bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical Simulation of the 65Mn-Cr Steel Slab Solidification Process and Analysis of the Formation Mechanism of Internal Cracks
Authors: Zhang Li , Xu Lijun , Zhang Guifang , Zhang Haibo , Jiang Qi , Yin Shubiao
Published: February 2025

There are still internal defects such as triangular zone cracks, centerline cracks, and intermediate cracks in 65Mn-Cr steel during the production process, which mostly occur in the initial solidification. In order to explore the evolution of intermediate cracks during the initial solidification process of 230 mm × 1255 mm slab 65Mn-Cr steel, this study was based on a combination of numerical simulation and experiment, using COMSOL numerical simulation software to establish a flow and heat transfer coupling model and stress model, and carried out simulation research. The results show that the solidification speed of slab 65Mn-Cr steel is different at different positions from the meniscus. At the position where the reheating occurs, the heat transfer speed from the solidification front to the surface of the slab slows down, but the solidification speed varies in different areas of the section. At the same time, the flow field, temperature field, and cross-sectional stress and strain field are all non-uniformly distributed, and the maximum plastic strain value exceeds the critical strain 0.004. The experimental results show that internal cracks occur within the range of 9–35 mm below the surface. This shows that the intermediate crack defects of 65Mn-Cr steel are easily caused by stress and strain. Adjusting the spray distribution and cooling intensity of the spray water in the secondary cooling section can be a feasible solution to reduce the occurrence of internal cracks.
Effects of Steel Slag, Desulfurization Gypsum, and Ground Granulated Blast-Furnace Slag on the Characterization of Recycled Cement-Stabilized Macadam
Authors: Tan Haoyu , Ji Henggang , Yuan Peilong , Fan Xiang
Published: February 2025

Steel slag powder (SS), ground granulated blast-furnace slag (GGBS), and flue gas desulfurization gypsum (FDG) are environmentally friendly and cost-effective substitute materials for ordinary Portland cement (OPC). This study investigated the use of industrial solid wastes, including SS, GGBS, and FDG, as auxiliary materials in OPC to stabilize pretreated recycled concrete aggregate (pretreated RCA). The use of pretreated RCA, mixed cementitious materials, and water at the optimum content created a mixture designated recycled cement-stabilized macadam (RCSM). A series of mechanical tests were conducted to clarify the performance of the RCSM, and microscopic tests were performed to elucidate the microcharacteristics of the mixed cementitious materials. With a curing time from 3 days to 28 days, the unconfined compression strength (UCS) of the mixed cementitious materials (A4) composed of SS, GGBS, FDG, and OPC increased by 5.94–10.79% compared with that of the cementitious material of OPC (A0). The UCS of the mixture composed (C4) of SS, GGBS, FDG, OPC, and pretreated RCA was greater than that of the mixture composed (C0) of OPC and RCA from 7 days to 90 days, increasing by 4.26–8.35%. The total drying shrinkage coefficient of C4 was lower than that of C0, whereas the temperature shrinkage coefficient of C4 was higher than that of C0, indicating that the use of A4 can effectively reduce drying shrinkage cracking in C4. The hydration products of A4 primarily consisted of flocculent calcium silicate hydrate (C-S-H) gel, fibrous calcium aluminate hydrate gel, and needle-like ettringite crystals. The interlocked growth of C-S-H gel and ettringite crystals continued and promoted an increase in the UCS of the cementitious system. The test results provide a reference for the application of similar materials.
Assessment of Mechanical and Ecotoxicological Properties of Mortar with Wood Waste Biochar as Partial Cement Replacement
Authors: Legan Maša , Štukovnik Petra , Zupan Klementina , Žgajnar Gotvajn Andreja
Published: February 2025

For several decades, cement production has caused concerns about CO2 emissions. As the production of concrete has increased over the years, the fact that cement is its key component additionally raises a concern. By partially replacing cement with waste material such as biomass waste biochar, the reduction in waste and the reduction of CO2 emissions could be addressed at the same time but raises a concern about the ecotoxicological potential of biochar-containing cementitious composites. During their use, recycling and disposal of biochar-containing mortars could pose hazardous environmental impacts due to their exposure to rain and other environmental conditions. The aim of the study was to determine the early-age mechanical properties of mortars with 5%, 10%, and 15% biochar as partial cement replacement. The environmental impact of biochar-containing mortars in terms of carbon footprint reduction and ecotoxicological potential was addressed simultaneously. The biochar used was prepared from waste wood biomass as carpentry waste wood. Results showed that added biochar caused no significant changes in flowability and fresh density of fresh mortar mixture. The strength tests revealed mortars with 5% and 10% biochar had higher 3-day flexural strength, while only mortar with 5% biochar had higher 7- and 28-day compressive strength (4% and 6%) than the conventional mortar. The X-ray diffraction (XRD) analysis detected five main crystalline phases in biochar-containing mortars. SEM-EDS showed the strong embedment of biochar particles in cement paste. Ecotoxicological assessment based on acute toxicity tests with mortar leachates using duckweed and mustard seeds showed low toxicity of leachates with the highest inhibition values around 50%. The calculations of the total CO2-equivalent emissions for selected mortars revealed mortars with biochar as partial cement replacement had lower CO2-equivalent emissions than the conventional mortar and can contribute to carbon footprint reduction and at the same time to natural resource conservation.
Impact of Deep Cryogenic Treatment on X210CrW12 Steel’s Wear Behavior and Microstructural Characteristics
Authors: Özbek Onur , Altan Özbek Nursel
Published: February 2025

In this work, the microstructure, hardness, tensile and yield strength, and wear resistance of X210CrW12 steel are examined in relation to the impacts of deep cryogenic treatment. In order to achieve this, deep cryogenic treatment at −180 °C was applied to X210CrW12 steel samples for 12, 18, 24, and 36 h following quenching. Following the cryogenic treatments, a tempering heat treatment was applied to the samples at 300 °C for two hours. Experimental results showed that deep cryogenic treatment significantly improved the mechanical properties of X210CrW12 steel. The best mechanical properties were obtained after applying deep cryogenic treatment for 24 and 36 h. The cryogenic treatment showed the most dominant effect on wear resistance. As a result of the wear tests performed with the pin-on-disk method, it was determined that the wear rate of the sample subjected to cryogenic treatment for 36 h was 59.37% less than that of the conventionally hardened sample. The deep cryogenic treatment applied for 36 h provided the highest hardness increase of 12.06%. Compared to the conventionally hardened sample, the tensile and yield strength in the steel subjected to deep cryogenic treatment for 24 h is up to 11.02% and 11.35% higher. As a result of microstructural analysis, it was determined that it provides cryogenic new carbide precipitation, increases carbide density, and provides a more homogeneous carbide distribution.
Advanced Tax Fraud Detection: A Soft-Voting Ensemble Based on GAN and Encoder Architecture
Authors: Alrasheedi Masad A. , Ijaz Samia , Alrashdi Ayed M. , Lee Seung-Won
Published: February 2025

The world prevalence of the two types of authorized and fraudulent transactions makes it difficult to distinguish between the two operations. The small percentage of fraudulent transactions, in turn, gives rise to the class imbalance problem. Hence, an adequately robust fraud detection mechanism must exist for tax systems to avoid their collapse. It has become significantly difficult to obtain any dataset, specifically a tax return dataset, because of the rising importance of privacy in a society where people generally feel squeamish about sharing personal information. Because of this, we arrive at the decision to synthesize our dataset by employing publicly available data, as well as enhance them through Correlational Generative Adversarial Networks (CGANs) and the Synthetic Minority Oversampling Technique (SMOTE). The proposed method includes a preprocessing stage to denoise the data and identify anomalies, outliers, and dimensionality reduction. Then the data have undergone enhancement using the SMOTE and the proposed CGAN techniques. A unique encoder design has been proposed, which serves the purpose of exposing the hidden patterns among legitimate and fraudulent records. This research found anomalous deductions, income inconsistencies, recurrent transaction manipulations, and irregular filing practices that distinguish fraudulent from valid tax records. These patterns are identified by encoder-based feature extraction and synthetic data augmentation. Several machine learning classifiers, along with a voting ensemble technique, have been used both with and without data augmentation. Experimental results have shown that the proposed Soft-Voting technique outperformed the original without an ensemble method.
Volume-Increasing Inextensional Deformations of Platonic Polyhedra
Authors: Lengyel András
Published: February 2025

It is known that the volume of a convex polyhedron can be increased by suitable isometric deformation of its surface resulting in a non-convex shape. Deformation patterns and the associated enclosed volumes of the Platonic polyhedra were theoretically and numerically investigated by a few authors in the past. In this paper, a generic diamond-shaped folding pattern for all Platonic polyhedra is presented, optimised to achieve the maximum enclosed volumes. The numerically obtained volume increases (44.70%, 25.12%, 13.86%, 10.61%, and 4.36% for the regular tetrahedron, cube, octahedron, dodecahedron, and icosahedron, respectively) improve the existing results (44.00%, 24.62%, 13.58%, 9.72%, and 4.27%, respectively). Quasi-rigid inflatable membrane representations of such deformed polyhedra imply a significant change of structural shape due to initial inflation and subsequent compressive stresses transverse to the crease lines.
Digital Watermarking Technology for AI-Generated Images: A Survey
Authors: Luo Huixin , Li Li , Li Juncheng
Published: February 2025

The rapid advancement of AI-generated content (AIGC) has significantly improved the realism and accessibility of synthetic images. While large image generation models offer immense potential in creative industries, they also introduce serious challenges, including copyright infringement, content authentication, and the traceability of generated images. Digital watermarking has emerged as a promising approach to address these concerns by embedding imperceptible yet detectable signatures into generated images. This survey provides a comprehensive review of three core areas: (1) the evolution of image generation technologies, highlighting key milestones such as the transition from GANs to diffusion models; (2) traditional and state-of-the-art digital image watermarking algorithms, encompassing spatial domain, transform domain, and deep learning-based approaches; (3) watermarking methods specific to AIGC, including ownership authentication of AI model and diffusion model, and watermarking of AI-generated images. Additionally, we examine common performance evaluation metrics used in this field, such as watermark capacity, watermark detection accuracy, fidelity, and robustness. Finally, we discuss the unresolved issues and propose several potential directions for future research. We look forward to this paper offering valuable reference for academics in the field of AIGC watermarking and related fields.
Editorial for the Special Issue “Novel Echocardiographic Techniques for the Assessment of Cardiovascular Disease”
Authors: Katogiannis Konstantinos
Published: February 2025

The global burden of cardiovascular disease (CVD) continues to pose a significant challenge to healthcare systems worldwide [...]
Effect of Porosity on the Corrosion Behavior of FeCoNiMnCrx Porous High-Entropy Alloy in 3.5 Wt.% NaCl Solution
Authors: Wang Ying , Chen Shuobin , Peng Yuhua , Zheng Xijie , Li Dong , Nie Cheng , Gong Pan , Hu Zhigang , Ma Ming
Published: February 2025

The effects of different Cr contents on the corrosion resistance of FeCoNiMnCrx (x = 0.5;1;1.5) porous high-entropy alloys (HEAs) in 3.5 wt.% NaCl solution on corrosion resistance was investigated. With the increase in Cr content, the total porosity and permeability of the porous HEA increased. The increase in porosity improves the interconnectivity between the pores and enhances the contact area with the corrosion solution. The pore-making mechanism is mainly a powder compaction, and Kirkendall holes are caused by different elements due to different diffusion rates. With the increase in Cr content, the icorr increases, and the Ecorr decreases in the porous HEAs of FeCoNiMnCrx (x = 0.5;1;1.5). The corrosion resistance of FeCoNiMnCrx (x = 0.5;1;1.5) porous HEAs decreases with the increase in the Cr element. With the increase in Cr content, the weight gain rate of FeCoNiMnCrx porous HEA increases gradually after immersion for 168 h, and the average pore size and permeability of the sample decrease gradually. The corrosion resistance of FeCoNiMnCrx porous HEA decreases with increasing Cr content.
Dynamics Research of the Hopfield Neural Network Based on Hyperbolic Tangent Memristor with Absolute Value
Authors: Gao Huiyan , Xu Hongmei
Published: February 2025

Neurons in the brain are interconnected through synapses. Local active memristors can both simulate the synaptic behavior of neurons and the action potentials of neurons. Currently, the hyperbolic tangent function-type memristors used for coupling neural networks do not belong to local active memristors. To take advantage of local active memristors and consider the multi-equilibrium point problem, a cosine function is introduced into the state equation, resulting in the design of an absolute value hyperbolic tangent-type double local active memristor, and it is used as a coupling synapse to replace a synaptic weight in a 3-neuron HNN. Then, basic dynamical analysis methods are used to study the effects of different memristor synapse coupling strengths and different initial conditions on the dynamics of the neural network. The research results indicate that dynamical behavior of memristor Hopfield neural network is closely related to the synaptic coupling strengths and the initial conditions, and this neural network exhibits rich dynamical behaviors, including the coexistence of chaotic and periodic attractors, super-multistability phenomena, etc. Finally, the neural network was implemented using an FPGA development board, verifying the hardware feasibility of this system.
Fabrication and Characterization of a Flexible Polyurethane-Based Triboelectric Nanogenerator for a Harvesting Energy System
Authors: Ejaz Saba , Shah Imran , Aziz Shahid , Hassan Gul , Shuja Ahmed , Khan Muhammad Asif , Jung Dong-Won
Published: February 2025

Powering wearable and portable devices, triboelectric nanogenerators (TENGs) are a considerably promising technology. Low-cost production, ease of fabrication, optimal efficiency, and high output performance are always key concerns in developing energy harvesting technologies. Optimum efficiency and high output are always key concerns. This research addresses the ongoing challenge of raising efficient, flexible, and lightweight energy harvesting systems for recent wearable technologies. In this research, a triboelectric nanogenerator is proposed for harvesting the triboelectric effect. Using polyurethane (PU), a bendable TENG that is in the vertical contact separation mode was developed. UV-curable PU forms the basis of TENGs. A sponge, repurposed from landfill waste, acts by means of a spacer to maintain a consistent air gap between the tribo-layers for enhanced triboelectrification. The triboelectric nanogenerators formed a Voc approaching 500 V and a current of ~2 µA and also showed high performance with a power density of 8.53 W/m2. In addition, the triboelectric nanogenerator can light LEDs and charge capacitors, making it a self-powered energy source for portable devices, Wi-Fi, and monitoring systems. The proposed TENG provides a capable solution for sustainable, self-powered wearable electronics and has the potential for further development in energy-efficient and eco-friendly applications.
Implementation of Antimicrobial Stewardship Programs in Saudi Arabia: A Systematic Review
Authors: Alshehri Abdullah , Aldali Jehad , Abdelhamid Maysoon , Alanazi Alaa , Alhuraiz Ratal , Alanazi Lamya , Alshmrani Meaad , Alqahtani Alhanouf , Alrshoud Maha , Alharbi Reema
Published: February 2025

Background: Antimicrobial resistance has highlighted the need for effective infectious disease strategies. Antimicrobial stewardship programs (ASPs) may reduce antibiotic resistance, adverse reactions, and treatment failures. This systematic review examines ASPs in Saudi Arabia, assessing their efficacy, challenges, and outcomes to improve antimicrobial use and patient care. Methods: Searches were carried out in the Ovid, MEDLINE, Embase, PsycInfo, Scopus, and Web of Science Core Collection databases for studies published from 2007 to July 2024, in Saudi Arabia, following the PRISMA guidelines. Studies that assessed ASPs’ implementation, effectiveness, and outcomes in hospital settings were included. Results: Out of the 6080 titles identified, 14 studies met the inclusion criteria, covering different regions of the country, including Riyadh, Jeddah, Dhahran, Makkah, Al-Kharj, and a multi-regional study in Qassim and Riyadh. Various interventions were implemented by the ASPs, such as educational programs, audit and feedback, switching from intravenous to oral administration, and enhanced policies. These interventions collectively led to a decrease in the overall antimicrobial consumption and cost, and a reduction in cases with multidrug-resistant bacteria. Conclusions: The findings of this review highlight the positive impact of ASPs in Saudi Arabia. However, addressing challenges such as data limitations and training gaps is essential to enhance their effectiveness. Expanding education and refining implementation strategies are crucial for ensuring their long-term success.
Sources and Enrichment Mechanisms of Rare-Earth Elements in the Mosuoying Granites, Sichuan Province, Southwest China
Authors: Xiao Xuepeng , Li Guoxin , Dong Shuyi , Qian Lijun , Ou Lihua
Published: February 2025

Ion-adsorption-type rare-earth element (iREE) deposits, a primary source of global heavy REE (HREE) ores, have attracted wide attention worldwide due to their concentrated distributions and irreplaceable role in the field of cutting-edge technologies. In recent years, iREE mineralization has been reported in the overlying weathering crust of the Mosuoying granites within the Dechang counties, Sichuan Province, Southwest China, suggesting great potential for the formation of iREE deposits. The Mosuoying granites, acting as the primary carrier of REE pre-enrichment, govern the contents and distribution patterns of REEs in their weathering crust. Therefore, investigating the sources and enrichment mechanisms of REEs in the parent rocks will provide a critical theoretical basis for the scientific exploitation and utilization of iREE deposits. In this study, we investigated the migration and enrichment of REEs in the Mosuoying granites (850–832 Ma) using petrography, geochronology, geochemical, and Sr-Nd-Hf isotopic data. The results reveal that the REE enrichment in the Mosuoying granites might be associated with both the melting of crustal felsic rocks and the magmatic-hydrothermal evolution. On the one hand, the granites exhibit different REE patterns. Compared to the light REE (LREE)-rich granites, the HREE-rich granites feature higher SiO2 contents, higher differentiation index (DI), lower Nb/Ta and Zr/Hf ratios, and more significant negative Eu anomalies, indicating that the crystal fractionation of magmas governed the differentiation of REEs. Furthermore, the hydrothermal fluids further promoted the formation of the HREE-rich granites. On the other hand, the geochemical characteristics suggest that they are A-type granites. Regarding the isotopic characteristics, the Mosuoying granites exhibit negative whole-rock εNd(t) and zircon εHf(t) values, suggesting an evolved crustal source. Therefore, we suggest that the high REE contents in the Mosuoying A-type granites might originate from the partial melting of felsic rocks in a shallow crustal source under high-temperature and low-pressure conditions. Specifically, the high-temperature A-type granitic magmas caused the partial melting of the felsic crustal materials to release REEs; concurrently, these magmas enhanced the solubility of REEs in melt during magmatic evolution, inhibiting the separation of REE-bearing minerals from the melts. These increased the REE contents of the granites. The high-temperature heat source might be associated with the process where the asthenospheric mantle experienced upwelling along slab windows and heated continental crust in the Neoproterozoic extensional setting.
Two-Dimensional Carbon Film-Supported ZnS Nanocomposites Obtained from Thermal Decomposition of Organic Zinc Salts and Sulfidation Reactions for Lithium Storage
Authors: Wei Denghu , Wang Ting , Jiao Ranran , Qu Lixue , Zeng Suyuan
Published: February 2025

This article reports a general method for carbon-composited ZnS nanoparticles. By mixing thiourea with an appropriate amount of citric acid zinc, glycine zinc, lactate zinc, and gluconate zinc, respectively, and then heating at 700 °C under a nitrogen atmosphere for 4 h, four types of target product ZnS/C were obtained. Thiourea and organic zinc salts serve as reactants, providing zinc, sulfur, and carbon sources. During the thermal decomposition process, sulfidation and carbonization can be completed simultaneously. As an anode material for lithium-ion batteries, all four products exhibit excellent lithium storage performance. The two-dimensional carbon film can, on the one hand, enhance the conductivity of the material, and on the other hand, act as a carrier for ZnS particles, effectively cushioning the volume deformation of ZnS during the lithiation process.
The Effect of Farming Systems and Cultivars on the Qualitative and Quantitative Composition of Bioactive Compounds in Winter Wheat (Triticum aestivum L.)
Authors: Kowalska Iwona , Soluch Agata , Mołdoch Jarosław , Jończyk Krzysztof
Published: February 2025

Triticum aestivum L. subsp. spelta (cv. Rokosz) and common winter wheat Triticum aestivum L. subsp. aestivum (cv. Arktis, Belissa, Estivus, Fidelius, Hondia, Jantarka, KWS Ozon, Linus, Markiza, Ostka Strzelecka, Pokusa) grown in an organic farming system were analyzed and compared. Furthermore, the productivity of four common wheat cultivars (cv. Fidelius, Hondia, Jantarka, KWS Ozon) grown under four different (organic, conventional integrated, and monoculture) farming systems was compared. Using UPLC-DAD-MS, UPLC-PDA-MS/MS, and TLC-DPPH•, nine phenolic acids, nine alkylresorcinols, and their antiradical activity were identified and quantified. In the organic farming system, the highest yield was observed for T. aestivum L. subsp. aestivum cv. Fidelius (4.17 t/ha). Infections of wheat cultivars were low or at a medium level. The highest resistance to Fusarium fungi was shown by cv. Fidelius, which also exhibited the highest alkylresorcinol content and antioxidant capacity. The total phenolic acid content was highest in cv. Rokosz (1302.3 µg/g), followed by common winter wheat cultivars cv. Linus (1135.1 µg/g) and cv. Markiza (1089.6 µg/g). The potential of winter wheat cultivars for human health and their suitability for cultivation in different production systems was determined, showing significant differences in bioactive compounds depending on cultivars, systems, and years.
Design, Synthesis and Biological Activity Study of γ-Aminobutyric Acid (GABA) Derivatives Containing Bridged Bicyclic Skeletons as BCAT1 Inhibitors
Authors: Luo Wen , Pan Zilu , Zhu Xinyuan , Li Yan , Li Yong , Zhang Yudi , Pan Jiamin , Ding Jian , Xie Hua , Zhao Guilong
Published: February 2025

Branched-chain amino acid aminotransferases (BCATs), existing as the two isoforms BCAT1 and BCAT2, are responsible for the catabolism of branched-chain amino acids (BCAAs) and are highly upregulated and implicated in a diverse range of cancers. BCAT1 inhibitors represent a potential class of therapeutic agents for cancers; however, none have yet progressed to clinical development. Our earlier research identified WQQ-345 as a novel BCAT1 inhibitor featuring a unique bridged bicyclic skeleton and demonstrating both in vitro and in vivo antitumor activity against tyrosine kinase inhibitor (TKI)-resistant lung cancer with high BCAT1 expression. In the present study, we proceeded to modify the structure of WQQ-345 by two-round structure–activity relationship (SAR) exploration, leading to the discovery of a bicyclo[3.2.1]octene-bearing GABA derivative 7. Compound 7 exhibited a 6-fold enhancement in BCAT1 enzymatic inhibitory activity compared to the parent compound WQQ-345 and could effectively suppress the growth of 67R cells that highly expressed BCAT1 and was resistant to third-generation TKIs. GABA derivatives are an important chemical class of BCAT1 inhibitors, and therefore, the findings in the present study represent great progress both in the discovery of potent BCAT1 inhibitors with new chemical structures and in the treatment of cancer resistance.
From Waste to Value: Solubility and Dissolution Enhancement of Bioactive Extracts from Olive Leaves Using Poloxamers
Authors: Wasim Muhammad , Bergonzi Maria Camilla
Published: February 2025

The European Union, producing over 2.5 billion tons of waste annually, has prompted the European Parliament to implement legal measures and encourage the shift towards a circular economy. Millions of tons of biowaste from olive plant leaves are generated annually, resulting in environmental and economic challenges. To address this, the biowaste of olive leaves was valorized, resulting in the extraction of valuable components, triterpenes and polyphenols, which hold potential pharmaceutical, food, or cosmetic applications. Our research involved the formulation of a triterpene extract (TTP70, 70% triterpenes) as a solid dispersion using Poloxamer-188 (P188) and Poloxamer-407 (P407). The solid dispersions were prepared using a kneading method and various extract-to-polymer weight ratios, including 1:1, 1:2, and 1:5. The influence of hydrophilic carriers on the solubility, dissolution profile, and in vitro passive permeability of TTP70 was evaluated. Both carriers and all considered weight ratios significantly improved the solubility of hydrophobic extract and the dissolution of triterpenes. PAMPA experiments demonstrated the efficacy of the formulation in improving the passive permeation of triterpenes. Subsequently, the solid dispersions were physically mixed with a polyphenol-enriched extract (OPA40, 49% of polyphenols) also obtained from olive leaves, and they were used to fill hard gelatin capsules and produce an oral dosage form. The composite formulations improved the dissolution of both classes of constituents.
Carbonylation of Polyfluorinated Alkylbenzenes and Benzocycloalkenes at the Benzyl C-F and C-Cl Bonds Under the Action of CO/SbF5
Authors: Zonov Yaroslav V. , Wang Siqi , Komarov Vladislav V. , Karpov Victor M. , Parkhomenko Dmitriy A. , Mezhenkova Tatyana V.
Published: February 2025

The carbonylation at the benzyl C-Hal bonds (Hal = F, Cl) of a number of polyfluorinated alkylbenzenes and benzocycloalkenes using carbon monoxide in the presence of SbF5 is described. The reaction provided the corresponding α-arylcarboxylic acids or their methyl esters following aqueous or methanol treatment. The products of double carbonylation were obtained from bis(chloromethyl)tetrafluorobenzenes and benzal fluorides. For benzal chloride derivatives, the possibility of selective mono- or dicarbonylation was shown to depend on the amount of antimony pentafluoride. In the case of polyfluorinated secondary benzyl halides with a hydrogen atom at the α-carbon atom and vicinal fluorine atoms, the addition of CO was found to be accompanied by the elimination of HF, resulting in α,β-unsaturated α-arylcarboxylic acids. The double elimination of HF during the carbonylation of 1,4-dichloro-2,2,3,3,5,6,7,8-octafluorotetralin yielded dimethyl perfluoronaphthalene-1,4-dicarboxylate.
Phytochemical Analysis and Allelopathic Potential of an Aggressive Encroacher Shrub, Euryops floribundus (Asteraceae)
Authors: Gxasheka Masibonge , Mbita Zukile , Laka Kagiso , Mndela Mthunzi , Dlamini Phesheya
Published: February 2025

Euryops floribundus is an encroaching shrub species that poses a threat to grassland diversity and productivity in the Eastern Cape region of South Africa. This shrub inhibits understory herbaceous plant recruitment and establishment, thereby exposing soils to erosion, owing potentially to toxins it secretes. However, the allelochemicals of E. floribundus and their potential effects on the germination and establishment of plants remains poorly understood. We investigated the phytochemical classes of leaves and twigs of E. floribundus and evaluated the effects of extracts from these plant parts on seed germination and seedling growth of Lactuca sativa through a laboratory experiment. In the laboratory, we analysed phytochemicals in leaf and twig extracts and tested their allelopathic effects on Lactuca sativa seed germination and growth using the Petri dish method. In this proof-of-concept study, we identified 12 phytochemical classes of E. floribundus. Quantitative analysis showed that the leaves had significantly higher levels of flavonoids, phenolics, and tannins than twigs. As a result, leaf extracts caused 100% inhibition of seed germination, while twig extracts inhibited seed germination by 90% at 50 g L−1. Both leaf and twig extracts also significantly reduced radicle and plumule growth, with a stronger effect observed from the leaves than twigs. This study provides new insights into the phytochemical composition and strong allelopathic potential of E. floribundus, contributing to a better understanding of the mechanisms driving its encroachment in semi-arid grasslands.
Comprehensive Comparison and Validation of Forest Disturbance Monitoring Algorithms Based on Landsat Time Series in China
Authors: Liang Yunjian , Shang Rong , Chen Jing M. , Lin Xudong , Li Peng , Yang Ziyi , Fan Lingyun , Xu Shengwei , Lin Yingzheng , Chen Yao
Published: February 2025

Accurate long-term and high-resolution forest disturbance monitoring are pivotal for forest carbon modeling and forest management. Many algorithms have been developed for this purpose based on the Landsat time series, but their nationwide performance across different regions and disturbance types remains unexplored. Here, we conducted a comprehensive comparison and validation of six widely used forest disturbance- monitoring algorithms using 12,328 reference samples in China. The algorithms included three annual-scale (VCT, LandTrendr, mLandTrendr) and three daily-scale (BFAST, CCDC, COLD) algorithms. Results indicated that COLD achieved the highest accuracy, with F1 and F2 scores of 81.81% and 81.25%, respectively. Among annual-scale algorithms, mLandTrendr exhibited the best performance, with F1 and F2 scores of 73.04% and 72.71%, and even outperformed the daily-scale BFAST algorithm. Across China’s six regions, COLD consistently achieved the highest F1 and F2 scores, showcasing its robustness and adaptability. However, regional variations in accuracy were observed, with the northern region exhibiting the highest accuracy and the southwestern region the lowest. When considering different forest disturbance types, COLD achieved the highest accuracies for Fire, Harvest, and Other disturbances, while CCDC was most accurate for Forestation. These findings highlight the necessity of region-specific calibration and parameter optimization tailored to specific disturbance types to improve forest disturbance monitoring accuracy, and also provide a solid foundation for future studies on algorithm modifications and ensembles.
BIM-Based Trajectory Planning for Unmanned Aerial Vehicle-Enabled Box Girder Bridge Inspection
Authors: Shu Jiangpeng , Xia Zhe , Gao Yifan
Published: February 2025

Inspection is essential for bridge maintenance and has been supplemented by the use of unmanned aerial vehicle (UAV) photogrammetry. However, a review of the literature reveals that existing approaches require the intervention of a human operator to select waypoints in digital twin environments. Thus, existing studies are limited by either manual or semi-automatic control restrictions on UAV navigation settings, which is the main motivation for our work. This research developed a building information modelling (BIM)-based trajectory planning approach to enable fully autonomous UAV navigation for box girder bridge inspection, where the UAV follows a predetermined sequence to traverse the environmental space of a box girder bridge. The approach reflects the geometry properties of box girders as inspection characteristics and is designed with algorithms to determine a mathematical relationship between the box girders’ coordinates and inspection sequences. Field testing of the approach shows that it has satisfactory performance in terms of (1) navigation efficiency, (2) reasonableness of the sequence determined for trajectory feature points, (3) trajectory closeness and deviation, and (4) trajectory smoothness. Its satisfactory performance supports the practicability of fully autonomous UAV-enabled bridge inspection.
A Multi-Scale Self-Supervision Approach for Bearing Anomaly Detection Using Sensor Data Under Multiple Operating Conditions
Authors: Dai Zhuoheng , Jiang Lei , Li Feifan , Chen Yingna
Published: February 2025

Early fault detection technologies play a decisive role in preventing equipment failures in industrial production. The primary challenges in early fault detection for industrial applications include the severe imbalance of time-series data, where normal operating data vastly outnumber anomalous data, and in some cases, anomalies may be virtually absent. Additionally, the frequent changes in operational modes during machinery operation further complicate the detection process, making it difficult to effectively identify faults across varying conditions. This study proposes a bearing early anomaly detection method based on contrastive learning and reconstruction approaches to address the aforementioned issues. The raw time-domain vibration data, which were collected from sensors mounted on the bearings of the machinery, are first preprocessed using the Ricker wavelet transform to effectively remove noise and extract useful signal components. These processed signals are then fed into a BYOL-based contrastive learning network to learn more discriminative global feature representations. In addition, we design the reconstruction loss to complement contrastive learning. By reconstructing the masked original data, the reconstruction loss forces the model to learn detailed information, thereby emphasizing the preservation and restoration of local details. Our model not only eliminates the reliance on negative samples found in mainstream unsupervised methods but also captures data features more comprehensively, achieving superior fault detection accuracy under different operating conditions compared to related methods. Experiments on the widely used CWRU multi-condition-bearing fault dataset demonstrate that our method achieves an average fault detection accuracy of 96.97%. Moreover, the experimental results show that on the full-cycle IMS dataset, our method detects early faults at least 2.3 h earlier than the other unsupervised methods. Furthermore, the validation results for the full-cycle XJTU-SY dataset further demonstrate its excellent generalization ability.
Development of an Internet of Things-Based Ultra-Pure Water Quality Monitoring System
Authors: Öztürk Mehmet Akif , Ünsal Emre , Yelkuvan Ahmet Fırat
Published: February 2025

Monitoring ultra-pure water quality is crucial in dialysis centers and medical laboratories as even minor impurities can significantly impact health and diagnostic accuracy. In addition, the semiconductor industry needs and uses a significant amount of ultra-pure water. This study introduces an Internet of Things-based system for real-time monitoring and analysis of ultra-pure water conductivity, temperature, and other key parameters. The proposed system integrates a high-precision conductivity sensor, an ESP32 microcontroller, and a web-based interface to enable remote data access and visualization. Data transmission is through wireless communication, and values are stored on a web-based server for long-term analysis. Rigorous tests conducted at Sivas Numune Hospital validated the system’s reliability, accuracy, and ability to maintain stringent ultra-pure water quality standards. This robust and cost-effective monitoring solution addresses the limitations of conventional systems and provides real-time insights, ensuring consistent water quality for sensitive medical applications.
Design, Implementation and Practical Evaluation of an Opportunistic Communications Protocol Based on Bluetooth Mesh and libp2p
Authors: Niebla-Montero Ángel , Froiz-Míguez Iván , Fraga-Lamas Paula , Fernández-Caramés Tiago M.
Published: February 2025

The increasing proliferation of Internet of Things (IoT) devices has created a growing need for more efficient communication networks, especially in areas where continuous connectivity is unstable or unavailable. Opportunistic networks have emerged as a possible solution in such scenarios, allowing for intermittent and decentralized data sharing. This article presents a novel communication protocol that uses Bluetooth 5 and the libp2p framework to enable decentralized and opportunistic communications among IoT devices. The protocol provides dynamic peer discovery and decentralized management, resulting in a more flexible and robust IoT network infrastructure. The performance of the proposed architecture was evaluated through experiments in both controlled and industrial scenarios, with a particular emphasis on latency and on the impact of the presence of obstacles. The obtained results show that the protocol has the ability to improve data transfer in environments with limited connectivity, making it adequate for both urban and rural areas, as well as for challenging environments such as shipyards. Moreover, the presented findings conclude that the protocol works well in situations with minimal signal obstruction and short distances, like homes, where average latency values of about 8 s have been achieved with no losses. Furthermore, the protocol can also be used in industrial scenarios, even when metal obstacles increase signal attenuation, and over long distances, where average latency values of about 8.5 s have been obtained together with packet losses of less than 5%.
Sensitivity-Enhanced Temperature Sensor Based on PDMS-Coated Mach–Zehnder Interferometer
Authors: Yang Wenlei , Li Le , Zhang Shuo , Tian Ke
Published: February 2025

A sensitivity-enhanced temperature sensor based on a Mach–Zehnder interferometer (MZI) coated by polydimethylsiloxane (PDMS) film is proposed and investigated. The MZI with a compact size of 2.28 mm is fabricated by embedding a tapered single-mode fiber (SMF) between two multimode fibers (MMFs). Since PDMS has a higher thermo-optical coefficient than silica, the proposed sensor has better temperature sensing performance than the case without PDMS coating, which is demonstrated by simulation and experiment. The experimental results show that the sensitivity of the proposed sensor is as high as −1.06 nm/°C in the range from −5 °C to 45 °C.
Adaptive Exposure Control for Line-Structured Light Sensors Based on Global Grayscale Statistics
Authors: Li Yuehua , Zhao Qingfeng , Hu Po , Zhang Hao , Zhang Ziheng , Liu Xiaohong , Zhou Jingbo
Published: February 2025

Stripe images are crucial for ensuring the measurement quality of line-structured light sensors. To improve the measurement effectiveness of objects with different shapes, materials, and colors, an adaptive exposure method is proposed based on global grayscale statistical analysis of stripe images. The logarithm sum of grayscale statistical results is calculated as the quality evaluation parameter for each stripe image. Theoretical analysis and experiments demonstrate that the proposed quality evaluation value exhibits an approximate linear relationship with a camera’s exposure time. Subsequently, an adaptive exposure control method is developed. The influence of control system parameters on measurement results is also analyzed in detail. The experimental results show that our method can adaptively adjust a camera’s exposure time according to different surface characteristics. Both the number of effective measurement points and the accuracy are improved.
Design of Electronic Nose Based on MOS Gas Sensors and Its Application in Juice Identification
Authors: Zhang Yafei , Zhao Yongli , Jiang Feiyang , Lai Rongjie
Published: February 2025

Due to its advantages of fast response, low cost, low power consumption, and easy integration, Metal Oxide Semiconductor (MOS) gas sensor is widely used in the electronic nose system (E-nose). However, the MOS sensor has cross-sensitivity to different gases, which can impair the performance of the E-nose. Another key factor affecting the E-nose performance is the extraction method of gas features. In order to overcome the above shortcomings, an E-nose system that can modulate the operating temperature of gas sensors during the gas detection was designed in this paper, and a new gas feature extraction algorithm named Boruta-Recursive Feature Elimination (Boruta-RFE) was proposed based on the designed system. In order to verify the effectiveness of the designed system and the gas feature extraction algorithm, they were applied to the identification of different categories of apple juice. The experimental results show that more gas features can be obtained by modulating the operating temperature of the gas sensors, and the Boruta-RFE algorithm can effectively reduce the dimensionality of the original gas feature dataset, and can quickly select the key gas features, so as to effectively improve the identification accuracy of the E-nose system.
Solving Integer Ambiguity Based on an Improved Ant Lion Algorithm
Authors: Guo Wuzheng , Ji Yuanfa , Sun Xiyan , Jia Xizi
Published: February 2025

In GNSS, a double-difference carrier phase observation model is typically employed, and high-accuracy position coordinates can be obtained by resolving the integer ambiguity within the model through algorithmic processing. To address the challenge of a double-difference integer ambiguity resolution, an enhanced Simulated Annealing Ant Lion Optimizer (SAALO) is proposed. This algorithm is designed to efficiently resolve integer ambiguities. First, the performance of the SAALO algorithm was evaluated by comparing its solving speed and success rate with those of the Ant Lion Optimization Algorithm (ALO), the LAMBDA algorithm and the MLAMBDA algorithm. The results demonstrate that the SAALO algorithm achieved a solution success rate that was 0.0496 s and 0.01 s faster than the LAMBDA and M-LAMBDA algorithms, respectively. Second, to further validate the high-dimensional ambiguity resolution capability of the SAALO algorithm, integer ambiguity resolution tests were conducted in both 6-dimensional and 12-dimensional scenarios. The results indicate that the SAALO algorithm achieves a success rate exceeding 98%, confirming its robust performance in high-dimensional problem-solving. Finally, the practical application of the SAALO algorithm was tested in short- and medium-baseline scenarios using a single-frequency GPS system. With a baseline length of 42.7 km, the SAALO algorithm exhibited a slightly faster average solution time compared to the LAMBDA algorithm, while its solution success rate was 5.2% higher. These findings underscore the effectiveness and reliability of the SAALO algorithm in real-world GNSS applications.
A Semi-Autonomous Telemanipulation Order-Picking Control Based on Estimating Operator Intent for Box-Stacking Storage Environments
Authors: Min Donggyu , Yoon Hojin , Lee Donghun
Published: February 2025

Teleoperation-based order picking in logistics warehouse environments has been advancing steadily. However, the accuracy of such operations varies depending on the type of human–robot interface (HRI) employed. Immersive HRI, which uses a head-mounted display (HMD) and controllers, can significantly reduce task accuracy due to the limited field of view in virtual environments. To address this limitation, this study proposes a semi-autonomous telemanipulation order-picking control method based on operator intent estimation using intersection points between the end-effector and the target logistics plane in box-stacking storage environments. The proposed method consists of two stages. The first stage involves operator intent estimation, which approximates the target logistics plane using objects identified through camera vision and calculates the intersection points by intersecting the end-effector heading vector with the plane. These points are accumulated and modeled as a Gaussian distribution, with the probability density function (PDF) of each target object treated as its likelihood. Bayesian probability filtering is then applied to estimate target probabilities, and predefined conditions are used to switch control between autonomous and manual controllers. Results show that the proposed operator intent estimation method identified the correct target in 74.6% of the task’s duration. The proposed semi-autonomous control method successfully transferred control to the autonomous controller within 32.2% of the total task duration using a combination of three parameters. This approach inferred operator intent based solely on manipulator motion and reduced the fatigue of the operator. This method demonstrates potential for broad application in teleoperation systems, offering high operational efficiency regardless of operator expertise or training level.