bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Wedge Anchor System for Double-Layer CFRP Plate Cables: Concept, Theoretical Analysis and FEA
Authors: Zhang Zeping , Bai Jie , Yue Qingrui , Xu Guowen , Liu Xiaogang
Published: July 2024

This study introduces an innovative wedge anchor for double-layer carbon fiber reinforced polymer (CFRP) plate cable to address the current limitation of traditional wedge anchors. By employing the design concept of “secondary force transmission path”, the friction force for anchoring the CFRP plate is effectively transferred into the barrel through its contracting wedge, thus reducing the clamping pressure requirement of traditional wedge anchorage for anchoring thick or double-layer CFRP plates. Based on this conception, this study presents a theoretical analysis model for predicting the influence of parameter variations on the compressive stress of the CFRP plate, which can serve as a tool for rapid configuration preliminary design. Through finite element analysis, the internal stress distribution of the anchor is thoroughly investigated, and the theoretical analysis model for fast predicting compressive stress of CFRP plate is also validated. The results also indicate that the anchorage conception is valid and effective, providing sufficient anchorage of CFPR plates with an anchorage length of 100 mm.
Surface Modification of Silk Fabric by Polysaccharide Derivatives towards High-Quality Printing Performance Using Bio-Based Gardenia Blue Ink
Authors: Liang Yan , Wang Ni , Li Qing , Jiang Huiyu
Published: July 2024

Ink-jet-printed silk, a premium textile material, was achieved by utilizing a bio-based gardenia blue dye. However, the sharpness of the printing pattern is difficult to control due to the limited water-retention capacity of silk. To address this issue, three polysaccharide derivatives, namely, sodium alginate (SA), low-viscosity hydroxypropyl methyl cellulose (HPMC-I), and high-viscosity hydroxypropyl methyl cellulose (HPMC-II), were employed as thickeners to modify the silk by the dipping–padding method. Firstly, the preparation of the gardenia blue ink and the rheology assessment of the thickener solution were conducted. Furthermore, the impacts of different thickeners on the micro-morphology, element composition, and hydrophilicity of the silk, along with the wetting behavior of the ink on the silk, were analyzed comparatively in order to identify an appropriate thickener for preserving pattern outlines. Lastly, the color features, color fastness, and wearing characteristics of the printed silk were discussed to evaluate the overall printing quality. Research results showed that the optimized ink formulation, comprising 12% gardenia blue, 21% alcohols, and 5.5% surfactant, met the requirements for ink-jet printing (with a viscosity of 4.48 mPa·s, a surface tension of 34.12 mN/m, and a particle size of 153 nm). The HPMC-II solution exhibited prominent shear-thinning behavior, high elasticity, and thixotropy, facilitating the achievement of an even modification effect. The treatment of the silk with HPMC-II resulted in the most notable decrease in hydrophilicity. This can be attributed to the presence of filled gaps and a dense film on the fibers’ surface after the HPMC-II treatment, as observed by scanning electron microscopy. Additionally, X-ray photoelectron spectroscopy analysis confirmed that the HPMC-II treatment introduced the highest content of hydrophobic groups on the fiber surface. The reduced hydrophilicity inhibited the excessive diffusion and penetration of gardenia blue ink, contributing to a distinct printing image and enhanced apparent color depth. Moreover, the printed silk demonstrated qualified color fastness to rubbing and soaping (exceeding grade four), a soft handle feeling, an ignorable strength loss (below 5%), and a favorable air/moisture penetrability. In general, the surface modification with the HPMC-II treatment has been proven as an effective strategy for upgrading the image quality of bio-based dye-printed silk.
Experimental Permeability and Porosity Determination of All-Oxide Ceramic Matrix Composite Material
Authors: Szwaba Ryszard , Madejski Pawel , Kaczynski Piotr , Kurowski Marcin , Kunz Mathias , Berent Katarzyna , Ochrymiuk Tomasz
Published: July 2024

This paper presents an investigation into the water permeability of an all-oxide ceramic matrix composite. To determine the parameters and characterize the water permeability of the ceramic composite material, an experimental study was carried out in which a dedicated test rig was constructed and commissioned. A total of five different configurations of composite tubes were tested. They differed in fibre roving strength, winding angle, fibre bundle arrangement during winding, and matrix grain size distribution. To better understand the internal structure of the analysed ceramic matrix composite material, the experimental study used scanning electron microscopy for microstructure and porosity observation. The tested tubes will be used as liners in an oxy-combustion chamber in future studies. The experiments obtained new and interesting results regarding the water permeability of the ceramic matrix composite with different structural parameters. It was also observed that, as with some porous materials, the permeability of ceramic matrix composites decreases with time as more and more liquid is pressed through it.
Inverse Design of Low-Resistivity Ternary Gold Alloys via Interpretable Machine Learning and Proactive Search Progress
Authors: Che Hang , Lu Tian , Cai Shumin , Li Minjie , Lu Wencong
Published: July 2024

Ternary gold alloys (TGAs) are highly regarded for their excellent electrical properties. Electrical resistivity is a crucial indicator for evaluating the electrical performance of TGAs. To explore new promising TGAs with lower resistivity, we developed a reverse design approach integrating machine learning techniques and proactive searching progress (PSP) method. Compared with other models, the support vector regression (SVR) was determined to be the most optimal model for resistivity prediction. The training and test sets yielded R2 values of 0.73 and 0.77, respectively. The model interpretation indicated that lower electrical resistivity was associated with the following conditions: a van der Waals Radius (Vrt) of 0, a Vr (another van der Waals Radius) of less than 217, and a mass attenuation coefficient of MoKα (Macm) greater than 77.5 cm2g−1. Applying the PSP method, we successfully identified eight candidates whose resistivity was lower than that of the sample with the lowest resistivity in the dataset by more than 53–60%, e.g., Au1.000Cu4.406Pt1.833 and Au1.000Pt2.232In1.502. Finally, the candidates were validated to possess low resistivity through the pattern recognition method.
Surface Analysis of Stainless Steel Electrodes Cleaned by Atmospheric Pressure Plasma
Authors: Zhang Jia , Dang Mengjia , Luo Cheng , Ba Yongshan , Li Qingkai
Published: July 2024

The Z-pinch device is a critical component in inertial confinement fusion, where stainless steel electrodes must withstand high current densities of up to MA/cm2. Gases and difficult-to-remove impurities adhering to the electrode surfaces can ionize, significantly impacting the device’s electrical conductivity efficiency. In this paper, the surface of stainless steel electrodes was subjected to cleaning using a large-area plasma jet under atmospheric pressure. The wettability, chemical composition, and chemical state of the electrode surface were characterized using a water contact angle measuring instrument and X-ray photoelectron spectroscopy (XPS). The cleaning effect under different discharge parameters was systematically analyzed. The results revealed a significant reduction in the content of carbon pollutants on the surface of stainless steel electrodes, decreasing from 62.95% to a minimum of 37.68% after plasma cleaning. Moreover, the water contact angle decreased from 70.76° to a minimum of 29.31°, and the content of water molecules adsorbed on the surface decreased from 17.31% to a minimum of 5.9%. Based on the evolution process of micro-element content and chemical state on the surface of stainless steel electrode, the cleaning process of adhering substances on the surface by atmospheric pressure plasma was analyzed by the layered cleaning model for surface pollutants on stainless steel.
Damage Mechanism Analysis of the Connecting Screw of Turbine Disk-Drum Assembly
Authors: Wang Haijun , Wang Shengxu , Xue Pu , Guo Yongxin , Jiang Liang
Published: July 2024

The turbine disk-drum is one of the key components of an aero-engine and its assembly is connected with high-strength refined screws. But due to the uncoordinated rotation and deformation, the screws have abnormal wear damage. Through detailed contact stress analysis of screw body and component level using the finite element method, combined with experimental observation, the mechanism of wear damage of screw surface in screws is determined. It mainly includes the following: Firstly, the finite element method is used to calculate the deformation and stress distribution of the connecting screw of the turbine disk-drum assembly. Then, after the overspeed test, the morphology of the screws disassembled from the disk-drum assembly is evaluated. It was found that the wear degree in the circumferential direction and axial direction of the screw was quite different, that is, the screw wear experiment was consistent with the finite element analysis results. Finally, the influence of different rotation states and screw tightening states on screw wear was compared and analyzed. Conclusions obtained in this paper will be helpful to improve the assembly reliability of turbine drum.
Industrial Robot Trajectory Optimization Based on Improved Sparrow Search Algorithm
Authors: Ma Fei , Sun Weiwei , Jiang Zhouxiang , Suo Shuangfu , Wang Xiao , Liu Yue
Published: July 2024

This paper proposes an enhanced multi-strategy sparrow search algorithm to optimize the trajectory of a six-axis industrial robot, addressing issues of low efficiency and high vibration impact on joints during operation. Initially, the improved D-H parametric method is employed to establish both forward and inverse kinematic models of the robot. Subsequently, a 3-5-3 mixed polynomial interpolation trajectory planning approach is applied to the robot. Building upon the conventional sparrow algorithm, a two-dimensional Logistic chaotic system initializes the population. Additionally, a Levy flight strategy and nonlinear adaptive weighting are introduced to refine the discoverer position update operator, while an inverse learning strategy enhances the vigilante position update operator. These modifications boost both the local and global search capabilities of the algorithm. The improved sparrow algorithm, based on 3-5-3 hybrid polynomial trajectory planning, is then used for the time-optimal trajectory planning of the robot. This is compared with traditional sparrow search algorithm and particle swarm algorithm optimization results. The findings indicate that the proposed enhanced sparrow search algorithm outperforms both the standard sparrow algorithm and the particle swarm algorithm in terms of convergence speed and accuracy for robot trajectory optimization. This can lead to the increased work efficiency and performance of the robot.
An Advanced Diagnostic Approach for Broken Rotor Bar Detection and Classification in DTC Controlled Induction Motors by Leveraging Dynamic SHAP Interaction Feature Selection (DSHAP-IFS) GBDT Methodology
Authors: Khan Muhammad Amir , Asad Bilal , Vaimann Toomas , Kallaste Ants
Published: July 2024

This paper introduces a sophisticated approach for identifying and categorizing broken rotor bars in direct torque-controlled (DTC) induction motors. DTC is implemented in industrial drive systems as a suitable control method to preserve torque control performance, which sometimes shows its impact on fault-representing frequencies. This is because of the DTC’s closed-loop control nature, whichtriesto reduce speed and torque ripples by changing the voltage profile. The proposed model utilizes the modified Shapley Additive exPlanations (SHAP) technique in combination with gradient-boosting decision trees (GBDT) to detect and classify the abnormalities in BRBs at diverse (0%, 25%, 50%, 75%, and 100%) loading conditions. To prevent overfitting of the proposed model, we used the adaptive fold cross-validation (AF-CV) technique, which can dynamically adjust the number of folds during the optimization process. By employing extensive feature engineering in the original dataset and then applying Shapely Additive exPlanations(SHAP)-based feature selection, our methodology effectively identifies informative features from signals (three-phase current, three-phase voltage, torque, and speed) and motor characteristics. The gradient-boosting decision tree (GBDT) classifier, trained using the given characteristics, extracts consistent and reliable classification performance under different loading circumstances and enables precise and accurate detection and classification of broken rotor bars. The proposed approach (SHAP-Fusion GBDT with AF-CV) is a major advancement in the field of machine learning in detecting motor anomalies at varying loading conditions and proved to be an effective mechanism for preventative maintenance and preventing faults in DTC-controlled induction motors byattaining an accuracy rate of 99% for all loading conditions.
A Multi-Agent Reinforcement Learning-Based Task-Offloading Strategy in a Blockchain-Enabled Edge Computing Network
Authors: Liu Chenlei , Sun Zhixin
Published: July 2024

In recent years, many mobile edge computing network solutions have enhanced data privacy and security and built a trusted network mechanism by introducing blockchain technology. However, this also complicates the task-offloading problem of blockchain-enabled mobile edge computing, and traditional evolutionary learning and single-agent reinforcement learning algorithms are difficult to solve effectively. In this paper, we propose a blockchain-enabled mobile edge computing task-offloading strategy based on multi-agent reinforcement learning. First, we innovatively propose a blockchain-enabled mobile edge computing task-offloading model by comprehensively considering optimization objectives such as task execution energy consumption, processing delay, user privacy metrics, and blockchain incentive rewards. Then, we propose a deep reinforcement learning algorithm based on multiple agents sharing a global memory pool using the actor–critic architecture, which enables each agent to acquire the experience of another agent during the training process to enhance the collaborative capability among agents and overall performance. In addition, we adopt attenuatable Gaussian noise into the action space selection process in the actor network to avoid falling into the local optimum. Finally, experiments show that this scheme’s comprehensive cost calculation performance is enhanced by more than 10% compared with other multi-agent reinforcement learning algorithms. In addition, Gaussian random noise-based action space selection and a global memory pool improve the performance by 38.36% and 43.59%, respectively.
Centroidous Method for Determining Objective Weights
Authors: Vinogradova-Zinkevič Irina
Published: July 2024

When using multi-criteria decision-making methods in applied problems, an important aspect is the determination of the criteria weights. These weights represent the degree of each criterion’s importance in a certain group. The process of determining weight coefficients from a dataset is described as an objective weighting method. The dataset considered here contains quantitative data representing measurements of the alternatives being compared, according to a previously determined system of criteria. The purpose of this study is to suggest a new method for determining objective criteria weights and estimating the proximity of the studied criteria to the centres of their groups. It is assumed that the closer a criterion is to the centre of the group, the more accurately it describes the entire group. The accuracy of the description of the entire group’s priorities is interpreted as the importance, and the higher the value, the more significant the weight of the criterion. The Centroidous method suggested here evaluates the importance of each criterion in relation to the centre of the entire group of criteria. The stability of the Centroidous method is examined in relation to the measures of Euclidean, Manhattan, and Chebyshev distances. By slightly modifying the data in the original normalised data matrix by 5% and 10% 100 and 10,000 times, stability is examined. A comparative analysis of the proposed Centroidous method obtained from the entropy, CRITIC, standard deviation, mean, and MEREC methods was performed. Three sets of data were generated for the comparative study of the methods, as follows: the mean value for alternatives with weak and strong differences and criteria with linear dependence. Additionally, an actual dataset from mobile phones was also used for the comparison.
On the Continuity Equation in Space–Time Algebra: Multivector Waves, Energy–Momentum Vectors, Diffusion, and a Derivation of Maxwell Equations
Authors: Beato Vásquez Manuel , Arias Polanco Melvin
Published: July 2024

Historically and to date, the continuity equation (C.E.) has served as a consistency criterion for the development of physical theories. In this paper, we study the C.E. employing the mathematical framework of space–time algebra (STA), showing how common equations in mathematical physics can be identified and derived from the C.E.’s structure. We show that, in STA, the nabla equation given by the geometric product between the vector derivative operator and a generalized multivector can be identified as a system of scalar and vectorial C.E.—and, thus, another form of the C.E. itself. Associated with this continuity system, decoupling conditions are determined, and a system of wave equations and the generalized analogous quantities to the energy–momentum vectors and the Lorentz force density (and their corresponding C.E.) are constructed. From the symmetry transformations that make the C.E. system’s structure invariant, a system with the structure of Maxwell’s field equations is derived. This indicates that a Maxwellian system can be derived not only from the nabla equation and the generalized continuity system as special cases, but also from the symmetries of the C.E. structure. Upon reduction to well-known simpler quantities, the results found are consistent with the usual STA treatment of electrodynamics and hydrodynamics. The diffusion equation is explored from the continuity system, where it is found that, for decoupled systems with constant or explicitly dependent diffusion coefficients, the absence of external vector sources implies a loss in the diffusion equation structure, transforming it into Helmholtz-like and wave equations.
Coefficient Functionals of Sakaguchi-Type Starlike Functions Involving Caputo-Type Fractional Derivatives Subordinated to the Three-Leaf Function
Authors: Alsager Kholood M. , El-Deeb Sheza M. , Murugusundaramoorthy Gangadharan , Breaz Daniel
Published: July 2024

A challenging part of studying geometric function theory is figuring out the sharp boundaries for coefficient-related problems that crop up in the Taylor–Maclaurin series of univalent functions. Using Caputo-type fractional derivatives to define the families of Sakaguchi-type starlike functions with respect to symmetric points, this article aims to investigate the first three initial coefficient estimates, the bounds for various problems such as Fekete–Szegő inequality, and the Zalcman inequalities, by subordinating to the function of the three leaves domain. Fekete–Szegő-type inequalities and initial coefficients for functions of the form H−1 and ζH(ζ) and 12logHζζ connected to the three leaves functions are also discussed.
Stability and Instability of an Apollonius-Type Functional Equation
Authors: Arumugam Ponmana Selvan , Park Won-Gil , Roh Jaiok
Published: July 2024

For the inner product space, we have Appolonius’ identity. From this identity, Park and Th. M. Rassias induced and investigated the quadratic functional equation of the Apollonius type. And Park and Th. M. Rassias first introduced an Apollonius-type additive functional equation. In this work, we investigate an Apollonius-type additive functional equation in 2-normed spaces. We first investigate the stability of an Apollonius-type additive functional equation in 2-Banach spaces by using Hyers’ direct method. Then, we consider the instability of an Apollonius-type additive functional equation in 2-Banach spaces.
Numerical Investigation of Nucleotides’ Interaction Considering Changes Caused by Liquid Influences
Authors: Jasevičius Raimondas
Published: July 2024

This work is devoted to the interaction of nucleotides. The goal of this study is to learn or try to learn how the interaction between nucleotides with exposure to a liquid takes place. Will the interacting forces of the nucleotides be sufficient to approach the incision? A numerical imitation of the interaction is conducted using the discrete element method and a Gears predictor–corrector as part of the integrated scheme. In this work, the results reflect the dynamics of nucleotides: velocity, displacement, and force graphs are presented with and without the effect of the liquid. During changes caused by the influence of a liquid, the nucleotide interaction transforms and passes three stages: a full stop, one similar to viscous damping, and one similar to non-dissipative behaviors. The main contribution of this work is a better understanding of the behavior of infinitely small objects that would be difficult to observe in vivo. The changing influence of a liquid can transform into certain effects. As a result, a model is provided, which can be based on the results of well-known physical experiments (DNA unzipping) for modeling nucleotide interactions.
Seismic Response Prediction of Rigid Rocking Structures Using Explainable LightGBM Models
Authors: Karampinis Ioannis , Bantilas Kosmas E. , Kavvadias Ioannis E. , Iliadis Lazaros , Elenas Anaxagoras
Published: July 2024

This study emphasizes the explainability of machine learning (ML) models in predicting the seismic response of rigid rocking structures, specifically using the LightGBM algorithm. By employing SHapley Additive exPlanations (SHAP), partial dependence plots (PDP), and accumulated local effects (ALE), a comprehensive feature importance analysis has been performed. This revealed that ground motion parameters, particularly peak ground acceleration (PGA), are critical for predicting small rotations, while structural parameters like slenderness and frequency are more significant for larger rotations. Utilizing an extensive dataset generated from nonlinear time history analyses, the trained LightGBM model demonstrated high accuracy in estimating the maximum rotation angle of rigid blocks under natural ground motions. The study also examined the sensitivity of model performance to lower bound thresholds of the target variable, revealing that reduced feature sets can maintain predictive performance effectively. These findings advance ML-based modeling of seismic rocking responses, providing interpretable and accurate models that enhance our understanding of rocking structures’ dynamic behavior, which is crucial for designing resilient structures and improving seismic risk assessments. Future research will focus on incorporating additional parameters and exploring advanced ML techniques to further refine these models.
Preface to the Special Issue “Mathematical Modelling and Optimization of Service Supply Chain”
Authors: He Yong
Published: July 2024

In recent years, as the world economy has grown, increasingly, service-oriented systems play a more significant role in the supply chain [...]
Best Proximity Point Results for Fuzzy Proximal Quasi Contractions with Applications
Authors: Ali Muzammil , Ali Basit
Published: July 2024

In this work, we introduce a new type of multivalued fuzzy proximal quasi-contraction. These are generalized contractions which are a hybrid of H-contractive mappings and quasi-contractions. Furthermore, we establish the best proximity point results for newly introduced fuzzy contractions in the context of fuzzy b-metric spaces. Fuzzy b-metric spaces are more general than fuzzy metric spaces and are linked with the cosine distance, which is used in various contexts of artificial intelligence to measure the similarity between elements of a vector space.
FutureCite: Predicting Research Articles’ Impact Using Machine Learning and Text and Graph Mining Techniques
Authors: Thafar Maha A. , Alsulami Mashael M. , Albaradei Somayah
Published: July 2024

The growth in academic and scientific publications has increased very rapidly. Researchers must choose a representative and significant literature for their research, which has become challenging worldwide. Usually, the paper citation number indicates this paper’s potential influence and importance. However, this standard metric of citation numbers is not suitable to assess the popularity and significance of recently published papers. To address this challenge, this study presents an effective prediction method called FutureCite to predict the future citation level of research articles. FutureCite integrates machine learning with text and graph mining techniques, leveraging their abilities in classification, datasets in-depth analysis, and feature extraction. FutureCite aims to predict future citation levels of research articles applying a multilabel classification approach. FutureCite can extract significant semantic features and capture the interconnection relationships found in scientific articles during feature extraction using textual content, citation networks, and metadata as feature resources. This study’s objective is to contribute to the advancement of effective approaches impacting the citation counts in scientific publications by enhancing the precision of future citations. We conducted several experiments using a comprehensive publication dataset to evaluate our method and determine the impact of using a variety of machine learning algorithms. FutureCite demonstrated its robustness and efficiency and showed promising results based on different evaluation metrics. Using the FutureCite model has significant implications for improving the researchers’ ability to determine targeted literature for their research and better understand the potential impact of research publications.
Compositional Data and Microbiota Analysis: Imagination and Reality
Authors: Itagaki Tatsuki , Kobayashi Hirokazu , Sakata Ken-ichiro , Miyamoto Ikuya , Hasebe Akira , Kitagawa Yoshimasa
Published: July 2024

The relationships among bacterial flora, diseases, and diet have been described by many authors. An operational taxonomic units (OTUs) are the result of clustering the 16S rRNA gene sequences at a certain cutoff value, and they are considered compositional data. As Pearson’s correlation coefficient is difficult to interpret, Aitchison’s ratio analysis was used to develop a method to handle compositional data. Multivariate analysis was developed because univariate analysis can be subject to large biases. Simulations regarding absolute abundance based on certain assumptions and some analyses, such as nonparametric multidimensional scaling (NMDS), principal component analysis (PCA), and ratio analysis, were conducted in this study. The same content as a 100% stacked bar graph could be expressed in low dimensions using PCA. However, the relative diversity was not reproducible with NMDS. Various assumptions were made regarding absolute abundance based on the relative abundance. However, which assumptions are true could not be determined. In summary, ratio analysis and PCA are useful for analyzing compositional data and the gut microbiota.
Microbial Electrolysis Cells Based on a Bacterial Anode Encapsulated with a Dialysis Bag Including Graphite Particles
Authors: Dubrovin Irina Amar , Hirsch Lea Ouaknin , Chiliveru Abhishiktha , Jukanti Avinash , Rozenfeld Shmuel , Schechter Alex , Cahan Rivka
Published: July 2024

One of the main barriers to MEC applicability is the bacterial anode. Usually, the bacterial anode contains non-exoelectrogenic bacteria that act as a physical barrier by settling on the anode surface and displacing the exoelectrogenic microorganisms. Those non-exoelectrogens can also compete with exoelectrogenic microorganisms for nutrients and reduce hydrogen production. In this study, the bacterial anode was encapsulated by a dialysis bag including suspended graphite particles to improve current transfer from the bacteria to the anode material. An anode encapsulated in a dialysis bag without graphite particles, and a bare anode, were used as controls. The MEC with the graphite-dialysis-bag anode was fed with artificial wastewater, leading to a current density, hydrogen production rate, and areal capacitance of 2.73 A·m−2, 134.13 F·m−2, and 7.6 × 10−2 m3·m−3·d−1, respectively. These were highest when compared to the MECs based on the dialysis-bag anode and bare anode (1.73 and 0.33 A·m−2, 82.50 and 13.75 F·m−2, 4.2 × 10−2 and 5.2 × 10−3 m3·m−3·d−1, respectively). The electrochemical impedance spectroscopy of the modified graphite-dialysis-bag anode showed the lowest charge transfer resistance of 35 Ω. The COD removal results on the 25th day were higher when the MEC based on the graphite-dialysis-bag anode was fed with Geobacter medium (53%) than when it was fed with artificial wastewater (40%). The coulombic efficiency of the MEC based on the graphite-dialysis-bag anode was 12% when was fed with Geobacter medium and 15% when was fed with artificial wastewater.
Optimization of H2O2 Production in Biological Systems for Design of Bio-Fenton Reactors
Authors: Zhou Peiguo , Yang Liping , Yang Wenjing , Hou Jiaxin , Liao Ziqiao
Published: July 2024

The treatment of antibiotic wastewater, which is known for its micro-toxicity, inhibition, and poor biochemistry, poses significant challenges, including complex processes, high energy demands, and secondary pollution. Bio-Fenton, a novel Fenton technology, enables the in situ production of H2O2 at near-neutral pH, having low energy requirements and sustainable properties, and reduces the hazards of H2O2 transportation and storage. We preliminary self-designed a heterogeneous Bio-Fenton reactor. An aerobic SBBR system with pure algae, pure bacteria, and bacteria–algae symbiosis was first constructed to investigate the optimal process conditions through the effects of carbon source concentration, light duration, bamboo charcoal filling rate, and dissolved oxygen (DO) content on the H2O2 production and COD removal. Second, the reactor was constructed by adding iron-carrying catalysts to remove ROX and SDZ wastewater. The results demonstrated that the optimal operating parameters of aerobic SBBR were an influent carbon source concentration of 500 mg/L, a water temperature of 20 ± 2 °C, pH = 7.5, a dissolved oxygen content of 5 mg/L, a light–dark ratio of 12 h:12 h, a light intensity of 2500 Lux, an HRT of 10 h, and a bamboo charcoal filling rate of 33%. Given these conditions, the bacterial–algal system was comprehensively found to be the most suitable biosystem for this experiment. Ultimately, the dynamically coupled Bio-Fenton process succeeded in the preliminary removal of 41.32% and 42.22% of the ROX and SDZ from wastewater, respectively.
Influence of Cheese Composition on Aroma Content, Release, and Perception
Authors: Andriot Isabelle , Septier Chantal , Peltier Caroline , Noirot Elodie , Barbet Pascal , Palme Romain , Arnould Céline , Buchin Solange , Salles Christian
Published: July 2024

The quality of a cheese is determined by the balance of aroma compounds primarily produced by microorganisms during the transformation of milk into ripened cheese. The microorganisms, along with the technological parameters used in cheese production, influence aroma formation. The perception of these compounds is further influenced by the composition and structure of the cheese. This study aimed to characterize how cheese composition affects aroma compound production, release, and perception. Sixteen cheeses were produced under controlled conditions, followed by a quantitative descriptive analysis post ripening. Aroma composition was analyzed using HS-SPME–GC–MS, and a dynamic sensory evaluation (TCATA) was combined with nosespace analysis using PTR-ToF-MS. Image analysis was also conducted to characterize cheese structure. Cheese fat and whey lactose contents were identified as key factors in the variability of sensory attributes. GC–MS analyses identified 27 compounds correlated with sensory attributes. In terms of aroma compound release, 23 ions were monitored, with fat, salt, and lactose levels significantly affecting the release of most compounds. Therefore, cheese fat, salt, and whey lactose levels, as well as the types of microbial strains, play a role in influencing the composition, structure, release of aroma compounds, and sensory perception.
Ion Chromatography and Related Techniques in Carbohydrate Analysis: A Review
Authors: Michalski Rajmund , Kończyk Joanna
Published: July 2024

Ion chromatography and related techniques have been the most popular separation methods used in the determination of organic and inorganic anions and cations, predominantly in water and wastewater samples. Making progress in their development and introducing new stationary phases, methods of detection and preparation of samples for analyses have given rise to the broadening of their analytical range. Nowadays, they are also used for substances that are not ionic by nature but can convert to such forms under certain conditions. These encompass, among others, carbohydrates, whose role and significance in humans’ lives and environment is invaluable. Their presence in the air is mostly due to the industrial burning of biomass for energy production purposes. In addition, the content of sugars in plants, fruits and vegetables, constituting the base of human diets, affects our health condition. Given that, there is not only a need for their determination by means of routine methods but also for searching for novel analytical solutions. Based on literature data from the past decade, this paper presents the possibilities and examples of applications regarding ion chromatography and related techniques for the determination of carbohydrates in environmental samples, biomass and plants constituting food or raw materials for food production. Attention has been paid to the virtues and limitations of the discussed separation methods in this respect. Moreover, perspectives on their development have been defined.
Praseodymium-Doped Cr2O3 Prepared by In Situ Pyrolysis of MIL-101(Cr) for Highly Efficient Catalytic Oxidation of 1,2-Dichloroethane
Authors: Zhu Pengfei , Hu Zhaoxia , Chen Shouwen
Published: July 2024

The development of economical catalysts that exhibit both high activity and durability for chlorinated volatile organic compounds (CVOCs) elimination remains a challenge. The oxidizing and acidic sites play a crucial role in the oxidation process of CVOCs; herein, praseodymium (Pr) was introduced into CrOx catalysts via in situ pyrolysis of MIL-101(Cr). With the decomposition of the ligand, a mixed micro-mesoporous structure was formed within the M-Cr catalyst, thereby reducing the contact resistance between catalyst active sites and the 1,2-dichloroethane molecule. Moreover, the synergistic interaction between chromium and praseodymium facilitates Oβ species and acidic sites, significantly enhancing the low-temperature catalytic performance and durability of the M-PrCr catalyst for 1,2-dichloroethane (1,2-DCE) oxidation. The M-30PrCr catalyst possess enhanced active oxygen sites and acid sites, thereby exhibiting the highest catalytic activity and stability. This study may provide a novel and promising strategy for practical applications in the elimination of 1,2-DCE.
New Series of Hydrogen-Bonded Liquid Crystal with High Birefringence and Conductivity
Authors: Ben Salah Manel , Saadaoui Lotfi , Soltani Taoufik , Ben Hamadi Naoufel , Guesmi Ahlem , Maschke Ulrich
Published: July 2024

Liquid crystals with high dielectric anisotropy, low operational thresholds, and significant birefringence (Δn) represent a key focus in soft matter research. This work introduces a novel series of hydrogen-bonded liquid crystals (HBLCs) derived from 4-n-alkoxybenzoic, 4-alkoxy-3-fluorobenzoic derivatives (nOBAF), 4-alkoxy-2,3-fluorobenzoic derivatives (nOBAFF), and 2-fluoro-4-nitrobenzoic acid. The HBLCs were characterized using Fourier transform infrared spectroscopy, and their thermal behavior was evaluated via differential scanning calorimetry. Optical observations were conducted using polarized optical microscopy. The results indicate that mixtures containing benzoic acid with a bilateral fluorine substituent exhibit both SmA and SmC phases, while those with a unilateral fluorine substituent exhibit nematic and SmA phases. Moreover, an increase in the length of the alkoxy chain results in an expanded mesophase temperature range. This study demonstrates that the presence of a fluorine substituent and the incorporation of an NO2 group in the molecular structure result in an increase in dielectric permittivity, DC conductivity, dielectric anisotropy, and birefringence.
Analysis of Chemical Composition, Antioxidant Activity, and Toxicity of Essential Oil from Virola sebifera Aubl (Myristicaceae)
Authors: Cruz Jorddy Neves , de Oliveira Mozaniel Santana , Ferreira Oberdan Oliveira , Gomes Antonio Rafael Quadros , Mali Suraj N. , Pereira Soluan Felipe Melo , Ansar Sabah , Santos Cleydson Breno Rodrigues dos , Lima Rafael Rodrigues , de Andrade Eloisa Helena Aguiar
Published: July 2024

Volatile oils or essential oils (EOs) were extracted from three V. sebifera samples (labeled as A, B, and C) in September 2018 and February 2019; the extraction process involved hydrodistillation of the leaves. The chemical compositions of the EOs were analyzed using gas chromatography-mass spectrometry (GC/MS). The volatile components were identified by comparing their retention indices and mass spectra with standard substances documented in the literature (ADAMS). The antioxidant activity of the EOs was evaluated using 2, 2-diphenyl-1-picrylhydrazyl (DPPH), while their toxicity was assessed using Artemia salina Leach. Molecular docking was utilized to examine the interaction between the major constituents of V. sebifera EO and acetylcholinesterase (AChE), a molecular target linked to toxicity in A. salina models. The EO obtained from specimen A, collected in September 2018, was characterized by being primarily composed of (E,E)-α-farnesene (47.57%), (E)-caryophyllene (12.26%), and α-pinene (6.93%). Conversely, the EO from specimen A, collected in February 2019, was predominantly composed of (E,E)-α-farnesene (42.82%), (E)-caryophyllene (16.02%), and bicyclogermacrene (8.85%), the EO from specimen B, collected in September 2018, primarily contained (E,E)-α-farnesene (47.65%), (E)-caryophyllene (19.67%), and α-pinene (11.95%), and the EO from the leaves collected in February 2019 was characterized by (E,E)-α-farnesene (23.57%), (E)-caryophyllene (19.34%), and germacrene D (7.33%). The EO from the leaves collected in September 2018 contained (E,E)-α-farnesene (26.65%), (E)-caryophyllene (15.7%), and germacrene D (7.72%), while the EO from the leaves collected in February 2019 was primarily characterized by (E,E)-α-farnesene (37.43%), (E)-caryophyllene (21.4%), and α-pinene (16.91%). Among these EOs, sample B collected in February 2019 demonstrated the highest potential for inhibiting free radicals, with an inhibition rate of 34.74%. Conversely, the EOs from specimen A exhibited the highest toxic potentials, with an lethal concentration 50 (LC50) value of 57.62 ± 1.53 µg/mL, while specimen B had an LC50 value of 74.72 ± 2.86 µg/mL. Molecular docking results suggested that hydrophobic interactions significantly contributed to the binding of the major compounds in the EO from sample B to the binding pocket of AChE.
Multicomponent Synthesis of New Fluorescent Boron Complexes Derived from 3-Hydroxy-1-phenyl-1H-pyrazole-4-carbaldehyde
Authors: Savickienė Viktorija , Bieliauskas Aurimas , Belyakov Sergey , Arbačiauskienė Eglė , Šačkus Algirdas
Published: July 2024

Novel fluorescent pyrazole-containing boron (III) complexes were synthesized employing a one-pot three-component reaction of 3-hydroxy-1-phenyl-1H-pyrazole-4-carbaldehyde, 2-aminobenzenecarboxylic acids, and boronic acids. The structures of the novel heterocyclic compounds were confirmed using 1H-, 13C-, 15N-, 19F-, and 11B-NMR, IR spectroscopy, HRMS, and single-crystal X-ray diffraction data. The photophysical properties of the obtained iminoboronates were investigated using spectroscopic techniques, such as UV–vis and fluorescence spectroscopies. Compounds display main UV–vis absorption maxima in the blue region, and fluorescence emission maxima are observed in the green region of the visible spectrum. It was revealed that compounds exhibit fluorescence quantum yield up to 4.3% in different solvents and demonstrate an aggregation-induced emission enhancement effect in mixed THF–water solutions.
Enhancing Sulfidization and Flotation of Smithsonite Using Eco-Friendly Triethanolamine: Insights from Experimental and Simulation Studies
Authors: Zhang Song , Liang Guanyu , Xian Yongjun , Wen Shuming
Published: July 2024

Triethanolamine (TEA) is a promising eco-friendly alternative to inorganic ammonia for enhancing surface sulfidization and flotation recovery of smithsonite. Micro-flotation experiments revealed an enhancement in smithsonite recovery to 95.21% with TEA modification, comparable to the results obtained using ammonia. The mechanisms behind the ability of TEA to enhance the sulfidization process were investigated through surface analysis and molecular dynamics simulations. TEA modification increased the content of sulfidization products, the proportion of crucial S22− in adsorbed products, and the thickness and size of the sulfidization product layer. The complexation of TEA with Zn sites formed positively charged Zn–TEA complexes that adsorb onto the smithsonite surface. These complexes promoted negatively charged HS− adsorption, creating a multi-layered adsorption structure. Moreover, TEA modification reduced the total energy required for the sulfidization. These findings open up new possibilities for using eco-friendly reagents in mineral processing, highlighting the potential of TEA in green mineral processing practices.
A Series of Lanthanide Coordination Polymers as Luminescent Sensors for Selective Detection of Inorganic Ions and Nitrobenzene
Authors: Wu Miao , Song Juan , Zhou Yun-Long , Chen Hui-Hui , Duan Bo-Feng , Jin Ling-Xia , Ren Chuan-Qing , Lu Jiu-Fu
Published: July 2024

Seven new lanthanide coordination polymers, namely [Ln(cpt)3H2O)]n(Ln = La (1), Pr (2), Sm (3), Eu (4), Gd (5), Dy (6), and Er (7)), which were synthesized under hydrothermal conditions using 4′-(4-(4-carboxyphenyloxy)phenyl)-4,2′:6′,4′-tripyridine (Hcpt) as the ligand. The crystal structures of these seven complexes were determined using single-crystal X-ray diffraction, and they were found to be isostructural, crystallizing in the triclinic P1- space group. The Ln(III) ions were nine-coordinated with tricapped trigonal prism coordination geometry. The Ln(III) cations were coordinated by carboxylic and pyridine groups from (cpt)− ligands, forming one-dimensional ring-chain structures. Furthermore, the luminescent properties of complexes 1–7 were investigated using fluorescent spectra in the solid state. The fluorescence sensing experiments demonstrated that complex 4 exhibits high selectivity and sensitivity for detecting Co2+, Cu2+ ions, and nitrobenzene. Moreover, complex 3 shows good capability for detecting Cu2+ ions and nitrobenzene. Additionally, the sensing mechanism was also thoroughly examined through theoretical calculations.
QuEChERS Extraction and Simultaneous Quantification in GC-MS/MS of Hexahydrocannabinol Epimers and Their Metabolites in Whole Blood, Urine, and Oral Fluid
Authors: Di Trana Annagiulia , Sprega Giorgia , Kobidze Giorgi , Taoussi Omayema , Lo Faro Alfredo Fabrizio , Bambagiotti Giulia , Montanari Eva , Fede Maria Sofia , Carlier Jeremy , Tini Anastasio , Busardò Francesco Paolo , Di Giorgi Alessandro , Pichini Simona
Published: July 2024

Recently, hexahydrocannabinol (HHC) was posed under strict control in Europe due to the increasing HHC-containing material seizures. The lack of analytical methods in clinical laboratories to detect HHC and its metabolites in biological matrices may result in related intoxication underreporting. We developed and validated a comprehensive GC-MS/MS method to quantify 9(R)-HHC, 9(S)-HHC, 9αOH-HHC, 9βOH-HHC, 8(R)OH-9(R)-HHC, 8(S)OH-9(S)HHC, 11OH-9(R)HHC, 11OH-9(S)HHC, 11nor-carboxy-9(R)-HHC, and 11nor-carboxy-9(S)-HHC in whole blood, urine, and oral fluid. A novel QuEChERS extraction protocol was optimized selecting the best extraction conditions suitable for all the three matrices. Urine and blood were incubated with β-glucuronidase at 60 °C for 2 h. QuEChERS extraction was developed assessing different ratios of Na2SO4:NaCl (4:1, 2:1, 1:1, w/w) to be added to 200 µL of any matrix added with acetonitrile. The chromatographic separation was achieved on a 7890B GC with an HP-5ms column, (30 m, 0.25 mm × 0.25 µm) in 12.50 min. The analytes were detected with a triple-quadrupole mass spectrometer in the MRM mode. The method was fully validated following OSAC guidelines. The method showed good validation parameters in all the matrices. The method was applied to ten real samples of whole blood (n = 4), urine (n = 3), and oral fluid (n = 3). 9(R)-HHC was the prevalent epimer in all the samples (9(R)/9(S) = 2.26). As reported, hydroxylated metabolites are proposed as urinary biomarkers, while carboxylated metabolites are hematic biomarkers. Furthermore, 8(R)OH-9(R)HHC was confirmed as the most abundant metabolite in all urine samples.
Development and Optimization Method for Determination of the Strawberries’ Aroma Profile
Authors: Palac Bešlić Iva , Ivešić Martina , Mandić Andačić Ivana , Bursać Kovačević Danijela , Žuntar Irena , Bebek Markovinović Anica , Oštarić Fabijan , Krivohlavek Adela
Published: July 2024

The strawberry (genus Fragaria) is a plant from the rose family (Rosaceae). As the fruits are likely to be picked mechanically, they are grown close to consumption centers. The aim of this work was to develop a suitable method for detecting as many molecules as possible in order to be able to distinguish between different strawberry cultivars and geographical origins in the future. Whole strawberries of the “Albion” cultivar, grown in the Jagodica Purgerica region of Zagreb, were used. Gas chromatography-mass spectrometry (GC-MS) in SCAN mode was used to analyze the aroma profile and to determine the proportion of individual components. The samples were prepared and analyzed using the solid-phase microextraction method (SPME). The impact of SPME fiber selection and GC column type was investigated, as well as sample weight, ionic strength, agitation temperature, and sampling time. A higher ionic strength was achieved by adding a 20% NaCl solution to the sample. The aroma profile of the studied strawberry cultivar consisted of furanone, esters, aldehydes, and carboxylic acids. Optimal results were achieved by adjusting the ionic strength during 15 min of extraction and incubation. The individual compounds were identified using NIST, Wiley libraries, and the “area normalization” method.