SyreaNet: A Physically Guided Underwater Image Enhancement Framework Integrating Synthetic and Real Images

Underwater image enhancement (UIE) is vital for high-level vision-related underwater tasks. Although learning-based UIE methods have made remarkable achievements in recent years, it's still challenging for them to consistently deal with various underwater conditions, which could be caused by: 1) the use of the simplified atmospheric image formation model in UIE may result in severe errors; 2) the network trained solely with synthetic images might have difficulty in generalizing well to real underwater images. In this work, we, for the first time, propose a framework \textit{SyreaNet} for UIE that integrates both synthetic and real data under the guidance of the revised underwater image formation model and novel domain adaptation (DA) strategies. First, an underwater image synthesis module based on the revised model is proposed. Then, a physically guided disentangled network is designed to predict the clear images by combining both synthetic and real underwater images. The intra- and inter-domain gaps are abridged by fully exchanging the domain knowledge. Extensive experiments demonstrate the superiority of our framework over other state-of-the-art (SOTA) learning-based UIE methods qualitatively and quantitatively. The code and dataset are publicly available at https://github.com/RockWenJJ/SyreaNet.git.Comment: 7 pages; 10 figure

Robust cross-linked Na3V2(PO4)2F3 full sodium-ion batteries

Sodium-ion batteries (SIBs) have rapidly risen to the forefront of energy storage systems as a promising supplementary for Lithium-ion batteries (LIBs). Na3V2(PO4)2F3 (NVPF) as a common cathode of SIBs, features the merits of high operating voltage, small volume change and favorable specific energy density. However, it suffers from poor cycling stability and rate performance induced by its low intrinsic conductivity. Herein, we propose an ingenious strategy targeting superior SIBs through cross-linked NVPF with multi-dimensional nanocarbon frameworks composed of amorphous carbon and carbon nanotubes (NVPF@C@CNTs). This rational design ensures favorable particle size for shortened sodium ion transmission pathway as well as improved electronic transfer network, thus leading to enhanced charge transfer kinetics and superior cycling stability. Benefited from this unique structure, significantly improved electrochemical properties are obtained, including high specific capacity (126.9 mAh g−1 at 1 C, 1 C = 128 mA g−1) and remarkably improved long-term cycling stability with 93.9% capacity retention after 1000 cycles at 20 C. The energy density of 286.8 Wh kg−1 can be reached for full cells with hard carbon as anode (NVPF@C@CNTs//HC). Additionally, the electrochemical performance of the full cell at high temperature is also investigated (95.3 mAh g−1 after 100 cycles at 1 C at 50 oC). Such nanoscale dual-carbon networks engineering and thorough discussion of ion diffusion kinetics might make contributions to accelerating the process of phosphate cathodes in SIBs for large-scale energy storages

Ultrasonic line source and its coupling with the tool induced heat generation and material flow in friction stir welding

To understand the synchronous interaction mechanism between the ultrasonic vibration exerted on the tool and the tool induced thermo-mechanical behavior in ultrasonic vibration-assisted friction stir welding (UVaFSW) process, the geometric shape of the contact surface between the horn and the tool was considered, and a previous point source of ultrasound was replaced by a line source which is more in line with the actual situation. With the established ultrasonic field model based on a line source of sound, the friction coefficient on the tool/workpiece interface was modified by considering the ultrasonic action from different directions. Combined with the computational fluid dynamics model, the UVaFSW process was numerically simulated. It was found that the line source of ultrasonic energy improved the computation accuracy of ultrasound pressure distribution, and ultrasonic antifriction effect greatly reduced the interfacial friction coefficient near the pin. The exerted ultrasonic vibration led to a slight overall decrease in total amount of heat generation in UVaFSW due to the dual effects of acoustic softening and ultrasonic antifriction. The model was validated by comparing the calculated thermal cycles and the thermo-mechanically affected zone with the experimental measurements

Electromagnetic Forming Rules of a Stiffened Panel with Grid Ribs

Electromagnetic forming (EMF), a technology with advantages of contact-free force and high energy density, generally aims at forming parts by using a fixed coil and one-time discharge. In this study, multi-stage EMF is introduced to form a panel with stiffened grid ribs. The forming rules of the stiffened panel is revealed via analyzing the distribution and evolution of the simulated stress and strain in the ribs and web, where the grid-rib panels were decomposed as the flat panel and two panels with uni-directional ribs (ribs only in X direction or Y direction). It is shown that the forming depth is mainly attributed to the forces on the web, although electromagnetic force is applied on both the ribs and the web, especially, large force on the ribs. The ribs are subjected to uniaxial stress parallel to their directions, and the web is subjected to plane stress in the deformation region. Furthermore, the change of the uniaxial stress characteristic in the X-direction ribs is influenced by the electromagnetic force, reverse bend and inertial effect. The plastic deformation mainly occurs in the Y-direction ribs of the deformation region under a three-direction strain state

Stage-specific appearance of cytoplasmic microtubules around the surviving nuclei during the third prezygotic division of Paramecium

There are six micronuclear divisions during conjugation of Paramecium caudatum : three prezygotic and three postzygotic divisions. Four haploid nuclei are formed during the first two meiotic prezygotic divisions. Usually only one meiotic product is located in the paroral cone (PC) region at the completion of meiosis, which survives and divides mitotically to complete the third prezygotic division to yield a stationary and a migratory pronucleus. The remaining three located outside of the PC degenerate. The migratory pronuclei are then exchanged between two conjugants and fuse with the stationary pronuclei to form synkarya, which undergo three successive divisions (postzygotic divisions). However, little is known about the surviving mechanism of the PC nuclei. In the current study, stage-specific appearance of cytoplasmic microtubules (cMTs) was indicated during the third prezygotic division by immunofluorescence labeling with anti-alpha tubulin antibodies surrounding the surviving nuclei, including the PC nuclei and the two types of prospective pronuclei. This suggested that cMTs were involved in the formation of a physical barrier, whose function may relate to sequestering and protecting the surviving nuclei from the major cytoplasm, where degeneration of extra-meiotic products occurs, another important nuclear event during the third prezygotic division

Characterization of the Microstructure Evolution of Ni-Based Superalloy at Liquidus Temperature by Electromagnetic Field

The effect of isothermal treatment temperatures and isothermal treatment time on the microstructure was studied. The results showed that the globular and equiaxed grains with the average grain size of 60 μm and the shape factor of circle of 0.95 can be obtained when the melt of Ni-Cr-W superalloy was subjected to the heat treatment of 10 min at 1400 °C. The quenching results showed the volume fraction of the eutectic phase was the largest and the volume fraction of primary γ phase was the smallest after the isothermal treatment of 1400 °C. The optimal melt treatment temperature and time were 1400 °C and 10 min, respectively. Moreover, the effect of electromagnetic field on the solidification was also investigated. It was demonstrated that applying electromagnetic field was beneficial to the uniform temperature, solute field and the high density of the secondary nuclei, which contributed to grain refinement

A two-stage density-aware single image deraining method

Although advanced single image deraining methods have been proposed, one main challenge remains: the available methods usually perform well on specific rain patterns but can hardly deal with scenarios with dramatically different rain densities, especially when the impacts of rain streaks and the veiling effect caused by rain accumulation are heavily coupled. To tackle this challenge, we propose a two-stage density-aware single image deraining method with gated multi-scale feature fusion. In the first stage, a realistic physics model closer to real rain scenes is leveraged for initial deraining, and a network branch is also trained for rain density estimation to guide the subsequent refinement. The second stage of model-independent refinement is realized using conditional Generative Adversarial Network (cGAN), aiming to eliminate artifacts and improve the restoration quality. In particular, dilated convolutions are applied to extract rain features at multiple scales and gated feature fusion is exploited to better aggregate multi-level contextual information in both stages. Extensive experiments have been conducted on representative synthetic rain datasets and real rain scenes. Quantitative and qualitative results demonstrate the superiority of our method in terms of effectiveness and generalization ability, which outperforms the state-of-the-art

An Improved Ship Trajectory Prediction Based on AIS Data Using MHA-BiGRU

According to the statistics of water transportation accidents, collision accidents are on the rise as the shipping industry has expanded by leaps and bounds, and the water transportation environment has become more complex, which can result in grave consequences, such as casualties, environmental destruction, and even massive financial losses. In view of this situation, high-precision and real-time ship trajectory prediction based on AIS data can serve as a crucial foundation for vessel traffic services and ship navigation to prevent collision accidents. Thus, this paper proposes a high-precision ship track prediction model based on a combination of a multi-head attention mechanism and bidirectional gate recurrent unit (MHA-BiGRU) to fully exploit the valuable information contained in massive AIS data and address the insufficiencies in existing trajectory prediction methods. The primary advantages of this model are that it allows for the retention of long-term ship track sequence information, filters and modifies ship track historical data for enhanced time series prediction, and models the potential association between historical and future ship trajectory status information with the current state via the bidirectional gate recurrent unit. Significantly, the introduction of a multi-head attention mechanism calculates the correlation between the characteristics of AIS data, actively learns cross-time synchronization between the hidden layers of ship track sequences, and assigns different weights to the result based on the input criterion, thereby enhancing the accuracy of forecasts. The comparative experimental results also verify that MHA-BiGRU outperforms the other ship track prediction models, demonstrating that it possesses the characteristics of ease of implementation, high precision, and high reliability