bluuebunny/crossref_metadata_2025 huggingface dataset:
MDCT-Based Finite Element Analysis for the Prediction of Functional Spine Unit Strength—An In Vitro Study
Authors: Rayudu Nithin Manohar , Baum Thomas , Kirschke Jan S. , Subburaj Karupppasamy
Published: October 2021

(1) Objective: This study aimed to analyze the effect of ligaments on the strength of functional spine unit (FSU) assessed by finite element (FE) analysis of anatomical models developed from multi-detector computed tomography (MDCT) data. (2) Methods: MDCT scans for cadaveric specimens were acquired from 16 donors (7 males, mean age of 84.29 ± 6.06 years and 9 females, mean age of 81.00 ± 11.52 years). Two sets of FSU models (three vertebrae + two disks), one with and another without (w/o) ligaments, were generated. The vertebrae were segmented semi-automatically, intervertebral disks (IVD) were generated manually, and ligaments were modeled based on the anatomical location. FE-predicted failure loads of FSU models (with and w/o ligaments) were compared with the experimental failure loads obtained from the uniaxial biomechanical test of specimens. (3) Results: The mean and standard deviation of the experimental failure load of FSU specimens was 3513 ± 1029 N, whereas of FE-based failure loads were 2942 ± 943 N and 2537 ± 929 N for FSU models with ligaments and without ligament attachments, respectively. A good correlation (ρ = 0.79, and ρ = 0.75) was observed between the experimental and FE-based failure loads for the FSU model with and with ligaments, respectively. (4) Conclusions: The FE-based FSU model can be used to determine bone strength, and the ligaments seem to have an effect on the model accuracy for the failure load calculation; further studies are needed to understand the contribution of ligaments.
Parameter Optimization of Laser Direct-Write Patterning on Indium Tin Oxide/Polycarbonate Thin Films Using Multi-Performance Characteristics Analysis
Authors: Chen Yi-Cheng , Hsiung Yi-Kai , Chang Chih-Yuan , Ou Shih-Fu
Published: October 2021

Indium tin oxide (ITO) thin films on polycarbonate (PC) substrates were patterned using the laser direct-write (LDW) technique to form an isolation line. The effect of the LDW parameters (power, pulse repetition rate, and defocusing distance) on the isolation line width, depth and roughness of the PC within the line was investigated. Additionally, the Taguchi method of experimental design was applied to determine the optimal parameters of LDW. Results showed that increasing the power led to an increase in the isolation line width and decrease in the surface roughness of the PC within the line. The increase in the pulse repetition rate and defocusing distance caused a decrease in the isolation line width. The optimal parameters were found to be A2B3C3, consisting of power of 5 W, pulse repetition rate of 100 kHz, and defocusing distance of +3 mm. Under these parameters, we obtained an isolation line width of 48.4 μm, and a surface roughness of Ra 38 nm of the PC within the isolation line. We confirmed that the ITO films separated by the isolation lines attained electrical isolation.
Experimental Investigation and Optimization of Electric Discharge Machining Process Parameters Using Grey-Fuzzy-Based Hybrid Techniques
Authors: Sharma Ankit , Kumar Vidyapati , Babbar Atul , Dhawan Vikas , Kotecha Ketan , Prakash Chander
Published: October 2021

Electrical discharge machining (EDM) has recently been shown to be one of the most successful unconventional machining methods for meeting the requirements of today’s manufacturing sector by producing complicated curved geometries in a broad variety of contemporary engineering materials. The machining efficiency of an EDM process during hexagonal hole formation on pearlitic Spheroidal Graphite (SG) iron 450/12 grade material was examined in this study utilizing peak current (I), pulse-on time (Ton), and inter-electrode gap (IEG) as input parameters. The responses, on the other hand, were the material removal rate (MRR) and overcut. During the experimental trials, the peak current ranged from 32 to 44 A, the pulse-on duration ranged from 30–120 s, and the inter-electrode gap ranged from 0.011 to 0.014 mm. Grey relational analysis (GRA) was interwoven with a fuzzy logic method to optimize the multi-objective technique that was explored in this EDM process. The effect of changing EDM process parameter values on responses was further investigated and statistically analyzed. Additionally, a response graph and response table were produced to determine the best parametric setting based on the calculated grey-fuzzy reasoning grade (GFRG). Furthermore, predictor regression models for response characteristics and GFRG were constructed, and a confirmation test was performed using randomly chosen input parameters to validate the generated models.
Analysis of the Frequency of Acoustic Emission Events in Terms of the Assessment of the Reduction of Mechanical Parameters of Cellulose–Cement Composites
Authors: Adamczak-Bugno Anna , Krampikowska Aleksandra , Świt Grzegorz
Published: October 2021

The article proposes the application of the acoustic emission method as a technique for the evaluation of mechanical parameters of cellulose–cement composites. The analysis focused on frequency values in a time series analysis of elements subject to three-point flexural stress. In the course of a statistic analysis, it has been demonstrated that a significant reduction of the recorded frequency values is associated with a considerable reduction in strength. This allowed the authors to determine the range of frequencies related to the depreciation in the strength of an element. The tests were carried out on elements cut from a full-size cellulose–cement board. Samples exposed to potential operational factors (environmental and exceptional) were analysed. It was shown that the frequencies recorded before reaching the maximum load during bending of samples exposed to environmental factors (water and low temperature) were significantly different (were much lower) from the sounds emitted by elements subjected to exceptional factors (fire and high temperature). Considering the fact that the analysed frequencies of acoustic emission events occur before the maximum stresses in the material are reached and the elements are destroyed, this provides the basis for the use of the acoustic emission method to assess the condition of cellulose–cement composites in terms of lowering mechanical parameters by observing the frequency of events generated by the material during load action. It was found that generating by material frequencies above 300 kHz during bending does not result in a significant decrease in mechanical parameters. The emission of signals with frequencies ranging from 200 to 300 kHz indicate that there was a decline in strength exceeding 25% but less than 50%. The registration of signals with frequencies below 200 kHz indicates that the reduction in mechanical parameters was greater than 50%.
Comparison of Properties of 3D-Printed Mortar in Air vs. Underwater
Authors: Woo Seong-Jin , Yang Jun-Mo , Lee Hojae , Kwon Hong-Kyu
Published: October 2021

Research and technological advancements in 3D concrete printing (3DCP) have led to the idea of applying it to offshore construction. The effect of gravity is reduced underwater, which can have a positive effect on 3DCP. For basic verification of this idea, this study printed and additively manufactured specimens with the same mortar mixture in air and underwater and evaluated properties in the fresh state and the hardened state. The mechanical properties were evaluated using the specimens produced by direct casting to the mold and specimens produced by extracting from the additive part through coring and cutting. The results of the experiment show that underwater 3D printing required a greater amount of printing output than in-air 3D printing for a good print quality, and buildability was improved underwater compared to that in air. In the case of the specimen layered underwater, the density and compressive strength decreased compared to the specimen layered in air. Because there are almost no effects of moisture evaporation and bleeding in water, the interlayer bond strength of the specimen printed underwater was somewhat larger than that printed in air, while there was no effect of the deposition time interval underwater.
Valorization of Recycled Tire Rubber for 3D Printing of ABS- and TPO-Based Composites
Authors: Laoutid Fouad , Lafqir Soumaya , Toncheva Antoniya , Dubois Philippe
Published: October 2021

Vulcanized and devulcanized ground tire rubber microparticles have been used as a minor phase in acrylonitrile butadiene styrene copolymer (ABS) and thermoplastic polyolefins (TPO) for the development of materials with desired functionalities by 3D printing. These polymers have been selected because they (i) present part of the plastic waste generated by the automotive industry and (ii) have totally different properties (ABS for its stiffness and robustness and TPO for its softness and ductility). The study aims to improve the circular economy of the automotive industry by proposing a promising route for recycling the generated tire rubber waste. In this respect, emergent technology for plastic processing such as 3D printing is used, as part of the additive manufacturing technologies for the prolongated end of life of recycled plastics originated from automotive waste such as ABS and TPO. The obtained results revealed that (i) the composites are suitable for successful filament production with desired composition and diameter required for successful 3D printing by fused deposition modeling, and that (ii) the optimization of the composition of the blends allows the production of materials with interesting mechanical performances. Indeed, some of the investigated ABS-recycled rubber tire blends exhibit high impact properties as TPO-based composites do, which in addition exhibits elongation at break higher than 500% and good compression properties, accompanied with good shape recovery ratio after compression.
Analysis of Advanced Pore Morphology (APM) Foam Elements Using Compressive Testing and Time-Lapse Computed Microtomography
Authors: Borovinsek Matej , Koudelka Petr , Sleichrt Jan , Vopalensky Michal , Kumpova Ivana , Vesenjak Matej , Kytyr Daniel
Published: October 2021

Advanced pore morphology (APM) foam elements are almost spherical foam elements with a solid outer shell and a porous internal structure mainly used in applications with compressive loading. To determine how the deformation of the internal structure and its changes during compression are related to its mechanical response, in-situ time-resolved X-ray computed microtomography experiments were performed, where the APM foam elements were 3D scanned during a loading procedure. Simultaneously applying mechanical loading and radiographical imaging enabled new insights into the deformation behaviour of the APM foam samples when the mechanical response was correlated with the internal deformation of the samples. It was found that the highest stiffness of the APM elements is reached before the appearance of the first shear band. After this point, the stiffness of the APM element reduces up to the point of the first self-contact between the internal pore walls, increasing the sample stiffness towards the densification region.
Conduction Mechanisms in Au/0.8 nm–GaN/n–GaAs Schottky Contacts in a Wide Temperature Range
Authors: Helal Hicham , Benamara Zineb , Wederni Mouhamed Amine , Mourad Sabrine , Khirouni Kamel , Monier Guillaume , Robert-Goumet Christine , Rabehi Abdelaziz , Hatem Kacha Arslane , Bakkali Hicham , Gontard Lionel C. , Dominguez Manuel
Published: October 2021

Au/0.8 nm–GaN/n–GaAs Schottky diodes were manufactured and electrically characterized over a wide temperature range. As a result, the reverse current Iinv increments from 1 × 10−7 A at 80 K to about 1 × 10−5 A at 420 K. The ideality factor n shows low values, decreasing from 2 at 80 K to 1.01 at 420 K. The barrier height qϕb grows abnormally from 0.46 eV at 80 K to 0.83 eV at 420 K. The tunnel mechanism TFE effect is the responsible for the qϕb behavior. The series resistance Rs is very low, decreasing from 13.80 Ω at 80 K to 4.26 Ω at 420 K. These good results are due to the good quality of the interface treated by the nitridation process. However, the disadvantage of the nitridation treatment is the fact that the GaN thin layer causes an inhomogeneous barrier height.
Reinforced Concrete Beam under Support Removal—Parametric Analysis
Authors: Kokot Seweryn
Published: October 2021

This paper investigates the behaviour of a reinforced concrete beam under a support removal. A detailed parametric analysis is carried out, covering the effect of support removal rate on dynamic response. The linear elastic and nonlinear inelastic responses are computed and studied in detail. Critical parameters during the structural response are identified. In order to determine the ultimate load, the vertical pushover analysis is performed. The key parameters driving the beam response are assumed as random variables, and respective reliability study makes it possible to check the overall uncertainty of the dynamic response. In particular, the response spectrum measuring the effect of support removal rate has been computed. It has been demonstrated that the critical vertical response occurs when the time of support removal is up to to 17% of the first natural period. The vertical pushover analysis results in obtaining capacity curves and showed the order in which two plastic hinges occur for various load patterns. Finally, the reliability-based sensitivity analysis indicates the geometric cross-section cover and height are the most sensitive parameters of the beam response.
Study on Structural Design and Analysis of Composite Boat Hull Manufactured by Resin Infusion Simulation
Authors: Lee Haseung , Jung Kyungwoo , Park Hyunbum
Published: October 2021

In this paper, structural design and analysis of a composite boat hull was performed. A resin transfer molding manufacturing method was adopted for manufacturing the composite boat hull. The RTM process is an advanced composite manufacturing method that allows a much higher quality product than the hand lay-up process, and less manufacturing cost compared to the autoclave method. Therefore, the RTM manufacturing method was adopted. The mechanical properties of the various aramid fibers and polyester resin were investigated. Based on this, structural design of boat hull was performed using aramid fiber or polyester. After structural design, the optimized resin infusion analysis for RTM manufacturing method was performed. Through the resin infusion analysis, it is confirmed that the designed location of resin injection and outlet is acceptable for manufacturing.
Test and Finite Element Analysis of a New Type of Double-Limb Double-Plate Connection Joint in Narrow Base Tower
Authors: Yan Hong , Nie Xianze , Zhang Lei , Yang Feng , Huang Mojia , Zhao Tengfei
Published: October 2021

The connection between the leg members and diagonal members of the urban transmission line tower is mostly in the form of single-limb connection. This paper puts forward a new connection form of pipe double-limb double-plate connection joint, which is based on the model of key joints in an urban narrow base tower structure. The traditional pipe single-limb single-plate and new pipe double-limb double-plate joint are analyzed and studied from three aspects of theory, numerical simulation and experimental study. Through finite element analysis, it is obtained that the section stress of angle steel under eccentric load is 2.05 times of that under axial load, which is basically consistent with the 2.5 times of the theoretical calculation. This shows that the stress of the angle steel in the pipe double-limb double-plate joint is greatly reduced as the axial stress component, which can ensure the safety of the angle steel. Based on the theoretical analysis of the tensile force of two kinds of joints, through the test research and corresponding numerical simulation of pipe single-limb single-plate and pipe double-limb double-plate joints, under the same load, compared with pipe single-limb single-plate joints, the pipe double-limb double-plate joints designed in this paper can greatly reduce the stress of connection plates and members, and compared with the existing joint forms, the bending stress of joint plates can be reduced by about four times, which greatly improves the bearing capacity of the joint. The research on the pipe double-limb double-plate connection joint will provide the basis for the design of new connection joints of narrow base towers in urban areas.
Mechanical Properties of Polylactide Admixed with Carbon Nanotubes or Graphene Nanopowder
Authors: Szatkowski Piotr , Czechowski Leszek , Gralewski Jacek , Szatkowska Martyna
Published: October 2021

The aim of this work was to verify the material properties of polylactic acid (PLA) with an addition of carbon nanotubes (CNTs) or graphene nanopowder (GNP). The pure polylactide and admixed polylactide samples were subjected to chemical–physical tests to determine their stiffness and strength parameters. The tensile and impact tests were performed on samples without UV (ultraviolet) treatment and after UV treatment, in a physiological saline solution. The investigations were composed of two stages. The first one was related to the examination of the properties of pure polylactide, denoted as the following: 3001D, 4032D, and 4043D. The second stage was based on an analysis of the properties of PLA 4032D with an admixture of GNP or CNTs, at 0.1 wt.% and 0.5 wt.%. By comparing the strength and the stiffness of pure samples with samples with the considered admixtures, an essential increase was not observed. However, it is stated that the presence of GNP and CNTs in the samples positively influenced the resistance of the materials to the ageing process.
Selective Laser Melting of Stainless Steel 316L with Face-Centered-Cubic-Based Lattice Structures to Produce Rib Implants
Authors: Jiang Cho-Pei , Wibisono Alvian Toto , Pasang Tim
Published: October 2021

Selective laser melting has a great potential to manufacture biocompatible metal alloy scaffolds or implants with a regulated porosity structure. This study uses five face-centered cubic (FCC) lattice structures, including FCC, FCC-Z, S-FCC, S-FCC-Z, and FCC-XYZ. Specimens with different lattice structures are fabricated using two laser energy densities, 71 J/mm3 and 125 J/mm3. Density, tensile, compressive and flexural test results exhibit the effect of laser parameters and lattice structure geometries on mechanical properties. The higher laser energy density of 125 J/mm3 results in higher properties such as density, strength, and Young’s modulus than the laser energy density of 71 J/mm3. The S-FCC lattice has the lowest density among all lattices. The mechanical tests result show specimen with FCC-XYZ lattice structures fabricated using a laser energy density of 125 J/mm3 meet the tensile properties requirement for human ribs. This structure also meets the requirement in flexural strength performance, but its stiffness is over that of human ribs. The compression test results of lattices are still incomparable due to unavailable compression data of the human ribs. In short, The FCC-XYZ lattice design fabricated by the 125 J/mm3 laser energy density parameter can be used to manufacture customized rib implants.
Visible Light-Mediated Sustainable Antibacterial Activity and Osteogenic Functionality of Au and Pt Multi-Coated TiO2 Nanotubes
Authors: Moon Kyoung-Suk , Park Young-Bum , Bae Ji-Myung , Choi Eun-Joo , Oh Seung-Han
Published: October 2021

The visible light reactions of noble metal-based photocatalysts have been increasingly utilized to investigate their antibacterial activities. Furthermore, the photoreactions at various visible light wavelengths for specific combinations of titania nanotubes and noble metal nanoparticles have been found to promote osteogenic functionality. In this investigation, a novel multi-coating combination of noble metals (gold and platinum) on titania nanotubes was assessed using plasmonic photocatalysis and low-level laser therapy at 470 and 600 nm. The results showed that this coating on the nanotubes promoted antibacterial activity and osteogenic functionality. The order in which the gold and platinum coatings were layered onto the titania nanotubes strongly affected the osteogenic performance of the human mesenchymal stem cells. These results have identified a new approach for the development of efficient novel combinations of noble metal nanoparticles and titania nanotubes with visible light responses, sustainable antimicrobial activity, and osteogenic functionality.
Influence of Interlayer Temperature and Welding Sequence on the Temperature Distribution and Welding Residual Stress of the Saddle-Shaped Joint of Weldolet-Header Butt Welding
Authors: Mai Chunliang , Hu Xue , Zhang Lixin , Song Bao , Zheng Xiongfei
Published: October 2021

In this paper, based on Simufact Welding finite element analysis software, a numerical simulation of the temperature and residual stress distribution of the weldolet-header multi-layer multi-pass welding process is carried out, and the simulation results are verified through experiments. The experimental results are in good agreement with the numerical simulation results, which proves the validity of the numerical simulation results. Through the results of the numerical simulation, the influence of the welding sequence and interlayer temperature on the temperature and residual stress distribution at different locations of the saddle-shaped weld was studied. The results show that the temperature and residual stress distribution on the header and weldolet are asymmetric, and the high-stress area of the saddle-shaped welded joint always appears at the saddle shoulder or saddle belly position. When the interlayer temperature is 300 °C, the peak residual stress reaches a minimum of 428.35 MPa. Adjusting the welding sequence can change the distribution trend of residual stress. There is no high-stress area on the first welding side of the two-stage welding path-2. The peak values of residual stresses for continuous welding path-1 and two-stage welding path-2 are 428.35 MPa and 434.01 MPa, respectively, which are very close to each other.
Optimal Vibration Suppression Modification Method for High-Speed Helical Gear Transmission of Battery Electric Vehicles under Full Working Conditions
Authors: Du Jinfu , Hu Liang , Mao Jin , Zhang Yanchao
Published: October 2021

To improve the working performance of battery electric vehicle (BEV) high-speed helical gear transmission under full working conditions, combined with Tooth Contact Analysis (TCA) and Loaded Tooth Contact Analysis (LTCA), the vibration model of single-stage helical gear bending-torsion-axis-swing coupling system considering time-varying mesh stiffness was established. The genetic algorithm was used to optimize the tooth surface with the objective of minimizing the mean value of the vibration acceleration at full working conditions. Finally, a high-speed helical gear transmission system in a BEV gearbox was taken as a simulation example and the best-modified tooth surface at full working conditions was obtained. Experiment and simulation results show that the proposed calculation method of time-varying meshing stiffness is accurate, and tooth surface modification can effectively suppress the vibration of high-speed helical gear transmission in BEV; compared to the optimally modified tooth surface under a single load, the optimal modified tooth surface under full working conditions has a better vibration reduction effect over the entire working range.
Magnetic Properties of a Ni Nanonet Grown in Superfluid Helium under Laser Irradiation
Authors: Koplak Oksana , Dvoretskaya Elizaveta , Stepanov Maxim , Karabulin Alexander , Matyushenko Vladimir , Morgunov Roman
Published: October 2021

A nanonet consisting of ultrathin Ni nanowires (diameter <4 nm) and Ni nanoballs (diameter <20 nm) has been grown through laser ablation of a Ni target in superfluid helium. At a low Ni concentration, the nanonet consists mainly of nanowires and manifests a rectangular magnetic hysteresis loop, while an increase in the Ni concentration results in an increase in both the concentration and diameter of the nanoballs. A decrease in hysteresis loop rectangularity is observed as the concentration of the nanoball increases. We show that the composition of the system can be determined from the changes in the magnetic hysteresis loop and the temperature dependence of magnetization. The significance of the work consists of the observation of evolution of magnetic properties of the ferromagnetic nanonet, while its composition varies from nanowires to a combined nanowires–nanoballs system.
Stability Analysis of Unsteady MHD Rear Stagnation Point Flow of Hybrid Nanofluid
Authors: Zainal Nurul Amira , Nazar Roslinda , Naganthran Kohilavani , Pop Ioan
Published: October 2021

Previous studies have reported that investigating the stagnation point flow is relevant in a variety of industrial and technological processes, including extrusion and the polymer industries. Hence, the present work aims to analyse the heat transfer performance of unsteady magnetohydrodynamics (MHD) in hybrid nanofluid and heat generation/absorption impact. The multivariable differential equations with partial derivatives are converted into a specific type of ordinary differential equations by using valid similarity transformations. The resulting mathematical model is clarified utilising the bvp4c function. The results of various control parameters were analysed, and it was discovered that increasing the nanoparticle concentration and magnetic field increases the coefficient of skin friction along the stretching/shrinking surface. The inclusion of the heat generation parameter displays an upward trend in the temperature distribution profile, consequently degrading the heat transfer performance. The findings are confirmed to have more than one solution, and this invariably leads to a stability analysis, which confirms the first solution’s feasibility.
Convex Obstacles from Travelling Times
Authors: Noakes Lyle , Stoyanov Luchezar
Published: October 2021

We consider situations where rays are reflected according to geometrical optics by a set of unknown obstacles. The aim is to recover information about the obstacles from the travelling-time data of the reflected rays using geometrical methods and observations of singularities. Suppose that, for a disjoint union of finitely many strictly convex smooth obstacles in the Euclidean plane, no Euclidean line meets more than two of them. We then give a construction for complete recovery of the obstacles from the travelling times of reflected rays.
A Convex Data-Driven Approach for Nonlinear Control Synthesis
Authors: Choi Hyungjin , Vaidya Umesh , Chen Yongxin
Published: October 2021

We consider a class of nonlinear control synthesis problems where the underlying mathematical models are not explicitly known. We propose a data-driven approach to stabilize the systems when only sample trajectories of the dynamics are accessible. Our method is built on the density-function-based stability certificate that is the dual to the Lyapunov function for dynamic systems. Unlike Lyapunov-based methods, density functions lead to a convex formulation for a joint search of the control strategy and the stability certificate. This type of convex problem can be solved efficiently using the machinery of the sum of squares (SOS). For the data-driven part, we exploit the fact that the duality results in the stability theory can be understood through the lens of Perron–Frobenius and Koopman operators. This allows us to use data-driven methods to approximate these operators and combine them with the SOS techniques to establish a convex formulation of control synthesis. The efficacy of the proposed approach is demonstrated through several examples.
Global Stabilization of a Single-Species Ecosystem with Markovian Jumping under Neumann Boundary Value via Laplacian Semigroup
Authors: Rao Ruofeng , Huang Jialin , Yang Xinsong
Published: October 2021

By applying impulsive control, this work investigated the global stabilization of a single-species ecosystem with Markovian jumping, a time delay and a Neumann boundary condition. Variational methods, a fixed-point theorem, and Laplacian semigroup theory were employed to derive the unique existence of the global stable equilibrium point, which is a positive number. Numerical examples illuminate the feasibility of the proposed methods.
Dynamic Susceptibility of Ferrofluids: The Numerical Algorithm for the Inverse Problem of Magnetic Granulometry
Authors: Ivanov Alexey O. , Zverev Vladimir S.
Published: October 2021

The size-dependent properties of magnetic nanoparticles (MNP) are the major characteristics, determining MNP application in modern technologies and bio-medical techniques. Direct measurements of the nanosized particles, involved in intensive Brownian motion, are very complicated; so the correct mathematical methods for the experimental data processing enable to successfully predict the properties of MNP suspensions. In the present paper, we describe the fast numerical algorithm allowing to get the distribution over the relaxation time of MNP magnetic moments in ferrofluids. The algorithm is based on numerical fitting of the experimentally measured frequency spectra of the initial dynamic magnetic susceptibility. The efficiency of the algorithm in the solution of the inverse problem of magnetic granulometry is substantiated by the computer experiments for mono- and bi-fractional ferrofluids.
Distribution Linguistic Fuzzy Group Decision Making Based on Consistency and Consensus Analysis
Authors: Jin Feifei , Li Chang , Liu Jinpei , Zhou Ligang
Published: October 2021

The development of distribution linguistic provides a new research idea for linguistic information group decision-making (GDM) problems, which is more flexible and convenient for experts to express their opinions. However, in the process of using distribution linguistic fuzzy preference relations (DLFPRs) to solve linguistic information GDM problems, there are few studies that pay attention to both internal consistency adjustment and external consensus of experts. Therefore, this study proposes a fresh decision support model based on consistency adjustment algorithm and consensus adjustment algorithm to solve GDM problems with distribution linguistic data. Firstly, we review the concept of DLFPRs to describe the fuzzy linguistic evaluation information, and then we present the multiplicative consistency of DLFPRs and a new consistency measurement method based on the distance, and investigate the consistency adjustment algorithm to ameliorate the consistency level of DLFPRs. Subsequently, the consensus degree measurement is carried out, and a new consensus degree calculation method is put forward. At the same time, the consensus degree adjustment is taken the expert cost into account to make it reach the predetermined level. Finally, a distribution linguistic fuzzy group decision making (DLFGDM) method is designed to integrate the evaluation linguistic elements and obtain the final evaluation information. A case of the evaluation of China’s state-owned enterprise equity incentive model is provided, and the validity and superiority of the proposed method are performed by comparative analysis.
Comparison of Non-Newtonian Models of One-Dimensional Hemodynamics
Authors: Krivovichev Gerasim Vladimirovich
Published: October 2021

The paper is devoted to the comparison of different one-dimensional models of blood flow. In such models, the non-Newtonian property of blood is considered. It is demonstrated that for the large arteries, the small parameter is observed in the models, and the perturbation method can be used for the analytical solution. In the paper, the simplified nonlinear problem for the semi-infinite vessel with constant properties is solved analytically, and the solutions for different models are compared. The effects of the flattening of the velocity profile and hematocrit value on the deviation from the Newtonian model are investigated.
Stability Analysis and Optimization of Semi-Explicit Predictor–Corrector Methods
Authors: Tutueva Aleksandra , Butusov Denis
Published: October 2021

The increasing complexity of advanced devices and systems increases the scale of mathematical models used in computer simulations. Multiparametric analysis and study on long-term time intervals of large-scale systems are computationally expensive. Therefore, efficient numerical methods are required to reduce time costs. Recently, semi-explicit and semi-implicit Adams–Bashforth–Moulton methods have been proposed, showing great computational efficiency in low-dimensional systems simulation. In this study, we examine the numerical stability of these methods by plotting stability regions. We explicitly show that semi-explicit methods possess higher numerical stability than the conventional predictor–corrector algorithms. The second contribution of the reported research is a novel algorithm to generate an optimized finite-difference scheme of semi-explicit and semi-implicit Adams–Bashforth–Moulton methods without redundant computation of predicted values that are not used for correction. The experimental part of the study includes the numerical simulation of the three-body problem and a network of coupled oscillators with a fixed and variable integration step and finely confirms the theoretical findings.
Mathematical Problems of Managing the Risks of Complex Systems under Targeted Attacks with Known Structures
Authors: Shiroky Alexander , Kalashnikov Andrey
Published: October 2021

This paper deals with the problem of managing the risks of complex systems under targeted attacks. It is usually solved by using Defender–Attacker models or similar ones. However, such models do not consider the influence of the defending system structure on the expected attack outcome. Our goal was to study how the structure of an abstract system affects its integral risk. To achieve this, we considered a situation where the Defender knows the structure of the expected attack and can arrange the elements to achieve a minimum of integral risk. In this paper, we consider a particular case of a simple chain attack structure. We generalized the concept of a local risk function to account for structural effects and found an ordering criterion that ensures the optimal placement of the defending system’s elements inside a given simple chain structure. The obtained result is the first step to formulate the principles of optimally placing system elements within an arbitrarily complex network. Knowledge of these principles, in turn, will allow solving the problems of optimal allocation of resources to minimize the risks of a complex system, considering its structure.
Continuum Modelling for Encapsulation of Anticancer Drugs inside Nanotubes
Authors: Alshehri Mansoor H.
Published: October 2021

Nanotubes, such as those made of carbon, silicon, and boron nitride, have attracted tremendous interest in the research community and represent the starting point for the development of nanotechnology. In the current study, the use of nanotubes as a means of drug delivery and, more specifically, for cancer therapy, is investigated. Using traditional applied mathematical modelling, I derive explicit analytical expressions to understand the encapsulation behaviour of drug molecules into different types of single-walled nanotubes. The interaction energies between three anticancer drugs, namely, cisplatin, carboplatin, and doxorubicin, and the nanotubes are observed by adopting the Lennard–Jones potential function together with the continuum approach. This study is focused on determining a favourable size and an appropriate type of nanotube to encapsulate anticancer drugs. The results indicate that the drug molecules with a large size tend to be located inside a large nanotube and that encapsulation depends on the radius and type of the tube. For the three nanotubes used to encapsulate drugs, the results show that the nanotube radius must be at least 5.493 Å for cisplatin, 6.452 Å for carboplatin, and 10.208 Å for doxorubicin, and the appropriate type to encapsulate drugs is the boron nitride nanotube. There are some advantages to using different types of nanotubes as a means of drug delivery, such as improved chemical stability, reduced synthesis costs, and improved biocompatibility.
On the First-Passage Time Problem for a Feller-Type Diffusion Process
Authors: Giorno Virginia , Nobile Amelia G.
Published: October 2021

We consider the first-passage time problem for the Feller-type diffusion process, having infinitesimal drift B1(x,t)=α(t)x+β(t) and infinitesimal variance B2(x,t)=2r(t)x, defined in the space state [0,+∞), with α(t)∈R, β(t)>0, r(t)>0 continuous functions. For the time-homogeneous case, some relations between the first-passage time densities of the Feller process and of the Wiener and the Ornstein–Uhlenbeck processes are discussed. The asymptotic behavior of the first-passage time density through a time-dependent boundary is analyzed for an asymptotically constant boundary and for an asymptotically periodic boundary. Furthermore, when β(t)=ξr(t), with ξ>0, we discuss the asymptotic behavior of the first-passage density and we obtain some closed-form results for special time-varying boundaries.
Data Mining of Job Requirements in Online Job Advertisements Using Machine Learning and SDCA Logistic Regression
Authors: Walek Bogdan , Pektor Ondrej
Published: October 2021

There are currently many job portals offering job positions in the form of job advertisements. In this article, we are proposing an approach to mine data from job advertisements on job portals. Mainly, it would concern job requirements mining from individual job advertisements. Our proposed system consists of a data mining module, a machine learning module, and a postprocessing module. The machine learning module is based on the SDCA logistic regression. The postprocessing module includes several approaches to increase the success rate of the job requirements identification. The proposed system was verified on 20 most searched IT job positions from the selected job portal. In total, 9971 job advertisements were analyzed. Our system’s verification is finding all job requirements in 80% of analyzed advertisements. The detected job requirements were also compared with the Open Skills database. Based on this database and the extension of IT job positions with other typical job skills, we created a list of the most frequent job skills in selected IT job positions. The main contribution is the development of a universal system to detect job requirements in job advertisements. The proposed approach can be used not only for IT positions, but also for various job positions. The presented data mining module can also be used for various job portals.
Contributions from Spatial Models to Non-Life Insurance Pricing: An Empirical Application to Water Damage Risk
Authors: Rivas-Lopez Maria Victoria , Minguez-Salido Roman , Matilla Garcia Mariano , Echeverria Rey Alejandro
Published: October 2021

This paper explores the application of spatial models to non-life insurance data focused on the multi-risk home insurance branch. In the pricing modelling and rating process, spatial information should be considered by actuaries and insurance managers because frequencies and claim sizes may vary by region and the premium should be different considering this rating variable. In addition, it is relevant to examine the spatial dependence due to the fact that the frequency of claims in neighbouring regions is often expected to be more closely related than those in regions far from each other. In this paper, a comparison between spatial models, such as spatial autoregressive models (SAR), the spatial error model (SEM), and the spatial Durbin model (SDM), and a non-spatial model has been developed. The data used for this analysis are for a home insurance portfolio located in Spain, from which we have selected peril of water coverage.
On Well-Posedness of Some Constrained Variational Problems
Authors: Treanţă Savin
Published: October 2021

By considering the new forms of the notions of lower semicontinuity, pseudomonotonicity, hemicontinuity and monotonicity of the considered scalar multiple integral functional, in this paper we study the well-posedness of a new class of variational problems with variational inequality constraints. More specifically, by defining the set of approximating solutions for the class of variational problems under study, we establish several results on well-posedness.
Alzheimer Identification through DNA Methylation and Artificial Intelligence Techniques
Authors: Alfonso Perez Gerardo , Caballero Villarraso Javier
Published: October 2021

A nonlinear approach to identifying combinations of CpGs DNA methylation data, as biomarkers for Alzheimer (AD) disease, is presented in this paper. It will be shown that the presented algorithm can substantially reduce the amount of CpGs used while generating forecasts that are more accurate than using all the CpGs available. It is assumed that the process, in principle, can be non-linear; hence, a non-linear approach might be more appropriate. The proposed algorithm selects which CpGs to use as input data in a classification problem that tries to distinguish between patients suffering from AD and healthy control individuals. This type of classification problem is suitable for techniques, such as support vector machines. The algorithm was used both at a single dataset level, as well as using multiple datasets. Developing robust algorithms for multi-datasets is challenging, due to the impact that small differences in laboratory procedures have in the obtained data. The approach that was followed in the paper can be expanded to multiple datasets, allowing for a gradual more granular understanding of the underlying process. A 92% successful classification rate was obtained, using the proposed method, which is a higher value than the result obtained using all the CpGs available. This is likely due to the reduction in the dimensionality of the data obtained by the algorithm that, in turn, helps to reduce the risk of reaching a local minima.
Conditional Time-Varying General Dynamic Factor Models and Its Application to the Measurement of Volatility Spillovers across Russian Assets
Authors: Balash Vladimir , Faizliev Alexey , Sidorov Sergei , Chistopolskaya Elena
Published: October 2021

This study analyzes the spillover effects of volatility in the Russian stock market. The paper applies the Diebold–Yilmaz connectedness methodology to characterize volatility spillovers between Russian assets. The spectral representation of the forecast variance decomposition proposed by Baruník and Křehlik is used to describe the connectivity in short-term (up to 5 days), medium-term (6–20 days) and long-term (more than 20 days) time frequencies. Additionally, two new augmented models are developed and applied to evaluate conditional spillover effects in different sectors of the Russian economy for the period from January 2012 to June 2021. It is shown that spillover effects increase significantly during political and economic crises and decrease during periods of relative stability. The rising of the overall level of spillovers in the Russian stock market coincides in time with the political crisis of 2014, the intensification of anti-Russian sanctions in 2018 and the fall in oil prices and the start of the pandemic in 2020. With the consideration of the augmented models it can be argued that a significant part of the long-term spillover effects on the Russian stock market may be caused by the influence of external economic and political factors. However, volatility spillovers generated by internal Russian idiosyncratic shocks are short-term. Thus, the proposed approach provides new information on the impact of external factors on volatility spillovers in the Russian stock market.
Strong Differential Superordination Results Involving Extended Sălăgean and Ruscheweyh Operators
Authors: Alb Lupaş Alina , Oros Georgia Irina
Published: October 2021

The notion of strong differential subordination was introduced in 1994 and the theory related to it was developed in 2009. The dual notion of strong differential superordination was also introduced in 2009. In a paper published in 2012, the notion of strong differential subordination was given a new approach by defining new classes of analytic functions on U×U¯ having as coefficients holomorphic functions in U¯. Using those new classes, extended Sălăgean and Ruscheweyh operators were introduced and a new extended operator was defined as Lαm:Anζ*→Anζ*,Lαmf(z,ζ)=(1−α)Rmf(z,ζ)+αSmf(z,ζ),z∈U,ζ∈U¯, where Rmf(z,ζ) is the extended Ruscheweyh derivative, Smf(z,ζ) is the extended Sălăgean operator and Anζ*={f∈H(U×U¯),f(z,ζ)=z+an+1ζzn+1+⋯,z∈U,ζ∈U¯}. This operator was previously studied using the new approach on strong differential subordinations. In the present paper, the operator is studied by applying means of strong differential superordination theory using the same new classes of analytic functions on U×U¯. Several strong differential superordinations concerning the operator Lαm are established and the best subordinant is given for each strong differential superordination.
Markov and Semi-Markov Chains, Processes, Systems, and Emerging Related Fields
Authors: Vassiliou P.-C.G. , Georgiou Andreas C.
Published: October 2021

Probability resembles the ancient Roman God Janus since, like Janus, probability also has a face with two different sides, which correspond to the metaphorical gateways and transitions between the past and the future [...]
Super-Resolved Recognition of License Plate Characters
Authors: Lee Sung-Jin , Yoo Seok Bong
Published: October 2021

Object detection and recognition are crucial in the field of computer vision and are an active area of research. However, in actual object recognition processes, recognition accuracy is often degraded due to resolution mismatches between training and test image data. To solve this problem, we designed and developed an integrated object recognition and super-resolution framework by proposing an image super-resolution technique that improves object recognition accuracy. In detail, we collected a number of license plate training images through web-crawling and artificial data generation, and the image super-resolution artificial neural network was trained by defining an objective function to be robust to image flips. To verify the performance of the proposed algorithm, we experimented with the trained image super-resolution and recognition on representative test images and confirmed that the proposed super-resolution technique improves the accuracy of character recognition. For character recognition with the 4× magnification, the proposed method remarkably increased the mean average precision by 49.94% compared to the existing state-of-the-art method.
Model-Assisted Labeling and Self-Training for Label Noise Reduction in the Detection of Stains on Images of Laundry
Authors: Huxohl Tamino , Kummert Franz
Published: October 2021

In this work, the creation of a dataset labeled in a pixel-wise manner for the uncommon domain of stain detection on patterned laundry is described. The unique properties of images in this dataset—stains are small and sometimes occur in large amounts—led to the creation of noisy labels. Indeed, the training of a fully convolutional neural network for salient object detection with this dataset revealed that the model predicts stains missed by human labelers. Thus, the reduction in label noise by adding overlooked regions with the help of the model’s predictions is examined in two different experiments. In the model-assisted labeling experiment, a simulation is ran where a human selects correct regions from the predictions. In the self-training experiment, regions of high certainty are automatically selected from the predictions. Re-training the model with the revised labels shows that model-assisted labeling leads to an average improvement in performance by 8.52%. In contrast, with self-training, the performance increase is generally lower (2.58% on average) and a decrease is even possible since regions of high certainty are often false positives.