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Flows in river habitats are characterized by unsteady turbulence due to the existence of woody debris, boulders and vegetation. As a representative aquatic species, fish is important for the riverine ecosystems, with its complex behavioural responses to turbulent flows. Previous studies investigated the fish–vortices interaction with vortex streets by placing objects with simplified geometries centred at the flow. Nonetheless, complex river morphology in natural rivers results in much more spatially heterogeneous flows due to randomly distributed obstructions. Thus, a semi‐circular cylinder patch located on one side of the flume is used to mimic a vegetation patch at the riverbank. The patch varies in diameter (D0 = 16, 20 and 24 cm) and density (φ = 0.04 and 0.1), whereas the flow velocity is fixed at 25 cm s−1. Fish are observed to swim in three typical patterns, which are "swim around" (pattern 1), "spill" (pattern 2) and "swim through" (pattern 3). For flow with a dense patch, all three patterns are recorded, but only patterns 1 and 2 are observed in sparse patches. It is noticed that in patterns 1 and 2, fish prefer to hold place in zones of low velocity and low turbulence. Moreover, variations in patch diameter have little influence on pattern selection. Results showed that tail beat amplitude (TBA*) in each zone displayed more variations compared with tail beat frequency (TBF). In addition, Spearman's rank tests revealed that TBA* is affected by none of the four hydrodynamic variables (U,ustd,τxy,Ωz), whereas flow velocity imposes the most influence on TBF. Both diameter and density of the patch displayed no significant influence on TBA* and TBF. [ABSTRACT FROM AUTHOR]

The sudden‐expansion effect created by natural and man‐made structures such as unsubmerged boulders, spur dikes, and culvert structures is common in open channels. Migratory fishes may use the heterogeneous flow generated by sudden expansion to their benefit, to select habitats for balancing energy expenditure or for maximizing predation opportunities. This study explores the swimming behavior of three size classes of crucian carp in response to hydrodynamic characteristics in an experimental open channel with sudden expansion. The flow field was characterized using particle image velocimetry (PIV) measurements and featured a recirculation zone in the vicinity of the expansion. Based on the classification of the swimming trajectory, four specific swimming behaviours (SSBs) were utilized by crucian carp during migration. With increasing flow velocity, fish spent more time in the recirculation zone. Residence time in the recirculation zone was inversely correlated with fish body length. Due to the advantage in providing shelter from challenging heterogeneous hydraulic conditions, the recirculation zone was preferred by crucian carp, especially the smaller ones, indicating the importance of energy conservation in habitat occupation. These findings confirm that the recirculation zone generated by sudden expansion may be beneficial to the upstream passage of fish and in habitat restoration. [ABSTRACT FROM AUTHOR]

Background: MRI of hyperpolarized 129 Xenon (HP 129 Xe) is increasingly utilized for investigating pulmonary function. The solubility of HP 129 Xe in lung tissue, blood plasma (Barrier), and red blood cells (RBC), with unique chemical shifts, enables spectroscopic imaging of potential imaging biomarkers of gas exchange and microstructural pulmonary physiology.Purpose: To quantify global average and regional repeatability of Barrier:gas, RBC:gas, and RBC:Barrier ratios derived from dissolved-phase 129 Xe imaging and their dependence on intervisit changes in lung inflation volume.Study Type: Prospective.Population: Fourteen healthy volunteers. One subject was unable to complete the study resulting in 13 subjects for analysis (eight female, five male, ages 24-69, 53.8 ± 13.9).Field Strength: 1.5T.Assessment: Subjects were imaged using a 3D radial 1-point Dixon method to separate Barrier and RBC component signals, at two different timepoints, with ~1 month between visits. RBC:Gas, Barrier:Gas, and RBC:Barrier measures were compared across time and with pulmonary function tests (PFTs).Statistical Tests: Repeatablilty was quantified using Bland-Altman plots, coefficient of repeatability, coefficient of variation (CV), and intraclass correlation coefficients (ICCs). Dependence of imaging measures on PFTs and lung volume was evaluated using Spearman and Pearson correlation coefficients, respectively. Statistical significance was determined by F-test for intraclass correlations, and t-test for Spearman correlations and regression.Results: Mean RBC:Gas, Barrier:Gas, and RBC:Barrier had CVs of 19.2%, 20.0%, and 11.5%, respectively, and had significant ICCs, equal to 0.78, 0.79, and 0.92, respectively. Intervisit differences in RBC:Barrier were significantly correlated with intervisit differences in DLCO (r = 0.93, P = 0.007). Significant correlations with intervisit lung volume differences and intervisit differences in mean RBC:Gas (r = -0.73, P = 0.005) and Barrier:Gas (r = -0.69, P = 0.009) were found.Data Conclusion: Three commonly used 129 Xe MRI-based measures of gas-exchange show good repeatability, particularly the Barrier:RBC ratio, which did not depend on lung inflation volume and was strongly associated with intervisit changes in DLCO .Level Of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1182-1190. [ABSTRACT FROM AUTHOR]

Background: Ultrashort echo time (UTE) proton MRI has gained popularity for assessing lung structure and function in pulmonary imaging; however, the development of rapid biomarker extraction and regional quantification has lagged behind due to labor-intensive lung segmentation.Purpose: To evaluate a deep learning (DL) approach for automated lung segmentation to extract image-based biomarkers from functional lung imaging using 3D radial UTE oxygen-enhanced (OE) MRI.Study Type: Retrospective study aimed to evaluate a technical development.Population: Forty-five human subjects, including 16 healthy volunteers, 5 asthma, and 24 patients with cystic fibrosis.Field Strength/sequence: 1.5T MRI, 3D radial UTE (TE = 0.08 msec) sequence.Assessment: Two 3D radial UTE volumes were acquired sequentially under normoxic (21% O2 ) and hyperoxic (100% O2 ) conditions. Automated segmentation of the lungs using 2D convolutional encoder-decoder based DL method, and the subsequent functional quantification via adaptive K-means were compared with the results obtained from the reference method, supervised region growing.Statistical Tests: Relative to the reference method, the performance of DL on volumetric quantification was assessed using Dice coefficient with 95% confidence interval (CI) for accuracy, two-sided Wilcoxon signed-rank test for computation time, and Bland-Altman analysis on the functional measure derived from the OE images.Results: The DL method produced strong agreement with supervised region growing for the right (Dice: 0.97; 95% CI = [0.96, 0.97]; P < 0.001) and left lungs (Dice: 0.96; 95% CI = [0.96, 0.97]; P < 0.001). The DL method averaged 46 seconds to generate the automatic segmentations in contrast to 1.93 hours using the reference method (P < 0.001). Bland-Altman analysis showed nonsignificant intermethod differences of volumetric (P ≥ 0.12) and functional measurements (P ≥ 0.34) in the left and right lungs.Data Conclusion: DL provides rapid, automated, and robust lung segmentation for quantification of regional lung function using UTE proton MRI.Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;50:1169-1181. [ABSTRACT FROM AUTHOR]

Background: A previous study demonstrated the feasibility of using 3D radial ultrashort echo time (UTE) oxygen-enhanced MRI (UTE OE-MRI) for functional imaging of healthy human lungs. The repeatability of quantitative measures from UTE OE-MRI needs to be established prior to its application in clinical research.Purpose: To evaluate repeatability of obstructive patterns in asthma and cystic fibrosis (CF) with UTE OE-MRI with isotropic spatial resolution and full chest coverage.Study Type: Volunteer and patient repeatability.Population: Eighteen human subjects (five asthma, six CF, and seven normal subjects).Field Strength/sequence: Respiratory-gated free-breathing 3D radial UTE (80 μs) sequence at 1.5T.Assessment: Two 3D radial UTE volumes were acquired sequentially under normoxic and hyperoxic conditions. A subset of subjects underwent repeat acquisitions on either the same day or ≤15 days apart. Asthma and CF subjects also underwent spirometry. A workflow including deformable registration and retrospective lung density correction was used to compute 3D isotropic percent signal enhancement (PSE) maps. Median PSE (MPSE) and ventilation defect percent (VDP) of the lung were measured from the PSE map.Statistical Tests: The relations between MPSE, VDP, and spirometric measures were assessed using Spearman correlations. The test-retest repeatability was evaluated using Bland-Altman analysis and intraclass correlation coefficients (ICC).Results: Ventilation measures in normal subjects (MPSE = 8.0%, VDP = 3.3%) were significantly different from those in asthma (MPSE = 6.0%, P = 0.042; VDP = 21.7%, P = 0.018) and CF group (MPSE = 4.5%, P = 0.0006; VDP = 27.2%, P = 0.002). MPSE correlated significantly with forced expiratory lung volume in 1 second percent predicted (ρ = 0.72, P = 0.017). The ICC of the test-retest VDP and MPSE were both ≥0.90. In all subject groups, an anterior/posterior gradient was observed with higher MPSE and lower VDP in the posterior compared to anterior regions (P ≤ 0.0021 for all comparisons).Data Conclusion: 3D radial UTE OE-MRI supports quantitative differentiation of diseased vs. healthy lungs using either whole lung VDP or MPSE with excellent test-retest repeatability.Level Of Evidence: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:1287-1297. [ABSTRACT FROM AUTHOR]

Summary: The automobile transmission is the core component of the automobile transmission system. Extracting effective fault feature information from a complex mechanical device like a car transmission is the key to fault diagnosis. In this paper, the vibration signals of the normal transmission and different faulty transmissions are collected through experiments, and the weak fault feature extraction of automobile transmission gears is based on the combination of Teager energy operator demodulation method and empirical mode decomposition method. Finally, the theory of SVM and its application in fault diagnosis are introduced. Based on the cross‐validation method, the grid search method and particle swarm optimization algorithm are used to search and optimize the important parameters in the SVM model to improve the performance of the SVM classifier. [ABSTRACT FROM AUTHOR]