bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental and Numerical Study of the Ultimate Flexural Capacity of a Full-Size Damaged Prestressed Concrete Box Girder Strengthened with Bonded Steel Plates
Authors: Li Yong , Yu Zijie , Liu Yongqian
Published: March 2023

Using steel plates attached with epoxy resin adhesive to strengthen prestressed reinforced concrete bridges has become a common method to increase bearing capacity in engineering because of the simple technology, low cost and good strengthening effects. The strengthening method of steel plates has been gradually applied to repair damaged bridges in practical engineering. After a cross-line box girder bridge was struck by a vehicle, the steel bars and concrete of a damaged girder were repaired and strengthened by steel plates, and then the ultimate bending bearing capacity was studied through a destructive test. The results of the destructive test were compared with those of an undamaged girder to verify the effect of the repair and strengthening of the damaged girder. The results showed that the actual flexural bearing capacity of the repaired girder strengthened by steel plates was 1.63 times the theoretical bearing capacity, 36.7% more than that of the damaged girder and 95.3% of that of an undamaged girder. The flexural cracking moment of the repaired girder strengthened by steel plates reached 66.3% of that of the undamaged girder. The maximum crack width decreased by 24.6%, and the maximum deflection increased by 2.7%, compared with the undamaged girder when the repaired girder strengthened by steel plates finally failed. Moreover, this method of attaching steel plates can increase the ductility of bridges and reduce the degree of cracking. Additionally, the actual safety factor of the repaired girder was greater than three, and it had a large safety reserve.
SiC Nanoparticles Strengthened Alumina Ceramics Prepared by Extrusion Printing
Authors: Wu Jian , Zheng Hai , Tang Mingliang , Yu Zhuqing , Pan Zhigang
Published: March 2023

Extrusion-free-form printing of alumina ceramics has the advantages of low cost, short cycle time, and high customization. However, some problems exist, such as the low solid content of ceramic paste and the unsatisfactory mechanical properties of pure alumina ceramics. In this study, SiC nanoparticles were used as a reinforcement phase added to the alumina ceramic matrix. Methylcellulose is used as the binder in the raw material system. Ammonium polyacrylate is used as a dispersant to change the rheological properties of the slurry and increase the solid content of ceramics. SiC nanoparticle-strengthened alumina ceramics were successfully prepared by the extrusion process. The relative settling height and viscosity of ceramic slurries were characterized. The sintering shrinkage of composite ceramics was tested. The flexural strength, fracture toughness, and hardness of the ceramics were characterized. The strengthening and toughening mechanisms of the composite ceramics were further explained by microscopic morphology analysis. Experimental results show that when the content of the dispersant is 1 wt.%, the rheological properties of the slurry are the best. Maximum measured bending strength (227 MPa) and fracture toughness (5.35 MPa·m1/2) were reached by adding 8 wt% SiC nanoparticles; compared with pure alumina ceramics, flexural strength and fracture toughness increased by 42% and 41%, respectively. This study provides a low-cost and effective method for preparing ceramic composite parts.
Investigation of the Damage Phenomenology with Dependence on the Macroporosity and Microporosity of Porous Freeze Foams
Authors: Maier Johanna , Werner David , Geske Vinzenz , Behnisch Thomas , Ahlhelm Mathias , Moritz Tassilo , Michaelis Alexander , Gude Maik
Published: March 2023

Freeze Foams are cellular, ceramic structures with hierarchical pore structures that are manufactured using the direct foaming process. By tailoring their morphology and strength, these foam structures are able to cover a wide range of application. Earlier works identified that pore-forming influencing factors (water and air content, suspension temperature, as well as pressure reduction rate) dictate the constitution on a macroscopic and microscopic scale. Therefore, the ability to manufacture foams whose properties align with the component requirements would be an important step in advancing towards a widespread application of these promising materials. With this goal in mind, the correlation between the pore-forming influencing factors and the resulting mechanical properties was quantified. Foams with independently adjustable porosities were produced at the micro and macro scales and evaluated according to their material failure behavior under compressive loads. As a result, foams with determined macroporosities between 38 and 62%, microporosities between 25 and 42%, and compression strengths between 1 and 7 MPa with different material failure characteristics were manufactured and systematically investigated.
Microstructural and Electrochemical Influence of Zn in MgCaZn Biodegradable Alloys
Authors: Istrate Bogdan , Munteanu Corneliu , Bălțatu Madălina-Simona , Cimpoeșu Ramona , Ioanid Nicoleta
Published: March 2023

In recent years, biodegradable materials have included magnesium alloys with homogenous disintegration and a controllable degradation rate. Utilized in medical applications, biodegradable materials based on magnesium have been widely explored throughout the years. It is well-known that alloying Mg with biocompatible and non-toxic elements increases the biodegradability of surgical alloys. The purpose of this study was to examine the microstructure and the electrochemical response (corrosion resistance) of a new experimental Mg-based biodegradable alloy—Mg–0.5%Ca with additions of Zn as follows: 0.5, 1.5, and 3.0 wt.% in order to control the corrosion rate. Immersion tests were performed for different periods in a simulated body fluid electrolyte solution at 37 °C, and the mass loss was appreciated in order to calculate the corrosion rate (CR). The investigation led to the discovery of a dendritic Mg solid solution, a lamellar Mg2Ca compound, and a MgZn2 intermetallic phase. Scanning electron microscopy, optical microscopy, and energy dispersive spectroscopy were used for surface analysis after the immersion and electro-corrosion resistance tests. The metallic and ceramic compounds that detached themselves from the sample and passed into the solution were evaluated using the SEM-EDS system. All samples presented a generalized electro-corrosion with anodic and cathodic reactions of similar intensity. The corrosion rate was similar regardless of the percentage of zinc, with a smaller value for a higher than 3 wt.% Zn percentage based on the more protective zinc oxide that appeared on the surface.
Research on an Optimized Evaluation Method of the Bearing Capacity of Reinforced Concrete Beam Based on the Bayesian Theory
Authors: Wang Lifeng , Xiao Ziwang , Yu Fei , Li Wei , Fu Ning
Published: March 2023

An optimized evaluation method of the bearing capacity of reinforced concrete beam based on the Bayesian theory was proposed in this paper. This evaluation method optimized the traditional Markov Chain-Monte Carlo (MCMC) sampling method, and proposed an improved Metropolis–Hastings (MH) sampling method and a transitive MCMC (TMCMC) sampling method based on the MCMC theory. These two derived sampling methods solved the problem that the traditional MCMC algorithm makes it difficult to achieve convergence when the number of modified parameters is large. Therefore, on the basis of obtaining the measured sample information and the prior information of uncertain parameters, this paper first used multiple “model components” to form a model sample, then carried out a sensitivity analysis based on the relevant response indicators and selected the key parameters that had a great impact on the bearing capacity, carried out static load tests, and extracted and analyzed the experimental data. Then, based on a large amount of analysis data, the improved MH sampling method and TMCMC sampling method were used to establish a posterior probability distribution database. Finally, multiple posterior probability distributions were used to identify and predict the bearing capacity. The results showed that the method was feasible and effective for the evaluation of the bearing capacity of reinforced concrete beam.
Fatigue Life Modelling of Steel Suspension Coil Springs Based on Wavelet Vibration Features Using Neuro-Fuzzy Methods
Authors: Chin C. H. , Abdullah S. , Singh S. S. K. , Ariffin A. K. , Schramm D.
Published: March 2023

This study proposed wavelet-based approaches to characterise random vibration road excitations for durability prediction of coil springs. Conventional strain-life approaches require long computational time, while the accuracy of the vibration fatigue methods is unsatisfactory. It is therefore a necessity to establish an accurate fatigue life prediction model based on vibrational features. Wavelet-based methods were applied to determine the low-frequency energy and multifractality of road excitations. Strain-life models were applied for fatigue life evaluation from strain histories. ANFIS modelling was subsequently adopted to associate the vibration features with the fatigue life of coil springs. Results showed that the proposed wavelet-based methods were effective to determine the signal energy and multifractality of vibration signals. The established vibration-based models showed good fatigue life conservativity with a data survivability of more than 90%. The highest Pearson coefficient of 0.955 associated with the lowest RMSE of 0.660 was obtained by the Morrow-based model. It is suggested that the low-frequency energy and multifractality of the vibration signals can be used as fatigue-related features in life predictions of coil springs under random loading. Finally, the proposed model is an acceptable fatigue life prediction method based on vibration features, and it can reduce the dependency on strain data measurement.
Dual-Porosity (Ta0.2Nb0.2Ti0.2Zr0.2Hf0.2)C High-Entropy Ceramics with High Compressive Strength and Low Thermal Conductivity Prepared by Pressureless Sintering
Authors: Yang Qian , Li Cuiyan , Ouyang Haibo , Gao Ruinan , Shen Tianzhan , Huang Jianfeng
Published: March 2023

Porous (Ta0.2Nb0.2Ti0.2Zr0.2Hf0.2)C high-entropy ceramics (HEC) with a dual-porosity structure were fabricated by pressureless sintering using a mixture powder of ceramic precursor and SiO2 microspheres. The carbothermal reduction in the ceramic precursor led to the formation of pores with sizes of 0.4–3 μm, while the addition of SiO2 microspheres caused the appearance of pores with sizes of 20–50 μm. The porous HECs exhibit competitive thermal insulation (4.12–1.11 W·m−1 k−1) and extraordinary compressive strength (133.1–41.9 MPa), which can be tailored by the porosity of the ceramics. The excellent properties are ascribed to the high-entropy effects and dual-porosity structures. The severe lattice distortions in the HECs lead to low intrinsic thermal conductivity and high compressive strength. The dual-porosity structure is efficient at phonon scattering and inhabiting crack propagations, which can further improve the thermal insulation and mechanical properties of the porous HECs.
Killing Two Birds with One Stone: Upgrading Organic Compounds via Electrooxidation in Electricity-Input Mode and Electricity-Output Mode
Authors: Ma Jiamin , Chen Keyu , Wang Jigang , Huang Lin , Dang Chenyang , Gu Li , Cao Xuebo
Published: March 2023

The electrochemically oxidative upgrading reaction (OUR) of organic compounds has gained enormous interest over the past few years, owing to the advantages of fast reaction kinetics, high conversion efficiency and selectivity, etc., and it exhibits great potential in becoming a key element in coupling with electricity, synthesis, energy storage and transformation. On the one hand, the kinetically more favored OUR for value-added chemical generation can potentially substitute an oxygen evolution reaction (OER) and integrate with an efficient hydrogen evolution reaction (HER) or CO2 electroreduction reaction (CO2RR) in an electricity-input mode. On the other hand, an OUR-based cell or battery (e.g., fuel cell or Zinc–air battery) enables the cogeneration of value-added chemicals and electricity in the electricity-output mode. For both situations, multiple benefits are to be obtained. Although the OUR of organic compounds is an old and rich discipline currently enjoying a revival, unfortunately, this fascinating strategy and its integration with the HER or CO2RR, and/or with electricity generation, are still in the laboratory stage. In this minireview, we summarize and highlight the latest progress and milestones of the OUR for the high-value-added chemical production and cogeneration of hydrogen, CO2 conversion in an electrolyzer and/or electricity in a primary cell. We also emphasize catalyst design, mechanism identification and system configuration. Moreover, perspectives on OUR coupling with the HER or CO2RR in an electrolyzer in the electricity-input mode, and/or the cogeneration of electricity in a primary cell in the electricity-output mode, are offered for the future development of this fascinating technology.
Optimizing Cascaded Control of Mechatronic Systems through Constrained Residual Reinforcement Learning
Authors: Staessens Tom , Lefebvre Tom , Crevecoeur Guillaume
Published: March 2023

Cascaded control structures are prevalent in industrial systems with many disturbances to obtain stable control but are cumbersome and challenging to tune. In this work, we propose cascaded constrained residual reinforcement learning (RL), an intuitive method that allows to improve the performance of a cascaded control structure while maintaining safe operation at all times. We draw inspiration from the constrained residual RL framework, in which a constrained reinforcement learning agent learns corrective adaptations to a base controller’s output to increase optimality. We first revisit the interplay between the residual agent and the baseline controller and subsequently extend this to the cascaded case. We analyze the differences and challenges this structure brings and derive some principle insights from this into the stability and operation of the cascaded residual architecture. Next, we propose a novel actor structure to enable efficient learning under the cascaded setting. We show that the standard algorithm is suboptimal for application to cascaded control structures and validate our method on a high-fidelity simulator of a dual motor drivetrain, resulting in a performance improvement of 14.7% on average, with only a minor decrease in performance occurring during the training phase. We study the different principles constituting the method and examine and validate their contribution to the algorithm’s performance under the considered cascaded control structure.
Proposal of Hybrid Discontinuous PWM Technique for Five-Phase Inverters under Open-Phase Fault Operation
Authors: Fernandez Markel , Robles Endika , Aretxabaleta Iker , Kortabarria Iñigo , Martín José Luis
Published: March 2023

One of the most common issues in inverters are open-circuit faults (OPF). In this scenario, a proper fault-tolerant technique must be used to improve the motor performance. Although basic fault-tolerant modulation techniques are normally preferred, this paper proposes a discontinuous pulse-width modulation algorithm (HD-PWM) to operate five-phase inverters under a single OPF. In particular, loss equalization between the remaining switches after a fault occurs is the main objective of the HD-PWM algorithm, thus preventing future faults from occurring. The efficiency and harmonic distortion of the proposed technique are compared to the well-known sinusoidal PWM by simulation and experimentation under OPF conditions. The results obtained show a great performance of the proposed modulation technique, obtaining a relevant efficiency improvement.
Bio-Inspired Smart Machines: Structure, Mechanisms and Applications
Authors: Wang Yanjie , Mei Dong , Liu Xiaofeng , Ji Aihong , Niu Shichao , Li Bo
Published: March 2023

With the long-term evolution of nature, each creature has its unique structure and function, which can adjust to unstructured environments with diversity [...]
Distributed Moving Horizon Fusion Estimation for Nonlinear Constrained Uncertain Systems
Authors: Wang Shoudong , Xue Binqiang
Published: March 2023

This paper studies the state estimation of a class of distributed nonlinear systems. A new robust distributed moving horizon fusion estimation (DMHFE) method is proposed to deal with the norm-bounded uncertainties and guarantee the estimation performance. Based on the given relationship between a state covariance matrix and an error covariance matrix, estimated values of the unknown parameters in the system model can be obtained. Then, a local moving horizon estimation optimization algorithm is constructed by using the measured values of sensor nodes themselves, the measured information of adjacent nodes and the prior state estimates. By solving the above nonlinear optimization problem, a local optimal state estimation is obtained. Next, based on covariance intersection (CI) fusion strategy, the local optimal state estimates sent to the fusion center are fused to derive optimal state estimates. Furthermore, the sufficient conditions for the square convergence of the fusion estimation error norm are given. Finally, a simulation example is employed to demonstrate the effectiveness of the proposed algorithm.
A Continuum Damage-Based Anisotropic Hyperelastic Fatigue Model for Short Glass Fiber Reinforced Polyamide 66
Authors: Chebbi Elouni , Ben Said Lotfi , Ayadi Badreddine , Dammak Fakhreddine
Published: March 2023

A phenomenological 3D anisotropic nonlinear fatigue damage model has been developed for a short glass fiber-reinforced polyamide. The model is formulated within the framework of continuum damage mechanics and is based on a proposed anisotropic hyperelastic strain energy function. The proposed model accounts for the effects of fiber content and nonlinear material behavior. The mechanical behavior of polyamide reinforced with 20% and 30% wt short glass fiber has been experimentally investigated under quasi-static and fatigue loading. Fatigue tests under bending loading are carried out on rectangular specimens cut in the parallel and perpendicular direction to the mold flow direction. The proposed fatigue damage model allows predicting the fatigue damage of composite materials reinforced with short fiberglass, considering fiber orientation and fiber content. The model is used to predict the damage evolution and the number of cycles to failure, and good agreement between predicted values and experimental data is observed.
Numerical Fractional Optimal Control of Respiratory Syncytial Virus Infection in Octave/MATLAB
Authors: Rosa Silvério , Torres Delfim F. M.
Published: March 2023

In this article, we develop a simple mathematical GNU Octave/MATLAB code that is easy to modify for the simulation of mathematical models governed by fractional-order differential equations, and for the resolution of fractional-order optimal control problems through Pontryagin’s maximum principle (indirect approach to optimal control). For this purpose, a fractional-order model for the respiratory syncytial virus (RSV) infection is considered. The model is an improvement of one first proposed by the authors in 2018. The initial value problem associated with the RSV infection fractional model is numerically solved using Garrapa’s fde12 solver and two simple methods coded here in Octave/MATLAB: the fractional forward Euler’s method and the predict-evaluate-correct-evaluate (PECE) method of Adams–Bashforth–Moulton. A fractional optimal control problem is then formulated having treatment as the control. The fractional Pontryagin maximum principle is used to characterize the fractional optimal control and the extremals of the problem are determined numerically through the implementation of the forward-backward PECE method. The implemented algorithms are available on GitHub and, at the end of the paper, in appendixes, both for the uncontrolled initial value problem as well as for the fractional optimal control problem, using the free GNU Octave computing software and assuring compatibility with MATLAB.
Advanced Numerical Methods in Computational Solid Mechanics
Authors: Lebon Frédéric , Ramière Isabelle
Published: March 2023

Efficient numerical solving of nonlinear solid mechanics problems is still a challenging issue which concerns various fields: nonlinear behavior, micromechanics, contact mechanics, damage, crack propagation, rupture, etc [...]
A Heuristic Approach to Forecasting and Selection of a Portfolio with Extra High Dimensions
Authors: Hu Yujia
Published: March 2023

The performance of a financial portfolio depends on the output of two tasks: first, a forecasting process, where quantities of interest for the investors, such as the rate of return and risk for each stock, are predicted into the future, and second, an optimization process, where those individual stocks are formed into the portfolio optimizing the combined risk and reward features. However, in very large dimensions, when the number of stocks is high, those two quantitative problems often become intractable because of a loss in precision. This paper introduces a forecasting and portfolio formation strategy in multiple periods based on the splitting of the multivariate forecasting model into multiple bivariate forecasting models and updating investment weights at each period based on the predicted target quantities for the returns and the covariances. The methodology proposed is suitable for a very large portfolio of assets. The experimental results are based on a sample of one thousand stocks from the Chinese stock market. For such a large sample, the forecast and optimization process is executed speedily. The investment strategies are benchmarked with the equally weighted portfolio. In the long run, they offer a better investment performance in terms of a higher rate of return or lower risk, compared with this portfolio, demonstrating the applicability and economic value of the proposed methodology in practice.
Validity Evidence for the Internal Structure of the Maslach Burnout Inventory-Student Survey: A Comparison between Classical CFA Model and the ESEM and the Bifactor Models
Authors: Aguayo-Estremera Raimundo , Cañadas Gustavo R. , Ortega-Campos Elena , Ariza Tania , De la Fuente-Solana Emilia Inmaculada
Published: March 2023

Academic burnout is a psychological problem characterized by three dimensions: emotional exhaustion, depersonalization, and personal accomplishment. This paper studies the internal structure of the MBI-SS, the most widely used instrument to assess burnout in students. The bifactor model and the ESEM approach have been proposed as alternatives, capable of overcoming the classical techniques of CFA to address this issue. Our study considers the internal structure of the MBI-SS by testing the models most frequently referenced in the literature, along with the bifactor model and the ESEM. After determining which model best fits the data, we calculate the most appropriate reliability index. In addition, we examined the validity evidence using other variables, namely the concurrent relationships with depression, anxiety, neuroticism, and conscientiousness, and the discriminant relationships with the dimensions of engagement, extraversion, and agreeableness. The results obtained indicate that the internal structure of the MBI-SS is well reflected by the three-factor congeneric oblique model, reaching good values of reliability and convergent and discriminant validity. Therefore, when the scale is used in applied contexts, we recommend considering the total scores obtained for each of the dimensions. Finally, we recommend using the omega coefficient and not the alpha coefficient as an estimator of reliability.
Quantile Regression with a New Exponentiated Odd Log-Logistic Weibull Distribution
Authors: Rodrigues Gabriela M. , Ortega Edwin M. M. , Cordeiro Gauss M. , Vila Roberto
Published: March 2023

We define a new quantile regression model based on a reparameterized exponentiated odd log-logistic Weibull distribution, and obtain some of its structural properties. It includes as sub-models some known regression models that can be utilized in many areas. The maximum likelihood method is adopted to estimate the parameters, and several simulations are performed to study the finite sample properties of the maximum likelihood estimators. The applicability of the proposed regression model is well justified by means of a gastric carcinoma dataset.
Improved Multi-Strategy Harris Hawks Optimization and Its Application in Engineering Problems
Authors: Tian Fulin , Wang Jiayang , Chu Fei
Published: March 2023

In order to compensate for the low convergence accuracy, slow rate of convergence, and easily falling into the trap of local optima for the original Harris hawks optimization (HHO) algorithm, an improved multi-strategy Harris hawks optimization (MSHHO) algorithm is proposed. First, the population is initialized by Sobol sequences to increase the diversity of the population. Second, the elite opposition-based learning strategy is incorporated to improve the versatility and quality of the solution sets. Furthermore, the energy updating strategy of the original algorithm is optimized to enhance the exploration and exploitation capability of the algorithm in a nonlinear update manner. Finally, the Gaussian walk learning strategy is introduced to avoid the algorithm being trapped in a stagnant state and slipping into a local optimum. We perform experiments on 33 benchmark functions and 2 engineering application problems to verify the performance of the proposed algorithm. The experimental results show that the improved algorithm has good performance in terms of optimization seeking accuracy, the speed of convergence, and stability, which effectively remedies the defects of the original algorithm.
Investigation of Radiochromic Film Use for Source Position Verification through a LINAC On-Board Imager (OBI)
Authors: Karaçam Songül Çavdar , Tunçman Duygu , ALMisned Ghada , Ene Antoaneta , Tekin Huseyin Ozan
Published: March 2023

Background and Objectives: Quality assurance is an integral part of brachytherapy. Traditionally, radiographic films have been used for source position verification, however, in many clinics, computerized tomography simulators have replaced conventional simulators, and computerized radiography systems have replaced radiographic film processing units. With these advances, the problem of controlling source position verification without traditional radiographic films and conventional simulators has appeared. Materials and Methods: In this study, we investigated an alternative method for source position verification for brachytherapy applications. Source positions were evaluated using Gafchromic™ RTQA2 and EBT3 film and visually compared to exposed RTQA radiochromic film when using a Nucletron Oldelft Simulix HP conventional simulator and a Gammamed 12-i brachytherapy device for performance evaluation. Gafchromic film autoradiography was performed with a linear accelerator (LINAC) on-board imager (OBI). Radiochromic films are very suitable for evaluation by visual inspection with a LINAC OBI. Results: The results showed that this type of low-cost, easy-to-find material can be used for verification purposes under clinical conditions. Conclusions: It can be concluded that source-position quality assurance may be performed through a LINAC OBI device.
Effects of Rare Earth La–Ce Alloying Treatment on Modification of Inclusions and Magnetic Properties of W350 Non-Oriented Silicon Steel
Authors: Wang Haijun , Niu Yuhao , Ling Haitao , Qiao Jialong , Zhang Yanling , Zhong Wei , Qiu Shengtao
Published: March 2023

In order to study the effects of rare earth La–Ce alloying treatment on the characteristics of inclusions in non-oriented silicon steels, industrial experiments were conducted studying the composition, morphology, size and quantity of inclusions in W350 non-oriented silicon steel during the RH (Ruhrstahl-Hereaeus) refining process and tundish process, after rare earth treatment. The products were analyzed by means of ICP-MS (inductively coupled plasma mass spectrometry), SEM/EDS (scanning electron microscope-energy dispersive spectrometry), and ASPEX (automated SEM/EDS inclusion analysis). The research results showed that the types of inclusions in experimental steel changed significantly after rare earth treatment. The types of inclusions after RE (rare earth) treatment are typically rare earth composite inclusions that are mainly composed of (La, Ce)Al2O3, and conventional inclusions. The addition of rare earth promotes the agglomeration of inclusions; the morphologies of the inclusions are mostly blocky, and some are distributed in long strips. After rare earth treatment during the RH refining process, the number of inclusions with sizes of 1.0~3.5 μm in the experimental steel is increased, and the average size of the inclusions is 2.66 μm. In addition, the number of inclusions larger than 4 μm in the specimens increases due to the collision and growth of inclusions caused by the RH circulation. After rare earth treatment during the tundish process, the number of micro inclusions with sizes of 1.0~2.5 μm in the specimen steels decreases, while the number of inclusions larger than 5 μm increases. The size distribution of micro inclusions in hot-rolled sheets after rare earth treatment was studied using TEM (transmission electron microscopy). In the specimens without rare earth, the content of micro inclusions (≤1 μm) is 51,458.2/mm2 and the average size is 0.388 μm. In the specimens with rare earth added, the content of micro inclusions (≤1 μm) is 24,230.2/mm2 and the average size is 0.427 μm. Compared to sheet produced by the original process, the iron loss of the 0.35 mm finished experimental sheet is reduced by 0.068 W/kg, and the magnetic induction is increased by 0.007 T. The iron loss of the 0.50 mm finished experimental sheet is reduced by 0.008 W/kg, and the magnetic induction is increased by 0.004 T. After rare earth treatment, the average size of micro inclusions increases and the magnetic properties are obviously improved.
A Cascade BP Neural Network Tuned PID Controller for a High-Voltage Cable-Stripping Robot
Authors: Zhong Jun , Hu Shaoguang , Wang Zhichao , Han Zhenfeng
Published: March 2023

A 10 kV distribution network is a crucial piece of infrastructure to guarantee enterprises’ and households’ access to electricity. Stripping cables is one of many power grid maintenance procedures that are now quickly expanding. However, typical cable-stripping procedures are manual and harmful to workers. Although numerous automated solutions for grid maintenance have been created, none of them focus on cable stripping, and most of them have large dimensions to guarantee multi-functions. In this paper, a new cable-stripping robot for the 10 kV power system is introduced. The design of a live working cable-stripping robot that is appropriate for installing insulating rods is introduced, taking into account the working environment of 10 kV overhead lines and the structural characteristics of overhead cables. The robot is managed by an auxiliary remote control device. A cascade PID control technology based on the back propagation neural network (BPNN) method was developed, as the stripper robot’s whole system is nonlinear and the traditional PID controller lacked robustness and adaptability in complex circumstances. To validate the structural feasibility of the cable-stripping robot, as well as the working stability and adaptability of the BPNN–PID controller, a 95 mm2 cable-stripping experiment are carried out. A comparison of the BPNN–PID controller with the traditional PID method revealed that the BPNN–PID controller has a greater capacity for speed tracking and system stability. This robot demonstrated its ability to replace manual stripping procedures and will be used for practical routine power maintenance.
Transition-Metal Dichalcogenides in Electrochemical Batteries and Solar Cells
Authors: Askari Mohammad Bagher , Salarizadeh Parisa , Veisi Payam , Samiei Elham , Saeidfirozeh Homa , Tourchi Moghadam Mohammad Taghi , Di Bartolomeo Antonio
Published: March 2023

The advent of new nanomaterials has resulted in dramatic developments in the field of energy production and storage. Due to their unique structure and properties, transition metal dichalcogenides (TMDs) are the most promising from the list of materials recently introduced in the field. The amazing progress in the use TMDs for energy storage and production inspired us to review the recent research on TMD-based catalysts and electrode materials. In this report, we examine TMDs in a variety of electrochemical batteries and solar cells with special focus on MoS2 as the most studied and used TMD material.
Research on MEMS Solid-State Fuse Logic Control Chip Based on Electrical Explosion Effect
Authors: Su Wenting , Lou Wenzhong , Feng Hengzhen , Zhao Yuecen , Lv Sining , Kan Wenxing , He Bo
Published: March 2023

A microelectromechanical systems (MEMS) solid-state logic control chip with three layers—diversion layer, control layer, and substrate layer—is designed to satisfy fuse miniaturization and integration requirements. A mathematical model is established according to the heat conduction equation, and the limit conditions of different structures are presented. The finite element multi-physical field simulation method is used to simulate the size and the action voltage of the diversion layer of the control chip. Based on the surface silicon process, fuse processing, and testing with the MEMS solid-state fuse-logic control chip, a diversion layer constant current, maximum current resistance test, and a control layer of different bridge area sizes, the bridge area size is 200 × 30 μm, and the minimum electrical explosion voltage is 23.6 V. The theoretical calculation results at 20 V and 100 μF demonstrate that the capacitor energy is insufficient to support the complete vaporization of the bridge area, but can be partially vaporized, consistent with the experimental results.
A Novel Analog Interpolation Method for Heterodyne Laser Interferometer
Authors: Chang Chung-Ping , Chang Syuan-Cheng , Wang Yung-Cheng , He Pin-Yi
Published: March 2023

Laser interferometer technology is used in the precision positioning stage as an encoder. For better resolution, laser interferometers usually work with interpolation devices. According to the interpolation factor, these devices can convert an orthogonal sinusoidal signal into several square-wave signals via digital processing. The bandwidth of the processing will be the limitation of the moving speed of the positioning stage. Therefore, the user needs to make a trade-off between the interpolation factor and the moving speed. In this investigation, a novel analog interpolation method for a heterodyne laser interferometer has been proposed. This method is based on the principle of the lock-in amplifier (LIA). By using the proposed interpolation method, the bandwidth of the laser encoder system can be independent of the interpolation factor. This will be a significant benefit for the ultra-high resolution encoder system and the laser interferometers. The concept, design, and experiment are revealed in this manuscript. The experimental results show that the proposed interpolation method can reach nanometer resolution with a heterodyne laser interferometer, and the bandwidth of the signal is independent of the resolution.
Knocking Down Gm16685 Decreases Liver Granuloma in Murine Schistosomiasis Japonica
Authors: Zhao Ruyu , Tang Xiaoxue , Lin Huiyao , Xing Chen , Xu Na , Dai Bingxin , Wang Pingping , Shao Wei , Liu Miao , Shen Jijia , Deng Shengqun , Ren Cuiping
Published: March 2023

Long noncoding RNAs (lncRNAs) can regulate key genes and pathways in liver disease development. Moreover, macrophages are speculated to play an important role in regulating granulomatous inflammation during schistosomiasis. However, the role of lncRNAs in the formation of liver granulomas by influencing the polarization of macrophages in Schistosoma japonicum infection is unclear. Our study aimed to determine whether lncRNAs can play a role in S. japonicum-induced hepatic egg granulomas and elucidate their effect on macrophages. We established S. japonicum infection models and screened the target lncRNA Gm16685 highly expressed in schistosomiasis mice using high-throughput sequencing. Hematoxylin and eosin staining revealed that the knockdown of Gm16685 reduced the area of egg granulomas. Moreover, M1 macrophage factor genes were significantly downregulated in Gm16685 knockdown livers. Meanwhile, M2 macrophage factor genes were significantly upregulated, which was consistent with the protein detection results. Hepatocytes, hepatic stellate cells, and macrophages were isolated from mouse models infected with S. japonicum, with Gm16685 being significantly upregulated in macrophages. Moreover, the knockdown of Gm16685 in RAW264.7 cells revealed similar results to in liver tissue. RNA fluorescence in situ hybridization (FISH) and nucleocytoplasmic separation experiments revealed that Gm16685 was predominantly localized in the cytoplasm of cells. We found that miR-205-5p was upregulated after Gm16685 was knocked down. After overexpression of miR-205-5p, the expression of Gm16685 and inflammatory factors was significantly downregulated. These results indicate that Gm16685 can participate in the pathogenesis of hepatic disease in schistosomiasis and promote M1 macrophage polarization by regulating miR-205-5p. Thus, our study may provide a new target for schistosomiasis japonica treatment.
Characterization of the Bacterial Microbiome in Natural Populations of Barley Stem Gall Midge, Mayetiola hordei, in Morocco
Authors: Remmal Imane , Bel Mokhtar Naima , Maurady Amal , Reda Britel Mohammed , El Fakhouri Karim , Asimakis Elias , Tsiamis George , Stathopoulou Panagiota
Published: March 2023

Mayetiola hordei (Kieffer), known as barley stem gall midge, is one of the most destructive barley pests in many areas around the world, inflicting significant qualitative and quantitative damage to crop production. In this study, we investigate the presence of reproductive symbionts, the effect of geographical origin on the bacterial microbiome’s structure, and the diversity associated with natural populations of M. hordei located in four barley-producing areas in Morocco. Wolbachia infection was discovered in 9% of the natural populations using a precise 16S rDNA PCR assay. High-throughput sequencing of the V3-V4 region of the bacterial 16S rRNA gene indicated that the native environments of samples had a substantial environmental impact on the microbiota taxonomic assortment. Briefly, 5 phyla, 7 classes, and 42 genera were identified across all the samples. To our knowledge, this is the first report on the bacterial composition of M. hordei natural populations. The presence of Wolbachia infection may assist in the diagnosis of ideal natural populations, providing a new insight into the employment of Wolbachia in the control of barley midge populations, in the context of the sterile insect technique or other biological control methods.
Assessing Continuity of Adherence to Precautionary Measures for COVID-19 among Vaccinated People in Jazan, Saudi Arabia
Authors: Alameer Anwar , Maslamani Yahya , Gosadi Ibrahim M. , Elamin Mohammed Y. , Muaddi Mohammed A. , Alqassim Ahmad Y. , Doweri Abrar , Namis Ibrahim , Busayli Fatimah , Ahmadini Hussam , Hejri Yehya , Dahlan Abdu
Published: March 2023

Background: Adherence to behavioral respiratory hygiene practices is essential in preventing the transmission of COVID-19, especially given the appearance of new variants of the COVID-19 virus. This study estimated the pre- and post-vaccination levels of adherence to COVID-19 preventive behavioral measures among vaccinated people. Methods: This cross-sectional study assessed the sociodemographics and preventive behavioral measures, and pre- and post-vaccination data, via a questionnaire. Paired t-tests and Chi-squared tests were used to assess the variation in adherence levels. Results: Of the 480 participants, 57.9% were male, and 30.4% were aged between 30 and 39 years of age. After vaccination, there was a statistically significant decline in adherence to all the assessed behavioral protective measures (p < 0.05). Being 50 years old or older, female, a healthcare worker, and a smoker were associated with higher adherence levels compared with other groups in the same categories. Conclusions: A change in the behavior of the community members regarding COVID-19 after receiving the vaccination and a reduction in adherence to respiratory hygiene practices was observed. This indicates the importance of raising awareness about the possibility of reinfection with COVID-19 despite the vaccination, and the importance of behavioral respiratory hygiene for the prevention and control of COVID-19.
Phonolite-Carbonatite Liquid Immiscibility at 3–6 GPa
Authors: Arefiev Anton V. , Shatskiy Anton , Bekhtenova Altyna , Litasov Konstantin D.
Published: March 2023

Liquid immiscibility plays an important role in the formation of carbonatites and associated alkaline Si-undersaturated magmas. Experiments in the sodium carbonate-aluminosilicate systems suggest that the carbonate-silicate miscibility gap is limited by crustal and shallow mantle pressures (up to 2.5 GPa). Unlike in the potassium-rich carbonate-aluminosilicate systems, the carbonate-silicate miscibility gap was established at pressures of 3.5–6 GPa. It is therefore interesting to elucidate the immiscibility range under intermediate pressures, corresponding to 100–200 km depths. Here we conducted experiments over 3–6 GPa and 1050–1500 °C in the systems corresponding to immiscible melts obtained by partial melting of carbonated pelite (DG2) at 6 GPa and 1200 °C. We found that partial melting begins with the alkali-rich carbonatite melt, while immiscible phonolite melt appears over 1050–1200 °C at 3 GPa, 1200 °C at 4.5 GPa, and 1200–1500 °C at 6 GPa. As pressure decreases from 6 to 3 GPa, Na becomes less compatible, and the concentration of the jadeite component in clinopyroxene decreases by a factor of 1.5–6. As a result, the compositions of the immiscible phonolite and carbonatite melts evolve from ultrapotassic (K2O/Na2O weight ratio = 10–14) resembling silicic and carbonatitic micro-inclusions in diamonds from kimberlites and placers worldwide to moderately potassic (K2O/Na2O = 1–2), which may correspond to phonolitic and associated carbonatitic melts of the spinel facies of the shallow mantle.
Ion-Imprinted Polymeric Materials for Selective Adsorption of Heavy Metal Ions from Aqueous Solution
Authors: Lazar Maria Marinela , Ghiorghita Claudiu-Augustin , Dragan Ecaterina Stela , Humelnicu Doina , Dinu Maria Valentina
Published: March 2023

The introduction of selective recognition sites toward certain heavy metal ions (HMIs) is a great challenge, which has a major role when the separation of species with similar physicochemical features is considered. In this context, ion-imprinted polymers (IIPs) developed based on the principle of molecular imprinting methodology, have emerged as an innovative solution. Recent advances in IIPs have shown that they exhibit higher selectivity coefficients than non-imprinted ones, which could support a large range of environmental applications starting from extraction and monitoring of HMIs to their detection and quantification. This review will emphasize the application of IIPs for selective removal of transition metal ions (including HMIs, precious metal ions, radionuclides, and rare earth metal ions) from aqueous solution by critically analyzing the most relevant literature studies from the last decade. In the first part of this review, the chemical components of IIPs, the main ion-imprinting technologies as well as the characterization methods used to evaluate the binding properties are briefly presented. In the second part, synthesis parameters, adsorption performance, and a descriptive analysis of solid phase extraction of heavy metal ions by various IIPs are provided.
Heterologous Biosynthesis of Myxobacterial Antibiotic Miuraenamide A
Authors: Liu Ying , Yamazaki Satoshi , Ojika Makoto
Published: March 2023

The hard-to-culture slightly halophilic myxobacterium “Paraliomyxa miuraensis” SMH-27-4 produces antifungal cyclodepsipeptide miuraenamide A (1). Herein, the region (85.9 kbp) containing the biosynthetic gene cluster (BGC) coding the assembly of 1 was identified and heterologously expressed in Myxococcus xanthus. A biosynthetic pathway proposed using in silico analysis was verified through the gene disruption of the heterologous transformant. In addition to the core polyketide synthase (PKS) and nonribosomal peptide synthase (NRPS) genes, tyrosine halogenase and O-methyltransferase genes participated in the biosynthesis of 1 as their gene-disrupted mutants produced a new congener, debromomiuraenamide A (4), and a previously isolated congener, miuraenamide E (3), respectively. Multigene disruption provided a heterologous mutant that produced 1 with the highest yield among the prepared mutants. When fed on 3-bromo-L-tyrosine, this mutant produced more 1 in the yield of 1.21 mg/L, which was 20 times higher than that produced by the initially prepared heterologous transformant. Although this yield was comparable to that of the original producer SMH-27-4 (1 mg/L), the culture time was 4.5 times shorter than that of SMH-27-4, indicating a five-fold efficiency in productivity. The results indicate the great potential of the miuraenamide BGC for the future contribution to drug development through logical gene manipulation.
Thickness Effects on Boron Doping and Electrochemical Properties of Boron-Doped Diamond Film
Authors: Long Hangyu , Hu Huawen , Wen Kui , Liu Xuezhang , Liu Shuang , Zhang Quan , Chen Ting
Published: March 2023

As a significant parameter in tuning the structure and performance of the boron-doped diamond (BDD), the thickness was focused on the mediation of the boron doping level and electrochemical properties. BDD films with different thicknesses were deposited on silicon wafers by the hot filament chemical vapor deposition (HFCVD) method. The surface morphology and composition of the BDD films were characterized by SEM and Raman, respectively. It was found that an increase in the BDD film thickness resulted in larger grain size, a reduced grain boundary, and a higher boron doping level. The electrochemical performance of the electrode equipped with the BDD film was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) in potassium ferricyanide. The results revealed that the thicker films exhibited a smaller peak potential difference, a lower charge transfer resistance, and a higher electron transfer rate. It was believed that the BDD film thickness-driven improvements of boron doping and electrochemical properties were mainly due to the columnar growth mode of CVD polycrystalline diamond film, which led to larger grain size and a lower grain boundary density with increasing film thickness.
Defect Engineering of Nanomaterials for Catalysis
Authors: Luo Yang , Wu Yinghong
Published: March 2023

Defect chemistry is a branch of materials science that deals with the study of the properties and behavior of defects in crystalline solids [...]