bluuebunny/crossref_metadata_2025 huggingface dataset:
N-(p-Toluenesulfonyl)-1-(4′-acetylphenoxy)acrylimidate: Synthesis, Crystal Structure and Theoretical Studies
Authors: Escandón-Mancilla Flor María , Cedillo-Cruz Alberto , Gordillo-Cruz Raúl Eduardo , Martínez-Otero Diego , Unnamatla M. V. Basavanag , Cuevas-Yañez Erick
Published: November 2022

The formation of N-sulfonyl-1-aryloxy acrylimidate is described, for the first time, from a consecutive process, which involves a CuAAC reaction, a ketenimine formation and subsequent rearrangement between an aryl propargyl ether and a sulfonyl azide. The structure of this newly synthesized compound was analyzed by NMR spectra and unambiguously established by X-ray analysis. In addition, theoretical calculations, which included a Hirshfeld surface, FMO, QTAIM and NCI indices analysis, corroborated the formation of π-π stacking interactions among aromatic rings, as well as C-H···O interactions between vinyl hydrogens with ketone carbonyl oxygen.
Super Hydrophobic SiO2/Phenolic Resin-Coated Filter Screen and Its Application in Efficient Oil–Water Separation
Authors: Zhao Yan , Xiao Zhongmin , Feng Ziming , Luo Qing , Liu Xiaoping , Cui Wei
Published: November 2022

The discharge of industrial liquid waste continues to cause more and more environmental problems. The current research aims at developing a durable and highly efficient filter screen for oil-water separation. In this paper, hydrophobic nano-SiO2 and phenolic resin were used as raw materials. Hydrophobic SiO2 particles were fixed on the surface of the coated filter screen by heating and curing the anchored particles. The surface morphology, element composition, surface roughness and water contact angle of the prepared super hydrophobic SiO2/phenolic resin-coated filter screen were analyzed and discussed by using SEM, EDS, AFM, OCA and other instruments. The results showed that the prepared filter screen contained Si, O, C elements, which proved that the resin coating film had adhered to the filter screen surface. When the aperture of the phenolic resin-coated filter screen was 400 meshes, the drainage angle reached a maximum value of 153.8° ± 0.8°. When two layers of hydrophobic SiO2 phenolic resin were coated on the screen, the surface of the filter screen had a sufficient nano-porous structure and high roughness. The tests showed that the minimum water contact angle of the filter screen exceeded 150°, which indicated excellent chemical resistance. Through the analysis of oil-water separation efficiency of isooctane, gasoline, n-hexane, dodecane, edible oil, dichloromethane and trichloromethane, it was concluded that the lowest separation efficiency for edible oil was 97.2%, and the highest separation efficiency for n-hexane was 99.4%. After 50 cycles of separation, the oil-water separation efficiency for n-hexane was still at 99%.
Adsorption of 2,4-D and MCPA Herbicides on Carbon Black Modified with Hydrogen Peroxide and Aminopropyltriethoxysilane
Authors: Legocka Izabella , Kuśmierek Krzysztof , Świątkowski Andrzej , Wierzbicka Ewa
Published: November 2022

The carbon black N-220 surface was subjected to modification through H2O2 oxidation and deposition of aminopropyltriethoxysilane. The pristine (CB-NM) and modified materials (CB-Ox and CB-APTES) were characterized by N2 adsorption–desorption isotherms, scanning electron microscopy, energy-dispersive X-ray spectroscopy (SEM-EDS), thermogravimetry, and FTIR spectroscopy. Carbon black samples were applied as adsorbents for the removal of 2,4-dichlorophenoxyacetic acid (2,4-D) and 2-methyl-4-chlorophenoxyacetic acid (MCPA) herbicides from aqueous solutions. The influence of their surface properties on adsorption efficiency was analyzed and discussed. The results showed that the adsorption of the herbicides was pH-dependent, and the most favorable adsorption was observed in an acidic environment. The experimental data best fit pseudo-second-order and Langmuir models for kinetic and equilibrium data, respectively. The adsorption rate of both the herbicides increased in the order of CB-APTES < CB-Ox < CB-NM and was closely correlated with the mesopore volume of the carbon blacks. The monolayer adsorption capacities were found to be 0.138, 0.340, and 0.124 mmol/g for the adsorption of 2,4-D and 0.181, 0.348, and 0.139 mmol/g for the adsorption of MCPA on CB-NM, CB-APTES, and CB-Ox, respectively. The results showed that the surface chemistry of the adsorbent plays a more important role than its porous structure. Both herbicides were preferably adsorbed on APTES-modified carbon black and were adsorbed the worst on oxidized carbon black (CB-APTES > CB-NM > CB-Ox).
Optimization Effect of Metakaolin on Macro- and Micro-Mechanical Properties of Composite Cementitious Materials under Different Curing Conditions
Authors: Liang Chao , Xing Yongming , Hou Xiaohu
Published: November 2022

To provide the theoretical basis for the engineering application of metakaolin as aluminum-rich pozzolanic ash materials, the promoting effect of metakaolin on the macro- and micro-mechanical properties of composite cement-based composite materials was explored under high-temperature steam and standard curing conditions. Analysis techniques, which involved thermogravimetric and nanoindentation coupled with scanning electron microscopy–energy dispersive X-ray spectroscopy, were used. To analyze the experimental data, the ACI empirical formula and the copula function were used. The correlation among the hydration degree of the MK-cement cementation system, the Al/Si of the C-(A)-S-H phase, and the nanomechanical properties of the C-(A)-S-H gel phase was investigated. According to prior research, the macroscopic mechanical properties and the substitution rate of the MK-cement composite cementitious system can be improved under high-temperature curing conditions in a short period, in which the optimum substitution rate of metakaolin is 20%. The ACI empirical formula was used to demonstrate the functional relationship between the metakaolin replacement rate, curing time, and compressive strength. The MK-cement cementation system can eliminate the defect phase, reduce the CH phase content, and then increase the C-(A)-S-H gel phase content and bulk density. The micro-mechanical properties of the C-(A)-S-H gel phase rises due to its phase content and Al/Si ratio. Furthermore, the copula function verifies the dependence of the nanomechanical properties of C-(A)-S-H gel and Al/Si.
Effect of Thermal Growth Oxide Composition and Morphology on Local Stresses in Thermal Barrier Coatings
Authors: Ding Kunying , Zhang Tao , Wang Zhe , Yu Jun , Guo Wansen , Yang Yifei
Published: November 2022

The failure of thermal barrier coatings (TBCs) during operation depends mainly on the thermal mismatch between the ceramic top coat (TC) and the metal bond coat (BC). The thermal mismatch at the interface is influenced by the dynamic changes in the composition and morphology of the thermally grown oxide (TGO) between TC and BC during thermal cycling. This work focuses on the establishment of a TGO dynamic growth model, which considers the changes in TGO composition and morphology for investigating the effect of dynamic growth of TGO on local mismatch stresses during thermal cycling. The results show that the sharp locations at the TGO/BC interface are more prone to high tensile stresses during thermal cycling due to the uneven growth behavior of TGO, leading to crack initiation. The valley region of the interface is in a state of compressive stress σxx during the early stages of thermal exposure. The peak region preferentially forms a concentration of tensile stress σyy. Once large-scale “layer” (Ni, Co)Al2O4-based spinel-like mixed oxides(MO) growth occurs in TGO, the stress σxx changes from compressive stress to tensile stress in the valley region, eventually forming high tensile stress (Max: +158 MPa). The maximum tensile stress σyy in the peak region is increased to 256 MPa, which is more than two times larger than the early period of thermal exposure. As a result, the dramatic changes in local stresses seriously affect the time and location of microcracks.
Research on Spheroidization of Tungsten Powder from Three Different Raw Materials
Authors: Zhang Xiuqing , Hou Xuchu , Hao Zhenhua , Wang Pei , Shu Yongchun , He Jilin
Published: November 2022

In this work, three kinds of tungsten powders with different particle sizes were spheroidized by radio-frequency (RF) inductively coupled plasma spheroidization. The spheroidization behavior of these tungsten powders was investigated and compared. The spheroidization effects of irregular tungsten powder improves with the decrease in degree of agglomeration and increases with primary particle size. Spherical tungsten powder from irregular powder with a primary particle size of 19.9 μm and an agglomeration coefficient of 1.59 had the best spheroidization effect; its apparent density, hall flow time, and spheroidization ratio are 9.36 g/cm3, 6.28 s/50 g, and 98%, respectively. The results show that irregular feedstock tungsten powder with a smaller primary particle size and higher agglomeration degree has a poor spheroidization effect because it is easily affected by the gas flow and deviates from the high temperature zone. On the contrary, irregular feedstock tungsten powder with larger primary particle sizes and lower agglomeration degrees has better spheroidization effects.
The Effect of Yttrium on the Solution and Diffusion Behaviors of Helium in Tungsten: First-Principles Simulations
Authors: Wu Mingyu , Zhang Yujuan , Qiu Kaikai , Shi Yaxian , Jin Jingyuan , Ge Changchun
Published: November 2022

We systematically investigated the influence of yttrium (Y) on the evolution behavior of helium (He) in tungsten (W) by first-principles calculations. It is found that the addition of Y reduces the solution energy of He atoms in W. Interestingly, the solution energy of He decreases with decreasing distance between Y and He. The binding energies between Y and He are inversely correlated with the effective charge of He atoms, which can be attributed to the closed shell structure of He. In addition, compared with pure W, the diffusion barrier (0.033 eV) of He with Y is lower, calculated by the climbing-image nudged elastic band (CI-NEB) simulations, reflecting that the existence of Y contributes to the diffusion of He in W. The obtained results provide a theoretical direction for understanding the diffusion of He.
A Facile Approach to the Hydrothermal Synthesis of Silica Nanoparticle/Carbon Nanostructure Luminescent Composites
Authors: Podkolodnaya Yuliya A. , Kokorina Alina A. , Goryacheva Irina Yu.
Published: November 2022

Luminescent carbon nanostructures (CNSs) have been intensively researched, but there is still no consensus on a fundamental understanding of their structure and properties that limits their potential applications. In this study, we developed a facile approach to the synthesis of luminescent composite SiO2 nanoparticles/CNSs by the targeted formation of a molecular fluorophore, as the significant luminescent component of CNSs, on the surface of a silica matrix during a one-stage hydrothermal synthesis. Silica nanoparticles were synthesized by reverse microemulsion and used as a matrix for luminescent composites. The as-prepared silica nanoparticles had a functional surface, a spherical shape, and a narrow size distribution of about 29 nm. One-stage hydrothermal treatment of citric acid and modified silica nanoparticles made it possible to directly form the luminescent composite. The optical properties of composites could be easily controlled by changing the hydrothermal reaction time and temperature. Thus, we successfully synthesized luminescent composites with an emission maximum of 450 nm, a quantum yield (QY) of 65 ± 4%, and an average size of ~26 nm. The synthesis of fluorophore doped composite, in contrast to CNSs, makes it possible to control the shape, size, and surface functionality of particles and allows for avoiding difficult and time-consuming fractionation steps.
Cooling Subgrade Effectiveness by L-Shaped Two-Phase Closed Thermosyphons with Different Inclination Angles and XPS Insulation Boards in Permafrost Regions
Authors: Zhou Yalong , Wang Xu , Guo Chunxiang , Hu Yuan , He Fei , Liu Deren , Jiang Daijun
Published: November 2022

This study focused on the coupling heat transfer mechanism and the cooling efficiency of L-shaped two-phase closed thermosyphons (L-shaped TPCTs) in the wide subgrade of permafrost regions. Considering the fact that time–space dynamics change the effects of the air temperature, wind speed, and geotemperature, a coupled air temperature–L-shaped TPCT–subgrade soil heat transfer model was established using the ANSYS 15.0 software platform, and the rationality of the model was verified through measured data. The heat-transfer characteristics of the L-shaped TPCTs and the long-term thermal stability of the subgrade were studied under different inclination angles of the evaporator (α = 15°, 30°, 50°, 70°, and 90°). Then, the cooling effectiveness of a composite subgrade with TPCTs and an XPS insulation board was numerically calculated. The results show that the heat flux of the L-shaped TPCT was the greatest when α = 50°, and the heat flux reached the maximum value of 165.7 W·m−2 in January. The L-shaped TPCT had a relatively good cooling effect on the subgrade as a whole when α = 50° and 70°, but the thawing depth at the center of the subgrade with L-shaped TPCTs reached 9.0 m below the ground surface in the 30th year. The composite subgrade with L-shaped TPCTs/vertical TPCT/XPS insulation board is an effective method to protect the permafrost foundation and improve the long-term thermal stability of the wide subgrade. The maximum heat flux of evaporation section of the L-shaped TPCT is 18.8% higher than that of the vertical TPCT during the working period of the TPCTs of the composite subgrade.
Implementation of a Lean 4.0 Project to Reduce Non-Value Add Waste in a Medical Device Company
Authors: Foley Ida , McDermott Olivia , Rosa Angelo , Kharub Manjeet
Published: November 2022

The fourth industrial revolution, also referred to as Industry 4.0, has resulted in many changes within the manufacturing industry. The purpose of the study is to demonstrate how an Industry 4.0 project was scoped and deployed utilising Lean tools to reduce non-value add wastes and aid regulatory compliance. A case study research approach was utilised to demonstrate how the Lean Industry 4.0 project was implemented in a Medtech company to enhance Lean processes while increasing digitalisation. This research demonstrates that Industry 4.0 can enhance Lean, improve flow, reduce nonvalue add waste, and facilitate product lifecycle regulatory compliance to reduce defects, enhance quality, improve cycle time, and minimise reworks and over-processing. Lean and Industry 4.0 combined offer many benefits to the MedTech Industry. This research will support organisations in demonstrating how digital technologies can synergistically affect Lean processes, positively impact product lifecycle regulatory compliance, and support the industry in building a business case for future implementation of Industry 4.0 technologies.
A Digital Twin Model of Three-Dimensional Shading for Simulation of the Ironmaking Process
Authors: Lei Yongxiang , Karimi Hamid Reza
Published: November 2022

Advanced manufacturing is a new trend for sustainable industrial development, and digital twin is a new technology that has attracted attention. Blast furnace smelting is an effective method in the manufacturing of iron and steel. Comprehensive and dependable surveillance of the blast furnace smelting process is essential for ensuring the smooth operation and improving of iron and steel output quality. The current technology makes it difficult to monitor the entire process of blast furnace ironmaking. Based on Unity 3D, this study presents a digital-twin virtual reality simulation system of blast furnace ironmaking. First, shading modeling creates a three-dimensional dynamic geometric model in different ironmaking system scenarios. Then, we script the animation and call particle system according to the motion mode of distinct geometric objects to give the dynamic effect of geometric objects. Shaders are the focus of the design and contributions. In addition, shader optimization technology can reduce hardware resource consumption and increase system fluency. Vertex shaders are used for all types of coordinate space transformation and vertex output; fragment shaders are used for texture sampling, light model calculation, normal calculation, noise superposition, and color output. The shader rendering technique allows for more realistic lighting effects. The presented dynamic digital twin system implements more realistic lighting analyzed in the ironmaking process. Virtual interaction logic’s design and deployment process is based on HTC VIVE hardware and VRTK toolkit. In the actual simulation process, the typical animation frame rate is stable at about 75 FPS (frames per second). The simulation system runs smoothly and a cutting-edge and state-of-the-art method for observing the blast furnace ironmaking process is suggested.
Energy Saving Characteristics of a Winch System Driven by a Four-Quadrant Hydraulic Pump
Authors: Ren Haoling , Wu Shiyi , Lin Tianliang , Zhang Yonghua , Miao Cheng , Li Zhongshen
Published: November 2022

In this study, an integrated system of winch driving and potential energy recovery using a four-quadrant pump was proposed, aimed at the large amount of recoverable gravitational potential energy in a winch system. The proposed system changed the original open system into a closed-structure part, using a four-quadrant pump to drive the winch, and an open-structure part, using an open hydraulic pump to balance torque. The closed-structure and open-structure parts were coaxial, and connected with the engine through the transfer case, which was able to make full use of the four-quadrant pump characteristics. It was able to achieve flow regeneration when the weight was lowered, and to achieve direct use of gravitational potential energy. The AMESim model of the original and proposed systems was further established according to a working characteristics analysis of the energy consumption of the winch-driving system. The simulation results verified that the proposed system kept good controllability while recovering potential energy. An experimental prototype was built; the test results showed that, compared with the original winch system, the proposed system increased lifting speed and reduced fuel consumption significantly. Additionally, diesel consumption was reduced by 87% in the descending process.
Amorphous Carbon Films with Embedded Well-Dispersed Nanodiamonds: Plasmon-Enhanced Analysis and Possible Antimicrobial Applications
Authors: Streletskiy Oleg , Perevedentseva Elena , Zavidovskiy Ilya , Karmenyan Artashes , Sychev Vladimir , Sadykova Vera , Kuvarina Anastasia , Cheng Chia-Liang
Published: November 2022

An amorphous carbon film with embedded detonation nanodiamond (DND) particles (a-C:ND) was produced by magnetron sputtering of nanodiamond powder. An Ag film was deposited on the carbon structure by radiofrequency magnetron sputtering. The silver film was irradiated with a 150 eV Ar+ to form plasmonic-active nanoparticles (NP) on the surface of the a-C:ND. The structure of the obtained a-C:ND and a-C:ND/Ag structures were studied by scanning and transmission electron microscopy, electron energy-loss spectroscopy, UV–Visible absorption spectroscopy, Raman spectroscopy, and fluorescence lifetime imaging at two-photon excitation. The analysis revealed 76% of sp3-carbon and a good dispersion of diamond nanoparticles in the a-C. Surface-enhanced Raman scattering (SERS) was applied to investigate the a-C:ND/Ag structure, allowing for the observation of SERS from the sp2-carbon species and the absence of significant a-C:ND damage after Ar+ irradiation of the Ag overlayer. A plasmonic-metal-enhanced luminescence was observed at one- and two-photon excitations, revealing a two- to five-fold intensity increase. The activity of the used DNDs was tested using the agar diffusion method and observed against the bacteria of Bacillus subtilis, Staphylococcus aureus, and Escherichia coli and the fungi of Aspergillus niger, Aspergillus fumigatus, and the yeast of Candida albicans, showing DND activity against all the test strains of fungi.
Interaction of Variable Fluid Properties with Electrokinetically Modulated Peristaltic Flow of Reactive Nanofluid: A Thermodynamical Analysis
Authors: Akbar Yasir , Huang Shiping , Alotaibi Hammad
Published: November 2022

In the present study, the interaction of variable fluid properties with electrokinetically regulated peristaltic transportation of a reactive nanofluid embedded in a porous space is studied. The nanofluid saturates the porous space/medium with inhomogeneous porosity, which changes with distance from the channel boundary. It is assumed that nanofluids are accompanied by variable thermal conductivity and viscosity. The impacts of magnetic field, Brownian motion, electric field, viscous dissipation, chemical reaction, mixed convection, and thermophoresis are incorporated. Moreover, the contribution of zero mass flux boundary condition is executed. The complexity of the equations describing the flow of a nanofluid is reduced by applying the lubrication theory. The fully non-linear equations are solved by utilizing a numerical technique. Particular attention is paid to the analysis of entropy optimization, since its minimization is the best measure to enhance the efficiency of thermal systems. These results demonstrate that a positively oriented external electric field contributes to an increase in nanofluid velocity. Temperature of nanofluid increases more rapidly due to an augmentation in Joule heating parameter. It is noticed that the temperature of water is comparatively lower than that of kerosene. The system’s energy loss can be reduced when the thermal conductivity parameter enhance. The magnitude of Bejan number is enhanced by increasing electroosmotic parameter. Further, a substantial decrement in concentration profile is perceived when the Schmidt number is augmented.
The Groups of Isometries of Metric Spaces over Vector Groups
Authors: Bau Sheng , Lei Yiming
Published: November 2022

In this paper, we consider the groups of isometries of metric spaces arising from finitely generated additive abelian groups. Let A be a finitely generated additive abelian group. Let R={1,ϱ} where ϱ is a reflection at the origin and T={ta:A→A,ta(x)=x+a,a∈A}. We show that (1) for any finitely generated additive abelian group A and finite generating set S with 0∉S and −S=S, the maximum subgroup of IsomX(A,S) is RT; (2) D⊴RT if and only if D≤T or D=RT′ where T′={h2:h∈T}; (3) for the vector groups over integers with finite generating set S={u∈Zn:|u|=1}, IsomX(Zn,S)=On(Z)Zn. The paper also includes a few intermediate technical results.
Dynamic Constrained Boundary Method for Constrained Multi-Objective Optimization
Authors: Wang Qiuzhen , Liang Zhibing , Zou Juan , Yin Xiangdong , Liu Yuan , Hu Yaru , Xia Yizhang
Published: November 2022

When solving complex constrained problems, how to efficiently utilize promising infeasible solutions is an essential issue because these promising infeasible solutions can significantly improve the diversity of algorithms. However, most existing constrained multi-objective evolutionary algorithms (CMOEAs) do not fully exploit these promising infeasible solutions. In order to solve this problem, a constrained multi-objective optimization evolutionary algorithm based on the dynamic constraint boundary method is proposed (CDCBM). The proposed algorithm continuously searches for promising infeasible solutions between UPF (the unconstrained Pareto front) and CPF (the constrained Pareto front) during the evolution process by the dynamically changing auxiliary population of the constraint boundary, which continuously provides supplementary evolutionary directions to the main population and improves the convergence and diversity of the main population. Extensive experiments on three well-known test suites and three real-world constrained multi-objective optimization problems demonstrate that CDCBM is more competitive than seven state-of-the-art CMOEAs.
Three-Branch Random Forest Intrusion Detection Model
Authors: Zhang Chunying , Wang Wenjie , Liu Lu , Ren Jing , Wang Liya
Published: November 2022

Network intrusion detection has the problems of large amounts of data, numerous attributes, and different levels of importance for each attribute in detection. However, in random forests, the detection results have large deviations due to the random selection of attributes. Therefore, aiming at the current problems, considering increasing the probability of essential features being selected, a network intrusion detection model based on three-way selected random forest (IDTSRF) is proposed, which integrates three decision branches and random forest. Firstly, according to the characteristics of attributes, it is proposed to evaluate the importance of attributes by combining decision boundary entropy, and using three decision rules to divide attributes; secondly, to keep the randomness of attributes, three attribute random selection rules based on attribute randomness are established, and a certain number of attributes are randomly selected from three candidate fields according to conditions; finally, the training sample set is formed by using autonomous sampling method to select samples and combining three randomly selected attribute sets randomly, and multiple decision trees are trained to form a random forest. The experimental results show that the model has high precision and recall.
Characterization of All Graphs with a Failed Skew Zero Forcing Number of 1
Authors: Johnson Aidan , Vick Andrew E. , Narayan Darren A.
Published: November 2022

Given a graph G, the zero forcing number of G, Z(G), is the minimum cardinality of any set S of vertices of which repeated applications of the forcing rule results in all vertices being in S. The forcing rule is: if a vertex v is in S, and exactly one neighbor u of v is not in S, then u is added to S in the next iteration. Hence the failed zero forcing number of a graph was defined to be the cardinality of the largest set of vertices which fails to force all vertices in the graph. A similar property called skew zero forcing was defined so that if there is exactly one neighbor u of v is not in S, then u is added to S in the next iteration. The difference is that vertices that are not in S can force other vertices. This leads to the failed skew zero forcing number of a graph, which is denoted by F−(G). In this paper, we provide a complete characterization of all graphs with F−(G)=1. Fetcie, Jacob, and Saavedra showed that the only graphs with a failed zero forcing number of 1 are either: the union of two isolated vertices; P3; K3; or K4. In this paper, we provide a surprising result: changing the forcing rule to a skew-forcing rule results in an infinite number of graphs with F−(G)=1.
Kinematic Modeling and Stiffness Analysis of a 3-DOF 3SPS + 3PRS Parallel Manipulator
Authors: Zhou Shenghao , Gao Houkun , Xu Chunyang , Jia Zhichao , Lin Junzhe , Han Qingkai , Luo Zhong
Published: November 2022

The driving mechanism of an axisymmetric vectoring exhaust nozzle (AVEN) is a 3-degrees-of-freedom (3-DOF) parallel manipulator (PM) with a centering device. According to the characteristics of the vectoring nozzle’s movement mechanism, the 3-DOF kinematics model of the 3SPS + 3PRS PM is established. The forward and inverse positional posture models are built based on the mechanism architecture of PM and the closed-loop vector method. The Jacobian matrix and Hessian matrix are derived using screw theory, and velocity and acceleration models are established. Based on the principle of virtual work and combined with the kinematics model of PM, a stiffness model was established to analyze stiffness performance. Finally, the effectiveness of the kinematics model of the PM was verified by a simulation, and the variation of stiffness performances with the positional posture of the PM was quantitatively analyzed. The results show that the translational stiffness decreases with forward axial translation of the moving platform and the rotational stiffness is mainly determined by the posture parameters. This study is expected to offer ideas for the kinematic modeling of 3-DOF PM and provide references for application and optimizing of the AVEN’s driving mechanism.
Multiple Surrogate-Model-Based Optimization Method Using the Multimodal Expected Improvement Criterion for Expensive Problems
Authors: Li Mingyang , Tang Jinjun , Meng Xianwei
Published: November 2022

In this article, a multiple surrogate-model-based optimization method using the multimodal expected improvement criterion (MSMEIC) is proposed. In MSMEIC, an important region is first identified and used alternately with the whole space. Then, in each iteration, three common surrogate models, kriging, radial basis function (RBF), and quadratic response surface (QRS), are constructed, and a multipoint expected improvement (EI) criterion that selects the highest peak and other peaks of EI is proposed to obtain several potential candidates. Furthermore, the optimal predictions of the three surrogate models are regarded as potential candidates. After deleting redundant candidates, the remaining points are saved as the new sampling points. Finally, several well-known benchmark functions and an engineering application are employed to assess the performance of MSMEIC. The testing results demonstrate that, compared with four recent counterparts, the proposed method can obtain more precise solutions more efficiently and with strong robustness.
Special Fractional-Order Map and Its Realization
Authors: Khennaoui Amina-Aicha , Ouannas Adel , Momani Shaher , Almatroud Othman Abdullah , Al-Sawalha Mohammed Mossa , Boulaaras Salah Mahmoud , Pham Viet-Thanh
Published: November 2022

Recent works have focused the analysis of chaotic phenomena in fractional discrete memristor. However, most of the papers have been related to simulated results on the system dynamics rather than on their hardware implementations. This work reports the implementation of a new chaotic fractional memristor map with “hidden attractors”. The fractional memristor map is developed based on a memristive map by using the Grunwald–Letnikov difference operator. The fractional memristor map has flexible fixed points depending on a system’s parameters. We study system dynamics for different values of the fractional orders by using bifurcation diagrams, phase portraits, Lyapunov exponents, and the 0–1 test. We see that the fractional map generates rich dynamical behavior, including coexisting hidden dynamics and initial offset boosting.
WSI: A New Early Warning Water Survival Index for the Domestic Water Demand
Authors: Shih Dong-Her , Liao Ching-Hsien , Wu Ting-Wei , Chang Huan-Shuo , Shih Ming-Hung
Published: November 2022

A reservoir is an integrated water resource management infrastructure that can be used for water storage, flood control, power generation, and recreational activities. Predicting reservoir levels is critical for water supply management and can influence operations and intervention strategies. Currently, the water supply monitoring index is used to warn the water level of most reservoirs. However, there is no precise calculation method for the current water supply monitoring index to warn about the adequacy of the domestic water demand. Therefore, taking Feitsui Reservoir as an example, this study proposes a new early warning water survival index (WSI) to warn users whether there is a shortage of domestic water demand in the future. The calculation of WSI was divided into two stages. In the first stage, the daily rainfall, daily inflow, daily outflow, and daily water level of the Feitsui Reservoir were used as input variables to predict the water level of the Feitsui Reservoir by the machine learning method. In the second stage, the interpolation method was used to calculate the daily domestic water demand in Greater Taipei. Combined with the water level prediction results of the Feitsui Reservoir in the first stage, the remaining estimated days of domestic water supply from the Feitsui Reservoir to Greater Taipei City were calculated. Then, the difference between the estimated remaining days of domestic water demand and the moving average was converted by the bias ratio to obtain a new WSI. WSI can be divided into short-term bias ratios and long-term bias ratios. In this study, the degree of the bias ratio of WSI was given in three colors, namely, condition blue, condition green, and condition red, to provide users with a warning of the shortage of domestic water in the future. The research results showed that compared with the existing water supply monitoring index, the new WSI proposed in this study can faithfully present the warning of the lack of domestic water demand in the future.
Sub-Super Solutions Method Combined with Schauder’s Fixed Point for Existence of Positive Weak Solutions for Anisotropic Non-Local Elliptic Systems
Authors: Guefaifia Rafik , dos Santos Gelson Concei¸cao G. , Bouali Tahar , Jan Rashid , Boulaaras Salah , Alharbi Asma
Published: November 2022

In this research, we investigate the presence of weak positive solutions for a family of anisotropic non-local elliptic systems in bounded domains using the sub-super solutions approach in conjunction with Schauder’s fixed point.
The Impact of Sub-Sector of Economic Activity and Financial Development on Environmental Degradation: New Evidence Using Dynamic Heterogeneous Panel
Authors: Al-Kubati Nada Amer Abdulhafedh , Karim Zulkefly Abdul , Khalid Norlin , Hassan M. Kabir
Published: November 2022

While many recent studies have used the ecological footprint as a comprehensive indicator of environmental degradation instead of CO2 emission, these were mainly focused on consumer responsibility. This study, however, aims to cover both aspects of consumption and production to elicit a more comprehensive understanding. Furthermore, this study addresses another information gap by analyzing the effect of aggregated and disaggregated economic activities on the environment. Panel data were used and sourced from 92 countries classified by income group spanning 1992 to 2015. Comprehensive financial development indicators, energy structure, energy intensity, trade openness, and urbanization were considered in examining their impacts on environmental degradation. The pooled mean group estimation was adopted in examining the long-run and short-run relationship between variables. The main findings suggest that financial development promotes green investment in high-income and upper-middle-income countries but increases degradation in lower-middle and lower-income countries. Renewable energy improves the environment in general, and energy intensity is a crucial factor in environmental modeling across all groups. Most importantly, a U-shape relationship is found on both the consumption and the production side for all income groups except for lower-income countries (inverse U-shape) on the production side. Interestingly, a U-shape relationship was found in high-income and upper-middle-income countries in the industrial sector, but a monotonic relationship in the service sector. A U-shape relationship was found for the industrial and service sectors in lower-middle-income and lower-income countries, but an inverse U-shape for agriculture outputs in lower-middle-income countries. This finding suggests the need to shift from fast-growth strategies to strategic growth planning that considers the nature of the relationship between economic sectors and the environment while diversifying the economic structure to allow for the recovery of natural capital.
Distilled and Contextualized Neural Models Benchmarked for Vulnerable Function Detection
Authors: Lin Guanjun , Jia Heming , Wu Di
Published: November 2022

Detecting vulnerabilities in programs is an important yet challenging problem in cybersecurity. The recent advancement in techniques of natural language understanding enables the data-driven research on automated code analysis to embrace Pre-trained Contextualized Models (PCMs). These models are pre-trained on the large corpus and can be fine-tuned for various downstream tasks, but their feasibility and effectiveness for software vulnerability detection have not been systematically studied. In this paper, we explore six prevalent PCMs and compare them with three mainstream Non-Contextualized Models (NCMs) in terms of generating effective function-level representations for vulnerability detection. We found that, although the detection performance of PCMs outperformed that of the NCMs, training and fine-tuning PCMs were computationally expensive. The budgets for deployment and inference are also considerable in practice, which may prevent the wide adoption of PCMs in the field of interest. However, we discover that, when the PCMs were compressed using the technique of knowledge distillation, they achieved similar detection performance but with significantly improved efficiency compared with their uncompressed counterparts when using 40,000 synthetic C functions for fine-tuning and approximately 79,200 real-world C functions for training. Among the distilled PCMs, the distilled CodeBERT achieved the most cost-effective performance. Therefore, we proposed a framework encapsulating the Distilled CodeBERT for an end-to-end Vulnerable function Detection (named DistilVD). To examine the performance of the proposed framework in real-world scenarios, DistilVD was tested on four open-source real-world projects with a small amount of training data. Results showed that DistilVD outperformed the five baseline approaches. Further evaluations on multi-class vulnerability detection also confirmed the effectiveness of DistilVD for detecting various vulnerability types.
Generation of a Synthetic Database for the Optical Response of One-Dimensional Photonic Crystals Using Genetic Algorithms
Authors: Isaza Cesar , Lujan-Cabrera Ivan Alonso , Anaya Rivera Ely Karina , Rizzo Sierra Jose Amilcar , Zavala De Paz Jonny Paul , Ramirez-Gutierrez Cristian Felipe
Published: November 2022

This work proposes an optimization tool based on genetic algorithms for the inverse design of photonic crystals. Based on target reflectance, the algorithm generates a population of chromosomes where the genes represent the thickness of a layer of a photonic crystal. Each layer is independent of another. Therefore, the sequence obtained is a disordered configuration. In the genetic algorithm, two dielectric materials are first selected to generate the population. Throughout the simulation, the chromosomes are evaluated, crossed over, and mutated to find the best-fitted one based on an error function. The target reflectance was a perfect mirror in the visible region. As a result, it was found that obtaining photonic crystal configurations with a specific stop band with disordered arrangements is possible. The genetic information of the best-fitted individuals (layer sequence, optical response, and error) is stored in an h5 format. This method of generating artificial one-dimensional photonic crystal data can be used to train a neural network for solving the problem of the inverse design of any crystal with a specific optical response.
Daily Peak-Electricity-Demand Forecasting Based on Residual Long Short-Term Network
Authors: Kim Hyunsoo , Jeong Jiseok , Kim Changwan
Published: November 2022

Forecasting the electricity demand of buildings is a key step in preventing a high concentration of electricity demand and optimizing the operation of national power systems. Recently, the overall performance of electricity-demand forecasting has been improved through the application of long short-term memory (LSTM) networks, which are well-suited to processing time-series data. However, previous studies have focused on improving the accuracy in forecasting only overall electricity demand, but not peak demand. Therefore, this study proposes adding residual learning to the LSTM approach to improve the forecast accuracy of both peak and total electricity demand. Using a residual block, the residual LSTM proposed in this study can map the residual function, which is the difference between the hypothesis and the observed value, and subsequently learn a pattern for the residual load. The proposed model delivered root mean square errors (RMSE) of 10.5 and 6.91 for the peak and next-day electricity demand forecasts, respectively, outperforming the benchmark models evaluated. In conclusion, the proposed model provides highly accurate forecasting information, which can help consumers achieve an even distribution of load concentration and countries achieve the stable operation of the national power system.
On a Novel Algorithmic Determination of Acoustic Low Frequency Coefficients for Arbitrary Impenetrable Scatterers
Authors: Kariotou Foteini , Sinikis Dimitris E. , Hadjinicolaou Maria
Published: November 2022

The calculation of low frequency expansions for acoustic wave scattering has been under thorough investigation for many decades due to their utility in technological applications. In the present work, we revisit the acoustic Low Frequency Scattering theory, and we provide the theoretical framework of a new algorithmic procedure for deriving the scattering coefficients of the total pressure field, produced by a plane wave excitation of an arbitrary, convex impenetrable scatterer. The proposed semi-analytical procedure reduces the demands for computation time and errors significantly since it includes mainly algebraic and linear integral operators. Based on the Atkinson–Wilcox theorem, any order low frequency scattering coefficient can be calculated, in finite steps, through algebraic operators at all steps, except for the last one, where a regular Fredholm integral equation with a continuous and separable integral kernel is needed to be solved. Explicit, ready to use formulae are provided for the first three low frequency scattering coefficients, demonstrating the applicability of the algorithm. The validation of the obtained formulae is demonstrated through recovering of the well-known analytical results for the case of a radially symmetric scatterer.
Two New Families of Supra-Soft Topological Spaces Defined by Separation Axioms
Authors: Al-shami Tareq , Alcantud José , Azzam A.
Published: November 2022

This paper contributes to the field of supra-soft topology. We introduce and investigate supra pp-soft Tj and supra pt-soft Tj-spaces (j=0,1,2,3,4). These are defined in terms of different ordinary points; they rely on partial belong and partial non-belong relations in the first type, and partial belong and total non-belong relations in the second type. With the assistance of examples, we reveal the relationships among them as well as their relationships with classes of supra-soft topological spaces such as supra tp-soft Tj and supra tt-soft Tj-spaces (j=0,1,2,3,4). This work also investigates both the connections among these spaces and their relationships with the supra topological spaces that they induce. Some connections are shown with the aid of examples. In this regard, we prove that for i=0,1, possessing the Ti property by a parametric supra-topological space implies possessing the pp-soft Ti property by its supra-soft topological space. This relationship is invalid for the other types of soft spaces introduced in previous literature. We derive some results of pp-soft Ti-spaces from the cardinality numbers of the universal set and a set of parameters. We also demonstrate how these spaces behave as compared to their counterparts studied in soft topology and its generalizations (such as infra-soft topologies and weak soft topologies). Moreover, we investigated whether subspaces, finite product spaces, and soft S
Role of Nanoparticles and Heat Source/Sink on MHD Flow of Cu-H2O Nanofluid Flow Past a Vertical Plate with Soret and Dufour Effects
Authors: Kune Ramesh , Naik Hari Singh , Reddy Borra Shashidar , Chesneau Christophe
Published: November 2022

The study is devoted to investigating the effect of an unsteady non-Newtonian Casson fluid over a vertical plate. A mathematical analysis is presented for a Casson fluid by taking into consideration Soret and Dufour effects, heat generation, heat radiation, and chemical reaction. The novelty of the problem is the physical interpretation of Casson fluid before and after adding copper water-based nanoparticles to the governing flow. It is found that velocity was decreased and the temperature profile was enhanced. A similarity transformation is used to convert the linked partial differential equations that control flow into non-linear coupled ordinary differential equations. The momentum, energy, and concentration formulations are cracked by means of the finite element method. The thermal and solute layer thickness growth is due to the nanoparticles’ thermo-diffusion. The effects of relevant parameters such as the Casson fluid parameter, radiation, Soret and Dufour effects, chemical reaction, and Prandtl number are discussed. A correlation of the average Nusselt number and Sherwood number corresponding to active parameters is presented. It can be noticed that increasing the Dufour number leads to an uplift in heat transfer. Fluid velocity increases with Grashof number and decreases with magnetic effect. The impact of heat sources and radiation is to increase the thermal conductivity. Concentration decreases with the Schmidt number.
Discovery of Novel Pimprinine and Streptochlorin Derivatives as Potential Antifungal Agents
Authors: Liu Jing-Rui , Liu Jia-Mu , Gao Ya , Shi Zhan , Nie Ke-Rui , Guo Dale , Deng Fang , Zhang Hai-Feng , Ali Abdallah S. , Zhang Ming-Zhi , Zhang Wei-Hua , Gu Yu-Cheng
Published: November 2022

Pimprinine and streptochlorin are indole alkaloids derived from marine or soil microorganisms. In our previous study, they were promising lead compounds due to their potent bioactivity in preventing many phytopathogens, but further structural modifications are required to improve their antifungal activity. In this study, pimprinine and streptochlorin were used as parent structures with the combination strategy of their structural features. Three series of target compounds were designed and synthesized. Subsequent evaluation for antifungal activity against six common phytopathogenic fungi showed that some of thee compounds possessed excellent effects, and this is highlighted by compounds 4a and 5a, displaying 99.9% growth inhibition against Gibberella zeae and Alternaria Leaf Spot under 50 μg/mL, respectively. EC50 values indicated that compounds 4a, 5a, 8c, and 8d were even more active than Azoxystrobin and Boscalid. SAR analysis revealed the relationship between 5-(3′-indolyl)oxazole scaffold and antifungal activity, which provides useful insight into the development of new target molecules. Molecular docking models indicate that compound 4a binds with leucyl-tRNA synthetase in a similar mode as AN2690, offering a perspective on the mode of action for the study of its antifungal activity. These results suggest that compounds 4a and 5a could be regarded as novel and promising antifungal agents against phytopathogens due to their valuable potency.