables such as the flange thickness and the occurrence of rolling contact fatigue (RCF) defects, wheel flats and cavities. Different model specifications for the SFA are compared with Linear Mixed Model (LMM) specifications, showing that the SFA model exhibits a better Akaike Information Criterion (AIC)

Detailed Clinical, Ophthalmic, and Genetic Characterization of ADGRV1-Associated Usher Syndrome

Purpose: To present the clinical characteristics, retinal features, natural history, and genetics of ADGRV1-Usher syndrome (USH). Design: Multicenter international retrospective cohort study. Methods: Clinical notes, hearing loss history, multimodal retinal imaging, and molecular diagnosis were reviewed. Thirty patients (28 families) with USH type 2 and disease-causing variants in ADGRV1 were identified. Visual function, retinal imaging, and genetics were evaluated and correlated, with retinal features also compared with those of the commonest cause of USH type 2, USH2A-USH. Results: The mean age at the first visit was 38.6 ± 12.0 years (range: 19-74 years), and the mean follow-up time was 9.0 ± 7.7 years. Hearing loss was reported in the first decade of life by all patients, 3 (10%) described progressive loss, and 93% had moderate-severe impairment. Visual symptom onset was at 17.0 ± 7.7 years of age (range: 6-32 years), with 13 patients noticing problems before the age of 16. At baseline, 90% of patients had no or mild visual impairment. The most frequent retinal features were a hyperautofluorescent ring at the posterior pole (70%), perimacular patches of decreased autofluorescence (59%), and mild-moderate peripheral bone-spicule–like deposits (63%). Twenty-six (53%) variants were previously unreported, 19 families (68%) had double-null genotypes, and 9 were not-double-null. Longitudinal analysis showed significant differences between baseline and follow-up central macular thickness (−1.25 µm/y), outer nuclear layer thickness (−1.19 µm/y), and ellipsoid zone width (−40.9 µm/y). The rate of visual acuity decline was 0.02 LogMAR (1 letter)/y, and the rate of constriction of the hyperautofluorescent ring was 0.23 mm2/y. Conclusions: ADGRV1-USH is characterized by early-onset, usually non-progressive, mild-to-severe hearing loss and generally good central vision until late adulthood. Perimacular atrophic patches and relatively retained ellipsoid zone and central macular thickness in later adulthood are more often seen in ADGRV1-USH than in USH2A-USH

Applying Bayesian model averaging for uncertainty estimation of input data in energy modelling

Background Energy scenarios that are used for policy advice have ecological and social impact on society. Policy measures that are based on modelling exercises may lead to far reaching financial and ecological consequences. The purpose of this study is to raise awareness that energy modelling results are accompanied with uncertainties that should be addressed explicitly. Methods With view to existing approaches of uncertainty assessment in energy economics and climate science, relevant requirements for an uncertainty assessment are defined. An uncertainty assessment should be explicit, independent of the assessor’s expertise, applicable to different models, including subjective quantitative and statistical quantitative aspects, intuitively understandable and be reproducible. Bayesian model averaging for input variables of energy models is discussed as method that satisfies these requirements. A definition of uncertainty based on posterior model probabilities of input variables to energy models is presented. Results The main findings are that (1) expert elicitation as predominant assessment method does not satisfy all requirements, (2) Bayesian model averaging for input variable modelling meets the requirements and allows evaluating a vast amount of potentially relevant influences on input variables and (3) posterior model probabilities of input variable models can be translated in uncertainty associated with the input variable. Conclusions An uncertainty assessment of energy scenarios is relevant if policy measures are (partially) based on modelling exercises. Potential implications of these findings include that energy scenarios could be associated with uncertainty that is presently neither assessed explicitly nor communicated adequately