bluuebunny/crossref_metadata_2025 huggingface dataset:
iTRAQ-Based Quantitative Proteomics Unveils Protein Dynamics in the Root of Solanum melongena L. under Waterlogging Stress Conditions
Authors: Yang Xu , Jiang Zheng , He Jie , Shen Lei
Published: June 2023

Waterlogging poses significant abiotic stress that endangers the survival of plants, including crops. In response, plants dramatically change their physiology to enhance their tolerance to waterlogging, such as proteome reconfiguration. Here, we utilized isobaric tags for the relative and absolute quantitation (iTRAQ)-based protein labeling technique to examine the proteomic changes induced by waterlogging in the roots of Solanum melongena L., a solanaceous plant. The plants were subjected to 6, 12, and 24 h of waterlogging stress at the flowering stage. Of the 4074 identified proteins, compared to the control, the abundance of the proteins increased and decreased in 165 and 78 proteins, respectively, in 6 h of treatments; 219 and 89 proteins, respectively, in 12 h of treatments; and 126 and 127 proteins, respectively, in 24 h of treatments. The majority of these differentially regulated proteins participated in processes such as energy metabolism, amino acid biosynthesis, signal transduction, and nitrogen metabolism. Fructose–bisphosphate aldolase and three alcohol dehydrogenase genes, in particular, were up- or down-regulated in waterlogging-treated Solanum melongena roots, suggesting that some proteins related to anaerobic metabolism (glycolysis and fermentation) may play vital roles in protecting its roots from waterlogging stress to enable long-term survival. Overall, this research not only offers a comprehensive dataset of protein alterations in waterlogged Solanum melongena roots but also insights into the mechanisms by which solanaceous plants adapt to waterlogging stress.
Is Advanced Age a Factor That Influences the Clinical Outcome of Single- or Double-Level MIS-TLIF? A Single-Center Study with a Minimum Two-Year Follow-Up on 103 Consecutive Cases
Authors: Bongetta Daniele , de Laurentis Camilla , Bruno Raffaele , Versace Alessandro , Colombo Elena Virginia , Giussani Carlo Giorgio , Assietti Roberto
Published: June 2023

As life expectancy rises, more elderly people undergo spinal fusion surgery to treat lumbar degenerative diseases. The MIS-TLIF technique, which minimizes soft tissue manipulation, is a promising fusion technique for frailer patients. The aim of this study was to investigate if older age is a significant factor in the clinical outcome of single- or double-level MIS-TLIF. A cross-sectional study was conducted on 103 consecutive patients. Data were compared between younger (<65 y.o.) and older (≥65 y.o.) patients. We observed no significant differences between baseline characteristics of the two groups apart from the frequency of disk space treated, with a relative predominance of L3-L4 space treated in the elderly (10% vs. 28%, p = 0.01) and L5-S1 space in younger patients (36% vs. 5%, p = 0.006). There was no significant difference in complication rate, surgical satisfaction, EQ 5D-5L, or Oswestry Disability Index (ODI) global or specific scores, with the exception of the EQ 5D-5L “mobility” score, where older patients fared worse (1.8 ± 1.1 vs. 2.3 ± 1.4; p = 0.05). The minimal invasiveness of the surgical technique, age-related specific outcome expectations, and biomechanical issues are all potential factors influencing the lack of age group differences in outcome scores.
Shedding Light on the Cell Biology of Platelet-Derived Extracellular Vesicles and Their Biomedical Applications
Authors: Chaudhary Preeti Kumari , Kim Sanggu , Kim Soochong
Published: June 2023

EVs are membranous subcellular structures originating from various cells, including platelets which consist of biomolecules that can modify the target cell’s pathophysiological functions including inflammation, cell communication, coagulation, and metastasis. EVs, which are known to allow the transmission of a wide range of molecules between cells, are gaining popularity in the fields of subcellular treatment, regenerative medicine, and drug delivery. PEVs are the most abundant EVs in circulation, being produced by platelet activation, and are considered to have a significant role in coagulation. PEV cargo is extremely diverse, containing lipids, proteins, nucleic acids, and organelles depending on the condition that induced their release and can regulate a wide range of biological activities. PEVs, unlike platelets, can overcome tissue barriers, allowing platelet-derived contents to be transferred to target cells and organs that platelets cannot reach. Their isolation, characterization, and therapeutic efficacy, on the other hand, are poorly understood. This review summarizes the technical elements of PEV isolation and characterization methods as well as the pathophysiological role of PEVs, including therapeutic potential and translational possibility in diverse disciplines.
Scrophularia peyronii Post. from Jordan: Chemical Composition of Essential Oil and Phytochemical Profiling of Crude Extracts and Their In Vitro Antioxidant Activity
Authors: Al-Dalahmeh Yousef , Almahmoud Sondos Abdullah J. , Al-Bataineh Nezar , Alghzawi Taqwa A. , Alhamzani Abdulrahman G. , Al-Mutairi Aamal A. , Al-Jaber Hala I. , Abu Orabi Sultan T. , Bataineh Tareq T. , Al-Sheraideh Mohammed S. , Al-Qudah Mahmoud A.
Published: June 2023

The genus Scrophularia is one of the largest genera belonging to the Scrophulariaceae family. Different members of the genus exhibit an interesting, wide spectrum of bioactivities. Accordingly, the current study aimed to investigate, for the first time, the chemical composition of the essential oil of Scrophularia peyronii Post. from Jordan. Additionally, extracts obtained from the aerial parts with solvents of different polarities were assayed for their phytochemical constituents and in vitro antioxidant activities. The major constituents detected in the essential oil, as revealed by GC/MS analysis, contained mainly Z,Z-farnesyl acetone (11.04%), β-elemene (6.36%), n-octanal (5.98%), and spathulenol (4.58%). Each of the aqueous methanol (Sp-M) and butanol (Sp-B) extracts contained flavonoids, saponins, anthraquinone, and glycosides. Both extracts were evaluated for their total phenolic content (TPC), total flavonoid content (TFC), and their in vitro antioxidant activity, which were assayed using the DPPH radical scavenging activity and ABTS radical scavenging methods. Additionally, the two extracts were then subjected to LC-ESI-MS/MS for the qualitative determination of their secondary metabolite content, especially in flavonoids and phenolic compounds. The results showed that the Sp-B extract of S. peyronii had the highest contents of both phenolic compounds and flavonoids and showed high radical scavenging activity, as determined by the two assay methods, when compared with the Sp-M extract. The LC-ESI-MS/MS analysis resulted in the detection of 21 compounds, including 8 flavonoids, 6 phenolic acids, 6 iridoids, and 2 acids. Although the majority of compounds were detected in both extracts, it was noticed that scropolioside B, 6′-O-cinnamoylharpagide, isoferulic acid, and 6-O-methylcatapol were only detected in the Sp-M fraction.
Experimental Investigation of Tribology-Related Topography Parameters of Hard-Turned and Ground 16MnCr5 Surfaces
Authors: Molnar Viktor
Published: June 2023

Several surface topography parameters are available for the quantification of tribological properties of machined surfaces. Although these parameters and their influences are widely studied, there are contradictory findings due to the nature of the topography parameters, i.e., the behavior of different materials and cutting tool interactions lead to relatively varying numerical results. A comprehensive study of these interactions can contribute to more exact industrial machining applications. In this study, tribology-related 3D topography parameters of hard-machined (hard-turned and ground) surfaces were analyzed. The machining experiments were carried out based on a detailed design of the experiment; the analyzed material was case-hardened low-carbon content steel, which is widely used for automotive, industrial components such as bearings or gears. From the topography data, response function, correlation, and relative deviation analyses were carried out for the analyzed topography parameters, and tribology maps were created to support the selection of optimal cutting parameter values.
The Evolution of Structural Defects under Irradiation in W by Molecular Dynamics Simulation
Authors: Zheng Ruxin , Xuan Wujing , Xie Junjun , Chen Shasha , Yang Liuqing , Zhang Liang
Published: June 2023

Tungsten (W) can be used in plasma-facing components in a fusion reactor because of its excellent radiation resistance. Some studies have found that nanocrystalline metals with a high density of grain boundary show a higher ability to resist radiation damage compared to conventional coarse-grained materials. However, the interaction mechanism between grain boundary and defect is still unclear. In the present study, molecular dynamics simulations were carried out to explore the difference of defect evolution in single-crystal and bicrystal W, while the effects of temperature and the energy of the primary knocked atom (PKA) were taken into account. The irradiation process was simulated at the temperature range of 300 to 1500 K, and the PKA energy varied from 1 to 15 keV. The results show that the generation of defects is more sensitive to the energy of PKA than temperature; the number of defects increases at the thermal spike stage with the increase of the PKA energy, but the correlation with temperature is not strong. The presence of the grain boundary prevented the recombination of interstitial atoms and vacancies during the collision cascades, and the vacancies were more likely to form large clusters than interstitial atoms in the bicrystal models. This can be ascribed to the strong segregation tendency of the interstitial atoms to grain boundaries. The simulations provide useful information for understanding the role of grain boundaries in the evolution of irradiated structural defects.
Effect of the Addition of Re on the Microstructure and Phase Composition of Haynes 282: Ab Initio Modelling and Experimental Investigation of Additively Manufactured Specimens
Authors: Wadowski Antoni , Wróbel Jan S. , Koralnik Milena , Sitek Ryszard
Published: June 2023

Interactions in a multicomponent Ni-Cr-Mo-Al-Re model alloy were determined by ab initio calculations in order to investigate the Re doping effect on Haynes 282 alloys. Simulation results provided an understanding of short-range interactions in the alloy and successfully predicted the formation of a Cr and Re-rich phase. The Haynes 282 + 3 wt% Re alloy was manufactured using the additive manufacturing direct metal laser sintering (DMLS) technique, in which the presence of the (Cr17Re6)C6 carbide was confirmed by an XRD study. The results provide useful information about the interactions between Ni, Cr, Mo, Al, and Re as a function of temperature. The designed five-element model can lead to a better understanding of phenomena that occur during the manufacture or heat treatment of modern, complex, multicomponent Ni-based superalloys.
Linalool-Incorporated Synergistically Engineered Modified Liposomal Nanocarriers for Enhanced Transungual Delivery of Terbinafine against Onychomycosis
Authors: Gupta Isha , Adin Syeda Nashvia , Rashid Md Abdur , Alhamhoom Yahya , Aqil Mohd. , Mujeeb Mohd.
Published: June 2023

This work investigates the synthesis of linalool-containing invasomes for terbinafine (TBF-IN) in order to increase the solubility, bioavailability, and nail permeability of terbinafine (TBF) for transungual administration. TBF-IN was created utilising the thin-film hydration technique, and with the Box–Behnken design (BBD), optimisation was carried out. TBF-INopt were investigated for vesicle size, zeta potential, PDI (Polydispersity index), entrapment efficiency (EE) and in vitro TBF release. In addition, nail permeation analysis, TEM (transmission electron microscopy), and CLSM (confocal scanning laser microscopy) were performed for further evaluation. The TBF-INopt exhibited spherical as well as sealed vesicles with a considerably small size of 146.3 nm, an EE of 74.23 per cent, a PDI of 0.1612, and an in vitro release of 85.32 per cent. The CLSM investigation revealed that the new formulation had better TBF nail penetration than the TBF suspension gel. The antifungal investigation demonstrated that the TBF-IN gel has superior antifungal activity against Trichophyton rubrum and Candida albicans compared to the commercially available terbinafine gel. In addition, an investigation of skin irritation using Wistar albino rats indicates that the TBF-IN formulation is safe for topical treatment. This study confirmed that the invasomal vesicle formulation is an effective vehicle for the transungual delivery of TBF for the treatment of onychomycosis.
Preparation of a Ni-P-nanoPTFE Composite Coating on the Surface of GCr15 Steel for Spinning Rings via a Defoamer and Transition Layer and Its Wear and Corrosion Resistance
Authors: Mei Shunqi , Zhou Cong , Hu Zekui , Xiao Zhi , Zheng Quan , Chai Xuhui
Published: June 2023

In this study, a method of preparing a Ni-P-nanoPTFE composite coating on the surface of GCr15 steel for spinning rings is proposed. The method incorporates a defoamer into the plating solution to inhibit the agglomeration of nano-PTFE particles and pre-deposits a Ni-P transition layer to reduce the possibility of leakage coating. Meanwhile, the effect of varying the PTFE emulsion content in the bath on the micromorphology, hardness, deposition rate, crystal structure, and PTFE content of the composite coatings was investigated. The wear and corrosion resistances of the GCr15 substrate, Ni-P coating, and Ni-P-nanoPTFE composite coating are compared. The results show that the composite coating prepared at a PTFE emulsion concentration of 8 mL/L has the highest concentration of PTFE particles (up to 2.16 wt%). Additionally, its wear resistance and corrosion resistance are improved compared with Ni-P coating. The friction and wear study shows that the nano-PTFE particles with low dynamic friction coefficient are mixed in the grinding chip, which gives the composite coating self-lubricating characteristics, and the friction coefficient decreases to 0.3 compared with 0.4 of Ni-P coating. The corrosion study shows that the corrosion potential of the composite coating has increased by 7.6% compared with that of the Ni-P coating, which shifts from −456 mV to a more positive value of −421 mV. The corrosion current reduces from 6.71 μA to 1.54 μA, which is a 77% reduction. Meanwhile, the impedance increased from 5504 Ω·cm2 to 36,440 Ω·cm2, which is an increase of 562%.
Efficient Evaluation of Concrete Fracture Surface Roughness Using Fringe Projection Technology
Authors: Dai Meiling , Wang Xirui , Cheng Cheng , Chen Zhuoli , Deng Jiyu
Published: June 2023

The evaluation of concrete surface roughness is crucial in the field of civil engineering. The purpose of this study is to propose a no-contact and efficient method for the measurement of the roughness of concrete fracture surfaces based on fringe-projection technology. A simple phase-correction method using one additional strip image is presented for the phase unwrapping to improve the measurement efficiency and accuracy. The experimental results indicate that the measuring error for plane height is less than 0.1mm, and the relative accuracy for measuring a cylindrical object is about 0.1%, meeting the requirements for concrete fracture-surface measurement. On this basis, three-dimensional reconstructions were carried out on various concrete fracture surfaces to evaluate the roughness. The results reveal that the surface roughness (R) and fractal dimension (D) decrease as the concrete strength increases or the water-to-cement ratio decreases, consistent with previous studies. In addition, compared with the surface roughness, the fractal dimension is more sensitive to the change in concrete surface shape. The proposed method is effective for detecting concrete fracture-surface features.
Superior Mechanical Properties of Invar36 Alloy Lattices Structures Manufactured by Laser Powder Bed Fusion
Authors: He Gongming , Peng Xiaoqiang , Zhou Haotian , Huang Guoliang , Xie Yanjun , He Yong , Liu Han , Huang Ke
Published: June 2023

Invar36 alloy is a low expansion alloy, and the triply periodic minimal surfaces (TPMS) structures have excellent lightweight, high energy absorption capacity and superior thermal and acoustic insulation properties. It is, however, difficult to manufacture by traditional processing methods. Laser powder bed fusion (LPBF) as a metal additive manufacturing technology, is extremely advantageous for forming complex lattice structures. In this study, five different TPMS cell structures, Gyroid (G), Diamond (D), Schwarz-P (P), Lidinoid (L), and Neovius (N) with Invar36 alloy as the material, were prepared using the LPBF process. The deformation behavior, mechanical properties, and energy absorption efficiency of these structures under different load directions were studied, and the effects and mechanisms of structure design, wall thickness, and load direction were further investigated. The results show that except for the P cell structure, which collapsed layer by layer, the other four TPMS cell structures all exhibited uniform plastic collapse. The G and D cell structures had excellent mechanical properties, and the energy absorption efficiency could reach more than 80%. In addition, it was found that the wall thickness could adjust the apparent density, relative platform stress, relative stiffness, energy absorption, energy absorption efficiency, and deformation behavior of the structure. Printed TPMS cell structures have better mechanical properties in the horizontal direction due to intrinsic printing process and structural design.
Knock Mitigation and Power Enhancement of Hydrogen Spark-Ignition Engine through Ammonia Blending
Authors: Ge Haiwen , Bakir Ahmad Hadi , Zhao Peng
Published: June 2023

Hydrogen and ammonia are primary carbon-free fuels that have massive production potential. In regard to their flame properties, these two fuels largely represent the two extremes among all fuels. The extremely fast flame speed of hydrogen can lead to an easy deflagration-to-detonation transition and cause detonation-type engine knock that limits the global equivalence ratio, and consequently the engine power. The very low flame speed and reactivity of ammonia can lead to a low heat release rate and cause difficulty in ignition and ammonia slip. Adding ammonia into hydrogen can effectively modulate flame speed and hence the heat release rate, which in turn mitigates engine knock and retains the zero-carbon nature of the system. However, a key issue that remains unclear is the blending ratio of NH3 that provides the desired heat release rate, emission level, and engine power. In the present work, a 3D computational combustion study is conducted to search for the optimal hydrogen/ammonia mixture that is knock-free and meanwhile allows sufficient power in a typical spark-ignition engine configuration. Parametric studies with varying global equivalence ratios and hydrogen/ammonia blends are conducted. The results show that with added ammonia, engine knock can be avoided, even under stoichiometric operating conditions. Due to the increased global equivalence ratio and added ammonia, the energy content of trapped charge as well as work output per cycle is increased. About 90% of the work output of a pure gasoline engine under the same conditions can be reached by hydrogen/ammonia blends. The work shows great potential of blended fuel or hydrogen/ammonia dual fuel in high-speed SI engines.
Dynamic Modeling and Performance Evaluation of a 5-DOF Hybrid Robot for Composite Material Machining
Authors: Wang Xiaojian , Wu Jun , Zhou Yulin
Published: June 2023

Dynamic performance is an important performance of robots used for machine processing. This paper studies the dynamic modeling and evaluation method of a 5-DOF (Degree of Freedom) hybrid robot used in aerospace composite material processing. With the consideration of the dynamics of the serial part, the complete dynamic model of the hybrid robot is established based on the virtual work principle. In addition to the widely considered acceleration term, a dynamic performance evaluation index that comprehensively considers the acceleration term, velocity term and gravity term in the dynamic model is proposed. Using the dynamic performance index, the effect of the placement direction of the robot and the arrangement of the double symmetric limbs on robot dynamics are investigated. The results indicate that the vertical placement is beneficial to the dynamics of the hybrid robot, and the arrangement of double symmetric limbs has different effects on different limbs.
Dynamic Footprints of the Specific Artificial Spin Ice Microstate on Its Spin Waves
Authors: Micaletti Pietro , Montoncello Federico
Published: June 2023

We present a micromagnetic investigation of the spin dynamics at remanence (zero applied field) in a periodic square artificial spin ice (ASI) prepared four different microstates (i.e., with zero, two or four magnetic charges at the vertex). The ASI elements consist of permalloy elliptical dots with a fixed long axis, and a variable width and interdot separation. For each vertex configuration, we compute the equilibrium ground state at zero applied field by relaxing a previously set magnetic configuration (microstate). After the excitation of such ground state, we perform a Fourier analysis obtaining frequency spectra and space phase profiles. We discuss the behavior of the spectra in changing the system’s microstate and geometry, with reference to the spin mode space profiles, magnetization configuration, and effective internal field. Our results draw a correlation between ASI macrospin orientation at vertex and a few important dynamic properties like a phase-shift in the mode profiles or the frequency gap between the edge and fundamental modes. We suggest a few specific experiments to validate of our predictions, as well as applications in the field of interferometric magnonic devices. We believe that our results can help, from the fabrication stage, in tailoring the appropriate ASI geometry for specific application purposes.
RDAF-IIoT: Reliable Device-Access Framework for the Industrial Internet of Things
Authors: Alasmary Hisham
Published: June 2023

The Internet of Things (IoT) has experienced significant growth and is now a fundamental part of the next-generation Internet. Alongside improving daily life, IoT devices generate and collect vast amounts of data that can be leveraged by AI-enabled big data analytics for diverse applications. However, due to the machine-to-machine communication inherent in IoT, ensuring data security and privacy is crucial to mitigate various malicious cyber attacks, including man-in-the-middle, impersonation, and data poisoning attacks. Nevertheless, designing an efficient and adaptable IoT security framework poses challenges due to the limited computational and communication power of IoT devices, as well as their wide-ranging variety. To address these challenges, this paper proposes an Access Key Agreement (AKA) scheme called the “Reliable Device-Access Framework for the Industrial IoT (RDAF-IIoT)”. RDAF-IIoT verifies the user’s authenticity before granting access to real-time information from IIoT devices deployed in an industrial plant. Once authenticated at the gateway node, the user and IIoT device establish a session key for future encrypted communication. The security of the proposed RDAF-IIoT is validated using a random oracle model, while the Scyther tool is employed to assess its resilience against various security attacks. Performance evaluations demonstrate that the proposed scheme requires lower computational and communication costs compared to related security frameworks while providing enhanced security features.
The Mechanism of Orientation Detection Based on Artificial Visual System for Greyscale Images
Authors: Zhang Xiliang , Tao Sichen , Tang Zheng , Zheng Shuxin , Todo Yoki
Published: June 2023

Human visual system is a crucial component of the nervous system, enabling us to perceive and understand the surrounding world. Advancements in research on the visual system have profound implications for our understanding of both biological and computer vision. Orientation detection, a fundamental process in the visual cortex where neurons respond to linear stimuli in specific orientations, plays a pivotal role in both fields. In this study, we propose a novel orientation detection mechanism for local neurons based on dendrite computation, specifically designed for grayscale images. Our model comprises eight neurons capable of detecting local orientation information, with inter-neuronal interactions facilitated through nonlinear dendrites. Through the extraction of local orientation information, this mechanism effectively derives global orientation information, as confirmed by successful computer simulations. Experimental results demonstrate that our mechanism exhibits remarkable orientation detection capabilities irrespective of variations in size, shape, or position, which aligns with previous physiological research findings. These findings contribute to our understanding of the human visual system and provide valuable insights into both biological and computer vision. The proposed orientation detection mechanism, with its nonlinear dendritic computations, offers a promising approach for improving orientation detection in grayscale images.
Deep Diffusion Kalman Filter Combining Large-Scale Neuronal Networks Simulation with Multimodal Neuroimaging Data
Authors: Zhang Wenyong , Lu Wenlian
Published: June 2023

Using computers to numerically simulate large-scale neuronal networks has become a common method for studying the mechanism of the human brain, and neuroimaging has brought forth multimodal brain data. Determining how to fully consider these multimodal data in the process of brain modeling has become a crucial issue. Data assimilation is an efficient method for combining the dynamic system with the observation data, and many related algorithms have been developed. In this paper, we utilize data assimilation to perform brain state variables estimation, put forward a general form of a diffusion Kalman filter named the deep diffusion Kalman filter, and provide a specific algorithm that is combined with data assimilation. Then, we theoretically demonstrate the deep diffusion Kalman filter’s effectiveness and further validate it by using an experiment in the toy model. Finally, according to the resting state functional magnetic resonance imaging signals, we assimilate a cortex networks model with the resting state brain, where the correlation is as high as 98.42%.
(Iq)–Stability and Uniform Convergence of the Solutions of Singularly Perturbed Boundary Value Problems
Authors: Vrabel Robert
Published: June 2023

In this paper, using the notion of (Iq)–stability and the method of a priori estimates, known as the method of lower and upper solutions, the sufficient conditions guaranteeing uniform convergence of solutions to the solution of a reduced problem on the entire interval [a,b] have been established for four different types of boundary conditions for a singularly perturbed differential equation εy″=f(x,y,y′), a≤x≤b. In the second part of the paper, by employing the Peano phenomenon, we analyzed the structure of the solutions of the reduced problem f(x,y,y′)=0.
Research Based on High-Dimensional Fused Lasso Partially Linear Model
Authors: Feng Aifen , Fan Jingya , Jin Zhengfen , Zhao Mengmeng , Chang Xiaogai
Published: June 2023

In this paper, a partially linear model based on the fused lasso method is proposed to solve the problem of high correlation between adjacent variables, and then the idea of the two-stage estimation method is used to study the solution of this model. Firstly, the non-parametric part of the partially linear model is estimated using the kernel function method and transforming the semiparametric model into a parametric model. Secondly, the fused lasso regularization term is introduced into the model to construct the least squares parameter estimation based on the fused lasso penalty. Then, due to the non-smooth terms of the model, the subproblems may not have closed-form solutions, so the linearized alternating direction multiplier method (LADMM) is used to solve the model, and the convergence of the algorithm and the asymptotic properties of the model are analyzed. Finally, the applicability of this model was demonstrated through two types of simulation data and practical problems in predicting worker wages.
Pricing Variance Swaps under MRG Model with Regime-Switching: Discrete Observations Case
Authors: Zou Anqi , Wang Jiajie , Wu Chiye
Published: June 2023

In this paper, we creatively price the discretely sampled variance swaps under the mean-reverting Gaussian model (MRG model in short) with regime-switching asymmetric double exponential jump diffusion. We extend the traditional MRG model by further considering the trend of the financial market as well as a sudden and unexpected event of the market. This new model is meaningful because it uses observable Markov chains that represent market states to adjust its parameters, which helps capture the movement of the market and fluctuations in asset prices. By utilizing the characteristic function and the conditional transition characteristic function, we obtain analytical solutions for pricing formulae. Note that this is our first effort to provide the analytical solution for the ordinary differential equations satisfied by the Feynman–Kac theorem. To achieve this, we have developed a new methodology in Proposition 2 that involves dividing the sampling interval into more detailed switching and non-switching intervals. One significant advantage of our closed-form solution is its high computational accuracy and efficiency. Subsequent semi-Monte Carlo simulations will provide specific validation results.
Position and Attitude Tracking Finite-Time Adaptive Control for a VTOL Aircraft using Global Fast Terminal Sliding Mode Control
Authors: Deng Xiongfeng , Huang Yiqing , Xu Binzi , Tao Liang
Published: June 2023

In this work, the position and attitude tracking finite-time adaptive control problem of a type of vertical take-off and landing (VTOL) aircraft system is studied. Here, the dynamic of the VTOL aircraft is subjected to external disturbances and unknown nonlinearities. Firstly, radial basis function neural networks are introduced to approximate these unknown nonlinearities, and adaptive weight update laws are proposed to replace unknown ideal weights. Secondly, for the errors generated in the approximation process and the external disturbances of the aircraft system, adaptive parameter update laws are presented. After that, based on the designed global fast terminal sliding mode control functions and adaptive update laws, we present the position tracking control laws and the roll angle control law. Then, based on this, the adaptive global fast terminal sliding control laws for the given aircraft system are finally obtained. Meanwhile, the stability of the aircraft control system is proven by using Lyapunov stability theory and designed adaptive control laws. It is not only ensured that the outputs of the aircraft system can track the given trajectories, but also ensured that the tracking errors can converge to approximately zero within a finite time. Finally, the validity of the designed adaptive control laws is verified through three numerical examples. It can be obtained that the finite-time tracking problems of the given aircraft system can be achieved at 18.8766 s and 14.6340 s under the given parameters. The results are consistent with the theoretical analysis. In addition, under the control laws proposed in this work, the aircraft system can achieve tracking after 9.443 s and 9.674 s and the tracking errors are basically close to zero, which is significantly superior to other control methods considered in this work.
Non-Ferrous Metal Price Point and Interval Prediction Based on Variational Mode Decomposition and Optimized LSTM Network
Authors: Zhao Yifei , Chen Jianhong , Shimada Hideki , Sasaoka Takashi
Published: June 2023

The accurate forecasting of metal prices is of great importance to industrial producers as the supply of metal raw materials is a very important part of industrial production. The futures market is subject to many factors, and metal prices are highly volatile. In the past, most of the relevant research has focused only on deterministic point forecasting, with less research performed on interval uncertainty forecasting. Therefore, this paper proposes a novel forecasting model that combines point forecasting and interval forecasting. First, a novel hybrid price point forecasting model was established using Variational Modal Decomposition (VMD) and a Long Short-Term Memory Neural Network (LSTM) based on Sparrow Search Algorithm (SSA) optimization. Then, five distribution functions based on the optimization algorithm were used to fit the time series data patterns and analyze the metal price characteristics, Finally, based on the optimal distribution function and point forecasting results, the forecasting range and confidence level were set to determine the interval forecasting model. The interval forecasting model was validated by inputting the price data of copper and aluminum into the model and obtaining the interval forecasting results. The validation results show that the proposed hybrid forecasting model not only outperforms other comparative models in terms of forecasting accuracy, but also has a better performance in forecasting sharp fluctuations and data peaks, which can provide a more valuable reference for producers and investors.
Parameter Tuning for WECC Generic Photovoltaic System Models Using Latin Hypercube Sampling and Pareto Optimality
Authors: Yang Nien-Che , Hsu Chun-Wei , Sen Abhilash
Published: June 2023

With attention increasing towards worldwide ecological conservation, the energy policies of various countries are moving towards renewable energy systems, primarily with solar and wind as the primary power sources. The Western Electricity Coordinating Council (WECC) has developed a generic model as a simulation framework for a typical solar wind generation system to analyze the response of the actual equipment. In this paper, we propose a parameter tuning process for a generic model controller that combines Latin hypercube sampling and Pareto optimization to enable a generic model to effectively match the output of an actual inverter device. Different operating scenarios were considered to match the dynamic characteristics of the inverter device using the multi-objective particle swarm algorithm (MOPSO) along with Pareto optimization. The effectiveness of the proposed parameter tuning process was verified on a user-defined test system and, later, the IEEE 39 bus system with a large solar power facility.
Magnetohydrodynamics Williamson Nanofluid Flow over an Exponentially Stretching Surface with a Chemical Reaction and Thermal Radiation
Authors: Muzara Hillary , Shateyi Stanford
Published: June 2023

Presented in this current study is the numerical analysis of magnetohydrodynamics Williamson nanofluid flow over an exponentially stretching surface. The most important aspect of the investigation is that the effects of the magnetic field, chemical reaction and thermal radiation in the fluid flow are taken into account. The partial differential equations governing the present Williamson nanofluid flow problem were observed to be highly nonlinear and coupled. Suitable similarity transformations were used to transmute the coupled system of nonlinear partial differential equations governing the fluid flow into a linear system. The linear system was solved numerically using the spectral quasi-linearization method. The MATLAB bvp4c numerical technique and a comparison with existing results for the skin friction coefficient were used to confirm the appropriateness of the method in solving the current problem. The influence of some pertinent physical parameters on the fluid’s velocity, temperature and concentration profiles were displayed graphically. The effects of all the physical parameters on the skin friction coefficient, Nusselt number and Sherwood number were portrayed in a tabular form. It was noted that enhancing the thermal radiation parameter reduces the fluid’s temperature, Nusselt number and the skin friction coefficient, while the Sherwood number is improved.
The “Selfie Test”: A Novel Test for the Diagnosis of Lateral Epicondylitis
Authors: Factor Shai , Snopik Pablo Gabriel , Albagli Assaf , Rath Ehud , Amar Eyal , Atlan Franck , Morag Guy
Published: June 2023

Background: Lateral epicondylitis (LE) is one of the most diagnosed elbow pathologies. The purpose of this study was to determine the diagnostic test accuracy of a new test (selfie test) for the diagnosis of LE. Methods: Medical data were collected from adult patients who presented with LE symptoms and ultrasound findings that supported the diagnosis. Patients underwent a physical examination, including provocative tests for diagnosis as well as the selfie test, and were asked to fill out the Patient-Rated Tennis Elbow Evaluation (PRTEE) questionnaire and subjectively rate the activity of their affected elbow. Results: Thirty patients were included in this study (seventeen females, 57%). The mean age was 50.1 years old (range of 35 to 68 years). The average duration of symptoms was 7 ± 3.1 months (range of 2 to 14 months). The mean PRTEE score was 61.5 ± 16.1 (range of 35 to 98), and the mean subjective elbow score was 63 ± 14.2 (range of 30 to 80). Mill’s, Maudsley’s, Cozen’s, and the selfie tests had sensitivities of 0.867, 0.833, 0.967, and 0.933, respectively, with corresponding positive predictive values of 0.867, 0.833, 0.967, and 0.933. Conclusions: The selfie test’s active nature, which allows patients to perform the assessment themselves, could be a valuable addition to the diagnostic process, potentially improving the accuracy of the diagnosis of LE (levels of evidence: IV).
Sintering Aid Strategy for Promoting Oxygen Reduction Reaction on High-Performance Double-Layer LaNi0.6Fe0.4O3–δ Composite Electrode for Devices Based on Solid-State Membranes
Authors: Osinkin Denis , Bogdanovich Nina
Published: June 2023

Strontium and cobalt-free LaNi0.6Fe0.4O3–δ is considered one of the most promising electrodes for solid-state electrochemical devices. LaNi0.6Fe0.4O3–δ has high electrical conductivity, a suitable thermal expansion coefficient, satisfactory tolerance to chromium poisoning, and chemical compatibility with zirconia-based electrolytes. The disadvantage of LaNi0.6Fe0.4O3–δ is its low oxygen-ion conductivity. In order to increase the oxygen-ion conductivity, a complex oxide based on a doped ceria is added to the LaNi0.6Fe0.4O3–δ. However, this leads to a decrease in the conductivity of the electrode. In this case, a two-layer electrode with a functional composite layer and a collector layer with the addition of sintering additives should be used. In this study, the effect of sintering additives (Bi0.75Y0.25O2–δ and CuO) in the collector layer on the performance of LaNi0.6Fe0.4O3–δ-based highly active electrodes in contact with the most common solid-state membranes (Zr0.84Sc0.16O2–δ, Ce0.8Sm0.2O2–δ, La0.85Sr0.15Ga0.85Mg0.15O3–δ, La10(SiO4)6O3–δ, and BaCe0.89Gd0.1Cu0.01O3–δ) was investigated. It was shown that LaNi0.6Fe0.4O3–δ has good chemical compatibility with the abovementioned membranes. The best electrochemical activity (polarization resistance about 0.02 Ohm cm2 at 800 °C) was obtained for the electrode with 5 wt.% Bi0.75Y0.25O1.5 and 2 wt.% CuO in the collector layer.
Nano-Chitosan/Eucalyptus Oil/Cellulose Acetate Nanofibers: Manufacturing, Antibacterial and Wound Healing Activities
Authors: Elbhnsawi Nagwa A. , Elwakil Bassma H. , Hassanin Ahmed H. , Shehata Nader , Elshewemi Salma Sameh , Hagar Mohamed , Olama Zakia A.
Published: June 2023

Accelerated wound healing in infected skin is still one of the areas where current therapeutic tactics fall short, which highlights the critical necessity for the exploration of new therapeutic approaches. The present study aimed to encapsulate Eucalyptus oil in a nano-drug carrier to enhance its antimicrobial activity. Furthermore, in vitro, and in vivo wound healing studies of the novel nano-chitosan/Eucalyptus oil/cellulose acetate electrospun nanofibers were investigated. Eucalyptus oil showed a potent antimicrobial activity against the tested pathogens and the highest inhibition zone diameter, MIC, and MBC (15.3 mm, 16.0 μg/mL, and 256 μg/mL, respectively) were recorded against Staphylococcus aureus. Data indicated a three-fold increase in the antimicrobial activity of Eucalyptus oil encapsulated chitosan nanoparticle (43 mm inhibition zone diameter against S. aureus). The biosynthesized nanoparticles had a 48.26 nm particle size, 19.0 mV zeta potential, and 0.45 PDI. Electrospinning of nano-chitosan/Eucalyptus oil/cellulose acetate nanofibers was conducted, and the physico-chemical and biological properties revealed that the synthesized nanofibers were homogenous, with a thin diameter (98.0 nm) and a significantly high antimicrobial activity. The in vitro cytotoxic effect in a human normal melanocyte cell line (HFB4) proved an 80% cell viability using 1.5 mg/mL of nano-chitosan/Eucalyptus oil/cellulose acetate nanofibers. In vitro and in vivo wound healing studies revealed that nano-chitosan/Eucalyptus oil/cellulose acetate nanofibers were safe and efficiently enhanced the wound-healing process through enhancing TGF-β, type I and type III collagen production. As a conclusion, the manufactured nano-chitosan/Eucalyptus oil/cellulose acetate nanofiber showed effective potentiality for its use as a wound healing dressing.
Membranes in Water Reclamation: Treatment, Reuse and Concentrate Management
Authors: Devaisy Sukanyah , Kandasamy Jaya , Nguyen Tien Vinh , Ratnaweera Harsha , Vigneswaran Saravanamuthu
Published: June 2023

In this article, an extensive examination is provided on the possible uses of membranes and hybrid processes in wastewater treatment. While membrane technologies face certain constraints, such as membrane fouling and scaling, the incomplete elimination of emerging contaminants, elevated expenses, energy usage, and brine disposal, there are approaches that can address these challenges. Methods such as pretreating the feed water, utilizing hybrid membrane systems and hybrid dual-membrane systems, and employing other innovative membrane-based treatment techniques can enhance the efficacy of membrane processes and advance sustainability.
Bringing GPCR Structural Biology to Medical Applications: Insights from Both V2 Vasopressin and Mu-Opioid Receptors
Authors: Fouillen Aurélien , Bous Julien , Granier Sébastien , Mouillac Bernard , Sounier Remy
Published: June 2023

G-protein coupled receptors (GPCRs) are versatile signaling proteins that regulate key physiological processes in response to a wide variety of extracellular stimuli. The last decade has seen a revolution in the structural biology of clinically important GPCRs. Indeed, the improvement in molecular and biochemical methods to study GPCRs and their transducer complexes, together with advances in cryo-electron microscopy, NMR development, and progress in molecular dynamic simulations, have led to a better understanding of their regulation by ligands of different efficacy and bias. This has also renewed a great interest in GPCR drug discovery, such as finding biased ligands that can either promote or not promote specific regulations. In this review, we focus on two therapeutically relevant GPCR targets, the V2 vasopressin receptor (V2R) and the mu-opioid receptor (µOR), to shed light on the recent structural biology studies and show the impact of this integrative approach on the determination of new potential clinical effective compounds.
A Novel Electrode Front-End Face Design to Improve Geometric Accuracy in Electrical Discharge Machining Process
Authors: Wang Shih-Ming , Peng Jin-Kai , Gunawan Hariyanto , Tu Ren-Qi , Chiou Shean-Juinn
Published: June 2023

Electrical discharge machining (EDM) is one of the important machining processes to produce mold components. When using the EDM process, surface quality, processing time, accuracy, and electrode cost must be considered. The electrode wear is the main factor that causes error on the geometric accuracy, especially the workpiece corner. Therefore, this study proposes a novel electrode design to improve the geometric accuracy for the EDM process. Firstly, the effect of discharge current, electrode diameter, and depth of cut on the electrode wear and workpiece corner were investigated. Multiple regression and analysis of variant were used to analyze the experiment data. The electrode end-face design with compensation rule and algorithm was established based on the data analysis and error value. Furthermore, a compensated electrode end-face design system with human machine interface, which has a procedure guiding function, was developed. The system can design the electrode end-face for minimizing workpiece corner error and improve geometric accuracy. Finally, cutting experiments were conducted to verify the proposed method, and the results show that the proposed method can effectively enhance the geometric accuracy by around 22~37%.
Differential Analysis and Prediction of Planar Shape at the Head and Tail Ends of Medium-Thickness Plate Rolling
Authors: Yang Shiyu , Liu Hongmin , Wang Dongcheng
Published: June 2023

This paper aims to improve planar shape prediction accuracy in the rolling process of medium and thick plates. We present a model based on the strip method that addresses limitations in predicting planar shape variations at the head and tail ends of rolled pieces. By analysing the rolling process, we introduce the concept of an imaginary strip longitudinal length difference to represent planar shape characteristics effectively. By analysing the change in metal shape in the rolling deformation zone, the calculation formula for metal volume in the deformation zone is derived. This establishes a relationship between the longitudinal length difference at the rolled piece ends and the metal volume in the deformation zone. The prediction of plane shape difference between the end and the head of medium and medium-thickness plate is realized. The experimental results confirm the feasibility and effectiveness of the proposed method.
Effect of B and N Content and Austenitization Temperature on the Tensile and Impact Properties of Modified 9Cr-1Mo Steels
Authors: Rejeesh Ravindran , Barik Rakesh , Mitra Rahul , Kostryzhev Andrii , Das Chitta , Albert Shaju , Chakrabarti Debalay
Published: June 2023

The present study investigates the relative effect of B and N concentrations and the austenitization temperature on the microstructure and mechanical properties (tensile and Charpy impact) of modified 9Cr-1Mo (P91) steels. Initially, a B-free P91 steel (with 500 ppm N) and four different B-containing steels (25–100 ppm) with varying N concentrations (20–108 ppm) were hot-rolled, normalized from different austenitization temperatures (1000–1100 °C/1 h) and finally tempered at 760 °C for 1 h. A Charpy impact test shows that the ductile–brittle transition temperature (DBTT) of all the B-added steels decreases with an increase in the austenitization temperature, where the 100 ppm B steel offers the lowest DBTT (−85 °C). Similarly, the strength increases with the increase in the austenitization temperature (1100 °C), with a slight drop in ductility. The influence of precipitates on the microstructure and mechanical properties is explained considering the B enrichment at the precipitates and the thermodynamic stability of the precipitates. The 100 ppm B steel (containing the maximum B and minimum N), normalized from 1100 °C austenitization, shows the best combination of tensile and Charpy impact properties, owing to the effective dissolution of coarse M23C6 and MX precipitates during the normalization treatment and the formation of fine B-rich (Fe,Cr)23(B,C)6 precipitates during the subsequent tempering.