bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Sintering Temperature on the Physical and Mechanical Characteristics of Fabricated ZrO2–Cr–Ni–Ce–Y Composite
Authors: Saini Brajesh Chandra , Jain Naman , Rao Dinesh Kumar , Singhal Varun , Verma Akarsh , Goudar Dayanand M. , Raju Kandavalli , Pinto Deesy G.
Published: November 2024

The present study investigates the synthesis and characterization of a zirconium oxide (ZrO2)-based metal composite doped with cerium (Ce) and yttrium (Y), using chromium (Cr) and nickel (Ni) as base metals. These constituents were selected for their superior mechanical properties and compatibility with the ceramic phase. High-purity powders were homogenized via high-energy ball milling, followed by cold pressing and sintering in a controlled atmosphere of hydrogen. The sintering process was conducted at temperatures ranging from 850 °C to 1350 °C to examine the evolution of microstructure, grain growth, and densification. Scanning electron microscopy (SEM) revealed a homogeneous distribution of phases, with distinct microstructural features attributed to each element at different sintering temperatures. The experimental results revealed that the composite’s density was increased by 30% and porosity was reduced by 61% at a sintering temperature of 1350 °C. The hardness and flexural strength of composite were found to be 23% and 60% higher at 1350 °C, respectively, compared to that at 850 °C, suggesting enhanced mechanical properties due to cerium and yttrium reinforcement within matrix and efficient doping and phase transformation. Overall, incorporation of cerium and yttrium significantly improved mechanical behavior and phase stability of ZrO2–Cr–Ni composite, highlighting its potential for advanced engineering applications.
The Impact of Helium and Nitrogen Plasmas on Electrospun Gelatin Nanofiber Scaffolds for Skin Tissue Engineering Applications
Authors: Mozaffari Abolfazl , Parvinzadeh Gashti Mazeyar , Alimohammadi Farbod , Pousti Mohammad
Published: November 2024

This study explores the fabrication of tannic acid-crosslinked gelatin nanofibers via electrospinning, followed by helium and nitrogen plasma treatment to enhance their biofunctionality, which was assessed using fibroblast cells. The nanofibers were characterized using scanning electron microscopy, atomic force microscopy, attenuated total reflection Fourier transform infrared spectroscopy, X-ray diffraction, and water contact angle measurements before and after treatment. Helium and nitrogen gas plasma were employed to modify the nanofiber surfaces. Results indicated that helium and nitrogen plasma treatment significantly increased the hydrophilicity and biofunctionality of the nanofibers by 5.1° ± 0.6 and 15.6° ± 2.2, respectively, making them more suitable for human skin fibroblast applications. To investigate the impact of plasma treatment on gelatin, we employed a computational model using density functional theory with the B3LYP/6-31+G(d) method. This model represented gelatin as an amino acid chain composed of glycine, hydroxyproline, and proline, interacting with plasma particles. Vibrational analysis of these systems was used to interpret the vibrational spectra of untreated and plasma-treated gelatin. To further correlate with experimental findings, molecular dynamics simulations were performed on a system of three interacting gelatin chains. These simulations explored changes in amino acid bonding. The computational results align with experimental observations. Comprehensive analyses confirmed that these treatments improved hydrophilicity and biofunctionality, supporting the use of plasma-treated gelatin nanofibers in skin tissue engineering applications. Gelatin’s natural biopolymer properties and the versatility of plasma surface modification techniques underscore its potential in regenerating cartilage, skin, circulatory tissues, and hamstrings.
A Dual-Module System for Copyright-Free Image Recommendation and Infringement Detection in Educational Materials
Authors: Kim Yeongha , Kim Soyeon , Min Seonghyun , Han Youngung , Lee Ohyoung , Kim Wongyum
Published: November 2024

Images are extensively utilized in educational materials due to their efficacy in conveying complex concepts. However, unauthorized use of images frequently results in legal issues related to copyright infringement. To mitigate this problem, we introduce a dual-module system specifically designed for educators. The first module, a copyright infringement detection system, employs deep learning techniques to verify the copyright status of images. It utilizes a Convolutional Variational Autoencoder (CVAE) model to extract significant features from copyrighted images and compares them against user-provided images. If infringement is detected, the second module, an image retrieval system, recommends alternative copyright-free images using a Vision Transformer (ViT)-based hashing model. Evaluation on benchmark datasets demonstrates the system’s effectiveness, achieving a mean Average Precision (mAP) of 0.812 on the Flickr25k dataset. Additionally, a user study involving 65 teachers indicates high satisfaction levels, particularly in addressing copyright concerns and ease of use. Our system significantly aids educators in creating educational materials that comply with copyright regulations.
First Long-Term Measurements on Kazakhstan Shelf of the Caspian Sea Reveal Alternating Currents and Energetic Temperature Variability
Authors: Zavialov Peter O. , Kostianoy Andrey G. , Sapozhnikov Philipp V. , Khan Valentina M. , Kurbaniyazov Nurgazy K. , Kurbaniyazov Abilgazi K.
Published: November 2024

Moored near-bottom current velocity and water temperature measurements were performed during a period of 194 days (from October 2022 through April 2023) with a 15-min sampling rate at two locations on the shelf of the Kazakhstan sector of the Caspian Sea in its Middle Caspian basin. The area has not been covered by in situ measurements over several decades. The two stations were separated by a distance of 22 km along the coast. The velocity and temperature data collected at 14 m depth were analyzed together with the wind data from the local meteorological station, NCEP/NCAR reanalysis of wind curl data over the Caspian Sea, as well as multi-mission satellite imagery. The analysis revealed that the currents were predominantly along-shore and highly variable in direction, with nearly zero average over the observation period. The along-shore and cross-shore components of velocity exhibited rather high correlation with the along-shore wind stress with the maximum (r = 0.68 and r = 0.53, respectively) at a time lag of about 9.5 h. The velocity series were not significantly correlated with the wind curl averaged over the entire Caspian Sea at any temporal lag, while there were weak but significant correlations between the along-shore current velocity and the curl of the wind fields over the Middle Caspian and Northern Caspian basins with time lags from one to nine days. The along-shore current velocities at the two stations were highly correlated (r = 0.78) with each other at no temporal lag. The temperature at both stations demonstrated nearly identical seasonal march, but a higher frequency variability superimposed on the latter was also evident with amplitudes as high as 2.79 °C. Somewhat surprisingly, the series of these anomalies at the two stations were not correlated either with each other or with surface wind forcing. However, there is evidence pointing to their connection with the cross-shore component of near bottom velocity, i.e., the cross-shore, up or down the bottom slope excursions of water from deeper or shallower depths, retaining a different temperature. During intense winter cooling of the surface layer, this effect is manifested as «warm upwelling» creating strong positive temperature anomalies or the opposite «cold downwelling» and negative anomalies.
Multiparameter Collaborative Optimization and Analysis of the Non-Penetrating Tunnel Thruster
Authors: Guo Jinyu , Yang Yi , Wang Chao , Hu Zhiqiang , Zheng Quan , Fan Chuanzhi
Published: November 2024

A brand new non-penetrating tunnel thruster (short for NPT thruster) is proposed in this paper. The tunnel structural parameters of the thruster are optimized, and the performance and optimization effect are verified by experiments. First, the design and function of the NPT thruster are introduced. Second, the computational fluid dynamics method is used to calculate the hydrodynamic performance of the NPT thruster and to analyze the static mooring thrust performance. Third, the tunnel structural parameters of the NPT thruster are optimized with the method of the response surface methodology. The pressure distributions and the flow fields on the tunnel surface of the NPT thrusters before and after optimization are compared with simulations. Finally, the mooring static thrust of the NPT thrusters is tested with experiments. The results show that the average increase in the mooring static thrust for the optimized thruster is 12.4%, and the maximum increase can reach 21.79% when the rotational speed is from 3000 rpm to 6500 rpm.
Intercomparison of Surface Currents Obtained Using SCHISM and the HF Radar Data in Galveston Bay and Sabine Lake, Texas
Authors: Ogbodo Cletus O. , Fitzgerald Rosa M. , Fuller Christopher , Lee Jungwoo , Perea Roberto , Polanco-Gonzalez Javier
Published: November 2024

This study provides a comprehensive analysis and intercomparison of surface currents, for Galveston Bay and Sabine Lake, Texas, obtained from High-Frequency (HF) radars and SCHISM model. We established a methodology based on qualitative and quantitative analyses to compare measured and modeled surface currents. One-month HF radar data, in April 2023, were extracted from the two newly installed HF radar networks comprising two and three HF radar stations at Sabine Lake and Galveston Bay, respectively. The extracted surface current data were compared to corresponding SCHISM-simulated currents to assess the model’s performance in predicting currents. The comparison encompassed qualitative and quantitative assessments by evaluating current vectors and the magnitude of eastward and northward velocity components from both methods. The results showed the ocean current predictive capabilities of SCHISM exemplified by their strong correlations (up to 0.94), high index of agreement (up to 0.95), and low error metrics, during the study period. The disparities in the eastward and northward current measurements across the dates underscore the complex interplay between prevailing winds, bay-ocean interactions, and regional weather patterns. This study sheds light on the intricate dynamics of the surface currents in estuaries and nearshore lakes with the underlying efficacy of both the HF radar and SCHISM surface current determinations. The findings can contribute to advancing the understanding of coastal dynamics and determining the strategies for environmental monitoring and management.
Development of a Key Method for the Optimization of Port Vessel Detection Based on an Improved Multi-Structural Morphology Approach
Authors: Tabi Fouda Bernard Marie , Zhang Wenjun , Atangana Jacques , Edima-Durand Helene Carole
Published: November 2024

All over the world, many ports have implemented surveillance camera systems to monitor the vessels and activities around them. These types of systems are not very effective in accurately detecting activities around the port due to background noise and congestion interference at the sea surface. This is why it is difficult to accurately detect vessels, especially smaller vessels, when it turns dark. It is known that some vessels do not comply with maritime rules, particularly in port and safety zones; these must be detected to avoid incidents. For these reasons, in this study, we propose and develop an improved multi-structural morphology (IMSM) approach to eliminate all of this noise and interference so that vessels can be accurately detected in real time. With this new approach, the target vessel is separated from the sea surface background through the weighted morphological filtering of several datasets of structural components. Then, neighborhood-based adaptive fast median filtering is used to filter out impulse noise. Finally, a characteristic morphological model of the target vessel is established using the connected domain; this allows the sea surface congestion to be eliminated and the movement of vessels to be detected in real time. Multiple tests are carried out on a small and discrete area of moving vessels. The results from several collected datasets show that the proposed approach can effectively eliminate background noise and congestion interference in video monitoring. The detection accuracy rate and the processing time are improved by approximately 3.91% and 1.14 s, respectively.
Antifungal Effect of Oregano Essential Oil Against Penicillium expansum on Pyrus sinkiangensis
Authors: Liu Qun , Li Li , Yang Zhenyuan , Xiong Xiaodi , Song Qi , Li Baishu , Zou Hang , Zhang Lixiang , Liu Tao
Published: November 2024

Given the increasing demand for fruit safety assurance and environmental protection, plant essential oils have gained significant attention as natural alternatives for control of postharvest decay caused by various pathogens. In postharvest management, it is particularly important to effectively control postharvest decay without compromising the quality attributes of fruits. Although oregano essential oil (OEO) has been extensively studied for its antimicrobial properties against various postharvest pathogens, few studies have focused on its interactions with postharvest fruits. In this study, OEO was applied for management of postharvest decay of Pyrus sinkiangensis caused by Penicillium expansum, and its antifungal mechanisms and impacts on the quality attributes of pears were investigated. The OEO exhibited notable inhibitory effects, with determined MIC (0.02%) and MFC (0.04%) against P. expansum, which highlighted its potential as a viable alternative to synthetic fungicides. Our findings revealed that OEO disrupted P. expansum by compromising the integrity of the fungal plasma membrane, as evidenced by changes in plasma membrane permeability and the leakage of cellular components. The OEO treatment significantly reduced weight loss, maintained firmness, and preserved soluble-solid content in the treated pears. In addition, OEO treatment stimulated the intrinsic antioxidant mechanisms of pears, as demonstrated by elevated activities of superoxide dismutase and catalase during storage. This study provides compelling evidence for the antifungal and quality-preserving properties of OEO in the postharvest management of pears, underscoring its potential as an alternative to synthetic fungicides for controlling postharvest decay. The elucidation of the interaction between OEO and P. sinkiangensis would greatly enhance our comprehensive understanding of the biological activities of OEO and facilitate its practical application in the postharvest management of pears.
Polyphasic Characterization of the Biocontrol Potential of a Novel Strain of Trichoderma atroviride Isolated from Central Mexico
Authors: González-Martínez Karla Ivonne , Vázquez-Garcidueñas Ma. Soledad , Herrera-Estrella Alfredo , Fernández-Pavía Sylvia P. , Salgado-Garciglia Rafael , Larsen John , Ochoa-Ascencio Salvador , Rodríguez-Alvarado Gerardo , Vázquez-Marrufo Gerardo
Published: November 2024

This work describes the characterization of Trichoderma atroviride strain CMU-08, isolated from Michoacán, Mexico. CMU-08 demonstrated robust growth and conidiation across a temperature range from 16 to 32 °C and a pH range from 4 to 9 on potato dextrose agar (PDA) and malt extract agar (MEA) media. The strain is an efficient antagonist of six species of phytopathogenic fungi and oomycetes in PDA, MEA, and Vogel minimal medium (VMM). Antagonist mechanisms of CMU-08 included direct mycoparasitism observed in dual-culture assays, as well as antibiosis attributed to growth inhibition via both volatile and non-volatile metabolites, with the effectiveness varying depending on the test phytopathogen and culture medium. Extracellular filtrates (ECFs) recovered from liquid cultures of CMU-08 under basal and induced conditions using Botrytis cinerea cell walls significantly inhibited their growth at a concentration of 750 µg/mL. Moreover, in detached tomato leaf assays, these ECFs reduced foliar damage caused by B. cinerea by 24–34%. The volatile organic compounds (VOCs) produced by CMU-08 also exhibited substantial efficacy, reducing foliar damage by up to 50% in similar tests. Despite showing no basal extracellular chitinase enzymatic activity, CMU-08 demonstrated significant induction of this activity in cultures supplemented with B. cinerea and Fusarium sp. cell walls. Four genes encoding extracellular chitinases (chit33, chit36, ech42, and locus 217415) showed different dynamics of transcriptional regulation during the dual-culture confrontation of strain CMU-08 with B. cinerea and Fusarium sp., varying according to the phytopathogen and the interaction stage. The CMU-08 strain shows physiological versatility and employs a variety of antagonist mechanisms toward different species of phytopathogenic microorganisms, making it a good candidate for developing a biocontrol product for field application.
AI-Reinforced Wearable Sensors and Intelligent Point-of-Care Tests
Authors: Yammouri Ghita , Ait Lahcen Abdellatif
Published: November 2024

Artificial intelligence (AI) techniques offer great potential to advance point-of-care testing (POCT) and wearable sensors for personalized medicine applications. This review explores the recent advances and the transformative potential of the use of AI in improving wearables and POCT. The integration of AI significantly contributes to empowering these tools and enables continuous monitoring, real-time analysis, and rapid diagnostics, thus enhancing patient outcomes and healthcare efficiency. Wearable sensors powered by AI models offer tremendous opportunities for precise and non-invasive tracking of physiological conditions that are essential for early disease detection and personalized treatments. AI-empowered POCT facilitates rapid, accurate diagnostics, making these medical testing kits accessible and available even in resource-limited settings. This review discusses the key advances in AI applications for data processing, sensor fusion, and multivariate analytics, highlighting case examples that exhibit their impact in different medical scenarios. In addition, the challenges associated with data privacy, regulatory approvals, and technology integrations into the existing healthcare system have been overviewed. The outlook emphasizes the urgent need for continued innovation in AI-driven health technologies to overcome these challenges and to fully achieve the potential of these techniques to revolutionize personalized medicine.
Impact of Refined Boundary Conditions of Land Objects on Urban Hydrological Process Simulation
Authors: Chen Chaohui , Zhang Yindong , Lou Yihan , Tang Ziyi , Wang Pin , Hu Tangao
Published: November 2024

Urbanization has led to an increase in impervious areas and, consequently, an increase in the surface runoff volume and runoff rate. This has exacerbated urban flooding and highlighted the importance of modeling urban hydrological processes. The Waterview Community of Hangzhou City (WCHC) was taken as the study area, and three scenarios were developed: the original scenario, the rough description scenario, and the fine description scenario. The urban hydrological processes were simulated through a coupled model incorporating actual measurements and four design precipitation events (1-year, 5-year, 10-year, and 20-year return periods). The results show the following: (1) The refined depiction scenario has the highest accuracy in terms of measured precipitation, with an average error of 0.54 cm. (2) During different precipitation return periods, the refined depiction scenario shows the smallest range of accumulated water, with a more realistic distribution. On average, it differed from the original scenario by 21.45% and from the rough depiction scenario by 32.18%. (3) The simulation results after the refinement of the feature boundaries are more reasonable in terms of the flow rate and flow direction, indicating that the simulation results have better dynamics. The results showed that refined boundary conditions improved the accuracy and dynamics of urban hydrological simulations, especially in terms of their reflection of actual water accumulation under varying precipitation conditions.
Comprehensive Representations of Subpixel Land Use and Cover Shares by Fusing Multiple Geospatial Datasets and Statistical Data with Machine-Learning Methods
Authors: Chen Yuxuan , Li Rongping , Tu Yuwei , Lu Xiaochen , Chen Guangsheng
Published: November 2024

Land use and cover change (LUCC) is a key factor influencing global environmental and socioeconomic systems. Many long-term geospatial LUCC datasets have been developed at various scales during the recent decades owing to the availability of long-term satellite data, statistical data and computational techniques. However, most existing LUCC products cannot accurately reflect the spatiotemporal change patterns of LUCC at the regional scale in China. Based on these geospatial LUCC products, normalized difference vegetation index (NDVI), socioeconomic data and statistical data, we developed multiple procedures to represent both the spatial and temporal changes of the major LUC types by applying machine-learning, regular decision-tree and hierarchical assignment methods using northeastern China (NEC) as a case study. In this approach, each individual LUC type was developed in sequence under different schemes and methods. The accuracy evaluation using sampling plots indicated that our approach can accurately reflect the actual spatiotemporal patterns of LUC shares in NEC, with an overall accuracy of 82%, Kappa coefficient of 0.77 and regression coefficient of 0.82. Further comparisons with existing LUCC datasets and statistical data also indicated the accuracy of our approach and datasets. Our approach unfolded the mixed-pixel issue of LUC types and integrated the strengths of existing LUCC products through multiple fusion processes. The analysis based on our developed dataset indicated that forest, cropland and built-up land area increased by 17.11 × 104 km2, 15.19 × 104 km2 and 2.85 × 104 km2, respectively, during 1980–2020, while grassland, wetland, shrubland and bare land decreased by 26.06 × 104 km2, 4.24 × 104 km2, 3.97 × 104 km2 and 0.92 × 104 km2, respectively, in NEC. Our developed approach accurately reconstructed the shares and spatiotemporal patterns of all LUC types during 1980–2020 in NEC. This approach can be further applied to the entirety of China, and worldwide, and our products can provide accurate data supports for studying LUCC consequences and making effective land use policies.
Reduce Speed Limits to Minimize Potential Harm and Maximize the Health Benefits of Street Trees
Authors: Feng Xiaoqi , Navakatikyan Michael , Astell-Burt Thomas
Published: November 2024

Urban greening is threatened by the concern that street trees increase traffic-related injury/death. Associations between all serious and fatal traffic crashes and street tree percentages were examined in Sydney, Australia. Associations were adjusted for confounding factors relating to driver behavior (speeding, fatigue, and use of alcohol) and road infrastructure, including alignment (e.g., straight, curved), surface condition (e.g., dry, wet, ice), type (e.g., freeway, roundabout), and speed limit. Models indicated that 10% more street trees were associated with 3% and 20% higher odds of serious or fatal injuries and 20% tree collisions on roads of any speed, respectively. However, further analysis stratified by speed limit revealed contrasting results. Along roads of 70 km/h or greater, 10% more street trees were associated with 8% higher odds of serious or fatal injury and 25% higher odds of death. Comparable associations were not found between street trees and serious or fatal injuries along roads below 70 km/h. Reducing speed limits below 70 km/h saves lives and may mitigate risks of serious or fatal traffic accidents associated with street trees, enabling greener, cooler, healthier cities.
The Formation and Preservation of Urban Heritage Through Urban Landscape Transformation: A Case Study of Pittsburgh
Authors: Lovra Éva , Sarihan Elif
Published: November 2024

This study examines the potential of urban landscape transformation to generate and develop new heritage and the role of heritage urbanism in an industrial city. It explores whether the changeover of urban heritage districts in Pittsburgh (PA, USA) can give rise to a novel type of urban heritage. Pittsburgh experienced urban development primarily driven by the presence and accessibility of natural resources, rather than favorable geographical conditions: topography characterized by rugged hills, rock formations, rivers, and stream valleys. The integration of the American-style grid within this unique natural environment resulted in intriguing juxtapositions. Consequently, elements such as bridges, viaducts, stairs, tunnels, and historical inclines gained paramount importance in shaping the urban fabric. The city’s remaining preserved or transformed urban heritage is protected through historic districts designated by the Department of City Planning, which enforces specific planning and design guidelines. The study employs a multi-faceted approach combining the concepts of historic stratification (urban palimpsest), integrated urban morphology, space syntax (integration analysis), and heritage urbanism. During the personally conducted long-term fieldwork, the selected case studies described herein (historic districts, university campus, and traditional neighborhood) proved to be the most suitable for demonstrating urban heritage formation through urban landscape transformation.
Astaxanthin Protects Against H2O2- and Doxorubicin-Induced Cardiotoxicity in H9c2 Rat Myocardial Cells
Authors: Krestinin Roman , Kobyakova Margarita , Baburina Yulia , Sotnikova Linda , Krestinina Olga
Published: November 2024

Astaxanthin (AST) is a carotenoid that has positive effects on various organs and tissues. It also exhibits a cardioprotective action. In this study, the influence of AST on the survival of H9c2 cardiomyocytes under hydrogen peroxide (H2O2)- and doxorubicin (DOX)-induced cardiotoxicity was investigated. Under these conditions, the content of cytosolic Ca2+ was measured, and changes in the area of the mitochondrial mass, as well as in the content of the voltage-dependent anion channel 1 (VDAC1), the autophagy marker LC3A/B, and the pro-apoptotic transcription factor homologous protein (CHOP), were determined. It was found that AST removed the cytotoxic effect of H2O2 and DOX, while cell survival increased, and the mitochondrial mass did not differ from the control. At the same time, a decrease in the content of cytosolic Ca2+ and the restoration of the VDAC1 level to values close to the control were observed. The restoration of the CHOP level suggests a reduction in endoplasmic reticulum (ER) stress in cells. The results allow us to consider AST as a potential agent in the prevention and/or treatment of cardiac diseases associated with oxidative stress.
Investigation of the Softening Resistance Behavior and Its Mechanism in Cu-Ni-Si Alloys with Discontinuous Precipitates
Authors: Cao Yicheng , Luo Wei , Yang Zhen , Xie Haofeng , Zhang Wenjing , Li Zengde , Peng Lijun , Zhu Yunqing , Liu Jun
Published: November 2024

In this study, isothermal annealing experiments were conducted on copper-nickel-silicon alloys containing continuous precipitates (CP) and discontinuous precipitates (DP) to investigate the effects of different types of precipitate phases on the microstructural evolution and softening temperature during annealing, as well as to analyze the differences in softening mechanisms. The experimental results revealed that the softening temperature of the CP alloy, subjected to 75% cold deformation, was 505 °C. In contrast, the DP alloy achieved softening temperatures of 575 °C and 515 °C after 75% and 97.5% cold deformation, respectively. This indicates that the DP alloy exhibits significantly superior softening resistance compared to the CP alloy, attributed to the distinct softening mechanisms of the two alloys. In the CP alloy, softening is primarily influenced by factors such as the coarsening of the precipitate phase, the occurrence of recrystallization, and the reduction in dislocation density. In the DP alloy, the balling phenomenon of the DP phase is more pronounced, and its unique microstructure exerts a stronger hindrance to dislocation and grain boundary motion. This hindrance effect reduces the extent of recrystallization and results in a smaller decrease in dislocation density. In summary, the DP alloy, due to its unique microstructure and softening mechanisms, demonstrates better softening resistance, providing higher durability and stability for high-temperature applications.
Effect of Waste PET Fiber on the Mechanical Properties and Chloride Ion Penetration of Emergency Repair Concrete for Road Pavement
Authors: Lee Su-Jin , Shin Hyungjin , Lee Han-Na , Park Sang-Hyun , Kim Hyoung-Moo , Park Chan-Gi
Published: November 2024

This study evaluated the effects of adding waste PET fibers on the mechanical properties and chloride ion penetration of latex-modified ultra-rapid hardening cement concrete used for emergency road pavement repairs. The primary experimental variable was the content of waste PET fibers. The mechanical properties of the concrete were evaluated through compressive strength, flexural strength, and splitting tensile strength tests. Its durability was evaluated through chloride ion penetration, surface resistivity, and abrasion resistance tests. The experimental results were compared with the quality standards for emergency repair concrete set by the Korea Expressway Corporation. As a result, this study has enhanced the strength and resistance to chloride ions of latex-modified concrete by incorporating waste PET fibers. In the mixture with 3.84 kg/m3 of waste PET fibers, the compressive strength was 29.9 MPa at 4 h and 42.5 MPa at 28 curing days. The flexural strength was 6.0 MPa at 4 curing hours and 7.0 MPa at 28 days, and the splitting tensile strength was 4.5 MPa at 28 days of curing. The chloride ion permeability amount and abrasion depth were 1081C and 0.82 mm, respectively. The mixture with 3.84 kg/m3 of waste PET fibers has superior compressive strength, flexural strength, splitting tensile strength, chloride ion penetration, and surface resistivity compared to the mixture with 7.68 kg/m3. This result means that the waste PET fibers caused poor dispersion and fiber-balling within the concrete, leading to loose internal void structures when incorporated at 3.84 kg/m3. However, the abrasion resistance test showed better results for the mixture with 7.68 kg/m3 of waste PET fibers than the 3.84 kg/m3 mixture. Therefore, the test results indicated that 3.84 kg/m3 of waste PET fibers is the most effective for latex-modified concrete used in emergency road pavement repairs.
Luminescence Thermometry with Eu3+-Doped Y2Mo3O12: Comparison of Performance of Intensity Ratio and Machine Learning Temperature Read-Outs
Authors: Gavrilović Tamara , Đorđević Vesna , Periša Jovana , Medić Mina , Ristić Zoran , Ćirić Aleksandar , Antić Željka , Dramićanin Miroslav D.
Published: November 2024

Accurate temperature measurement is critical across various scientific and industrial applications, necessitating advancements in thermometry techniques. This study explores luminescence thermometry, specifically utilizing machine learning methodologies to enhance temperature sensitivity and accuracy. We investigate the performance of principal component analysis (PCA) on the Eu3+-doped Y2Mo3O12 luminescent probe, contrasting it with the traditional luminescence intensity ratio (LIR) method. By employing PCA to analyze the full emission spectra collected at varying temperatures, we achieve an average accuracy (ΔT) of 0.9 K and a resolution (δT) of 1.0 K, significantly outperforming the LIR method, which yielded an average accuracy of 2.3 K and a resolution of 2.9 K. Our findings demonstrate that while the LIR method offers a maximum sensitivity (Sr) of 5‰ K⁻1 at 472 K, PCA’s systematic approach enhances the reliability of temperature measurements, marking a crucial advancement in luminescence thermometry. This innovative approach not only enriches the dataset analysis but also sets a new standard for temperature measurement precision.
Fuzzy Logic Approach for Modeling of Heating and Scale Formation in Industrial Furnaces
Authors: Krzywanski Jaroslaw , Boryca Jaroslaw , Urbaniak Dariusz , Otwinowski Henryk , Wylecial Tomasz , Sosnowski Marcin
Published: November 2024

Heating steel charges is essential for proper charge formation. At the same time, it is a highly energy-intensive process. Limiting the scale formed is critical for reducing heat consumption in this process. This paper applies fuzzy logic to model heating and scale formation in industrial re-heating furnaces. Scale formation depends on the temperature of the initial charge, heating time, excess air coefficient value, and initial scale thickness. These parameters were determined based on experimental tests, which are also the inputs in the model of the analyzed process. The research was carried out in walking beam furnaces operating in hot rolling mill departments. To minimize the excess energy consumption for heating a steel charge in an industrial furnace before forming, a heating and scale formation (HSF) model was developed using the fuzzy logic-based approach. The developed model allows for the prediction of the outputs, i.e., the charge’s final surface temperature and the scale layer’s final thickness. The comparison between the measured and calculated results shows that the model’s accuracy is acceptable.
Structural Color of Partially Deacetylated Chitin Nanowhisker Film Inspired by Jewel Beetle
Authors: Zewude Dagmawi Abebe , Akamatsu Masaaki , Ifuku Shinsuke
Published: November 2024

Nanochitin was developed to effectively utilize crab shells, a food waste product, and there is ongoing research into its applications. Short nanowhiskers were produced by sonicating partially deacetylated nanochitin in water, resulting in a significant decrease in viscosity due to reduced entanglement of the nanowhiskers. These nanowhiskers self-assembled into a multilayered film through an evaporation technique. The macro- and nanoscale structures within the film manipulate light, producing vibrant and durable structural colors. The dried cast film exhibited green and purple stripes extending from the center to the edge formed by interference effects from the multilayer structure and thickness variations. Preserving structural colors requires maintaining a low ionic strength in the dispersion, as a higher ionic strength reduces electrostatic repulsion between nanofibers, increasing viscosity and potentially leading to the fading of color. This material’s sensitivity to environmental changes, combined with chitin’s biocompatibility, makes it well-suited for food sensors, wherein it can visually indicate freshness or spoilage. Furthermore, chitin’s stable and non-toxic properties offer a sustainable alternative to traditional dyes in cosmetics, delivering vivid and long-lasting color.
Fractal Modelling of Heterogeneous Catalytic Materials and Processes
Authors: Mousa Suleiman , Rigby Sean P.
Published: November 2024

This review considers the use of fractal concepts to improve the development, fabrication, and characterisation of catalytic materials and supports. First, the theory of fractals is discussed, as well as how it can be used to better describe often highly complex catalytic materials and enhance structural characterisation via a variety of different methods, including gas sorption, mercury porosimetry, NMR, and several imaging modalities. The review then surveys various synthesis and fabrication methods that can be used to create catalytic materials that are fractals or possess fractal character. It then goes on to consider how the fractal properties of catalysts affect their performance, especially their overall activity, selectivity for desired products, and resistance to deactivation. Finally, this review describes how the optimum fractal catalyst material for a given reaction system can be designed on a computer.
Study on High-Temperature Activated Products and Hydration Properties of Aga Soil in Tibet for Cement Concrete
Authors: Li Lihui , Niu Kaiming , Ji Jianrui , Zhang Panpan , Zhang Jilin
Published: November 2024

In order to impart the properties of cementitious material to the Tibetan Agar soil, two high-temperature activation mechanisms (HTMA, HTMB) were designed in this study, and the products and hydration-hardening properties of Tibetan Agar soil high-temperature activation mechanism were analyzed by means of SEM, XRD, and XRF. The results show that the main components of Tibetan Aga soil are calcite and quartz; Aga soil is activated by HTMA high-temperature activation, forming the main products of CaO, C2S, CaSiO3, and CaAl2Si2O8, and its products have both air-hardening and water-hardening characteristics; Aga soil is activated by HTMB high-temperature activation, and when the temperature reaches 1250 °C when the clinker is not found in the CaO, the generation of C2S, C3S, C3A, C4AF, and Mg2SiO4 minerals with good water-hardening cementitious properties occurs when the temperature rises to 1350 °C, although the formation of some inert minerals that do not have the cementitious properties, but this temperature activation products of the thermodynamic properties of the best; Enhancing the value of lime saturation degree (KH) and silicon rate (SM) can promote the formation of the products of the C2S and C3S, increase the reactivity of the Aga soil activation products, and increase the hydration heat as well as compressive and flexural strength, combined with the results of the hydration heat and mechanical test, KH is recommended to be 0.9~0.94, SM is recommended to be 1.8~2.4, and alumina ratio (IM) is recommended to be 1.8~2.4 when Aga soil is used with raw materials.
Accounting of Deformation Heating During Upsetting of AMg6 Alloy
Authors: Radionova Liudmila V. , Gromov Dmitry V. , Bykov Vitaly A.
Published: November 2024

The AMg6 alloy, which belongs to the Al–Mg–Mn system, has high corrosion resistance in various environments, good weldability, and good mechanical properties. During analytical and experimental studies, it was established that the AMg6 alloy, when deformed in the temperature range of 130–175 °C, has high plastic properties and can withstand large degrees of deformation without destruction and crack formation. At the same time, its microstructure retains the texture of deformation, and the hardness of the alloy increases, which indicates its deformation hardening. The article presents the results of numerical and laboratory experiments on upsetting of 20 mm diameter workpieces from a heating temperature of 20, 130, 260 and 390 °C. Using numerical experiments, the dependences of deformation heating on the upsetting rate and the initial temperature of the workpiece were obtained. Deformation heating should be taken into account when choosing heating before deformation since it can be critical in terms of overburning and loss of plastic properties and corrosion resistance of finished products. The deformation behavior of the AMg6 alloy at a heating temperature of the workpiece up to 130–175 °C, revealed in this study, indicates the prospects for conducting additional research on the study of changes in the microstructure and mechanical properties of this alloy during warm deformation.
Mathematical Modeling and Generating Method of Hourglass Worm Gear Hob’s Rake Face Based on a Rotating Paraboloid Surface
Authors: Li Yupeng , Yang Jie , Gu Run , Chen Zhijiang , Xia Chunming
Published: November 2024

The rake angles on both sides of the cutting edges of the hourglass worm gear hob significantly influence its cutting performance, which, in turn, plays a decisive role in the surface quality of the machined worm wheel. To balance the rake angles along the tooth height direction of each hob tooth and enhance the overall cutting performance of the hob, this paper proposes a method that utilizes a rotating paraboloid surface to generate the helical rake face of the hourglass worm gear hob. First, the conjugate condition equations for the rake face generated by the rotating paraboloid surface are derived. A mathematical model for the helical rake face of planar double-enveloping hourglass worm gear hob is established. This study explores the influence of two machining parameters on the rake angle, specifically the milling drive ratio coefficient k and the geometric parameter of a parabolic milling cutter p. Through a systematic analysis of the variations in rake angle at the dividing toroidal surface and along the tooth height direction, the optimal parameter values were identified as k = 0.9115 and p = 0.6834. The results show that, after optimization, the hob rake angle range is around ±4.7°, with a maximum rake angle difference of 6.3072° along the tooth height direction, and the rake angles on both sides of the teeth are more balanced. The structure of the rake face is more reasonable, reflecting the feasibility of rotating paraboloid tools for forming tools in the machining of complex surfaces.
A Simheuristic Approach to Scheduling Sustainable and Reliable Maintenance for Bridge Infrastructure
Authors: Pastore Tommaso , Mariniello Giulio , Asprone Domenico
Published: November 2024

Designing maintenance strategies for a vast portfolio of aging infrastructures requires decision-makers to ensure adequate safety levels while addressing the requirements on service interruptions, costs, and workforce availability. This study addresses the problem of scheduling maintenance interventions for a portfolio of bridges, aiming to minimize CO2 emissions while meeting minimum reliability requirements and adhering to workforce and budget constraints. To achieve this, we present a Simheuristic algorithm that combines a metaheuristic core based on the Adaptive Large Neighborhood Search metaheuristic with a Monte Carlo simulation module. This integration allows for the evaluation of optimized scheduling solutions, accounting for the inherent randomness in the structural deterioration process. The proposed approach is tested in a comparative analysis against traditional time-based and condition-based scheduling methods. Results from diverse bridge portfolios demonstrate that the proposed algorithm offers improved performance in terms of both total costs and CO2 emissions.
Ensemble-Based Machine Learning Algorithm for Loan Default Risk Prediction
Authors: Akinjole Abisola , Shobayo Olamilekan , Popoola Jumoke , Okoyeigbo Obinna , Ogunleye Bayode
Published: November 2024

Predicting credit default risk is important to financial institutions, as accurately predicting the likelihood of a borrower defaulting on their loans will help to reduce financial losses, thereby maintaining profitability and stability. Although machine learning models have been used in assessing large applications with complex attributes for these predictions, there is still a need to identify the most effective techniques for the model development process, including the technique to address the issue of data imbalance. In this research, we conducted a comparative analysis of random forest, decision tree, SVMs (Support Vector Machines), XGBoost (Extreme Gradient Boosting), ADABoost (Adaptive Boosting) and the multi-layered perceptron, to predict credit defaults using loan data from LendingClub. Additionally, XGBoost was used as a framework for testing and evaluating various techniques. Moreover, we applied this XGBoost framework to handle the issue of class imbalance observed, by testing various resampling methods such as Random Over-Sampling (ROS), the Synthetic Minority Over-Sampling Technique (SMOTE), Adaptive Synthetic Sampling (ADASYN), Random Under-Sampling (RUS), and hybrid approaches like the SMOTE with Tomek Links and the SMOTE with Edited Nearest Neighbours (SMOTE + ENNs). The results showed that balanced datasets significantly outperformed the imbalanced dataset, with the SMOTE + ENNs delivering the best overall performance, achieving an accuracy of 90.49%, a precision of 94.61% and a recall of 92.02%. Furthermore, ensemble methods such as voting and stacking were employed to enhance performance further. Our proposed model achieved an accuracy of 93.7%, a precision of 95.6% and a recall of 95.5%, which shows the potential of ensemble methods in improving credit default predictions and can provide lending platforms with the tool to reduce default rates and financial losses. In conclusion, the findings from this study have broader implications for financial institutions, offering a robust approach to risk assessment beyond the LendingClub dataset.
Synchronization of Multi-Agent Systems Composed of Second-Order Underactuated Agents
Authors: Rehák Branislav , Lynnyk Anna , Lynnyk Volodymyr
Published: November 2024

The consensus problem of a multi-agent system with nonlinear second-order underactuated agents is addressed. The essence of the approach can be outlined as follows: the output is redesigned first so that the agents attain the minimum-phase property. The second step is to apply the exact feedback linearization to the agents. This transformation divides their dynamics into a linear observable part and a non-observable part. It is shown that consensus of the linearizable parts of the agents implies consensus of the entire multi-agent system. To achieve the consensus of the original system, the inverse transformation of the exact feedback linearization is applied. However, its application causes changes in the dynamics of the multi-agent system; a way to mitigate this effect is proposed. Two examples are presented to illustrate the efficiency of the proposed synchronization algorithm. These examples demonstrate that the synchronization error decreases faster when the proposed method is applied. This holds not only for the states constituting the linearizable dynamics but also for the hidden internal dynamics.
A Multicriteria Customer Classification Method in Supply Chain Management
Authors: Barrera Felipe , Segura Marina , Maroto Concepción
Published: November 2024

Since Kraljic’s strategic matrix was applied to supply chain management, classification of items, suppliers, and customers has become of increasing interest to research and companies. The aim of this research is to develop an easily interpretable multicriteria classification matrix method and validate it in real-world scenarios with a robustness analysis. This method assigns alternatives to one of four classes defined by critical dimensions that integrate several evaluation criteria. Initially, a global search pre-classifies the alternatives using the PROMETHEE net flows. Then, two local searches are carried out that make use of the discriminant properties of the net flow signs to improve the quality of the assignments. This approach is specifically applied to pre-classified alternatives near the boundary between two or more categories. The method has been validated by segmenting thousands of customers. Four customer segments were identified: strategic, collaborative, transactional, and non-preferred. A comparison was made between the results and those derived from an alternative method. Through an extensive sensitivity analysis, the proposed method was shown to be robust to parameter variation, highlighting its reliability in real dynamic contexts. The method provides valuable, easily interpretable information, which constitutes the basis for developing personalised strategies to enhance customer relationship management.