bluuebunny/crossref_metadata_2025 huggingface dataset:
An Analytical Model for the Normal Contact Stiffness of Mechanical Joint Surfaces Based on Parabolic Cylindrical Asperities
Authors: Bai Yuzhu , An Qi , Suo Shuangfu , Wang Weikun , Jia Xiaohong
Published: February 2023

The analytical results of normal contact stiffness for mechanical joint surfaces are quite different from the experimental data. So, this paper proposes an analytical model based on parabolic cylindrical asperity that considers the micro-topography of machined surfaces and how they were made. First, the topography of a machined surface was considered. Then, the parabolic cylindrical asperity and Gaussian distribution were used to create a hypothetical surface that better matches the real topography. Second, based on the hypothetical surface, the relationship between indentation depth and contact force in the elastic, elastoplastic, and plastic deformation intervals of the asperity was recalculated, and the theoretical analytical model of normal contact stiffness was obtained. Finally, an experimental test platform was then constructed, and the numerical simulation results were compared with the experimental results. At the same time, the numerical simulation results of the proposed model, the J. A. Greenwood and J. B. P. Williamson (GW) model, the W. R. Chang, I. Etsion, and D. B. Bogy (CEB) model, and the L. Kogut and I. Etsion (KE) model were compared with the experimental results. The results show that when roughness is Sa 1.6 μm, the maximum relative errors are 2.56%, 157.9%, 134%, and 90.3%, respectively. When roughness is Sa 3.2 μm, the maximum relative errors are 2.92%, 152.4%, 108.4%, and 75.1%, respectively. When roughness is Sa 4.5 μm, the maximum relative errors are 2.89%, 158.07%, 68.4%, and 46.13%, respectively. When roughness is Sa 5.8 μm, the maximum relative errors are 2.89%, 201.57%, 110.26%, and 73.18%, respectively. The comparison results demonstrate that the suggested model is accurate. This new method for examining the contact characteristics of mechanical joint surfaces uses the proposed model in conjunction with a micro-topography examination of an actual machined surface.
Experimental Studies of Welded Joints in Structures Subject to High Impact Vibrations Using Destructive and Non-Destructive Methods
Authors: Wróblewski Piotr , Niekurzak Mariusz , Kachel Stanisław
Published: February 2023

This article presents the issues of control and quality assurance of high-strength railway rail joints. Selected test results and requirements for rail joints made by welding with stationary welders on the basis of the requirements included in the PN-EN standards have been described. In addition, destructive and non-destructive tests of weld quality were performed, including visual tests, geometrical measurements of irregularities, magnetic particle and penetration tests, fracture tests, observations of micro- and macro-structure and hardness measurements. The scope of these studies included conducting tests, monitoring the process and evaluating the results obtained. Laboratory tests on the rail joints confirmed the good quality of the rail joints from the welding shop. Increasingly less damage to the track in places of new welded joints is proof that the methodology of laboratory qualification tests is correct and fulfils its task. The presented research will help educate engineers on the welding mechanism and the importance of quality control of rail joints during their design. The results of this study are of key importance for public safety and will improve knowledge on the correct implementation of the rail joint and how to conduct quality control tests in accordance with the requirements of the currently applicable standards. It will help engineers choose the right welding technique and choose solutions to minimize cracks.
Identification of the Radiative Parameters-Albedo and Optical Thickness—Of the Juncus maritimus Fiber
Authors: Borges dos Santos Marcelo , Moura Luís Mauro , Baillis Dominique
Published: February 2023

The present work aims to characterize the radiative thermal properties albedo and optical thickness of Juncus maritimus fibers using a FTIR spectrometer. Measurements of normal/directional transmittance and normal and hemispherical reflectance are performed. The numerical determination of the radiative properties is conducted through the computational treatment of the Radiative Transfer Equation (RTE) using the Discrete Ordinate Method (DOM), together with the inverse method, which is done through Gauss linearization. As it is a non-linear system, iterative calculations are necessary, which demand a significant computational cost, and, to optimize this problem, the Neumann method is used for the numerical determination of the parameters. These radiative properties are useful to quantify the radiative effective conductivity.
Thermal Ablation Experiments of Carbon Phenolic and SiC-Coated Carbon Composite Materials Using a High-Velocity Oxygen-Fuel Torch
Authors: Chinnaraj Rajesh Kumar , Kim Young Chan , Choi Seong Man
Published: February 2023

For future spacecraft TPS (heat shield) applications, ablation experiments of carbon phenolic material specimens with two lamination angles (0° and 30°) and two specially designed SiC-coated carbon–carbon composite specimens (with either cork or graphite base) were conducted using an HVOF material ablation test facility. The heat flux test conditions ranged from 3.25 to 11.5 MW/m2, corresponding to an interplanetary sample return re-entry heat flux trajectory. A two-color pyrometer, an IR camera, and thermocouples (at three internal locations) were used to measure the specimen temperature responses. At the 11.5 MW/m2 heat flux test condition, the 30° carbon phenolic specimen’s maximum surface temperature value is approximately 2327 K, which is approximately 250 K higher than the corresponding value of the SiC-coated specimen with a graphite base. The 30° carbon phenolic specimen’s recession value is approximately 44-fold greater, and the internal temperature values are approximately 1.5-fold lower than the corresponding values of the SiC-coated specimen with a graphite base. This indicates that increased surface ablation and a higher surface temperature relatively reduced heat transfer to the 30° carbon phenolic specimen’s interior, leading to lower internal temperature values compared to those of the SiC-coated specimen with a graphite base. During the tests, a phenomenon of periodic explosions occurred on the 0° carbon phenolic specimen surfaces. The 30° carbon phenolic material is considered more suitable for TPS applications due to its lower internal temperatures, as well as the absence of abnormal material behavior as observed in the 0° carbon phenolic material.
Construction of Bouquet-like Bi2Se3/Bi2O3@Bi Composites with High Interfacial Charge Separation for the Degradation of Atrazine
Authors: Han Juncheng , Pang Menghan , Meng Donghuan , Qiu Jianrong , Wang Dongbo
Published: February 2023

Using low-density solar energy in the environment and converting it into chemical energy that can drive the degradation of organic pollutants is considered to be a very promising strategy for solving the problem of environmental pollution. The efficacy of photocatalytic destruction of organic contaminants is nonetheless constrained by the high composite rate of photogenic carriers, insufficient light absorption and utilization impact, and sluggish charge transfer rate. In this work, we created a new type of heterojunction photocatalyst with a spherical Bi2Se3/Bi2O3@Bi core–shell structure and investigated its degrading properties of organic pollutants in the environment. Interestingly, benefiting from the fast electron transfer capability of the Bi0 electron bridge, the charge separation and transfer efficiency between Bi2Se3 and Bi2O3 is greatly improved. In this photocatalyst, Bi2Se3 not only has a photothermal effect to speed up the process of photocatalytic reaction, but also has fast electrical conductivity of topological materials at the surface, which speeds up the transmission efficiency of photogenic carriers. As expected, the removal performance of the Bi2Se3/Bi2O3@Bi photocatalyst to atrazine is 4.2 and 5.7 times higher than that of the original Bi2Se3 and Bi2O3. Meanwhile, the best samples Bi2Se3/Bi2O3@Bi showed 98.7%, 97.8%, 69.4%, 90.6%, 91.2%, 77.2%, 97.7%, and 98.9% removal of ATZ, 2,4-DCP, SMZ, KP, CIP, CBZ, OTC-HCl, and RhB, and 56.8%, 59.1%, 34.6%, 34.5%, 37.1%, 73.9%, and 78.4% mineralization. Through characterization such as XPS and electrochemical workstations, it is proved that the photocatalytic properties of Bi2Se3/Bi2O3@Bi catalysts are far superior to other materials, and a suitable photocatalytic mechanism is proposed. A novel form of bismuth-based compound photocatalyst is anticipated to be produced as a result of this research in order to address the increasingly critical problem of environmental water pollution in addition to presenting fresh avenues for the creation of adaptable nanomaterials for additional environmental applications.
Zinc Oxide Films Fabricated via Sol-Gel Method and Dip-Coating Technique–Effect of Sol Aging on Optical Properties, Morphology and Photocatalytic Activity
Authors: Wojtasik Katarzyna , Zięba Magdalena , Tyszkiewicz Cuma , Pakieła Wojciech , Żak Grażyna , Jeremiasz Olgierd , Gondek Ewa , Drabczyk Kazimierz , Karasiński Paweł
Published: February 2023

Zinc oxide layers on soda-lime glass substrates were fabricated using the sol-gel method and the dip-coating technique. Zinc acetate dihydrate was applied as the precursor, while diethanolamine as the stabilizing agent. This study aimed to determine what effect has the duration of the sol aging process on the properties of fabricated ZnO films. Investigations were carried out with the sol that was aged during the period from 2 to 64 days. The sol was studied using the dynamic light scattering method to determine its distribution of molecule size. The properties of ZnO layers were studied using the following methods: scanning electron microscopy, atomic force microscopy, transmission and reflection spectroscopy in the UV-Vis range, and the goniometric method for determination of the water contact angle. Furthermore, photocatalytic properties of ZnO layers were studied by the observation and quantification of the methylene blue dye degradation in an aqueous solution under UV illumination. Our studies showed that ZnO layers have grain structure, and their physical–chemical properties depend on the duration of aging. The strongest photocatalytic activity was observed for layers produced from the sol that was aged over 30 days. These layers have also the greatest porosity (37.1%) and the largest water contact angle (68.53°). Our studies have also shown that there are two absorption bands in studied ZnO layers, and values of optical energy band gaps determined from positions of maxima in reflectance characteristics are equal to those determined using the Tauc method. Optical energy band gaps of the ZnO layer fabricated from the sol aged over 30 days are EgI = 4.485 eV and EgII = 3.300 eV for the first and second bands, respectively. This layer also showed the highest photocatalytic activity, causing the pollution to degrade 79.5% after 120 min of UV irradiation. We believe that ZnO layers presented here, thanks to their attractive photocatalytic properties, may find application in environmental protection for the degradation of organic pollutants.
Materials Make a Better Life: Functional Metals, Metal Oxides, and Metal Complexes
Authors: Piszczek Piotr , Radtke Aleksandra
Published: February 2023

Materials based on metals, metal oxides, and metal complexes play an essential role in various areas of our lives [...]
Design of Functional Polymer Systems to Optimize the Filler Retention in Obtaining Cellulosic Substrates with Improved Properties
Authors: Ungureanu Elena , Fortună Maria E. , Țopa Denis C. , Lobiuc Andrei , Ungureanu Ovidiu C. , Jităreanu Doina C.
Published: February 2023

In the present work, the possibility of increasing the calcium carbonate (CaCO3) content in sheets of paper to optimize their properties was investigated. A new class of polymeric additives for papermaking is proposed as well as a method for their use in paper sheet containing the CaCO3 precipitated addition. Calcium carbonate precipitated (PCC) and fibers cellulose were adjusted with a cationic polyacrylamide flocculating agent (polydiallyldimethylammonium chloride (plyDADMAC) or cationic polyacrylamide (cPAM)). PCC was obtained in the laboratory by a double-exchange reaction between calcium chloride (CaCl2) and sodium carbonate (Na2CO3) suspension. After testing, the dosage of PCC was established at 35%. To improve the systems of additives studied, the materials obtained were characterized and their optical and mechanical properties were analysed. The PCC had a positive influence over all of the paper samples, but in the case of use of cPAM and polyDADMAC polymers the paper obtained had superior properties compared to the paper obtained without additives. Also, the samples obtained in the presence of cationic polyacrylamide exhibit superior properties to those obtained in the presence of polyDADMAC.
Microstructure, Characterization and Mechanical Properties of Coal and Coal-like Materials
Authors: Liu Xuesheng , Tan Yunliang , Wu Yunhao , Li Xuebin
Published: February 2023

Energy is the most basic driving force for world development and economic growth and the basis for human survival [...]
Si-Cr Nano-Alloys Fabricated by Direct Femtosecond Laser Writing
Authors: Maksimovic Jovan , Mu Haoran , Han Molong , Smith Daniel , Katkus Tomas , Anand Vijayakumar , Nishijima Yoshiaki , Ng Soon Hock , Juodkazis Saulius
Published: February 2023

Ultra-short 230 fs laser pulses of 515 nm wavelength were tightly focused into 700 nm focal spots and utilised in opening ∼400 nm nano-holes in a Cr etch mask that was tens-of-nm thick. The ablation threshold was found to be 2.3 nJ/pulse, double that of plain silicon. Nano-holes irradiated with pulse energies below this threshold produced nano-disks, while higher energies produced nano-rings. Both these structures were not removed by either Cr or Si etch solutions. Subtle sub-1 nJ pulse energy control was harnessed to pattern large surface areas with controlled nano-alloying of Si and Cr. This work demonstrates vacuum-free large area patterning of nanolayers by alloying them at distinct locations with sub-diffraction resolution. Such metal masks with nano-hole opening can be used for formation of random patterns of nano-needles with sub-100 nm separation when applied to dry etching of Si.
MWCNTs-TiO2 Incorporated-Mg Composites to Improve the Mechanical, Corrosion and Biological Characteristics for Use in Biomedical Fields
Authors: Amirzade-Iranaq Mohammad Taher , Omidi Mahdi , Bakhsheshi-Rad Hamid Reza , Saberi Abbas , Abazari Somayeh , Teymouri Nadia , Naeimi Farid , Sergi Claudia , Ismail Ahmad Fauzi , Sharif Safian , Berto Filippo
Published: February 2023

This study attempts to synthesize MgZn/TiO2-MWCNTs composites with varying TiO2-MWCNT concentrations using mechanical alloying and a semi-powder metallurgy process coupled with spark plasma sintering. It also aims to investigate the mechanical, corrosion, and antibacterial properties of these composites. When compared to the MgZn composite, the microhardness and compressive strength of the MgZn/TiO2-MWCNTs composites were enhanced to 79 HV and 269 MPa, respectively. The results of cell culture and viability experiments revealed that incorporating TiO2-MWCNTs increased osteoblast proliferation and attachment and enhanced the biocompatibility of the TiO2-MWCNTs nanocomposite. It was observed that the corrosion resistance of the Mg-based composite was improved and the corrosion rate was reduced to about 2.1 mm/y with the addition of 10 wt% TiO2-1 wt% MWCNTs. In vitro testing for up to 14 days revealed a reduced degradation rate following the incorporation of TiO2-MWCNTs reinforcement into a MgZn matrix alloy. Antibacterial evaluations revealed that the composite had antibacterial activity, with an inhibition zone of 3.7 mm against Staphylococcus aureus. The MgZn/TiO2-MWCNTs composite structure has great potential for use in orthopedic fracture fixation devices.
Investigation of Cross-Linked Chitosan-Based Membranes as Potential Adsorbents for the Removal of Cu2+ Ions from Aqueous Solutions
Authors: Vlachou Irene , Bokias Georgios
Published: February 2023

Rapid industrialization has led to huge amounts of organic pollutants and toxic heavy metals into aquatic environment. Among the different strategies explored, adsorption remains until the most convenient process for water remediation. In the present work, novel cross-linked chitosan-based membranes were elaborated as potential adsorbents of Cu2+ ions, using as cross-linking agent a random water-soluble copolymer P(DMAM-co-GMA) of glycidyl methacrylate (GMA) and N,N-dimethylacrylamide (DMAM). Cross-linked polymeric membranes were prepared through casting aqueous solutions of mixtures of P(DMAM-co-GMA) and chitosan hydrochloride, followed by thermal treatment at 120 °C. After deprotonation, the membranes were further explored as potential adsorbents of Cu2+ ions from aqueous CuSO4 solution. The successful complexation of copper ions with unprotonated chitosan was verified visually through the color change of the membranes and quantified through UV-vis spectroscopy. Cross-linked membranes based on unprotonated chitosan adsorb Cu2+ ions efficiently and decrease the concentration of Cu2+ ions in water to a few ppm. In addition, they can act as simple visual sensors for the detection of Cu2+ ions at low concentrations (~0.2 mM). The adsorption kinetics were well-described by a pseudo-second order and intraparticle diffusion model, while the adsorption isotherms followed the Langmuir model, revealing maximum adsorption capacities in the range of 66–130 mg/g. Finally, it was shown that the membranes can be effectively regenerated using aqueous H2SO4 solution and reused.
Experimental Characterization, Modeling, and Numerical Evaluation of a Novel Friction Damper for the Seismic Upgrade of Existing Buildings
Authors: Bruschi Eleonora , Zoccolini Luca , Cattaneo Sara , Quaglini Virginio
Published: February 2023

The paper presents the experimental characterization, the formulation of a numerical model, and the evaluation, by means of non-linear analyses, of a new friction damper conceived for the seismic upgrade of existing building frames. The damper dissipates seismic energy through the friction force triggered between a steel shaft and a lead core prestressed within a rigid steel chamber. The friction force is adjusted by controlling the prestress of the core, allowing the achievement of high forces with small dimensions, and reducing the architectural invasiveness of the device. The damper has no mechanical parts subjected to cyclic strain above their yield limit, thereby avoiding any risk of low-cycle fatigue. The constitutive behavior of the damper was assessed experimentally, demonstrating a rectangular hysteresis loop with an equivalent damping ratio of more than 55%, a stable behavior over repeated cycles, and a low dependency of the axial force on the rate of displacement. A numerical model of the damper was formulated in the OpenSees software by means of a rheological model comprising an in-parallel system of a non-linear spring element and a Maxwell element, and the model was calibrated on the experimental data. To assess the viability of the damper for the seismic rehabilitation of buildings, a numerical investigation was conducted by performing non-linear dynamic analyses on two case-study structures. The results highlight the benefits of the PS-LED in dissipating the largest part of seismic energy, limiting the lateral deformation of the frames, and controlling the increase in structural accelerations and internal forces at the same time.
Assessment of the Possibility of Reducing Energy Consumption and Environmental Pollution in the Steel Wire Manufacturing Process
Authors: Suliga Maciej , Wartacz Radosław , Kostrzewa Joanna , Hawryluk Marek
Published: February 2023

This paper describes research on the influence the technology of zinc-coated steel wire manufacturing has on the energy and force parameters of the drawing process, energy consumption and zinc expenditure. In the theoretical part of the paper, the theoretical work and drawing power were calculated. Calculations of the electric energy consumption have shown that usage of the optimal wire drawing technology results in a 37% drop in energy consumption, which in the course of a single year translates to savings equal to 13 TJ. This, in turn, results in the decrease of CO2 emissions by tons and a total decrease of the eco-costs by approximately EUR 0.5 mln. Drawing technology also influences the losses of the zinc coating and CO2 emissions. Properly adjusted parameters of the wire drawing technology allow obtaining a zinc-coating that is 100% thicker, translating to 265 tons of zinc, whose production generates 900 tons of CO2 and incurs eco-costs equal to EUR 0.6 mln. Optimal parameters for drawing, from the perspective of decreased CO2 emissions during the zinc-coated steel wire manufacturing, are as follows: usage of the hydrodynamic drawing dies, angle of the die reducing zone α = 5°, and drawing speed of 15 m/s.
Fatigue Life Prediction of Notched Details Using SWT Model and LEFM-Based Approach
Authors: Hao Rui , Wen Zongyi , Xin Haohui , Lin Weiwei
Published: February 2023

The fatigue crack initiation life of unwelded steel components accounts for the majority of the total fatigue life, and the accurate prediction of it is of vital importance. In this study, a numerical model utilizing the extended finite element method (XFEM) and Smith–Watson–Topper (SWT) model is established to predict the fatigue crack initiation life of notched details extensively used in orthotropic steel deck bridges. Using the user subroutine UDMGINI in Abaqus, a new algorithm was proposed to calculate the damage parameter of SWT under high-cycle fatigue loads. The virtual crack-closure technique (VCCT) was introduced to monitor crack propagation. Nineteen tests were performed, and the results were used to validate the proposed algorithm and XFEM model. The simulation results show that the proposed XFEM model with UDMGINI and VCCT can reasonably predict the fatigue lives of the notched specimens within the regime of high-cycle fatigue with a load ratio of 0.1. The error for the prediction of fatigue initiation life ranges from −27.5% to 41.1%, and the prediction of total fatigue life has a good agreement with the experimental results with a scatter factor of around 2.
Microstructure and Mechanical Characteristics of Ti-Ta Alloys before and after NaOH Treatment and Their Behavior in Simulated Body Fluid
Authors: Hulka Iosif , Mirza-Rosca Julia Claudia , Buzdugan Dragos , Saceleanu Adriana
Published: February 2023

In the present study, the microstructure and mechanical properties of Ti-xTa (x = 5%, 15%, and 25% wt. Ta) alloys produced by using an induced furnace by the cold crucible levitation fusion technique were investigated and compared. The microstructure was examined by scanning electron microscopy and X-ray diffraction. The alloys present a microstructure characterized by the α′ lamellar structure in a matrix of the transformed β phase. From the bulk materials, the samples for the tensile tests were prepared and based on the results and the elastic modulus was calculated by deducting the lowest values for the Ti-25Ta alloy. Moreover, a surface alkali treatment functionalization was performed using 10 M NaOH. The microstructure of the new developed films on the surface of the Ti-xTa alloys was investigated by scanning electron microscopy and the chemical analysis revealed the formation of sodium titanate and sodium tantanate along with titanium and tantalum oxides. Using low loads, the Vickers hardness test revealed increased hardness values for the alkali-treated samples. After exposure to simulated body fluid, phosphorus and calcium were identified on the surface of the new developed film, indicating the development of apatite. The corrosion resistance was evaluated by open cell potential measurements in simulated body fluid before and after NaOH treatment. The tests were performed at 22 °C as well as at 40 °C, simulating fever. The results show that the Ta content has a detrimental effect on the investigated alloys’ microstructure, hardness, elastic modulus, and corrosion behavior.
Lychee-like TiO2@Fe2O3 Core-Shell Nanostructures with Improved Lithium Storage Properties as Anode Materials for Lithium-Ion Batteries
Authors: Chen Yuan , Liu Feihong , Zhao Yufei , Ding Mengdie , Wang Juan , Zheng Xuan , Wang Huihu , Record Marie-Christine , Boulet Pascal
Published: February 2023

In this study, lychee-like TiO2@Fe2O3 microspheres with a core-shell structure have been prepared by coating Fe2O3 on the surface of TiO2 mesoporous microspheres using the homogeneous precipitation method. The structural and micromorphological characterization of TiO2@Fe2O3 microspheres has been carried out using XRD, FE-SEM, and Raman, and the results show that hematite Fe2O3 particles (7.05% of the total mass) are uniformly coated on the surface of anatase TiO2 microspheres, and the specific surface area of this material is 14.72 m2 g−1. The electrochemical performance test results show that after 200 cycles at 0.2 C current density, the specific capacity of TiO2@Fe2O3 anode material increases by 219.3% compared with anatase TiO2, reaching 591.5 mAh g−1; after 500 cycles at 2 C current density, the discharge specific capacity of TiO2@Fe2O3 reaches 273.1 mAh g−1, and its discharge specific capacity, cycle stability, and multiplicity performance are superior to those of commercial graphite. In comparison with anatase TiO2 and hematite Fe2O3, TiO2@Fe2O3 has higher conductivity and lithium-ion diffusion rate, thereby enhancing its rate performance. The electron density of states (DOS) of TiO2@Fe2O3 shows its metallic nature by DFT calculations, revealing the essential reason for the high electronic conductivity of TiO2@Fe2O3. This study presents a novel strategy for identifying suitable anode materials for commercial lithium-ion batteries.
Experimental Study on the Mechanical Behaviors of Aeolian Sand Treated by Microbially Induced Calcite Precipitation (MICP) and Basalt Fiber Reinforcement (BFR)
Authors: Liu Jia , Li Xi’an , Li Gang , Zhang Jinli
Published: February 2023

Aeolian sand flow is a major cause of land desertification, and it is prone to developing into a dust storm coupled with strong wind and thermal instability. The microbially induced calcite precipitation (MICP) technique can significantly improve the strength and integrity of sandy soils, whereas it easily leads to brittle destruction. To effectively inhibit land desertification, a method coupled with MICP and basalt fiberreinforcement (BFR) was put forward to enhance the strength and toughness of aeolian sand. Based on a permeability test and an unconfined compressive strength (UCS) test, the effects of initial dry density (ρd), fiber length (FL), and fiber content (FC) on the characteristics of permeability, strength, and CaCO3 production were analyzed, and the consolidation mechanism of the MICP-BFR method was explored. The experiments indicated that the permeability coefficient of aeolian sand increased first, then decreased, and subsequently increased with the increase in FC, whereas it exhibited a tendency to decrease first and then increase with the increase in FL. The UCS increased with the increase in the initial dry density, while it increased first and then decreased with the increase in FL and FC. Furthermore, the UCS increased linearly with the increase in CaCO3 generation, and the maximum correlation coefficient reached 0.852. The CaCO3 crystals played the roles of providing bonding, filling, and anchoring effects, and the spatial mesh structure formed by the fibers acted as a bridge effect to enhance the strength and brittle damage of aeolian sand. The findings could supply a guideline for sand solidification in desert areas.
Fluorescent Magnetic Mesoporous Nanoprobes for Biotechnological Enhancement Procedures in Gene Therapy
Authors: González-Gómez Manuel A. , Seco-Gudiña Román , García-Acevedo Pelayo , Arnosa-Prieto Ángela , de Castro-Alves Lisandra , Piñeiro Yolanda , Rivas José
Published: February 2023

In recent years, nanotechnology has deployed a new set of theragnostic tools, including magnetic resonance contrast agents, nano-delivery systems and magnetic hyperthermia treatments in cancer therapy, exploiting not only the small size of nanoparticles, but also relevant nanoscale properties such as superparamagnetism. Specifically, magnetic nanostructures can be remotely manipulated by external magnetic fields, incrementing their possibilities not only for theragnosis, but also for biotech procedures. Genetic engineering processes involve a set of steps like extracting cells from complex environments, their selection and subsequent cultivation or modification by transfection and can benefit from the use of bioconjugated magnetic nanoparticles. Magnetofection of cells with genes or biological material uploaded on superparamagnetic nanoparticles attracted by a magnetic field greatly increases the efficiency, specificity and speed of the biotechnological procedure in gene transfer systems. This article presents a preliminary investigation into the enhanced transfection efficiency of fluorescent magnetic mesoporous silica nanostructures functionalized with mCherry plasmid, which were used to transfect HeLa cells in just 15 min via magnetic transfection. This method was compared to passive transfection (4 h) and conventional gene transfer using the commercial K2 Transfection System (16 h). The results demonstrated that the fluorescent magnetic mesoporous silica nanostructures were similarly effective to the commercial kit, without the need for reagents that increase costs in clinical therapy. Furthermore, viability assays conducted with HeLa cells showed negligible toxicity at concentrations of up to 50 μg/mL.
A Multi-Factor Selection and Fusion Method through the CNN-LSTM Network for Dynamic Price Forecasting
Authors: Liu Yishun , Yang Chunhua , Huang Keke , Liu Weiping
Published: February 2023

Commodity prices are important factors for investment management and policy-making, and price forecasting can help in making better business decisions. Due to the complex and volatile nature of the market, commodity prices tend to change frequently and fluctuate violently, often influenced by many potential factors with strong nonstationary and nonlinear characteristics. Thus, it is difficult to obtain satisfactory prediction effects by only using the historical data of prices individually. To address this problem, a novel dynamic price forecasting method based on multi-factor selection and fusion with CNN-LSTM is proposed. First, the factors related to commodity price are collected, and Granger causality inference is used to identify causal factors that affect the commodity price. Then, XGBoost is used to evaluate the importance of the remaining factors and screen out critical factors to reduce the interference of redundant information. Due to the high amount and complicated changes of the selected factors, a convolutional neural network is employed to fuse the selected factors and extract the hidden features. Finally, a long short-term memory network is adopted to establish a multi-input predictor to obtain the dynamic price. Compared with several advanced approaches, the evaluation results indicate that the proposed method has an excellent performance in dynamic price forecasting.
Ensemble Methods in Customer Churn Prediction: A Comparative Analysis of the State-of-the-Art
Authors: Bogaert Matthias , Delaere Lex
Published: February 2023

In the past several single classifiers, homogeneous and heterogeneous ensembles have been proposed to detect the customers who are most likely to churn. Despite the popularity and accuracy of heterogeneous ensembles in various domains, customer churn prediction models have not yet been picked up. Moreover, there are other developments in the performance evaluation and model comparison level that have not been introduced in a systematic way. Therefore, the aim of this study is to perform a large scale benchmark study in customer churn prediction implementing these novel methods. To do so, we benchmark 33 classifiers, including 6 single classifiers, 14 homogeneous, and 13 heterogeneous ensembles across 11 datasets. Our findings indicate that heterogeneous ensembles are consistently ranked higher than homogeneous ensembles and single classifiers. It is observed that a heterogeneous ensemble with simulated annealing classifier selection is ranked the highest in terms of AUC and expected maximum profits. For accuracy, F1 measure and top-decile lift, a heterogenous ensemble optimized by non-negative binomial likelihood, and a stacked heterogeneous ensemble are, respectively, the top ranked classifiers. Our study contributes to the literature by being the first to include such an extensive set of classifiers, performance metrics, and statistical tests in a benchmark study of customer churn.
Intelligent Adaptive PID Control for the Shaft Speed of a Marine Electric Propulsion System Based on the Evidential Reasoning Rule
Authors: Zhang Xuelin , Xu Xiaobin , Xu Xiaojian , Hou Pingzhi , Gao Haibo , Ma Feng
Published: February 2023

To precisely and timely control the shaft speed for a marine electric propulsion system under normal sea conditions, a new shaft speed control technique combining the evidential reasoning rule with the traditional PID controller was proposed in this study. First, an intelligent adaptive PID controller based on the evidential reasoning rule was designed for a marine electric propulsion system to obtain the PID parameters KP, KI, and KD. Then, a local iterative optimization strategy for model parameters was proposed. Furthermore, the parameters of the adaptive PID controller model were optimized in real time by using the sequential linear programming algorithm, which enabled the adaptive adjustment of KP, KI, and KD. Finally, the performance of the adaptive PID controller regarding the shaft speed control was compared with that of other controllers. The results showed that the adaptive PID controller designed in this study had better control performance, and the shaft speed control method based on the adaptive PID controller could better control the shaft speed of the marine electric propulsion system.
First Natural Connection on Riemannian Π-Manifolds
Authors: Manev Hristo
Published: February 2023

A natural connection with torsion is defined, and it is called the first natural connection on the Riemannian Π-manifold. Relations between the introduced connection and the Levi–Civita connection are obtained. Additionally, relations between their respective curvature tensors, torsion tensors, Ricci tensors, and scalar curvatures in the main classes of a classification of Riemannian Π-manifolds are presented. An explicit example of dimension five is provided.
Third Hankel Determinant for a Subfamily of Holomorphic Functions Related with Lemniscate of Bernoulli
Authors: Orhan Halit , Çağlar Murat , Cotîrlă Luminiţa-Ioana
Published: February 2023

The main goal of this investigation is to obtain sharp upper bounds for Fekete-Szegö functional and the third Hankel determinant for a certain subclass SL∗u,v,α of holomorphic functions defined by the Carlson-Shaffer operator in the unit disk. Finally, for some special values of parameters, several corollaries were presented.
A State-of-the-Art Review of Probabilistic Portfolio Management for Future Stock Markets
Authors: Cheng Longsheng , Shadabfar Mahboubeh , Sioofy Khoojine Arash
Published: February 2023

Portfolio management has long been one of the most significant challenges in large- and small-scale investments alike. The primary objective of portfolio management is to make investments with the most favorable rate of return and the lowest amount of risk. On the other hand, time series prediction has garnered significant attention in recent years for predicting the trend of stock prices in the future. The combination of these two approaches, i.e., predicting the future stock price and adopting portfolio management methods in the forecasted time series, has turned out to be a novel research line in the past few years. That is, to have a better understanding of the future, various researchers have attempted to predict the future behavior of stocks and subsequently implement portfolio management techniques on them. However, due to the uncertainty in predicting the future, the reliability of these methodologies is in question, and it is unclear to what extent their results can be relied upon. Therefore, probabilistic approaches have also entered the research arena, and attempts have been made to incorporate uncertainty into future forecasting and portfolio management. This issue has led to the development of probabilistic portfolio management for future data. This review paper begins with a discussion of various time-series prediction methods for stock market data. Next, a classification and evaluation of portfolio management approaches are provided. Afterwards, the Monte Carlo sampling method is discussed as the most prevalent technique for probabilistic analysis of stock market data. The probabilistic portfolio management method is applied to future Shanghai Stock Exchange data in the form of a case study to measure the applicability of this method to real-world projects. The results of this research can serve as a benchmark example for the analysis of other stock market data.
Hurwitz Zeta Function Is Prime
Authors: Dundulis Marius , Garunkštis Ramūnas , Karikovas Erikas , Šimėnas Raivydas
Published: February 2023

We proved that the Hurwitz zeta function is prime. In addition, we derived the Nevanlinna characteristic for this function.
Fixed Point Results in C🟉-Algebra-Valued Partial b-Metric Spaces with Related Application
Authors: Mani Gunaseelan , Gnanaprakasam Arul Joseph , Ege Ozgur , Aloqaily Ahmad , Mlaiki Nabil
Published: February 2023

In this manuscript, we prove some fixed point theorems on C🟉-algebra-valued partial b-metric spaces by using generalized contraction. We give support and suitable examples of our main results. Moreover, we present a generative application of the main results.
Keep It Simple: A Methodological Discussion of Wage Inequalities in the Spanish Hospitality Industry
Authors: Sánchez-Cubo Francisco , Mondéjar-Jiménez José , García-Pozo Alejandro , Maltagliati Mauro
Published: February 2023

Human capital in hospitality has been widely addressed by applying sophisticated econometric methods. However, for the Spanish case, there was a gap in the analyses as the crucial importance of collective agreements was undervalued. This paper redesigns the conceptualisation of the variables and applies a subsequent new classification to job positions, as it deals with the outliers at different levels of rigorousness. Then, linearised and quantile regressions were run for each case, obtaining an outcome of thirty values for each variable. The analyses and comparisons show the high importance of collective agreements on salaries, the noticeable low values of human capital variables, and provides additional information for the nationality and gender gaps, the latter strikingly high in upper professional categories. Overall, this paper demonstrates the importance of a proper study design to prevent advanced econometric models from falling into bias and it minimises the differences between methods.
Avoiding the Worst Decisions: A Simulation and Experiment
Authors: Takemura Kazuhisa , Tamari Yuki , Ideno Takashi
Published: February 2023

Many practical decisions are more realistic concerning preventing bad decisions than seeking better ones. However, there has been no behavioral decision theory research on avoiding the worst decisions. This study is the first behavioral decision research on decision strategies from the perspective of avoiding the worst decisions. We conducted a computer simulation with the Mersenne Twister method and a psychological experiment using the monitoring information acquisition method for two-stage decision strategies of all combinations for different decision strategies: lexicographic, lexicographic semi-order, elimination by aspect, conjunctive, disjunctive, weighted additive, equally weighted additive, additive difference, and a majority of confirming dimensions. The rate of choosing the least expected utility value among the alternatives was computed as the rate of choosing the worst alternative in each condition. The results suggest that attention-based decision rules such as disjunctive strategy lead to a worse decision, and that striving to make the best choice can conversely often lead to the worst outcome. From the simulation and the experiment, we concluded that simple decision strategies such as considering what is most important can lead to avoiding the worst decisions. The findings of this study provide practical implications for decision support in emergency situations.
Government Interventions and Sovereign Bond Market Volatility during COVID-19: A Quantile Analysis
Authors: Albulescu Claudiu Tiberiu , Grecu Eugenia
Published: February 2023

We test the interaction between governments’ COVID-19 interventions, COVID-19-induced uncertainty, and the volatility of sovereign bonds. Different from previous literature, we investigate the asymmetric response of bond market volatility to both governmental interventions and COVID-19-induced uncertainty. With a focus on the first waves of the pandemic and using a panel quantile approach and a comprehensive dataset of 31 countries worldwide, we document that containment and closure policies tend to amplify volatility. Furthermore, the price variability is augmented by the spread of the pandemic itself. On the contrary, economic support policies have a substantial stabilizing effect on bond price fluctuations. Both phenomena are not subsumed by additional control variables and are robust to multiple considerations. Our findings may serve financial market participants in their risk management decisions, as well as policymakers to better shape their preparedness for future pandemics.
Preface to Computational Mathematics and Applied Statistics
Authors: Ferreira Sandra
Published: February 2023

The rapid advances in modeling research have created new challenges and opportunities for statisticians [...]
Bibliometric Review of the Literature on Cone Snail Peptide Toxins from 2000 to 2022
Authors: Nguyen Linh T. T. , Craik David J. , Kaas Quentin
Published: February 2023

The venom of marine cone snails is mainly composed of peptide toxins called conopeptides, among which conotoxins represent those that are disulfide-rich. Publications on conopeptides frequently state that conopeptides attract considerable interest for their potent and selective activity, but there has been no analysis yet that formally quantifies the popularity of the field. We fill this gap here by providing a bibliometric analysis of the literature on cone snail toxins from 2000 to 2022. Our analysis of 3028 research articles and 393 reviews revealed that research in the conopeptide field is indeed prolific, with an average of 130 research articles per year. The data show that the research is typically carried out collaboratively and worldwide, and that discoveries are truly a community-based effort. An analysis of the keywords provided with each article revealed research trends, their evolution over the studied period, and important milestones. The most employed keywords are related to pharmacology and medicinal chemistry. In 2004, the trend in keywords changed, with the pivotal event of that year being the approval by the FDA of the first peptide toxin drug, ziconotide, a conopeptide, for the treatment of intractable pain. The corresponding research article is among the top ten most cited articles in the conopeptide literature. From the time of that article, medicinal chemistry aiming at engineering conopeptides to treat neuropathic pain ramped up, as seen by an increased focus on topological modifications (e.g., cyclization), electrophysiology, and structural biology.
Possible Role of Docosahexaenoic Acid in Response to Diarrhetic Shellfish Toxins in the Mussel Perna viridis
Authors: Yuan Kuan-Kuan , Chen Zi-Min , Liu Ya-Xin , Li Hong-Ye , Yang Wei-Dong
Published: February 2023

Marine bivalves are rich in docosahexaenoic acid (DHA), a polyunsaturated fatty acid known to be beneficial for human health; however, the potential role of DHA in protecting shellfish from the toxicity of diarrhetic shellfish toxins (DSTs) remains poorly understood. Here, we aimed to study the effect of DHA on the response of the bivalve, Perna viridis, to DSTs by using LC-MS/MS, RT-qPCR, and histological examination. In this study, we observed that the DHA content decreased significantly with esterification of DSTs in the digestive gland of the mussel P. viridis after 96 h of exposure to Prorocentrum lima, a DST-producing dinoflagellate. The addition of DHA significantly increased the esterification level of DSTs and increased the expression of Nrf2 signaling pathway-related genes and enzyme activities, alleviating the damage of DSTs to digestive glands. These results suggested that DHA may mediate the esterification of DSTs and activation of the Nrf2 signaling pathway in P. viridis to protect mussels from the toxic effects of DSTs. This study may provide new insights regarding the response of bivalves to DSTs and lay the foundation for uncovering the role of DHA in environmental adaptation of bivalves.
Maternal Gestational Diabetes Is Associated with High Risk of Childhood Overweight and Obesity: A Cross-Sectional Study in Pre-School Children Aged 2–5 Years
Authors: Mantzorou Maria , Papandreou Dimitrios , Pavlidou Eleni , Papadopoulou Sousana K. , Tolia Maria , Mentzelou Maria , Poutsidi Antigoni , Antasouras Georgios , Vasios Georgios K. , Giaginis Constantinos
Published: February 2023

Background and Objectives: Childhood obesity is a global public health concern with long-term and serious health implications. An important factor for childhood obesity is maternal gestational diabetes mellitus (GDM), which in turn impacts maternal and offspring long-term health. This study aimed to investigate the associations between maternal GDM and childhood weight status and multiple anthropometric and sociodemographic factors and perinatal outcomes. Materials and Methods: A total of 5348 children aged 2–5 years old and their paired mothers took part in the study. Questionnaires were utilized to evaluate the sociodemographic factors and perinatal outcomes as well as smoking habits, educational level, economic status, age, and parity status. Children’s anthropometric parameters were measured, and maternal medical history, preterm birth records, and anthropometric measures during pregnancy were retrieved by their medical records. Results: Overall, 16.4% of the children aged at 2–5 years were overweight, and 8.2% of them were affected by obesity, leading to a total 24.6% of children with overweight/obesity. Further, 5.5% of the enrolled mothers were diagnosed with gestational diabetes mellitus. GDM doubles the probability of childhood overweight/obesity at ages 2–5 years old independently of multiple confounding factors. Pre-pregnancy overweight and obesity, older maternal age, and smoking are risk factors for GDM, while GDM additionally increases the risk of preterm birth. Children of mothers that developed GDM were at greater risk of overweight or obesity, with the association between GDM and offspring’s weight status being independent of confounding factors. Conclusions: GDM is a severe public health issue with prolonged complications for both the mother and their children. Public health approaches and programs need to promote the negative role of pre-pregnancy weight and smoking status as well as the significance of a good glycemic control throughout gestation in women of childbearing age.