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Open AccessProceeding Paper

Synthesis, Characterization, and Regeneration of Ag/TiO₂ Nanoparticles: Photocatalytic Removal of Mixed Dye Pollutants

by Zainab S. Mahdi, Aseel M. Aljeboree, Fadhil A. Rasen, Noor Abd Alkhudhur Salman and Ayad F. Alkaim

Eng. Proc. 2023, 59(1), 216; https://doi.org/10.3390/engproc2023059216 - 26 Jan 2024

Cited by 4 | Viewed by 1288

Abstract

Titanium dioxide nanoparticles were prepared via the hydrothermal method, and silver was supported on Ti

O_{2}

nanoparticles to form Ag/Ti

O_{2}

using the photoreduction method. The prepared samples were dried overnight at

60^{\circ} C

and then calcined at [...] Read more.

Titanium dioxide nanoparticles were prepared via the hydrothermal method, and silver was supported on Ti

O_{2}

nanoparticles to form Ag/Ti

O_{2}

using the photoreduction method. The prepared samples were dried overnight at

60^{\circ} C

and then calcined at

500^{\circ} C

for 2 h. Structural and morphological characterization were carried out using X-ray diffraction, field emission scanning electron microscopy (FE-SEM), and transmission electron microscopy (TEM). The adsorption performance and photocatalytic activity of the Ag/Ti

O_{2}

were investigated using malachite green dye (MG) as a model organic pollutant in water. Along the way, the effects of various parameters were examined, such as regeneration experiments and removal of a laboratory sample (a mixture of several dyes) from aqueous solutions. The photocatalytic degradation efficiency reached 83.9%, 78.8%, and 68.5% during three cycles, compared to the standard solution (fresh), which reached 90.9%. These results underscore the potential application of Ag/Ti

O_{2}

in environmental remediation, particularly in the degradation of organic dyes. Full article

(This article belongs to the Proceedings of Eng. Proc., 2023, RAiSE-2023)

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11 pages, 1931 KB

Open AccessArticle

Localization of TWISTED NEEDLES Locus on Linkage Map of Japanese Cedar (Cryptomeria japonica D. Don)

by Yoshinari Moriguchi, Ryunosuke Saito, Saneyoshi Ueno, Yoichi Hasegawa, Hiroyuki Kakui and Asako Matsumoto

Forests 2022, 13(9), 1524; https://doi.org/10.3390/f13091524 - 19 Sep 2022

Cited by 1 | Viewed by 2445

Abstract

Sugi (Cryptomeria japonica D. Don) is an important forestry species in Japan. C. japonica ‘Spiralis’ is a mutant with twisted needles. The mutant is called Yore-sugi in Japan and is known as ‘Rasen’ in other countries. The twisted trait is regulated by a dominant gene called TWISTED NEEDLES, and it can be identified by observing the needles within 1 to 2 months after germination. The TWISTED NEEDLES gene may be useful for improving the efficiency of genome editing technology in C. japonica. In this study, we attempted to identify the linkage group of the TWISTED NEEDLES locus and investigate markers that sandwich this locus using the mapping family. First, we identified the linkage group containing the TWISTED NEEDLES locus based on the distortion from the expected segregation ratio using 32 mutant individuals of the mapping family. The segregation distortion showed that the TWISTED NEEDLES locus was located on the 11th linkage group (LG11). Next, a linkage map of LG11 was constructed based on genotype data from the single-nucleotide polymorphism (SNP) markers and double digested restriction site-associated DNA sequencing (ddRAD-seq) using 123 individuals of the MMY-1 family. On this map, six markers were located at the same position as the TWISTED NEEDLES locus. To investigate markers sandwiching the TWISTED NEEDLES locus, a partial linkage map around the TWISTED NEEDLES locus was constructed using 643 individuals of the MMY-1 family. The TWISTED NEEDLES locus was located in the 0.6 cM region between gSNP01822 and the other five markers (Contig_4705-179, Contig_4518-93, Contig_4398-118, gSNP04056, and Contig_4970-113). Full article

(This article belongs to the Special Issue Application of Biotechnology Techniques on Tree Species—Series II)

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18 pages, 388 KB

Open AccessArticle

Super RaSE: Super Random Subspace Ensemble Classification

by Jianan Zhu and Yang Feng

J. Risk Financial Manag. 2021, 14(12), 612; https://doi.org/10.3390/jrfm14120612 - 17 Dec 2021

Cited by 1 | Viewed by 2975

Abstract

We propose a new ensemble classification algorithm, named super random subspace ensemble (Super RaSE), to tackle the sparse classification problem. The proposed algorithm is motivated by the random subspace ensemble algorithm (RaSE). The RaSE method was shown to be a flexible framework that can be coupled with any existing base classification. However, the success of RaSE largely depends on the proper choice of the base classifier, which is unfortunately unknown to us. In this work, we show that Super RaSE avoids the need to choose a base classifier by randomly sampling a collection of classifiers together with the subspace. As a result, Super RaSE is more flexible and robust than RaSE. In addition to the vanilla Super RaSE, we also develop the iterative Super RaSE, which adaptively changes the base classifier distribution as well as the subspace distribution. We show that the Super RaSE algorithm and its iterative version perform competitively for a wide range of simulated data sets and two real data examples. The new Super RaSE algorithm and its iterative version are implemented in a new version of the R package RaSEn. Full article

(This article belongs to the Special Issue Predictive Modeling for Economic and Financial Data)

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