bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Dietary Bacillus amyloliquefaciens SCAU-070 (Based on a Woody Plant-Based Diet) on Antioxidation, Immune and Intestinal Microbiota of Tilapia (Oreochromis niloticus)
Authors: Chen Qijing , Wu Feng , Chen Xinye , Yang Qiaoting , Ye Biyin , Chen Xiaoyu , Zhang Xiaoyong , Pan Qin
Published: May 2024

This study aimed to explore the effects of Bacillus amyloliquefaciens (BA) as one woody forage addition (as a probiotic, 1 × 107 CFU/g) on tilapia (Oreochromis niloticus). Woody forage is one kind of fishery feed that could significantly enhance the growth, feed utilization, and digestibility of tilapia. At first, tilapia was divided into eight groups and fed with control, control + BA, Moringa oleifera, M. oleifera + BA, Neolamarckia cadamba, N. cadamba + BA, Broussonetia papyrifera, and B. papyrifera + BA diets, respectively. After dieting for 8 weeks, the intestinal morphology of tilapia in the eight groups was observed, and the effects of the B. amyloliquefaciens addition and wordy forage on the intestine functions were analyzed by two-way ANOVA. As no significant negative effects were found on the woody forage on tilapia, the villus height, density and width, and epithelial goblet cells in the posterior intestines of tilapia with BA supplementation were greater than those in the groups without BA supplementation, suggesting B. amyloliquefaciens SCAU-070 could promote the growth and development of tilapia intestinal tracts. Furthermore, it was found that B. amyloliquefaciens SCAU-070 enhanced the antioxidation capacity of tilapia posterior intestine tissue by promoting the activity of superoxide dismutase and content of malondialdehyde. In addition, the result of high-throughput sequencing (16S rDNA) showed that the beneficial bacteria Cetobacterium and Romboutsia in the probiotic groups increased significantly, while the potential pathogenic bacteria Acinetobacter decreased significantly.
Identification and Evaluation of Olive Phenolics in the Context of Amine Oxidase Enzyme Inhibition and Depression: In Silico Modelling and In Vitro Validation
Authors: Karagiannis Tom C. , Ververis Katherine , Liang Julia J. , Pitsillou Eleni , Liu Siyao , Bresnehan Sarah M. , Xu Vivian , Wijoyo Stevano J. , Duan Xiaofei , Ng Ken , Hung Andrew , Goebel Erik , El-Osta Assam
Published: May 2024

The Mediterranean diet well known for its beneficial health effects, including mood enhancement, is characterised by the relatively high consumption of extra virgin olive oil (EVOO), which is rich in bioactive phenolic compounds. Over 200 phenolic compounds have been associated with Olea europaea, and of these, only a relatively small fraction have been characterised. Utilising the OliveNetTM library, phenolic compounds were investigated as potential inhibitors of the epigenetic modifier lysine-specific demethylase 1 (LSD1). Furthermore, the compounds were screened for inhibition of the structurally similar monoamine oxidases (MAOs) which are directly implicated in the pathophysiology of depression. Molecular docking highlighted that olive phenolics interact with the active site of LSD1 and MAOs. Protein–peptide docking was also performed to evaluate the interaction of the histone H3 peptide with LSD1, in the presence of ligands bound to the substrate-binding cavity. To validate the in silico studies, the inhibitory activity of phenolic compounds was compared to the clinically approved inhibitor tranylcypromine. Our findings indicate that olive phenolics inhibit LSD1 and the MAOs in vitro. Using a cell culture model system with corticosteroid-stimulated human BJ fibroblast cells, the results demonstrate the attenuation of dexamethasone- and hydrocortisone-induced MAO activity by phenolic compounds. The findings were further corroborated using human embryonic stem cell (hESC)-derived neurons stimulated with all-trans retinoic acid. Overall, the results indicate the inhibition of flavin adenine dinucleotide (FAD)-dependent amine oxidases by olive phenolics. More generally, our findings further support at least a partial mechanism accounting for the antidepressant effects associated with EVOO and the Mediterranean diet.
Recent Advances in the Preparation Methods of Magnesium-Based Hydrogen Storage Materials
Authors: Xu Yaohui , Zhou Yang , Li Yuting , Hao Yechen , Wu Pingkeng , Ding Zhao
Published: May 2024

Magnesium-based hydrogen storage materials have garnered significant attention due to their high hydrogen storage capacity, abundance, and low cost. However, the slow kinetics and high desorption temperature of magnesium hydride hinder its practical application. Various preparation methods have been developed to improve the hydrogen storage properties of magnesium-based materials. This review comprehensively summarizes the recent advances in the preparation methods of magnesium-based hydrogen storage materials, including mechanical ball milling, methanol-wrapped chemical vapor deposition, plasma-assisted ball milling, organic ligand-assisted synthesis, and other emerging methods. The principles, processes, key parameters, and modification strategies of each method are discussed in detail, along with representative research cases. Furthermore, the advantages and disadvantages of different preparation methods are compared and evaluated, and their influence on hydrogen storage properties is analyzed. The practical application potential of these methods is also assessed, considering factors such as hydrogen storage performance, scalability, and cost-effectiveness. Finally, the existing challenges and future research directions in this field are outlined, emphasizing the need for further development of high-performance and cost-effective magnesium-based hydrogen storage materials for clean energy applications. This review provides valuable insights and references for researchers working on the development of advanced magnesium-based hydrogen storage technologies.
Effect of Different Selenium Species on Indole-3-Acetic Acid Activity of Selenium Nanoparticles Producing Strain Bacillus altitudinis LH18
Authors: Li Mengjun , Yang Rui , Li Nana , Zhao Siyang , Wei Shiya , Zhang Sishang , Gong Jue , Song Jie , Kim Jun-Ran , He Yi , Gao Chao , Wang Zhangqian , Cheng Shuiyuan
Published: May 2024

Acting as a growth regulator, Indole-3-acetic acid (IAA) is an important phytohormone that can be produced by several Bacillus species. However, few studies have been published on the comprehensive evaluation of the strains for practical applications and the effects of selenium species on their IAA-producing ability. The present study showed the selenite reduction strain Bacillus altitudinis LH18, which is capable of producing selenium nanoparticles (SeNPs) at a high yield in a cost-effective manner. Bio-SeNPs were systematically characterized by using DLS, zeta potential, SEM, and FTIR. The results showed that these bio-SeNPs were small in particle size, homogeneously dispersed, and highly stable. Significantly, the IAA-producing ability of strain was differently affected under different selenium species. The addition of SeNPs and sodium selenite resulted in IAA contents of 221.7 µg/mL and 91.01 µg/mL, respectively, which were 3.23 and 1.33 times higher than that of the control. This study is the first to examine the influence of various selenium species on the IAA-producing capacity of Bacillus spp., providing a theoretical foundation for the enhancement of the IAA-production potential of microorganisms.
Fructose Reduces Mitochondrial Metabolism and Increases Extracellular BCAA during Insulin Resistance in C2C12 Myotubes
Authors: Cook Norah E. , McGovern Macey R. , Zaman Toheed , Lundin Pamela M. , Vaughan Roger A.
Published: May 2024

Fructose is a commonly consumed monosaccharide implicated in developing several metabolic diseases. Previously, elevated branched-chain amino acids (BCAA) have been correlated with the severity of insulin resistance. Most recently, the effect of fructose consumption on the downregulation of BCAA catabolic enzymes was observed. Thus, this mechanistic study investigated the effects of physiologically attainable levels of fructose, both with and without concurrent insulin resistance, in a myotube model of skeletal muscle. Methods: C2C12 mouse myoblasts were treated with fructose at a concentration of 100 µM (which approximates physiologically attainable concentrations in peripheral circulation) both with and without hyperinsulinemic-mediated insulin resistance. Gene expression was assessed by qRT-PCR, and protein expression was assessed by Western blot. Oxygen consumption rate and extracellular acidification rate were used to assess mitochondrial oxidative and glycolytic metabolism, respectively. Liquid chromatography-mass spectrometry was utilized to analyze leucine, isoleucine and valine concentration values. Results: Fructose significantly reduced peak glycolytic and peak mitochondrial metabolism without altering related gene or protein expression. Similarly, no effect of fructose on BCAA catabolic enzymes was observed; however, fructose treatment resulted in elevated total extracellular BCAA in insulin-resistant cells. Discussion: Collectively, these observations demonstrate that fructose at physiologically attainable levels does not appear to alter insulin sensitivity or BCAA catabolic potential in cultured myotubes. However, fructose may depress peak cell metabolism and BCAA utilization during insulin resistance.
Anti-Vasculogenic, Antioxidant, and Anti-Inflammatory Activities of Sulfated Polysaccharide Derived from Codium tomentosum: Pharmacokinetic Assay
Authors: Lakhrem Marwa , Eleroui Malek , Boujhoud Zakaria , Feki Amal , Dghim Amel , Essayagh Sanah , Hilali Said , Bouhamed Marwa , Kallel Choumous , Deschamps Nathalie , Toffol Bertrand de , Pujo Jean Marc , Badraoui Riadh , Kallel Hatem , Ben Amara Ibtissem
Published: May 2024

The purpose of this paper was to investigate the anti-inflammatory and anti-angiogenic activities of sulfated polysaccharide from C. tomentosum (PCT) using carrageenan (CARR)-induced paw edema in a rat model and anti-vasculogenic activity on a chorioallantoic membrane assay (CAM) model. Based on in vitro tests of anti-radical, total antioxidant, and reducing power activities, PCT presents a real interest via its antioxidant activity and ability to scavenge radical species. The in vivo pharmacological tests suggest that PCT possesses anti-inflammatory action by reducing paw edema and leukocyte migration, maintaining the redox equilibrium, and stabilizing the cellular level of several pro-/antioxidant system markers. It could significantly decrease the malondialdehyde levels and increase superoxide dismutase, glutathione peroxidase, and glutathione activities in local paw edema and erythrocytes during the acute inflammatory reaction of CARR. PCT pretreatment was effective against DNA alterations in the blood lymphocytes of inflamed rats and reduced the hematological alteration by restoring blood parameters to normal levels. The anti-angiogenic activity results revealed that CAM neovascularization, defined as the formation of new vessel numbers and branching patterns, was decreased by PCT in a dose-dependent manner, which supported the in silico bioavailability and pharmacokinetic findings. These results indicated the therapeutic effects of polysaccharides from C. tomentosum and their possible use as anti-proliferative molecules based on their antioxidant, anti-inflammatory, and anti-angiogenic activities.
A Review of Optical Parametric Amplification at the Vulcan Laser Facility
Authors: Buck Samuel , Oliveira Pedro , Angelides Theodoros , Galimberti Marco
Published: May 2024

An overview of Optical Parametric Chirped Pulse Amplification (OPCPA) is given as the basis for the next generation of ultra-intense laser systems (>1×1023 W/cm2). The benefits and drawbacks of OPCPA are discussed to explain the choice behind the decisions for the direction of the Central Laser Facility’s (CLF) upcoming Vulcan 20-20 project. A history of OPCPA use at the CLF is described to surmise the foundation of the confidence in this technology for Vulcan 20-20; a 20 PW user facility for high-intensity plasma physics.
Engineering Implementation of the Acosta Fermentation Method to Obtain Cuban Schnapps with Reduced Concentrations of Higher Alcohols
Authors: Vergel-Alfonso Ariel Alain , Acosta-Martínez Delvis Rafael , Arencibia-Sánchez José Ariel , Rodríguez-Félix Francisco , Reyes-Delgado Yosviel , González-Morales Rosa Virginia , Benítez-Sánchez Rosbel , Gonzalez-Bravo Ana Liz , Tapia-Hernández José Agustín
Published: May 2024

The Acosta method involves rewiring the yeast metabolic pathway to enhance biomass production and prevent a significant increase in higher alcohols during the late stages of fermentation. This study aimed to assess fermentation conditions to achieve Cuban schnapps with reduced concentrations of higher alcohols and replicate the process on an industrial scale. To achieve this, the quality of final sugarcane molasses for fermentation by Saccharomyces cerevisiae (S. cerevisiae) yeast was evaluated. Industrial pre-fermentation and fermentation processes were successfully conducted, followed by laboratory-scale fermentation using the Acosta fermentation method to determine crucial parameters for industrial implementation. Operational parameters for fermentation were identified from the following results: 13.5 °Brix seeding, metabolic pathway inversion of S. cerevisiae at 16 h, and an air concentration of 0.1 m3/min. The resulting Cuban schnapps obtained using this method exhibited a concentration of higher alcohols of 132.5 mg/L, a value that is within the standard parameters, showing a positive impact of this fermentation method on the quality of the schnapps. Scaling up this method to an industrial level, in addition to offering higher quality products and being an economically viable alternative, also stands out for its sustainable and environmentally friendly aspect, and results in higher production of yeast biomass as a byproduct, which can be used for various purposes, such as animal feed. This method constitutes an important update to the schnapps production process as a technological improvement that respects sustainable production trends and the characteristics of the final product.
Experimental Study on Microwave Pyrolysis of Decommissioned Wind Turbine Blades Based on Silicon Carbide Absorbents
Authors: Zhang Dongwang , Song Qiang , Hou Bo , Zhang Man , Teng Da , Zhang Yaning , Bie Rushan , Yang Hairui
Published: May 2024

The rapid expansion of the scale of wind power has led to a wave of efforts to decommission wind turbine blades. The pyrolysis of decommissioned wind turbine blades (DWTBs) is a promising technological solution. Microwave pyrolysis offers the benefits of fast heating rates and uniform heat transfer, making it a widely used method in various heating applications. However, there are few studies on the microwave pyrolysis of DWTBs, and pyrolysis characteristics under different boundary conditions remain unclear. In this paper, we investigate the pyrolysis characteristics of DWTBs by utilizing silicon carbide (SiC) particles as a microwave absorbent. The results demonstrated that, when the microwave heating power increased from 400 W to 600 W, the heating rate and pyrolysis final temperature of the material increased, resulting in a reduction in pyrolysis residual solid yield from 88.30% to 84.40%. At 600 W, pyrolysis gas components included C2H4, CH4, and CO, while the tar components included phenol and toluene. The highest degree of pyrolysis was achieved under the condition of an SiC particle size of 0.85 mm, with better heating performance, and the calorific value of the pyrolysis gas generated was 36.95 MJ/Nm3. The DWTBs did not undergo pyrolysis when SiC was not added. However, when the mass ratio of SiC to DWTBs was 4, the tar yield was 4.7% and the pyrolysis gas yield was 17.0%, resulting in a faster heating rate and the highest degree of pyrolysis. Based on this, an optimal process for the microwave pyrolysis of DWTBs was proposed, providing a reference for its industrial application.
Enhancement of Mine Images through Reflectance Estimation of V Channel Using Retinex Theory
Authors: Wu Changlin , Wang Dandan , Huang Kaifeng , Wu Long
Published: May 2024

The dim lighting and excessive dust in underground mines often result in uneven illumination, blurriness, and loss of detail in surveillance images, which hinders subsequent intelligent image recognition. To address the limitations of the existing image enhancement algorithms in terms of generalization and accuracy, this paper proposes an unsupervised method for enhancing mine images in the hue–saturation–value (HSV) color space. Inspired by the HSV color space, the method first converts RGB images to the HSV space and integrates Retinex theory into the brightness (V channel). Additionally, a random perturbation technique is designed for the brightness. Within the same scene, a U-Net-based reflectance estimation network is constructed by enforcing consistency between the original reflectance and the perturbed reflectance, incorporating ResNeSt blocks and a multi-scale channel pixel attention module to improve accuracy. Finally, an enhanced image is obtained by recombining the original hue (H channel), brightness, and saturation (S channel), and converting back to the RGB space. Importantly, this image enhancement algorithm does not require any normally illuminated images during training. Extensive experiments demonstrated that the proposed method outperformed most existing unsupervised low-light image enhancement methods, qualitatively and quantitatively, achieving a competitive performance comparable to many supervised methods. Specifically, our method achieved the highest PSNR value of 22.18, indicating significant improvements compared to the other methods, and surpassing the second-best WCDM method by 10.3%. In terms of SSIM, our method also performed exceptionally well, achieving a value of 0.807, surpassing all other methods, and improving upon the second-place WCDM method by 19.5%. These results demonstrate that our proposed method significantly enhanced image quality and similarity, far exceeding the performance of the other algorithms.
A Study on the Man-Hour Prediction in Structural Steel Fabrication
Authors: Wei Zhangliang , Li Zhigang , Niu Renzhong , Jin Peilin , Yu Zipeng
Published: May 2024

Longitudinal cutting is the most common process in steel structure manufacturing, and the man-hours of the process provide an important basis for enterprises to generate production schedules. However, currently, the man-hours in factories are mainly estimated by experts, and the accuracy of this method is relatively low. In this study, we propose a system that predicts man-hours with history data in the manufacturing process and that can be applied in practical structural steel fabrication. The system addresses the data inconsistency problem by one-hot encoding and data normalization techniques, Pearson correlation coefficient for feature selection, and the Random Forest Regression (RFR) for prediction. Compared with the other three Machine-Learning (ML) algorithms, the Random Forest algorithm has the best performance. The results demonstrate that the proposed system outperforms the conventional approach and has better forecast accuracy so it is suitable for man-hours prediction.
Enzymic Deactivation in Tender Coconut Water by Supercritical Carbon Dioxide
Authors: Poça D’Água Alice Zinneck , Silva Priscila Alves da , Oliveira Alessandra Lopes de , Petrus Rodrigo Rodrigues
Published: May 2024

Polyphenol oxidase (PPO) and peroxidase (POD) are target enzymes in the processing of tender coconut water (TCW). This study primarily evaluated the combined effect of supercritical carbon dioxide (SC-CO2) and mild temperatures on the PPO and POD deactivation of TCW. A factorial design was performed to investigate the effect of temperature (in the range of 35 to 85 °C), pressure (75 to 370 bar), and holding time (13 to 47 min) on the enzymic deactivation, physicochemical parameters, and color of the TCW. The percentages of reduction in PPO activity ranged from 3.7 to 100%, and POD ranged from 43.4 to 100%. The pH values of the freshly extracted and processed TCW were 5.09 and 4.90, and the soluble solids content were 5.5 and 5.4 °Brix, respectively. The holding time (t) had a significant effect (p ≤ 0.1) on the total color variation. As for the reduction of PPO activity, the temperature (T) and the interaction between pressure (P) and t had a significant effect. None of variables (P, T, or t) affected (p > 0.1) the POD reduction, pH, and soluble solids variation. The combination of SC-CO2 and mild temperatures is a promising intervention in the enzymic stabilization of TCW.
Samuel Taylor Coleridge (1772–1834) and Nature’s Divine Participation: Reverence for the One and the Many in the Scientific and Poetic Imagination
Authors: Smoker James Gordon
Published: May 2024

This paper considers the influence of Platonism and Neoplatonism on the British Romantic poet and theologian Samuel Taylor Coleridge (1772–1834) and how they informed his reverence for nature. Coleridge did not see this reverence as merely personal but sought to call an increasingly materialist and industrializing England back to a Platonic social imagination that would better revere the created world. First, I will establish the influence of Platonic and Neoplatonic thought on his philosophical system. Second, I will show how the relationship between Platonic philosophy and scientific pursuit is worked out in Coleridge’s “Essays on Method”, wherein he attempts to synthesize Plato with Frances Bacon and poetry with science and proposes a scientific method that reverences all of creation in its individuality and participation within a spiritual whole. Third, I will briefly explore two of Coleridge’s most famous poems, The Rime of the Ancient Mariner and Christabel, as both show the destructive potential of a lack of reverence for the mysterious natural order. These poems may be read as case studies, experimental worlds where refusal to recognize nature’s order and participation with the divine results in the coming apart of those worlds and the self’s relation to them.
An Improved Gross Primary Production Model Considering Atmospheric CO2 Fertilization: The Qinghai–Tibet Plateau as a Case Study
Authors: Li Jie , Jia Kun , Zhao Linlin , Tao Guofeng , Zhao Wenwu , Liu Yanxu , Yao Yunjun , Zhang Xiaotong
Published: May 2024

Involving the effect of atmospheric CO2 fertilization is effective for improving the accuracy of estimating gross primary production (GPP) using light use efficiency (LUE) models. However, the widely used LUE model, the remote sensing-driven Carnegie–Ames–Stanford Approach (CASA) model, scarcely considers the effects of atmospheric CO2 fertilization, which causes GPP estimation uncertainties. Therefore, this study proposed an improved method for estimating GPP by integrating the atmospheric CO2 concentration into the CASA model and generated a long time series GPP dataset with high precision for the Qinghai–Tibet Plateau. The CASA model was improved by considering the impact of atmospheric CO2 on vegetation productivity and discerning variations in CO2 gradients within the canopy and leaves. A 500 m monthly GPP dataset for the Qinghai–Tibet Plateau from 2003 to 2020 was generated. The results showed that the improved GPP estimation model achieved better performances on estimating GPP (R2 = 0.68, RMSE = 406 g C/m2/year) than the original model (R2 = 0.67, RMSE = 499.32 g C/m2/year) and MODIS GPP products (R2 = 0.49, RMSE = 522.56 g C/m2/year). The GPP on the Qinghai–Tibet Plateau increased significantly with the increase in atmospheric CO2 concentration and the gradual accumulation of dry matter. The improved method can also be used for other regions and the generated GPP dataset is valuable for further understanding the ecosystem carbon cycles on the Qinghai–Tibet Plateau.
An EOF-Based Global Plasmaspheric Electron Content Model and Its Potential Role in Vertical-Slant TEC Conversion
Authors: Long Fengyang , Gao Chengfa , Dong Yanfeng , Xu Zhenhao
Published: May 2024

Topside total electron content (TEC) data measured by COSMIC/FORMAT-3 during 2008 and 2016 were used to analyze and model the global plasmaspheric electron content (PEC) above 800 km with the help of the empirical orthogonal function (EOF) analysis method, and the potential role of the proposed PEC model in helping Global Navigation Satellite System (GNSS) users derive accurate slant TEC (STEC) from existing high-precision vertical TEC (VTEC) products was validated. A uniform gridded PEC dataset was first obtained using the spherical harmonic regression method, and then, it was decomposed into EOF basis modes. The first four major EOF modes contributed more than 99% of the total variance. They captured the pronounced latitudinal gradient, longitudinal differences, hemispherical differences, diurnal and seasonal variations, and the solar activity dependency of global PEC. A second-layer EOF decomposition was conducted for the spatial pattern and amplitude coefficients of the first-layer EOF modes, and an empirical PEC model was constructed by fitting the second-layer basis functions related to latitude, longitude, local time, season, and solar flux. The PEC model was designed to be driven by whether solar proxy or parameters derived from the Klobuchar model meet the real-time requirements. The validation of the results demonstrated that the proposed PEC model could accurately simulate the major spatiotemporal patterns of global PEC, with a root-mean-square (RMS) error of 1.53 and 2.24 TECU, improvements of 40.70% and 51.74% compared with NeQuick2 model in 2009 and 2014, respectively. Finally, the proposed PEC model was applied to conduct a vertical-slant TEC conversion experiment with high-precision Global Ionospheric Maps (GIMs) and dual-frequency carrier phase observables of more than 400 globally distributed GNSS sites. The results of the differential STEC (dSTEC) analysis demonstrated the effectiveness of the proposed PEC model in aiding precise vertical-slant TEC conversion. It improved by 18.52% in dSTEC RMS on a global scale and performed better in 90.20% of the testing days compared with the commonly used single-layer mapping function.
Three-Dimensional Structure of Mesoscale Eddies and Their Impact on Diapycnal Mixing in a Standing Meander of the Antarctic Circumpolar Current
Authors: Bao Yanan , Ma Chao , Luo Yiyong , Phillips Helen Elizabeth , Cyriac Ajitha
Published: May 2024

Mesoscale eddies are known to enhance diapycnal mixing in the ocean, yet direct observation of this effect remains a significant challenge, especially in the robust Antarctic Circumpolar Current (ACC). To quantify the diapycnal mixing induced by mesoscale eddies in the standing meander of the ACC, satellite altimeter and Argo profile data were combined to composite eddies, where the 1.6 m dynamic height contour was used for the first time instead of the climatological Northern Sub-Antarctic Front (SAFN) to define the northern boundary of the ACC to eliminate the influence of frontal shift. The 3D structures of the composite anticyclonic/cyclonic eddy (CAE/CCE) were obtained. Both the CAE and CCE were similar in shape to Taylor columns, from sea surface to the neutral surface of 28.085 kgm−3 (1689 ± 66 dbar) for the CAE, and from sea surface to 28.01 kgm−3 (1491 ± 202 dbar) for the CCE. On the same neutral surface, the diffusivity (κ) inside the CCE was one to two orders of magnitude higher than that inside the CAE. Vertically, the maximum influence depth of the CCE on κ reached 1200 dbar, while for the CAE, it reached 800 dbar, where κ exceeded O(10−4) m2s−1, and κ gradually decreased from these depths downwards.
Validation of Red-Edge Vegetation Indices in Vegetation Classification in Tropical Monsoon Region—A Case Study in Wenchang, Hainan, China
Authors: Liu Miao , Zhan Yulin , Li Juan , Kang Yupeng , Sun Xiuling , Gu Xingfa , Wei Xiangqin , Wang Chunmei , Li Lingling , Gao Hailiang , Yang Jian
Published: May 2024

Vegetation classification has always been the focus of remote sensing applications, especially for tropical regions with fragmented terrain, cloudy and rainy climates, and dense vegetation. How to effectively classify vegetation in tropical regions by using multi-spectral remote sensing with high resolution and red-edge spectrum needs to be further verified. Based on the experiment in Wenchang, Hainan, China, which is located in the tropical monsoon region, and combined with the ZY-1 02D 2.5 m fused images in January, March, July, and August, this paper discusses whether NDVI and four red-edge vegetation indices (VIs), CIre, NDVIre, MCARI, and TCARI, can promote vegetation classification and reduce the saturation. The results show that the schemes with the highest classification accuracies in all phases are those in which the red-edge VIs are involved, which suggests that the red-edge VIs can effectively contribute to the classification of vegetation. The maximum accuracy of the single phase is 86%, and the combined accuracy of the four phases can be improved to 92%. It has also been found that CIre and NDVIre do not reach saturation as easily as NDVI and MCARI in July and August, and their ability to enhance the separability between different vegetation types is superior to that of TCARI. In general, red-edge VIs can effectively promote vegetation classification in tropical monsoon regions, and red-edge VIs, such as CIre and NDVIre, have an anti-saturation performance, which can slow down the confusion between different vegetation types due to saturation.
Utilizing the Sentinel-6 Michael Freilich Equivalent Number of Looks for Sea State Applications
Authors: Recchia Lisa , Guccione Pietro , Moreau Thomas , Donlon Craig
Published: May 2024

Sentinel-6 Michael Freilich (S6-MF) is the first altimeter operating in a continuous high-rate pulse mode, i.e., interleaved mode. This ensures the generation of low-resolution (LR) mode measurements with a pulse repetition frequency (PRF) of ∼9 kHz (variable along the orbit) for the Ku-band as well as the processing of high-resolution (HR) echoes on ground. This operating mode provides an elevated number of highly correlated single looks with respect to the fewer number, weakly correlated echoes of Jason-3 altimeter. A theoretical model is exploited to envisage the correlation properties of S6-MF pulse limited waveform echoes for different sea-state conditions; after that, the model is validated by comparison with the equivalent number of looks (ENL) empirically estimated from real data. The existence of a significant dependence of the statistical properties on the range is verified, and its impact on the precision and on the accuracy in the estimation of the geophysical parameters is assessed in case of the 9 kHz PRF of S6-MF. By applying pulse decimation before the multilook processing, an investigation on new processing techniques is performed, aimed at exploiting the higher ENL in S6-MF low-resolution mode waveforms. It is shown that a bias of less than 0.4 cm is found for SSH and about 1.5 cm for SWH at SWH = 2 m when the decimated waveforms processing is compared with full high-PRF processing.
A Dual-Band Polarization-Insensitive Frequency Selective Surface for Electromagnetic Shielding Applications
Authors: Idrees Muhammad , He Yejun , Ullah Shahid , Wong Sai-Wai
Published: May 2024

This paper presents a novel polarization-insensitive dual-band frequency-selective surface (FSS)-based electromagnetic shield. The miniaturized FSS unit cell consists of a modified Jerusalem crossed loop and a corner-modified square loop. These FSS elements are arranged in a co-planner configuration over a single-layer Rogers 5880 substrate and simultaneously offer effective shielding in the X- and Ku-bands. Moreover, the FSS manifests polarization-independent and angularly stable band-reject filter characteristics over various oblique angles of incidence for both the TE and TM polarizations with virtuous attenuation at both resonances. In addition, the FSS structure is modelled into an equivalent lumped circuit to better analyze the phenomenon of EM wave suppression. A finite prototype of FSS is fabricated and tested. The simulated and measured results are in good agreement, thus making it a potential candidate for RF shielding/isolation applications.
A Robotic Solution for Precision Smoothing and Roughening of Precast Concrete Surfaces: Design and Experimental Validation
Authors: Gang Rui , Duan Zhongxing , Wang Lin , Nan Lemeng , Song Jintao
Published: May 2024

Prefabricated construction has pioneered a new model in the construction industry, where prefabricated component modules are produced in factories and assembled on-site by construction workers, resulting in a highly efficient and convenient production process. Within the construction industry value chain, the smoothing and roughening of precast concrete components are critical processes. Currently, these tasks are predominantly performed manually, often failing to achieve the desired level of precision. This paper designs and develops a robotic system for smoothing and roughening precast concrete surfaces, along with a multi-degree-of-freedom integrated intelligent end-effector for smoothing and roughening. Point-to-point path planning methods are employed to achieve comprehensive path planning for both smoothing and roughening, enhancing the diversity of textural patterns using B-spline curves. In the presence of embedded obstacles, a biologically inspired neural network method is introduced for precise smoothing operation planning, and the A* algorithm is incorporated to enable the robot’s escape from dead zones. Experimental validation further confirms the feasibility of the entire system and the accuracy of the machining path planning methods. The experimental results demonstrate that the proposed system meets the precision requirements for smoothing and offers diversity in roughening, affirming its practicality in the precast concrete process and expanding the automation level and application scenarios of robots in the field of prefabricated construction.
Instability Compensation of Recording Interferometer in Phase-Sensitive OTDR
Authors: Stepanov Konstantin V. , Zhirnov Andrey A. , Gritsenko Tatyana V. , Khan Roman I. , Koshelev Kirill I. , Svelto Cesare , Pnev Alexey B.
Published: May 2024

In the paper, a new method of phase measurement error suppression in a phase-sensitive optical time domain reflectometer is proposed and experimentally proved. The main causes of phase measurement errors are identified and considered, such as the influence of the recording interferometer instabilities and laser wavelength instability, which can cause inaccuracies in phase unwrapping. The use of a Mach–Zender interferometer made by 3 × 3 fiber couplers is proposed and tested to provide insensitivity to the recording interferometer and laser source instabilities. It is shown that using all three available photodetectors of the interferometer, instead of just one pair, achieves significantly better accuracy in the phase unwrapping. A novel compensation scheme for accurate phase measurements in a phase-sensitive optical time domain reflectometer is proposed, and a comparison of the measurement signals with or without such compensation is shown and discussed. The proposed method, using three photodetectors, allows for very good compensation of the phase measurement errors arising from common-mode noise from the interferometer and laser source, providing a significant improvement in signal detection. In addition, the method allows the tracking of slow temperature changes in the monitored fiber/object, which is not obtainable when using a simple low-pass filter for phase unwrapping error reduction, as is customary in several systems of this kind.
Vibration Signal Noise-Reduction Method of Slewing Bearings Based on the Hybrid Reinforcement Chameleon Swarm Algorithm, Variate Mode Decomposition, and Wavelet Threshold (HRCSA-VMD-WT) Integrated Model
Authors: Li Zhuang , Yao Xingtian , Zhang Cheng , Qian Yongming , Zhang Yue
Published: May 2024

To enhance fault detection in slewing bearing vibration signals, an advanced noise-reduction model, HRCSA-VMD-WT, is designed for effective signal noise elimination. This model innovates by refining the Chameleon Swarm Algorithm (CSA) into a more potent Hybrid Reinforcement CSA (HRCSA), incorporating strategies from Chaotic Reverse Learning (CRL), the Whale Optimization Algorithm’s (WOA) bubble-net hunting, and the greedy strategy with the Cauchy mutation to diversify the initial population, accelerate convergence, and prevent local optimum entrapment. Furthermore, by optimizing Variate Mode Decomposition (VMD) input parameters with HRCSA, Intrinsic Mode Function (IMF) components are extracted and categorized into noisy and pure signals using cosine similarity. Subsequently, the Wavelet Threshold (WT) denoising targets the noisy IMFs before reconstructing the vibration signal from purified IMFs, achieving significant noise reduction. Comparative experiments demonstrate HRCSA’s superiority over Particle Swarm Optimization (PSO), WOA, and Gray Wolf Optimization (GWO) regarding convergence speed and precision. Notably, HRCSA-VMD-WT increases the Signal-to-Noise Ratio (SNR) by a minimum of 74.9% and reduces the Root Mean Square Error (RMSE) by at least 41.2% when compared to both CSA-VMD-WT and Empirical Mode Decomposition with Wavelet Transform (EMD-WT). This study improves fault detection accuracy and efficiency in vibration signals and offers a dependable and effective diagnostic solution for slewing bearing maintenance.
NMR in Battery Anode Slurries with a V-Shaped Sensor
Authors: Schmid Eric , Kontschak Louis , Nirschl Hermann , Guthausen Gisela
Published: May 2024

Inline analytics in industrial processes reduce operating costs and production rejection. Dedicated sensors enable inline process monitoring and control tailored to the application of interest. Nuclear Magnetic Resonance is a well-known analytical technique but needs adapting for low-cost, reliable and robust process monitoring. A V-shaped low-field NMR sensor was developed for inline process monitoring and allows non-destructive and non-invasive measurements of materials, for example in a pipe. In this paper, the industrial application is specifically devoted to the quality control of anode slurries in battery production. The characterization of anode slurries was performed with the sensor to determine chemical composition and detect gas inclusions. Additionally, flow properties play an important role in continuous production processes. Therefore, the in- and outflow effects were investigated with the V-shaped NMR sensor as a basis for the future determination of slurry flow fields.
Weakly Supervised Pose Estimation of Surgical Instrument from a Single Endoscopic Image
Authors: Hu Lihua , Feng Shida , Wang Bo
Published: May 2024

Instrument pose estimation is a key demand in computer-aided surgery, and its main challenges lie in two aspects: Firstly, the difficulty of obtaining stable corresponding image feature points due to the instruments’ high refraction and complicated background, and secondly, the lack of labeled pose data. This study aims to tackle the pose estimation problem of surgical instruments in the current endoscope system using a single endoscopic image. More specifically, a weakly supervised method based on the instrument’s image segmentation contour is proposed, with the effective assistance of synthesized endoscopic images. Our method consists of the following three modules: a segmentation module to automatically detect the instrument in the input image, followed by a point inference module to predict the image locations of the implicit feature points of the instrument, and a point back-propagatable Perspective-n-Point module to estimate the pose from the tentative 2D–3D corresponding points. To alleviate the over-reliance on point correspondence accuracy, the local errors of feature point matching and the global inconsistency of the corresponding contours are simultaneously minimized. Our proposed method is validated with both real and synthetic images in comparison with the current state-of-the-art methods.
Vibration Suppression of Graphene Reinforced Laminates Using Shunted Piezoelectric Systems and Machine Learning
Authors: Drosopoulos Georgios , Foutsitzi Georgia , Daraki Maria-Styliani , Stavroulakis Georgios E.
Published: May 2024

The implementation of a machine learning approach to predict vibration suppression, as derived from nanocomposite laminates with piezoelectric shunted systems, is studied in this article. Datasets providing the vibration response and vibration attenuation are developed using parametric finite element simulations. A graphene/fibre-reinforced laminate cantilever beam is used in those simulations. Parameters, including the graphene and fibre reinforcements content, as well as the fibre angles, are among the inputs. Output is the vibration suppression achieved by the piezoelectric shunted system. Artificial Neural Networks are trained and tested using the derived datasets. The proposed methodology can be used for a fast and accurate prediction of the vibration response of nanocomposite laminates.
Measuring and Assessing the Level of Living Conditions and Quality of Life in Smart Sustainable Cities in Poland—Framework for Evaluation Based on MCDM Methods
Authors: Brodny Jarosław , Tutak Magdalena , Bindzár Peter
Published: May 2024

The increasing degree of urbanization of the world community is creating several multidimensional challenges for modern cities in terms of the need to provide adequate living and working conditions for their residents. An opportunity to ensure optimal conditions and quality of life are smart sustainable cities, which integrate various resources for their sustainable development using modern and smart technological solutions. This paper addresses these issues by presenting the results of a study of the level and quality of living conditions in the 29 largest cities in Poland, an EU member state. This study used 35 indicators characterizing the six main areas of activity of the cities to assess the living conditions and quality of life in these cities. To achieve this purpose, an original research methodology was developed, in which the EDAS and WASPAS methods and the Laplace criterion were applied. The application of a multi-criteria approach to the issue under study made it possible to determine the levels of quality of life and living conditions in the studied cities for each dimension, as well as the final index of this assessment (Smart Sustainable Cities Assessment Scores). On this basis, a ranking of these cities was made. In addition, relationships between living conditions and quality of life and the levels of wealth and population of the cities were also assessed. The results showed a wide variation in the levels of living conditions and quality of life in the cities studied, as well as their independence from geographic location. Cities with higher GDP levels that were investing in innovation and knowledge-based development fared much better.
Sex Differences in Athletic Performance Response to the Imagery and Mental Toughness of Elite Middle- and Long-Distance Runners
Authors: Yarayan Yunus Emre , Solmaz Serdar , Aslan Mehdi , Batrakoulis Alexios , Al-Mhanna Sameer Badri , Keskin Kadir
Published: May 2024

This study aimed to determine whether there is a difference between the levels of imagery and mental toughness in the context of sports performance in male and female athletes. A total of 344 track and field athletes, 205 male (59.6%, 23.3 ± 4.0 years) and 139 female (40.4%, 22.9 ± 4.0 years), voluntarily participated in the study. Imagery Inventory and Mental Toughness Inventory in Sport were used as data collection tools in the study. In the evaluation of athletic performance, athletes were asked about their ranks in the years 2020, 2021, and 2022 and were categorized according to the scoring tables specified by the International Association of Athletics Federation. A MANOVA analysis was used to determine whether there was a difference between low (−2% to +5%), medium (+6 to +11%), and high (+12 to +17%) performers among male and female athletes, and a post hoc analysis was used to determine the source of the difference. According to the present findings, there was no significant difference between the imagery and mental toughness levels of athletes with high, medium, and low performance among male athletes. On the contrary, a significant difference was detected between the imagery and mental toughness levels of female athletes with medium and high performances, showing that athletes in the high-performance range had higher levels of imagery (Eta2 = 8) and mental toughness (Eta2 = 10) than athletes in the medium- and low-performance ranges. The findings of this study show that imagery and emotional intelligence are important factors for sports performance. In this context, coaches and sports psychologists can include these parameters in their training programs to achieve the optimal performance range.
Differences and Relationship between Body Composition and Motor Coordination in Children Aged 6–7 Years
Authors: Pelemiš Vladan , Pavlović Slobodan , Mandić Danimir , Radaković Milan , Branković Dragan , Živanović Vladimir , Milić Zoran , Bajrić Senad
Published: May 2024

Background: The primary goal of this study was to investigate the relationship between body composition and motor coordination performance, and the secondary goal was to determine sex differences in body composition and motor coordination of preschool children. Methods: Forty-eight children (23 boys and 25 girls) underwent assessments for body composition and motor coordination using the Köperkoordinationstest für Kinder (KTK). Results: Linear regression analysis revealed significant associations between body composition and motor coordination in boys (p < 0.05) but not in girls. In boys, Body height (p = 0.01), Total muscle mass (p = 0.03), Total fat (p = 0.03), and Total water (p = 0.02) show statistically significant influence on single-leg jumps. Similar results were obtained for lateral jumps where there was a statistically significant influence of Body height (p = 0.01), Total muscle mass (p = 0.03), and Total water (p = 0.02). Interestingly, predictive variables showed no statistically significant influence on KTK overall score in boys (p = 0.42) nor in girls (p = 0.90). Conclusions: The predictive system of morphological variables demonstrated significance only among boys in this age group and sample. Girls outperformed boys due to early maturation, resulting in better average KTK scores.
A Novel Self-Adaptive Deformable Convolution-Based U-Net for Low-Light Image Denoising
Authors: Wang Hua , Cao Jianzhong , Guo Huinan , Li Cheng
Published: May 2024

Capturing images under extremely low-light conditions usually suffers from various types of noise due to the limited photon and low signal-to-noise ratio (SNR), which makes low-light denoising a challenging task in the field of imaging technology. Nevertheless, existing methods primarily focus on investigating the precise modeling of real noise distributions while neglecting improvements in the noise modeling capabilities of learning models. To address this situation, a novel self-adaptive deformable-convolution-based U-Net (SD-UNet) model is proposed in this paper. Firstly, deformable convolution is employed to tackle noise patterns with different geometries, thus extracting more reliable noise representations. After that, a self-adaptive learning block is proposed to enable the network to automatically select appropriate learning branches for noise with different scales. Finally, a novel structural loss function is leveraged to evaluate the difference between denoised and clean images. The experimental results on multiple public datasets validate the effectiveness of the proposed method.