YoloCurvSeg: You Only Label One Noisy Skeleton for Vessel-style Curvilinear Structure Segmentation

Weakly-supervised learning (WSL) has been proposed to alleviate the conflict between data annotation cost and model performance through employing sparsely-grained (i.e., point-, box-, scribble-wise) supervision and has shown promising performance, particularly in the image segmentation field. However, it is still a very challenging problem due to the limited supervision, especially when only a small number of labeled samples are available. Additionally, almost all existing WSL segmentation methods are designed for star-convex structures which are very different from curvilinear structures such as vessels and nerves. In this paper, we propose a novel sparsely annotated segmentation framework for curvilinear structures, named YoloCurvSeg, based on image synthesis. A background generator delivers image backgrounds that closely match real distributions through inpainting dilated skeletons. The extracted backgrounds are then combined with randomly emulated curves generated by a Space Colonization Algorithm-based foreground generator and through a multilayer patch-wise contrastive learning synthesizer. In this way, a synthetic dataset with both images and curve segmentation labels is obtained, at the cost of only one or a few noisy skeleton annotations. Finally, a segmenter is trained with the generated dataset and possibly an unlabeled dataset. The proposed YoloCurvSeg is evaluated on four publicly available datasets (OCTA500, CORN, DRIVE and CHASEDB1) and the results show that YoloCurvSeg outperforms state-of-the-art WSL segmentation methods by large margins. With only one noisy skeleton annotation (respectively 0.14%, 0.03%, 1.40%, and 0.65% of the full annotation), YoloCurvSeg achieves more than 97% of the fully-supervised performance on each dataset. Code and datasets will be released at https://github.com/llmir/YoloCurvSeg.Comment: 11 pages, 10 figures, submitted to IEEE Transactions on Medical Imaging (TMI

Femtosecond Laser Filamentation in Atmospheric Turbulence

The effects of turbulence intensity and turbulence region on the distribution of femtosecond laser filaments are experimentally elaborated. Through the ultrasonic signals emitted by the filaments, and it is observed that increasing turbulence intensity and expanding turbulence active region cause an increase in the start position of the filament, and a decrease in filament length, which can be well explained by the theoretical calculation. It is also observed that the random perturbation of the air refractive index caused by atmospheric turbulence expanded the spot size of the filament. Additionally, when turbulence intensity reaches , multiple filaments are formed. Furthermore, the standard deviation of the transverse displacement of filament is found to be proportional to the square root of turbulent structure constant under the experimental turbulence parameters in this paper. These results contribute to the study of femtosecond laser propagation mechanisms in complex atmospheric turbulence conditionsComment: 9 pages, 4 figure

Coupled air lasing gain and Mie scattering loss: aerosol effect in filament-induced plasma spectroscopy

Femtosecond laser filament-induced plasma spectroscopy (FIPS) demonstrates great potentials in the remote sensing for identifying atmospheric pollutant molecules. Due to the widespread aerosols in atmosphere, the remote detection based on FIPS would be affected from both the excitation and the propagation of fingerprint fluorescence, which still remain elusive. Here the physical model of filament-induced aerosol fluorescence is established to reveal the combined effect of Mie scattering and amplification spontaneous emission, which is then proved by the experimental results, the dependence of the backward fluorescence on the interaction length between filament and aerosols. These findings provide an insight into the complicated aerosol effect in the overall physical process of FIPS including propagation, excitation and emission, paving the way to its practical application in atmospheric remote sensing.Comment: 7 pages, 4 figure

Effects of misalignment on the nonlinear dynamics of a two-shaft rotor-bearing-gear coupling system with rub-impact fault

In rotor-bearing system, the misalignment can lead to secondary faults, such as the rub-impact fault. How the development of misalignment could affect the rub-impact force and other dynamic responses is important for the vibration control and fault diagnosis of rotor system. In this paper, a mathematical model of a two-shaft rotor-bearing- gear coupling system is established. The model is validated through the misaligned force of gear coupling, the supporting force of the lubricated ball bearing and the whole rotor response. To overcome the limit of traditional approaches and further dig out fault characteristics, the time-frequency method is introduced to analyze the dynamic response from both the time and frequency domains points of view. It is found the misalignment effect on rotor dynamic responses is mainly focused in high rotating speed range. The development of misalignment has an obvious adverse effect on the rotor stability. Some intermittent components in low frequency range due to the occurrence and development of misalignment can be found affecting the rotor stability at low speed range, and the high frequency rub-impact components can be found responsible for the unstable state of rotor

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing

The novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 2.3 million people, killed over 160,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven clinical efficacy, nor are there vaccines for its prevention, and these efforts are hampered by limited knowledge of the molecular details of SARS-CoV-2 infection. To address this, we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), identifying 332 high-confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (29 FDA-approved drugs, 12 drugs in clinical trials, and 28 preclinical compounds). Screening a subset of these in multiple viral assays identified two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the Sigma1 and Sigma2 receptors. Further studies of these host factor targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19

Numerical Study on Vibration Response and Fatigue Damage of Axial Compressor Blade Considering Aerodynamic Excitation

Axial compressor blades with a deformed initial torsion angle caused by aerodynamic excitation resonated at the working speed and changed the rule of fatigue damage accumulation. The fatigue life of a blade has a prediction error, even causing serious flight accidents if the effect of torque causing damage deterioration of the blade fatigue life is neglected. Therefore, in this paper, a uniaxial non-linear fatigue damage model was modified using the equivalent stress with torsional shear stress, and the proposed fatigue model including the torsional moment was used to study the compressor blade fatigue life. Then, the blade numerical simulation model was established to calculate the vibration characteristics under complex loads of airflow excitation and a rotating centrifugal force. Finally, the blade fatigue life under actual working conditions was predicted using the modified fatigue model. The results show that the interaction between centrifugal and aerodynamic loads affects the natural frequency, as the frequencies in modes dominated by bending deformation decreased whereas those dominated by torsional deformation increased. Furthermore, the blade root of the suction surface showed stress concentration, but there is an obvious difference of stress distribution and amplitude between the normal stress and the equivalent stress including torsional shear stress. The additional consideration of the torsional shear stress decreased the predicted fatigue life by 4.5%. The damage accumulation rate changes with the loading cycle, and it accelerates fast for the last 25% of the cycle, when the blade fracture may occur at any time. Thus, the aerodynamic excitation increased the safety factor of blade fatigue life prediction

A mathematical model for coupled vibration system of road vehicle and coupling effect analysis

info:eu-repo/semantics/publishe

Study on Lubrication Performance of Journal Bearing with Multiple Texture Distributions

The lubrication performance of journal bearings with different sorts of uniformly distributed micro-spherical textures are studied in this paper. Geometries and dynamic models of journal bearings with pure concave/convex textures are developed. The validity of the proposed models is verified against the oil film pressure distribution from the literature. The effects of geometry parameters (the texture depth and the area density) on the load capacity and the friction coefficient of the bearing are analyzed and discussed. Results indicate that: the bearing load capacity is reduced by the concave spherical texture, but enhanced by the convex texture; both the concave and convex textures have a very slight influence on the friction coefficient. Aiming to further improve the bearing lubrication performance, a novel concave-convex composite texture is proposed and modelled. Results show that the composite texture can significantly improve both the load capacity and the friction coefficient, because the concave spherical segments among the convex ones protect the oil film from rupture near the main load region. The oil film region is expanded by the composite texture as well