CAP-VSTNet: Content Affinity Preserved Versatile Style Transfer

Content affinity loss including feature and pixel affinity is a main problem which leads to artifacts in photorealistic and video style transfer. This paper proposes a new framework named CAP-VSTNet, which consists of a new reversible residual network and an unbiased linear transform module, for versatile style transfer. This reversible residual network can not only preserve content affinity but not introduce redundant information as traditional reversible networks, and hence facilitate better stylization. Empowered by Matting Laplacian training loss which can address the pixel affinity loss problem led by the linear transform, the proposed framework is applicable and effective on versatile style transfer. Extensive experiments show that CAP-VSTNet can produce better qualitative and quantitative results in comparison with the state-of-the-art methods.Comment: CVPR 202

New Self-Expanding Transcatheter Valve for Off-Pump Transatrial Mitral Valve-In-Ring Implantation.

OBJECTIVES To validate a self-expanding transcatheter valve for off-pump transatrial mitral valve-in-ring (VIR) implantation via a left thoracotomy. METHODS Mitral valve annuloplasty was performed via sternotomy during cardiopulmonary bypass on 9 pigs. After successful weaning from extracorporal circulation, the custom-made, self-expanding transcatheter VIR device was deployed under fluoroscopic guidance within the annuloplasty ring via a left thoracotomy. Hemodynamic data before and after the implantation were recorded. Mitral annulus diameter and valve area were measured by echocardiography. Transvalvular and left-ventricular outflow-tract pressure gradient were measured invasively. RESULTS Eight successful implantations were performed. Implantation failed in 1 pig because of difficulty with technical delivery of the sheath. Mean transatrial procedure time was 12.6 ± 1.7 min. Hemodynamic status during transatrial implantation was stable, and differences were not statistically significant. Mean mitral annulus diameter and mean mitral orifice area were 2.32 ± 0.2 and 3.84 ± 0.55 cm2, respectively. Mild regurgitation was detected in 7 animals and moderate regurgitation in 1. Mean gradients were 6.1 ± 5.0 mm Hg across the device. Postmortem examination confirmed adequate positioning of devices within the annuloplasty ring. CONCLUSIONS This custom-made transcatheter device allows for safe and reproducible off-pump transatrial mitral VIR implantations. Transatrial access is a promising route to facilitate VIR implantations. Our custom-made stent-valve may be suitable for VIR procedures

An Attention-Based Method for Remaining Useful Life Prediction of Rotating Machinery

Data imbalance and large data probability distribution discrepancies are major factors that reduce the accuracy of remaining useful life (RUL) prediction of high-reliability rotating machinery. In feature extraction, most deep transfer learning models consider the overall features but rarely attend to the local target features that are useful for RUL prediction; insufficient attention paid to local features reduces the accuracy and reliability of prediction. By considering the contribution of input data to the modeling output, a deep learning model that incorporates the attention mechanism in feature selection and extraction is proposed in our work; an unsupervised clustering method for classification of rotating machinery performance state evolution is put forward, and a similarity function is used to calculate the expected attention of input data to build an input data extraction attention module; the module is then fused with a gated recurrent unit (GRU), a variant of a recurrent neural network, to construct an attention-GRU model that combines prediction calculation and weight calculation for RUL prediction. Tests on public datasets show that the attention-GRU model outperforms traditional GRU and LSTM in RUL prediction, achieves less prediction error, and improves the performance and stability of the model

New Self-Expanding Transcatheter Valve for Off-Pump Transatrial Mitral Valve-In-Ring Implantation.

OBJECTIVES To validate a self-expanding transcatheter valve for off-pump transatrial mitral valve-in-ring (VIR) implantation via a left thoracotomy. METHODS Mitral valve annuloplasty was performed via sternotomy during cardiopulmonary bypass on 9 pigs. After successful weaning from extracorporal circulation, the custom-made, self-expanding transcatheter VIR device was deployed under fluoroscopic guidance within the annuloplasty ring via a left thoracotomy. Hemodynamic data before and after the implantation were recorded. Mitral annulus diameter and valve area were measured by echocardiography. Transvalvular and left-ventricular outflow-tract pressure gradient were measured invasively. RESULTS Eight successful implantations were performed. Implantation failed in 1 pig because of difficulty with technical delivery of the sheath. Mean transatrial procedure time was 12.6 ± 1.7 min. Hemodynamic status during transatrial implantation was stable, and differences were not statistically significant. Mean mitral annulus diameter and mean mitral orifice area were 2.32 ± 0.2 and 3.84 ± 0.55 cm2, respectively. Mild regurgitation was detected in 7 animals and moderate regurgitation in 1. Mean gradients were 6.1 ± 5.0 mm Hg across the device. Postmortem examination confirmed adequate positioning of devices within the annuloplasty ring. CONCLUSIONS This custom-made transcatheter device allows for safe and reproducible off-pump transatrial mitral VIR implantations. Transatrial access is a promising route to facilitate VIR implantations. Our custom-made stent-valve may be suitable for VIR procedures

Synergistic Application of Molecular Docking and Machine Learning for Improved Protein-Ligand Binding Pose Prediction

Accurate prediction of protein-ligand complex structures is a crucial step in structure-based drug design. Traditional molecular docking methods exhibit limitations in terms of accuracy and sampling space, while relying on machine-learning approaches may lead to invalid conformations. In this study, we propose a novel strategy that combines molecular docking and machine learning methods. Firstly, the protein-ligand binding poses are predicted using the Uni-Mol Docking machine learning approach. Subsequently, position-restricted docking(PR Docking) on predicted binding poses is performed using Uni-Dock, generating physically constrained and valid binding poses. Finally, the binding poses are re-scored and ranked using machine learning scoring functions. This strategy harnesses the predictive power of machine learning and the physical constraints advantage of molecular docking. Evaluation experiments on multiple datasets demonstrate that, compared to using molecular docking or machine learning methods alone, our proposed strategy can significantly improve the success rate and accuracy of protein-ligand complex structure predictions. This strategy is avaliable at https://github.com/dptech-corp/Uni-Dock

Characterization and Quantification of Luteolin-Metal Complexes in Aqueous Extract of Lonicerae Japonicae Flos and Huangshan Wild Chrysanthemum

Luteolin is a flavonoid compound widely found in vegetables, fruits, and medicinal plants. In this study, the reaction conditions for luteolin and five metal ions (Ca2+, Mg2+, Zn2+, Fe3+, and Cu2+) to form complexes in hot water were optimized, which was at a molar ratio of 1 : 1 for luteolin and metal ions at 90°C in a volume of 20 mL for 2 h, and the ability of luteolin to form complexes with Cu2+ was the strongest. The DPPH scavenging test showed that luteolin exerted a dose-dependent effect on the clearance of free radicals; luteolin-Cu2+ complexes and luteolin-Fe3+ complexes accentuated the clearance of free radicals. Furthermore, we used high performance liquid chromatography (HPLC) to analyze luteolin in samples from two medicinal plants, obtained from the dissolution of aqueous extracts in two different solvents. The results showed that the peak areas for luteolin in the samples dissolved in 20% formic acid-methanol were significantly larger than those from the samples dissolved in methanol alone, with increases in the peak area being 135.6% (Lonicerae Japonicae Flos), and 161.16% (Huangshan wild chrysanthemum). The aforementioned results indicate that complexes formed from organic compounds and metal ions are present in the decoction of a plant

Signature of quantum Griffiths singularity state in a layered quasi-one-dimensional superconductor

Quantum Griffiths singularity was theoretically proposed to interpret the phenomenon of divergent dynamical exponent in quantum phase transitions. It has been discovered experimentally in three-dimensional (3D) magnetic metal systems and two-dimensional (2D) superconductors. But, whether this state exists in lower dimensional systems remains elusive. Here, we report the signature of quantum Griffiths singularity state in quasi-one-dimensional (1D) TaPdS nanowires. The superconducting critical field shows a strong anisotropic behavior and a violation of the Pauli limit in a parallel magnetic field configuration. Current-voltage measurements exhibit hysteresis loops and a series of multiple voltage steps in transition to the normal state, indicating a quasi-1D nature of the superconductivity. Surprisingly, the nanowire undergoes a superconductor-metal transition when the magnetic field increases. Upon approaching the zero-temperature quantum critical point, the system uncovers the signature of the quantum Griffiths singularity state arising from enhanced quenched disorders, where the dynamical critical exponent becomes diverging rather than being constant

Overlooked Role of Coexistent Hydrogen Peroxide in Activated Peracetic Acid by Cu(II) for Enhanced Oxidation of Organic Contaminants

Cu(II)-catalyzed peracetic acid (PAA) processes have shown significant potential to remove contaminants in water treatment. Nevertheless, the role of coexistent H2O2 in the transformation from Cu(II) to Cu(I) remained contentious. Herein, with the Cu(II)/PAA process as an example, the respective roles of PAA and H2O2 on the Cu(II)/Cu(I) cycling were comprehensively investigated over the pH range of 7.0–10.5. Contrary to previous studies, it was surprisingly found that the coexistent deprotonated H2O2 (HO2–), instead of PAA, was crucial for accelerating the transformation from Cu(II) to Cu(I) (kHO2–/Cu(II) = (0.17–1) × 106 M–1 s–1, kPAA/Cu(II) –1 s–1). Subsequently, the formed Cu(I) preferentially reacted with PAA (kPAA/Cu(I) = (5.84 ± 0.17) × 102 M–1 s–1), rather than H2O2 (kH2O2/Cu(I) = (5.00 ± 0.2) × 101 M–1 s–1), generating reactive species to oxidize organic contaminants. With naproxen as the target pollutant, the proposed synergistic role of H2O2 and PAA was found to be highly dependent on the solution pH with weakly alkaline conditions being more conducive to naproxen degradation. Overall, this study systematically investigated the overlooked but crucial role of coexistent H2O2 in the Cu(II)/PAA process, which might provide valuable insights for better understanding the underlying mechanism in Cu-catalyzed PAA processes