Abstract ：

Underwater imaging technologies play a critical role in military operations, marine research and development, as well as engineering applications. However, the underwater environment with various of extraneous matter usually presents strong back-scattering and photon absorption effects when light propagates in this kind of media, thus leading to the poor imaging quality. Polarization difference imaging is an available method of suppressing back-scattered light while the method often results in lower brightness and some frequency components loss. A parameter optimization-based polarization difference fusion imaging method for underwater turbid medium is proposed in this paper. Back-scattering and polarization intensity can be estimated accurately by utilizing our proposed method, and further incorporates the estimated parameter values to better represent the global features and information of the scene. Experimental imaging tests were conducted on different targets, and the results demonstrate that the proposed method effectively overcomes the non-uniform illumination problem in underwater turbid medium conditions, enabling high-quality imaging of targets in such environments. © 2024 Elsevier Ltd

Keyword ：

Marine applications Polarization Backscattering Military applications Underwater imaging Military operations Turbidity

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Abstract ：

With the global outbreak of COVID-19, an increasing number of countries have made imported epidemic control a priority, imposing restriction measures to prevent the spread of the virus caused by imported cases. To control the imported epidemic, it is necessary to accurately predict the number of imported cases from different source countries. This paper proposes a novel time series prediction approach called PNICA (Prediction on Number of Imported CAses) that uses deep learning to predict the number of COVID-19 imported cases. On the one hand, the proposed PNICA approach adopts a multi-modal learning strategy to fuse three sources of data: flight data, the epidemic data, and the data of historical imported cases. On the other hand, the proposed PNICA approach extends the traditional transformer model with cross-modal attention to learn the interactions between different data modalities to improve prediction accuracy. We use China as the target country and collect the number of imported cases from four source countries—Japan, USA, Russia, and the UK—as well as the epidemic data and flight data from May to November 2020. Experiments on the collected data demonstrate that the proposed PNICA approach outperforms the baseline methods in predicting the number of imported cases. The ablation study shows that both the multi-modal learning strategy and cross-modal attention can significantly improve prediction performance. © 2024 Elsevier Ltd

Keyword ：

Prediction models COVID-19

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Abstract ：

Organizing interesting webpages into hot topics is one of key steps to understand the trends of multimodal web data. A state-of-the-art solution is firstly to organize webpages into a large volume of multi-granularity topic candidates; hot topics are further identified by estimating their interestingness. However, these topic candidates contain a large number of fragments of hot topics due to both the inefficient feature representations and the unsupervised topic generation. This paper proposes a bundling-refining approach to mine more complete hot topics from fragments. Concretely, the bundling step organizes the fragment topics into coarse topics; next, the refining step proposes a submodular-based method to refine coarse topics in a scalable approach. The propose unconventional method is simple, yet powerful by leveraging submodular optimization, our approach outperforms the traditional ranking methods which involve the careful design and complex steps. Extensive experiments demonstrate that the proposed approach surpasses the state-of-the-art method (i.e., latent Poisson deconvolution Pang et al. (2016)) 20% accuracy and 10% one on two public data sets, respectively. © 2024 Elsevier Ltd

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Abstract ：

Plume is an inherent physical phenomenon in fiber laser keyhole welding, negatively affecting welding quality. This paper proposes a new type of high-speed shielding gas microbeam (HSGM) based on the limitation of conventional shielding gas regulating plumes. The gas flow characteristics of the HSGM on the molten pool surface were explored using numerical simulation. Then, the coaxial double-layer shielding nozzle was trial-manufactured to clarify the regulation law for the HSGM on the plume. The gas velocity and pressure produced by the HSGM on the molten pool surface were positively correlated with the shielding gas flow rate, and the gas flow pattern was an acute triangle shape. The suitable HSGM can significantly restrain plume formation, improve the weld surface forming quality, increase the weld penetration depth (about 15.4%), and reduce the mass loss of the weld (about 58.7%). The significant blowing pressure effect of HSGM on plumes and splashes was the key to regulating the welding process. Compared with conventional shielding gas, the use of HSGM was significantly reduced. © 2024 Elsevier Ltd

Keyword ：

Spatter High-speed shielding gas microbeam Plume Welding quality Fiber laser welding

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Marine recirculating aquaculture systems (marine RAS) are increasingly utilized for their high productivity and minimal environmental impact. However, effective nutrient management and biosecurity measures remain crucial for sustainable operation of marine RAS. This study successfully established a simultaneous nitrification and denitrification (SND) process using a biofloc technology (BFT)–ultrafiltration (UF) combined approach. A stable autotrophic marine nitrification system was rapidly initiated within 23 days using a ceramic ring (CR)–granular activated carbon (GAC)–UF process (CGUF), followed by the substitution of polyhydroxyalkanoates (PHA) for GAC filter to achieve rapid start-up of SND in 24 h (CG/PUF). Soluble reactive phosphate (SRP) was removed in-situ via biofloc adsorption. The co-existence of ammonia-oxidizing archaea (Candidatus_Nitrosopumilus) and denitrifying bacteria (Stenotrophomonas, Ruegeria and Ilumatobacter) synergistic promoted the SND start-up in CG/PUF process. Stenotrophomonas emerged as the keystone species which closely linked to amoA/B/C, hao and nosZ genes (p −2∙ h−1 (LMH) for 180 days, with a 2-day intermittent hydraulic flushing keeping transmembrane pressure below 50 kPa. These findings provide insights for broader application of BFT–UF combined process in marine RAS. © 2024 Elsevier B.V.

Keyword ：

Aquaculture Elastin Ultrafiltration Nitrification Denitrification

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Abstract ：

High energy consumption represents one of the hindrances in enabling large scale application of membrane distillation. In this work, experimental and simulation studies of a double-effect direct-contact membrane distillation integrated with a single-stage vapor-compression heat pump (DE-DCMD-HP) were carried out for concentrating tap water with the aim to evaluate the energy saving of the integrated system. It was found during our experiments that an auxiliary cooler must be added to remove the excess heat from HP to enable the integrated system to reach the steady-state condition. The temperature-heat flux plots were first utilized to analyze how HP and DE-DCMD affected each other and reveal their coupling mechanism. The simulation results showed that the increase in the first-effect feed inlet temperature, Tfi,1 and the flow rate, V caused the thermodynamic cycle line of refrigerant shift to higher temperature, which led to the increase of the input power of the compressor and the auxiliary cooler, ultimately affecting the water production mass rate, ṁd, the coefficient of performance, COP, the gain output ratio, GOR, and the specific energy consumption, SEC. The experimental and simulation results revealed that increasing Tfi,1 and V increased the permeate flux Nh and GOR and reduced the SEC. The performances for three different DCMD configurations were furthermore evaluated via experiments at constant feed temperature whereby the SEC decreased from 2168 kWh·t−1 for single-effect DCMD to 1085 kWh·t−1 for DE-DCMD to 257 kWh·t−1 for DE-DCMD-HP. © 2024 The Authors

Keyword ：

Specific energy consumption Permeation flux Hollow fiber Thermodynamic Coupling mechanism

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Abstract ：

As an energy and carbon saving process for nitrogen removal from wastewater, the partial nitrification and denitrification process (PN/D) has been extensively researched. However, achieving stable PN in municipal wastewater has always been challenging. In this study, a gel immobilized PN/D nitrogen removal process (GI-PN/D) was established. A 94d pilot-scale experiment was conducted using real municipal wastewater with an ammonia concentration of 43.5 ± 5.3 mg N/L at a temperature range of 11.3–28.7℃. The nitrogen removal performance and associated pathways, shifts in the microbial community as well as sludge yield were investigated. The results were as follows: the effluent TN and COD were 0.6 ± 0.4 mg/L and 31.1 ± 3.8 mg/L respectively, and the NAR exceeding 95 %. GI-PN/D achieved deep nitrogen removal of municipal wastewater through stable PN without taking any other measures. The primary pathways for nitrogen removal were identified as denitrification, simultaneous nitrification-denitrification, and aerobic denitrification. High-throughput sequencing analysis revealed that the immobilized fillers facilitated the autonomous enrichment of functional bacteria in each reactor, effectively promoting the dominance and stability of the microbial communities. In addition, GI-PN/D had the characteristic of low sludge yield, with an average sludge yield of 0.029 kg SS/kg COD. This study provides an effective technical for nitrogen removal from municipal wastewater through PN. © 2024

Keyword ：

Gel immobilization Sludge yield Autonomous enrichment Deep nitrogen removal Partial nitrification

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Abstract ：

The organic compound composition of wastewater, serves as a crucial indicator for the operational performance of activated sludge processes and has a major influence on the development of filamentous bulking in activated sludge. This study focused on the impact of typical soluble and slowly-biodegradable organic compounds, investigating the pathways through which these substrates affect the occurrence of filamentous bulking in systems operated under both high- and low-oxygen conditions. Results showed that slowly-biodegradable organic compounds lead to a concentrated distribution of microorganisms within flocs, with inward growth of filamentous bacteria. Both Tween-80 and granular starch treated systems exhibited a significant increase in protein content. The glucose system, utilizing soluble substrates, exhibited a markedly higher total polysaccharide content. Microbial communities in the Tween-80 and granular starch treated systems were characterized by a higher abundance of bacteria known to enhance sludge flocculation and settling, such as Competibacter, Xanthomonadaceae and Zoogloea. These findings are of high significance for controlling the operational performance and stability of activated sludge systems, deepening our understanding and providing a novel perspective for the improvement of wastewater treatment processes. © 2024

Keyword ：

EPS Microbial community Slowly biodegradable organic compounds Sludge bulking Sludge morphology

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Abstract ：

In this article, we focus on an efficient multilevel finite element method to solve the time-dependent nonlinear Schrödinger equation which is one of the most important equations of mathematical physics. For the time derivative, we adopt implicit schemes including the backward Euler method and the Crank–Nicolson method. Based on these stable implicit schemes, the proposed method requires solving a nonlinear elliptic problem at each time step. For these nonlinear elliptic equations, a multilevel mesh sequence is constructed. At each mesh level, we first derive a rough approximation by correcting the approximation of the previous mesh level in a special correction subspace. The correction subspace is composed of a coarse finite element space and an additional approximate solution derived from the previous mesh level. Next, we only need to solve a linearized elliptic equation by inserting the rough approximation into the nonlinear term. Then, we derive an accurate approximate solution by performing the aforementioned solving process on the multilevel mesh sequence until we reach the final mesh level. Owing to the special construct of the correction subspace, we derive a multilevel finite element method to solve the nonlinear Schrödinger equation for the first time, and meanwhile we also derive an optimal error estimate with linear computational complexity. Additionally, unlike the existing multilevel methods for nonlinear problems, that typically require bounded second-order derivatives of the nonlinear terms, the nonlinear term in our study requires only one-order derivatives. Numerical results are provided to support our theoretical analysis and demonstrate the efficiency of the presented method. © 2024 Elsevier B.V.

Keyword ：

Subspace correction Finite element method Nonlinear Schrödinger problem Multilevel finite element method

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Abstract ：

The intermetallic compounds based on the tetragonal ThMn12 prototype crystal structure have exhibited great potential as advanced rare-earth-lean permanent magnets due to their excellent intrinsic magnetic properties. However, the trade-off between the phase stability and the magnetic performance is often encountered in the ThMn12-type magnets. This work was focused on the effects of V doping and nanostructuring on the phase stability and magnetic properties of ThMn12-type Sm-Co-based magnets. Novel SmCo12-based nanocrystalline alloys with the SmCo12 main phase were prepared for the first time. The prepared alloys from the optimal design achieved obviously higher coercivity than the isotropic SmFe12-based alloys, together with comparable performance of other magnetic features. The enhancement in the coercivity was ascribed to the pinning of domain walls by the nanocrystalline grain boundaries and stacking faults. First-principles calculations and magnetic structure analysis disclosed that V substitution can stabilize the SmCo12 lattice and elevate its magnetocrystalline anisotropy. This study provides a new approach to developing stabilized metastable structured rare-earth-lean alloys with high magnetic performance. © 2024

Keyword ：

Phase stability Coercivity SmCo12-based magnets Nanostructuring

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