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15 pages, 427 KiB  
Article
The Influence of the Digital Economy on the Foreign Trade Competitiveness of Hunan Province in China
by Minglan Yuan, Hui Zhong, Zhijie Hao, Decai Tang and Eugene Ray Atsi
Sustainability 2025, 17(1), 2; https://doi.org/10.3390/su17010002 - 24 Dec 2024
Viewed by 401
Abstract
With the evolution of the Internet, artificial intelligence, and other technologies, the era of the digital economy has quietly emerged. The digital economy’s growth is a major trend, and China is dedicated to building data power and strengthening foreign trade competitiveness (FTC). As [...] Read more.
With the evolution of the Internet, artificial intelligence, and other technologies, the era of the digital economy has quietly emerged. The digital economy’s growth is a major trend, and China is dedicated to building data power and strengthening foreign trade competitiveness (FTC). As an essential strategic region, Hunan Province should grasp the opportunities of the digital economy and constantly develop and increase its competitiveness. This research will explore the effect of Digital economy (DIG) on the FTC of Hunan Province. The study collected data from the region from 2013 to 2022 and Stata 17 software was applied to obtain the research outcomes. The findings indicate that DIG can significantly enhance the development of FTC in Hunan Province. This result remains consistent even after conducting robustness tests, showing its reliability. Furthermore, the positive impact is even more pronounced in urban agglomerations of major cities and larger areas. The paper’s main innovation lies in its focus on the Hunan Province region, which holds significant regional importance and plays a key role in enhancing China’s FTC. Full article
(This article belongs to the Special Issue Digital Economy and Sustainable Development)
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<p>The DIG index.</p>
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22 pages, 16060 KiB  
Article
Study on the Dynamic Fracture Properties of Defective Basalt Fiber Concrete Materials Under a Freeze–Thaw Environment
by Guangzhao Pei, Dingjun Xiao, Miaomiao Zhang, Jiajie Jiang, Jiping Xie, Xiongzi Li and Junbo Guo
Materials 2024, 17(24), 6275; https://doi.org/10.3390/ma17246275 - 22 Dec 2024
Viewed by 413
Abstract
This study examines the crack resistance of basalt-fiber-reinforced concrete (BFRC) materials subjected to freeze–thaw cycles (FTCs). We utilized a φ50 mm Split Hopkinson Pressure Bar (SHPB) apparatus alongside numerical simulations to carry out impact compression tests at a velocity of 5 m/s on [...] Read more.
This study examines the crack resistance of basalt-fiber-reinforced concrete (BFRC) materials subjected to freeze–thaw cycles (FTCs). We utilized a φ50 mm Split Hopkinson Pressure Bar (SHPB) apparatus alongside numerical simulations to carry out impact compression tests at a velocity of 5 m/s on BFRC specimens that experienced 0, 10, 20, and 30 FTCs. Additionally, we investigated the effects of basalt fiber (BF) orientation position and length on stress intensity factors. The results reveal that with an increasing number of FTCs, the dynamic crack propagation speed of BFRC with a prefabricated crack inclined at 0° rises from 311.84 m/s to 449.92 m/s, while its pure I fracture toughness decreases from 0.6266 MPa·m0.5 to 0.4902 MPa·m0.5. For BFRC specimens with a prefabricated crack inclination of 15°, the dynamic crack propagation speed increases from 305.81 m/s to 490.02 m/s, accompanied by a reduction in mode I fracture toughness from 0.3901 MPa·m0.5 to 0.2867 MPa·m0.5 and mode II fracture toughness from 0.6266 MPa·m0.5 to 0.4902 MPa·m0.5. In the case of a prefabricated crack inclination of 28.89°, the dynamic crack propagation speed rises from 436.10 m/s to 494.28 m/s, while its pure mode II fracture toughness decreases from 1.1427 MPa·m0.5 to 0.7797 MPa·m0.5. Numerical simulations indicate that fibers positioned ahead of the crack tip—especially those that are longer, located closer to the crack tip, and oriented more perpendicularly—significantly reduce the mode I stress intensity factor. However, these fibers have a minimal impact on reducing the mode II stress intensity factor. The study qualitatively and quantitatively analyzes the crack resistance of basalt-fiber-reinforced concrete in relation to freeze–thaw cycles and the fibers ahead of the crack tip, offering insights into the fiber reinforcement effects within the concrete matrix. Full article
(This article belongs to the Special Issue Advances in Natural Rocks and Their Composite Materials)
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<p>Test setup and flow chart.</p>
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<p>The crack tip position and crack propagation speed of the specimen when the inclination angle of the precast crack is 0.</p>
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<p>The crack tip position and crack propagation speed of the specimen when the precast crack inclination angle is 15.</p>
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<p>The crack tip position and crack propagation speed of the specimen when the precast crack inclination angle is 28.89.</p>
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<p>The crack tip position and crack propagation speed of the specimen when the precast crack inclination angle is 28.89.</p>
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<p>Crack propagation path.</p>
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<p>Relationship between dynamic crack growth rate and FTC.</p>
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<p>SEM images of basalt fiber concrete with different freeze–thaw times.</p>
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<p>Numerical verification of Chen problem.</p>
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<p>Time history curve of stress intensity factor <span class="html-italic">K</span><sub>I</sub> when the inclination angle of the precast crack is 0.</p>
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<p>Time history curve of stress intensity factor <span class="html-italic">K</span><sub>I</sub> when the inclination angle of the precast crack is 15.</p>
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<p>Time history curve of stress intensity factor <span class="html-italic">K</span><sub>I</sub> when the inclination angle of the precast crack is 15.</p>
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<p>Time history curve of stress intensity factor <span class="html-italic">K</span><sub>II</sub> when the inclination angle of the precast crack is 15.</p>
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<p>Time history curve of stress intensity factor <span class="html-italic">K</span><sub>II</sub> when the inclination angle of the precast crack is 28.89.</p>
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<p>Fracture toughness of the Brazilian disc specimen with a straight crack platform in a dynamic fracture test center calculated by an experimental–numerical analysis method.</p>
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<p>Fiber distribution before crack tip.</p>
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<p>Stress intensity factors of concrete with different fiber lengths (<b>a</b>) <span class="html-italic">K</span><sub>I</sub> with a 0 inclination angle of precast crack; (<b>b</b>) <span class="html-italic">K</span><sub>II</sub> with a 28.89 inclination angle of precast crack; (<b>c</b>) <span class="html-italic">K</span><sub>I</sub> with a 15 inclination angle of precast crack; (<b>d</b>) <span class="html-italic">K</span><sub>II</sub> with a 15 inclination angle of precast crack.</p>
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<p>Force nephogram of fiber influence: (<b>a</b>) pure I stress nephogram; (<b>b</b>) pure II stress nephogram; (<b>c</b>) force nephogram of pure I fiber; (<b>d</b>) force nephogram of pure II fiber.</p>
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<p>Stress intensity factors of concrete under different fiber angles (<b>a</b>) <span class="html-italic">K</span><sub>I</sub> with a 0 inclination angle of precast crack; (<b>b</b>) <span class="html-italic">K</span><sub>II</sub> with a 28.89 inclination angle of precast crack; (<b>c</b>) <span class="html-italic">K</span><sub>I</sub> with a 15 inclination angle of precast crack; (<b>d</b>) <span class="html-italic">K</span><sub>II</sub> with a 15 inclination angle of precast crack.</p>
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<p>Force nephogram influenced by fiber angle: (<b>a</b>) pure I 0-degree fiber stress nephogram; (<b>b</b>) pure I 40-degree fiber stress nephogram; (<b>c</b>) pure II 0-degree fiber stress nephogram; (<b>d</b>) pure II 40-degree fiber stress nephogram.</p>
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<p>Stress intensity factors of concrete under different fiber positions: (<b>a</b>) <span class="html-italic">K</span><sub>I</sub> with a 0 inclination angle of the precast crack; (<b>b</b>) <span class="html-italic">K</span><sub>II</sub> with a 28.89 inclination angle of the precast crack; (<b>c</b>) <span class="html-italic">K</span><sub>I</sub> with a 15 inclination angle of the precast crack; (<b>d</b>) <span class="html-italic">K</span><sub>II</sub> with 15 inclination angle of the precast crack.</p>
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<p>Fiber position affects the force nephogram: (<b>a</b>) force nephogram of pure I short-distance fiber; (<b>b</b>) force nephogram of pure I long-distance fiber; (<b>c</b>) force nephogram of pure II short-distance fiber; (<b>d</b>) force nephogram of pure II long-distance fiber.</p>
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13 pages, 790 KiB  
Article
High Prevalence of Severe Depression in Mexican Patients Diagnosed with HIV Treated with Efavirenz and Atazanavir: Clinical Follow-Up at Four Weeks and Analysis of TPH2 SNPs
by Sandra Angélica Rojas-Osornio, Francisco Guerra-Castillo, Antonio Mata-Marín, Vladimir Paredes-Cervantes, Charmina Aguirre-Alvarado, Carolina Bekker-Méndez, Gilberto Pérez-Sánchez, José Molina-López, Mónica Ortiz-Maganda, Aurora Mercado-Méndez and Emiliano Tesoro-Cruz
J. Clin. Med. 2024, 13(24), 7823; https://doi.org/10.3390/jcm13247823 - 21 Dec 2024
Viewed by 391
Abstract
Efavirenz (EFV) causes neuropsychiatric effects such as anxiety, depression, and suicidal thoughts in people with HIV (PWH). Depressive disorders have been associated with the Tryptophan hydroxylase type 2 (TPH2) gene. Objectives: This study determines the genotypes and allelic frequencies of [...] Read more.
Efavirenz (EFV) causes neuropsychiatric effects such as anxiety, depression, and suicidal thoughts in people with HIV (PWH). Depressive disorders have been associated with the Tryptophan hydroxylase type 2 (TPH2) gene. Objectives: This study determines the genotypes and allelic frequencies of three TPH2 single nucleotide polymorphisms (SNPs) in a Mexican cohort of HIV-1 treatment-naïve-patients and the severity of depressive symptoms at baseline and after a four-week clinical follow-up of antiretroviral treatment. Methods: In a pilot prospective study, eighty-one antiretroviral treatment-naïve patients were recruited from the Infectious Disease Hospital, National Medical Center “La Raza”, in Mexico City. Of these, 39 were treated using a set-dose combination regimen of tenofovir disoproxil fumarate/emtricitabine (TDF/FTC) plus EFV and 42 were treated with TDF/FTC plus atazanavir/ritonavir (ATV/r), and fifty-nine control volunteers. Genomic DNA was obtained from peripheral blood mononuclear cells. All DNA samples underwent qPCR utilizing TaqMan probes for the three TPH2 SNPs studied. All participants underwent evaluation utilizing the Beck Depression Inventory. Results: Of the three SNPs examined, none exhibited any notable differences in the distribution of the alleles between the groups; nevertheless, rs4570625 TT and rs1386493 GG presented a twofold and fivefold greater risk of severe depression in PWH, respectively, independently of the treatment. Among PWH, those treated with EFV experienced severe depression at a higher rate of 90.4% after four weeks, compared to 87.5% in those treated with ATV/r. Conclusions: High rates of severe depression were identified in PWH, who presented the rs4570625 TT and rs1386493 GG polymorphic variants. Depression increased after four weeks of treatment and was higher with EFV than ATV/r. It is crucial to emphasize the necessity of conducting psychiatric monitoring for every patient with HIV and administering prompt antidepressant treatment. Full article
(This article belongs to the Section Mental Health)
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<p>Graphic representation of the differences in severe depression between groups. Graphic representation differences in severe depression (&gt;26 points) presented by the BDI study individuals at the beginning and 4 weeks later. An increase can be observed in both treated groups, with greater significance in patients treated with TDF/FTC + EFV (*** <span class="html-italic">p</span> &lt; 0.0001) compared to patients treated with TDF/FTC + ATV/r (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Graphic representation of the relative risk (RR) between the presence of SNPs and severe depression. Regardless of the group (control, TDF/FTC + EFV or TDF/FTC +ATV/r), the three SNPs studied showed a greater risk of severe depression: rs7305115 presented a 1.5-fold greater risk, rs4570625 polymorphic variant presented a twofold greater risk, while those with the rs1386493 polymorphic variant presented more than fivefold greater risk.</p>
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21 pages, 4283 KiB  
Article
Modeling Floral Induction in the Narrow-Leafed Lupin Lupinus angustifolius Under Different Environmental Conditions
by Maria A. Duk, Vitaly V. Gursky, Mikhail P. Bankin, Elena A. Semenova, Maria V. Gurkina, Elena V. Golubkova, Daisuke Hirata, Maria G. Samsonova and Svetlana Yu. Surkova
Plants 2024, 13(24), 3548; https://doi.org/10.3390/plants13243548 - 19 Dec 2024
Viewed by 332
Abstract
Flowering is initiated in response to environmental cues, with the photoperiod and ambient temperature being the main ones. The regulatory pathways underlying floral transition are well studied in Arabidopsis thaliana but remain largely unknown in legumes. Here, we first applied an in silico [...] Read more.
Flowering is initiated in response to environmental cues, with the photoperiod and ambient temperature being the main ones. The regulatory pathways underlying floral transition are well studied in Arabidopsis thaliana but remain largely unknown in legumes. Here, we first applied an in silico approach to infer the regulatory inputs of four FT-like genes of the narrow-leafed lupin Lupinus angustifolius. We studied the roles of FTc1, FTc2, FTa1, and FTa2 in the activation of meristem identity gene AGL8 in response to 8 h and 16 h photoperiods, vernalization, and the circadian rhythm. We developed a set of regression models of AGL8 regulation by the FT-like genes and fitted these models to the recently published gene expression data. The importance of the input from each FT-like gene or their combinations was estimated by comparing the performance of models with one or few FT-like genes turned off, thereby simulating loss-of-function mutations that were yet unavailable in L. angustifolius. Our results suggested that in the early flowering Ku line and intermediate Pal line, the FTc1 gene played a major role in floral transition; however, it acted through different mechanisms under short and long days. Turning off the regulatory input of FTc1 resulted in substantial changes in AGL8 expression associated with vernalization sensitivity and the circadian rhythm. In the wild ku line, we found that both FTc1 and FTa1 genes had an essential role under long days, which was associated with the vernalization response. These results could be applied both for setting up new experiments and for data analysis using the proposed modeling approach. Full article
(This article belongs to the Section Plant Modeling)
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<p>A general scheme of flowering initiation in <span class="html-italic">Arabidopsis thaliana</span> and a putative network in the narrow-leafed lupin <span class="html-italic">Lupinus angustifolius</span>. In <span class="html-italic">Arabidopsis</span>, the expression of the <span class="html-italic">FT</span> gene is activated in the leaves by the photoperiod and vernalization pathways. Next, the FT protein becomes expressed in the shoot apical meristem, where in complex with the transcription factor FD, it activates meristem identity genes, including <span class="html-italic">AP1</span> and <span class="html-italic">FUL</span>. Meristem identity genes, in turn, activate pathways responsible for the formation of floral organs. <span class="html-italic">L. angustifolius</span> has four <span class="html-italic">FT</span> gene orthologues, which are <span class="html-italic">FTc1</span>, <span class="html-italic">FTc2</span>, <span class="html-italic">FTa1</span>, and <span class="html-italic">FTa2</span>. The mechanisms of <span class="html-italic">FT</span>-like gene activation by environmental signals and the involvement of each <span class="html-italic">FT</span>-like gene in the regulation of meristem identity genes are still unknown (shown in the blue dotted box). <span class="html-italic">AGL8</span> is the <span class="html-italic">L. angustifolius</span> orthologue of the <span class="html-italic">Arabidopsis AP1</span> and <span class="html-italic">FUL</span> genes and a putative target of <span class="html-italic">FT</span>-like genes.</p>
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<p>Data fitting results for Models 1 and 3, which show the lowest values of the cost function. Averaged dynamics and standard deviation of the experimental data are shown in red, and the model solutions (averaged over 1000 runs) are shown in black. Green dots represent the simulation results from 10 randomly chosen runs of the minimization process. “N” and “V” stand for non-vernalized and vernalized data, respectively. “9 A.M.” and “3 P.M.” are the times of the day when the data were collected. T1–T4 stand for sampling terms [<a href="#B21-plants-13-03548" class="html-bibr">21</a>].</p>
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<p>Number (#) of free parameters (red), minimal cost function value F<sub>min</sub> (blue), and AIC value (green) for Models 1–3. The blue and green dotted lines correspond to the minimum values of the cost function and AIC, respectively.</p>
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<p>Cost function values (F) from 1000 minimization runs in <b>Model 1</b> under hypotheses H0–5 for three <span class="html-italic">L. angustifolius</span> lines. Asterisks indicate statistically significant differences in the mean F between Hi (i = 1…5) and H0 (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01). The labels 8 h and 16 h are SD and LD photoperiods, respectively.</p>
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<p>Expression dynamics in <b>Models H4, H5, and H0</b> compared to experimental data for the 8 h photoperiod. Averaged dynamics of the experimental data are shown in red, and the model solution (average of 1000 runs) is shown in blue. Green dots represent the simulation results from 10 random runs of the minimization process. Models showing specific defects in solutions compared to H0 are marked with brown frames. “N” and “V” stand for non-vernalized and vernalized data, respectively. The labels “9 A.M.” and “3 P.M.” are the times of the day when the data were collected. T1–T4 stand for sampling terms [<a href="#B21-plants-13-03548" class="html-bibr">21</a>].</p>
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<p>Expression dynamics in Models H4, H5, and H0 compared to experimental data for the 16 h photoperiod. Averaged dynamics of the experimental data are shown in red, and the model solution (average of 1000 runs) is shown in blue. Green dots represent the simulation results from 10 random runs of the minimization process. Models showing specific defects in solutions compared to H0 are marked with brown frames. “N” and “V” stand for non-vernalized and vernalized data; “7 A.M.” and “6 P.M.” are the times of data collection during LD. T1–T4 stand for sampling terms [<a href="#B21-plants-13-03548" class="html-bibr">21</a>].</p>
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<p>Cost function values (F) for 1000 minimization runs of <b>Model 1</b> and <b>Models 4–7</b> for three <span class="html-italic">L. angustifolius</span> lines. Asterisks indicate statistically significant differences in the mean F between Model i (i = 4…7) and <b>Model 1</b> (** <span class="html-italic">p</span> &lt; 0.01). The labels 8 h and 16 h are SD and LD photoperiods.</p>
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<p>The roles of <span class="html-italic">FT</span>-like genes in <span class="html-italic">AGL8</span> regulation in <span class="html-italic">L. angustifolius</span> models. The figure summarizes the regulatory effects of the exclusion of one or several <span class="html-italic">FT</span>-like genes from <span class="html-italic">AGL8</span> regulation under 8 and 16 h photoperiods. Circles of different sizes show an effect of <span class="html-italic">FT</span>-like gene exclusion on the cost function values of <b>Model 1</b> under hypotheses H1–H5. <span class="html-italic">FT</span>-like genes excluded from each model are specified in the top panel and crossed out in red. The larger the circle, the stronger the influence of regulators on <span class="html-italic">AGL8</span> expression. In models with the smallest circles, cost function values did not show statistically significant differences from model H0, where <span class="html-italic">AGL8</span> was regulated by all four <span class="html-italic">FT</span>-like genes (<span class="html-italic">FTa1</span>, <span class="html-italic">FTa2</span>, <span class="html-italic">FTc1</span>, and <span class="html-italic">FTc2</span>) (<a href="#plants-13-03548-f004" class="html-fig">Figure 4</a>). Cost function values in the models with middle and large circles had statistically significant differences from model H0. However, only models with large circles exhibited patterning defects and/or changes in regulatory parameters. The association of changes in the regulatory parameters with vernalization and circadian rhythms are indicated by different colors, according to the key at the bottom panel. The <span class="html-italic">c</span><sub>1</sub> constant presents the regulatory input of <span class="html-italic">FT</span>-like genes, while <span class="html-italic">c</span><sub>0</sub> reflects the regulation of <span class="html-italic">AGL8</span> by other factors (<a href="#app1-plants-13-03548" class="html-app">Supplementary Tables S1 and S2</a>).</p>
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<p>Experimental data on the expression dynamics of <span class="html-italic">AGL8</span>, <span class="html-italic">FTc1</span>, <span class="html-italic">FTa1</span>, <span class="html-italic">FTa2,</span> and <span class="html-italic">FTc2</span> genes over the 8 h (SD) and 16 h (LD) photoperiods [<a href="#B21-plants-13-03548" class="html-bibr">21</a>]. The data were obtained with qRT-PCR. “N” and “V” stand for non-vernalized and vernalized data; “9 A.M.” and “3 P.M.” are the times of the day when the data were collected during SD, while “7 A.M.” and “6 P.M.” are the times of data collection for LD. T1–T4 stand for sampling terms [<a href="#B21-plants-13-03548" class="html-bibr">21</a>].</p>
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25 pages, 5125 KiB  
Article
Relationship Between the Carbonation Depth and Microstructure of Concrete Under Freeze–Thaw Conditions
by Shuhua Zhang, Guangrong Tan, Zhiqiang Qi, Bin Tian, Jijun Cao and Bofu Chen
Materials 2024, 17(24), 6191; https://doi.org/10.3390/ma17246191 - 18 Dec 2024
Viewed by 484
Abstract
Concrete structures in cold regions are affected by freeze–thaw cycles (FTCs) and carbonation, which lead to the premature failure of concrete structures. The carbonation depth, relative dynamic elastic modulus (RDEM), compressive strength, porosity, and pore size distribution of concrete under FTC conditions were [...] Read more.
Concrete structures in cold regions are affected by freeze–thaw cycles (FTCs) and carbonation, which lead to the premature failure of concrete structures. The carbonation depth, relative dynamic elastic modulus (RDEM), compressive strength, porosity, and pore size distribution of concrete under FTC conditions were tested through an accelerated carbonation experiment to study the carbonation performance evolution. The freeze–thaw effect mechanism on concrete carbonation was further analyzed via the obtained relationship between carbonation depth and pore structure. The results showed that the FTC, as a powerful source of concrete damage, accelerates the carbonation reaction. Carbonization products fill some microcracks caused by the freeze–thaw process, improve the compressive strength and dynamic elastic modulus, and alleviate the damage to concrete caused by the FTC. After carbonization under freeze–thaw damage conditions, the content of macropores with d > 1000 nm decreases, while the content of transition pores with d ≤ 10 nm increases, which is the direct reason for the decrease in porosity and the improvement in strength. Therefore, the carbonation durability of concrete under freeze–thaw conditions can be improved by controlling the content of macropores with d > 1000 nm and increasing the content of transition pores with a pore size of 10 nm ≤ d < 100 nm. In addition, the relationship between carbonation depth and pore structure under freeze–thaw conditions was established, and the research results can provide a reference for the study of the carbonation performance of concrete under freeze–thaw conditions. Full article
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Figure 1

Figure 1
<p>Flow diagram of the experiment.</p>
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<p>Real-time curve display of FTC.</p>
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<p>Measurement of carbonation depth of concrete (<b>a</b>) pre-carbonization specimen, (<b>b</b>) carbonized specimen.</p>
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<p>Relationship between the number of FTCs and the depth of carbonation for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Relationship between carbonation age and the depth of carbonation for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Relationship between water–binder ratio and the depth of carbonation for (<b>a</b>) 14 days of carbonation and (<b>b</b>) 28 days of carbonation.</p>
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<p>Relationship between the number of FTCs and influence coefficient of carbonization performance for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Relationship between the number of FTCs and influence coefficient of carbonization performance for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Relationship between the number of FTCs and the RDEM for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Relationship between carbonization age and compressive strength for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>Electron microscope scanning of concrete after carbonization: (<b>a</b>) carbonization for 0 days, (<b>b</b>) carbonization for 14 days, (<b>c</b>) carbonization for 28 days.</p>
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<p>Electron microscope scanning of concrete after carbonization under freeze–thaw conditions: (<b>a</b>) carbonization for 0 days under 100 FTCs, (<b>b</b>) carbonization for 28 days under 100 FTCs, (<b>c</b>) carbonization for 0 days under 200 FTCs, (<b>d</b>) carbonization for 28 days under 200 FTCs.</p>
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<p>Porosity after carbonation under freeze–thaw conditions for (<b>a</b>) 0.35 water–binder ratio, (<b>b</b>) 0.40 water–binder ratio, (<b>c</b>) 0.45 water–binder ratio.</p>
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<p>PSD before and after carbonization under FTC conditions for (<b>a</b>) 0.35 water–binder ratio, 0 FTCs, (<b>b</b>) 0.40 water–binder ratio, 0 FTCs, (<b>c</b>) 0.40 water–binder ratio, 0 FTCs, (<b>d</b>) 0.35 water–binder ratio, 200 FTCs, (<b>e</b>) 0.40 water–binder ratio, 200 FTCs, (<b>f</b>) 0.40 water–binder ratio, 200 FTCs.</p>
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<p>PSD of specimens with different corrosion rates: (<b>a</b>) 0 FTCs, carbonization for 0 days, (<b>b</b>) 0 FTCs, carbonization for 28 days, (<b>c</b>) 200 FTCs, carbonization for 0 days, (<b>d</b>) 200 FTCs, carbonization for 28 days.</p>
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<p>Relationship between carbonation depth and (<b>a</b>) porosity, (<b>b</b>) the most probable size.</p>
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12 pages, 1036 KiB  
Article
Effectiveness and Tolerability of DOR/3TC/TDF in Experienced People with HIV Switching from RPV/FTC/TDF: A Retrospective, Single Center Cohort Study
by Stefania Cicalini, Simone Lanini, Roberta Gagliardini, Rita Bellagamba, Alessandra Vergori, Ilaria Mastrorosa, Valentina Mazzotta, Rozenn Esvan, Maria Maddalena Plazzi, Sandrine Ottou, Elisabetta Grilli, Federico De Zottis, Marisa Fusto, Jessica Paulicelli and Andrea Antinori
Pharmaceuticals 2024, 17(12), 1706; https://doi.org/10.3390/ph17121706 - 17 Dec 2024
Viewed by 596
Abstract
Background: With advances in antiretroviral therapy for HIV treatment, newer drug combinations provide improved efficacy, safety, and compliance. This study evaluates switching to a regimen of doravirine (DOR), tenofovir disoproxil fumarate (TDF), and lamivudine (3TC) in a cohort of people living with HIV [...] Read more.
Background: With advances in antiretroviral therapy for HIV treatment, newer drug combinations provide improved efficacy, safety, and compliance. This study evaluates switching to a regimen of doravirine (DOR), tenofovir disoproxil fumarate (TDF), and lamivudine (3TC) in a cohort of people living with HIV (PLWH). Methods: this Italian retrospective study included 426 PLWH who switched from rilpivirine (RPV)/TDF/emtricitabine (FTC) to DOR/3TC/TDF. The analysis focused on treatment effectiveness, safety, and metabolic and renal markers. Results: this study reports a treatment failure (defined as virological failure or discontinuation of the regimen) rate of 2.34% (95% confidence interval, 1.28–4.50%), with significant improvement in CD4 counts (+49.93 cells/µL, p < 0.001). Notably, the switch to DOR/3TC/TDF did not result in adverse metabolic effects or significant changes in renal function. Analysis of lipid profiles showed stabilization in the majority of PLWH. Conclusions: this study indicates that switching to a DOR/3TC/TDF from RPV/TDF/FTC is an effective and well-tolerated option for PLWH, with benefits in terms of maintaining viral suppression, CD4 count recovery, and metabolic health, without evidence of renal impairment. These results support the continued use of DOR/3TC/TDF as part of HIV treatment strategies and highlight the need for ongoing research to refine ART regimens for different populations. Full article
(This article belongs to the Special Issue HIV and Viral Hepatitis: Prevention, Treatment and Coinfection)
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<p>Sample selection and main outcome.</p>
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<p>Proportion of TND PLWH. Analysis was performed on a set of 461 PLWH, accounting for a total of 1693 HIV-RNA measurements. Estimates were calculated using a mixed-effects logistic regression model with a random intercept at the individual level. In red, PLWH with more than 5 years of virologic control; in blue, PLWH who achieved HIV RNA &lt; 50 copies/mL for 5 years or less. Within-group analysis: estimates for PLWH with more than 5 years of virologic control and those who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less over time. Between-group analysis: comparison between PLWH with more than 5 years of virologic control and those who achieved HIV RNA &lt; 50 copies/mL for 5 years or less at each follow-up time point.</p>
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<p>CD4 lymphocyte variation over time. The analysis was performed on a set of 461 PLWH with a total of 1693 HIV RNA measurements. Estimates were calculated using a mixed effects linear regression model with a random intercept at the individual level. In red, PLWH with more than 5 years of virologic control; in blue, PLWH who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less. Black dotted line shows pooled estimates for both groups. Within-group analysis: estimates for PLWH with more than 5 years of virologic control and those who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less over time. Between-group analysis: comparison between PLWH with more than 5 years of virologic control and those who achieved HIV RNA &lt; 50 copies/mL for 5 years or less at each follow-up endpoint.</p>
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<p>Change in CD4:CD8 ratio over time. The analysis was performed on a set of 461 PLWH with a total of 1693 HIV-RNA measurements. Estimates were calculated using a mixed effects linear regression model with a random intercept at the individual level. In red, PLWH with more than 5 years of virologic control; in blue, PLWH who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less. Within-group analysis: estimates for PLWH with more than 5 years of virologic control and those who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less over time. Between-group analysis: comparison between PLWH with more than 5 years of virologic control and those who achieved HIV-RNA &lt; 50 copies/mL for 5 years or less at each follow-up endpoint.</p>
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11 pages, 692 KiB  
Article
Prognostic Factors for Cancer-Specific Survival and Disease-Free Interval in 130 Patients with Follicular Thyroid Carcinoma: Single Institution Experience
by Matija Buzejic, Zoran Bukumiric, Branislav Rovcanin, Milan Jovanovic, Marina Stojanovic, Goran Zoric, Katarina Tausanovic, Nikola Slijepcevic and Vladan Zivaljevic
Diagnostics 2024, 14(24), 2817; https://doi.org/10.3390/diagnostics14242817 - 14 Dec 2024
Viewed by 383
Abstract
Background: Follicular thyroid carcinoma (FTC) is categorized into three groups: minimally invasive FTC (MIFTC), encapsulated angioinvasive FTC (EAIFTC), and widely invasive FTC (WIFTC). FTC is the second most common type of thyroid tumor, though it remains relatively rare in the general population. This [...] Read more.
Background: Follicular thyroid carcinoma (FTC) is categorized into three groups: minimally invasive FTC (MIFTC), encapsulated angioinvasive FTC (EAIFTC), and widely invasive FTC (WIFTC). FTC is the second most common type of thyroid tumor, though it remains relatively rare in the general population. This study aimed to examine the prognosis and prognostic factors in patients with follicular thyroid carcinoma. Methods: Data were obtained from a tertiary referral center for 130 FTC patients, covering the period from 1995 to 2020. Clinical data included demographic characteristics, tumor features, type of surgery, tumor recurrence, and vital status. Descriptive statistical methods, Kaplan–Meier survival curves, and Cox proportional hazard regression were used for statistical analysis to identify independent predictors. Results: Distant metastases occurred in 12 patients during the follow-up period. The 5-year, 10-year, 15-year, and 20-year cancer-specific survival (CSS) rates were 98.1%, 92.3%, 83.5%, and 79.8%, respectively. Independent unfavorable prognostic factors for CSS included widely invasive tumor type (hazard ratio [HR] 3.63, 95% CI 1.29–10.18), multifocality (HR 6.7, 95% CI 1.37–32.72), and presence of distant metastases (HR 2.29, 95% CI 1.08–4.84). When disease-free interval (DFI) was considered, the 5-year, 10-year, 15-year, and 20-year rates were 92.3%, 85.3%, 82.0%, and 76.6%, respectively. Independent unfavorable prognostic factors for DFI were widely invasive tumor type (HR 2.53, 95% CI 1.02–6.28) and tumor multifocality (HR 7.69, 95% CI 1.07–55.17). Conclusions: The 10-year survival rate for patients with FTC is relatively favorable. Factors associated with poorer prognosis include the presence of distant metastases, WIFTC, and multifocality. Factors linked to disease recurrence are WIFTC and multifocality. Full article
(This article belongs to the Special Issue Advances in the Diagnosis and Management of Thyroid Cancer)
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<p>Kaplan–Meier for the disease-free interval of patients with FTC.</p>
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<p>Kaplan–Meier curve for the cancer-specific survival curve of patients with FTC.</p>
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18 pages, 3905 KiB  
Article
Fault-Tolerant Control Implemented for Sustainable Active and Reactive Regulation of a Wind Energy Generation System
by Adolfo R. Lopez, Jesse Y. Rumbo-Morales, Gerardo Ortiz-Torres, Jesus E. Valdez-Resendiz, Gerardo Vazquez and Julio C. Rosas-Caro
Sustainability 2024, 16(24), 10875; https://doi.org/10.3390/su162410875 - 12 Dec 2024
Viewed by 407
Abstract
This paper presents the design of a fault-tolerant control system based on fault estimation, aimed at enhancing the sustainability and efficiency of a wind energy conversion system using a doubly-fed induction generator. The control architecture comprises a rotor-side converter (RSC) and a grid-side [...] Read more.
This paper presents the design of a fault-tolerant control system based on fault estimation, aimed at enhancing the sustainability and efficiency of a wind energy conversion system using a doubly-fed induction generator. The control architecture comprises a rotor-side converter (RSC) and a grid-side converter (GSC). The RSC is responsible for regulating both active and reactive power, and its model incorporates two linear subsystem representations. A fault-tolerant control (FTC) scheme is developed using a state-feedback controller; this controller is applied to regulate stator and rotor currents. Additionally, for comparison purposes, Proportional–Integral (PI) and Sliding-Mode Controllers (SMCs) are designed to analyze the performance of each controller. Furthermore, a proportional integral observer is employed in the proposed fault-tolerant scheme for actuator fault estimation. Fault detection is achieved by comparing the fault estimation signal with a predefined threshold. The main contribution of this work is the design and validation of a comprehensive active FTC scheme that enhances system reliability and sustainability. It also includes a performance analysis comparing three controllers (PI, SMC, and state-feedback) applied to the RSC. These controllers are evaluated for their ability to regulate active and reactive power in a wind energy conversion system under conditions of non-constant actuator faults. Full article
(This article belongs to the Special Issue Power Electronics on Recent Sustainable Energy Conversion Systems)
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<p>Stages of a wind energy conversion system.</p>
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<p>WECS based on DFIG and back-to-back converter.</p>
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<p>Vector diagram of the DFIG variables oriented to the stator flux.</p>
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<p>RSC PI control scheme.</p>
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<p>RSC sliding-mode control scheme.</p>
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<p>RSC state-feedback control scheme.</p>
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<p>FTC scheme applied to the RSC system, with (1) the RSC system, (2) the nominal controller, and (3) the active fault-tolerant control system.</p>
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<p>Simulation model of the FTC scheme with the state-feedback controller, developed in Matlab/Simulink 2023B, with (1) the RSC system, (2) the nominal controller, and (3) the active fault-tolerant control system.</p>
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<p>Scenario 1—comparison between PI, SMC and nominal state-feedback controller.</p>
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<p>Scenario 1—input signal comparison between PI, SMC and nominal state-feedback controller.</p>
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<p>Scenario 2—additive fault estimation.</p>
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<p>Scenario 2—comparison between PI, SMC and state-feedback controller with FTC.</p>
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<p>Scenario 2—input signal comparison between PI, SMC and state-feedback with FTC.</p>
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<p>Scenario 2—comparison of absolute tracking error between the SMC and the state-feedback with FTC.</p>
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14 pages, 20689 KiB  
Article
Enhancing Lithium Recovery from Slag Through Dry Forced Triboelectric Separation: A Sustainable Recycling Approach
by Mehran Javadi, Cindytami Rachmawati, Annett Wollmann, Joao Weiss, Hugo Lucas, Robert Möckel, Bernd Friedrich, Urs Peuker and Alfred P. Weber
Minerals 2024, 14(12), 1254; https://doi.org/10.3390/min14121254 - 10 Dec 2024
Viewed by 497
Abstract
The increasing use of lithium-containing materials highlights the urgent need for their recycling to preserve resources and protect the environment. Lithium-containing slags, produced during the pyrometallurgical process in lithium-ion battery recycling, represent an essential resource for lithium recovery efforts. While multiple methods for [...] Read more.
The increasing use of lithium-containing materials highlights the urgent need for their recycling to preserve resources and protect the environment. Lithium-containing slags, produced during the pyrometallurgical process in lithium-ion battery recycling, represent an essential resource for lithium recovery efforts. While multiple methods for lithium recycling exist, it is crucial to emphasize environmentally sustainable approaches. This study employs dry forced triboelectrification (FTC) to recover valuable components from slag powder, commonly known as engineered artificial minerals (EnAMs). The FTC method is used to change the charge of the target material and achieve a neutral state while other materials remain charged. The downstream electrostatic separator enables the charged particles to be separated from the target material, which in this study is lithium aluminate. The results show that the method is effective, and lithium aluminate can be successfully enriched. Full article
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<p>Schematic of (<b>a</b>) liberation by comminution (crushing and grinding), (<b>b</b>) slag components liberated to various degrees of free surface area (FSA) (partially and fully surface-liberated target phases).</p>
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<p>Experimental setup: (<b>a</b>) combination of dry forced triboelectric charging (FTC) of powders and the Faraday cup electrometer (FCE) test to determine the PZNC of the used materials and (<b>b</b>) the electrostatic separator, including five collection bins at the bottom.</p>
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<p>Slag’s transformation from (<b>a</b>) solid block to (<b>b</b>) powder form and (<b>c</b>) mineral characterization using an electron probe micro-analyzer (EPMA).</p>
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<p>(<b>a</b>) Particle size distribution of Li-Slag obtained by MLA and (<b>b</b>) X-ray diffraction (XRD) pattern of Li-Slag and single-phase components [<a href="#B8-minerals-14-01254" class="html-bibr">8</a>].</p>
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<p>Characterization of the liberation of the lithium aluminate component in the Li-Slag: (<b>a</b>) examples of particles extracted from EPMA analysis (from <a href="#minerals-14-01254-f003" class="html-fig">Figure 3</a>c, lithium aluminate in pink color) exhibiting different degrees of FSA, (<b>b</b>) lithium aluminate percentage in each liberation class by free surface area, and (<b>c</b>) particle size classes in the 90%–100% liberation class by free surface area.</p>
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<p>The specific charge of powders as a function of the applied voltage in the range of −12 to +12 kV for pure lithium aluminate, Li-Slag, and their mixture (10%/90%). From the fits of the two powders, the charging behavior of the mixture was calculated as a weighted average (black dashed line), which agrees very well with the measurements (green points).</p>
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<p>Free fall test of (<b>a</b>) Li-Slag and (<b>b</b>) lithium aluminate powders, demonstrating particle settling behavior through the separator without applied voltages (V<sub>chute</sub> = 0 kV, V<sub>sep</sub> = 0 kV).</p>
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<p>Electrostatic separation of original Li-Slag (<b>a</b>) at −3 kV (PZNC of Li-Slag) and (<b>b</b>) at −10.3 kV (PZNC of lithium aluminate). The numbers in the figure give the mass fraction of lithium slag (red) and of lithium aluminate (blue) (the sum of a mass fraction over all bins accounts for 100%).</p>
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<p>Electrostatic separation of the mixture of Li-Slag and lithium aluminate (<b>a</b>) at −3 kV (PZNC of Li-Slag) and (<b>b</b>) at −10.3 kV (PZNC of lithium aluminate). The numbers in the figure show the mass fraction of lithium slag (red) and lithium aluminate (blue).</p>
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<p>Conductivity of the mixture of Li-Slag and lithium aluminate for adding different amounts of lithium aluminate.</p>
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20 pages, 1862 KiB  
Article
Thymidine Analogue Mutations with M184V Significantly Decrease Phenotypic Susceptibility of HIV-1 Subtype C Reverse Transcriptase to Islatravir
by Hyeonah Byun, Maria Antonia Papathanasopoulos, Kim Steegen and Adriaan Erasmus Basson
Viruses 2024, 16(12), 1888; https://doi.org/10.3390/v16121888 - 6 Dec 2024
Viewed by 651
Abstract
Islatravir (ISL) is the first-in-class nucleoside reverse transcriptase translocation inhibitor (NRTtI) with novel modes of action. Data on ISL resistance are currently limited, particularly to HIV-1 non-B subtypes. This study aimed to assess prevalent nucleos(t)ide reverse transcriptase inhibitor (NRTI)-resistant mutations in HIV-1 subtype [...] Read more.
Islatravir (ISL) is the first-in-class nucleoside reverse transcriptase translocation inhibitor (NRTtI) with novel modes of action. Data on ISL resistance are currently limited, particularly to HIV-1 non-B subtypes. This study aimed to assess prevalent nucleos(t)ide reverse transcriptase inhibitor (NRTI)-resistant mutations in HIV-1 subtype C for their phenotypic resistance to ISL. Prevalent single and combinations of NRTI-resistant mutations were selected from a routine HIV-1 genotypic drug resistance testing database and introduced into HIV-1 subtype C-like pseudoviruses, which were then tested for ISL susceptibility. Single NRTI-resistant mutations were susceptible or showed only a low level of resistance to ISL. This included thymidine analogue mutations (TAMs, i.e., M41L, D67N, K70R, T215FY, and K219EQ) and non-TAMs (i.e., A62V, K65R, K70ET, L74IV, A114S, Y115F, and M184V). Combinations of M184V with one or more additional NRTI-resistant mutations generally displayed reduced ISL susceptibilities. This was more prominent for combinations that included M184V+TAMs, and particularly M184V+TAM-2 mutations. Combinations that included M184V+K65R did not impact significantly on ISL susceptibility. Our study suggests that ISL would be effective in treating people living with HIV (PLWH) failing tenofovir disoproxil fumarate (TDF)/lamivudine (3TC) or TDF/emtricitabine (FTC)-containing regimens, but would be less effective in PLH failing zidovudine (AZT) with 3TC or FTC-containing regimens. Full article
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<p>Variation in IC<sub>50</sub> and fold-change of ISL against wild-type PSV. (<b>A</b>) Multiple independent in vitro assays (<span class="html-italic">n</span> = 41) were conducted to determine the IC<sub>50</sub> of ISL against the wild-type HIV-1 subtype C virus (i.e., p8.9MJ4). The mean IC<sub>50</sub> = 8.32 nM ± 4.99 nM (median IC<sub>50</sub> = 7.27 nM, IQR 4.16–12.88). (<b>B</b>) Each IC<sub>50</sub> value was divided by the mean IC<sub>50</sub> value to determine the fold-change (FC). The mean FC was, therefore, 1.0 ± 0.6 FC (median FC = 0.87, IQR 0.54–1.55). Technical cut-off (TCO): obtained from the 99th percentile of the IC<sub>50</sub> values. (<b>C</b>) Multiple independent in vitro assays (<span class="html-italic">n</span> = 13) were conducted to determine the IC<sub>50</sub> value of ISL against the wild-type HIV-1 subtype B virus (i.e., p8.9NSX). The mean IC<sub>50</sub> concentration was shown to be 7.91 nM ± 5.51 nM (median IC<sub>50</sub> = 5.90 nM, IQR 2.58–13.32). (<b>D</b>) Each IC<sub>50</sub> value was divided by the mean IC<sub>50</sub> value to obtain a mean FC value of 1 (median FC = 0.74, IQR 0.33–1.68).</p>
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<p>Fold-change in IC<sub>50</sub> of single mutants in subtype C PSVs compared to the wild-type PSV. Following the in vitro phenotypic activity assays, the IC<sub>50</sub> values for each mutant was compared against the mean IC<sub>50</sub> of the MJ4 wild-type PSV, allowing the determination of fold changes. The 99th percentile of variation in the wild-type IC<sub>50</sub> value, calculated to be 2.2 (TCO), served as the threshold for categorizing mutants as either susceptible or having a decreased susceptibility to ISL. Among the single mutants, M41L, K65R, D67N, K70E/R/T, L74I, A114S, Y115F, T215F, and K219E/Q demonstrated susceptibility to ISL. In contrast, A62V, L74V, and T215Y exhibited potential low-level resistance, and M184V exhibited potential-low- to low-level resistance. Susceptible (<span class="html-italic">n</span>), potential-low-level resistance (<span class="html-italic">n</span>), low-level resistance (<span class="html-italic">n</span>), intermediate resistance (<span class="html-italic">n</span>), and high-level resistance (<span class="html-italic">n</span>). Data are shown as median bar graphs with the IQR as error bars.</p>
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<p>Single mutant L74V in wild-type HIV-1 subtype B and C laboratory-adapted strains. A phenotypic activity assay was conducted to determine whether ISL had similar potencies against the single mutant L74V in different wild-type strains and subtypes of HIV-1. IC<sub>50</sub> values are expressed as median fold-change differences to the IC<sub>50</sub> of the relevant control subtype, with the IQR as error bars. The TCO for each subtype is indicated on the graph by a dotted line.</p>
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<p>IC<sub>50</sub> values of L74V in laboratory-adapted PSVs and inter-subtype Kruskal–Wallis test. Site-directed mutagenesis was performed to introduce the L74V mutant into the wild-type p8.9NSX and p8.9MJ4, and laboratory-adapted strains. (<b>A</b>) Median IC<sub>50</sub> values of the L74V mutation in laboratory-adapted strains show that the LTNP5 PSV has the highest median IC<sub>50</sub> of 9.76 nM (IQR 6.27–9.98). DS9 had the lowest median IC<sub>50</sub> of 2.31 nM (IQR 1.78–4.20). Data are shown as median bar graphs with the IQR. (<b>B</b>) Inter-subtype non-parametric statistical analysis was performed using a Kruskal–Wallis multiple comparisons test. The grid shows the <span class="html-italic">p</span>-values of the comparisons in IC<sub>50</sub> values. No significant differences (<span class="html-italic">p</span> &gt; 0.05) were observed.</p>
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<p>Fold-change in IC<sub>50</sub> of mutation combinations in subtype C PSVs compared to the wild-type MJ4 PSV. Following the in vitro phenotypic activity assays, the IC<sub>50</sub> value for each mutant was compared against the mean IC<sub>50</sub> of the MJ4 wild-type PSV, allowing for the determination of fold changes. The 99th percentile of variation in the wild-type IC<sub>50</sub> value, calculated to be 2.2 (TCO), served as the threshold for categorizing mutants as either susceptible or resistant to ISL. It was observed that the combination of NRTI mutations generally increased resistance to ISL. The A114S/M184V mutation combination showed a very high level of resistance to ISL. Its IC<sub>50</sub> value was greater than the highest ISL concentration tested, and consequently, its FC value was &gt; 60. Susceptible (<span class="html-italic">n</span>), potential-low-level resistance (<span class="html-italic">n</span>), low-level resistance (<span class="html-italic">n</span>), intermediate resistance (<span class="html-italic">n</span>), and high-level resistance (<span class="html-italic">n</span>). Data are shown as median bar graphs with the IQR as error bars.</p>
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12 pages, 549 KiB  
Article
Generalized Dimensions of Self-Affine Sets with Overlaps
by Guanzhong Ma, Jun Luo and Xiao Zhou
Fractal Fract. 2024, 8(12), 722; https://doi.org/10.3390/fractalfract8120722 - 6 Dec 2024
Viewed by 480
Abstract
Two decades ago, Ngai and Wang introduced a well-known finite type condition (FTC) on the self-similar iterated function system (IFS) with overlaps and used it to calculate the Hausdorff dimension of self-similar sets. In this paper, inspired by Ngai and Wang’s idea, we [...] Read more.
Two decades ago, Ngai and Wang introduced a well-known finite type condition (FTC) on the self-similar iterated function system (IFS) with overlaps and used it to calculate the Hausdorff dimension of self-similar sets. In this paper, inspired by Ngai and Wang’s idea, we define a new FTC on self-affine IFS and obtain an analogous formula on the generalized dimensions of self-affine sets. The generalized dimensions raised by He and Lau are used to estimate the Hausdorff dimension of self-affine sets. Full article
(This article belongs to the Special Issue Fractal Dimensions with Applications in the Real World)
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<p>The iterates of <span class="html-italic">U</span> under <math display="inline"><semantics> <mrow> <mo stretchy="false">{</mo> <msub> <mi>S</mi> <mn>1</mn> </msub> <mo>,</mo> <msub> <mi>S</mi> <mn>2</mn> </msub> <mo>,</mo> <msub> <mi>S</mi> <mn>3</mn> </msub> <mo stretchy="false">}</mo> </mrow> </semantics></math>.</p>
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<p>The iterates of <span class="html-italic">U</span> under <math display="inline"><semantics> <msub> <mi>S</mi> <mi>I</mi> </msub> </semantics></math>’s.</p>
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18 pages, 520 KiB  
Article
Adaptive Fault-Tolerant Tracking Control for Continuous-Time Interval Type-2 Fuzzy Systems
by Ming-Yang Qiao and Xiao-Heng Chang
Mathematics 2024, 12(23), 3682; https://doi.org/10.3390/math12233682 - 24 Nov 2024
Viewed by 465
Abstract
This paper investigated the tracking problem of mixed H and L2L adaptive fault-tolerant control (FTC) for continuous-time interval type-2 fuzzy systems (IT2FSs). For the membership function mismatch and uncertainty between the modules of the nonlinear system, the IT2 [...] Read more.
This paper investigated the tracking problem of mixed H and L2L adaptive fault-tolerant control (FTC) for continuous-time interval type-2 fuzzy systems (IT2FSs). For the membership function mismatch and uncertainty between the modules of the nonlinear system, the IT2 fuzzy model is applied to linearly approximate it. The observer can sensitively estimate the system state, and the adaptive fault estimation functions can estimate adaptively the fault signals, which enables the designed adaptive FTC scheme to ensure the asymptotic stability of the closed-loop control system and achieve the desired mixed H and L2L tracking performance. The designed adaptive control law can achieve the purpose of dynamic compensation for faults and disturbances, and the introduced lemmas further reduce the design conservatism by adjusting the slack parameters and matrices. Finally, a mass-spring-damping system is used to illustrate the effectiveness of the designed method. Full article
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<p>Framework of closed-loop adaptive FTC system.</p>
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<p>System states <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math> and observer states <math display="inline"><semantics> <mrow> <mover accent="true"> <mi>x</mi> <mo stretchy="false">^</mo> </mover> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>System output with faults <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>f</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> and reference output <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>r</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>System tracking error <math display="inline"><semantics> <mrow> <msub> <mi>e</mi> <mi>y</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>Adaptive control signal <math display="inline"><semantics> <mrow> <mi>u</mi> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
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<p>The trajectory of <math display="inline"><semantics> <mrow> <msub> <mi>L</mi> <mn>2</mn> </msub> <mo>−</mo> <msub> <mi>L</mi> <mo>∞</mo> </msub> </mrow> </semantics></math> performance.</p>
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<p>The trajectory of <math display="inline"><semantics> <msub> <mi mathvariant="script">H</mi> <mo>∞</mo> </msub> </semantics></math> performance.</p>
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<p>System output with faults <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>f</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> and reference output <math display="inline"><semantics> <mrow> <msub> <mi>y</mi> <mi>r</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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22 pages, 8038 KiB  
Article
Fault-Tolerant Control for Quadcopters Under Actuator and Sensor Faults
by Kenji Fabiano Ávila Okada, Aniel Silva Morais, Laura Ribeiro, Caio Meira Amaral da Luz, Fernando Lessa Tofoli, Gabriela Vieira Lima and Luís Cláudio Oliveira Lopes
Sensors 2024, 24(22), 7299; https://doi.org/10.3390/s24227299 - 15 Nov 2024
Viewed by 788
Abstract
Fault detection and diagnosis (FDD) methods and fault-tolerant control (FTC) have been the focus of intensive research across various fields to ensure safe operation, reduce costs, and optimize maintenance tasks. Unmanned aerial vehicles (UAVs), particularly quadcopters or quadrotors, are often prone to faults [...] Read more.
Fault detection and diagnosis (FDD) methods and fault-tolerant control (FTC) have been the focus of intensive research across various fields to ensure safe operation, reduce costs, and optimize maintenance tasks. Unmanned aerial vehicles (UAVs), particularly quadcopters or quadrotors, are often prone to faults in sensors and actuators due to their complex dynamics and exposure to various external uncertainties. In this context, this work implements different FDD approaches based on the Kalman filter (KF) for fault estimation to achieve FTC of the quadcopter, considering different faults with nonlinear behaviors and the possibility of simultaneous occurrences in actuators and sensors. Three KF approaches are considered in the analysis: linear KF, extended KF (EKF), and unscented KF (UKF), along with three-stage and adaptive variations of the KF. FDD methods, especially the adaptive filter, could enhance fault estimation performance in the scenarios considered. This led to a significant improvement in the safety and reliability of the quadcopter through the FTC architecture, as the system, which previously became unstable in the presence of faults, could maintain stable operation when subjected to uncertainties. Full article
(This article belongs to the Section Fault Diagnosis & Sensors)
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<p>Quadcopter structure and variables.</p>
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<p>Initial configuration of the quadcopter’s control system.</p>
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<p>FDD and FTC systems implemented for the quadcopter.</p>
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<p>Innovation of the fault sub-filter using ATsUKF.</p>
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<p>Estimation of sensor faults using ATsUKF.</p>
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<p>Estimation of actuator faults using ATsUKF.</p>
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<p>Displacement of the quadcopter subjected to actuator and sensor faults.</p>
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<p>Control signals generated in systems with (<b>a</b>) and without (<b>b</b>) FTC.</p>
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<p>Quadcopter displacement in the <span class="html-italic">xy</span> plane.</p>
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<p>Behavior of systems in the presence of lock-up sensor faults.</p>
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<p>Estimation of sensor lock-up faults.</p>
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<p>Behavior of systems in the presence of wind-generated disturbances.</p>
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<p>Fault estimations in (<b>a</b>) sensors and (<b>b</b>) actuators.</p>
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26 pages, 11387 KiB  
Article
Fixed-Time Control with an Improved Sparrow Search Algorithm for Robotic Arm Performance Optimization
by Ruochen Zhang, Hyeung-Sik Choi, Dongwook Jung, Hyunjoon Cho, Phan Huy Nam Anh and Mai The Vu
Appl. Sci. 2024, 14(22), 10096; https://doi.org/10.3390/app142210096 - 5 Nov 2024
Viewed by 601
Abstract
This paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov function (BLF) and adaptive [...] Read more.
This paper presents an innovative approach that integrates a fixed-time control (FTC) algorithm with an improved sparrow search algorithm (ISSA) to enhance the trajectory tracking accuracy of a two-degree-of-freedom (two-DOF) robotic arm. The FTC algorithm, which incorporates barrier Lyapunov function (BLF) and adaptive neural network strategies, ensures rapid convergence, effective vibration suppression, and the robust handling of system uncertainties and input saturation. The ISSA, inspired by the foraging behavior of sparrows, improves search efficiency through dynamic weight adjustments and chaotic mapping, balancing global and local search capabilities. By optimizing control parameters, ISSA minimizes tracking errors. Simulation results demonstrate that the combined FTC and ISSA approach significantly reduces tracking errors and improves response speed compared to the use of FTC alone, underscoring its potential for achieving high-precision control in robotic arms and offering a promising direction for precise robotic control applications. Full article
(This article belongs to the Section Robotics and Automation)
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<p>A sketch of a n-degree-of-freedom (n-DOF) robotic arm.</p>
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<p>The workflow of ISSA.</p>
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<p>Iteration curves for functions F1 to F8. (<b>a</b>) Iteration curve for F1. (<b>b</b>) Iteration curve for F2. (<b>c</b>) Iteration curve for F3. (<b>d</b>) Iteration curve for F4. (<b>e</b>) Iteration curve for F5. (<b>f</b>) Iteration curve for F6. (<b>g</b>) Iteration curve for F7. (<b>h</b>) Iteration curve for F8.</p>
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<p>The simulation of the trajectory tracking without the ISSA. (<b>a</b>) The simulation results of the first link. (<b>b</b>) The simulation results of the second link.</p>
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<p>The simulation of the trajectory tracking error without the ISSA. (<b>a</b>) The simulation results of the first link. (<b>b</b>) The simulation results of the second link.</p>
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<p>Control torques: (<b>a</b>) the simulation results of the first link; (<b>b</b>) the simulation results of the second link.</p>
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<p>The simulation of trajectory tracking with the ISSA. (<b>a</b>) The simulation results of the first link. (<b>b</b>) The simulation results of the second link.</p>
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<p>The simulation of trajectory tracking errors with the ISSA. (<b>a</b>) The simulation results of the first link. (<b>b</b>) The simulation results of the second link.</p>
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<p>The simulation of PD control: (<b>a</b>) the simulation results of the first link; (<b>b</b>) the simulation results of the second link.</p>
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<p>The simulation of fixed-time control with ISSA: (<b>a</b>) the simulation results of the first link; (<b>b</b>) the simulation results of the second link.</p>
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<p>A comparison of errors between ISSA combined with fixed-time control and PD control under external disturbances. (<b>a</b>) The simulation results of the first link. (<b>b</b>) The simulation results of the second link.</p>
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15 pages, 1744 KiB  
Article
SIMS and Numerical Analysis of Asymmetrical Out-Diffusion of Hydrogen and Carbon in CdxZn1−xO:Eu Multilayer
by Zeinab Khosravizadeh, Anastasiia Lysak, Ewa Przeździecka and Rafał Jakieła
Materials 2024, 17(21), 5240; https://doi.org/10.3390/ma17215240 - 28 Oct 2024
Viewed by 649
Abstract
This study employs secondary ion mass spectrometry (SIMS) to investigate the diffusion behavior of hydrogen and carbon in a CdxZn1−xO:Eu multilayer at different annealing temperatures (500–900 °C). The SIMS results reveal a significant out-diffusion of these elements toward [...] Read more.
This study employs secondary ion mass spectrometry (SIMS) to investigate the diffusion behavior of hydrogen and carbon in a CdxZn1−xO:Eu multilayer at different annealing temperatures (500–900 °C). The SIMS results reveal a significant out-diffusion of these elements toward the surface and diffusion to the interface region. The diffusion flow rates are asymmetric and favor the interface direction. The depth profiles of diffused elements are fitted using the forward timecentered space (FTCS) iteration method. The activation energies are determined to be 0.35 ± 0.06 eV for hydrogen and 0.33 ± 0.09 eV for carbon, suggesting an interstitial mechanism in CdxZn1−xO. The results indicate that increasing the annealing temperatures leads to a significant decrease in impurity concentrations. Full article
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<p>SIMS depth profiles of elements in the as-grown sample with high Eu content. Depth profiles for (<b>a</b>) hydrogen (H) and carbon (C) (left axis) and silicon (Si) and <math display="inline"><semantics> <mrow> <msub> <mi>Zn</mi> <mn>2</mn> </msub> <msub> <mi mathvariant="normal">O</mi> <mn>2</mn> </msub> </mrow> </semantics></math> (right axis), and (<b>b</b>) cadmium (Cd) and europium (Eu) (left axis) and oxygen (O), silicon (Si), and zinc (Zn) (right axis). The concentration of Eu and Cd remained constant before and after annealing. The observed increase in the Cd signal at the surface is attributed to the CdO cap.</p>
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<p>Hydrogen concentration profiles versus depth in <math display="inline"><semantics> <mrow> <msub> <mi>Cd</mi> <mi>x</mi> </msub> <msub> <mi>Zn</mi> <mrow> <mn>1</mn> <mo>−</mo> <mi>x</mi> </mrow> </msub> <mi mathvariant="normal">O</mi> </mrow> </semantics></math>:Eu (Cd content <math display="inline"><semantics> <mrow> <mo>&lt;</mo> <mn>0.25</mn> <mo>%</mo> </mrow> </semantics></math>) under various annealing conditions. The profiles are shown for the as-grown sample (grey solid line), and after annealing at 500 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 20 min (green solid line), 700 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 5 min (red solid line), and 900 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 5 min (blue solid line). The dashed black lines represent the diffusion profiles estimated using the iteration method. Numbers (<b>1</b>)–(<b>4</b>) correspond to different samples, as listed in <a href="#materials-17-05240-t001" class="html-table">Table 1</a>, where the Eu content increases progressively from sample 1 to sample 4.</p>
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<p>Carbon concentration profiles versus depth in <math display="inline"><semantics> <mrow> <msub> <mi>Cd</mi> <mi>x</mi> </msub> <msub> <mi>Zn</mi> <mrow> <mn>1</mn> <mo>−</mo> <mi>x</mi> </mrow> </msub> <mi mathvariant="normal">O</mi> </mrow> </semantics></math>:Eu (Cd content <math display="inline"><semantics> <mrow> <mo>&lt;</mo> <mn>0.25</mn> <mo>%</mo> </mrow> </semantics></math>) under various annealing conditions. The profiles are shown for the as-grown sample (grey solid line), and after annealing at 500 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 20 min (green solid line), 700 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 5 min (red solid line), and 900 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C for 5 min (blue solid line). The dashed black lines represent the diffusion profiles estimated using the iteration method. Numbers (<b>1</b>)–(<b>4</b>) correspond to different samples, as listed in <a href="#materials-17-05240-t001" class="html-table">Table 1</a>, where the Eu content increases progressively from sample 1 to sample 4.</p>
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<p>The SIMS depth profile of the reference’s signals of <math display="inline"><semantics> <mrow> <msub> <mi>Zn</mi> <mn>2</mn> </msub> <msub> <mi mathvariant="normal">O</mi> <mn>2</mn> </msub> </mrow> </semantics></math> and silicon (Si). The profile labeled “ag” denotes the as-grown sample. The data reveal a sharp interface between ZnO and Si in the as-grown sample and at 500 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C. At higher annealing temperatures of 700 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C and 900 <math display="inline"><semantics> <mo>°</mo> </semantics></math>C, Si is observed to penetrate deeper into the ZnO layer, indicating the formation of a <math display="inline"><semantics> <mrow> <mi>Si</mi> <msub> <mi mathvariant="normal">O</mi> <mn>2</mn> </msub> </mrow> </semantics></math> layer and changes in diffusion behavior.</p>
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<p>Cross-sectional SEM image of the <math display="inline"><semantics> <mrow> <msub> <mi>Cd</mi> <mi>x</mi> </msub> <msub> <mi>Zn</mi> <mrow> <mn>1</mn> <mo>−</mo> <mi>x</mi> </mrow> </msub> <mi mathvariant="normal">O</mi> </mrow> </semantics></math>:Eu.</p>
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<p>EDX elemental mapping of silicon (Si K-<math display="inline"><semantics> <mi>α</mi> </semantics></math> line) (<b>a</b>) and oxygen (O K-<math display="inline"><semantics> <mi>α</mi> </semantics></math> line) (<b>b</b>) from the cross-section of the <math display="inline"><semantics> <mrow> <msub> <mi>Cd</mi> <mi>x</mi> </msub> <msub> <mi>Zn</mi> <mrow> <mn>1</mn> <mo>−</mo> <mi>x</mi> </mrow> </msub> <mi mathvariant="normal">O</mi> </mrow> </semantics></math>:Eu multilayer film. The maps confirm the formation of the <math display="inline"><semantics> <msub> <mi>SiO</mi> <mn>2</mn> </msub> </semantics></math> layer.</p>
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<p>Arrhenius plot of the hydrogen diffusion coefficient (<span class="html-italic">D</span>) vs. reciprocal temperature (1000/T). The blue circles represent the experimental data points for different temperatures, while the red dashed line indicates the Arrhenius fitting curve obtained using Origin software. The spread of data points reflects variations in Eu concentration across different samples at varying temperatures. Some points may overlap due to similar diffusion values.</p>
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<p>Arrhenius plot of the carbon diffusion coefficient (<span class="html-italic">D</span>) vs. reciprocal temperature (1000/T). The green circles represent the experimental data points for different temperatures, while the red dashed line indicates the Arrhenius fitting curve obtained using Origin software. The spread of data points reflects variations in Eu concentration across different samples at varying temperatures. Some points may overlap due to similar diffusion values.</p>
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