A common volatilization trend in Transantarctic Mountain and Australasian microtektites: Implications for their formation model and parent crater location

ABSTRACT We investigate whether the galaxy and star formation model used for the Auriga simulations can produce a realistic globular cluster (GC) population. We compare statistics of GC candidate star particles in the Auriga haloes with catalogues of the Milky Way (MW) and Andromeda (M31) GC populations. We find that the Auriga simulations do produce sufficient stellar mass for GC candidates at radii and metallicities that are typical for the MW GC system (GCS). We also find varying mass ratios of the simulated GC candidates relative to the observed mass in the MW and M31 GCSs for different bins of galactocentric radius metallicity (rgal–[Fe/H]). Overall, the Auriga simulations produce GC candidates with higher metallicities than the MW and M31 GCS and they are found at larger radii than observed. The Auriga simulations would require bound cluster formation efficiencies higher than 10 per cent for the metal-poor GC candidates, and those within the Solar radius should experience negligible destruction rates to be consistent with observations. GC candidates in the outer halo, on the other hand, should either have low formation efficiencies, or experience high mass-loss for the Auriga simulations to produce a GCS that is consistent with that of the MW or M31. Finally, the scatter in the metallicity as well as in the radial distribution between different Auriga runs is considerably smaller than the differences between that of the MW and M31 GCSs. The Auriga model is unlikely to give rise to a GCS that can be consistent with both galaxies.

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Fourier analysis of an electrochemical phase formation model enables the rationalization of zinc-anode battery dynamics

Applications in Engineering Science ◽

10.1016/j.apples.2020.100033 ◽

2021 ◽

Vol 5 ◽

pp. 100033

Author(s):

Benedetto Bozzini ◽

Maria Chiara D’Autilia ◽

Claudio Mele ◽

Ivonne Sgura

Keyword(s):

Fourier Analysis ◽

Phase Formation ◽

Formation Model ◽

Zinc Anode ◽

Anode Battery

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Underwater Image Enhancement Based on Local Contrast Correction and Multi-Scale Fusion

Journal of Marine Science and Engineering ◽

10.3390/jmse9020225 ◽

2021 ◽

Vol 9 (2) ◽

pp. 225

Author(s):

Farong Gao ◽

Kai Wang ◽

Zhangyi Yang ◽

Yejian Wang ◽

Qizhong Zhang

Keyword(s):

Image Enhancement ◽

Local Contrast ◽

Fusion Method ◽

Formation Model ◽

Low Contrast ◽

White Balance ◽

Multi Scale ◽

Color Distortion ◽

Underwater Image ◽

Enhancement Method

In this study, an underwater image enhancement method based on local contrast correction (LCC) and multi-scale fusion is proposed to resolve low contrast and color distortion of underwater images. First, the original image is compensated using the red channel, and the compensated image is processed with a white balance. Second, LCC and image sharpening are carried out to generate two different image versions. Finally, the local contrast corrected images are fused with sharpened images by the multi-scale fusion method. The results show that the proposed method can be applied to water degradation images in different environments without resorting to an image formation model. It can effectively solve color distortion, low contrast, and unobvious details of underwater images.

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Underwater Image Restoration via Non-Convex Non-Smooth Variation and Thermal Exchange Optimization

Journal of Marine Science and Engineering ◽

10.3390/jmse9060570 ◽

2021 ◽

Vol 9 (6) ◽

pp. 570

Author(s):

Qingliang Jiao ◽

Ming Liu ◽

Pengyu Li ◽

Liquan Dong ◽

Mei Hui ◽

...

Keyword(s):

Image Restoration ◽

Qualitative And Quantitative Analysis ◽

Formation Model ◽

High Quality ◽

Thermal Exchange ◽

Qualitative And Quantitative ◽

Smooth Variation ◽

Underwater Image ◽

Dark Channel

The quality of underwater images is an important problem for resource detection. However, the light scattering and plankton in water can impact the quality of underwater images. In this paper, a novel underwater image restoration based on non-convex, non-smooth variation and thermal exchange optimization is proposed. Firstly, the underwater dark channel prior is used to estimate the rough transmission map. Secondly, the rough transmission map is refined by the proposed adaptive non-convex non-smooth variation. Then, Thermal Exchange Optimization is applied to compensate for the red channel of underwater images. Finally, the restored image can be estimated via the image formation model. The results show that the proposed algorithm can output high-quality images, according to qualitative and quantitative analysis.

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