bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural Causes of Brittleness Changes in Aluminosilicate Glasses with Different Cooling Rates
Authors: Zheng Liqiang , Liu Shimin , Ji Fushun , Tong Lianjie , Xu Shiqing
Published: March 2024

Numerous sources have already demonstrated that varying annealing rates can result in distinct toughness and brittleness in glass. To determine the underlying mechanisms driving this phenomenon, molecular dynamic (MD) simulations were employed to investigate the microstructure of aluminosilicate glasses under different cooling rates, and then uniaxial stretching was performed on them under controlled conditions. Results indicated that compared with short-range structure, cooling rate has a greater influence on the medium-range structure in glass, and it remarkably affects the volume of voids. Both factors play a crucial role in determining the brittleness of the glass. The former adjusts network connectivity to influence force transmission by manipulating the levels of bridging oxygen (BO) and non-bridging oxygen (NBO), and the latter accomplishes the objective of influencing brittleness by modifying the environmental conditions that affect the changes in BO and NBO content. The variation in the void environment results in differences in the strategies of the changes in BO and NBO content during glass stress. These findings stem from the excellent response of BO and NBO to the characteristic points of stress–strain curves during stretching. This paper holds importance in understanding the reasons behind the effect of cooling rates on glass brittleness and in enhancing our understanding of the ductile/brittle transition (DTB) in glass.
Energy Absorption Characteristics of Composite Material with Fiber–Foam Metal Sandwich Structure Subjected to Gas Explosion
Authors: Zhang Baoyong , Tao Jin , Cui Jiarui , Zhang Yiyu , Wang Yajun , Zhang Yingxin , Han Yonghui , Sun Man
Published: March 2024

Based on the previous research on the energy absorption of foam metal materials with different structures, a composite blast-resistant energy-absorbing material with a flexible core layer was designed. The material is composed of three different fiber materials (carbon fiber, aramid fiber, and glass fiber) as the core layer and foamed iron–nickel metal as the front and rear panels. The energy absorption characteristics were tested using a self-built gas explosion tube network experimental platform, and the energy absorption effects of different combinations of blast-resistant materials were analyzed. The purpose of this paper is to evaluate the performance of blast-resistant materials designed with flexible fiber core layers. The experimental results show that the composite structure blast-resistant material with a flexible core layer has higher energy absorption performance. The work performed in this paper shows that the use of flexible core layer materials has great research potential and engineering research value for improving energy absorption performance, reducing the mass of blast-resistant materials, and reducing production costs. It also provides thoughts for the research of biomimetic energy-absorbing materials.
Crashworthiness of 3D Lattice Topologies under Dynamic Loading: A Comprehensive Study
Authors: Bernard Autumn R. , ElSayed Mostafa S. A.
Published: March 2024

Periodic truss-based lattice materials, a particular subset of cellular solids that generally have superior specific properties as compared to monolithic materials, offer regularity and predictability that irregular foams do not. Significant advancements in alternative technologies—such as additive manufacturing—have allowed for the fabrication of these uniquely complex materials, thus boosting their research and development within industries and scientific communities. However, there have been limitations in the comparison of results for these materials between different studies reported in the literature due to differences in analysis approaches, parent materials, and boundary and initial conditions considered. Further hindering the comparison ability was that the literature generally only focused on one or a select few topologies. With a particular focus on the crashworthiness of lattice topologies, this paper presents a comprehensive study of the impact performance of 24 topologies under dynamic impact loading. Using steel alloy parent material (manufactured using Selective Laser Melting), a numerical study of the impact performance was conducted with 16 different impact energy–speed pairs. It was possible to observe the overarching trends in crashworthiness parameters, including plateau stress, densification strain, impact efficiency, and absorbed energy for a wide range of 3D lattice topologies at three relative densities. While there was no observed distinct division between the results of bending and stretching topologies, the presence of struts aligned in the impact direction did have a significant effect on the energy absorption efficiency of the lattice; topologies with struts aligned in that direction had lower efficiencies as compared to topologies without.
Upcycling of Cr-Containing Sulfate Waste into Efficient FeCrO3/Fe2O3 Catalysts for CO2 Hydrogenation Reaction
Authors: Liu Yongqi , Chu Shasha , Xu Yuebing , Chen Xinyu , Zhou Hao , Li Jinlin , Ren Yanjie , Su Xintai
Published: March 2024

Upcycling Cr-containing sulfate waste into catalysts for CO2 hydrogenation reaction benefits both pollution mitigation and economic sustainability. In this study, FeCrO3/Fe2O3 catalysts were successfully prepared by a simple hydrothermal method using Cr-containing sodium sulfate (Cr-SS) as a Cr source for efficient conversion and stable treatment of Cr. The removal rate of Cr in Cr-SS can reach 99.9% at the optimized hydrothermal conditions. When the synthesized catalysts were activated and used for the CO2 hydrogenation reaction, a 50% increase in CO2 conversion was achieved compared with the catalyst prepared by impregnation with a comparable amount of Cr. According to the extraction and risk assessment code (RAC) of the Reference Office of the European Community Bureau (BCR), the synthesized FeCrO3/Fe2O3 is risk-free. This work not only realizes the detoxification of the Cr-SS but transfers Cr into stable FeCrO3 for application in a catalytic field, which provides a strategy for the harmless disposal and resource utilization of Cr-containing hazardous waste.
Rotating Sonotrode Design for Ultrasonic-Assisted Arc Welding of Metal Materials
Authors: Mao Xinyu , Yang Zhidong , Chen Qihao , Hu Mingzhu , Gan Tian
Published: March 2024

In the process of the ultrasonic-assisted arc welding of metal materials, traditional ultrasonic application methods, such as the low-frequency impact of ultrasonic horns on a base material, can easily cause the non-fusion defect. In order to solve this problem, a rotating sonotrode with a groove and double thin ends was designed in this study. The ultrasonic vibration is transmitted into the weld pool by the rolling of the sonotrode on both sides of the weld. The resonant frequency was set at 50 kHz. Firstly, based on the Mindlin theory, a rotating sonotrode without a groove was designed by solving the frequency equation and by conducting a finite element simulation. Secondly, the effects of the groove, perforation, and transition mode on the resonant frequency, stress distribution, and amplification factor were investigated by finite element simulation. Finally, the optimum rotating sonotrode with a groove was obtained. The results show that the size of a rotating sonotrode that has a small frequency error can be obtained by using the discrete interval solver method combined with finite element simulation. The groove can significantly reduce the resonant frequency. The stress concentration can be effectively reduced by using the elliptical transition mode. The resonant frequency and amplification factor of a rotating sonotrode with a groove could be effectively adjusted by a method of double-position joint perforation. The final resonant frequency was 49.721 kHz and the amplification factor was 3.02. This study provides an effective design method for a sonotrode with double thin ends and a groove structure.
Strengthening Mechanism and Damping Properties of SiCf/Al-Mg Composites Prepared by Combining Colloidal Dispersion with a Squeeze Melt Infiltration Process
Authors: Lin Guanzhang , Sha Jianjun , Zu Yufei , Dai Jixiang , Su Cheng , Lv Zhaozhao
Published: March 2024

SiC-fiber-reinforced Al-Mg matrix composites with different mass fractions of Mg were fabricated by combining colloidal dispersion with a squeeze melt infiltration process. The microstructure, mechanical and damping properties, and the corresponding mechanisms were investigated. Microstructure analyses found that SiCf/Al-Mg composites presented a homogeneous distribution of SiC fibers, and the relative density was higher than 97% when the mass fraction of Mg was less than 20%; the fiber–matrix interface bonded well, and no obvious reaction occurred at the interface. The SiCf/Al-10Mg composite exhibited the best flexural strength (372 MPa) and elastic modulus (161.7 GPa). The fracture strain of the composites decreased with an increase in the mass fraction of Mg. This could be attributed to the strengthened interfacial bonding due to the introduction of Mg. The damping capacity at RT increased dramatically with an increase in the strain when the strain amplitude was higher than 0.001%, which was better than the alloys with similar composition, demonstrating a positive effect of the SiC fiber on improving the damping capacity of composite; the damping capacity at a temperature beyond 200 °C indicated a monotonic increase tendency with the testing temperature. This could be attributed to the second phase, which formed more strong pinning points and increased the dislocation energy needed to break away from the strong pinning points.
Microstructure and Corrosion of Mg-Based Composites Produced from Custom-Made Powders of AZ31 and Ti6Al4V via Pulse Plasma Sintering
Authors: Dobkowska Anna , Kruszewski Mirosław Jakub , Ciftci Jakub , Morończyk Bartosz , Zgłobicka Izabela , Zybała Rafał , Żrodowski Łukasz
Published: March 2024

Magnesium (Mg) and its alloys offer promise for aerospace, railway, and 3D technology applications, yet their inherent limitations, including inadequate strength, pose challenges. Magnesium matrix composites, particularly with metallic reinforcements like titanium (Ti) and its alloys, present a viable solution. Therefore, this study investigates the impact of Ti6Al4V reinforcement on AZ31 magnesium alloy composites produced using pulse plasma sintering (PPS). Results show enhanced microhardness of the materials due to improved densification and microstructural refinement. However, Ti6Al4V addition decreased corrosion resistance, leading to strong microgalvanic corrosion and substrate dissolution. Understanding these effects is crucial for designing Mg-based materials for industries like petrochemicals, where degradation-resistant materials are vital for high-pressure environments. This research provides valuable insights into developing Mg-Ti6Al4V composites with tailored properties for diverse industrial applications, highlighting the importance of considering corrosion behavior in material design. Further investigation is warranted to establish predictive correlations between Ti6Al4V content and corrosion rate for optimizing composite performance.
Processing, Microstructure, and Performance of Robocast Clay-Based Ceramics Incorporating Hollow Alumina Microspheres
Authors: Wu Yanfang , Lan Junjie , Wu Mingxuan , Wu Mingjun , Tian Li , Yang Hui , Li Qijiang , Li Yue
Published: March 2024

The restoration of ancient ceramics has attracted widespread attention as it can reveal the overall appearance of ancient ceramics as well as the original information and artistic charm of cultural relics. However, traditional manual restoration is constrained due to its time-consuming nature and susceptibility to damaging ancient ceramics. Herein, a three-dimensional (3D) printing technique was employed to accurately restore Chinese Yuan Dynasty Longquan celadon using hollow Al2O3 microsphere-modified 3D printing paste. The results show that the hollow Al2O3 microsphere content plays a vital role in the printability, physical properties, and firing performance of the modified 3D printing paste. The printed green bodies show no noticeable spacing or voids under moderate rheological conditions. The as-prepared ceramic body modified with 6 wt.% hollow Al2O3 microspheres and fired at 1280 °C exhibits optimal bending strength of 56.66 MPa and a relatively low density of 2.16 g∙cm−3, as well as a relatively uniform longitudinal elastic modulus and hardness along the interlayer. This 3D printing technique based on hollow Al2O3 microsphere-modified paste presents a promising pathway for achieving non-contact and damage-free restoration of cultural relics.
The Biofilm Inhibition Properties of Glucosamine Gold Nanoparticles in Combination with Meropenem against Pseudomonas aeruginosa on the Endotracheal Tube: A Model of Biofilm-Related Ventilator-Associated Pneumonia
Authors: Santosaningsih Dewi , Mulyastuti Yuanita , Poejiani Soeyati , Putri Rilia F. , Dewi Liliana , Arifani Hisanifa , Ni’mah Yatim L. , Baktir Afaf
Published: March 2024

Biofilm-related infections play a significant role in the development and persistence of ventilator-associated pneumonia. Pseudomonas aeruginosa (P. aeruginosa) frequently causes biofilm-related infections associated with ventilator tubing. Glucosamine gold nanoparticles (AuNPs) may exhibit antibiofilm properties; however, more studies, including combinatorial therapy with antibiotics, are needed to explore their potential applications in clinical settings. This study aims to investigate the biofilm inhibition properties of glucosamine AuNPs in combination with meropenem against P. aeruginosa ATCC 9027 on the endotracheal tube. A biofilm inhibition assay of glucosamine AuNPs at 0.02 mg/mL, both singly and in combination with meropenem at 1 mg/mL, was carried out against P. aeruginosa ATCC 9027 on an endotracheal tube using the tissue culture plate method. Scanning electron microscopy was performed for visualization. Glucosamine AuNPs at 0.02 mg/mL combined with meropenem at 1 mg/mL showed greater biofilm inhibition (72%) on the endotracheal tube than glucosamine nanoparticles at 0.02 mg/mL alone (26%) (p = 0.001). The scanning electron microscopic visualization revealed that the untreated P. aeruginosa biofilm was denser than the glucosamine nanoparticles-treated biofilm, whether combined with meropenem or using glucosamine nanoparticles alone. The combination of glucosamine AuNPs and meropenem may have the synergistic effect of inhibiting biofilm production of P. aeruginosa on the endotracheal tubes of patients with mechanical ventilation. Conducting additional experiments to explore the impact of combining glucosamine-coated gold nanoparticles (AuNPs) with meropenem on the inhibition of biofilm production by clinical P. aeruginosa isolates would be beneficial.
Design and Preliminary Evaluation of a Soft Finger Exoskeleton Controlled by Isometric Grip Force
Authors: Sanders Quentin , Reinkensmeyer David J.
Published: March 2024

Hand exoskeletons are potential solutions for enhancing upper extremity function after stroke, yet achieving intuitive control remains challenging. We recently showed that isometric grip force tracking is preserved after stroke, providing a possible control source for a hand exoskeleton. In this study, we developed a hand exoskeleton with a soft compliant mechanism and novel force control strategy that leverages isometric grip force control of digits 3–5 to control an index–thumb pinch grip. We first present characterization of the compliant mechanisms output impedance (34.77 N/m), and output force (2.3 ± 0.57 N). We then present results of a study that assessed the intuitiveness of the strategy during a grip–lift–move task in ten unimpaired individuals. From four unimpaired individuals we also gathered user preferences on force sensitivity and operating mode, where in one mode flexion force from digits 3–5 caused index finger closing, while in the other mode it caused index finger opening. The strategy proved intuitive, improving movement frequency on the grip–lift–move task by 30%. Users preferred greater force sensitivity and using flexion force from digits 3–5 to drive index finger extension. The force control strategy incorporated into the exoskeleton shows promise warranting further investigation in neurologically impaired participants.
Physical Ergonomics Monitoring in Human–Robot Collaboration: A Standard-Based Approach for Hand-Guiding Applications
Authors: Monari Eugenio , Avallone Giulia , Valori Marcello , Agostini Lorenzo , Chen Yi , Palazzi Emanuele , Vertechy Rocco
Published: March 2024

Human–robot collaboration stands as one of the research frontiers in industrial applications due to the possibility for human operators to be supported by robots in carrying out their tasks in a shared workspace. However, advances in this field can be slowed down by the lack of standards regarding the safety and ergonomics of such applications. This article aims at reducing this gap by presenting an adaptation of the standard ISO 11228-3 for the ergonomic evaluation of hand-guiding applications through the OCRA index. This innovative methodology is innovatively applied to a drilling application in which a human operator hand-guides a collaborative robotic system consisting of a Franka Emika Panda robot, a force/torque sensor and an IMU suit to track the motion of the operator’s body. The SaRAH app, a MATLAB 2020a-based software tool developed on purpose, implements the ergonomic assessment procedure, allowing the proper redesign of the working shift (offline mode) or providing the worker suggestions to improve his/her behavior (online mode) so as to reduce the ergonomic risk.
Design of a Flexure-Based Flywheel for the Storage of Angular Momentum and Kinetic Energy
Authors: Flückiger Patrick , Cosandier Florent , Schneegans Hubert , Henein Simon
Published: March 2024

The flywheel is a widespread mechanical component used for the storage of kinetic energy and angular momentum. It typically consists of cylindrical inertia rotating about its axis on rolling bearings, which involves undesired friction, lubrication, and wear. This paper presents an alternative mechanism that is functionally equivalent to a classical flywheel while relying exclusively on limited-stroke flexure joints. This novel one-degree-of-freedom zero-force mechanism has no wear and requires no lubrication: it is thus compatible with extreme environments, such as vacuum, cryogenics, or ionizing radiation. The mechanism is composed of two coupled pivoting rigid bodies whose individual angular momenta vary during motion but whose sum is constant at all times when the pivoting rate is constant. The quantitative comparison of the flexure-based flywheel to classical ones based on a hollow cylinder as inertia shows that the former typically stores 6 times less angular momentum and kinetic energy for the same mass while typically occupying 10 times more volume. The freedom of design of the shape of the rigid bodies offers the possibility of modifying the ratio of the stored kinetic energy versus angular momentum, which is not possible with classical flywheels. For example, a flexure-based flywheel with rigid pivoting bodies in the shape of thin discs stores 100 times more kinetic energy than a classical flywheel with the same angular momentum. A proof-of-concept prototype was successfully built and characterized in terms of reaction moment generation, which validates the presented analytical model.
Ni@C/PPy Composites Derived from Ni-MOF Materials for Efficient Microwave Absorption
Authors: Ma Yu , Zou Yupeng , Meng Lingsai , Cai Lijuan , Xiong Shengxiang , Chen Gang , Dong Chengjun , Guan Hongtao
Published: March 2024

Ni-MOF, as a metal–organic framework, has the advantages of morphological diversity and adjustable composition, which make its derivatives attractive for electromagnetic wave absorption. However, it is challenging for Ni-MOF derivatives to obtain strong absorption at low filling rates. Herein, ternary Ni@C/PPy composites based on Ni-MOF derivatives were synthesized by cooperatively coupling magnetic Ni@C nanoparticles with a conductive polymer PPy matrix through a facile self-assembly method. Among them, Ni@C nanoparticles are formed after Ni-MOF pyrolysis, and PPy serves as the backbone to effectively assemble and support the Ni@C nanoparticles. As a result, the Ni@C/PPy-3 sample exhibited excellent performance with a reflection loss value of −50.65 dB at a filling ratio of 15 wt% and a thickness of 2.5 mm. At the same time, its effective absorption bandwidth reached 6.24 GHz, covering the whole Ku frequency band. The results show that in comparison to pure Ni@C composite, the Ni@C/PPy multi-component composite with a porous structure shows significant advantages in terms of optimizing impedance matching, which can effectively enhance the interface polarization and, thus, greatly improve its electromagnetic absorption ability. In summary, this work provides a valuable research idea for developing strong absorbing properties of absorbing materials at a low filling rate.
Theory of Chiral Electrodeposition by Micro-Nano-Vortexes under a Vertical Magnetic Field-2: Chiral Three-Dimensional (3D) Nucleation by Nano-Vortexes
Authors: Morimoto Ryoichi , Miura Miki , Sugiyama Atsushi , Miura Makoto , Oshikiri Yoshinobu , Mogi Iwao , Yamauchi Yusuke , Aogaki Ryoichi
Published: March 2024

The contributions of magnetohydrodynamic (MHD) vortexes to chiral electrodeposition in a vertical magnetic field were theoretically examined based on the three-generation model of the 2D nucleus, 3D nucleus, and screw dislocation; for the vortexes to rotate in the second and third-generation, the kinematic viscosity must be at least 10−18 and 10−30 times lower than the ordinary value in the first generation, i.e., almost equal to zero. This implies that the ionic vacancy created on the electrode surface works as an atomic-scale lubricant. At the same time, the vortexes played three roles: promotion and suppression of nucleation, and transport of the chirality from the upper generation to the lower generation through precessional motion. Then, the rule of the chirality transfer was established, and finally, the relationship between the chiral activity and magnetic field was clarified in the presence and absence of chloride ions.
Asymptotic Antipodal Solutions as the Limit of Elliptic Relative Equilibria for the Two- and n-Body Problems in the Two-Dimensional Conformal Sphere
Authors: Ortiz Ortiz Rubén Darío , Marín Ramírez Ana Magnolia , Oviedo de Julián Ismael
Published: March 2024

We consider the two- and n-body problems on the two-dimensional conformal sphere MR2, with a radius R>0. We employ an alternative potential free of singularities at antipodal points. We study the limit of relative equilibria under the SO(2) symmetry; we examine the specific conditions under which a pair of positive-mass particles, situated at antipodal points, can maintain a state of relative equilibrium as they traverse along a geodesic. It is identified that, under an appropriate radius–mass relationship, these particles experience an unrestricted and free movement in alignment with the geodesic of the canonical Killing vector field in MR2. An even number of bodies with pairwise conjugated positions, arranged in a regular n-gon, all with the same mass m, move freely on a geodesic with suitable velocities, where this geodesic motion behaves like a relative equilibrium. Also, a center of mass formula is included. A relation is found for the relative equilibrium in the two-body problem in the sphere similar to the Snell law.
Evolutionary Model of Signed Edges in Online Networks Based on Infinite One-Dimensional Uniform Lattice
Authors: Li Zhenpeng , Yan Zhihua , Tang Xijin
Published: March 2024

The aim of this paper is to study the evolutionary dynamic model for signed edges as observed in online signed social networks. We introduce the incremental mechanism of signed edges behind a simple random walk and explain how this relates to Brownian motion and the diffusive process. We prove how a one-dimensional thermal diffusion equation can be obtained to describe such edge-generating mechanism, and moreover obtain a macroscopic probability distribution of positive and negative edges. The result reveals that the signed edge growth dynamics process can be regarded as a thermodynamic diffusion process. Both empirically and theoretically, we validate that signed network links follow the classic statistic mechanism, i.e., local Brownian motion gives rise to the global emergence pattern of the Gaussian process. The investigation might discover a new and universal characteristic for signed networks, and shed light on some potential applications, such as information spreading, evolutionary games, trust transmission, and dynamic structural balance.
SNC_Net: Skin Cancer Detection by Integrating Handcrafted and Deep Learning-Based Features Using Dermoscopy Images
Authors: Naeem Ahmad , Anees Tayyaba , Khalil Mudassir , Zahra Kiran , Naqvi Rizwan Ali , Lee Seung-Won
Published: March 2024

The medical sciences are facing a major problem with the auto-detection of disease due to the fast growth in population density. Intelligent systems assist medical professionals in early disease detection and also help to provide consistent treatment that reduces the mortality rate. Skin cancer is considered to be the deadliest and most severe kind of cancer. Medical professionals utilize dermoscopy images to make a manual diagnosis of skin cancer. This method is labor-intensive and time-consuming and demands a considerable level of expertise. Automated detection methods are necessary for the early detection of skin cancer. The occurrence of hair and air bubbles in dermoscopic images affects the diagnosis of skin cancer. This research aims to classify eight different types of skin cancer, namely actinic keratosis (AKs), dermatofibroma (DFa), melanoma (MELa), basal cell carcinoma (BCCa), squamous cell carcinoma (SCCa), melanocytic nevus (MNi), vascular lesion (VASn), and benign keratosis (BKs). In this study, we propose SNC_Net, which integrates features derived from dermoscopic images through deep learning (DL) models and handcrafted (HC) feature extraction methods with the aim of improving the performance of the classifier. A convolutional neural network (CNN) is employed for classification. Dermoscopy images from the publicly accessible ISIC 2019 dataset for skin cancer detection is utilized to train and validate the model. The performance of the proposed model is compared with four baseline models, namely EfficientNetB0 (B1), MobileNetV2 (B2), DenseNet-121 (B3), and ResNet-101 (B4), and six state-of-the-art (SOTA) classifiers. With an accuracy of 97.81%, a precision of 98.31%, a recall of 97.89%, and an F1 score of 98.10%, the proposed model outperformed the SOTA classifiers as well as the four baseline models. Moreover, an Ablation study is also performed on the proposed method to validate its performance. The proposed method therefore assists dermatologists and other medical professionals in early skin cancer detection.
Novel Approaches to the Formulation of Scheduling Problems
Authors: García-Sánchez José Manuel , Moreno Plácido
Published: March 2024

This paper presents two novel formulations for scheduling problems, namely order-position hybrid formulation (OPH) and order-disjunctive hybrid formulation (ODH), which extend and combine parts of existing formulation strategies. The first strategy (OPH) is based on sequence position and linear ordering formulations, adding relationships between constraints that allow relaxing some decision variables. The second approach (ODH) is based on linear ordering and disjunctive formulations. In this work, we prove ODH to be the most efficient formulation known so far. The experiments have been carried out with a large set of problems, which consider single machines and identical parallel machines. Computational results show that OPH is better than the rest of the existing formulations for the case of weighted completion objectives, while ODH turns out to be the best approach for most scenarios studied.
Hybrid DE-Optimized GPR and NARX/SVR Models for Forecasting Gold Spot Prices: A Case Study of the Global Commodities Market
Authors: García-Gonzalo Esperanza , García-Nieto Paulino José , Fidalgo Valverde Gregorio , Riesgo Fernández Pedro , Sánchez Lasheras Fernando , Suárez Gómez Sergio Luis
Published: March 2024

In this work, we highlight three different techniques for automatically constructing the dataset for a time-series study: the direct multi-step, the recursive multi-step, and the direct–recursive hybrid scheme. The nonlinear autoregressive with exogenous variable support vector regression (NARX SVR) and the Gaussian process regression (GPR), combined with the differential evolution (DE) for parameter tuning, are the two novel hybrid methods used in this study. The hyper-parameter settings used in the GPR and SVR training processes as part of this optimization technique DE significantly affect how accurate the regression is. The accuracy in the prediction of DE/GPR and DE/SVR, with or without NARX, is examined in this article using data on spot gold prices from the New York Commodities Exchange (COMEX) that have been made publicly available. According to RMSE statistics, the numerical results obtained demonstrate that NARX DE/SVR achieved the best results.
Transformer-Based Parameter Estimation in Statistics
Authors: Yin Xiaoxin , Yin David S.
Published: March 2024

Parameter estimation is one of the most important tasks in statistics, and is key to helping people understand the distribution behind a sample of observations. Traditionally, parameter estimation is done either by closed-form solutions (e.g., maximum likelihood estimation for Gaussian distribution) or by iterative numerical methods such as the Newton–Raphson method when a closed-form solution does not exist (e.g., for Beta distribution). In this paper, we propose a transformer-based approach to parameter estimation. Compared with existing solutions, our approach does not require a closed-form solution or any mathematical derivations. It does not even require knowing the probability density function, which is needed by numerical methods. After the transformer model is trained, only a single inference is needed to estimate the parameters of the underlying distribution based on a sample of observations. In the empirical study, we compared our approach with maximum likelihood estimation on commonly used distributions such as normal distribution, exponential distribution and beta distribution. It is shown that our approach achieves similar or better accuracy as measured by mean-square-errors.
An Algorithm for Calculating the Parameter Selection Area of a Doubly-Fed Induction Generator Based on the Guardian Map Method
Authors: Wang Yibo , Chen Futao , Jia Wei , Wang Rui
Published: March 2024

Large-scale wind farms incorporating doubly-fed induction generators (DFIGs) are considered a promising direction for modern energy supply systems due to their role in reducing dependence on fossil energy sources. However, the dynamic interactions between DFIGs and AC grids sometimes lead to sub-synchronous oscillation (SSO) that threatens the safe and stable operation of wind power systems. Therefore, it is essential to develop a mathematical model and design an algorithm to quantitatively design the control parameters. Such algorithms are helpful in preventing or mitigating system stability problems coming from wind power connected to the grid and reducing damage to power equipment. The traditional state-space model is mainly established to determine the stable operating point and analyze the influence of parameters on the system operating mode. However, this method does not provide the selection area for the system parameters. To address this shortcoming, this paper introduces a modular state-space model for DFIGs containing series compensation lines and proposes an algorithm for calculating the parameter selection area based on the Guardian map method. First, a detailed modular state-space model based on the virtual synchronous generator (VSG) control is established. The modular model helps to reflect the relationship between state variables and focuses on describing the operating state of DFIGs in wind farms. Second, this paper focuses on the influence of VSG control parameters and compensation capacitance on SSO. It aims to clarify the role of the series compensation level and control parameters on SSO based on VSG control. Then, an algorithm for the parameter selection area based on the Guardian map is proposed and the area of the VSG-controlled DFIG is obtained. Finally, the accuracy and validity of the algorithm are verified by time domain simulation in MATLAB/Simulink and HIL experiment.
Discrete Entropies of Chebyshev Polynomials
Authors: Sfetcu Răzvan-Cornel , Sfetcu Sorina-Cezarina , Preda Vasile
Published: March 2024

Because of its flexibility and multiple meanings, the concept of information entropy in its continuous or discrete form has proven to be very relevant in numerous scientific branches. For example, it is used as a measure of disorder in thermodynamics, as a measure of uncertainty in statistical mechanics as well as in classical and quantum information science, as a measure of diversity in ecological structures and as a criterion for the classification of races and species in population dynamics. Orthogonal polynomials are a useful tool in solving and interpreting differential equations. Lately, this subject has been intensively studied in many areas. For example, in statistics, by using orthogonal polynomials to fit the desired model to the data, we are able to eliminate collinearity and to seek the same information as simple polynomials. In this paper, we consider the Tsallis, Kaniadakis and Varma entropies of Chebyshev polynomials of the first kind and obtain asymptotic expansions. In the particular case of quadratic entropies, there are given concrete computations.
EFE-LSTM: A Feature Extension, Fusion and Extraction Approach Using Long Short-Term Memory for Navigation Aids State Recognition
Authors: Cao Jingjing , Wen Zhipeng , Huang Liang , Dai Jinshan , Qin Hu
Published: March 2024

Navigation aids play a crucial role in guiding ship navigation and marking safe water areas. Therefore, ensuring the accurate and efficient recognition of a navigation aid’s state is critical for maritime safety. To address the issue of sparse features in navigation aid data, this paper proposes an approach that involves three distinct processes: the extension of rank entropy space, the fusion of multi-domain features, and the extraction of hidden features (EFE). Based on these processes, this paper introduces a new LSTM model termed EFE-LSTM. Specifically, in the feature extension module, we introduce a rank entropy operator for space extension. This method effectively captures uncertainty in data distribution and the interrelationships among features. The feature fusion module introduces new features in the time domain, frequency domain, and time–frequency domain, capturing the dynamic features of signals across multiple dimensions. Finally, in the feature extraction module, we employ the BiLSTM model to capture the hidden abstract features of navigational signals, enabling the model to more effectively differentiate between various navigation aids states. Extensive experimental results on four real-world navigation aid datasets indicate that the proposed model outperforms other benchmark algorithms, achieving the highest accuracy among all state recognition models at 92.32%.
State of Health Prediction of Electric Vehicles’ Retired Batteries Based on First-Life Historical Degradation Data Using Predictive Time-Series Algorithms
Authors: Salek Farhad , Resalati Shahaboddin , Azizi Aydin , Babaie Meisam , Henshall Paul , Morrey Denise
Published: March 2024

The exponential growth of electric and hybrid vehicles, now numbering close to 6 million on the roads, has highlighted the urgent need to address the environmental impact of their lithium-ion batteries as they approach their end-of-life stages. Repurposing these batteries as second-life batteries (SLBs) for less demanding non-automotive applications is a promising avenue for extending their usefulness and reducing environmental harm. However, the shorter lifespan of SLBs brings them perilously close to their ageing knee, a critical point where further use risks thermal runaway and safety hazards. To mitigate these risks, effective battery management systems must accurately predict the state of health of these batteries. In response to this challenge, this study employs time-series artificial intelligence (AI) models to forecast battery degradation parameters using historical data from their first life cycle. Through rigorous analysis of a lithium-ion NMC cylindrical cell, the study tracks the trends in capacity and internal resistance fade across both the initial and second life stages. Leveraging the insights gained from first-life data, predictive models such as the Holt–Winters method and the nonlinear autoregressive (NAR) neural network are trained to anticipate capacity and internal resistance values during the second life period. These models demonstrate high levels of accuracy, with a maximum error rate of only 2%. Notably, the NAR neural network-based algorithm stands out for its exceptional ability to predict local noise within internal resistance values. These findings hold significant implications for the development of specifically designed battery management systems tailored for second-life batteries.
A Survey of Spatial Unit Roots
Authors: Baltagi Badi H. , Shu Junjie
Published: March 2024

This paper conducts a brief survey of spatial unit roots within the context of spatial econometrics. We summarize important concepts and assumptions in this area and study the parameter space of the spatial autoregressive coefficient, which leads to the idea of spatial unit roots. Like the case in time series, the spatial unit roots lead to spurious regression because the system cannot achieve equilibrium. This phenomenon undermines the power of the usual Ordinary Least Squares (OLS) method, so various estimation methods such as Quasi-maximum Likelihood Estimate (QMLE), Two Stage Least Squares (2SLS), and Generalized Spatial Two Stage Least Squares (GS2SLS) are explored. This paper considers the assumptions needed to guarantee the identification and asymptotic properties of these methods. Because of the potential damage of spatial unit roots, we study some test procedures to detect them. Lastly, we offer insights into how to relax the compactness assumption to avoid spatial unit roots, as well as the relationship between spatial unit roots and other models, such as the Spatial Dynamic Panel Data (SDPD) model and Lévy–Brownian motion.
Optimization of Vegetable Restocking and Pricing Strategies for Innovating Supermarket Operations Utilizing a Combination of ARIMA, LSTM, and FP-Growth Algorithms
Authors: Ping Haoyang , Li Zhuocheng , Shen Xizhu , Sun Haizhen
Published: March 2024

In the dynamic environment of fresh food supermarkets, managing the short shelf life and varying quality of vegetable products presents significant challenges. This study focuses on optimizing restocking and pricing strategies to maximize profits while accommodating the diverse and time-sensitive nature of vegetable sales. We analyze historical sales, pricing data, and loss rates of six vegetable categories in Supermarket A from 1 July 2020 to 30 June 2023. Using advanced data analysis techniques like K-means++ clustering, non-normal distribution assessments, Spearman correlation coefficients, and heat maps, we uncover significant correlations between vegetable categories and their sales patterns. The research further explores the implications of cost-plus pricing, revealing a notable relationship between pricing strategies and sales volumes. By employing Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) models, we forecast sales and determine optimal restocking volumes. Additionally, we use price elasticity theories and a comprehensive model to predict net profit changes, aiming to enhance profit margins by 47%. The study also addresses space constraints in supermarkets by proposing an effective assortment of salable items and individual product restocking plans, based on FP-Growth algorithm analysis and market demand. Our findings offer insightful strategies for sustainable and economic growth in the supermarket industry, demonstrating the impact of data-driven decision-making on operational efficiency and profitability.
Global Behavior of Solutions to a Higher-Dimensional System of Difference Equations with Lucas Numbers Coefficients
Authors: Berkal Messaoud , Navarro Juan Francisco , Abo-Zeid Raafat
Published: March 2024

In this paper, we derive the well-defined solutions to a θ-dimensional system of difference equations. We show that, the well-defined solutions to that system are represented in terms of Fibonacci and Lucas sequences. Moreover, we study the global stability of the solutions to that system. Finally, we give some numerical examples which confirm our theoretical results.
New Diterpenes and Diterpene Glycosides with Antibacterial Activity from Soft Coral Lemnalia bournei
Authors: Han Xiao , Wang Huiting , Li Bing , Chen Xiaoyi , Li Te , Yan Xia , Ouyang Han , Lin Wenhan , He Shan
Published: March 2024

Five new biflorane-type diterpenoids, biofloranates E–I (1–5), and two new bicyclic diterpene glycosides, lemnaboursides H–I (6–7), along with the known lemnabourside, were isolated from the South China Sea soft coral Lemnalia bournei. Their chemical structures and stereochemistry were determined based on extensive spectroscopic methods, including time-dependent density functional theory (TDDFT) ECD calculations, as well as a comparison of them with the reported values. The antibacterial activities of the isolated compounds were evaluated against five pathogenic bacteria, and all of these diterpenes and diterpene glycosides showed antibacterial activities against Staphylococcus aureus and Bacillus subtilis, with MICs ranging from 4 to 64 µg/mL. In addition, these compounds did not exhibit noticeable cytotoxicities on A549, Hela, and HepG2 cancer cell lines, at 20 μM.
Unlocking the Therapeutic Potential of Marine Collagen: A Scientific Exploration for Delaying Skin Aging
Authors: Rahman Azizur , Rehmani Rameesha , Pirvu Diana Gabby , Huang Siqi Maggie , Puri Simron , Arcos Mateo
Published: March 2024

Aging is closely associated with collagen degradation, impacting the structure and strength of the muscles, joints, bones, and skin. The continuous aging of the skin is a natural process that is influenced by extrinsic factors such as UV exposure, dietary patterns, smoking habits, and cosmetic supplements. Supplements that contain collagen can act as remedies that help restore vitality and youth to the skin, helping combat aging. Notably, collagen supplements enriched with essential amino acids such as proline and glycine, along with marine fish collagen, have become popular for their safety and effectiveness in mitigating the aging process. To compile the relevant literature on the anti-aging applications of marine collagen, a search and analysis of peer-reviewed papers was conducted using PubMed, Cochrane Library, Web of Science, and Embase, covering publications from 1991 to 2024. From in vitro to in vivo experiments, the reviewed studies elucidate the anti-aging benefits of marine collagen, emphasizing its role in combating skin aging by minimizing oxidative stress, photodamage, and the appearance of wrinkles. Various bioactive marine peptides exhibit diverse anti-aging properties, including free radical scavenging, apoptosis inhibition, lifespan extension in various organisms, and protective effects in aging humans. Furthermore, the topical application of hyaluronic acid is discussed as a mechanism to increase collagen production and skin moisture, contributing to the anti-aging effects of collagen supplementation. The integration of bio-tissue engineering in marine collagen applications is also explored, highlighting its proven utility in skin healing and bone regeneration applications. However, limitations to the scope of its application exist. Thus, by delving into these nuanced considerations, this review contributes to a comprehensive understanding of the potential and challenges associated with marine collagen in the realm of anti-aging applications.
Porous Nano-Fiber Structure of Modified Electrospun Chitosan GBR Membranes Improve Osteoblast Calcium Phosphate Deposition in Osteoblast-Fibroblast Co-Cultures
Authors: Su Hengjie , Fujiwara Tomoko , Skalli Omar , Selders Gretchen Schreyack , Li Ting , Mao Linna , Bumgardner Joel D.
Published: March 2024

Desirable characteristics of electrospun chitosan membranes (ESCM) for guided bone regeneration are their nanofiber structure that mimics the extracellular fiber matrix and porosity for the exchange of signals between bone and soft tissue compartments. However, ESCM are susceptible to swelling and loss of nanofiber and porous structure in physiological environments. A novel post-electrospinning method using di-tert-butyl dicarbonate (tBOC) prevents swelling and loss of nanofibrous structure better than sodium carbonate treatments. This study aimed to evaluate the hypothesis that retention of nanofiber morphology and high porosity of tBOC-modified ESCM (tBOC-ESCM) would support more bone mineralization in osteoblast-fibroblast co-cultures compared to Na2CO3 treated membranes (Na2CO3-ESCM) and solution-cast chitosan solid films (CM-film). The results showed that only the tBOC-ESCM retained the nanofibrous structure and had approximately 14 times more pore volume than Na2CO3-ESCM and thousands of times more pore volume than CM-films, respectively. In co-cultures, the tBOC-ESCM resulted in a significantly greater calcium-phosphate deposition by osteoblasts than either the Na2CO3-ESCM or CM-film (p < 0.05). This work supports the study hypothesis that tBOC-ESCM with nanofiber structure and high porosity promotes the exchange of signals between osteoblasts and fibroblasts, leading to improved mineralization in vitro and thus potentially improved bone healing and regeneration in guided bone regeneration applications
An Investigation of Quorum Sensing Inhibitors against Bacillus cereus in The Endophytic Fungus Pithomyces sacchari of the Laurencia sp.
Authors: Xiang Shi-Liang , Xu Kai-Zhong , Yin Lu-Jun , Jia Ai-Qun
Published: March 2024

Bacillus cereus, a common food-borne pathogen, forms biofilms and generates virulence factors through a quorum sensing (QS) mechanism. In this study, six compounds (dankasterone A, demethylincisterol A3, zinnimidine, cyclo-(L-Val-L-Pro), cyclo-(L-Ile-L-Pro), and cyclo-(L-Leu-L-Pro)) were isolated from the endophytic fungus Pithomyces sacchari of the Laurencia sp. in the South China Sea. Among them, demethylincisterol A3, a sterol derivative, exhibited strong QS inhibitory activity against B. cereus. The QS inhibitory activity of demethylincisterol A3 was evaluated through experiments. The minimum inhibitory concentration (MIC) of demethylincisterol A3 against B. cereus was 6.25 μg/mL. At sub-MIC concentrations, it significantly decreased biofilm formation, hindered mobility, and diminished the production of protease and hemolysin activity. Moreover, RT-qPCR results demonstrated that demethylincisterol A3 markedly inhibited the expression of QS-related genes (plcR and papR) in B. cereus. The exposure to demethylincisterol A3 resulted in the downregulation of genes (comER, tasA, rpoN, sinR, codY, nheA, hblD, and cytK) associated with biofilm formation, mobility, and virulence factors. Hence, demethylincisterol A3 is a potentially effective compound in the pipeline of innovative antimicrobial therapies.