bluuebunny/crossref_metadata_2025 huggingface dataset:
A Two-Layer SD-ANN-CA Model Framework for Multi-Typed Land Use and Land Cover Change Prediction under Constraints: Case Study of Ya’an City Area, Western China
Authors: Zhao Jingyao , Zhu Xiaofan , Zhang Fan , Gao Lei
Published: May 2024

Land use and land cover change (LUCC) prediction of cities in Western China requires higher accuracy in quantitative demand and spatial layout because of complex challenges in balancing relationships between urban constructions and ecological developments. Considering city-level areas and various types of land use and land cover, existing LUCC models without constraint or with only loose demand constraints were impractical in providing evidence of high accuracy and high-resolution predictions in areas facing fierce land competition. In this study, we proposed a two-layer SD-ANN-CA model to simulate and explore the LUCC trend and layout predictions for 2018, 2028, and 2038 in Ya’an City, Western China. The two-layer structure with an upper layer of the SD model and a lower layer of the ANN-CA model, as well as the advantages of all three methods of system dynamics (SD), artificial neural network (ANN), and cellular automata (CA), have allowed us to consider the macro-level demand constraints, meso-level driving factors constraints, and the micro-level spatial constraints into a unified model framework. The simulation results of the year 2018 have shown significant improvement in the accuracy of the ANN-CA model constructed in our earlier work, especially in types of forest land (error-accuracy: 0.08%), grassland (error-accuracy: 0.23%), and construction land (error-accuracy: 0.18%). The layout predictions of all six types of land use in 2028 and 2038 are then carried out to provide visual evidence support, which may improve the efficiency of planning and policy-making processes. Our work may also provide insights into new ways to combine quantitative methods into spatial methods in constructing city-level or even regional-level LUCC models with high resolution.
Urban Texture Identification and Characteristic Analysis Based on Percolation Theory—A Case Study of the Second Ring Road Area in Wuhan City
Authors: Yang Shen , Zhan Qingming , Zhang Kaili , Paryzat Hurex
Published: May 2024

The urban texture is the physical manifestation of the urban form’s evolution. In the rapid process of urbanization, protecting and reshaping the urban texture has become an essential means to sustain the overall form and vitality of cities. Previous studies in this field have primarily relied on image analysis or typological methods, lacking a quantitative approach to identify and analyze the urban texture on a large scale. Moreover, the hierarchical structure and networked organization of the urban texture are gradually being elucidated and emphasized. This study takes a complex network perspective and applies percolation theory to identify and analyze the urban texture. The hierarchical evolutionary characteristics of the urban fabric and the underlying mechanisms driving the scale-dependent differences are analyzed, and the toughness of the urban texture is evaluated based on hierarchical connections. The research findings reveal the key scale in the cross-scale evolution of urban textures, with variations in scale dependence and hierarchical evolution characteristics among different types of urban texture. The traditional urban texture displays sensitivity to scale changes, maintaining its integrity and internal connectivity at small scales. On the other hand, the texture characteristics of modern and contemporary urban areas are only discernible at larger scales. The emergence of large-scale texture clusters at specific scale levels can be explained using multiple index systems. This study has reference significance for the preservation and renewal of the urban fabric in urban renewal processes.
Defense Pathways of Wheat Plants Inoculated with Zymoseptoria tritici under NaCl Stress Conditions: An Overview
Authors: Baran Behzat , Ölmez Fatih , Çapa Beritan , Dikilitas Murat
Published: May 2024

Due to being sessile, plants develop a broad range of defense pathways when they face abiotic or biotic stress factors. Although plants are subjected to more than one type of stress at a time in nature, the combined effects of either multiple stresses of one kind (abiotic or biotic) or more kinds (abiotic and biotic) have now been realized in agricultural lands due to increases in global warming and environmental pollution, along with population increases. Soil-borne pathogens, or pathogens infecting aerial parts, can have devastating effects on plants when combined with other stressors. Obtaining yields or crops from sensitive or moderately resistant plants could be impossible, and it could be very difficult from resistant plants. The mechanisms of combined stress in many plants have previously been studied and elucidated. Recent studies proposed new defense pathways and mechanisms through signaling cascades. In light of these mechanisms, it is now time to develop appropriate strategies for crop protection under multiple stress conditions. This may involve using disease-resistant or stress-tolerant plant varieties, implementing proper irrigation and drainage practices, and improving soil quality. However, generation of both stress-tolerant and disease-resistant crop plants is of crucial importance. The establishment of a database and understanding of the defense mechanisms under combined stress conditions would be meaningful for the development of resistant and tolerant plants. It is clear that leaf pathogens show great tolerance to salinity stress and result in pathogenicity in crop plants. We noticed that regulation of the stomata through biochemical applications and some effort with the upregulation of the minor gene expressions indirectly involved with the defense mechanisms could be a great way to increase the defense metabolites without interfering with quality parameters. In this review, we selected wheat as a model plant and Zymoseptoria tritici as a model leaf pathogen to evaluate the defense mechanisms under saline conditions through physiological, biochemical, and molecular pathways and suggested various ways to generate tolerant and resistant cereal plants.
Keratin/Copper Complex Electrospun Nanofibers for Antibacterial Treatments: Property Investigation and In Vitro Response
Authors: Tummino Maria Laura , Cruz-Maya Iriczalli , Varesano Alessio , Vineis Claudia , Guarino Vincenzo
Published: May 2024

The frontiers of antibacterial materials in the biomedical field are constantly evolving since infectious diseases are a continuous threat to human health. In this work, waste-wool-derived keratin electrospun nanofibers were blended with copper by an optimized impregnation procedure to fabricate antibacterial membranes with intrinsic biological activity, excellent degradability and good cytocompatibility. The keratin/copper complex electrospun nanofibers were multi-analytically characterized and the main differences in their physical–chemical features were related to the crosslinking effect caused by Cu2+. Indeed, copper ions modified the thermal profiles, improving the thermal stability (evaluated by differential scanning calorimetry and thermogravimetry), and changed the infrared vibrational features (determined by infrared spectroscopy) and the chemical composition (studied by an X-ray energy-dispersive spectroscopy probe and optical emission spectrometry). The copper impregnation process also affected the morphology, leading to partial nanofiber swelling, as evidenced by scanning electron microscopy analyses. Then, the membranes were successfully tested as antibacterial materials against gram-negative bacteria, Escherichia coli. Regarding cytocompatibility, in vitro assays performed with L929 cells showed good levels of cell adhesion and proliferation (XTT assay), and no significant cytotoxic effect, in comparison to bare keratin nanofibers. Given these results, the material described in this work can be suitable for use as antibiotic-free fibers for skin wound dressing or membranes for guided tissue regeneration.
Influence of Solute Drag Effect and Interphase Precipitation of Nb on Ferrite Transformation
Authors: Cai Yiming , Wei Ran , Jin Duoduo , Wang Honghong , Wan Xiangliang , Hu Chengyang , Wu Kaiming
Published: May 2024

The significant impact of Nb on ferrite transformation, both in terms of solute drag effect (SDE) and interphase precipitation, was investigated quantitatively. Ferrite transformation kinetics were characterized using thermal expansion experiments and theoretical calculations. The microstructures were characterized using high−temperature confocal laser scanning microscopy (CLSM), a field−emission scanning electron microscope (FESEM), and a transmission electron microscope (TEM). Under a higher driving force, interphase precipitations were observed in the sample with a higher Nb content. A three−dimensional (3D) reconstruction method was used to convert the two−dimensional (2D) image of interphase precipitation into a three−dimensional model for a more typical view. The SDE and interphase precipitation had opposite effects on the kinetics of ferrite transformation. A lower Nb content showed a strong contribution to the SDE, which delayed ferrite transformation. A higher concentration of Nb was expected to enhance the SDE, but the inhibition effect was eliminated by the interphase precipitation of NbC during interfacial migration. Both the experimental results and theoretical calculations confirmed this phenomenon.
Viscoelastic Analysis of Asphalt Concrete with a Digitally Reconstructed Microstructure
Authors: Klimczak Marek
Published: May 2024

In the finite element analysis of asphalt concrete (AC), it is nowadays common to incorporate the information from the underlying scales to study the overall response of this material. Heterogeneity observed at the asphalt mixture scale is analyzed in this paper. Reliable finite element analysis (FEA) of asphalt concrete comprises a set of complex issues. The two main aspects of the asphalt concrete FEA discussed in this study are: (1) digital reconstruction of the asphalt pavement microstructure using processing of the high-quality images; and (2) FEA of the asphalt concrete idealized samples accounting for the viscoelastic material model. Reconstruction of the asphalt concrete microstructure is performed using a sequence of image processing operations (binarization, removing holes, filtering, segmentation and boundaries detection). Geometry of the inclusions (aggregate) are additionally simplified in a controlled mode to reduce the numerical cost of the analysis. As is demonstrated in the study, the introduced geometry simplifications are justified. Computational cost reduction exceeds of several orders of magnitude additional modeling error occurring due to the applied simplification technique. Viscoelastic finite element analysis of the AC identified microstructure is performed using the Burgers material model. The analysis algorithm is briefly described with a particular focus on the computational efficiency aspects. In order to illustrate the proposed approach, a set of 2D problems is solved. Numerical results confirm both the effectiveness of the self-developed code and the applicability of the Burgers model to the analyzed class of AC analysis problems. Further research directions are also described to highlight the potential benefits of the developed approach to numerical modeling of asphalt concrete.
Photoluminescence Spectra Correlations with Structural Distortion in Eu3+- and Ce3+-Doped Y3Al5-2x(Mg,Ge)xO12 (x = 0, 1, 2) Garnet Phosphors
Authors: Ha Heonji , Yang Sungjun , Park Sangmoon
Published: May 2024

Garnet-type materials consisting of Y3Al5-2x(Mg,Ge)xO12 (x = 0, 1, 2), combined with Eu3+ or Ce3+ activator ions, were prepared by a solid-state method to determine the structural and optical correlations. The structure of Y3Al5-2x(Mg,Ge)xO12 (x = 1, 2) was determined to be a cubic unit cell (Ia-3d), which contains an 8-coordinated Y3+ site with octahedral (Mg,Al)O6 and tetrahedral (Al,Ge)O4 polyhedra, using synchrotron powder X-ray diffraction. When Eu3+ or Ce3+ ions were substituted for the Y3+ site in the Y3Al5-2x(Mg,Ge)xO12 host lattices, the emission spectra showed a decrease in the magnetic dipole f-f Eu3+ transition and a redshift of the d-f Ce3+ transition, related to centrosymmetry and crystal field splitting, respectively. These changes were monitored according to the increase in Mg2+ and Ge4+ contents. The dodecahedral and octahedral edge sharing was identified as a key distortion factor for the structure-correlated luminescence in the Eu3+/Ce3+-doped Y3Al5-2x(Mg,Ge)xO12 garnet phosphors.
Cluster-Assisted Mesoplasma Chemical Vapor Deposition for Fast Epitaxial Growth of SiGe/Si Heterostructures: A Molecular Dynamics Simulation Study
Authors: Wang Wen-bo , Li Wenfang , Ohta Ryoshi , Kambara Makoto
Published: May 2024

Co-condensation of mixed SiGe nanoclusters and impingement of SiGe nanoclusters on a Si substrate were applied using molecular dynamics (MD) simulation in this study to mimic the fast epitaxial growth of SiGe/Si heterostructures under mesoplasma chemical vapor deposition (CVD) conditions. The condensation dynamics and properties of the SiGe nanoclusters during the simulations were investigated first, and then the impingement of transient SiGe nanoclusters on both Si smooth and trench substrate surfaces under varying conditions was studied theoretically. The results show that the mixed nanoclusters as precursors demonstrate potential for enhancing epitaxial SiGe film growth at a high growth rate, owing to their loosely bound atomic structures and high mobility on the substrate surface. By varying cluster sizes and substrate temperatures, this study also reveals that smaller clusters and higher substrate temperatures contribute to faster structural ordering and smoother surface morphologies. Furthermore, the formed layers display a consistent SiGe composition, closely aligning with nominal values, and the cluster-assisted deposition method achieves the epitaxial bridging of heterostructures during cluster impingement, highlighting its additional distinctive characteristics. The implications of this work make it clear that the mechanism of fast alloyed epitaxial film growth by cluster-assisted mesoplasma CVD is critical for extending it as a versatile platform for synthesizing various epitaxial films.
An Experimental Parametric Optimisation for Laser Engraving and Texturing to Integrate Zirconia Ceramic Blocks into Stainless Steel Cutlery: A State-of-the-Art Aesthetically Improved Perspective
Authors: Richhariya Vipin , Miranda Georgina , Silva Filipe Samuel
Published: May 2024

Cutlery and flatware designs are an everchanging phenomenon of the manufacturing industry. Worldwide hospitality businesses demand perpetual evolution in terms of aesthetics, designs, patterns, colours, and materials due to customers’ demands, modernisation, and fierce competition. To thrive in this competitive market, modern fabrication techniques must be flexible, adoptive, fast, and cost effective. For decades, static designs and trademark patterns were achieved through moulds, limiting production to a single cutlery type per mould. However, with the advent of laser engraving and design systems, the whole business of cutlery production has been revolutionised. This study explores the possibility of creating diverse designs for stainless steel 304 flatware sets without changing the entire production process. The research analyses three key laser process parameters, power, scanning speed, and number of passes, and their impacts on the resulting geometry, depth of cut, surface roughness, and material removed. These parameters are comprehensively studied and analysed for steel and zirconia ceramic. The study details the effects of power, scanning speed, number of passages, and fluence on engraved geometry. Fluence (power*number of passages/scanning speed) positively influences outputs and presents a positive trend. Medium power settings and higher scanning speeds with the maximum number of passages produce high-quality, low-roughness optimised cavities with the ideal geometric accuracy for both materials.
Nano-Enhanced Phase Reinforced Magnesium Matrix Composites: A Review of the Matrix, Reinforcement, Interface Design, Properties and Potential Applications
Authors: Ren Jiao-Yi , Ji Guan-Cheng , Guo Hao-Rui , Zhou Yu-Meng , Tan Xin , Zheng Wen-Fang , Xing Qian , Zhang Jia-Yi , Sun Jing-Ran , Yang Hong-Yu , Qiu Feng , Jiang Qi-Chuan
Published: May 2024

Magnesium matrix composites are essential lightweight metal matrix composites, following aluminum matrix composites, with outstanding application prospects in automotive, aerospace lightweight and biomedical materials because of their high specific strength, low density and specific stiffness, good casting performance and rich resources. However, the inherent low plasticity and poor fatigue resistance of magnesium hamper its further application to a certain extent. Many researchers have tried many strengthening methods to improve the properties of magnesium alloys, while the relationship between wear resistance and plasticity still needs to be further improved. The nanoparticles added exhibit a good strengthening effect, especially the ceramic nanoparticles. Nanoparticle-reinforced magnesium matrix composites not only exhibit a high impact toughness, but also maintain the high strength and wear resistance of ceramic materials, effectively balancing the restriction between the strength and toughness. Therefore, this work aims to provide a review of the state of the art of research on the matrix, reinforcement, design, properties and potential applications of nano-reinforced phase-reinforced magnesium matrix composites (especially ceramic nanoparticle-reinforced ones). The conventional and potential matrices for the fabrication of magnesium matrix composites are introduced. The classification and influence of ceramic reinforcements are assessed, and the factors influencing interface bonding strength between reinforcements and matrix, regulation and design, performance and application are analyzed. Finally, the scope of future research in this field is discussed.
Anisotropic Hyperelastic Strain Energy Function for Carbon Fiber Woven Fabrics
Authors: Cai Renye , Zhang Heng , Lai Chenxiang , Yu Zexin , Zeng Xiangkun , Wu Min , Wang Yankun , Huang Qisen , Zhu Yiwei , Kong Chunyu
Published: May 2024

The present paper introduces an innovative strain energy function (SEF) for incompressible anisotropic fiber-reinforced materials. This SEF is specifically designed to understand the mechanical behavior of carbon fiber-woven fabric. The considered model combines polyconvex invariants forming an integrity basisin polynomial form, which is inspired by the application of Noether’s theorem. A single solution can be obtained during the identification because of the relationship between the SEF we have constructed and the material parameters, which are linearly dependent. The six material parameters were precisely determined through a comparison between the closed-form solutions from our model and the corresponding tensile experimental data with different stretching ratios, with determination coefficients consistently reaching a remarkable value of 0.99. When considering only uniaxial tensile tests, our model can be simplified from a quadratic polynomial to a linear polynomial, thereby reducing the number of material parameters required from six to four, while the fidelity of the model’s predictive accuracy remains unaltered. The comparison between the results of numerical calculations and experiments proves the efficiency and accuracy of the method.
Rheological Properties and 3D Printing Behavior of PCL and DMSO2 Composites for Bio-Scaffold
Authors: Jang Jae-Won , Min Kyung-Eun , Kim Cheolhee , Wern Chien , Yi Sung
Published: May 2024

The significance of rheology in the context of bio three-dimensional (3D) printing lies in its impact on the printing behavior, which shapes material flow and the layer-by-layer stacking process. The objective of this study is to evaluate the rheological and printing behaviors of polycaprolactone (PCL) and dimethyl sulfone (DMSO2) composites. The rheological properties were examined using a rotational rheometer, employing a frequency sweep test. Simultaneously, the printing behavior was investigated using a material extrusion 3D printer, encompassing varying printing temperatures and pressures. Across the temperature range of 120–140 °C, both PCL and PCL/DMSO2 composites demonstrated liquid-like behavior, with a higher loss modulus than storage modulus. This behavior exhibited shear-thinning characteristics. The addition of DMSO2 10, 20, and 30 wt% into the PCL matrix reduced a zero-shear viscosity of 33, 46, and 74% compared to PCL, respectively. The materials exhibited extrusion velocities spanning from 0.0850 to 6.58 mm/s, with velocity being governed by the reciprocal of viscosity. A significant alteration in viscosity by temperature change directly led to a pronounced fluctuation in extrusion velocity. Extrusion velocities below 0.21 mm/s led to the production of unstable printed lines. The presence of distinct viscosities altered extrusion velocity, flow rate, and strut diameter. This phenomenon allowed the categorization of pore shape into three zones: irregular, normal, and no-pore zones. It underscored the importance of comprehending the rheological aspects of biomaterials in enhancing the overall quality of bio-scaffolds during the 3D printing process.
Hybrid Nanoparticles from Random Polyelectrolytes and Carbon Dots
Authors: Theodoropoulou Sophia , Vardaxi Antiopi , Kagkoura Antonia , Tagmatarchis Nikos , Pispas Stergios
Published: May 2024

The present study concerns the preparation of hybrid nanostructures composed of carbon dots (CDs) synthesized in our lab and a double-hydrophilic poly(2-dimethylaminoethyl methacrylate-co-oligo(ethylene glycol) methyl ether methacrylate) (P(DMAEMA-co-OEGMA)) random copolymer through electrostatic interactions between the negatively charged CDs and the positively charged DMAEMA segments of the copolymer. The synthesis of P(DMAEMA-co-OEGMA) copolymer was conducted through RAFT polymerization. Furthermore, the copolymer was converted into a strong cationic random polyelectrolyte through quaternization of the amine groups of DMAEMA segments with methyl iodide (CH3I), and it was subsequently utilized for the complexation with the carbon dots. The molecular, physicochemical, and photophysical characterization of the aqueous solution of the copolymers and their hybrid nanoparticles was conducted using dynamic and electrophoretic light scattering (DLS, ELS) and spectroscopic techniques, such as UV-Vis, fluorescence (FS), and FT-IR spectroscopy. In addition, studies of their aqueous solution using DLS and ELS showed their responsiveness to external stimuli (pH, temperature, ionic strength). Finally, the interaction of selected hybrid nanoparticles with iron (III) ions was confirmed through FS spectroscopy, demonstrating their potential application for heavy metal ions sensing.
Analysis of the Asymmetrical Rolling of Ultra-Thin Strips Considering Elastic Deformation of the Strips
Authors: Zhao Qilin , Hu Xianlei , Liu Xianghua
Published: May 2024

In normal cold rolling, the elastic deformation of the strip is typically ignored because of the dominant plastic deformation. However, this neglect may introduce additional errors when the strip is very thin. The aim of this study is to investigate the characteristics of the deformation region and thickness reduction in the asymmetrical rolling of ultra-thin strips. Mathematical models were developed based on the slab method, with consideration of the elastic deformation of the strips, and employed in the simulation calculation. The percentage of the three zones and the thickness reduction were analyzed using the simulation results. An increase in the speed ratio results in an increase in the reduction ratio, which is influenced by parameters, such as front tension, back tension, friction coefficient, and entry thickness. The elastic deformation of the strip reduces the tension and the roll pressure and causes the reduction ratio to decrease. The findings and conclusions of this study may be helpful to the mill operating in the asymmetrical rolling process of ultra-thin strips.
An Advanced IBVS-Flatness Approach for Real-Time Quadrotor Navigation: A Full Control Scheme in the Image Plane
Authors: Alshahir Ahmed , Kaaniche Khaled , Albekairi Mohammed , Alshahr Shahr , Mekki Hassen , Sahbani Anis , Alanazi Meshari D.
Published: May 2024

This article presents an innovative method for planning and tracking the trajectory in the image plane for the visual control of a quadrotor. The community of researchers working on 2D control widely recognizes this challenge as complex, because a trajectory defined in image space can lead to unpredictable movements of the robot in Cartesian space. While researchers have addressed this problem for mobile robots, quadrotors continue to face significant challenges. To tackle this issue, the adopted approach involves considering the separation of altitude control from the other variables, thus reducing the workspace. Furthermore, the movements of the quadrotor (pitch, roll, and yaw) are interdependent. Consequently, the connection between the inputs and outputs cannot be reversed. The task complexity becomes significant. To address this issue, we propose the following scenario: When the quadrotor is equipped with a downward-facing camera, flying at high altitude is sensible to spot a target. However, to minimize disturbances and conserve energy, the quadrotor needs to descend in altitude. This can result in the target being lost. The solution to this problem is a new methodology based on the principle of differential flatness, allowing the separation of altitude control from the other variables. The system first detects the target at high altitude, then plots a trajectory in the image coordinate system between the acquired image and the desired image. It is crucial to emphasize that this step is performed offline, ensuring that the image processing time does not affect the control frequency. Through the proposed trajectory planning, complying with the constraints of differential flatness, the quadrotor can follow the imposed dynamics. To ensure the tracking of the target while following the generated trajectory, the proposed control law takes the form of an Image Based Visual Servoing (IBVS) scheme. We validated this method using the RVCTOOLS environment in MATLAB. The DJI Phantom 1 quadrotor served as a testbed to evaluate, under real conditions, the effectiveness of the proposed control law. We specifically designed an electronic card to transfer calculated commands to the DJI Phantom 1 control joystick via Bluetooth. This card integrates a PIC18F2520 microcontroller, a DAC8564 digital-to-analogue converter, and an RN42 Bluetooth module. The experimental results demonstrate the effectiveness of this method, ensuring the precise tracking of the target as well as the accurate tracking of the path generated in the image coordinate system.
Ensemble Machine Learning Approach for Parkinson’s Disease Detection Using Speech Signals
Authors: Bukhari Syed Nisar Hussain , Ogudo Kingsley A.
Published: May 2024

The detection of Parkinson’s disease (PD) is vital as it affects the population worldwide and decreases the quality of life. The disability and death rate due to PD is increasing at an unprecedented rate, more than any other neurological disorder. To this date, no diagnostic procedures exist for this disease. However, several computational approaches have proven successful in detecting PD at early stages, overcoming the disadvantages of traditional methods of diagnosis. In this study, a machine learning (ML) detection system based on the voice signals of PD patients is proposed. The AdaBoost classifier has been utilized to construct the model and trained on a dataset obtained from the machine learning repository of the University of California, Irvine (UCI). This dataset includes voice attributes such as time-frequency features, Mel frequency cepstral coefficients, wavelet transform features, vocal fold features, and tremor waveform quality time. The model demonstrated promising performance, achieving high accuracy, precision, recall, F1 score, and AUC score of 0.96, 0.98, 0.93, 0.95, and 0.99, respectively. Furthermore, the robustness of the proposed model is rigorously assessed through cross-validation, revealing consistent performance across all iterations. The overarching objective of this study is to contribute to the scientific community by furnishing a robust system for the detection of PD.
A Negative Sample-Free Graph Contrastive Learning Algorithm
Authors: Chen Dongming , Nie Mingshuo , Wang Zhen , Chen Huilin , Wang Dongqi
Published: May 2024

Self-supervised learning is a new machine learning method that does not rely on manually labeled data, and learns from rich unlabeled data itself by designing agent tasks using the input data as supervision to obtain a more generalized representation for application in downstream tasks. However, the current self-supervised learning suffers from the problem of relying on the selection and number of negative samples and the problem of sample bias phenomenon after graph data augmentation. In this paper, we investigate the above problems and propose a corresponding solution, proposing a graph contrastive learning algorithm without negative samples. The model uses matrix sketching in the implicit space for feature augmentation to reduce sample bias and iteratively trains the mutual correlation matrix of two viewpoints by drawing closer to the distance of the constant matrix as the objective function. This method does not require techniques such as negative samples, gradient stopping, and momentum updating to prevent self-supervised model collapse. This method is compared with 10 graph representation learning algorithms on four datasets for node classification tasks, and the experimental results show that the algorithm proposed in this paper achieves good results.
Inverse Scheme to Locally Determine Nonlinear Magnetic Material Properties: Numerical Case Study
Authors: Kaltenbacher Manfred , Gschwentner Andreas , Kaltenbacher Barbara , Ulbrich Stefan , Reinbacher-Köstinger Alice
Published: May 2024

We are interested in the determination of the local nonlinear magnetic material behaviour in electrical steel sheets due to cutting and punching effects. For this purpose, the inverse problem has to be solved, where the objective function, which penalises the difference between the measured and the simulated magnetic flux density, has to be minimised under a constraint defined according to the corresponding partial differential equation model. We use the adjoint method to efficiently obtain the gradients of the objective function with respect to the material parameters. The optimisation algorithm is low-memory Broyden–Fletcher–Goldfarb–Shanno (BFGS), the forward and adjoint formulations are solved using the finite element (FE) method and the ill-posedness is handled via Tikhonov regularisation, in combination with the discrepancy principle. Realistic numerical case studies show promising results.
A Class of Bi-Univalent Functions in a Leaf-Like Domain Defined through Subordination via q̧-Calculus
Authors: Alsoboh Abdullah , Oros Georgia Irina
Published: May 2024

Bi-univalent functions associated with the leaf-like domain within open unit disks are investigated, and a new subclass is introduced and studied in the research presented here. This is achieved by applying the subordination principle for analytic functions in conjunction with q-calculus. The class is proved to not be empty. By proving its existence, generalizations can be given to other sets of functions. In addition, coefficient bounds are examined with a particular focus on |α2| and |α3| coefficients, and Fekete–Szegö inequalities are estimated for the functions in this new class. To support the conclusions, previous works are cited for confirmation.
A Study on Optimizing the Maximal Product in Cubic Fuzzy Graphs for Multifaceted Applications
Authors: Meenakshi Annamalai , Mythreyi Obel , Čep Robert , Karthik Krishnasamy
Published: May 2024

Graphs in the field of science and technology make considerable use of theoretical concepts. When dealing with numerous links and circumstances in which there are varying degrees of ambiguity or robustness in the connections between aspects, rather than purely binary interactions, cubic fuzzy graphs (CFGs) are more adaptable and compatible than fuzzy graphs. To better represent the complexity of interactions or linkages in the real world, an emerging CFG can be very helpful in achieving better problem-solving abilities that specialize in domains like network analysis, the social sciences, information retrieval, and decision support systems. This idea can be used for a variety of uncertainty-related issues and assist decision-makers in selecting the best course of action through the use of a CFG. Enhancing the maximized network of three cubic fuzzy graphs’ decision-making efficiency was the ultimate objective of this study. We introduced the maximal product of three cubic fuzzy graphs to investigate how interval-valued fuzzy membership, fuzzy membership, and the miscellany of relations are all simultaneously supported through the aspect of degree and total degree of a vertex. Furthermore, the domination on the maximal product of three CFGs was illustrated to analyze the minimum domination number of the weighted CFG, and the proposed approach is illustrated with applications.
Marine-Derived Sulfated Glycans Inhibit the Interaction of Heparin with Adhesion Proteins of Mycoplasma pneumoniae
Authors: Yang Jiyuan , Song Yuefan , Xia Ke , Pomin Vitor H. , Wang Chunyu , Qiao Mingqiang , Linhardt Robert J. , Dordick Jonathan S. , Zhang Fuming
Published: May 2024

Mycoplasma pneumoniae, a notable pathogen behind respiratory infections, employs specialized proteins to adhere to the respiratory epithelium, an essential process for initiating infection. The role of glycosaminoglycans, especially heparan sulfate, is critical in facilitating pathogen–host interactions, presenting a strategic target for therapeutic intervention. In this study, we assembled a glycan library comprising heparin, its oligosaccharide derivatives, and a variety of marine-derived sulfated glycans to screen the potential inhibitors for the pathogen–host interactions. By using Surface Plasmon Resonance spectroscopy, we evaluated the library’s efficacy in inhibiting the interaction between M. pneumoniae adhesion proteins and heparin. Our findings offer a promising avenue for developing novel therapeutic strategies against M. pneumoniae infections.
An Investigation into the Microstructures and Mechanical Properties of a TIG Welding Joint in Ti-4Al-2V Titanium Alloy
Authors: Chen Yao , Liu Xiao , Zhang Zhendi , Wang Kaiqing , Zhang Shanglin , Qian Bingnan , Wu Jun , Wang Li
Published: May 2024

The Ti-4Al-2V (wt. %) titanium alloy has garnered widespread applications across diverse fields due to its exceptional strength-to-weight ratio, high toughness, specific strength, and corrosion resistance. The welding of Ti-4Al-2V titanium alloy components is often necessary in manufacturing processes, where the reliability of a welded joint critically influences the overall service life of these components. Consequently, a comprehensive understanding of the welded joint’s microstructure and mechanical properties is imperative. In this study, Ti-4Al-2V titanium alloy was welded using multi-layer and multi-pass TIG welding techniques, and a detailed examination was conducted to analyze the microstructure and grain morphology of each microzone of the welded joint. The results revealed the presence of an initial α phase and a secondary lamellar α phase in the heat affected zone (HAZ). Meanwhile, the fusion zone (FZ) primarily comprised a coarse secondary α phase and a small amount of an acicular martensitic α’ phase. Both the recrystallization zone and the superheated zone exhibited a distinct preferred orientation, with grains smaller than 10 μm accounting for 65.9% and 55.1%, respectively. To assess the mechanical properties of the various microzones and the typical microstructure within the welded joint, nanoindentation tests were performed. The results indicated that the recrystallization zone possessed a higher nanohardness (3.753 GPa) than the incomplete recrystallization zone (3.563 GPa) and the superheated zone (3.48 GPa). Among all the microzones, the FZ exhibited the lowest average nanohardness (3.058 GPa). Notably, the basket-weave microstructure demonstrated the highest average nanohardness, reaching 3.93 GPa. This was followed by the fine-grain microstructure, which possessed a slightly lower nanohardness. The Widmanstätten microstructure, on the other hand, exhibited the lowest nanohardness among the three microstructures within the HAZ. Therefore, the basket-weave microstructure stands out as the most desirable microstructure to achieve in the welded joint. In summary, this study provides a comprehensive characterization and analysis of the microstructure and properties of Ti-4Al-2V titanium alloy TIG welds, aiming to contribute to the optimization of the TIG welding process for Ti-4Al-2V titanium alloy.
Investigation of Residual Stress Distribution and Fatigue of 7050-T7451 Alloy Hole Components with Laser Shock and Ultrasonic Extrusion
Authors: Jiang Yinfang , Liu Xiancheng , Wang Yangyang , Cui Lingling , Ji Guang , Liu Wei
Published: May 2024

Small-hole structures, such as the millions of fastener holes found on aircraft, are typical stress-concentration structures prone to fatigue failure. To further improve the strengthening process of this small-hole structure, we make up for the limitations of laser shock processing (LSP) of small holes by combining it with the ultrasonic extrusion strengthening (UES) process to form a new strengthening method—laser shock and ultrasonic extrusion strengthening (LUE). The influence of the LUE process sequence and process parameters on residual stress distribution was studied through FEM, and the gain of fatigue life of specimens after LUE strengthening was also explored through tests. The results show that when using LUE technology, the friction force decreases with the increase in amplitude and decreases by 3.2% when the amplitude is maximum. The LUE process eliminates the thickness effect generated by LSP, which can achieve good stress distribution of small-hole components under smaller laser shock peak pressure, and reduces equipment power. LUE can significantly improve the fatigue life of small-hole components, and the maximum fatigue life gain can be up to 310.66%.
Revealing the Superior Post-Necking Elongation in the Fine-Grained Ti-6Al-4V ELI at Cryogenic Temperature
Authors: Gao Quan , Li Rengeng , Wu Hao , Miao Kesong , Wu He , Liu Chenglu , Li Xuewen
Published: May 2024

The mechanical properties of a fine-grained (FG) Ti-6Al-4V extra-low interstitial (ELI) alloy were investigated by tensile tests at 298 K and 77 K. The experimental results indicated that, at 77 K, the alloy exhibits a small uniform elongation of 2.65%, but has a fracture elongation of 19.2%, showing superior post-necking elongation. At 298 K, the alloy displays a single dislocation slipping, β→α″ phase transformation occurred, and 6.35% uniform elongation was obtained, whereas the coupling of dislocation slipping and twinning deformation behaviors dominated at 77 K. The limited uniform elongation is attributed to the absence of martensite phase transformation at 77 K, whereas the decent fracture elongation is ascribed to the resistance offered by twinning against plastic instability.
Aging Treatment Induces the Preferential Crystallographic Orientation of αs in the Near-α Titanium Alloy Ti60
Authors: Liu Bin , Liu Chenglu , Li Xuewen , Wu Hao , Miao Kesong , Wu He , Li Rengeng
Published: May 2024

In this article, we subjected the Ti60 alloy to solid-solution treatment at 1020 °C and aging treatment at 600 °C, respectively, achieving a bimodal microstructure. The microstructures obtained after aging treatment showed no significant difference in the primary α-phase content, size, and width of the lamellar α phase. This suggests that the final microstructure morphology is primarily determined by the solid-solution temperature, with the aging process exerting less pronounced effects on microstructural alterations. Furthermore, we investigated the effect of solid-solution and aging treatment on the crystallographic orientation evolution of the secondary α phase (αs) in the near-α titanium alloy Ti60. The αs phase displays a random orientation in solid-solution treatment sample, while it demonstrated a preferential {0 1 −1 0} orientation after aging treatment. This interesting phenomenon is attributed to the enhanced variant selection resulting from the dissolution of variant near 60° and 90° during aging. Furthermore, the αs with {0 1 −1 0} orientation nucleated at the grain boundary and coalesced into larger αs lath with increasing aging time, further contributing to the αs {0 1 −1 0} texture.
Facial Skin Microbiome Composition and Functional Shift with Aging
Authors: Garlet Allison , Andre-Frei Valerie , Del Bene Nicolas , Cameron Hunter James , Samuga Anita , Rawat Vimal , Ternes Philipp , Leoty-Okombi Sabrina
Published: May 2024

The change in the skin microbiome as individuals age is only partially known. To provide a better understanding of the impact of aging, whole-genome sequencing analysis was performed on facial skin swabs of 100 healthy female Caucasian volunteers grouped by age and wrinkle grade. Volunteers’ metadata were collected through questionnaires and non-invasive biophysical measurements. A simple model and a biological statistical model were used to show the difference in skin microbiota composition between the two age groups. Taxonomic and non-metric multidimensional scaling analysis showed that the skin microbiome was more diverse in the older group (≥55 yo). There was also a significant decrease in Actinobacteria, namely in Cutibacterium acnes, and an increase in Corynebacterium kroppenstedtii. Some Streptococcus and Staphylococcus species belonging to the Firmicutes phylum and species belonging to the Proteobacteria phylum increased. In the 18–35 yo younger group, the microbiome was characterized by a significantly higher proportion of Cutibacterium acnes and Lactobacillus, most strikingly, Lactobacillus crispatus. The functional analysis using GO terms revealed that the young group has a higher significant expression of genes involved in biological and metabolic processes and in innate skin microbiome protection. The better comprehension of age-related impacts observed will later support the investigation of skin microbiome implications in antiaging protection.
Interplay of Demographic Influences, Clinical Manifestations, and Longitudinal Profile of Laboratory Parameters in the Progression of SARS-CoV-2 Infection: Insights from the Saudi Population
Authors: Al-Hassinah Sarah , Al-Daihan Sooad , Alahmadi Mashael , Alghamdi Sara , Almulhim Rawabi , Obeid Dalia , Arabi Yaseen , Alswaji Abdulrahman , Aldriwesh Marwh , Alghoribi Majed
Published: May 2024

Understanding the factors driving SARS-CoV-2 infection progression and severity is complex due to the dynamic nature of human physiology. Therefore, we aimed to explore the severity risk indicators of SARS-CoV-2 through demographic data, clinical manifestations, and the profile of laboratory parameters. The study included 175 patients either hospitalized at King Abdulaziz Medical City–Riyadh or placed in quarantine at designated hotels in Riyadh, Saudi Arabia, from June 2020 to April 2021. Hospitalized patients were followed up through the first week of admission. Demographic data, clinical presentations, and laboratory results were retrieved from electronic patient records. Our results revealed that older age (OR: 1.1, CI: [1.1–1.12]; p < 0.0001), male gender (OR: 2.26, CI: [1.0–5.1]; p = 0.047), and blood urea nitrogen level (OR: 2.56, CI: [1.07–6.12]; p = 0.034) were potential predictors of severity level. In conclusion, the study showed that apart from laboratory parameters, age and gender could potentially predict the severity of SARS-CoV-2 infection in the early stages. To our knowledge, this study is the first in Saudi Arabia to explore the longitudinal profile of laboratory parameters among risk factors, shedding light on SARS-CoV-2 infection progression parameters.
Reference Genes for Expression Analyses by qRT-PCR in Enterobacter cancerogenus
Authors: Pan Yang , Zhao Yue , Zeng Hua-Rui , Wu Jia-Qi , Song Ying-Ying , Rao Ya-Hao , Li Guo-Qing , Jin Lin
Published: May 2024

The Enterobacter cancerogenus strain EcHa1 was isolated from the dead larvae of Helicoverpa armigera, and has the potential for biocontrol of some Lepidoptera insects. In order to screen insecticidal-related genes by qRT-PCR, stable endogenous reference genes used for normalizing qRT-PCR data were selected and evaluated from 13 housekeeping genes (HKGs). The expression levels of the HKGs were determined using qRT-PCR under different experimental conditions, including two culture temperatures and three bacterial OD values. Five stability analysis methods (Ct, BestKeeper, NormFinder, geNorm, and RefFinder) were used to comprehensively rank the candidate genes. The results showed that the optimal reference genes varied under different experimental conditions. The combination of gyrA and gyrB was recommended as the best reference gene combination at 28 °C, while gyrA and rpoB was the best combination at 37 °C. When the OD values were 0.5, 1.0 and 2.0, the recommended reference gene combinations were ftsZ and gyrA, rpoB and gyrB, and gyrA and pyk, respectively. The most suitable reference genes were gyrA and gyrB under all experimental conditions. Using gyrA and gyrB as the reference genes for qRT-PCR, EcHa1 was found to invade all tissues of the H. armigera larvae, and expressed a candidate pathogenic factor Hcp at high levels in gut, Malpighian tubules, and epidermis tissues. This study not only establishes an accurate and reliable normalization for qRT-PCR in entomopathogenic bacteria but also lays a solid foundation for further study of functional genes in E. cancerogenus.
Exploring the Frozen Armory: Antiphage Defense Systems in Cold-Adapted Bacteria with a Focus on CRISPR-Cas Systems
Authors: Sandsdalen Greta Daae , Kumar Animesh , Hjerde Erik
Published: May 2024

Our understanding of the antiphage defense system arsenal in bacteria is rapidly expanding, but little is known about its occurrence in cold-adapted bacteria. In this study, we aim to shed light on the prevalence and distribution of antiphage defense systems in cold-adapted bacteria, with a focus on CRISPR-Cas systems. Using bioinformatics tools, Prokaryotic Antiviral Defense LOCator (PADLOC) and CRISPRCasTyper, we mapped the presence and diversity of antiphage defense systems in 938 available genomes of cold-adapted bacteria from diverse habitats. We confirmed that CRISPR-Cas systems are less frequent in cold-adapted bacteria, compared to mesophilic and thermophilic species. In contrast, several antiphage defense systems, such as dXTPases and DRTs, appear to be more frequently compared to temperate bacteria. Additionally, our study provides Cas endonuclease candidates with a potential for further development into cold-active CRISPR-Cas genome editing tools. These candidates could have broad applications in research on cold-adapted organisms. Our study provides a first-time map of antiphage defense systems in cold-adapted bacteria and a detailed overview of CRISPR-Cas diversity.