Timely detection of surface damages on wind turbine blades is imperative for minimizing downtime and avoiding possible catastrophic structural failures. With recent advances in drone technology, a large number of high-resolution images of wind turbines are routinely acquired and subsequently analyzed by experts to identify imminent damages. Automated analysis of these inspection images with the help of machine learning algorithms can reduce the inspection cost. In this work, we develop a deep learning-based automated damage suggestion system for subsequent analysis of drone inspection images. Experimental results demonstrate that the proposed approach can achieve almost human-level precision in terms of suggested damage location and types on wind turbine blades. We further demonstrate that for relatively small training sets, advanced data augmentation during deep learning training can better generalize the trained model, providing a significant gain in precision.

Physical exercise increases peripheral insulin sensitivity, but regional differences are poorly elucidated in humans. We investigated the effect of aerobic exercise training on insulin-stimulated glucose uptake in five individual femoral muscle groups and four different adipose tissue regions, using dynamic (femoral region) and static (abdominal region) 2-deoxy-2-[¹⁸F]fluoro-d-glucose (FDG) PET/CT methodology during steady-state insulin infusion (40 mU·m⁻²·min⁻¹). Body composition was measured by dual X-ray absorptiometry and MRI. Sixty-one healthy, sedentary [V̇o_2max 36(5) ml·kg⁻¹·min⁻¹; mean(SD)], moderately overweight [BMI 28.1(1.8) kg/m²], young [age: 30(6) yr] men were randomized to sedentary living (CON; n = 17 completers) or moderate (MOD; 300 kcal/day, n = 18) or high (HIGH; 600 kcal/day, n = 18) dose physical exercise for 11 wk. At baseline, insulin-stimulated glucose uptake was highest in femoral skeletal muscle followed by intraperitoneal visceral adipose tissue (VAT), retroperitoneal VAT, abdominal (anterior + posterior) subcutaneous adipose tissue (SAT), and femoral SAT ( P < 0.0001 between tissues). Metabolic rate of glucose increased similarly (∼30%) in the two exercise groups in femoral skeletal muscle (MOD 24[9, 39] μmol·kg⁻¹·min⁻¹, P = 0.004; HIGH 22[9, 35] μmol·kg⁻¹·min⁻¹, P = 0.003) (mean[95% CI]) and in five individual femoral muscle groups but not in femoral SAT. Standardized uptake value of FDG decreased ∼24% in anterior abdominal SAT and ∼20% in posterior abdominal SAT compared with CON but not in either intra- or retroperitoneal VAT. Total adipose tissue mass decreased in both exercise groups, and the decrease was distributed equally among subcutaneous and intra-abdominal depots. In conclusion, aerobic exercise training increases insulin-stimulated glucose uptake in skeletal muscle but not in adipose tissue, which demonstrates some interregional differences.

Introduction: Brain imaging studies in healthy elderly subjects suggest a positive effect of aerobic exercise on both brain structure and function, while the effects of aerobic exercise in Alzheimer’s Disease (AD) has been scarcely investigated. Methods: In a single-blinded randomized MRI study, we assessed the effects of an aerobic exercise intervention on brain volume as measured by magnetic resonance imaging (MRI) and its correlation to cognitive functioning in patients with AD. The study was a sub-study of a larger randomized controlled trial (ADEX study). Forty-one patients were assigned to a control or exercise group. The exercise group performed 60-min of aerobic exercise three times per week for 16 weeks. All participants underwent whole-brain MRI at 3 Tesla and cognitive assessment at baseline and after 16 weeks. Attendance and intensity were monitored providing a total exercise load. Changes in regional brain volumes and cortical thickness were analyzed using Freesurfer software. Results: There was no effect of the type of intervention on MRI-derived brain volumes. In the entire group with and without training, Exercise load showed a positive correlation with changes in volume in the hippocampus, as well as frontal cortical thickness. Volume changes in frontal cortical thickness correlated with changes in measures of mental speed and attention and exercise load in the exercise group. Conclusion: We did not find evidence to support an effect of 16 weeks of aerobic exercise on brain volume changes in patients with AD. Longer intervention periods may be needed to affect brain structure as measured with volumetric MRI. Clinical Trial registration: ClinicalTrials.gov Identifier: NCT01681602, registered September 10th, 2012 (Retrospectively registered).

Objectives: To evaluate effects of active bike commuting or leisure-time exercise of two intensities on peripheral insulin sensitivity (primary outcome), cardiorespiratory fitness and intra-abdominal adipose tissue mass (secondary outcomes).Methods: 188 physically inactive, healthy women and men (20-45 years) with overweight or class 1 obesity were recruited. In the 6-month trial, 130 participants were randomised to either: no intervention (CON), active commuting (BIKE) or leisure-time exercise of moderate (MOD, 50% VO₂peak) or vigorous (VIG, 70% VO₂peak) intensity. 100 completed follow-up testing. Exercise prescription was 5 days/week with a weekly exercise energy expenditure of 1600 kcal for women and 2100 kcal for men. Testing was performed at baseline, 3 months and 6 months.Results: Peripheral insulin sensitivity (ml/min/pmol insulin/L) increased (improved) by 24% (95% CI 6% to 46%, p=0.01) in VIG compared with CON at 3 months. Peripheral insulin sensitivity increased (improved) by 20% in BIKE (95% CI 1% to 43%, p=0.04) and 26% in VIG (95% CI 7% to 47%, p<0.01) compared with CON at 6 months. Cardiorespiratory fitness increased in all exercise groups compared with CON at 6 months; but the increase was higher in those that undertook vigorous exercise than those who did moderate exercise. Intra-abdominal adipose tissue mass diminished across all exercise groups in comparison to CON at 6 months.Conclusions: Active bike commuting improved cardiometabolic health; as did leisure-time exercise. Leisure-time exercise of vigorous intensity conferred more rapid effects on peripheral insulin sensitivity as well as additional effects on cardiorespiratory fitness than did moderate intensity exercise.Trial registration: NCT01962259

Objective: In this study, wepropose an automatic diagnostic algorithm for detecting otitis media based on wideband tympanometry measurements. Methods: We develop a convolutional neural network for classification of otitis media based on the analysis of the wideband tympanogram. Saliency maps are computed to gain insight into the decision process of the convolutional neural network. Finally, we attempt to distinguish between otitis media with effusion and acute otitis media, a clinical subclassification important for the choice of treatment. Results: The approach shows high performance on the overall otitis media detection with an accuracy of 92.6%. However, the approach is not able to distinguish between specific types of otitis media. Conclusion: Out approach can detect otitis media with high accuracy and the wideband tympanogram holds more diagnostic information than the commonly used techniques wideband absorbance measurements and simple tympanograms. Significance: This study shows how advanced deep learning methods enable automatic diagnosis of otitis media based on wideband tympanometry measurements, which could become a valuable diagnostic tool.