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17 pages, 26738 KiB  
Article
Fatigue Crack Growth Performance of Q370qENH Weathering Bridge Steel and Butt Welds
by Yujie Yu, Xiang Zhang, Chunjian Hu, Liangkun Liu and Haibo Wang
Materials 2024, 17(23), 6015; https://doi.org/10.3390/ma17236015 - 9 Dec 2024
Viewed by 421
Abstract
Weathering steel possesses good atmospheric corrosion resistance and is increasingly applied in highway and railway bridges. The fatigue performance of the weld joint is an important issue in bridge engineering. This study experimentally investigates the microstructural properties and fracture crack growth behaviors of [...] Read more.
Weathering steel possesses good atmospheric corrosion resistance and is increasingly applied in highway and railway bridges. The fatigue performance of the weld joint is an important issue in bridge engineering. This study experimentally investigates the microstructural properties and fracture crack growth behaviors of a Q370qENH bridge weathering steel weld joint. The FCG parameters of the base steel, butt weld, and HAZs, considering the effect of different plate thicknesses and stress ratios, are analyzed. Microstructural features, microhardness, and fatigue fracture surfaces are carefully inspected. The FCG rates of different weld regions in the stable crack growth stage are obtained using integral formulas based on the Paris and Walker law. The test results indicate that the heating and cooling process during the welding of Q370qENH steel creates improved microstructures with refined grain sizes and fewer impurities, thus leading to improved FCG performances in the HAZ and weld regions. The crack growth rate of Q370qENH weld regions increases with the stress ratio, and the influencing extent increasingly ranks as the base steel, HAZ, and the weld. The thick plate has a slightly slower fatigue crack growth rate for the Q370qENH weld joints. The Q370qENH base steel presents the highest fatigue crack growth rate, followed by the heat-treated and HAZ cases, while the weld area exhibits the lowest FCG rate. The Paris law coefficients of different regions of Q370qENH welds are presented. The collected data serve as a valuable reference for future analyses of fatigue crack propagation problems of Q370qENH steel bridge joints. Full article
(This article belongs to the Special Issue Engineering Materials and Structural Integrity)
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Figure 1

Figure 1
<p>Design geometry and the practical product of butt welds.</p>
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<p>The optical microscope scan specimen and the construction.</p>
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<p>Metallographic structure: (<b>a</b>) weld joint region × 50 (Red spots indicate hardness measuring locations); (<b>b</b>) weld × 500; (<b>c</b>) CGHAZ × 500; (<b>d</b>) FGHAZ × 500; (<b>e</b>) base metal × 500.</p>
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<p>Metallographic structure: (<b>a</b>) HV-1000Z Vickers indenter; (<b>b</b>) microhardness results; (<b>c</b>) Vickers indenter imprint.</p>
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<p>CT specimen design: (<b>a</b>) specimen dimensions; (<b>b</b>) specimen figure; (<b>c</b>) specimen locations.</p>
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<p>Fatigue crack growth test setup: (<b>a</b>) test setup; (<b>b</b>) specimen setup; (<b>c</b>) DIC measurement.</p>
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<p>Fatigue crack growth curves: (<b>a</b>) crack propagation trajectory; (<b>b</b>) crack lengths of base metal; (<b>c</b>) crack lengths of HAZ; (<b>d</b>) crack lengths of weld.</p>
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<p>Comparison of FCG rates under different stress ratios: (<b>a</b>) base metal—8 mm thick; (<b>b</b>) base metal—10 mm thick; (<b>c</b>) weld—8 mm thick; (<b>d</b>) HAZ—8 mm thick.</p>
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<p>Comparison of FCG rates under different plate thicknesses: (<b>a</b>) base steel cases; (<b>b</b>) HAZ cases; (<b>c</b>) weld cases.</p>
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<p>Comparison of FCG rates under different stress ratios: (<b>a</b>) 0.1 stress ratio; (<b>b</b>) 0.2 stress ratio; (<b>c</b>) 0.5 stress ratio.</p>
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<p>Comparison of FCG rates between different CT groups: (<b>a</b>) CT specimens from weld joint; (<b>b</b>) CT specimens from heated plates.</p>
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<p>FCG performance comparisons between Q370qENH, 14MNNbq, and Q500D.</p>
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<p>Fracture morphology of 8H0.2-2.</p>
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<p>Fracture surface and microscope morphology of critical regions: (<b>a</b>) weld—8W0.1; (<b>b</b>) HAZ—8H0.1; (<b>c</b>) base steel—8B0.1.</p>
Full article ">Figure 14 Cont.
<p>Fracture surface and microscope morphology of critical regions: (<b>a</b>) weld—8W0.1; (<b>b</b>) HAZ—8H0.1; (<b>c</b>) base steel—8B0.1.</p>
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<p>Fracture surface and microscope morphology of critical regions.</p>
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<p>Fracture surface of 6 mm and 8 mm thick 0.1 stress ratio cases.</p>
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13 pages, 537 KiB  
Article
Effect of Nd:YAG Laser Irradiation on the Growth of Oral Biofilm
by Zuzanna Grzech-Leśniak, Jagoda Szwach, Martyna Lelonkiewicz, Krzysztof Migas, Jakub Pyrkosz, Maciej Szwajkowski, Patrycja Kosidło, Magdalena Pajączkowska, Rafał Wiench, Jacek Matys, Joanna Nowicka and Kinga Grzech-Leśniak
Microorganisms 2024, 12(11), 2231; https://doi.org/10.3390/microorganisms12112231 - 4 Nov 2024
Viewed by 853
Abstract
Background: Oral microbiota comprises a wide variety of microorganisms. The purpose of this study was to evaluate the effects of Nd:YAG laser with a 1064 nm wavelength on the in vitro growth of Candida albicans, Candida glabrata, and Streptococcus mutans clinical [...] Read more.
Background: Oral microbiota comprises a wide variety of microorganisms. The purpose of this study was to evaluate the effects of Nd:YAG laser with a 1064 nm wavelength on the in vitro growth of Candida albicans, Candida glabrata, and Streptococcus mutans clinical strains, as well as their biofilm. The study also aimed to determine whether the parameters recommended for photobiomodulation (PBM) therapy, typically used for tissue wound healing, have any additional antibacterial or antifungal effects. Material and Methods: Single- and dual-species planktonic cell solution and biofilm cultures of Streptococcus mutans, Candida albicans, and Candida glabrata were irradiated using an Nd:YAG laser (LightWalker; Fotona; Slovenia) with a flat-top Genova handpiece. Two test groups were evaluated: Group 1 (G-T1) exposed to low power associated parameters (irradiance 0.5 W/cm2) and Group 2 (G-T2) with higher laser parameters (irradiance 1.75 W/cm2). Group 3 (control) was not exposed to any irradiation. The lasers’ effect was assessed both immediately after irradiation (DLI; Direct Laser Irradiation) and 24 h post-irradiation (24hLI) of the planktonic suspension using a quantitative method (colony-forming units per 1 mL of suspension; CFU/mL), and the results were compared with the control group, in which no laser was applied. The impact of laser irradiation on biofilm biomass was assessed immediately after laser irradiation using the crystal violet method. Results: Nd:YAG laser irradiation with photobiomodulation setting demonstrated an antimicrobial effect with the greatest immediate reduction observed in S. mutans, achieving up to 85.4% reduction at the T2 settings. However, the laser’s effectiveness diminished after 24 h. In single biofilm cultures, the highest reductions were noted for C. albicans and S. mutans at the T2 settings, with C. albicans achieving a 92.6 ± 3.3% reduction and S. mutans reaching a 94.3 ± 5.0% reduction. Overall, the T2 settings resulted in greater microbial reductions compared to T1, particularly in biofilm cultures, although the effectiveness varied depending on the microorganism and culture type. Laser irradiation, assessed immediately after using the crystal violet method, showed the strongest biofilm reduction for Streptococcus mutans in the T2 settings for both single-species and dual-species biofilms, with higher reductions observed in all the microbial samples at the T2 laser parameters (p < 0.05) Conclusion: The Nd:YAG laser using standard parameters typically applied for wound healing and analgesic effects significantly reduced the number of Candida albicans; Candida glabrata; and Streptococcus mutans strains. Full article
(This article belongs to the Special Issue Oral Biofilms and Human Health)
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<p>Diagram of methodology of laser irradiation of planktonic solutions of cells and biofilm.</p>
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16 pages, 8740 KiB  
Article
Crack Growth Analytical Model Considering the Crack Growth Resistance Parameter Due to the Unloading Process
by Guo Li, Shuchun Huang, Zhenlei Li, Wanqiu Lu, Shuiting Ding, Rong Chen and Fan Cao
Aerospace 2024, 11(10), 841; https://doi.org/10.3390/aerospace11100841 - 12 Oct 2024
Viewed by 707
Abstract
Crack growth analysis is essential for probabilistic damage tolerance assessment of aeroengine life-limited parts. Traditional crack growth models directly establish the stress ratio–crack growth rate or crack opening stress relationship and focus less on changes in the crack tip stress field and its [...] Read more.
Crack growth analysis is essential for probabilistic damage tolerance assessment of aeroengine life-limited parts. Traditional crack growth models directly establish the stress ratio–crack growth rate or crack opening stress relationship and focus less on changes in the crack tip stress field and its influence, so the resolution and accuracy of maneuvering flight load spectral analysis are limited. To improve the accuracy and convenience of analysis, a parameter considering the effect of unloading amount on crack propagation resistance is proposed, and the corresponding analytical model is established. The corresponding process for acquiring the model parameters through the constant amplitude test data of a Ti-6AL-4V compact tension specimen is presented. Six kinds of flight load spectra with inserted load pairs with different stress ratios and repetition times are tested to verify the accuracy of the proposed model. All the deviations between the proposed model and test life results are less than 10%, which demonstrates the superiority of the proposed model over the crack closure and Walker-based models in addressing relevant loading spectra. The proposed analytical model provides new insights for the safety of aeroengine life-limited parts. Full article
(This article belongs to the Section Aeronautics)
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<p>Relationship between the present research and the previous research.</p>
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<p>The CT specimen and the corresponding finite element model. (<b>a</b>) Schematic of the size and shape of the CT specimen. (<b>b</b>) Finite element model.</p>
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<p>Stress distribution along the crack growth path. (<b>a</b>) Stress distribution at different moments. (<b>b</b>) Stress variation with respect to the maximum load.</p>
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<p>Schematic of the UCR model. (<b>a</b>) Schematic of the UCR model under constant loading. (<b>b</b>) Schematic of the UCR model under variable loading.</p>
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<p>“Unloading-reloading” segment.</p>
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<p>Stress contour and displacement at the crack tip at different moments.</p>
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<p>Test equipment. (<b>a</b>) Servo-hydraulic test machine and the DIC device. (<b>b</b>) COD gauge.</p>
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<p>Crack growth test results and data processing.</p>
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<p>Acquisition of the effective stress intensity factor curve.</p>
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<p>Schematic of the block loading.</p>
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<p>Acquisition of the control group data.</p>
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<p>Different combined load spectra and corresponding crack propagation results. (<b>a</b>) Load spectra (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>b</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>c</b>) Load spectra (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </semantics></math>). (<b>d</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>e</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>f</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>g</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>h</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>i</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>j</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>k</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>l</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 12 Cont.
<p>Different combined load spectra and corresponding crack propagation results. (<b>a</b>) Load spectra (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>b</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>c</b>) Load spectra (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </semantics></math>). (<b>d</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.3</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>e</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>f</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>g</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>h</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.6</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>i</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>j</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>11</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>. (<b>k</b>) Load spectra <math display="inline"><semantics> <mrow> <mfenced> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> </mrow> </mfenced> </mrow> </semantics></math>. (<b>l</b>) Crack growth results (<math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>0.8</mn> <mo>,</mo> <mo> </mo> <msub> <mi>N</mi> <mrow> <mi>insert</mi> </mrow> </msub> <mo>=</mo> <mn>22</mn> <mo stretchy="false">)</mo> </mrow> </semantics></math>.</p>
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<p>Summary of the predicted life results.</p>
Full article ">
11 pages, 2146 KiB  
Article
Infrared Thermography Sensor in the Analysis of Acute Metabolic Stress Response during Race Walking Competition
by Alessio Cabizosu, Cristian Marín-Pagan, Pedro E. Alcaraz and Francisco Javier Martínez-Noguera
Biosensors 2024, 14(10), 478; https://doi.org/10.3390/bios14100478 - 5 Oct 2024
Viewed by 814
Abstract
Introduction: Due to the possible impact of the thermoregulatory process on sports performance, it is necessary to explore the existing relationships between kinetic, mechanical, and physiological variables. The objective of this study was to evaluate metabolic stress using thermography in the lower limb [...] Read more.
Introduction: Due to the possible impact of the thermoregulatory process on sports performance, it is necessary to explore the existing relationships between kinetic, mechanical, and physiological variables. The objective of this study was to evaluate metabolic stress using thermography in the lower limb after the Spanish Championship 2023 walk. Method: A descriptive study was carried out on national and international race walkers before and after the 2023 Spanish Championships. The participants performed different tests within the same circuit. Five walkers completed the long-distance race of 35 km, four walkers completed the middle-distance race of 20 km and finally, two walkers completed the short-distance race of 10 km. Result: Statistically significant changes were observed in the lower limbs of the walkers after completing the test. We observed a decrease in skin temperature in all the anatomical regions analyzed, except for the back of the leg. More specifically, the decrease was in the hip (−1.92 °C: p = 0.004), quadriceps, hamstrings (−1.23 °C: p = 0.002), and tibia (−1.23 °C: p = 0.030). However, in the posterior region of the leg, a significant increase in temperature was observed (+0.50 °C: p = 0.011) following the competition. Discussion and Conclusions: The findings in this descriptive investigation support the notion that thermography may serve as a useful tool in the acute analysis of muscle functional activation and metabolic response in professional marching athletes. Moreover, the results confirmed that the change in skin temperature is the result of a variation in acute metabolic and functional activation in the lower extremities of race walkers during competition, with infrared thermography representing an instrument capable of detecting such a change in a rapid and non-invasive manner. Full article
(This article belongs to the Section Biosensors and Healthcare)
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Figure 1
<p>Thermographic Roi’s. (<b>A</b>) Anterior vision, (<b>B</b>) posterior vision, (<b>C</b>) right lateral vision, and (<b>D</b>) left lateral vision.</p>
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<p>Changes in the surface skin temperature of the quadriceps after the end of the competition in the race walkers.</p>
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<p>Changes in the surface skin temperature of the tibia after the end of the competition in the race walkers.</p>
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<p>Changes in the surface skin temperature of the hamstrings after the end of the competition in the race walkers.</p>
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<p>Changes in the surface skin temperature of the calves after the end of the competition in the race walkers.</p>
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<p>Changes in the surface skin temperature of the hip after the end of the competition in the race walkers.</p>
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13 pages, 752 KiB  
Article
The Influence of Elite Race Walkers’ Year-Long Training on Changes in Total Energy and Energy Cost While Walking at Different Speeds
by Wiesław Chwała, Andrzej T. Klimek, Wacław Mirek, Tadeusz Ambroży and Łukasz Rydzik
Appl. Sci. 2024, 14(19), 8805; https://doi.org/10.3390/app14198805 - 30 Sep 2024
Viewed by 733
Abstract
The aim of the study was to assess the influence of year-long training of race walkers on physiological cost and total energy center of mass (CoM). The assessment performed was based on indicating the differences between the resulting energy cost in a group [...] Read more.
The aim of the study was to assess the influence of year-long training of race walkers on physiological cost and total energy center of mass (CoM). The assessment performed was based on indicating the differences between the resulting energy cost in a group of elite race walkers walking at technical, threshold, and racing speeds calculated by physiological and biomechanical methods before beginning and after finishing a year-long training cycle. The study involved 12 competitive race walkers who had achieved champion or international champion level. Their aerobic endurance was determined by means of a direct method, applying an incremental exercise test on the treadmill. The gait of the participants was recorded using the 3D Vicon analysis system. Changes in mechanical energy amounted to the value of the total external work of the muscles needed to accelerate and lift the center of mass during a normalized gait cycle. The highest influence on the total external work increase for increasing speeds of gait in both examinations was attributed to the changes in the kinetic energy resulting from the center of mass movement. A statistically significant decrease of the mean value of total external work for racing speed was observed in the second examination (p < 0.001). An approx. 8% decrease (NS) of EE energy cost, standardized by body mass and distance covered, was found between the first and second examinations. The energy cost and total external work were significantly differentiated by the walkers’ gait speeds (p < 0.05–0.001). The energy cost significantly differed from the total external work at p < 0.001. Full article
(This article belongs to the Special Issue Advances in Sports Training and Biomechanics)
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<p>The average values of the potential energy changes (ΔEp) in the second study at technical (vt), threshold (vp), and racing (vs) speeds, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The average values of the kinetic energy changes ΔEk, at technical (vt), threshold (vp), and racing (vs) speeds, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.005, **** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>The average values of total external work ΔEc (the biomechanical cost of walking) at technical (vt), threshold (vp), and racing (vs) speeds, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.001.</p>
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23 pages, 6044 KiB  
Article
Changes in Magnitude and Shifts in Timing of the Latvian River Annual Flood Peaks
by Elga Apsīte, Didzis Elferts, Jānis Lapinskis, Agrita Briede and Līga Klints
Atmosphere 2024, 15(9), 1139; https://doi.org/10.3390/atmos15091139 - 20 Sep 2024
Viewed by 713
Abstract
Climate change is expected to significantly impact temperature and precipitation, as well as snow accumulations and melt in mid-latitudes, including in the Baltic region, ultimately affecting the quantity and seasonal distribution of streamflow. This study aims to investigate the changes in the magnitude [...] Read more.
Climate change is expected to significantly impact temperature and precipitation, as well as snow accumulations and melt in mid-latitudes, including in the Baltic region, ultimately affecting the quantity and seasonal distribution of streamflow. This study aims to investigate the changes in the magnitude and timing of annual maximum discharge for 30 hydrological monitoring stations across Latvia from 1950/51 to 2021/22. Circular statistics and linear mixed effects models were applied to identify the strength of seasonality and timing. Trend analysis of the magnitude and timing of flood peaks were performed by using the Theil–Sen method and Mann–Kendall test. We analyzed regional significance of trends across different hydrological regions and country using the Walker test. Results indicate strong seasonality in annual flood peaks in catchments, with a single peak occurring in spring in the study sub-period of 1950/51–1986/87. Flood seasonality has changed over recent decades (i.e., 1987/88–2021/22) and is seen as a decrease in spring maximum discharge and increase in winter flood peaks. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt dominated to mixed snow–rainfall dominated, with consistent changes towards the earlier timing of the flood peak, with a more or less pronounced gradation from west to east. Analysis shows that a significant trend of decrease in the magnitude and timing of annual maximum discharge was detected. Full article
(This article belongs to the Special Issue The Hydrologic Cycle in a Changing Climate)
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<p>Map showing the location of hydrological stations and drainage regions: I—Western; II—Central; III—Northern; and IV—Eastern. The background information used for the map was obtained from the Latvian Geospatial Information Agency. The map was developed using the open-source software QGIS3.34.</p>
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<p>Annual mean air temperature for the period 1961–2020 mean value for Latvia (blue dots and solid line) its corresponding linear trend (dashed line) and the mean air temperature of four consecutive climate normal (thick black lines) (n = 25) Using Sen’s slope, statistically significant (<span class="html-italic">p</span> &lt; 0.001) with a rate of change of 0.4 °C decade<sup>−1</sup> [<a href="#B39-atmosphere-15-01139" class="html-bibr">39</a>].</p>
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<p>River hydrograph in Latvia and four hydrological regions of Latvia [<a href="#B33-atmosphere-15-01139" class="html-bibr">33</a>].</p>
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<p>Distribution of the annual Qmax observations in percentage per months, study periods, hydrological districts and Latvia as a whole.</p>
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<p>Percentage point changes in the distribution of the number of Qmax observations per months comparing years 1987/88−2021/22 to years 1950/51−1986/87 per hydrological regions and in Latvia.</p>
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<p>Results of the circular statistics analysis by using the Rayleigh test. Circular plot (grey bars) showing the mean direction and mean resultant length (from 0 at the center and 1 at the outermost line) of the annual maximum peak discharge data for each river station in a particular time period. The colored bars represent the mean resultant vector for each of the regions and Latvia as a whole (see <a href="#atmosphere-15-01139-t003" class="html-table">Table 3</a>).</p>
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<p>Map showing the results of trends in Mmax magnitude by using the Mann–Kendal test with blue and red symbols (see the legend) and the Theil–Sen approach with the numbers in the study period of 1950/51–2021/22 (if the mean trend value was positive, then all trends at the stations would also be positive and vice versa).</p>
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<p>Box-plot of Theil–Sen slope in Ls<sup>−1</sup> km<sup>−2</sup> decade<sup>−1</sup> for Mmax magnitude and days per decade for Qmax timing for stations (n = 30) showing trends across Latvia.</p>
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<p>Long-term temporal changes in annual Mmax of floods in four hydrological regions and across Latvia in the study period of 1950/51–2021/22. Green lines present Mmax mean values and red lines present median values over the entire drainage region and across Latvia. The green area represents 95% confidence interval for the mean annual Mmax values of the hydrological year. Blue, dashed lines present the linear trend.</p>
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<p>Map showing the results of trends in annual Qmax timing using the Mann–Kendal test with blue and red symbols (see legend) and the Theil–Sen approach with the numbers in the study period of 1950/51–2021/22 (if the mean trend value was positive, then all trends at the stations would also be positive and vice versa).</p>
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<p>Long-term temporal changes in timing of annual Qmax in four drainage regions and across Latvia in the study period of 1950/51–2021/22. Green lines show mean values and red lines show median values timing across drainage regions and the country. The green area represents a 95% confidence interval for the mean timing values of the hydrological year. Blue, dashed lines show a linear decreasing trend.</p>
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<p>Relationship of trends in magnitude of annual Mmax and changes in timing of annual Qmax. Negative values in timing indicate early changes. The grey area represents 95% confidence interval for the period of 1950/51–2021/22.</p>
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11 pages, 2224 KiB  
Article
Oxygen Consumption, Ventilatory Thresholds, and Work Zones in Nordic Walking Competitors
by María Serna-Martínez, Sandra Ribes-Hernández and Ignacio Martínez-González-Moro
J. Funct. Morphol. Kinesiol. 2024, 9(3), 171; https://doi.org/10.3390/jfmk9030171 - 19 Sep 2024
Viewed by 1464
Abstract
Background: Nordic walking (NW) is a physical sports activity that has been sufficiently studied from the point of view of health, but physiological and performance analyses have not been so much. Objectives: With this study, we intend to analyse the physical work areas, [...] Read more.
Background: Nordic walking (NW) is a physical sports activity that has been sufficiently studied from the point of view of health, but physiological and performance analyses have not been so much. Objectives: With this study, we intend to analyse the physical work areas, according to ventilatory thresholds, that occur during a NW competition. Methods: Four participants of different characteristics anthropometrics (weight 57.6–85.6 kg; height 165.8–178 cm; and fat percentage 14.5–21.5%) gender (3 males and 1 female) and age (15–57 years) who participated in the NW regional championship have been chosen, and their electrocardiographic tracing was recorded using a NUUBO® device throughout the race, obtaining average and maximum heart rates (HR) in eight sections of the circuit. Previously, in the laboratory, a maximal stress test was performed to determine the maximum oxygen consumption (VO2max), the first (VT1) and second (VT2) ventilatory threshold (VT). With these data, four work areas were obtained. Results: Most of the sections of the circuit were conducted with average HRs in zone 2a (above average between VT1 and VT2 but below VT2) and peak HRs in zone 3 (between VT2 and VO2max). Conclusions: We conclude that, with the data collected on HR, VO2max, and VT, the training zones obtained can be related to the heart rates in the different sections of the circuit. This can be used to improve the sports performance of the walkers. Full article
(This article belongs to the Section Athletic Training and Human Performance)
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<p>Placement of the Nuubo<sup>®</sup> device.</p>
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<p>Diagram of the circuit, controls, and sections. The red and green dots indicate the location of the time controls. The green dot marks the return of the cadet category.</p>
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<p>Example of minute electrocardiogram graph. The registration between 10.34 a.m. and 10.41 a.m. displayed. Blue shows events, in this case several supraventricular extrasystoles at minutes 34, 37, 39, and 41.</p>
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<p>Heart rate (HR) zones from ventilatory thresholds (VT1 = first ventilatory threshold; VT2 = second ventilatory threshold).</p>
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<p>Dynamic evolution % HR max.</p>
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15 pages, 648 KiB  
Article
The Assessment of Postural–Motor, Coordination, and Reflex Functions in Children and Adolescents with a History of Premature Verticalization and Ontogeny Disorders in Their First Year of Life
by Mieczysław Maciak, Kamil Koszela, Anna Beniuk and Marta Woldańska-Okońska
Children 2024, 11(9), 1071; https://doi.org/10.3390/children11091071 - 31 Aug 2024
Viewed by 2457
Abstract
(1) Background: Contracting diseases or being exposed to adverse environmental factors in the first year of life may impair the development of body posture and motor coordination. The purpose of this study was to evaluate the correlation between data on the speed of [...] Read more.
(1) Background: Contracting diseases or being exposed to adverse environmental factors in the first year of life may impair the development of body posture and motor coordination. The purpose of this study was to evaluate the correlation between data on the speed of passive verticalization, the number of risk factors and the quality of development in the first year of life, and the results of the functional examination of these individuals in adolescence. (2) Methods: Two groups of 60 volunteers, aged 9–14 years, were examined by performing functional tests and the retrospective analysis of their development up to the age of 1 year. The first group consisted of patients diagnosed with postural defects. The control group consisted of healthy people of the same age who volunteered for this study. (3) Results: Statistical analysis showed statistically significant differences between groups in terms of posture (p = 0.001), motor coordination (p = 0.001), and accumulated primitive reflexes (p = 0.001), as well as a high correlation between these disorders and the quality of development in the first year of life. In the first group, for the ages of 3–6 months (r = 0.96; p = 0.001), 6–9 months (r = 0.871; p = 0.001), and 9–12 months (r = 0.806; p = 0.001), no significant correlations were found with the age of 0–3 months. In the second group, the results were as follows: 0–3 months (r = 0.748; p = 0.001), 3–6 months (r = 0.862 p = 0.001), 6–9 months (r = 0.698; p = 0.001), and 9–12 months (r = 0.740; p = 0.001). In the group of adolescents with posture defects, we observed an earlier time of passive verticalization and sitting, as well as more frequent use of loungers, seats, and walkers (p = 0.026). (4) Conclusions: The analysis of this study’s data indicates that the development of body posture and motor coordination may be impaired due to accelerated and passive verticalization in the first year of life. Full article
(This article belongs to the Section Pediatric Neurology & Neurodevelopmental Disorders)
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<p>Selected developmental positions in the first year of life according to the principles of developmental kinesiology DNS (dynamic neuromuscular stabilization) [<a href="#B2-children-11-01071" class="html-bibr">2</a>].</p>
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<p>Distribution of body posture assessment results in standing position in group 1 (N = 60) and group 2 (N = 60).</p>
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12 pages, 7357 KiB  
Article
User-Centered Evaluation of the Wearable Walker Lower Limb Exoskeleton; Preliminary Assessment Based on the Experience Protocol
by Cristian Camardella, Vittorio Lippi, Francesco Porcini, Giulia Bassani, Lucia Lencioni, Christoph Mauer, Christian Haverkamp, Carlo Alberto Avizzano, Antonio Frisoli and Alessandro Filippeschi
Sensors 2024, 24(16), 5358; https://doi.org/10.3390/s24165358 - 19 Aug 2024
Viewed by 1086
Abstract
Using lower limb exoskeletons provides potential advantages in terms of productivity and safety associated with reduced stress. However, complex issues in human–robot interactions are still open, such as the physiological effects of exoskeletons and the impact on the user’s subjective experience. In this [...] Read more.
Using lower limb exoskeletons provides potential advantages in terms of productivity and safety associated with reduced stress. However, complex issues in human–robot interactions are still open, such as the physiological effects of exoskeletons and the impact on the user’s subjective experience. In this work, an innovative exoskeleton, the Wearable Walker, is assessed using the EXPERIENCE benchmarking protocol from the EUROBENCH project. The Wearable Walker is a lower-limb exoskeleton that enhances human abilities, such as carrying loads. The device uses a unique control approach called Blend Control that provides smooth assistance torques. It operates two models simultaneously, one in the case in which the left foot is grounded and another for the grounded right foot. These models generate assistive torques combined to provide continuous and smooth overall assistance, preventing any abrupt changes in torque due to model switching. The EXPERIENCE protocol consists of walking on flat ground while gathering physiological signals, such as heart rate, its variability, respiration rate, and galvanic skin response, and completing a questionnaire. The test was performed with five healthy subjects. The scope of the present study is twofold: to evaluate the specific exoskeleton and its current control system to gain insight into possible improvements and to present a case study for a formal and replicable benchmarking of wearable robots. Full article
(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)
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<p>The <span class="html-italic">Wearable Walker</span> lower limb exoskeleton along with the sensing devices used for the experiment. The CAD models show the kinematic variables and the detail of the two degrees of freedom that the thigh harness has with regards to the exoskeleton’s thigh link.</p>
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<p>Electronics, computing units, and assistance computation architecture of the <span class="html-italic">Wearable Walker</span> lower limb exoskeleton. In the bottom right scheme, red blocks highlight the components of assistive torques reported in Equation (<a href="#FD2-sensors-24-05358" class="html-disp-formula">2</a>).</p>
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<p>Scores of the physiological PIs of the EXPERIENCE protocol for each volunteer as a function of time. Each color corresponds to one volunteer. The three protocol phases, i.e., SIT, SIT EXO, and WALK are plotted together and marked in the figures.</p>
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<p>Scores for the psychophysiological performance indicators (PIs) of the EXPERIENCE protocol for each volunteer. Each point on the <span class="html-italic">x</span>-axis represents an average of a 1-minute recording. Curves show the evolution in time of such PIs.</p>
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<p>Distribution of answers to the questionnaire items. Bars report the average score and the whiskers their standard deviation.</p>
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14 pages, 1681 KiB  
Article
Functional and Structural Changes in Patients with Spinal Muscular Atrophy Treated in Poland during 12-Month Follow-Up: A Prospective Cohort Study
by Aleksandra Bieniaszewska, Magdalena Sobieska and Ewa Gajewska
J. Clin. Med. 2024, 13(14), 4232; https://doi.org/10.3390/jcm13144232 - 19 Jul 2024
Viewed by 1216
Abstract
Background: In recent years, rapid advances in diagnosis and treatment have been observed in spinal muscular atrophy (SMA) patients. The introduction of modern therapies and screening tests has significantly changed the clinical picture of the disease. The previous classification has, therefore, been replaced [...] Read more.
Background: In recent years, rapid advances in diagnosis and treatment have been observed in spinal muscular atrophy (SMA) patients. The introduction of modern therapies and screening tests has significantly changed the clinical picture of the disease. The previous classification has, therefore, been replaced by new phenotypes: non-sitters, sitters, and walkers, defined by the patient’s functional level. However, despite the change in the clinical picture of the disease, patients still suffer from accompanying structural disorders such as scoliosis or joint contractures. Their presence also significantly affects the acquisition of subsequent motor skills. Due to this, monitoring structural changes and ensuring therapists are aware of improvements or declines in patient functionality are essential components of clinical practice. This study aims to compare the assessment of structural and functional changes after a 12-month follow-up in SMA patients who have already experienced the effects of the disease and are now receiving modern therapy. Methods: We present a study of 34 SMA patients being treated with modern therapies and tested twice 12 months apart. The participants were tested using structural measurements and validated scales such as The Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND) and Hammersmith Functional Motor Scale–Expanded (HFMSE). Results: During the 12-month follow-up, patients showed deteriorating, non-statistically significant structural changes. We also proved that patients showed a trend toward functional improvement. Analyzing the individual scale items, we distinguished which participants obtained the maximum score for a given parameter and no longer had an opportunity to improve during the second examination. Conclusions: Our study proved that most patients improved overall motor function. The examination of structural measurements should become a standard in the evaluation of SMA patients. Full article
(This article belongs to the Section Clinical Neurology)
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<p>Changes for the non-sitters’ group in individual CHOP-INTEND scale items.</p>
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<p>Changes in individual HFMSE scale items for sitters and walkers.</p>
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47 pages, 776 KiB  
Article
Bivariate Random Coefficient Integer-Valued Autoregressive Model Based on a ρ-Thinning Operator
by Chang Liu and Dehui Wang
Axioms 2024, 13(6), 367; https://doi.org/10.3390/axioms13060367 - 29 May 2024
Viewed by 692
Abstract
While overdispersion is a common phenomenon in univariate count time series data, its exploration within bivariate contexts remains limited. To fill this gap, we propose a bivariate integer-valued autoregressive model. The model leverages a modified binomial thinning operator with a dispersion parameter ρ [...] Read more.
While overdispersion is a common phenomenon in univariate count time series data, its exploration within bivariate contexts remains limited. To fill this gap, we propose a bivariate integer-valued autoregressive model. The model leverages a modified binomial thinning operator with a dispersion parameter ρ and integrates random coefficients. This approach combines characteristics from both binomial and negative binomial thinning operators, thereby offering a flexible framework capable of generating counting series exhibiting equidispersion, overdispersion, or underdispersion. Notably, our model includes two distinct classes of first-order bivariate geometric integer-valued autoregressive models: one class employs binomial thinning (BVGINAR(1)), and the other adopts negative binomial thinning (BVNGINAR(1)). We establish the stationarity and ergodicity of the model and estimate its parameters using a combination of the Yule–Walker (YW) and conditional maximum likelihood (CML) methods. Furthermore, Monte Carlo simulation experiments are conducted to evaluate the finite sample performances of the proposed estimators across various parameter configurations, and the Anderson-Darling (AD) test is employed to assess the asymptotic normality of the estimators under large sample sizes. Ultimately, we highlight the practical applicability of the examined model by analyzing two real-world datasets on crime counts in New South Wales (NSW) and comparing its performance with other popular overdispersed BINAR(1) models. Full article
(This article belongs to the Section Mathematical Analysis)
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<p>Variation of MAE and RMSE for Model (A) estimates across various sample sizes.</p>
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<p>Variation of MAE and RMSE for Model (B) estimates across various sample sizes.</p>
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<p>Variation of MAE and RMSE for Model (C) estimates across various sample sizes.</p>
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<p>Variation of MAE and RMSE for Model (D) estimates across various sample sizes.</p>
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<p>Variation of MAE and RMSE for Model (E) estimates across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm511"><mml:semantics><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm512"><mml:semantics><mml:msub><mml:mi>p</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:semantics></mml:math></inline-formula> for Model (A) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm513"><mml:semantics><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ρ</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm514"><mml:semantics><mml:mi>μ</mml:mi></mml:semantics></mml:math></inline-formula> for Model (A) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm515"><mml:semantics><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm516"><mml:semantics><mml:msub><mml:mi>p</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:semantics></mml:math></inline-formula> for Model (B) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm517"><mml:semantics><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ρ</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm518"><mml:semantics><mml:mi>μ</mml:mi></mml:semantics></mml:math></inline-formula> for Model (B) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm519"><mml:semantics><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm520"><mml:semantics><mml:msub><mml:mi>p</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:semantics></mml:math></inline-formula> for Model (C) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm521"><mml:semantics><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ρ</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm522"><mml:semantics><mml:mi>μ</mml:mi></mml:semantics></mml:math></inline-formula> for Model (C) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm523"><mml:semantics><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm524"><mml:semantics><mml:msub><mml:mi>p</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:semantics></mml:math></inline-formula> for Model (D) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm525"><mml:semantics><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ρ</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm526"><mml:semantics><mml:mi>μ</mml:mi></mml:semantics></mml:math></inline-formula> for Model (D) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm527"><mml:semantics><mml:mrow><mml:msub><mml:mi>α</mml:mi><mml:mn>1</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:msub><mml:mi>α</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm528"><mml:semantics><mml:msub><mml:mi>p</mml:mi><mml:mn>1</mml:mn></mml:msub></mml:semantics></mml:math></inline-formula> for Model (E) across various sample sizes.</p>
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<p>Gaussian QQ plots of the estimates of <inline-formula><mml:math id="mm529"><mml:semantics><mml:mrow><mml:msub><mml:mi>p</mml:mi><mml:mn>2</mml:mn></mml:msub><mml:mo>,</mml:mo><mml:mi>ρ</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula>, and <inline-formula><mml:math id="mm530"><mml:semantics><mml:mi>μ</mml:mi></mml:semantics></mml:math></inline-formula> for Model (E) across various sample sizes.</p>
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<p>Sample paths of OCND and OLNG series.</p>
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<p>The autocorrelation function (ACF) and cross-correlation (CCF) plots of OCND and OLNG series.</p>
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<p>Histograms of OCND and OLNG counts.</p>
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<p>Sample paths of BETD and BETND series.</p>
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<p>The autocorrelation function (ACF) and cross-correlation (CCF) plots of BETD and BETND series.</p>
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<p>Histograms of BETD and BETND counts.</p>
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21 pages, 7418 KiB  
Article
Fatigue Crack Propagation of 51CrV4 Steels for Leaf Spring Suspensions of Railway Freight Wagons
by Vítor M. G. Gomes, Grzegorz Lesiuk, José A. F. O. Correia and Abílio M. P. de Jesus
Materials 2024, 17(8), 1831; https://doi.org/10.3390/ma17081831 - 16 Apr 2024
Viewed by 991
Abstract
Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible, which [...] Read more.
Leaf springs are critical components for the railway vehicle safety in which they are installed. Although these components are produced in high-strength alloyed steel and designed to operate under cyclic loading conditions in the high-cyclic fatigue region, their failure is still possible, which can lead to economic and human catastrophes. The aim of this document was to precisely characterise the mechanical crack growth behaviour of the chromium–vanadium alloyed steel representative of leaf springs under cyclic conditions, that is, the crack propagation in mode I. The common fatigue crack growth prediction models (Paris and Walker) considering the effect of stress ratio and parameters such as propagation threshold, critical stress intensity factor and crack closure ratio were also determined using statistical methods, which resulted in good approximations with respect to the experimental results. Lastly, the fracture surfaces under the different test conditions were analysed using SEM, with no significant differences to declare. As a result of this research work, it is expected that the developed properties and fatigue crack growth prediction models can assist design and maintenance engineers in understanding fatigue behaviour in the initiation and propagation phase of cracks in leaf springs for railway freight wagons. Full article
(This article belongs to the Special Issue Fatigue Crack Growth in Metallic Materials (Volume II))
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<p>Fatigue fracture of the master spring leaf of a parabolic leaf spring.</p>
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<p>Typical microstructure of the chromium–vanadium alloyed steel for all tested specimens [<a href="#B4-materials-17-01831" class="html-bibr">4</a>].</p>
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<p>Geometry of the compact tension specimen used to evaluate the crack growth propagation under mode I fatigue loading.</p>
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<p>Illustration of the directions from which samples were taken according to the LT and TL labels.</p>
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<p>Influence of the rolling direction in the crack propagation rate in propagation regime II.</p>
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<p>Variation in the crack propagation rate in propagation regime II in relation to the applied stress intensity factor range for different stress intensity ratios.</p>
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<p>Average value of the crack closure ratio and respective standard deviation determined throughout the fatigue crack propagation tests.</p>
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<p>Determination of the threshold of the stress intensity factor range from the analysis of the variation in stress intensity factor range throughout the crack growth fatigue testing.</p>
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<p>Effect of the stress ratio on the propagation threshold and the crack propagation model for regime I according to Equation (<a href="#FD3-materials-17-01831" class="html-disp-formula">3</a>).</p>
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<p>Global <math display="inline"><semantics> <mrow> <mi>d</mi> <mi>a</mi> <mo>/</mo> <mi>d</mi> <mi>N</mi> <mo>−</mo> <mo>Δ</mo> <mi>K</mi> </mrow> </semantics></math> curve representing the variation in crack propagation rate in propagation regime II for several stress ratios and its respective standard deviation.</p>
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<p>Relationship for determining the Walker’s parameter, <math display="inline"><semantics> <mi>γ</mi> </semantics></math>, in accordance with Equation (<a href="#FD8-materials-17-01831" class="html-disp-formula">8</a>).</p>
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<p>Representation of the Walker’s model (Equation (<a href="#FD4-materials-17-01831" class="html-disp-formula">4</a>)) for different stress intensity factor ratios.</p>
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<p>Representation of the Walker’s model (Equation (<a href="#FD9-materials-17-01831" class="html-disp-formula">9</a>)) for different stress intensity factor ratios.</p>
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<p>Illustration of a pre-crack size for a ×40 magnification.</p>
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<p>Comparison between fracture surface paths of specimens obtained from LT and TL directions for a ×500 magnification (<math display="inline"><semantics> <msub> <mi>R</mi> <mi>σ</mi> </msub> </semantics></math> = 0.1).</p>
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<p>Crack propagation path from the pre-crack initiation zone to the unstable propagation moment for a ×100 magnification (<math display="inline"><semantics> <msub> <mi>R</mi> <mi>σ</mi> </msub> </semantics></math> = 0.1 and 0.5).</p>
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<p>Topography comparison of fracture surfaces from the initiation zone to the unstable propagation zone for <math display="inline"><semantics> <msub> <mi>R</mi> <mi>σ</mi> </msub> </semantics></math> = 0.1 and 0.5.</p>
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<p>Magnification of the crack propagation path from the pre-crack initiation zone to the beginning moment of unstable propagation for a ×2.00k magnification (<math display="inline"><semantics> <msub> <mi>R</mi> <mi>σ</mi> </msub> </semantics></math> = 0.1 and 0.5).</p>
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23 pages, 4517 KiB  
Article
Aroplectrus dimerus (Hymenoptera: Eulophidae), Ectoparasitoid of the Nettle Caterpillar, Oxyplax pallivitta (Lepidoptera: Limacodidae): Evaluation in the Hawaiian Islands
by Juliana A. Yalemar, Walter T. Nagamine, Renato C. Bautista, Dexter Y. Cho, Larry M. Nakahara and Mohsen M. Ramadan
Life 2024, 14(4), 509; https://doi.org/10.3390/life14040509 - 15 Apr 2024
Viewed by 1686
Abstract
The stinging nettle caterpillar, Oxyplax (syn. Darna) pallivitta (Lepidoptera: Limacodidae), is a serious invasive pest of agricultural products and a health hazard on the Hawaiian Islands first discovered in 2001. Nursery workers and homeowners have been stung by the caterpillars while handling [...] Read more.
The stinging nettle caterpillar, Oxyplax (syn. Darna) pallivitta (Lepidoptera: Limacodidae), is a serious invasive pest of agricultural products and a health hazard on the Hawaiian Islands first discovered in 2001. Nursery workers and homeowners have been stung by the caterpillars while handling their plants, especially rhapis palms (Rhapis sp.). Throughout its invaded range, it causes widespread damage, including the many cultivated and native palm species that have grown in Hawaii. Larvae contain urticating hairs that secrete a toxin, causing painful skin swelling and irritation on contact. Horticulture and nursery products impacted by the limacodid pest are estimated at $84.3 million (2018 value). Suppression efforts with pesticides and lure traps were ineffective, and the moth population continued to spread to major Hawaiian Islands (Hawaii, Kauai, Maui, Oahu). The introduction of specific biological control agents from the native region was thought to be the long-term solution for this invasive pest. Initial exploration in Indonesia and Thailand resulted in the introduction of a pupal ectoparasitoid, Nesolynx sp. (Hymenoptera: Eulophidae: Tetrastichinae), that was not specific. The oriental wasp, Aroplectrus dimerus Lin (Hymenoptera: Eulophidae: Eulophinae), idiobiont gregarious ectoparasitoid of the stinging nettle caterpillar, was introduced from Taiwan in 2004 for host specificity studies and biocontrol in Hawaii. Host range testing showed the parasitoid attacked only limacodid species, and it was approved for field release in 2010. The parasitoid identity, host specificity under containment facility conditions, reproductive performance, and colonization on the major infested sites were assessed. A total of 13,379 parasitoids were colonized on 162 release sites on four Hawaiian Islands. Evaluations were conducted using field surveys of larvae, pupal counts, and male lure traps. Field parasitism was thoroughly investigated on Oahu Island, averaging 18.9 ± 5.6% of 3923 collected larvae during 2010–2023. The numbers of male moths caught/trap/month were significantly reduced on Oahu Island (p < 0.05). Recently, the hyperparasitoid, Pediobius imbreus Walker (Hymenoptera: Eulophidae: Entedoninae), was detected, reducing the efficiency of A. dimerus in the field. The mean hyperparasitism of A. dimerus pupae was 27.3 ± 7.6% on Oahu Island. There was no detailed biological assessment for A. dimerus or its field evaluation available in scientific literature. Results were discussed regarding the potential use of A. dimerus in biocontrol elsewhere if the stinging nettle caterpillar was invaded in the future. Full article
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<p>Map of major infestation sites, parasitoid colonization, and establishment on the Hawaiian Islands (sizes of the islands are not in scale). Sampling locations with GPS coordinates are shown in Tables. (Oahu Island GPS coordinates of 21°18′56.1708″ N, 157°51′29.1348″ W; Hawaii Island with the GPS coordinates of 19°44′30.3180″ N, 155°50′39.9732″ W; Kauai Island with GPS coordinates of 22°6′30.7548″ N, 159°29′48.3540″ W.; Maui Island with GPS coordinates of 20°47′54.1068″ N and 156°19′54.9264″ W. [<a href="https://www.latlong.net" target="_blank">https://www.latlong.net</a> (accessed on 13 December 2023)].</p>
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<p><span class="html-italic">Aroplectrus dimerus</span> (<b>A</b>) female side habitus, curved down mesosoma in profile along the dorsal margin, overall body color yellow and reddish, scape longer than eye, head narrower than mesosoma, smooth hind coxae; (<b>B</b>) scutellum finely granulate with longitudinal carinae, propodeum, median carina weak, submedian areola divided completely into two sectors by a continuous oblique carina; (<b>C</b>) forewing hyaline, densely pilose veins brownish wing post-marginal vein longer than stigmal vein; (<b>D</b>) elongate metatibial spur longer than basitarsus, not reaching apex of second tarsal segment; (<b>E</b>) gaster, female metasoma shorter and narrower than mesosoma, oblong-ovate in dorsal view unicolor, gaster showing dark bands and black ovipositor sheath, ovipositor exerting beyond abdominal apex, smooth hind coxae (pictures taken using MMR).</p>
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<p><span class="html-italic">Aroplectrus dimerus</span> (<b>A</b>) female antenna, funicle 4 segmented and a clava, F1 4X longer than broad, antenna with reddish scape, darker on funicle, female antenna, clava as long as F4; (<b>B</b>) male antenna showing slender funicle and shorter clava, antennae more slender, club broader than funicle 1; (<b>C</b>) showing vertex and yellow pronotum, head dorso-posterior view showing occipital carina feature, and quadrate pronotum with two side-long sitae in the middle; (<b>D</b>) dorso frontal view of head showing scape longer than eye and facial epistomal suture distinct straight, vertex with few black sitae and sparse cilia, malar space smooth shorter than eye, antenna with scape much longer than eye; (<b>E</b>) head frontal facial view showing head wider than head length (pictures taken using MMR).</p>
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<p><span class="html-italic">Pediobius imbreus</span>, (<b>A</b>) side habitus of female, has a body mostly dark with less metallic reflections, antennae inserted at the lower level of eyes, coxae, trochanters, femora black, tibiae, and tarsus coloration varied between specimens in HDOA collection, some specimens with all dark or all white, with or without metallic bluish reflections; (<b>B</b>) exit holes from pupae of <span class="html-italic">Aroplectrus dimerus</span> (red arrows on exit holes anterior with hyper pupal molt, and posterior of pupa); (<b>C</b>) head front view showing transverse frontal suture extended close to compound eyes; (<b>D</b>) scutum reticulate, scutellum with longitudinal reticulate sculpture having a median narrow, smooth band, broad head pronotum, and reticulate sculptured mesothorax; (<b>E</b>) propodium with divergent middle carina and lateral propodeal plicae. Propodeum short, with submedian carinae diverging posteriorly (pictures taken using MMR).</p>
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<p>(<b>A</b>) female <span class="html-italic">Aroplectrus dimerus</span> on the host larva; (<b>B</b>) female dorsal view showing color peculiarity; (<b>C</b>) eggs laid on host larva between scolli; (<b>D</b>) first instars <span class="html-italic">A. dimerus</span> migrate to the underside of host larva (arrows point at first instars, black marks are female stinging marks to paralyze the host before oviposition not the feeding wounds by larvae); (<b>E</b>) mature larvae consume the host still with uncharged prepupal meconia; (<b>F</b>) pupae of the parasitoid underneath the host‘ cadaver, dark material between pupae are the vacated meconia. Photos credited to MMR and WTN.</p>
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<p>Survivorship of male and female <span class="html-italic">Aroplectrus dimerus</span> under laboratory conditions. All wasp categories fed honey and had access to water, except starved wasps. Different letters on top of bars indicate significant differences (ANOVA, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Mean number of <span class="html-italic">Oxyplax pallivitta</span> lured into male pheromone traps per month on the Hawaiian Islands before parasitoid release during 2007, 2009, and after parasitoid establishment during 2011, 2021–2023 on Oahu Island. Different letters on top of bars indicate significant differences (ANOVA, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p><span class="html-italic">Oxyplax pallivittus</span>: (<b>A</b>) female habitus; (<b>B</b>) male habitus see bipectinate antennae and end of abdomen; (<b>C</b>) flat eggs (1.6 mm length); (<b>D</b>) stinging larvae (L6–L10); (<b>E</b>) spherical cocoons collected from Oahu nursery in thousands in 2007 (6.5 mm Ø); (<b>F</b>) male pupa removed from the cocoon. Photos taken using MMR, WTN.</p>
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20 pages, 2353 KiB  
Article
Design of Low-Cost Modular Bio-Inspired Electric–Pneumatic Actuator (EPA)-Driven Legged Robots
by Alessandro Brugnera Silva, Marc Murcia, Omid Mohseni, Ryu Takahashi, Arturo Forner-Cordero, Andre Seyfarth, Koh Hosoda and Maziar Ahmad Sharbafi
Biomimetics 2024, 9(3), 164; https://doi.org/10.3390/biomimetics9030164 - 7 Mar 2024
Viewed by 2422
Abstract
Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion [...] Read more.
Exploring the fundamental mechanisms of locomotion extends beyond mere simulation and modeling. It necessitates the utilization of physical test benches to validate hypotheses regarding real-world applications of locomotion. This study introduces cost-effective modular robotic platforms designed specifically for investigating the intricacies of locomotion and control strategies. Expanding upon our prior research in electric–pneumatic actuation (EPA), we present the mechanical and electrical designs of the latest developments in the EPA robot series. These include EPA Jumper, a human-sized segmented monoped robot, and its extension EPA Walker, a human-sized bipedal robot. Both replicate the human weight and inertia distributions, featuring co-actuation through electrical motors and pneumatic artificial muscles. These low-cost modular platforms, with considerations for degrees of freedom and redundant actuation, (1) provide opportunities to study different locomotor subfunctions—stance, swing, and balance; (2) help investigate the role of actuation schemes in tasks such as hopping and walking; and (3) allow testing hypotheses regarding biological locomotors in real-world physical test benches. Full article
(This article belongs to the Special Issue Bio-Inspired Locomotion and Manipulation of Legged Robot)
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<p>Evolutionary progression of the EPA Robot Series: MARCO-Hopper II began with a 1D hopping motion and later evolved into EPA-Hopper I, a human-sized, two-segmented leg with hip and knee joint motors and antagonistic PAMs. From this, EPA-Hopper II was designed to additionally include a 3D-printed foot, ankle-extensor PAM, and ankle-flexor spring. The iteration continued with the EPA Jumper, which incorporated a trunk and additional PAMs. This progression culminated in EPA Walker, the final bipedal iteration featuring four motors and a total of 18 PAMs for advanced mobility.</p>
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<p>Explosive CAD visualization for the latest iteration of the EPA leg.</p>
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<p>(<b>a</b>) Integration of PAMs into the robot, with the attachment points and configuration of PAMs on the robotic system being showcased. The robotic leg is equipped with six mono-articular PAMs (depicted in red) and three bi-articular PAMs (depicted in blue). The represented muscles are iliopsoas (IL), rectus femoris (RF), gluteus maximus (GL), hamstring (HAM), vastus (VAS), popliteus (POP), tibialis anterior (TIB), soleus (SOL), and gastrocnemius (GAS). (<b>b</b>) Extension from EPA Jumper to EPA Walker.</p>
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<p>Communication network and its layers: <span class="html-italic">high-level control layer</span>, where control and monitoring occur within the Simulink Real-Time environment; <span class="html-italic">low-level control layer</span> with boards facilitating communication with the robot’s actuators and sensors; and <span class="html-italic">hardware</span>, encompassing the physical components of the robot. Icons and photos can be found in [<a href="#B66-biomimetics-09-00164" class="html-bibr">66</a>].</p>
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<p>Preliminary hopping results of EPA Jumper using the FMC controller. The first two rows depict hip and knee angles throughout the hopping experiment, with gray-shaded backgrounds indicating the stance phase. The third row presents the center of pressure on the force plate with average positions highlighted at each step. The final row illustrates the ground reaction force measured by the force plate. A video of the experiment is available on [<a href="#B68-biomimetics-09-00164" class="html-bibr">68</a>].</p>
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<p>Representative hopping experiments conducted with MARCO-Hopper II, EPA-Hopper I, EPA-Hopper II, and EPA Jumper. Each graph depicts a single sample hop, starting at touchdown (0%). (<b>a</b>) Normalized GRF calculated by dividing the GRF by the corresponding robot weight and the (<b>b</b>) normalized hip displacement. A video of the robots’ hopping is available on [<a href="#B68-biomimetics-09-00164" class="html-bibr">68</a>].</p>
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13 pages, 4833 KiB  
Communication
A Rapid-Convergence Precise Point Positioning Approach Using Double Augmentations of Low Earth Orbit Satellite and Atmospheric Information
by Bei He, Changsheng Cai and Lin Pan
Remote Sens. 2023, 15(22), 5265; https://doi.org/10.3390/rs15225265 - 7 Nov 2023
Viewed by 1736
Abstract
The precise point positioning (PPP) technique generally takes tens of minutes to converge, severely limiting its use. This longer convergence time is mainly due to the slower variation of satellite geometry in space and the stronger correlation of unknown parameters to be estimated. [...] Read more.
The precise point positioning (PPP) technique generally takes tens of minutes to converge, severely limiting its use. This longer convergence time is mainly due to the slower variation of satellite geometry in space and the stronger correlation of unknown parameters to be estimated. Fortunately, the lower orbit altitude of Low Earth Orbit (LEO) satellites contributes to the fast variation of the satellites’ spatial geometry. In addition, high-precision atmospheric delay information has become readily available, which can help decrease unknown parameters’ correlation. This study proposes a double-augmentation PPP approach with accelerated convergence by tightly integrating the LEO/atmosphere-augmented information. The GNSS observations in both mid-latitude and low-latitude areas, and simulated LEO observations under a Walker/polar mixed constellation, are used to validate the double-augmentation PPP approach. Test results in both areas indicate that the double-augmentation PPP can converge within 0.8 min, improving the convergence time by over 73%, and over 83% compared to the LEO-only augmented PPP and atmosphere-only augmented PPP. Full article
(This article belongs to the Special Issue Precise Point Positioning (PPP) Based on Multi-GNSS)
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<p>Spatial configuration of simulated LEO constellation.</p>
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<p>Geographical distribution of GNSS stations.</p>
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<p>Visible LEO satellite distribution.</p>
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<p>Number of visible satellites and PDOP for LEO-augmented GNSS.</p>
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<p>LEO-augmented GNSS PPP errors at MAR7 and JFNG stations, ‘GRECL’ denotes GPS, GLONASS, Galileo, BDS, and LEO.</p>
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<p>Geographical distribution of regional GPS stations.</p>
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<p>Errors of the obtained tropospheric delay at mobile stations.</p>
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<p>Errors of the obtained slant ionospheric delay at mobile stations.</p>
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<p>Positioning errors for two different double-augmentation PPP processing scenarios.</p>
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<p>Positioning errors for different PPP-processing scenarios on 21 October 2022.</p>
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<p>Distribution of convergence time for different PPP-processing scenarios.</p>
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