Symmetry

15 pages, 3695 KiB

Open AccessArticle

Lepton Flavour Universality in Rare B Decays

by Paula Álvarez Cartelle and Richard Morgan Williams

Symmetry 2024, 16(7), 822; https://doi.org/10.3390/sym16070822 (registering DOI) - 30 Jun 2024

Tests of lepton flavour universality in rare decays of b hadrons mediated by flavour-changing neutral-current transitions constitute sensitive probes for physics beyond the standard model. In recent years, such tests have become increasingly precise and have attracted significant theoretical and experimental attention. In [...] Read more.

Tests of lepton flavour universality in rare decays of b hadrons mediated by flavour-changing neutral-current transitions constitute sensitive probes for physics beyond the standard model. In recent years, such tests have become increasingly precise and have attracted significant theoretical and experimental attention. In this article, we review the status of searches for lepton flavour universality violations in these processes and discuss prospects for future measurements at various facilities. Full article

(This article belongs to the Special Issue Symmetries and Anomalies in Flavour Physics)

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20 pages, 1489 KiB

Open AccessArticle

Portfolio Optimization with Multi-Trend Objective and Accelerated Quasi-Newton Method

by Caiming Lin and **nyi He

Symmetry 2024, 16(7), 821; https://doi.org/10.3390/sym16070821 (registering DOI) - 30 Jun 2024

Abstract

We propose a portfolio optimization method with a multi-trend objective and an accelerated quasi-Newton method (MTO-AQNM). It leverages a BFGS-based quasi-Newton algorithm and incorporates an

ℓ^{1}

regularization term and the self-funding constraint. The MTO is designed to identify multiple trend reversals. Different [...] Read more.

We propose a portfolio optimization method with a multi-trend objective and an accelerated quasi-Newton method (MTO-AQNM). It leverages a BFGS-based quasi-Newton algorithm and incorporates an

ℓ^{1}

regularization term and the self-funding constraint. The MTO is designed to identify multiple trend reversals. Different trend reversals are asymmetric, and we hoped to extract rich and effective information from them. The AQNM adopts the BFGS method with the Wolfe conditions, which reduces computational complexity and improves convergence speed. We wanted to evaluate the performance of our algorithm through financial markets that were asymmetric in all respects. To this end, we conducted comprehensive experimental approaches on six benchmark data sets of real-world financial markets that were asymmetric in time, frequency, and asset type. Our method demonstrated superior performance over other state-of-the-art competitors across several mainstream evaluation metrics. Full article

(This article belongs to the Special Issue Symmetry or Asymmetry in Machine Learning)

13 pages, 3442 KiB

Open AccessArticle

Design of a Photonic Crystal Exclusive-OR Gate Using Recurrent Neural Networks

by Pouya Karami, Salah I. Yahya, Muhammad Akmal Chaudhary, Maher Assaad, Saeed Roshani, Fawwaz Hazzazi, Fariborz Parandin and Sobhan Roshani

Symmetry 2024, 16(7), 820; https://doi.org/10.3390/sym16070820 (registering DOI) - 30 Jun 2024

Abstract

In this paper, a novel approach to design a photonic crystal exclusive-OR (XOR) gate with high performance using recurrent neural network (RNN) is proposed, integrating the principles of symmetry and asymmetry inherent in photonic structures. The proposed model realizes the nonlinearities and dispersion [...] Read more.

In this paper, a novel approach to design a photonic crystal exclusive-OR (XOR) gate with high performance using recurrent neural network (RNN) is proposed, integrating the principles of symmetry and asymmetry inherent in photonic structures. The proposed model realizes the nonlinearities and dispersion properties in photonic systems, optimizing the waveguide paths and interference patterns to improve the performance of the logic gate. Simulation results demonstrate that the presented RNN design not only achieves high fidelity in the logical operation but also significantly enhances the functionality of the all-optical gate. This integration of machine learning with photonic crystal technology opens a new era for develo** compact, energy-efficient photonic circuits for high-speed optical computing. Finally, the performance of the designed all-optical gate is compared with other related methods, which shows that the proposed gate outperforms other works. The results show that the obtained output power of the proposed all-optical XOR gate is 0, 0.813, 0.82, and 1 × 10⁻⁷ in the logical states. Full article

(This article belongs to the Section Computer)

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16 pages, 2405 KiB

Open AccessArticle

High Resilient Asymmetry and Anomaly Detection Based on Data Causality

by Zhiyong Hao, Chenhao Yu, Junyi Zhu and Leilei Chang

Symmetry 2024, 16(7), 819; https://doi.org/10.3390/sym16070819 (registering DOI) - 29 Jun 2024

Abstract

In the tunnel construction practice, multiple buildings’ tilt rate data are collected. In this study, data causality is defined to reflect the causal relation between the input and output of the building tilt rate detection data. Upon defining and calculating the data causality, [...] Read more.

In the tunnel construction practice, multiple buildings’ tilt rate data are collected. In this study, data causality is defined to reflect the causal relation between the input and output of the building tilt rate detection data. Upon defining and calculating the data causality, a new high resilient causality detection (HiReCau) method is proposed for abnormal building tilt rate detection. A numerical case and another practical case are studied for validation purposes. The case study results show that the proposed HiReCau method can accurately detect high-causality data and low-causality data among the building tilt rate detection data and produces superior results compared with the direct adoption of a machine learning approach. Furthermore, the resilience of HiReCau is validated by investigations testing varied levels of additional low-causality data in the training dataset. Presently, HiReCau is limited to handling problems with a single output. Furthermore, only the back-propagation neural network (BPNN) is tested as the baseline model and there is also room to further expand the data size. The proposed approach is versatile and able to be adjusted to handle fault diagnosis and safety assessment problems in varied theoretical and engineering backgrounds. Full article

(This article belongs to the Special Issue Applications Based on Symmetry/Asymmetry in Data Mining)

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14 pages, 861 KiB

Open AccessArticle

Crystallographic Quaternions

by Andrzej Katrusiak and Stiv Llenga

Symmetry 2024, 16(7), 818; https://doi.org/10.3390/sym16070818 (registering DOI) - 29 Jun 2024

Abstract

Abstract: Symmetry transformations in crystallography are traditionally represented as equations and matrices, which can be suitable both for orthonormal and crystal reference systems. Quaternion representations, easily constructed for any orientations of symmetry operations, owing to the vector structure based on the direction of [...] Read more.

Abstract: Symmetry transformations in crystallography are traditionally represented as equations and matrices, which can be suitable both for orthonormal and crystal reference systems. Quaternion representations, easily constructed for any orientations of symmetry operations, owing to the vector structure based on the direction of the rotation axes or of the normal vectors to the mirror plane, are known to be advantageous for optimizing numerical computing. However, quaternions are described in Cartesian coordinates only. Here, we present the quaternion representations of crystallographic point-group symmetry operations for the crystallographic reference coordinates in triclinic, monoclinic, orthorhombic, tetragonal, cubic and trigonal (in rhombohedral setting) systems. For these systems, all symmetry operations have been listed and their applications exemplified. Owing to their concise form, quaternions can be used as the symbols of symmetry operations, which contain information about both the orientation and the rotation angle. The shortcomings of quaternions, including different actions for rotations and improper symmetry operations, as well as inadequate representation of the point symmetry in the hexagonal setting, have been discussed. Full article

(This article belongs to the Special Issue Feature Papers in Section "Engineering and Materials" 2024)

16 pages, 280 KiB

Open AccessArticle

New Monotonic Properties for Solutions of Odd-Order Advanced Nonlinear Differential Equations

by Asma Al-Jaser, Belgees Qaraad, Faizah Alharbi and Stefano Serra-Capizzano

Symmetry 2024, 16(7), 817; https://doi.org/10.3390/sym16070817 (registering DOI) - 29 Jun 2024

Abstract

The present paper studies the asymptotic and oscillatory properties of solutions of odd-order differential equations with advanced arguments and in a noncanonical case. By providing new and effective relationships between the corresponding function and the solution, we present strict and new criteria for [...] Read more.

The present paper studies the asymptotic and oscillatory properties of solutions of odd-order differential equations with advanced arguments and in a noncanonical case. By providing new and effective relationships between the corresponding function and the solution, we present strict and new criteria for testing whether the studied equation exhibits oscillatory behavior or converges to zero. Our results contribute uniquely to oscillation theory by presenting some theorems that improve and expand upon the results found in the existing literature. We also provide an example to corroborate the validity of our proposed criteria. Full article

(This article belongs to the Special Issue Symmetry in Nonlinear Equations: Mathematical Models, Methods and Applications Ⅱ)

19 pages, 423 KiB

Open AccessArticle

Quantum Gravity Corrections to the Inflationary Spectrum in a Bohmian Approach

by Giulia Maniccia and Giovanni Montani

Symmetry 2024, 16(7), 816; https://doi.org/10.3390/sym16070816 (registering DOI) - 29 Jun 2024

Abstract

A precise interpretation of the universe wave function is forbidden in the spirit of the Copenhagen School since a precise notion of measure operation cannot be satisfactorily defined. Here, we propose a Bohmian interpretation of the isotropic universe quantum dynamics, in which the [...] Read more.

A precise interpretation of the universe wave function is forbidden in the spirit of the Copenhagen School since a precise notion of measure operation cannot be satisfactorily defined. Here, we propose a Bohmian interpretation of the isotropic universe quantum dynamics, in which the Hamilton–Jacobi equation is restated by including quantum corrections, which lead to a classical trajectory containing effects of order

ℏ^{2}

. This solution is then used to determine the spectrum of gauge-invariant quantum fluctuations living on the obtained background model. The analysis is performed adopting the wave function approach to describe the fluctuation dynamics, which gives a time-dependent harmonic oscillator for each Fourier mode and whose frequency is affected by the

ℏ^{2}

corrections. The properties of the emerging spectrum are discussed, outlining the modification induced with respect to the scale-invariant result, and the hierarchy of the spectral index running is discussed. Full article

(This article belongs to the Section Physics)

18 pages, 1039 KiB

Open AccessArticle

The Reliability and Availability Analysis of a Single-Unit System under the Influence of Random Shocks and the Variation in Demand from Production with Erlang Distribution

by Zienab M. Hussien and Mohamed S. El-Sherbeny

Symmetry 2024, 16(7), 815; https://doi.org/10.3390/sym16070815 (registering DOI) - 28 Jun 2024

Abstract

This study evaluates the reliability measures for a system consisting of a single unit that is subject to random shocks at random times with mismatches between demand and production. The system may sometimes be subject to random shocks leading to a system failure [...] Read more.

This study evaluates the reliability measures for a system consisting of a single unit that is subject to random shocks at random times with mismatches between demand and production. The system may sometimes be subject to random shocks leading to a system failure with probability p. The system may also fail completely for various reasons other than shocks. The unit is serviced by a technician if it is affected by a shock. However, the system may fail during operation for various other reasons, such as a programming error, human error, operational continuity and stress, and weather conditions. A single technician immediately repairs or maintains the failed unit. The system is in an operational state when there is demand or in an idle state when there is no demand. The distributions of all times in this system follow a negative exponential, while the time to repair follows a two-stage Erlang distribution. The expressions for the reliability metrics are obtained as functions of time using the Laplace transform and the supplementary variables technique. Sensitivity and relative sensitivity analyses were also performed for the system parameters. Finally, the efficiency of the system is illustrated using numerical examples. Full article

(This article belongs to the Special Issue Advances and Applications of Uncertainty Theory in Reliability and Systems Engineering)

24 pages, 352 KiB

Open AccessFeature PaperArticle

A Factory of Fractional Derivatives

by Manuel D. Ortigueira

Symmetry 2024, 16(7), 814; https://doi.org/10.3390/sym16070814 (registering DOI) - 28 Jun 2024

Abstract

This paper aims to demonstrate that, beyond the small world of Riemann–Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to different paths taken. The notions of [...] Read more.

This paper aims to demonstrate that, beyond the small world of Riemann–Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to different paths taken. The notions of time and scale sequences are introduced, and general associated basic derivatives, namely, right/stretching and left/shrinking, are defined. A general framework for fractional derivative definitions is reviewed and applied to obtain both known and new fractional-order derivatives. Several fractional derivatives are considered, mainly Liouville, Hadamard, Euler, bilinear, tempered, q-derivative, and Hahn. Full article

(This article belongs to the Section Mathematics)

13 pages, 444 KiB

Open AccessArticle

Knowledge-Guided Parallel Hybrid Local Search Algorithm for Solving Time-Dependent Agile Satellite Scheduling Problems

by Yuyuan Shan, Xue** Wang, Shi Cheng, Mingming Zhang and Lining **ng

Symmetry 2024, 16(7), 813; https://doi.org/10.3390/sym16070813 (registering DOI) - 28 Jun 2024

Abstract

As satellite capabilities have evolved and new observation requirements have emerged, satellites have become essential tools in disaster relief, emergency monitoring, and other fields. However, the efficiency of satellite scheduling still needs to be enhanced. Learning and optimization are symmetrical processes of solving [...] Read more.

As satellite capabilities have evolved and new observation requirements have emerged, satellites have become essential tools in disaster relief, emergency monitoring, and other fields. However, the efficiency of satellite scheduling still needs to be enhanced. Learning and optimization are symmetrical processes of solving problems. Learning problem knowledge could provide efficient optimization strategies for solving problems. A knowledge-guided parallel hybrid local search algorithm (KG-PHLS) is proposed in this paper to solve time-dependent agile Earth observation satellite (AEOS) scheduling problems more efficiently. Firstly, the algorithm uses heuristic algorithms to generate initial solutions. Secondly, a knowledge-based parallel hybrid local search algorithm is employed to solve the problem in parallel. Meanwhile, data mining techniques are used to extract knowledge to guide the construction of new solutions. Finally, the proposed algorithm has demonstrated superior efficiency and computation time through simulations across multiple scenarios. Notably, compared to benchmark algorithms, the algorithm improves overall efficiency by approximately 7.4% and 8.9% in large-scale data scenarios while requiring only about 60.66% and 31.89% of the computation time of classic algorithms. Moreover, the proposed algorithm exhibits scalability to larger problem sizes. Full article

(This article belongs to the Special Issue Symmetric Machine Learning Method Enhanced by Evolutionary Computation and Its Applications in Big Data Analytics II)

17 pages, 2103 KiB

Open AccessArticle

Structural Study of Four-Layered Cylindrical Shell Comprising Ring Support

by Madiha Ghamkhar, Ahmad N. Al-Kenani and Naveed Hussain

Symmetry 2024, 16(7), 812; https://doi.org/10.3390/sym16070812 (registering DOI) - 28 Jun 2024

Abstract

In this work, the vibration analysis of a layered, cylinder-shaped shell is undertaken. The structure of the shell layers is composed of functionally graded and isotropic materials. The vibrations of four-layered cylindrical shells with a ring support along the axial direction are investigated [...] Read more.

In this work, the vibration analysis of a layered, cylinder-shaped shell is undertaken. The structure of the shell layers is composed of functionally graded and isotropic materials. The vibrations of four-layered cylindrical shells with a ring support along the axial direction are investigated in this research. The two internal layers are composed of isotropic materials, and the external two layers are composed of functionally graded materials. The outer functionally graded material layers considered are stainless steel, zirconia, and nickel. The inner two isotropic layers considered are aluminum and stainless steel. The shell frequency equation is acquired by employing the Rayleigh–Ritz method under the shell theory of Sanders. The trigonometric volume fraction law is used to sort the functionally graded material composition of the FGM layers. The natural frequencies are attained under two boundary conditions, namely simply supported–simply supported and clamped–clamped. Full article

(This article belongs to the Special Issue Applied Mechanics, Engineering and Modeling - Volume II)

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16 pages, 2975 KiB

Open AccessArticle

Asymmetry Considerations in Constructing Control Charts: When Symmetry Is Not the Norm

by Ran Etgar

Symmetry 2024, 16(7), 811; https://doi.org/10.3390/sym16070811 - 28 Jun 2024

Abstract

Control charts (esp.

\bar{X}

-chart) are proven and useful tools to preserve process alignment with its design mean. The control charts’ limits are designed symmetrically around the process’s mean. The assumption of symmetry is justifiable when assuming that the measurements are infinite. [...] Read more.

Control charts (esp.

\bar{X}

-chart) are proven and useful tools to preserve process alignment with its design mean. The control charts’ limits are designed symmetrically around the process’s mean. The assumption of symmetry is justifiable when assuming that the measurements are infinite. Typically, these assumptions are warranted since the measuring resolution is significantly (by orders of magnitude) lower than the deviation of the controlled process. However, when the measuring device has a resolution of the same order of magnitude as the standard deviation of the controlled process, the symmetrical nature is no longer justified. In low-resolution measurement process control, symmetry is not the norm and both these control limits should be built asymmetrically. To help remedy this issue, this article explores the asymmetrical nature of the low-resolution measurement and suggests a new (asymmetric) control limit based on false-alarm-required probabilities. This represents a novel approach to the problem Full article

(This article belongs to the Section Engineering and Materials)

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11 pages, 2816 KiB

Open AccessArticle

Energy Efficiency Measurement of Mechanical Crushing Based on Non-Contact Identification Method

by **aoquan Lu, Meimei Duan, Huiling Su, Bo Li and Ying Liu

Symmetry 2024, 16(7), 810; https://doi.org/10.3390/sym16070810 - 28 Jun 2024

Abstract

The efficiency of mechanical crushing is a key metric for evaluating machinery performance. However, traditional contact-based methods for measuring this efficiency are unable to provide real-time data monitoring and can potentially disrupt the production process. In this paper, we introduce a non-contact measurement [...] Read more.

The efficiency of mechanical crushing is a key metric for evaluating machinery performance. However, traditional contact-based methods for measuring this efficiency are unable to provide real-time data monitoring and can potentially disrupt the production process. In this paper, we introduce a non-contact measurement technique for mechanical crushing efficiency based on deep learning algorithms. This technique utilizes close-range imaging equipment to capture images of crushed particles and employs deeply trained algorithmic programs rooted in symmetrical logical structures to extract statistical data on particle size. Additionally, we establish a relationship between particle size and crushing energy through experimental analysis, enabling the calculation of crushing efficiency data. Taking cement crushing equipment as an example, we apply this non-contact measurement technique to inspect cement particles of different sizes. Using deep learning algorithms, we automatically categorize and summarize the particle size ranges of cement particles. The results demonstrate that the crushing efficiencies of ore crushing particles, raw material crushing particles, and cement crushing particles can respectively reach 80.7%, 70.15%, and 80.27%, which exhibit a high degree of consistency with the rated value of the samples. The method proposed in this paper holds significant importance for energy efficiency monitoring in industries that require mechanical crushing. Full article

(This article belongs to the Special Issue Symmetry in the Mechanical Behavior of Materials)

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10 pages, 724 KiB

Open AccessArticle

Minimization over Nonconvex Sets

by José Antonio Vilchez Membrilla, Víctor Salas Moreno, Soledad Moreno-Pulido, Alberto Sánchez-Alzola, Clemente Cobos Sánchez and Francisco Javier García-Pacheco

Symmetry 2024, 16(7), 809; https://doi.org/10.3390/sym16070809 - 27 Jun 2024

Abstract

Minimum norm problems consist of finding the distance of a closed subset of a normed space to the origin. Usually, the given closed subset is also asked to be convex, thus resulting in a convex minimum norm problem. There are plenty of techniques [...] Read more.

Minimum norm problems consist of finding the distance of a closed subset of a normed space to the origin. Usually, the given closed subset is also asked to be convex, thus resulting in a convex minimum norm problem. There are plenty of techniques and algorithms to compute the distance of a closed convex set to the origin, which mostly exist in the Hilbert space setting. In this manuscript, we consider nonconvex minimum norm problems that arise from Bioengineering and reformulate them in such a way that the solution to their reformulation is already known. In particular, we tackle the problem of

min ∥ x ∥

subject to

∥ R_{k} (x) ∥ \geq a_{k}

for

k = 1, \dots, l

, where

x \in X

and

R_{k} : X \to Y

are continuous linear operators between real normed spaces

X, Y

, and

a_{k} > 0

for

k = 1, \dots, l

. Notice that the region of constraints of the previous problem is neither convex nor balanced. However, it is additively symmetric, which is also the case for the objective function, due to the properties satisfied by norms, which makes possible the analytic resolution of such a nonconvex minimization. The recent literature shows that the design of optimal coils for electronics applications can be achieved by solving problems like this. However, in this work, we apply our analytical solutions to design an optimal coil for an electromagnetic sensor. Full article

(This article belongs to the Section Mathematics)

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22 pages, 6275 KiB

Open AccessReview

Type-B Energetic Processes: Their Identification and Implications

by James Weifu Lee

Symmetry 2024, 16(7), 808; https://doi.org/10.3390/sym16070808 - 27 Jun 2024

Abstract

We have now identified two thermodynamically distinct types (A and B) of energetic processes naturally occurring on Earth. Type-A energy processes, such as classical heat engines, apparently well follow the second law of thermodynamics; Type-B energy processes, such as the newly discovered thermotrophic [...] Read more.

We have now identified two thermodynamically distinct types (A and B) of energetic processes naturally occurring on Earth. Type-A energy processes, such as classical heat engines, apparently well follow the second law of thermodynamics; Type-B energy processes, such as the newly discovered thermotrophic function that isothermally utilizes environmental heat energy to perform useful work in driving ATP synthesis, follow the first law of thermodynamics (conservation of mass and energy) but do not have to be constrained by the second law, owing to their special asymmetric functions. Several Type-B energy processes such as asymmetric function-gated isothermal electricity production and epicatalysis have been created through human efforts. The innovative efforts in Type-B processes to enable isothermally utilizing endless environmental heat energy could help to liberate all peoples from their dependence on fossil fuel energy, thus hel** to reduce greenhouse gas CO₂ emissions and control climate change towards a sustainable future for humanity on Earth. In addition to the needed support for further research, development, and commercialization efforts, currently, better messaging and education on Type-B energetic processes are also highly needed to achieve the mission. Full article

(This article belongs to the Section Chemistry: Symmetry/Asymmetry)

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18 pages, 704 KiB

Open AccessArticle

Radial Oscillations of Strange Quark Stars Admixed with Dark Matter

by Yu Zhen, Ting-Ting Sun, **-Biao Wei, Zi-Yue Zheng and Huan Chen

Symmetry 2024, 16(7), 807; https://doi.org/10.3390/sym16070807 - 27 Jun 2024

Abstract

We investigate the equilibrium structure and radial oscillations of strange quark stars admixed with fermionic dark matter. For strange quark matter, we employ a stiff equation of state from a color-superconductivity improved bag model. For dark matter, we adopt the cold free Fermi [...] Read more.

We investigate the equilibrium structure and radial oscillations of strange quark stars admixed with fermionic dark matter. For strange quark matter, we employ a stiff equation of state from a color-superconductivity improved bag model. For dark matter, we adopt the cold free Fermi gas model. We rederive and numerically solve the radial oscillation equations of two-fluid stars based on general relativity, in which the dark matter and strange quark matter couple through gravity and oscillate with the same frequency. Our results show that the stellar maximum mass and radius are reduced by inclusion of dark matter. As to the fundamental mode of the radial oscillations, the frequency

f_{0}

is also reduced comparing to pure strange stars, and

f_{0}^{2}

reaches the zero point at the maximum stellar mass with

d M / d ϵ_{q, c} = 0

. Therefore, the stability criteria

f_{0}^{2} > 0

and

d M / d ϵ_{q, c} > 0

are consistent in our dark matter-mixed strange quark stars with a fixed fraction of dark matter. We also find a discontinuity of

f_{0}

as functions of the stellar mass, in contrast to the continuous function in pure strange stars. And it is also accompanied with discontinuity of the oscillation amplitudes as well as a discontinuous in-phase-to-out-phase transition between oscillations of dark matter and strange quark matter. Full article

(This article belongs to the Special Issue Symmetry in Hadron Physics)

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12 pages, 2061 KiB

Open AccessArticle

Optimal Harvesting Strategies for Timber and Non-Timber Forest Products with Nonlinear Harvesting Terms

by Yaning Zhang, Lina Hao and Shan Zhang

Symmetry 2024, 16(7), 806; https://doi.org/10.3390/sym16070806 - 27 Jun 2024

Abstract

Forest resources are renewable, and the rational exploitation and utilization of forest resources are not only conducive to sustainable development on a population scale, they can also lead to higher economic benefits. Based on the actual timber harvest problem, this paper establishes the [...] Read more.

Forest resources are renewable, and the rational exploitation and utilization of forest resources are not only conducive to sustainable development on a population scale, they can also lead to higher economic benefits. Based on the actual timber harvest problem, this paper establishes the joint harvest model of timber and non-timber with nonlinear harvest items. In the numerical simulation, by comparing the existing proportional harvest model, it is concluded that the optimal harvest strategy of nonlinear harvest items in this paper can obtain larger ecological benefits and be more conducive to the sustainable development of a population. Firstly, using the qualitative theory of ordinary differential equations, the dynamic behavior of the model is studied, and the existence and stability of the equilibrium point of the model are proven. Secondly, the optimal control solution is obtained by using the optimal control theory. Finally, the optimal harvesting strategy of timber and non-timber products is given based on the numerical simulation results, and a comparison of the effects of different parameters on the optimal harvest strategy, which provides a certain theoretical basis for the sustainable development of the ecological economy of forestry, is carried out. Full article

(This article belongs to the Special Issue Symmetry/Asymmetry of Differential Equations in Biomathematics)

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16 pages, 1690 KiB

Open AccessArticle

Cold Chain Logistics Center Layout Optimization Based on Improved Dung Beetle Algorithm

by **hui Li and Qing Zhou

Symmetry 2024, 16(7), 805; https://doi.org/10.3390/sym16070805 - 27 Jun 2024

Abstract

To reduce the impact of the cold chain logistics center layout on economic benefits, operating efficiency and carbon emissions, a layout optimization method is proposed based on the improved dung beetle algorithm. Firstly, based on the analysis of the relationship between logistics and [...] Read more.

To reduce the impact of the cold chain logistics center layout on economic benefits, operating efficiency and carbon emissions, a layout optimization method is proposed based on the improved dung beetle algorithm. Firstly, based on the analysis of the relationship between logistics and non-logistics, a multi-objective optimization model is established to minimize the total logistics cost, maximize the adjacency correlation and minimize the carbon emissions; secondly, based on the standard Dung Beetle Optimization (DBO) algorithm, in order to further improve the global exploration ability of the algorithm, Chebyshev chaotic map** and an adaptive Gaussian–Cauchy hybrid mutation disturbance strategy are introduced to improve the DBO (IDBO) algorithm; finally, taking an actual cold chain logistics center as an example, the DBO algorithm and the improved DBO algorithm are applied to optimize its layout, respectively. The results show that the total logistics cost after optimization of the IDBO algorithm is reduced by 25.54% compared with the original layout, the adjacency correlation is improved by 29.93%, and the carbon emission is reduced by 6.75%, verifying the effectiveness of the proposed method and providing a reference for the layout design of cold chain logistics centers. Full article

(This article belongs to the Special Issue Symmetry: Recent Developments in Engineering Science and Applications)

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21 pages, 3192 KiB

Open AccessArticle

Cutting-Edge Machine Learning Techniques for Accurate Prediction of Agglomeration Size in Water–Alumina Nanofluids

by Behzad Vaferi, Mohsen Dehbashi and Ali Hosin Alibak

Symmetry 2024, 16(7), 804; https://doi.org/10.3390/sym16070804 - 27 Jun 2024

Abstract

Nanoparticle agglomeration is one of the most problematic phenomena during nanofluid synthesis by a two-step procedure. Understanding and accurately estimating agglomeration size is crucial, as it significantly affects nanofluids’ properties, behavior, and successful applications. To the best of our knowledge, the literature has [...] Read more.

Nanoparticle agglomeration is one of the most problematic phenomena during nanofluid synthesis by a two-step procedure. Understanding and accurately estimating agglomeration size is crucial, as it significantly affects nanofluids’ properties, behavior, and successful applications. To the best of our knowledge, the literature has not yet applied machine learning methods to estimate alumina agglomeration size in water-based nanofluids. So, this research employs a range of machine learning models—Random Forest, Adaptive Boosting, Extra Trees, Categorical Boosting, and Multilayer Perceptron Neural Networks—to predict alumina agglomeration sizes in water-based nanofluids. To this end, a comprehensive experimental database, including 345 alumina agglomeration sizes in water-based nanofluids, compiled from 29 various sources from the literature, is utilized to train these models and monitor their generalization ability in the testing stage. The models estimate agglomeration size based on multiple factors: alumina concentration, ultrasonic time, power, frequency, temperature, surfactant type and concentration, and pH levels. The relevancy test based on the Pearson method clarifies that Al₂O₃ agglomeration size in water primarily depends on ultrasonic frequency, ultrasonic power, alumina concentration in water, and surfactant concentration. Comparative analyses based on numerical and graphical techniques reveal that the Categorical Boosting model surpasses others in accurately simulating this complex phenomenon. It effectively captures the intricate relationships between key features and alumina agglomeration size, achieving an average absolute relative deviation of 6.75%, a relative absolute error of 12.83%, and a correlation coefficient of 0.9762. Furthermore, applying the leverage method to the experimental data helps identify two problematic measurements within the database. These results validate the effectiveness of the Categorical Boosting model and contribute to the broader goal of enhancing our understanding and control of nanofluid properties, thereby aiding in improving their practical applications. Full article

(This article belongs to the Special Issue Machine Learning and Data Analysis II)

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