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Designing a ship hull to keep the hydrodynamic performance meet the requirements is an indispensable step in the ship's preliminary design. However, in the traditional design process, the design workload is labor-intensive and time-consuming due to the need to estimate a large number of design schemes. To address this issue, this work developed a Neural Network Proxy Model (NNPM) to assist the hydrodynamic resistance prediction for the ship hull design process. The data used in the NNPM construction was supported by two Computational Fluid Dynamic (CFD) methods with different fidelity where the low-fidelity one for tuning and pre-training, and the high-fidelity one for fine-training. To mitigate the risk of overfitting stemming from disparities in data volumes, the parameter freezing strategy is adopted during the high-fidelity dataset-based fine-training. The results obtained from validation numerical experiments indicated that the NNPM exhibited a forecast error of less than 1% when compared to the high-fidelity CFD method. Importantly, this high accuracy is achieved while maintaining a low construction workload, demonstrating the potential of Artificial Intelligence (AI) to predict the hydrodynamic load of hulls in the ship's preliminary design, which can further advance the artificial intelligence-assisted design (AIAD) technology for various marine structures. [ABSTRACT FROM AUTHOR]

Macrophages play crucial and versatile roles in regulating tissue repair and regeneration upon injury. However, due to their complex compositional heterogeneity and functional plasticity, deciphering the nature of different macrophage subpopulations and unraveling their dynamics and precise roles during the repair process have been challenging. With its distinct advantages, zebrafish (Danio rerio) has emerged as an invaluable model for studying macrophage development and functions, especially in tissue repair and regeneration, providing valuable insights into our understanding of macrophage biology in health and diseases. In this review, we present the current knowledge and challenges associated with the role of macrophages in tissue repair and regeneration, highlighting the significant contributions made by zebrafish studies. We discuss the unique advantages of the zebrafish model, including its genetic tools, imaging techniques, and regenerative capacities, which have greatly facilitated the investigation of macrophages in these processes. Additionally, we outline the potential of zebrafish research in addressing the remaining challenges and advancing our understanding of the intricate interplay between macrophages and tissue repair and regeneration. [ABSTRACT FROM AUTHOR]

Quantum dot light-emitting diodes (QLEDs) are emerging as promising contenders for next-generation display technology owing to their remarkable performance. In extensive research on QLEDs, MoO3 is commonly used as a replacement for the acidic hole injection material PEDOT:PSS to avoid acid corrosion of the indium tin oxide (ITO) electrode, thus preventing degradation of QLED performance. The advantages of solution-processed QLEDs make them an attractive option for large-scale production. Nowadays, achieving pixelation is still a critical step in the commercialization of QLEDs. In this work, we synthesized ultrafine MoO3 nanoparticles with an average grain size around 2 nm and successfully achieved MoO3 patterns through direct photolithography by incorporating photosensitizers. Furthermore, QLED devices with the photolithographed MoO3 as the hole injection layer (HIL) were fabricated, and pixel patterns with different shapes were designed and achieved. Compared to QLEDs based on pristine MoO3, the devices with photolithographic MoO3 exhibited a higher external quantum efficiency (EQE) and brightness. We believed that this work could establish a technological foundation for the development of high-resolution QLED displays. [ABSTRACT FROM AUTHOR]

Gold nanoparticles (AuNPs) have been extensively utilized in various fields such as sensors, life sciences, and catalysis. In this study, AuNPs were synthesized using a reduction method and subsequently treated with thiourea in an ethanol-water environment to prepare AuNPs film using a centrifugal deposition method for first time, resulting in the aggregation of the initial small-sized AuNPs into larger microsphere-like structures. The addition of thiourea facilitated the interconnection between AuNPs, ultimately leading to the formation of large stable gold microspheres. The sheet resistance of the AuNP films transitioned from being non-conductive to exhibiting a sheet resistance of 42.6 Ω/sq following thiourea treatment. The transformation from a flat surface to tightly connected particles resembling microspheres was observed from SEM images. The thiourea treatment not only altered the morphological characteristic of the AuNPs films but also significantly increased the number of scattering sites on their surface, leading to a substantial enhancement in the Raman scattering effect for methylene blue. This structural configuration also improved the electronic conduction and stability of the treated AuNPs films. Consequently, these findings suggest that AuNPs have promising application prospects in surface-enhanced Raman scatting (SERS), as well as in flexible electronics, catalysis, adsorption, and energy fields., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The understanding of nonlinear propagation effects in low-crosstalk few-mode fiber is crucial for a weakly coupled mode-division multiplexed system. In this Letter, we report the first, to the best of our knowledge, experimental verification of the advantage of intramodal dispersion on mitigating intramodal cross-phase modulation in a weakly coupled few-mode fiber transmission. The experimental system is established over a 70-km multiple-ring-core few-mode fiber accommodating 6 linearly polarized modes, based on which the influences of intramodal cross-phase modulation on transmission performances of each linearly polarized mode are evaluated. Experimental results show that the intramodal cross-phase modulation of degenerate linearly polarized modes with much larger intramodal dispersion values are significantly weaker than those of non-degenerate linearly polarized modes, in which the maximum suppression of intramodal cross-phase modulation noise is up to 9.7 dB. We believe that this work would be beneficial to practical applications of weakly coupled mode-division multiplexing technologies.

Herein, a novel method is presented for the in situ growth of gold nanofilms with branched structures in the presence of organosulfur. The key feature in this approach is the Rayleigh instability of ultrathin gold nanowires (AuNWs) without oleylamine (OAm), which allows the ultrathin AuNWs to decompose into gold nanoparticles (AuNPs) and the AuNPs to in situ grow into branched structures for high-performance stability and electrical conductivity. The sheet resistance of the gold nanofilms initially sharply decreased, whereas it subsequently slightly increased with the concentration of CS(NH 2 ) 2 until it exceeded the optimal range. After undergoing a 10 min heat treatment at 150 °C, the sheet resistance of the nanofilms was further reduced to 18 Ω/sq, which could be maintained for more than five months. The internal structure becomes fully grown and denser, forming a branched structure after heat treatment. Only certain organosulfurs can improve the electrical properties of the gold nanofilms, and the mechanism of organosulfur in the in situ growth of gold nanofilms with branched structures has also been presented. Overall, this novel method provides a straightforward and convenient approach to obtaining gold nanomaterials with branched structures, holding great potential promise for applications in flexible electronics, catalysis, and energy fields.

Introduction: Because Alzheimer's disease (AD) has significant heterogeneity in encephalatrophy and clinical manifestations, AD research faces two critical challenges: eliminating the impact of natural aging and extracting valuable clinical data for patients with AD., Methods: This study attempted to address these challenges by developing a novel machine-learning model called tensorized contrastive principal component analysis (T-cPCA). The objectives of this study were to predict AD progression and identify clinical subtypes while minimizing the influence of natural aging., Results: We leveraged a clinical variable space of 872 features, including almost all AD clinical examinations, which is the most comprehensive AD feature description in current research. T-cPCA yielded the highest accuracy in predicting AD progression by effectively minimizing the confounding effects of natural aging., Discussion: The representative features and pathogenic circuits of the four primary AD clinical subtypes were discovered. Confirmed by clinical doctors in Tangdu Hospital, the plaques (18F-AV45) distribution of typical patients in the four clinical subtypes are consistent with representative brain regions found in four AD subtypes, which further offers novel insights into the underlying mechanisms of AD pathogenesis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Han, Peng, Du, Li, Wang, Sun, Cui and Peng.)

In the development process of thick reservoirs, the impact of various geological factors on the effectiveness of the CO 2 water alternating gas (CO 2 -WAG) flooding technology remains unclear. This paper establishes multiple CO 2 -WAG flooding models for thick reservoirs to study the effects of sedimentary rhythm, dip angle, matrix permeability, high-permeability streaks (HPS), and barrier layers on the effectiveness of CO 2 -WAG flooding and then uses the random forest algorithm to rank the importance of these geological factors. The results show that different geological factors have varying degrees of impact on the distribution of water and gas migration and recovery rates during the CO 2 -WAG flooding process. The ranking of the importance of various factors obtained by reservoir numerical simulations and the random forest algorithm is HPS, sedimentary rhythm, dip angle, matrix permeability, and barrier layers. These research findings will provide effective guidance and a reference for the optimal selection of CO 2 -WAG flooding schemes for similar thick reservoirs under different geological conditions., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Aqueous nickel-ion batteries (ANIBs) as an emerging energy storage device attracted much attention owing to their multielectron redox reaction and dendrite-free Ni anode, yet their development is hindered by the divalent properties of Ni 2+ and the lack of suitable cathode materials. Herein, a hydrated iron vanadate (Fe 2 V 3 O 10.5 ∙1.5H 2 O, FOH) with a preferred orientation along the (200) plane is innovatively proposed and used as cathode material for ANIBs. The FOH cathode exhibits a remarkable capacity of 129.3 mAh g -1 at 50 mA g -1 and a super-high capacity retention of 95% at 500 mA g -1 after 700 cycles. The desirable Ni 2+ storage capacity of FOH can be attributed to the preferentially oriented and tunnel structures, which offer abundant reaction active planes and a broad Ni 2+ diffusion path, the abundant vacancies and high specific surface area further increase ion storage sites and accelerate ion diffusion in the FOH lattice. Furthermore, the Ni 2+ storage mechanism and structural evolution in the FOH cathode are explored through ex situ XRD, ex situ Raman, ex situ XPS and other ex situ characteristics. This work opens a new way for designing novel cathode materials to promote the development of ANIBs., (© 2024 Wiley‐VCH GmbH.)

We investigate the robustness of a modified multi-trench fiber (MTF) design with two gaps numerically. The excellent suppression of high-order modes is demonstrated over a wide range of the gap misalignment and the fundamental mode loss is barely affected even with the 5 dB/m scattering loss in gaps at the modified two-gap MTF for the first time. Therefore, the required fabrication accuracy decreases.