Basis For Optimization Research Articles

Sparse representation for massive MIMO satellite channel based on joint dictionary learning

AbstractA constrained joint dictionary learning (CJDL) algorithm for high‐precision channel representation in massive multiple input multiple output (MIMO) satellite systems is proposed. Furthermore, taking into account the angular reciprocity of massive MIMO satellite systems, joint dictionary learning can establish a common support basis for both uplink and downlink. Previous deterministic dictionary has utilized deterministic basis, such as discrete Fourier transform (DFT) or orthogonal DFT (ODFT) basis, which tend to represent noise interference as part of channel characteristics. Furthermore, this deterministic dictionary is not able to adapt to dynamic communication environments. However, dictionary learning has shown the potential to significantly improve the accuracy of channel representation. Nevertheless, current research on training dictionary lacks analysis regarding constraints and boundary requirements, resulting in a suboptimal basis. To address this issue, conditional constraints associated with joint dictionary for channel representation are analysed. To screen for optimal basis, the joint dictionary is subject to constraints, including uplink and downlink constraints. Furthermore, the authors aim to quantify the maximum boundary of joint dictionary learning. Additionally, a joint dictionary updating method with singular value decomposition under constraint boundary conditions is proposed. Simulation results demonstrate that the proposed CJDL algorithm provides a more accurate and robust channel representation.

Application of proper orthogonal decomposition to flow fields around various geometries and reduced-order modeling

This study is focused on a reduced-order model (ROM) based on proper orthogonal decomposition (POD) for unsteady flow around a stationary object, which allows prediction with different object geometry as a parameter. The conventional POD method is applicable only to data with the same computational grid for all snapshots. This study proposed a novel POD methodology that performs on flow snapshots, including some time-series data of flow fields around objects of different shapes and numerically computed by different computational grids. The concept of the proposed POD involved mapping the flow fields computed on different grids in computational space. Consequently, the optimal POD basis for minimizing reconstruction errors in physical space was obtained in the computational space. The proposed POD was applied to the flow around ellipses and airfoils generated via conformal mapping to a cylinder. The ROM formulated using the proposed POD bases reconstructed the flow fields around the ellipses with different aspect ratios and airfoils with varying shapes. Using the modes obtained by the proposed POD, the ROM was demonstrated to stably predict the time evolution of the flow around objects, which is not included in the snapshots. In the ROM, the difference between the frequency of the flow field in the POD snapshot and that of the reconstructed flow field resulted in a phase error owing to the time evolution. The mean squared error between the flow fields obtained via the ROM and the directly solved Navier–Stokes equations was under 10−7 when the reconstructed flow and the flow included in the snapshot had the same frequency as that of Kármán vorticities behind the objects. Based on these observations, the proposed POD is suitable for constructing an ROM to reconstruct the flow around various geometries.

Innovative Research on the Integration of Traditional Chinese Medicine and Artificial Intelligence for the Treatment of Herpes Zoster

Herpes zoster is a skin disease caused by the varicella-zoster virus (VZV), primarily manifesting as painful skin rashes in localized areas. Traditional Chinese medicine has a long history of treating herpes zoster, and the integration of modern artificial intelligence (AI) technologies holds promise for further enhancing treatment efficacy. This study aims to construct an AI-based traditional Chinese medicine treatment plan by analyzing large-scale clinical data and traditional medical literature to establish individualized diagnostic models. The experimental results demonstrate that this method effectively shortens the disease course and reduces the incidence of complications. Additionally, the study reveals the mechanisms of action of various components of traditional Chinese medicine in treatment, providing a basis for further optimization of treatment plans. This innovative integration approach not only improves treatment precision but also offers a new paradigm for combined traditional and Western medicine treatment. This paper not only showcases the potential of AI in the field of traditional Chinese medicine but also provides new insights into the treatment of herpes zoster.

Research on weathering recognition model of ancient glass based on three-layer neural network

In this paper, a three-layer neural network-based weathering recognition model for ancient glass is proposed to cope with the limitations of traditional weathering analysis methods in dealing with complexity and large-scale data. By constructing a multi-layer feed-forward neural network model containing input, hidden and output layers, this paper achieves high-precision classification of the weathering state of ancient glass. The experimental results show that the accuracy of the model reaches 98.0% and 100% on the training set and test set, respectively, which proves the effectiveness and efficiency of the method in the recognition of ancient glass weathering. This study demonstrates the potential of neural network application in cultural relics conservation and provides a theoretical basis for further optimisation of cultural relics identification techniques.

Investigations of sequential excavation and reinforcement in tunnels based on the extended three-dimensional discontinuous deformation analysis method

The unloading effect of excavation is the key factor leading to rock mass instability, and bolt support is the key means of controlling the stability. However, the original three-dimensional discontinuous deformation analysis method (3D DDA) can only simulate rock mass instability and bolt support after the tunnel is excavated, which makes it difficult to study the effect of tunnel excavation and bolt support on rock mass stability. Therefore, an algorithm to confirm the excavated blocks and reinforced blocks based on the volume judgment method (VJM) was proposed in this paper. Sequential excavation and reinforcement in tunnels can be simulated by introducing the time variables of block excavation and bolt deployment into the 3D DDA method. By embedding these two algorithms in the 3D DDA method, an extended 3D DDA method for sequential excavation and reinforcement in tunnels was developed, named the 3D DDA_ES method. Based on the 3D DDA_ES method, the collapse that occurred during the construction of the Huangjiazhuang Tunnel was simulated, and the displacement of key blocks and the axial force of the bolts were analyzed. According to the simulation results, the axial force on the bolts is strongly related to the position of the key blocks, and the axial force on the bolts at the tunnel roof is much greater than that at the tunnel arch shoulder. In this regard, these bolts with axial forces less than 1 kN are removed during the simulation, and the key blocks remain stable with a maximum displacement of 12 cm. The research results can provide a theoretical basis for tunnel construction and reinforcement parameter optimization for similar projects.

Optical study on spray mixing, flame propagation and jets evolution within visible methanol active pre-chamber for turbulent jet ignition

Methanol spray impingement, mixing, flame propagation and jet evolution within the narrow-confined active pre-chamber (APC) with complex walls were experimentally observed by optical method for the first time. The effects of injection pressure and duration was investigated on an actual-geometry optical APC assembled in constant volume combustion chamber (CVC). Exploration on APC internal processes within static environments forms the basis for optimization of APC and analysis of jet formation. Mie scattering coupled with flame natural luminosity imaging were used to record spray mixing and combustion. The results show that in the APC with narrow-confined space, methanol spray undergoes three wall impingements, inducing a tumble that promotes mixing. High injection pressure enhances rapid spray tip penetration, while long injection duration slows methanol diffusion. In longer injection duration cases, the spray tip after the third impingement interferes with subsequent sprays. For higher injection pressure, this interference occurs in the APC cone section due to a larger spray cone angle, whereas for lower pressure, it happens in the APC duct section. Higher injection pressure also causes more spray to impact the APC bottom after the first wall impingement, hindering flame acceleration in the duct section. Irregular flame propagation is observed in the APC cone section due to wider space and uneven mixture conditions, while the convergent geometry from the APC throat to the duct section significantly accelerates flame propagation. The APC jet appears due to the pressure difference between the APC and the main chamber, with the brightness and length of the visible flame jet increasing with APC flame luminosity and pressure difference. A Mach ring structure is observed initially, but the jet velocity decreases as the Mach ring disappears during the APC inner flame extinguishing process. Through this study, the actual spraying and combustion process in APC is experimentally captured and revealed, which are an important contribution for APC optimization and development.

Fragmentation Characteristics of Bubbles in a Throttling Hole Pipe.

To enhance the performance of tubular microbubble generators, the Volume of Fluid (VOF) multiphase flow model in COMSOL Multiphysics was used to simulate the bubble fragmentation characteristics within a throttling hole microbubble generator. The effects of the inlet speed of the throttling hole pipe, the diameter of the throttling hole, and the length of the expansion section on bubble fragmentation performance were analyzed. The results indicated that an increase in the inlet speed of the throttling hole pipe gradually improved the bubble fragmentation performance. However, an increase in the throttling hole diameter significantly reduced the bubble fragmentation performance. Changes in the length of the expansion section had a minor impact on the bubble fragmentation performance. Experimental methods were used to verify the characteristics of bubble fragmentation, and it was found that the simulation and experimental results were consistent. This provides a theoretical basis and practical guidance for the design optimization of tubular microbubble generators.

Large-stroke and high-precision coaxial integrated macro-micro composite actuator based on VCM and GMA

A coaxially integrated macro-micro composite actuator (MMCA) with large stroke and high accuracy is proposed by combining a voice coil motor (VCM) with the giant magnetostrictive actuator (GMA). The magnetic circuit model of the macro-motion part is established based on the driving principle of VCM, and the multi-field coupling model of the micro-motion part is established based on the Jiles-Atherton model. The finite element method was used to analyze the relationship between displacement, output force, velocity, acceleration, and time of the macro-motion part under different currents, the magnetic flux density, output force, and displacement curves of the micro-motion part, and the mutual influence between the macro and micro motion parts were analyzed. The prototype of the MMCA was developed, and an experimental test platform was built. The results show that the MMCA macro-motion displacement curve can fit the simulation curve well during open-loop positioning, and when the current size of the input macro-motion coil is 4 A, the experimental curve of the MMCA is the most consistent with the simulation curve. When closed-loop control, the motion curve of the drive can well follow the set displacement curve, in which the maximum stroke of the prototype developed is 50 mm, the positioning error of the macro-motion part is less than 20 μm, the maximum stroke of the micro-motion part is 40 μm, and the overall positioning accuracy of the MMCA is 0.14 μm. The research results provide a new idea and theoretical basis for further optimization and development of precision positioning platform with high precision and large stroke.

Study on the Multiphase Flow Behavior in Jet Pump Drainage and Natural Gas Hydrate Production Wells with Combined Depressurization and Thermal Stimulation Method

Natural gas hydrate (NGH) trials have been performed successfully with different development methods and gas recovery drainage technologies. Multiphase flow in a wellbore and the drainage of natural gas hydrate are two important parts for its whole extraction process. Additionally, the choice of the drainage method is linked to the development method, making the drainage of NGH more complex. Jet pump drainage is usable for NGH production wells with the combined depressurization and thermal stimulation method. The objective of this study is to shed more light on the multiphase flow behavior in jet pump drainage and NGH production wells and put forward suggestions for adjusting heat injection parameters. The mechanism of jet pump drainage recovery technology for NGH wells was analyzed and its applicability to NGH development by the combined depressurization and thermal stimulation method was demonstrated. In addition, multiphase flow models of tubing and annulus were established, respectively, for the phenomenon of the countercurrent flow of heat exchange in the process of jet pump drainage and gas production, and the corresponding multiphase flow laws were derived. On the basis of these studies, sensitivity analysis and the optimization of thermal stimulation parameters were conducted. It is demonstrated that jet pump drainage gas recovery technology is feasible for the development of onshore NGH with the combined depressurization and thermal stimulation method. The laws of multiphase flow in the tubing and annulus of jet pump drainage and NGH production wells were disclosed in this study. Numerical simulation results show that the temperature and pressure profiles along the wellbore of jet pump drainage and NGH production wells during the drainage recovery process are affected by injection conditions. Increasing injection rate and injection temperature can both improve the effect of heat injection and reduce the hydrate reformation risk in the bottom of the annulus. This study offers a theoretical basis and technical support for production optimization and hydrate prevention and control in the wellbore of jet pump drainage and NGH production wells.

Research on data analysis method of oscillating water column wave energy converters

Abstract Taking the floating oscillating water column central tube wave energy converters (OWC WECs) as the research goal, the Fourier transform (FFT), and the ensemble empirical mode decomposition method (EEMD) were used to statistically analyze the wave height, motion acceleration, velocity and displacement of the device in the physical model test from the perspective of a frequency domain. Through the Fourier transform, the energy spectrum of the incident wave and the motion of the WEC is obtained, and it is found that the peak frequency of the two is the same, that is, the period is 1.138s, but the peak energy of the former is slightly greater than that of the latter. Through the ensemble empirical mode decomposition method, the 1-8 intrinsic mode functions of the incident wave and the displacement of the device are obtained, which shows that the device efficiently captures the dominant frequency wave in the incident wave, that is, the wave height is 0.0628m, the period is 1.1s, and the motion displacement of the vertical direction obtained by the device is 0.0585mm, and the period is 1.1119s. At the same time, it absorbs low-frequency, long-period reflected waves in the pool. The analysis results of the two methods are highly consistent, and the OWC WEC shows good hydrodynamic performance, with efficient wave trapping ability and fast wave responsability. This paper’s research methods and results provide a basis for the later optimization of the device and a new idea for the data processing method of the WECs.

An improved peridynamics topology optimization formulation for compliance minimization

This work proposes an improved peridynamics density-based topology optimization framework for compliance minimization. One of the main advantages of using a peridynamics discretization relies in the fact that it provides a consistent regularization of classical continuum mechanics into a nonlocal continuum, thus containing an inherent length scale called the horizon. Furthermore, this reformulation allows for discontinuities and is highly suitable for treating fracture and crack propagation. Partial differential equations are rewritten as integrodifferential equations and its numerical implementation can be straightforwardly done using meshfree collocation, inheriting its advantages. In the optimization formulation, Solid Isotropic Material with Penalization (SIMP) is used as interpolation for the design variables. To improve the peridynamic formulation and to evaluate the objective function in a energetically consistent manner, surface correction is implemented. Moreover, a detailed sensitivity analysis reveals an analytical expression for the objective function derivatives, different from an expression commonly used in the literature, providing an important basis for gradient-based topology optimization with peridynamics. The proposed implementation is studied with two examples illustrating different characteristics of this framework. The analytical expression for the sensitivities is validated against a reference solution, providing an improvement over the referred expression in the literature. Also, the effect of using the surface correction is evidenced. An extensive analysis of the horizon size and sensitivity filter radius indicates that the current method is mesh-independent, i.e. a sensitivity filter is redundant since peridynamics intrinsically filters length scales with the horizon. Different optimization methods are also tested for uncracked and cracked structures, demonstrating the capabilities and robustness of the proposed framework.

Line optimization of multi-beam sonar sounding technology in ocean surveying and mapping

Abstract In this paper, the problem of line optimization existing in the practical application of multi-beam sonar-sounding technology is studied. Firstly, by analyzing the working principle of multi-beam sonar, the multi-beam coverage width model and the overlap rate model between adjacent strips are established considering the slope of seabed terrain. Then, a more general parameterized multi-beam coverage width formula with an adjustable azimuth angle of the line is derived under three-dimensional space coordinates. Then, the minimum total line length is defined as the objective function, and the constraint conditions of overlap rate and complete coverage are added to establish the mathematical model of line planning. Then, an iterative algorithm is designed to quickly determine the line spacing, and an improved particle swarm optimization algorithm, including a trigonometric function change learning factor, is used to search for the optimal line layout. Finally, the simulation results show that the optimized scheme can reduce the total line length by 2% compared with the unoptimized line layout, which verifies the effectiveness of the established model and algorithm. This study provides a theoretical basis for navigation planning and shipboard system optimization of multi-beam sonar survey. Subsequent work taking into account the influence of complex sea conditions, efforts were made to expand the model’s applicability.

Multiphysics Coupling Simulation of Off-Axis Integrated Cavity Optical Sensing System

The optical properties of an off-axis integrated cavity system are influenced by both structural deformation and thermal deformation. In this paper, the finite element simulation and analysis software COMSOL multiphysics was used to numerically simulate the optical system. By coupling geometric optics, solid mechanics, and solid heat transfer and conducting parametric temperature scanning, a multiphysics simulation of the off-axis integrated cavity optical sensing system was achieved. The effects of different temperature conditions on the stress field, displacement field, and optical mirrors were analyzed, and changes in optical properties were assessed using ray trajectories and point diagrams. Additionally, optical simulation software was used to simulate and optimize the experimental optical path, obtaining the distribution of light spots on the detector surface. This provides a theoretical basis for the subsequent optimization of the off-axis integrated cavity optical system.

Fully Flexible Molecular Alignment Enables Accurate Ligand Structure Modeling.

Accurate protein-ligand binding poses are the prerequisites of structure-based binding affinity prediction and provide the structural basis for in-depth lead optimization in small molecule drug design. However, it is challenging to provide reasonable predictions of binding poses for different molecules due to the complexity and diversity of the chemical space of small molecules. Similarity-based molecular alignment techniques can effectively narrow the search range, as structurally similar molecules are likely to have similar binding modes, with higher similarity usually correlated to higher success rates. However, molecular similarity is not consistently high because molecules often require changes to achieve specific purposes, leading to reduced alignment precision. To address this issue, we propose a new alignment method─Z-align. This method uses topological structural information as a criterion for evaluating similarity, reducing the reliance on molecular fingerprint similarity. Our method has achieved success rates significantly higher than those of other methods at moderate levels of similarity. Additionally, our approach can comprehensively and flexibly optimize bond lengths and angles of molecules, maintaining a high accuracy even when dealing with larger molecules. Consequently, our proposed solution helps in achieving more accurate binding poses in protein-ligand docking problems, facilitating the development of small molecule drugs. Z-align is freely available as a web server at https://cloud.zelixir.com/zalign/home.

Hyperparameter optimization of orthogonal functions in the numerical solution of differential equations

Numerical methods for solving differential equations often rely on the expansion of the approximate solution using basis functions. The choice of an appropriate basis function plays a crucial role in enhancing the accuracy of the solution. In this study, our aim is to develop algorithms that can identify an optimal basis function for any given differential equation. To achieve this, we explore fractional rational Jacobi functions as a versatile basis, incorporating hyperparameters related to rational mappings, Jacobi polynomial parameters, and fractional components. Our research develops hyperparameter optimization algorithms, including parallel grid search, parallel random search, Bayesian optimization, and parallel genetic algorithms. To evaluate the impact of each hyperparameter on the accuracy of the solution, we analyze two benchmark problems on a semi‐infinite domain: Volterra's population model and Kidder's equation. We achieve improved convergence and accuracy by judiciously constraining the ranges of the hyperparameters through a combination of random search and genetic algorithms. Notably, our findings demonstrate that the genetic algorithm consistently outperforms other approaches, yielding superior hyperparameter values that significantly enhance the quality of the solution, surpassing state‐of‐the‐art results.

Investigation into Antioxidant Mechanism of Lycium barbarum Extract in Carbendazim-Induced PC12 Cell Injury Model through Transcriptomics and Metabolomics Analyses.

Lycium barbarum L., an important functional food in China, has antioxidant and antiaging activity. However, the exact antioxidant activity mechanism of Lycium barbarum extracts (LBE) is not well understood. Therefore, a carbendazim (CBZ)-induced PC12 cell injury model was constructed and vitrificated to study the antioxidant activity of fresh LBE on the basis of extraction parameter optimization via the full factorial design of experiments (DOE) method. The results showed that the pretreatment of PC12 cells with LBE could reduce the reactive oxygen species (ROS) level by 14.6% and inhibited the mitochondrial membrane potential (MMP) decline by 12.0%. Furthermore, the integrated analysis revealed that LBE played an antioxidant role by activating oxidative phosphorylation (OXPHOS) and restoring MMP, maintaining the tricarboxylic acid (TCA) cycle stability, and regulating the GSH metabolic pathway. The results of the present study provide new ideas for the understanding of the antioxidant function of LBE from a global perspective.

Experimental study on dynamic adsorption properties of methylene blue onto coal-based activated carbon using a hydrocyclone

To address the issues of low adsorption efficiency of activated carbon in dyeing wastewater treatment, a dynamic adsorption process using activated carbon for wastewater treatment was proposed. A hydrocyclone was used as the carrier, and the adsorbent separation process was integrated into the same single device. Methylene blue (MB) was used to simulate printing and dyeing wastewater. The effects of initial concentration of MB solution, ratio of activated carbon quality to wastewater flow, and adsorption temperature on the adsorption efficiency were investigated. The results showed that the optimal adsorption efficiency of MB by activated carbon was 95.2 % when the initial concentration of MB solution was 12 mg/L, the ratio of activated carbon quality to wastewater flow was 0.5 mg/mL, and the adsorption temperature of MB solution was 44.5 °C. In addition, compared with the water bath oscillation method, the removal efficiency of MB was increased by 731 % under the same adsorption conditions. The research shows that it is feasible to treat printing and dyeing wastewater by using a hydrocyclone to enhance activated carbon adsorption. The research aims to provide a practical basis for future optimization of the structure and operation parameters of hydrocyclone and to reveal their wide application prospects.

N-acylbenzimidazoles as selective Acylators of the catalytic cystein of the coronavirus 3CL protease

The 3CL protease (3CLpro, Mpro) plays a key role in the replication of the SARS-CoV-2 and was validated as therapeutic target by the development and approval of specific antiviral drugs (nirmatrelvir, ensitrelvir), inhibitors of this protease. Moreover, its high conservation within the coronavirus family renders it an attractive therapeutic target for the development of anti-coronavirus compounds with broad spectrum activity to control COVID-19 and future coronavirus diseases. Here we report on the design, synthesis and structure-activity relationships of a new series of small covalent reversible inhibitors of the SARS-CoV-2 3CLpro. As elucidated thanks to the X-Ray structure of some inhibitors with the 3CLpro, the mode of inhibition involves acylation of the thiol of the catalytic cysteine. The synthesis of 60 analogs led to the identification of compound 56 that inhibits the SARS-CoV-2 3CLpro with high potency (IC50 = 70 nM) and displays antiviral activity in cells (EC50 = 3.1 μM). Notably, compound 56 inhibits the 3CLpro of three other human coronaviruses and exhibit a good selectivity against two human cysteine proteases. These results demonstrate the potential of this electrophilic N-acylbenzimidazole series as a basis for further optimization.

Synergistic Effect of Microconvex Texture and Particle Medium on the Tribological Property of the Rubber Sliding Interface.

In this study, we examined how surface topography and particle medium interact to affect the tribological performance of rubber sliding interfaces, uncovering the mechanisms of particle lubrication under various conditions. We found that microtextured surfaces, created using a mold transfer method, modestly reduced the friction coefficient of rubber under both dry and lubricated states, primarily by altering the real contact area. Additionally, the presence of different microconvex textures on the surface topography significantly influenced rubber's tribological properties. Our three-dimensional morphological analysis revealed that microtextured rubber surfaces with higher Sa, Sku, and Sal and lower Str values consistently showed lower friction coefficients during sliding. The friction mechanism was attributed to the combined effects of the material properties, surface topography, and contact area. With the addition of a particle medium, the dry friction coefficient of the rubber interface decreased but exhibited an initial increase, followed by a decrease with increasing particle diameter. When particles were mixed with a water-based cutting fluid, the concentration, diameter, and wettability of the particles significantly impacted the tribological properties due to the synergistic effects of surface topography and particle lubrication. This work enhances our understanding of tribological control for viscoelastic materials through surface design, providing a theoretical basis for the tribological optimization of rubber surfaces.

Bidirectional Power Sharing Control with Current-Fed Dual Active Bridge Converter: Hybrid Technique

This paper proposes a hybrid method for controlling bidirectional power sharing among grids and dc microgrids. The interlinking converter (IC) and current-fed dual active bridge (CFDAB) converters connect the grid and dc microgrid. The proposed approach is the joint implementation of golden eagle optimization and radial basis function neural network, hence, named the GEO-RBFNN approach. The bidirectional power distribution control signal analysis significantly diminishes power distribution deviation and circulating current. This power-sharing control system neglects the need for battery backup since the required amount of power is brought from or handled by an AC utility. The dc microgrid incorporates the dc to dc converter, from which boost converters use sources and buckconverters use supply loads. The control of bidirectional power sharing among the microgrids and the grid is attained with the aid of the GEO-RBFNN algorithm. It delivers certain aids, like higher predictability, highly reliable results, high speed, and less complexity. The outcome is investigated on the MATLAB platform. According to the comparison outcome, the proposed method delivers higher performance than the existing system. The proposed method gives higher comparison outcomes than the current methods, which can conquer the associated problems. The proposed method-based settling time is 3.356 ms, and the rise time is 1.555 ms. The efficiency based on the proposed method is 97.54%, which is higher than the existing methods.