bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Use of Advanced Friction Models for the Simulation of an Industrial Stamping Process including the Analysis of Material and Lubricant Fluctuations
Authors: Muñiz Laura , Trinidad Javier , Garcia Eduardo , Peinado Ivan , Montes Nicolas , Galdos Lander
Published: April 2023

The use of numerical simulations for tool tryout and process control is becoming increasingly prevalent. In this work, the deep drawing process of a car inner door panel of DC06 mild steel is numerically analyzed and compared with industrial process results. Five batches of DC06 material were analyzed mechanically and tribologically. Diverse tribological models were developed based on experimental strip drawing tests, where a Coefficient of Friction (CoF) was obtained as a function of contact pressure, sliding velocity, and amount of lubricant. A topography analysis was defined to compare material batches and to replicate industrial tool conditions. The simulation was fed with three tribological models: constant (CoF 0.15), Filzek pressure and velocity dependent, and TriboForm with lubrication zones. Thinning, Forming Limit Diagram (FLD) and draw-in were used as indicators for the comparison. Using the industrial tool, both FLD and draw-in were measured and compared with the numerical models. The constant model predicted the most conservative strain state and also differed most from the experimental results. The P-v-dependent and TriboForm models more accurately predicted the experimental results. This work highlights the importance of considering more complex tribological models to feed numerical simulations to yield results closer to real process conditions.
Synthesis and Properties of Sulfur-Containing Organophosphorus Extractants Based on Red Phosphorus, Alkyl Bromides, and Elemental Sulfur
Authors: Bishimbayeva Gaukhar K. , Gusarova Nina K. , Nalibayeva Arailym M. , Verkhoturova Svetlana I. , Bold Amangul , Chernysheva Natalya A. , Zhangabayeva Assem K. , Arbuzova Svetlana N. , Abdikalykov Yerlan N. , Zhumabayeva Dinara S.
Published: April 2023

In order to obtain sulfur-containing organophosphorus compounds that are promising as extractants of heavy metals, the interaction of elemental phosphorus and sulfur with alkyl bromides catalyzed using strong bases was studied. According to the task, the reaction of non-toxic and non-flammable red phosphorus with alkyl bromides under conditions of phase transfer catalysts (PTC), followed by the introduction of elemental sulfur into the reaction medium, were studied. It is shown that alkyl bromides interact with red phosphorus when heated (95–105 °C, 5–8 h) under conditions of phase transfer catalysts (PTC) in a two-phase system: a 60% aqueous solution of KOH-toluene-benzyltriethylammonium chloride (BTEAC) forming a mixture of organophosphorus compounds along with alkylphosphines (57–60%), are the main reaction products; alkylphosphine oxides are also formed (40–43%). The introduction of elemental sulfur (solution in toluene) at the final stage of the process into the reaction mass cooled to 40–60 °C leads to the expected alkylphosphine sulfides, which are the result of the interaction of alkylphosphines with sulfur. The formation of complex mixtures of products prevents the release of target alkylphosphine sulfides in individual form. However, the synthesized mixture of alkylphosphine sulfides and alkylphosphine oxides without separation into individual components is promising for studying its extraction properties in relation to heavy metals. Testing of the extraction properties of synthesized mixtures of alkylphosphine sulfides and alkylphosphine oxides in relation to heavy metals (Ni, Co, Zn, Pb) and noble metals (Ag) showed that the resulting mixtures of tertiary phosphine oxides and phosphine sulfides are highly effective extractants. The degree of extraction in relation to Ni, Co, Zn, and Pb varies from 99.90 to 99.99%, and for Ag from 99.56 to 99.59%.
Structure and Performance Optimization of Co Magnetic Thin Films Deposited by Vacuum Evaporation Coating
Authors: Mao Mingheng , Ke Shaoqiu , Tang Dingguo , Sang Xiahan , He Danqi
Published: April 2023

Co magnetic films are widely used in high-frequency magnetic recording and vertical magnetic recording due to their high saturation magnetization and magnetocrystalline anisotropy. In this work, ferromagnetic Co magnetic films were prepared on copper substrate by vacuum evaporation combined with heat treatment (H2 atmosphere), to investigate the impact of film thickness and annealing temperature on microstructure and magnetic properties. The results show that with the increase in annealing temperature, the Co thin film physical phase does not change significantly, the crystallinity increases, and the grain size increases, which is consistent with the results obtained from the SEM morphology map of the sample surface, leading to an increase in coercivity. By annealing experiments (atmospheric atmosphere) on Co magnetic films with and without an Al protective layer, as shown by scanning electron microscopy microscopic characterization results, it was verified that the Al layer can protect the inner Co layer from oxidation. As the film thickness increases from 10 to 300 nm, the magnetic properties of Co films change significantly. The saturation magnetization gradually increases from 0.89 to 5.21 emu/g, and the coercivity increases from 124.3 to 363.8 Oe. The remanence ratio of the 10 nm magnetic film is 0.82, which is much higher than the film remanence ratio of 0.46 at 50 nm. This is because when the thickness of the film is between 10 and 50 nm, the magnetic moments partially deviate from the in-plane direction, and the out-of-plane component reduces the film remanence ratio. This study shows that optimizing annealing temperature and film thickness can effectively control the structure and magnetic properties of Co magnetic films, which is of great significance for the development of the magnetic recording field.
Metal Ions Release from Welded Co—Cr Dental Alloys
Authors: Carek Andreja , Slokar Benić Ljerka , Bubalo Vatroslav
Published: April 2023

Cobalt–chromium alloys (Co-Cr) are widely used in dentistry due to their excellent mechanical properties and corrosion resistance. Since prosthetic materials must be permanently stable in the oral cavity, it is very important to determine the release of ions from alloys in the oral cavity. In dentistry today, metals and alloys are mainly joined by laser and tungsten inert gas (TIG) welding. Therefore, in this work, the release of metal ions from six different Co-Cr alloys joined by these two welding methods was quantified to determine the effects of the welding method on an ion release. Static immersion tests, atomic absorption spectrometry and statistical analysis were performed for this purpose. The results showed that laser-welded alloys release a lower amount of metal ions compared to TIG-welded alloys.
Comparing the Properties of Bio-Polyols Based on White Mustard (Sinapis alba) Oil Containing Boron and Sulfur Atoms Obtained by Various Methods and Checking Their Influence on the Flammability of Rigid Polyurethane/Polyisocyanurate Foams
Authors: Borowicz Marcin , Isbrandt Marek , Paciorek-Sadowska Joanna , Sander Paweł
Published: April 2023

The article compares the properties of bio-polyols obtained from white mustard (Sinapis alba) seed oil, which contain boron and sulfur atoms. Each of the bio-polyols was prepared by a different method of testing the efficiency of the incorporation of boron and sulfur atoms. All synthesis methods were based on the epoxidation of unsaturated bonds followed by the opening of epoxy rings by compounds containing heteroatoms. Two of the bio-polyols were subjected to additional esterification reactions of hydroxyl groups with boric acid or its ester. Three new bio-polyols were obtained as a result of the performed syntheses. The synthesized compounds were subjected to detailed physicochemical (physical state, color, smell, density, viscosity and pH), analytical (hydroxyl number, acid number, water content, content of C, H, N, S, O, B elements and GPC analysis), spectroscopic (FTIR, 1H NMR and 13C NMR) and thermal (DSC) tests. The obtained results allowed for a detailed characterization of the synthesized bio-polyol raw materials. Their suitability for obtaining polyurethane materials was also determined. The synthesized compounds have been found to be an interesting alternative to petrochemical polyols. The influence of the synthesized compounds on the flammability of polyurethane materials was tested experimentally. On the basis of this testing, a number of rigid polyurethane/polyisocyanurate foams were obtained, which were then subjected to flammability tests with the methods of horizontal and vertical burning, limiting oxygen index (LOI) and using the cone calorimeter. Based on this research, it was found that the presence of sulfur and boron heteroatoms reduced the flammability of polyurethane materials based on synthesized bio-polyols.
Dynamic Fracture and Crack Arrest Toughness Evaluation of High-Performance Steel Used in Highway Bridges
Authors: Collins William N. , Yount Tristan D. , Sherman Ryan J. , Leon Roberto T. , Connor Robert J.
Published: April 2023

Impact energy tests are an efficient method of verifying adequate toughness of steel prior to it being put into service. Based on a multitude of historical correlations between impact energy and fracture toughness, minimum impact energy requirements that correspond to desired levels of fracture toughness are prescribed by steel bridge design specifications. Research characterizing the fracture behavior of grade 485 and 690 (70 and 100) high-performance steel utilized impact, fracture toughness, and crack arrest testing to verify adequate performance for bridge applications. Fracture toughness results from both quasi-static and dynamic stress intensity rate tests were analyzed using the most recently adopted master curve methodology. Both impact and fracture toughness tests indicated performance significantly greater than the minimum required by material specifications. Even at the AASHTO Zone III service temperature, which is significantly colder than prescribed test temperatures, minimum average impact energy requirements were greatly exceeded. All master curve reference temperatures, both for quasi-static and dynamic loading rates, were found to be colder than the Zone III minimum service temperature. Three correlations between impact energy and fracture toughness were evaluated and found to estimate reference temperatures that are conservative by 12 to 50 °C (22 to 90 °F) on average for the grades and specimen types tested. The evaluation of two reference temperature shifts intended to account for the loading rate was also performed and the results are discussed.
Numerical Investigation on Protective Mechanism of Metal Cover Plate for Alumina Armor against Impact of Fragment by FE-Converting-SPH Method
Authors: Dou Linlong , He Liling , Yin Yihui
Published: April 2023

It is of extreme importance to develop a reliable numerical prediction technique to simulate the ballistic response of ceramic armor subjected to high-velocity impact (HVI) to economize the test cost and shorten the design period. In the present manuscript, a series of experiments on tungsten heavy alloy (WHA) fragment’s penetration into 99.5% alumina (AD995) armors are systematically simulated by employing the FE-converting-SPH technique. The numerical results are compared with the experimental counterparts to find that the FE-converting-SPH method is fairly efficient in predicting the depth of penetration, the residual velocity, length and mass of fragment, and reproducing the crack forms of ceramic. The applicability and accuracy of the numerical model in terms of the algorithm, material model parameters and contact definitions are validated. Then, the relevant parameters of the calibrated numerical model are incorporated to explore the influence of cover-layer thickness on the armor performance. A few mechanisms regarding the cover plate have been identified to act on the armor performance, such as the alteration of fracture cone half-angle, proportion of energy absorbed by ceramic, mushrooming deformation of fragment, etc. The result of multi-mechanism superposition is that the best ballistic performance is endued with 1 mm cover-layer armor, which demonstrates a 24.6% improvement over the bi-layer armor with 4.96 g/cm2 area density, only at the cost of 15.7% increase in areal density, when back-plate thickness is held as 2 mm; for a constant area density of 4.96 g/cm2, a 1 mm cover-layer is also expected to be the best choice, with 10.7% improvement in armor performance.
MOF-Based Active Packaging Materials for Extending Post-Harvest Shelf-Life of Fruits and Vegetables
Authors: Fu Yabo , Yang Dan , Chen Yiyang , Shi Jiazi , Zhang Xinlin , Hao Yuwei , Zhang Zhipeng , Sun Yunjin , Zhang Jingyi
Published: April 2023

Active packaging that can extend the shelf-life of fresh fruits and vegetables after picking can assure food quality and avoid food waste. Such packaging can prevent the growth of microbial and bacterial pathogens or delay the production of ethylene, which accelerates the ripening of fruits and vegetables after harvesting. Proposed technologies include packaging that enables the degradation of ethylene, modified atmosphere packaging, and bioactive packaging. Packaging that can efficiently adsorb/desorb ethylene, and thus control its concentration, is particularly promising. However, there are still large challenges around toxicity, low selectivity, and consumer acceptability. Metal–organic framework (MOF) materials are porous, have a specific surface area, and have excellent gas adsorption/desorption performance. They can encapsulate and release ethylene and are thus good candidates for use in ethylene-adjusting packaging. This review focuses on MOF-based active-packaging materials and their applications in post-harvest fruit and vegetable packaging. The fabrication and characterization of MOF-based materials and the ethylene adsorption/desorption mechanism of MOF-based packaging and its role in fruit and vegetable preservation are described. The design of MOF-based packaging and its applications are reviewed. Finally, the potential future uses of MOF-based active materials in fresh food packaging are considered.
Advanced Materials for Clothing and Textile Engineering
Authors: Firšt Rogale Snježana , Rogale Dubravko
Published: April 2023

The main objective of this Special Issue is to showcase outstanding papers presenting advanced materials for clothing and textile engineering [...]
Charge Transport Enhancement in BiVO4 Photoanode for Efficient Solar Water Oxidation
Authors: Li Zhidong , Xie Zhibin , Li Weibang , Aziz Hafiz Sartaj , Abbas Muhammad , Zheng Zhuanghao , Su Zhenghua , Fan Ping , Chen Shuo , Liang Guangxing
Published: April 2023

Photoelectrochemical (PEC) water splitting in a pH-neutral electrolyte has attracted more and more attention in the field of sustainable energy. Bismuth vanadate (BiVO4) is a highly promising photoanode material for PEC water splitting. Additionally, cobaltous phosphate (CoPi) is a material that can be synthesized from Earth’s rich materials and operates stably in pH-neutral conditions. Herein, we propose a strategy to enhance the charge transport ability and improve PEC performance by electrodepositing the in situ synthesis of a CoPi layer on the BiVO4. With the CoPi co-catalyst, the water oxidation reaction can be accelerated and charge recombination centers are effectively passivated on BiVO4. The BiVO4/CoPi photoanode shows a significantly enhanced photocurrent density (Jph) and applied bias photon-to-current efficiency (ABPE), which are 1.8 and 3.2 times higher than those of a single BiVO4 layer, respectively. Finally, the FTO/BiVO4/CoPi photoanode displays a photocurrent density of 1.39 mA cm−2 at 1.23 VRHE, an onset potential (Von) of 0.30 VRHE, and an ABPE of 0.45%, paving a potential path for future hydrogen evolution by solar-driven water splitting.
Multiobjective Optimization of a Metal Complex Catalytic Reaction Based on a Detailed Kinetic Model with Parallelization of Calculations
Authors: Koledin Sergey , Koledina Kamila , Gubaydullin Irek
Published: April 2023

The solution of the multiobjective optimization problem was performed with the help of the Pareto approximation algorithm. The problem of multiobjective optimization of the reaction process conditions for the olefin hydroalumination catalytic reaction, with the presence of organoaluminum compounds diisobutylaluminiumchloride, diisobutylaluminiumhydrate, and triisobutylaluminum, was solved. The optimality criteria are the yield of the reaction resultants. The largest yield of the high-order organoaluminum compound Bu2AlR was observed for the reactions with diisobutylaluminiumhydrate and triisobutylaluminum. Such results were obtained due to the fact that in the case of diisobutylaluminiumchloride, Bu2AlR was used for the formation of ClBuAlR. The yield of the Schwartz reagent Cp2ZrHCl was higher by a third in the reaction in the presence of diisobutylaluminiumchloride. Unlike the experimental isothermal conditions, the temperature optimal control showed the sufficiency of the gradual growth temperature for achieving the same or higher values of optimality criteria. For computational experiments, the algorithm for solving the multi-criteria optimization problem was parallelized using an island model.
A Novel EA-Based Techno–Economic Analysis of Charging System for Electric Vehicles: A Case Study of Qassim Region, Saudi Arabia
Authors: Alsaidan Ibrahim , Bilal Mohd , Alaraj Muhannad , Rizwan Mohammad , Almasoudi Fahad M.
Published: April 2023

Because of the fast expansion of electric vehicles (EVs) in Saudi Arabia, a massive amount of energy will be needed to serve these vehicles. In addition, the transportation sector radiates a considerable amount of toxic gases in the form of SO2 and CO2. The national grid must supply a huge amount of electricity on a regular basis to meet the increasing power demands of EVs. This study thoroughly investigates the technical and economic benefits of an off-grid and grid-connected hybrid energy system with various configurations of a solar, wind turbine and battery energy storage system for the electric vehicle charging load in the Qassim region, Saudi Arabia. The goal is to decrease the cost of energy while reducing the chance of power outages in the system. This is achieved by using a new optimization algorithm called the modified salp swarm optimization algorithm (MSSOA), which is based on an evolutionary algorithm approach. MSSOA is an improved version of SSOA, which addresses its shortcomings. It has two search strategies to enhance its efficiency: first, it uses Levy flight distribution (LFD) to help individuals reach new positions faster, and second, it instructs individuals to spiral around the optimal solution, improving the exploitation phase. The MSSOA’s effectiveness is confirmed by comparing its results with those of the conventional salp swarm optimization algorithm and particle swarm optimization (PSO). According to simulation findings, MSSOA has excellent accuracy and robustness. In this region, the SPV/WT/BESS-based EV charging station is the optimal option for EV charging stations. The SPV/WT/BESS design has the lowest LCOE of all feasible configurations in the region under study. The optimum values for the LCOE and TNPC using MSSOA are USD 0.3697/kWh and USD 99,928.34, which are much lower than the optimized values for the LCOE (USD 0.4156) and TNPC (USD 1,12,671.75) using SSOA. Furthermore, a comprehensive techno–economic analysis of optimized hybrid systems is assessed by incorporating the grid-connected option. The grid connected system results in optimized values of the LCOE (USD 0.0732/kWh) and TNPC (USD 1,541,076). The impact of different grid purchase prices on the levelized cost of energy is also studied. Our results will assist the researchers to determine the best technique for the optimization of an optimal energy system.
Finding Patient Zero and Tracking Narrative Changes in the Context of Online Disinformation Using Semantic Similarity Analysis
Authors: Artene Codruț-Georgian , Oprișa Ciprian , Buțincu Cristian Nicolae , Leon Florin
Published: April 2023

Disinformation in the form of news articles, also called fake news, is used by multiple actors for nefarious purposes, such as gaining political advantages. A key component for fake news detection is the ability to find similar articles in a large documents corpus, for tracking narrative changes and identifying the root source (patient zero) of a particular piece of information. This paper presents new techniques based on textual and semantic similarity that were adapted for achieving this goal on large datasets of news articles. The aim is to determine which of the implemented text similarity techniques is more suitable for this task. For text similarity, a Locality-Sensitive Hashing is applied on n-grams extracted from text to produce representations that are further indexed to facilitate the quick discovery of similar articles. The semantic textual similarity technique is based on sentence embeddings from pre-trained language models, such as BERT, and Named Entity Recognition. The proposed techniques are evaluated on a collection of Romanian articles to determine their performance in terms of quality of results and scalability. The presented techniques produce competitive results. The experimental results show that the proposed semantic textual similarity technique is better at identifying similar text documents, while the Locality-Sensitive Hashing text similarity technique outperforms it in terms of execution time and scalability. Even if they were evaluated only on Romanian texts and some of them are based on pre-trained models for the Romanian language, the methods that are the basis of these techniques allow their extension to other languages, with few to no changes, provided that there are pre-trained models for other languages as well. As for a cross-lingual setup, more changes are needed along with tests to demonstrate this capability. Based on the obtained results, one may conclude that the presented techniques are suitable to be integrated into a decentralized anti-disinformation platform for fact-checking and trust assessment.
Review of Quaternion-Based Color Image Processing Methods
Authors: Huang Chaoyan , Li Juncheng , Gao Guangwei
Published: April 2023

Images are a convenient way for humans to obtain information and knowledge, but they are often destroyed throughout the collection or distribution process. Therefore, image processing evolves as the need arises, and color image processing is a broad and active field. A color image includes three distinct but closely related channels (red, green, and blue (RGB)). Compared to directly expressing color images as vectors or matrices, the quaternion representation offers an effective alternative. There are several papers and works on this subject, as well as numerous definitions, hypotheses, and methodologies. Our observations indicate that the quaternion representation method is effective, and models and methods based on it have rapidly developed. Hence, the purpose of this paper is to review and categorize past methods, as well as study their efficacy and computational examples. We hope that this research will be helpful to academics interested in quaternion representation.
Efficient and Low Color Information Dependency Skin Segmentation Model
Authors: You Hojoon , Lee Kunyoung , Oh Jaemu , Lee Eui Chul
Published: April 2023

Skin segmentation involves segmenting the human skin region in an image. It is a preprocessing technique mainly used in many applications such as face detection, hand gesture recognition, and remote biosignal measurements. As the performance of skin segmentation directly affects the performance of these applications, precise skin segmentation methods have been studied. However, previous skin segmentation methods are unsuitable for real-world environments because they rely heavily on color information. In addition, deep-learning-based skin segmentation methods incur high computational costs, even though skin segmentation is mainly used for preprocessing. This study proposes a lightweight skin segmentation model with a high performance. Additionally, we used data augmentation techniques that modify the hue, saturation, and values, allowing the model to learn texture or contextual information better without relying on color information. Our proposed model requires 1.09M parameters and 5.04 giga multiply-accumulate. Through experiments, we demonstrated that our proposed model shows high performance with an F-score of 0.9492 and consistent performance even for modified images. Furthermore, our proposed model showed a fast processing speed of approximately 68 fps, based on 3 × 512 × 512 images and an NVIDIA RTX 2080TI GPU (11GB VRAM) graphics card.
Frank Prioritized Aggregation Operators and WASPAS Method Based on Complex Intuitionistic Fuzzy Sets and Their Application in Multi-Attribute Decision-Making
Authors: Ali Zeeshan , Mahmood Tahir , Yang Miin-Shen
Published: April 2023

Complex intuitionistic fuzzy (CIF) information covers the degree of membership and the degree of non-membership in the form of polar coordinates with a valuable and dominant characteristic where the sum of the real parts (the same rule for the imaginary parts) of the pair must be contained in the unit interval. In this paper, we first derive the Frank operational laws for CIF information and then examine the prioritized aggregation operators based on Frank operational laws for managing the theory of CIF information. These are the CIF Frank prioritized averaging (CIFFPA) operator, the CIF Frank prioritized ordered averaging (CIFFPOA) operator, the CIF Frank prioritized geometric (CIFFPG) operator, and the CIF Frank prioritized ordered geometric (CIFFPOG) operator with properties of idempotency, monotonicity, and boundedness. Furthermore, we derive the WASPAS (weighted aggregates sum product assessment) under the consideration or presence of the CIF information and try to justify it with the help of a suitable example. Additionally, we illustrate some numerical examples in the presence of the MADM (multi-attribute decision-making) procedures for evaluating the comparison between the proposed operators with some well-known existing operators to show the validity and worth of the proposed approaches.
Temperature Time Series Prediction Model Based on Time Series Decomposition and Bi-LSTM Network
Authors: Zhang Kun , Huo Xing , Shao Kun
Published: April 2023

Utilizing a temperature time-series prediction model to achieve good results can help us to accurately sense the changes occurring in temperature levels in advance, which is important for human life. However, the random fluctuations occurring in a temperature time series can reduce the accuracy of the prediction model. Decomposing the time-series data prior to performing a prediction can effectively reduce the influence of random fluctuations in the data and consequently improve the prediction accuracy results. In the present study, we propose a temperature time-series prediction model that combines the seasonal-trend decomposition procedure based on the loess (STL) decomposition method, the jumps upon spectrum and trend (JUST) algorithm, and the bidirectional long short-term memory (Bi-LSTM) network. This model can achieve daily average temperature predictions for cities located in China. Firstly, we decompose the time series into trend, seasonal, and residual components using the JUST and STL algorithms. Then, the components determined by the two methods are combined. Secondly, the three components and original data are fed into the two-layer Bi-LSTM model for training purposes. Finally, the prediction results achieved for both the components and original data are merged by learnable weights and output as the final result. The experimental results show that the average root mean square and average absolute errors of our proposed model on the dataset are 0.2187 and 0.1737, respectively, which are less than the values 4.3997 and 3.3349 attained for the Bi-LSTM model, 2.5343 and 1.9265 for the EMD-LSTM model, and 0.9336 and 0.7066 for the STL-LSTM model.
Fractional Stochastic Search Algorithms: Modelling Complex Systems via AI
Authors: Herzog Bodo
Published: April 2023

The aim of this article is to establish a stochastic search algorithm for neural networks based on the fractional stochastic processes {BtH,t≥0} with the Hurst parameter H∈(0,1). We define and discuss the properties of fractional stochastic processes, {BtH,t≥0}, which generalize a standard Brownian motion. Fractional stochastic processes capture useful yet different properties in order to simulate real-world phenomena. This approach provides new insights to stochastic gradient descent (SGD) algorithms in machine learning. We exhibit convergence properties for fractional stochastic processes.
Nonlinear Constitutive and Mechanical Properties of an Auxetic Honeycomb Structure
Authors: Ma Qian , Zhang Junhua
Published: April 2023

Auxetic honeycomb has unique mechanical properties such as good energy absorption capacity, tensile strength and fracture toughness, etc. Therefore, honeycomb with a negative Poisson’s ratio is used widely in medical, biological, aerospace and other fields. This honeycomb has large deformations in energy absorption and vibration reduction. It is very important to study the nonlinear constitutive of the honeycomb structure. Therefore, this paper establishes the nonlinear constitutive relationship of the auxetic honeycomb structure under large deformations. This constitutive relation includes the in-plane stress, in-plane strain, Young’s modulus and Poisson’s ratio of the negative Poisson’s ratio honeycomb. The finite element model of the negative Poisson’s ratio honeycomb cells is established, and the calculated results of finite element model are compared with that of the theoretical calculation results. On this basis, the influence of the geometric parameters on the mechanical properties of the structure is studied. The results of this paper will provide a theoretical basis for the further study of the auxetic honeycomb sandwich structure and provide a basis for the engineering application of honeycomb structures.
Event-Triggered Extended Dissipativity Fuzzy Filter Design for Nonlinear Markovian Switching Systems against Deception Attacks
Authors: Kchaou Mourad , Regaieg Mohamed Amin
Published: April 2023

This article is concerned with the adaptive-event-triggered filtering problem as it relates to a class of nonlinear discrete-time systems characterized by interval Type-2 fuzzy models. The system under investigation is susceptible to Markovian switching and deception attacks. It is proposed to implement an improved event-triggering mechanism to reduce the unnecessary signal transmissions on the communication channel and formulate the extended dissipativity specification to quantify the transient dynamics of filtering errors. By resorting to the linear matrix inequality approach and using the information on upper and lower membership functions, stochastic analysis establishes sufficient conditions for the existence of the desired filter, ensuring the mean-squared stability and extended dissipativity of the augmented filtering system. Further, an optimization-based algorithm (PSO) is proposed for computing filter gains at an optimal level of performance. The developed scheme was finally tested through experimental numerical illustrations based on a single-link robot arm and a lower limbs system.
On a Low-Rank Matrix Single-Index Model
Authors: Mai The Tien
Published: April 2023

In this paper, we conduct a theoretical examination of a low-rank matrix single-index model. This model has recently been introduced in the field of biostatistics, but its theoretical properties for jointly estimating the link function and the coefficient matrix have not yet been fully explored. In this paper, we make use of the PAC-Bayesian bounds technique to provide a thorough theoretical understanding of the joint estimation of the link function and the coefficient matrix. This allows us to gain a deeper insight into the properties of this model and its potential applications in different fields.
The Existence Problems of Solutions for a Class of Differential Variational–Hemivariational Inequality Problems
Authors: Chang Shih-Sen , Salahuddin  , Ahmadini A. A. H. , Wang Lin , Wang Gang
Published: April 2023

In this work, we used reflexive Banach spaces to study the differential variational—hemivariational inequality problems with constraints. We established a sequence of perturbed differential variational–hemivariational inequality problems with perturbed constraints and penalty coefficients. Then, for each perturbed inequality, we proved the unique solvability and convergence of the solutions to the problems. Following that, we proposed a mathematical model for a viscoelastic rod in unilateral contact equilibrium, where the unknowns were the displacement field and the history of the deformation. We used the abstract penalty method in the analysis of this inequality and provided the corresponding mechanical interpretations.
A Deterministic Setting for the Numerical Computation of the Stabilizing Solutions to Stochastic Game-Theoretic Riccati Equations
Authors: Aberkane Samir , Dragan Vasile
Published: April 2023

In this paper, we are interested in the numerical aspects of the class of generalized Riccati difference equations which are involved in linear quadratic (LQ) stochastic difference games. More specifically, we address the problem of the numerical computation of the stabilizing solutions for this class of nonlinear difference equations. We propose an iterative deterministic algorithm for the computation of such a global solution. The performances of the proposed algorithm are illustrated with some numerical examples.
Gauss Quadrature Method for System of Absolute Value Equations
Authors: Shi Lei , Iqbal Javed , Riaz Faiqa , Arif Muhammad
Published: April 2023

In this paper, an iterative method was considered for solving the absolute value equation (AVE). We suggest a two-step method in which the well-known Gauss quadrature rule is the corrector step and the generalized Newton method is taken as the predictor step. The convergence of the proposed method is established under some acceptable conditions. Numerical examples prove the consistency and capability of this new method.
A New Method of Identifying the Aerodynamic Dipole Sound Source in the Near Wall Flow
Authors: Zhang Hao , Wang Yigang , Wang Yupeng
Published: April 2023

Consider that the sound dipole source in the flow field is composed of multiple micro-spherical oscillating sources. An aerodynamic sound source identification method is established by the relationship among the oscillating source, the radiated sound pressure, and the pressure gradient of flow in the near-wall flow field, and the formula for calculating the sound power of the sound dipole source in unsteady flow is derived. It shows that the power of sound dipole sources is proportional to the square of the oscillating force or pressure gradient. The combination of the formula and CFD method is further applied to the flow around the cylinder, which clearly presents the sound power and location characteristics of sound dipole sources. Further, the relationship between the sound source and the flow separation, or flow vortex shedding, is analyzed. The corresponding correlation analysis is also carried out, which indicates that the sound dipole source exists in a finite area of the attached wall. The front end of the area is at the separation point along the circumferential direction of the wall, and the end is at the location where the separation vortex completely falls off and a trailing vortex begins to form. In addition, the thickness of the area exists along the radial direction and gradually increases backward.
Clustering Synchronization in a Model of the 2D Spatio-Temporal Dynamics of an Age-Structured Population with Long-Range Interactions
Authors: Kulakov Matvey , Frisman Efim
Published: April 2023

The inhomogeneous population distribution appears as various population densities or different types of dynamics in distant sites of the extended habitat and may arise due to, for example, the resettlement features, the internal population structure, and the population dynamics synchronization mechanisms between adjacent subpopulations. In this paper, we propose the model of the spatio-temporal dynamics of two-age-structured populations coupled by migration (metapopulation) with long-range displacement. We study mechanisms leading to inhomogeneous spatial distribution as a type of cluster synchronization of population dynamics. To study the spatial patterns and synchronization, we use the method of constructing spatio-temporal profiles and spatial return maps. We found that patterns with spots or stripes are typical spatial structures with synchronous dynamics. In most cases, the spatio-temporal dynamics are mixed with randomly located single populations with strong burst (outbreak) of population size (solitary states). As the coupling parameters decrease, the number of solitary states grows, and they increasingly synchronize and form the clusters of solitary states. As a result, there are the several clusters with different dynamics. The appearance of these spatial patterns most likely occurs due to the multistability of the local age-structured population, leading to the spatio-temporal multistability.
Enhancing Data Security in IoT Networks with Blockchain-Based Management and Adaptive Clustering Techniques
Authors: Kiran Ajmeera , Mathivanan Prasad , Mahdal Miroslav , Sairam Kanduri , Chauhan Deepak , Talasila Vamsidhar
Published: April 2023

The rapid proliferation of smart devices in Internet of Things (IoT) networks has amplified the security challenges associated with device communications. To address these challenges in 5G-enabled IoT networks, this paper proposes a multi-level blockchain security architecture that simplifies implementation while bolstering network security. The architecture leverages an adaptive clustering approach based on Evolutionary Adaptive Swarm Intelligent Sparrow Search (EASISS) for efficient organization of heterogeneous IoT networks. Cluster heads (CH) are selected to manage local authentication and permissions, reducing overhead and latency by minimizing communication distances between CHs and IoT devices. To implement network changes such as node addition, relocation, and deletion, the Network Efficient Whale Optimization (NEWO) algorithm is employed. A localized private blockchain structure facilitates communication between CHs and base stations, providing an authentication mechanism that enhances security and trustworthiness. Simulation results demonstrate the effectiveness of the proposed clustering algorithm compared to existing methodologies. Overall, the lightweight blockchain approach presented in this study strikes a superior balance between network latency and throughput when compared to conventional global blockchain systems. Further analysis of system under test (SUT) behavior was accomplished by running many benchmark rounds at varying transaction sending speeds. Maximum, median, and lowest transaction delays and throughput were measured by generating 1000 transactions for each benchmark. Transactions per second (TPS) rates varied between 20 and 500. Maximum delay rose when throughput reached 100 TPS, while minimum latency maintained a value below 1 s.
An Overview of Aplysinopsins: Synthesis and Biological Activities
Authors: El-Sawy Eslam R. , Kirsch Gilbert
Published: April 2023

Marine products are among the most promising sources of biologically active molecules. Aplysinopsins, tryptophan-derived marine natural products, were isolated from different natural marine sources including sponges, stony corals (hard corals) especially genus scleractinian, as well as sea anemone, in addition to one nudibranch. Aplysinopsins were reported to be isolated from different marine organisms related to various geographic areas such as Pacific, Indonesia, Caribbean, and Mediterranean regions. This review gives an up-to-date overview of marine alkaloid aplysinopsins: their various sources, their synthesis, and the fact that many aplysinopsin derivatives are biologically active compounds.
Chemomodulatory Effect of the Marine-Derived Metabolite “Terrein” on the Anticancer Properties of Gemcitabine in Colorectal Cancer Cells
Authors: Abuhijjleh Reham Khaled , Al Saeedy Dalia Yousef , Ashmawy Naglaa S. , Gouda Ahmed E. , Elhady Sameh S. , Al-Abd Ahmed Mohamed
Published: April 2023

Background: Terrein (Terr) is a bioactive marine secondary metabolite that possesses antiproliferative/cytotoxic properties by interrupting various molecular pathways. Gemcitabine (GCB) is an anticancer drug used to treat several types of tumors such as colorectal cancer; however, it suffers from tumor cell resistance, and therefore, treatment failure. Methods: The potential anticancer properties of terrein, its antiproliferative effects, and its chemomodulatory effects on GCB were assessed against various colorectal cancer cell lines (HCT-116, HT-29, and SW620) under normoxic and hypoxic (pO2 ≤ 1%) conditions. Further analysis via flow cytometry was carried out in addition to quantitative gene expression and 1HNMR metabolomic analysis. Results: In normoxia, the effect of the combination treatment (GCB + Terr) was synergistic in HCT-116 and SW620 cell lines. In HT-29, the effect was antagonistic when the cells were treated with (GCB + Terr) under both normoxic and hypoxic conditions. The combination treatment was found to induce apoptosis in HCT-116 and SW620. Metabolomic analysis revealed that the change in oxygen levels significantly affected extracellular amino acid metabolite profiling. Conclusions: Terrein influenced GCB’s anti-colorectal cancer properties which are reflected in different aspects such as cytotoxicity, cell cycle progression, apoptosis, autophagy, and intra-tumoral metabolism under normoxic and hypoxic conditions.
The Zooxanthellate Jellyfish Holobiont Cassiopea andromeda, a Source of Soluble Bioactive Compounds
Authors: De Domenico Stefania , De Rinaldis Gianluca , Mammone Marta , Bosch-Belmar Mar , Piraino Stefano , Leone Antonella
Published: April 2023

Cassiopea andromeda (Forsskål, 1775), commonly found across the Indo-Pacific Ocean, the Red Sea, and now also in the warmest areas of the Mediterranean Sea, is a scyphozoan jellyfish that hosts autotrophic dinoflagellate symbionts (family Symbiodiniaceae). Besides supplying photosynthates to their host, these microalgae are known to produce bioactive compounds as long-chain unsaturated fatty acids, polyphenols, and pigments, including carotenoids, with antioxidant properties and other beneficial biological activities. By the present study, a fractionation method was applied on the hydroalcoholic extract from two main body parts (oral arms and umbrella) of the jellyfish holobiont to obtain an improved biochemical characterization of the obtained fractions from the two body parts. The composition of each fraction (i.e., proteins, phenols, fatty acids, and pigments) as well as the associated antioxidant activity were analyzed. The oral arms proved richer in zooxanthellae and pigments than the umbrella. The applied fractionation method was effective in separating pigments and fatty acids into a lipophilic fraction from proteins and pigment–protein complexes. Therefore, the C. andromeda–dinoflagellate holobiont might be considered as a promising natural source of multiple bioactive compounds produced through mixotrophic metabolism, which are of interest for a wide range of biotechnological applications.
Chemical and Nutritional Profiling of the Seaweed Dictyota dichotoma and Evaluation of Its Antioxidant, Antimicrobial and Hypoglycemic Potentials
Authors: Imran Muhammad , Iqbal Arshad , Badshah Syed Lal , Sher Ayaz Ali , Ullah Hammad , Ayaz Muhammad , Mosa Osama F. , Mostafa Nada M. , Daglia Maria
Published: April 2023

Seaweed has been known to possess beneficial effects forhuman health due to the presence of functional bioactive components. The n-butanol and ethyl acetate extracts of Dictyota dichotoma showed ash (31.78%), crude fat (18.93%), crude protein (14.5%), and carbohydrate (12.35%) contents. About 19 compounds were identified in the n-butanol extract, primarily undecane, cetylic acid, hexadecenoic acid, Z-11-, lageracetal, dodecane, and tridecane, whereas 25 compounds were identified in the ethyl acetate extract, mainly tetradecanoic, hexadecenoic acid, Z-11-, undecane, and myristic acid. FT-IR spectroscopy confirmed the presence of carboxylic acid, phenols, aromatics, ethers, amides, sulfonates, and ketones. Moreover, total phenolic contents (TPC) and total flavonoid contents (TFC) in ethyl acetate extract were 2.56 and 2.51 mg GAE/g and in n-butanol extract were 2.11 and 2.25 mg QE/g, respectively. Ethyl acetate and n-butanol extracts at a high concentration of 100 mg mL−1 showed 66.64 and 56.56 % inhibition of DPPH, respectively. Antimicrobial activity revealed that Candida albicans was the most susceptible microorganism, followed by Bacillus subtilis, Staphylococcus aureus, and Escherichia coli, whereas Pseudomonas aeruginosa showed the least inhibition at all concentrations. The in vivo hypoglycemic study revealed that both extracts exhibited concentration-dependent hypoglycemic activities. In conclusion, this macroalgae exhibited antioxidant, antimicrobial, and hypoglycemic potentials.
The Potassium Efflux System Kef: Bacterial Protection against Toxic Electrophilic Compounds
Authors: Rasmussen Tim
Published: April 2023

Kef couples the potassium efflux with proton influx in gram-negative bacteria. The resulting acidification of the cytosol efficiently prevents the killing of the bacteria by reactive electrophilic compounds. While other degradation pathways for electrophiles exist, Kef is a short-term response that is crucial for survival. It requires tight regulation since its activation comes with the burden of disturbed homeostasis. Electrophiles, entering the cell, react spontaneously or catalytically with glutathione, which is present at high concentrations in the cytosol. The resulting glutathione conjugates bind to the cytosolic regulatory domain of Kef and trigger activation while the binding of glutathione keeps the system closed. Furthermore, nucleotides can bind to this domain for stabilization or inhibition. The binding of an additional ancillary subunit, called KefF or KefG, to the cytosolic domain is required for full activation. The regulatory domain is termed K+ transport–nucleotide binding (KTN) or regulator of potassium conductance (RCK) domain, and it is also found in potassium uptake systems or channels in other oligomeric arrangements. Bacterial RosB-like transporters and K+ efflux antiporters (KEA) of plants are homologs of Kef but fulfill different functions. In summary, Kef provides an interesting and well-studied example of a highly regulated bacterial transport system.