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Maritime Power has gradually increased as a national strategy. In this process, gross marine products continue to grow, and the marine industry has become the most fundamental and critical object. The spatial layout and industrial organization of maritime enterprises are fundamental related tasks. Domestic research can be divided into two main categories, based on the data used. One is to use economic and social statistical data, which have a large spatial scope but large granularity and cannot reflect the details of the industrial layout. The other is to use point-of-interest data, which are often not fully mined owing to the heavy workload of data processing. Therefore, there is little relevant content on departmental and urban comparisons in the existing research. Four representative cities-Dalian, Qingdao, Ningbo, and Xiamen-were selected as the research areas. According to the Industrial Classification for Ocean Industries and Their Related Activities, the research objects were identified as the marine core layer, marine support layer, and marine peripheral layer industries and further refined into eight subcategories. This study is based on the information of maritime enterprises registered for business registration, and uses Python to crawl geographic coordinates to improve the spatial information of enterprises. An innovative task is to identify the industry categories of enterprises. This task was performed using fastText, Convolutional Neural Networks, and Recurrent Neural Network. Thus, a spatial enterprise information database, including multiple marine industry departments, was established. Kernel density analysis, standard deviational ellipse analysis, buffer analysis, and other methods were used. Finally, by comparing the visualization results of the marine industrial spatial layout in the four cities, we delved into the marine industrial spatial differentiation patterns. In the experiment, machine learning models, such as artificial neural networks, exhibited high accuracy and recall when completing human recognition tasks, and these methods were effective. Empirical research on the spatial layout and industrial organization of maritime enterprises revealed the following: 1)From the perspective of spatial pattern, the overall pattern is a balanced pattern of "large dispersion and small agglomeration." By comparing the distribution and organization of different types of marine industries, we found that there is industry agglomeration in the location selection of enterprises, resulting in industry agglomeration characteristics. The land sea relationship is reflected in the high-density single peak or "coastal zone-city center" Multimodal distribution pattern. 2) From the perspective of spatial organization mode, industrial clusters have multilevel hierarchical characteristics corresponding to population size and administrative levels. In addition to single core structures, multi core structures generally exhibit a "primary-secondary dual core" or "primary core-multiple radial" pattern, with spatial connections between core intervals forming a multi node axis or network structure. 3) From the perspective of spatial matching relationships, the elliptical area is positively related to the urban area, the direction of the long axis is close to the coastal direction, and the industrial distribution has a clear matching relationship with the urban center, ports, and other transportation hubs, bay terrain, coastline, and other spatial elements.

Quantifying the colors of objects is useful in a wide range of applications, including medical diagnosis, agricultural monitoring, and food safety. Accurate colorimetric measurement of objects is a laborious process normally performed through a color matching test in the laboratory. A promising alternative is to use digital images for colorimetric measurement, due to their portability and ease of use. However, image-based measurements suffer from errors caused by the non-linear image formation process and unpredictable environmental lighting. Solutions to this problem often perform relative color correction among multiple images through discrete color reference boards, which may yield biased results due to the lack of continuous observation. In this paper, we propose a smartphone-based solution, that couples a designated color reference board with a novel color correction algorithm, to achieve accurate and absolute color measurements. Our color reference board contains multiple color stripes with continuous color sampling at the sides. A novel correction algorithm is proposed to utilize a first-order spatial varying regression model to perform the color correction, which leverages both the absolute color magnitude and scale to maximize the correction accuracy. The proposed algorithm is implemented as a "human-in-the-loop" smartphone application, where users are guided by an augmented reality scheme with a marker tracking module to take images at an angle that minimizes the impact of non-Lambertian reflectance. Our experimental results show that our colorimetric measurement is device independent and can reduce up to 90% color variance for images collected under different lighting conditions. In the application of reading pH values from test papers, we show that our system performs 200% better than human reading. The designed color reference board, the correction algorithm, and our augmented reality guiding approach form an integrated system as a novel solution to measure color with increased accuracy. This technique has the flexibility to improve color reading performance in systems beyond existing applications, evidenced by both qualitative and quantitative experiments on example applications such as pH-test reading.

This paper first analyzes the network for 5G communication architecture and builds a framework for signal detection systems for wireless networks based on this architecture. Secondly, to better ensure the reliability of the signal detection system, the AE-ELM algorithm is built for wireless network signal detection by introducing an automatic coding machine and an overrun learning mechanism. Finally, an example is used to verify the reliability of the wireless network signal detection system in real-time. The results show that the signal detection rate of the real-time signal detection system with data volume over 300GB is 93% correct, and the maximum rate of missed rejection is about 6%. When SNR=25dB, the BER of the AE-ELM algorithm fluctuates around 10-5 with a variation of only about 0.1%. This shows that the signal detection system of a wireless network under 5G communication architecture has good reliability.

The processes of surfactant-enhanced soil washing have been widely applied to the remediation of polycyclic aromatic hydrocarbon (PAH)-contaminated soil, accompanied by the production of soil washing eluent. In this study, novel composite materials of beads containing alginate, carboxymethyl cellulose and diatomite (SCD) were used to encapsulate Bacillus subtilis to remove phenanthrene (PHE) from simulated soil washing eluent with rhamnolipid. The effects of dosage, pH and temperature on the PHE removal performance were explored, and the optimal PHE removal conditions [SCD bead dose 16.2% (w:v), pH 7.1 and 30.6°C] were determined using response surface methodology. After incubation in simulated soil washing eluent for 7 d, SCD beads removed 84.92% of PHE, which was 49.18% higher than by free bacteria. In addition, SCD beads mainly removed PHE through biodegradation processes, and the degradation rate (1.38 mg L−1 d−1) was higher than that of free bacteria (0.64 mg L−1 d−1). Characterization results revealed that the immobilized substrate provided the micro-environment for bacteria and reduced the intense effect of high rhamnolipid concentration. Reusability results showed that SCD beads could be recycled four times to remove 80.05% of PHE. Collectively, SCD beads have great prospects for the decontamination of soil-washing eluent containing complex components. [ABSTRACT FROM AUTHOR]

Despite its great promise in non-invasive treatment of cancers, magnetic resonance-guided focused ultrasound surgery (MRgFUS) is currently limited by the insensitivity of magnetic resonance imaging (MRI) for visualization of small tumors, low efficiency of in vivo ultrasonic energy deposition, and damage to surrounding tissues. We hereby report the development of an active targeting nano-sized theranostic superparamagnetic iron oxide (SPIO) platform for significantly increasing the imaging sensitivity and energy deposition efficiency using a clinical MRgFUS system. The surfaces of these PEGylated SPIO nanoparticles (NPs) were decorated with anti-EGFR (epidermal growth factor receptor) monoclonal antibodies (mAb) for targeted delivery to lung cancer with EGFR overexpression. The potential of these targeted nano-theranostic agents for MRI and MRgFUS ablation was evaluated in vitro and in vivo in a rat xenograft model of human lung cancer (H460). Compared with nontargeting PEGylated SPIO NPs, the anti-EGFR mAb targeted PEGylated SPIO NPs demonstrated better targeting capability to H460 tumor cells and greatly improved the MRI contrast at the tumor site. Meanwhile, this study showed that the targeting NPs, as synergistic agents, could significantly enhance the efficiency for in vivo ultrasonic energy deposition in MRgFUS. Moreover, we demonstrated that a series of MR methods including T2-weighted image (T2WI), T1-weighted image (T1WI), diffusion-weighted imaging (DWI) and contrast-enhanced T1WI imaging, could be utilized to noninvasively and conveniently monitor the therapeutic efficacy in rat models by MRgFUS.

The fastener clips of the high-speed railway may fracture due to accumulated fretting damage, posing a hazard to train operation safety. To investigate the evolution mechanism of fretting wear characteristics of high-speed railway fastener clips, this paper conducted fretting wear tests on 60Si2MnA steel used for clips and analyzed the fretting wear characteristics under different number of fretting cycles (N). The results indicate that as N increases, the friction coefficient rises initially, then falls, slightly rises again, and eventually stabilizes. Furthermore, the surface wear volume and depth of 60Si2MnA steel material increase continuously, and its fretting wear mechanism undergoes a transformation. Specifically, at 20,000 cycles, surface plastic deformation primarily causes material damage. While at 40,000 cycles, an oxide plastic deformation layer appears on the material surface, where adhesive wear and oxidation wear become the primary wear mechanisms. When N increases to 80,000, plastic strain accumulates continually on the material surface, causing the oxide plastic deformation layer in the outer contact area to break and detach gradually. Adhesive wear transforms into abrasive wear, cracks occur inside the material, and fatigue wear becomes a significant wear mechanism. This study fills the research gap in the fretting wear evolution mechanism of 60Si2MnA steel. [ABSTRACT FROM AUTHOR]

A comparative analysis was studied on the finishing performance of spherical CBN/Fe-based magnetic abrasive particles (MAPs) and Al2O3/Fe-based magnetic abrasive particles (MAPs) prepared by the gas atomization method in the magnetic abrasive finishing (MAF) of the Inconel 718 superalloy. In the MAF, it was found that compared with Al2O3/Fe-based MAPs, CBN/Fe-based MAPs have a lower grinding temperature and generate less heat during the grinding of the Inconel 718 superalloy. The grinding pressure generated on the workpiece is relatively stable (Al2O3/Fe-based MAPs have a larger fluctuation range of grinding pressure on the workpiece surface during the grinding process). The surface roughness of the workpiece rapidly drops from Ra 0.57 μm to Ra 0.039 μm, and the material removal reaches 42 mg within 20 min. After finishing, the scratches on the surface of the workpiece basically disappear, the contour curve is relatively flat, and there is almost no adhesion on the surface of the workpiece. The mirror effect of the superalloy surface is good, and ultimately a better surface quality can be obtained. [ABSTRACT FROM AUTHOR]

Eutrophication has become one of the most serious problems facing water environments. Exploring the relationship between anthropogenic activities and river trophic status provides effective information for environmental improvement and restoration, whilst the relationship remains poorly understood. Herein, 5225 water samples were collected monthly from 12 tributaries covered upstream in the Three Gorges Reservoir, China during 2014–2020. Quantitative anthropogenic activities based on land-use covers were used to establish correlations with tributary trophic status in small-scale watershed. The results showed that tributary trophic status had significant spatio-temporal variations and was the highest in summer, especially in July and August. Quantitative anthropogenic activities can explain well the eutrophic frequency and eutrophication risk in tributaries. Furthermore, it was proved that anthropogenic activities could accelerate the evolution of trophic status. Our findings increased the understanding of the interrelationship between humans and the environment and can provide practical strategies for river environmental restoration.