Real-time Multi-person Eyeblink Detection in the Wild for Untrimmed Video

Real-time eyeblink detection in the wild can widely serve for fatigue detection, face anti-spoofing, emotion analysis, etc. The existing research efforts generally focus on single-person cases towards trimmed video. However, multi-person scenario within untrimmed videos is also important for practical applications, which has not been well concerned yet. To address this, we shed light on this research field for the first time with essential contributions on dataset, theory, and practices. In particular, a large-scale dataset termed MPEblink that involves 686 untrimmed videos with 8748 eyeblink events is proposed under multi-person conditions. The samples are captured from unconstrained films to reveal "in the wild" characteristics. Meanwhile, a real-time multi-person eyeblink detection method is also proposed. Being different from the existing counterparts, our proposition runs in a one-stage spatio-temporal way with end-to-end learning capacity. Specifically, it simultaneously addresses the sub-tasks of face detection, face tracking, and human instance-level eyeblink detection. This paradigm holds 2 main advantages: (1) eyeblink features can be facilitated via the face's global context (e.g., head pose and illumination condition) with joint optimization and interaction, and (2) addressing these sub-tasks in parallel instead of sequential manner can save time remarkably to meet the real-time running requirement. Experiments on MPEblink verify the essential challenges of real-time multi-person eyeblink detection in the wild for untrimmed video. Our method also outperforms existing approaches by large margins and with a high inference speed.Comment: Accepted by CVPR 202

Torsional fretting and torsional sliding wear behaviors of CuNiAl against 42CrMo4 under dry condition

Many wear failures are caused by a combination of fretting wear and sliding wear. In this study, the torsional fretting and torsional sliding wear properties of CuNiAl against 42CrMo4 were comparatively investigated under dry condition using a flat on flat contact tester. Experimental results showed that the sliding friction coefficients declined more dramatically than the fretting friction coefficients when the normal load increased. The fretting wear rate was lower than the sliding wear rate, which was partly due to the solid lubrication effect of the wear debris and strain hardening of the worn surfaces. The dominant wear mechanisms for the fretting tests were oxidation, cracks and delamination, while for the sliding tests were abrasion combined with plastic deformation

Influence of surface topography on torsional fretting wear under flat-on-flat contact

Influence of surface topography on torsional fretting under flat-on-flat contact were investigated. Contact surfaces of the lower specimens were prepared by milling with different initial surface roughness while the upper specimens were polished. Results indicate that with the increase of surface roughness, friction torque and accumulated dissipated energy present a first increase and then decrease tendency and are higher when the texture is perpendicular to the relative movement direction. The wear volume and wear rate present increasing and decreasing tendencies separately for textures parallel and perpendicular to the relative movement direction, and they are higher when the texture is parallel to the relative movement direction. The results can provide guidance for the initial surface design to reduce fretting wear

Optimization of Non-Uniform Perforation Parameters for Multi-Cluster Fracturing

Stress shadowing affects the simultaneous propagation of fractures from multiple perforation clusters. Employing uniform perforation parameters for all clusters cause the unbalanced growth of fractures, which arouses the demand of optimizing non-uniform perforation parameters. An optimization workflow combining a fracture propagation model and the particle swarm optimization method (PSO) is proposed for multi-cluster fracturing in this study. The fracture model considers the coupling of rock deformation and fluid flow along the wellbore and fractures, and it is solved by using the Newton iteration method. The optimization is performed by taking the variance of multiple fracture lengths as fitness value function in the frame of the PSO method. Numerical results show that using the same spacings and perforation parameters for all clusters is detrimental to the balanced growth of multiple fractures. The variance of fracture lengths drops greatly through optimization of cluster spacings and perforation number/diameter. Properly increasing the spacing and perforation number/diameter for the middle clusters promotes the balanced growth of multiple fractures. This study provides an efficient optimization workflow for multi-cluster fracturing treatment in horizontal wells

Optimization of Non-Uniform Perforation Parameters for Multi-Cluster Fracturing

Stress shadowing affects the simultaneous propagation of fractures from multiple perforation clusters. Employing uniform perforation parameters for all clusters cause the unbalanced growth of fractures, which arouses the demand of optimizing non-uniform perforation parameters. An optimization workflow combining a fracture propagation model and the particle swarm optimization method (PSO) is proposed for multi-cluster fracturing in this study. The fracture model considers the coupling of rock deformation and fluid flow along the wellbore and fractures, and it is solved by using the Newton iteration method. The optimization is performed by taking the variance of multiple fracture lengths as fitness value function in the frame of the PSO method. Numerical results show that using the same spacings and perforation parameters for all clusters is detrimental to the balanced growth of multiple fractures. The variance of fracture lengths drops greatly through optimization of cluster spacings and perforation number/diameter. Properly increasing the spacing and perforation number/diameter for the middle clusters promotes the balanced growth of multiple fractures. This study provides an efficient optimization workflow for multi-cluster fracturing treatment in horizontal wells

L-Carnitine Protects Renal Tubular Cells Against Calcium Oxalate Monohydrate Crystals Adhesion Through Preventing Cells From Dedifferentiation

Background/Aims: The interactions between calcium oxalate monohydrate (COM) crystals and renal tubular epithelial cells are important for renal stone formation but still unclear. This study aimed to investigate changes of epithelial cell phenotype after COM attachment and whether L-carnitine could protect cells against subsequent COM crystals adhesion. Methods: Cultured MDCK cells were employed and E-cadherin and Vimentin were used as markers to estimate the differentiate state. AlexaFluor-488-tagged COM crystals were used in crystals adhesion experiment to distinguish from the previous COM attachment, and adhesive crystals were counted under fluorescence microscope, which were also dissolved and the calcium concentration was assessed by flame atomic absorption spectrophotometry. Results: Dedifferentiated MDCK cells induced by transforming growth factor β1 (TGF-β1) shown higher affinity to COM crystals. After exposure to COM for 48 hours, cell dedifferentiation were observed and more subsequent COM crystals could bind onto, mediated by Akt/GSK-3β/Snail signaling. L-carnitine attenuated this signaling, resulted in inhibition of cell dedifferentiation and reduction of subsequent COM crystals adhesion. Conclusions: COM attachment promotes subsequent COM crystals adhesion, by inducing cell dedifferentiation via Akt/GSK-3β/Snail signaling. L-carnitine partially abolishes cell dedifferentiation and resists COM crystals adhesion. L-carnitine, may be used as a potential therapeutic strategy against recurrence of urolithiasis