Journal Description
Symmetry
Symmetry
is an international, peer-reviewed, open access journal covering research on symmetry/asymmetry phenomena wherever they occur in all aspects of natural sciences. Symmetry is published monthly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), CAPlus / SciFinder, Inspec, Astrophysics Data System, and other databases.
- Journal Rank: JCR - Q2 (Multidisciplinary Sciences) / CiteScore - Q1 (General Mathematics); Q1 (Physics and Astronomy); Q1 (Computer Science)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 16.2 days after submission; acceptance to publication is undertaken in 3.5 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Testimonials: See what our editors and authors say about Symmetry.
Impact Factor:
2.7 (2022);
5-Year Impact Factor:
2.7 (2022)
Latest Articles
Control and Analysis of a Hybrid-Rotor Bearingless Switched Reluctance Motor with One-Phase Full-Period Suspension
Symmetry 2024, 16(3), 369; https://doi.org/10.3390/sym16030369 - 18 Mar 2024
Abstract
In the traditional control scheme of a 12/8-pole bearingless switched reluctance motor (BSRM), radial force and torque are usually controlled as a compromise due to the conflict between their effective output areas. Additionally, each phase requires individual power circuits and is excited in
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In the traditional control scheme of a 12/8-pole bearingless switched reluctance motor (BSRM), radial force and torque are usually controlled as a compromise due to the conflict between their effective output areas. Additionally, each phase requires individual power circuits and is excited in turn to produce a continuous levitation force, resulting in high power device requirements and high controller costs. This paper discusses a 12/8-pole single-winding hybrid-rotor bearingless switched reluctance motor (HBSRM) with a hybrid rotor consisting of cylindrical and salient-pole lamination segments. The asymmetric rotor of the HBSRM slightly increases the complexity of its structure and magnetic circuit, but makes it possible to generate the desired radial force at any rotor angular position. A control scheme for the HBSRM is developed to utilize the independent excitation of the four windings in one phase to generate the desired levitation force at any rotor angular position, and it requires only half the number of power circuits used in the conventional control scheme of a 12/8-pole single-winding BSRM. Different from the average torque chosen to be controlled in traditional methods, this scheme directly regulates the instantaneous total torque produced by all excited phases together and presents a current algorithm to optimize the torque contribution of each phase so as to reduce torque pulsation, and the improved performance of this bearingless motor is finally validated by simulation analysis.
Full article
(This article belongs to the Special Issue Research on Motor and Special Electromagnetic Device of Symmetry II)
Open AccessArticle
Recent Developments in Iterative Algorithms for Digital Metrics
by
Aasma Shaheen, Afshan Batool, Amjad Ali, Hamed Al Sulami and Aftab Hussain
Symmetry 2024, 16(3), 368; https://doi.org/10.3390/sym16030368 - 18 Mar 2024
Abstract
This paper aims to provide a comprehensive analysis of the advancements made in understanding Iterative Fixed-Point Schemes, which builds upon the concept of digital contraction mappings. Additionally, we introduce the notion of an Iterative Fixed-Point Schemes in digital metric spaces. In this study,
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This paper aims to provide a comprehensive analysis of the advancements made in understanding Iterative Fixed-Point Schemes, which builds upon the concept of digital contraction mappings. Additionally, we introduce the notion of an Iterative Fixed-Point Schemes in digital metric spaces. In this study, we extend the idea of Iteration process Mann, Ishikawa, Agarwal, and Thakur based on the ϝ-Stable Iterative Scheme in digital metric space. We also design some fractal images, which frame the compression of Fixed-Point Iterative Schemes and contractive mappings. Furthermore, we present a concrete example that exemplifies the motivation behind our investigations. Moreover, we provide an application of the proposed Fractal image and Sierpinski triangle that compress the works by storing images as a collection of digital contractions, which addresses the issue of storing images with less storage memory in this paper.
Full article
(This article belongs to the Special Issue New Trends in Fixed Point Theory with Emphasis on Symmetry)
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An ONIOM-Based High-Level Thermochemistry Study on Hydrogen Abstraction Reactions of Large Straight-Chain Alkanes by Hydrogen, Hydroxyl, and Hydroperoxyl Radicals
by
Yicheng Chi, Hao Pan, Qinghui Meng, Lidong Zhang and Peng Zhang
Symmetry 2024, 16(3), 367; https://doi.org/10.3390/sym16030367 - 18 Mar 2024
Abstract
Accurate thermochemical data are of great importance in developing quantitatively predictive reaction mechanisms for transportation fuels, such as diesel and jet fuels, which are primarily composed of large hydrocarbon molecules, especially large straight-chain alkanes containing more than 10 carbon atoms. This paper presents
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Accurate thermochemical data are of great importance in developing quantitatively predictive reaction mechanisms for transportation fuels, such as diesel and jet fuels, which are primarily composed of large hydrocarbon molecules, especially large straight-chain alkanes containing more than 10 carbon atoms. This paper presents an ONIOM[QCISD(T)/CBS:DFT]-based theoretical thermochemistry study on the hydrogen abstraction reactions of straight-chain alkanes, n-CnH2n+2, (n = 1–16) by hydrogen (H), hydroxyl (OH), and hydroperoxyl (HO2) radicals. These reactions, with n ≥ 10, pose significant computational challenges for prevalent high-level ab initio methods. However, they are effectively addressed using the ONIOM-based method. One notable aspect of this study is the consideration of the high symmetry of straight-chain alkanes. This symmetry allows us to study half of the reactions, employing a generalized approach. Therefore, a total of 216 reactions are systematically studied for the three reaction systems. Our results align very well with those from the widely accepted high-level QCISD(T)/CBS method, with discrepancies between the two generally less than 0.10 kcal/mol. Furthermore, we compared large straight-chain alkanes (n-C16H34 and n-C18H38) with large methyl ester molecules (C15H31COOCH3 and C17H33COOCH3) to elucidate the impact of functional groups (ester group and C=C double bond) on the reactivity of the long-chain structure. These findings underscore the accuracy and efficiency of the ONIOM-based method in computational thermochemistry, particularly for large straight-chain hydrocarbons in transportation fuels.
Full article
(This article belongs to the Special Issue Symmetry in Aerospace Sciences and Applications)
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An Extensive Investigation into the Use of Machine Learning Tools and Deep Neural Networks for the Recognition of Skin Cancer: Challenges, Future Directions, and a Comprehensive Review
by
Syed Ibrar Hussain and Elena Toscano
Symmetry 2024, 16(3), 366; https://doi.org/10.3390/sym16030366 - 18 Mar 2024
Abstract
Skin cancer poses a serious risk to one’s health and can only be effectively treated with early detection. Early identification is critical since skin cancer has a higher fatality rate, and it expands gradually to different areas of the body. The rapid growth
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Skin cancer poses a serious risk to one’s health and can only be effectively treated with early detection. Early identification is critical since skin cancer has a higher fatality rate, and it expands gradually to different areas of the body. The rapid growth of automated diagnosis frameworks has led to the combination of diverse machine learning, deep learning, and computer vision algorithms for detecting clinical samples and atypical skin lesion specimens. Automated methods for recognizing skin cancer that use deep learning techniques are discussed in this article: convolutional neural networks, and, in general, artificial neural networks. The recognition of symmetries is a key point in dealing with the skin cancer image datasets; hence, in developing the appropriate architecture of neural networks, as it can improve the performance and release capacities of the network. The current study emphasizes the need for an automated method to identify skin lesions to reduce the amount of time and effort required for the diagnostic process, as well as the novel aspect of using algorithms based on deep learning for skin lesion detection. The analysis concludes with underlying research directions for the future, which will assist in better addressing the difficulties encountered in human skin cancer recognition. By highlighting the drawbacks and advantages of prior techniques, the authors hope to establish a standard for future analysis in the domain of human skin lesion diagnostics.
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(This article belongs to the Special Issue Feature Papers in Mathematics Section)
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Open AccessArticle
Statistical Inference and Application of Asymmetrical Generalized Pareto Distribution Based on Peaks-Over-Threshold Model
by
Wenru Chen, Xu Zhao, Mi Zhou, Haiqing Chen, Qingqing Ji and Weihu Cheng
Symmetry 2024, 16(3), 365; https://doi.org/10.3390/sym16030365 - 18 Mar 2024
Abstract
Generalized Pareto distribution (GPD), an asymmetrical distribution, primarily models exceedances over a high threshold in many applications. Within the peaks-over-threshold (POT) framework, we consider a new GPD parameter estimation method to estimate a common tail risk measure, the value at risk (VaR). The
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Generalized Pareto distribution (GPD), an asymmetrical distribution, primarily models exceedances over a high threshold in many applications. Within the peaks-over-threshold (POT) framework, we consider a new GPD parameter estimation method to estimate a common tail risk measure, the value at risk (VaR). The proposed method is more suitable for the POT framework and makes full use of data information. Specifically, our estimation method builds upon the generalized probability weighted moments method and integrates it with the nonlinear weighted least squares method. We use exceedances for the GPD, minimizing the sum of squared differences between the sample and population moments of a function of GPD random variables. At the same time, the proposed estimator uses three iterations and assigns weight to further improving the estimated performance. Under Monte Carlo simulations and with a real heavy-tailed dataset, the simulation results show the advantage of the newly proposed estimator, particularly when VaRs are at high confidence levels. In addition, by simulating other heavy-tailed distributions, our method still exhibits good performance in estimating misjudgment distributions.
Full article
(This article belongs to the Special Issue Symmetrical and Asymmetrical Distributions in Statistics and Data Science II)
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Open AccessArticle
On the Breaking of the U(1) Peccei–Quinn Symmetry and Its Implications for Neutrino and Dark Matter Physics
by
Osvaldo Civitarese
Symmetry 2024, 16(3), 364; https://doi.org/10.3390/sym16030364 - 18 Mar 2024
Abstract
The Standard Model of electroweak interactions is based on the fundamental SU(2)weak × U(1)elect representation. It assumes massless neutrinos and purely left-handed massive and Z0 bosons to which one should add the massless photon. The existence,
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The Standard Model of electroweak interactions is based on the fundamental SU(2)weak × U(1)elect representation. It assumes massless neutrinos and purely left-handed massive and Z0 bosons to which one should add the massless photon. The existence, verified experimentally, of neutrino oscillations poses a challenge to this scheme, since the oscillations take place between at least three massive neutrinos belonging to a mass hierarchy still to be determined. One should also take into account the possible existence of sterile neutrino species. In a somehow different context, the fundamental nature of the strong interaction component of the forces in nature is described by the, until now, extremely successful representation based on the SU(3)strong group which, together with the confining rule, give a description of massive hadrons in terms of quarks and gluons. To this is added the minimal U(1) Higgs group to give mass to the otherwise massless generators. This representation may also be challenged by the existence of both dark matter and dark energy, of still unknown composition. In this note, we shall discuss a possible connection between these questions, namely the need to extend the SU(3)strong × SU(2)weak × U(1)elect to account for massive neutrinos and dark matter. The main point of it is related to the role of axions, as postulated by Roberto Peccei and Helen Quinn. The existence of neutral pseudo-scalar bosons, that is, the axions, has been proposed long ago by Peccei and Quinn to explain the suppression of the electric dipole moment of the neutron. The associated U(1)PQ symmetry breaks at very high energy, and it guarantees that the interaction of other particles with axions is very weak. We shall review the axion properties in connection with the apparently different contexts of neutrino and dark matter physics.
Full article
(This article belongs to the Special Issue Role of Symmetries in Nuclear Physics)
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Modified Tseng Method for Solving Pseudomonotone Variational Inequality Problem in Banach Spaces
by
Rose Maluleka, Godwin Chidi Ugwunnadi, Maggie Aphane, Hammed A. Abass and Abdul Rahim Khan
Symmetry 2024, 16(3), 363; https://doi.org/10.3390/sym16030363 - 18 Mar 2024
Abstract
This article examines the process for solving the fixed-point problem of Bregman strongly nonexpansive mapping as well as the variational inequality problem of the pseudomonotone operator. Within the context of p-uniformly convex real Banach spaces that are also uniformly smooth, we introduce
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This article examines the process for solving the fixed-point problem of Bregman strongly nonexpansive mapping as well as the variational inequality problem of the pseudomonotone operator. Within the context of p-uniformly convex real Banach spaces that are also uniformly smooth, we introduce a modified Halpern iterative technique combined with an inertial approach and Tseng methods for finding a common solution of the fixed-point problem of Bregman strongly nonexpansive mapping and the pseudomonotone variational inequality problem. Using our iterative approach, we develop a strong convergence result for approximating the solution of the aforementioned problems. We also discuss some consequences of our major finding. The results presented in this paper complement and build upon many relevant discoveries in the literature.
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(This article belongs to the Section Mathematics)
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Open AccessArticle
Pseudo-Finsler Radially Symmetric Spaces
by
Marianty Ionel and Miguel Ángel Javaloyes
Symmetry 2024, 16(3), 362; https://doi.org/10.3390/sym16030362 - 18 Mar 2024
Abstract
We introduce the concept of radially symmetric pseudo-Finsler spaces, which generalize the notion of symmetric Finsler spaces, and prove that this concept is equivalent to the preservation of flag curvature by parallel transport together with reversibility. As a consequence, reversible pseudo-Finsler manifolds with
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We introduce the concept of radially symmetric pseudo-Finsler spaces, which generalize the notion of symmetric Finsler spaces, and prove that this concept is equivalent to the preservation of flag curvature by parallel transport together with reversibility. As a consequence, reversible pseudo-Finsler manifolds with constant flag curvature are radially symmetric.
Full article
(This article belongs to the Special Issue Recent Advance in Mathematical Physics II)
Open AccessArticle
The Hermitian Solution to a New System of Commutative Quaternion Matrix Equations
by
Yue Zhang, Qing-Wen Wang and Lv-Ming Xie
Symmetry 2024, 16(3), 361; https://doi.org/10.3390/sym16030361 - 17 Mar 2024
Abstract
This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, where we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. In addition, we also
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This paper considers the Hermitian solutions of a new system of commutative quaternion matrix equations, where we establish both necessary and sufficient conditions for the existence of solutions. Furthermore, we derive an explicit general expression when it is solvable. In addition, we also provide the least squares Hermitian solution in cases where the system of matrix equations is not consistent. To illustrate our main findings, in this paper we present two numerical algorithms and examples.
Full article
(This article belongs to the Section Mathematics)
Open AccessArticle
New Approach of Normal and Shear Stress Components for Multiple Curvilinear Holes Which Weakened a Flexible Plate
by
Faizah M. Alharbi and Nafeesa G. Alhendi
Symmetry 2024, 16(3), 360; https://doi.org/10.3390/sym16030360 - 16 Mar 2024
Abstract
In this article, a thin infinite flexible plate weakened by multiple curvilinear holes is considered. The strength shapes are mapped outside a unit circle with the assistance of particular conformal mapping under certain conditions. The mathematical model that governs the rounded forces of
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In this article, a thin infinite flexible plate weakened by multiple curvilinear holes is considered. The strength shapes are mapped outside a unit circle with the assistance of particular conformal mapping under certain conditions. The mathematical model that governs the rounded forces of the current physical problem is the boundary value problem of elastic media. This study is applicable to many phenomena throughout nature, like tunnels, caves, and excavations in soil or rock. The Cauchy method for complex variables is used to get the closed forms of Gaursat functions and change the problem to a second-type integrodifferential equation with a Cauchy kernel, which is used for a large area of the contact problems. Then, the normal and shear stress components that act on the model are derived. Afterward, some of the physical applications are studied, and different stress components at specific values in each application are calculated and plotted using Maple 2023.
Full article
(This article belongs to the Section Mathematics)
Open AccessReview
Charged Lepton-Flavour Violation
by
Giulia Frau and Christoph Langenbruch
Symmetry 2024, 16(3), 359; https://doi.org/10.3390/sym16030359 - 16 Mar 2024
Abstract
We review the experimental status of searches for lepton-flavour violation in the charged sector. We give an overview of searches for lepton-flavour violation in purely leptonic decays, hadron decays, and decays of heavy bosons. We focus on the most stringent constraints on lepton-flavour
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We review the experimental status of searches for lepton-flavour violation in the charged sector. We give an overview of searches for lepton-flavour violation in purely leptonic decays, hadron decays, and decays of heavy bosons. We focus on the most stringent constraints on lepton-flavour violating processes in these areas and give prospects for ongoing and future experiments.
Full article
(This article belongs to the Special Issue Symmetries and Anomalies in Flavour Physics)
Open AccessArticle
Improved Generative Adversarial Network for Bearing Fault Diagnosis with a Small Number of Data and Unbalanced Data
by
Zhaohui Qin, Faguo Huang, Jiafang Pan, Junlin Niu and Haihua Qin
Symmetry 2024, 16(3), 358; https://doi.org/10.3390/sym16030358 - 15 Mar 2024
Abstract
Fault data under real operating conditions are often difficult to collect, making the number of trained fault data small and out of proportion to normal data. Thus, fault diagnosis symmetry (balance) is compromised. This will result in less effective fault diagnosis methods for
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Fault data under real operating conditions are often difficult to collect, making the number of trained fault data small and out of proportion to normal data. Thus, fault diagnosis symmetry (balance) is compromised. This will result in less effective fault diagnosis methods for cases with a small number of data and data imbalances (S&I). We present an innovative solution to overcome this problem, which is composed of two components: data augmentation and fault diagnosis. In the data augmentation section, the S&I dataset is supplemented with a deep convolutional generative adversarial network based on a gradient penalty and Wasserstein distance (WDCGAN-GP), which solve the problems of the generative adversarial network (GAN) being prone to model collapse and the gradient vanishing during the training time. The addition of self-attention allows for a better identification and generation of sample features. Finally, the addition of spectral normalization can stabilize the training of the model. In the fault diagnosis section, fault diagnosis is performed through a convolutional neural network with coordinate attention (CNN-CA). Our experiments conducted on two bearing fault datasets for comparison demonstrate that the proposed method surpasses other comparative approaches in terms of the quality of data augmentation and the accuracy of fault diagnosis. It effectively addresses S&I fault diagnosis challenges.
Full article
(This article belongs to the Topic Predictive Analytics and Fault Diagnosis of Machines with Machine Learning Techniques)
Open AccessArticle
Special Relativity in Terms of Hyperbolic Functions with Coupled Parameters in 3+1 Dimensions
by
Nikolai S. Akintsov, Artem P. Nevecheria, Gennadii F. Kopytov, Yongjie Yang and Tun Cao
Symmetry 2024, 16(3), 357; https://doi.org/10.3390/sym16030357 - 15 Mar 2024
Abstract
This paper presents a method for parameterizing new Lorentz spacetime coordinates based on coupled parameters. The role of symmetry in rapidity in special relativity is explored, and invariance is obtained for new spacetime intervals with respect to the Lorentz transformation. Using the Euler–Hamilton
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This paper presents a method for parameterizing new Lorentz spacetime coordinates based on coupled parameters. The role of symmetry in rapidity in special relativity is explored, and invariance is obtained for new spacetime intervals with respect to the Lorentz transformation. Using the Euler–Hamilton equations, an additional angular rapidity and perpendicular rapidity are obtained, and the Hamiltonian and Lagrangian of a relativistic particle are expanded into rapidity spectra. A so-called passage to the limit is introduced that makes it possible to decompose physical quantities into spectra in terms of elementary functions when explicit decomposition is difficult. New rapidity-dependent Lorentz spacetime coordinates are obtained. The descriptions of particle motion using the old and new Lorentz spacetime coordinates as applied to plane laser pulses are compared in terms of the particle kinetic energy. Based on a classical model of particle motion in the field of a plane monochromatic electromagnetic wave and that of a plane laser pulse, rapidity-dependent spectral decompositions into elementary functions are presented, and the Euler–Hamilton equations are derived as rapidity functions in 3+1 dimensions. The new and old Lorentz spacetime coordinates are compared with the Fermi spacetime coordinates. The proper Lorentz groups SO(1,3) with coupled parameters using the old and new Lorentz spacetime coordinates are also compared. As a special case, the application of Lorentz spacetime coordinates to a relativistic hydrodynamic system with coupled parameters in 1+1 dimensions is demonstrated.
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(This article belongs to the Special Issue Lorentz Symmetry and General Relativity)
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A Low-Latency Noise-Aware Tone Mapping Operator for Hardware Implementation with a Locally Weighted Guided Filter
by
Qianwang Liang, Tianyu Yan, Nan Wang, Zhiying Zhu and Jiongyao Ye
Symmetry 2024, 16(3), 356; https://doi.org/10.3390/sym16030356 - 15 Mar 2024
Abstract
A tone mapping operator (TMO) is a module in the image signal processing pipeline that is used to convert high dynamic range images to low dynamic range images for display. Currently, state-of-the-art TMOs typically take complex algorithms and are implemented on graphics processing
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A tone mapping operator (TMO) is a module in the image signal processing pipeline that is used to convert high dynamic range images to low dynamic range images for display. Currently, state-of-the-art TMOs typically take complex algorithms and are implemented on graphics processing units, making it difficult to run with low latency on edge devices, and TMOs implemented in hardware circuits often lack additional noise suppression because of latency and hardware resource constraints. To address these issues, we proposed a low-latency noise-aware TMO for hardware implementation. Firstly, a locally weighted guided filter is proposed to decompose the luminance image into a base layer and a detail layer, with the weight function symmetric concerning the central pixel value of a window. Secondly, the mean and standard deviation of the basic layer and the detail layer are used to estimate the noise visibility according to the human visual characteristics. Finally, the gain for the detail layer is calculated to achieve adaptive noise suppression. In this process, luminance is first processed by the log2 function before being filtered and then symmetrically converted back to the linear domain by the exp2 function after compression. Meanwhile, the algorithms within the proposed TMO were optimized for hardware implementation to minimize latency and cache, achieving a low latency of 60.32 under video specification of 1080 P at 60 frames per second and objective metric smoothness in dark flat regions could be improved by more than 10% compared to similar methods.
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(This article belongs to the Special Issue Security, Communication and Privacy in Internet of Things: Symmetry and Advances — Volume II)
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Enigma of Pyramidal Neurons: Chirality-Centric View on Biological Evolution. Congruence to Molecular, Cellular, Physiological, Cognitive, and Psychological Functions
by
Victor Vasilyevich Dyakin and Nika Viktorovna Dyakina-Fagnano
Symmetry 2024, 16(3), 355; https://doi.org/10.3390/sym16030355 - 15 Mar 2024
Abstract
The mechanism of brain information processing unfolds within spatial and temporal domains inherently linked to the concept of space–time symmetry. Biological evolution, beginning with the prevalent molecular chirality, results in the handedness of human cognitive and psychological functions (the phenomena known as biochirality).
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The mechanism of brain information processing unfolds within spatial and temporal domains inherently linked to the concept of space–time symmetry. Biological evolution, beginning with the prevalent molecular chirality, results in the handedness of human cognitive and psychological functions (the phenomena known as biochirality). The key element in the chain of chirality transfer from the downstream to upstream processes is the pyramidal neuron (PyrN) morphology–function paradigm (archetype). The most apparent landmark of PyrNs is the geometry of the cell soma. However, “why/how PyrN’s soma gains the shape of quasi-tetrahedral symmetry” has never been explicitly articulated. Resolving the above inquiry is only possible based on the broad-view assumption that encoding 3D space requires specific 3D geometry of the neuronal detector and corresponding network. Accordingly, our hypothesis states that if the primary function of PyrNs, at the organism level, is sensory space symmetry perception, then the pyramidal shape of soma is the best evolutionary-selected geometry to support sensory-motor coupling. The biological system’s non-equilibrium (NE) state is fundamentally linked to an asymmetric, non-racemic, steady state of molecular constituents. The chiral theory of pyramidal soma shape conceptually agrees that living systems have evolved as non-equilibrium systems that exchange energy with the environment. The molecular mechanism involved in developing PyrN’s soma is studied in detail. However, the crucial missing element—the reference to the fundamental link between molecular chirality and the function of spatial navigation—is the main obstacle to resolving the question in demand: why did PyrNs’ soma gain the shape of quasi-tetrahedral symmetry?
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(This article belongs to the Section Life Sciences)
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Open AccessArticle
Hidden-Charm Pentaquarks with Strangeness in a Chiral Quark Model
by
Gang Yang, Jialun Ping and Jorge Segovia
Symmetry 2024, 16(3), 354; https://doi.org/10.3390/sym16030354 - 14 Mar 2024
Abstract
The LHCb collaboration has recently announced the discovery of two hidden-charm pentaquark states with strange quark content, and ; its analysis points towards having both hadrons’ isospins equal to zero and
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The LHCb collaboration has recently announced the discovery of two hidden-charm pentaquark states with strange quark content, and ; its analysis points towards having both hadrons’ isospins equal to zero and spin-parity quantum numbers and , respectively. Herein, we perform a systematical investigation of the system by means of a chiral quark model, along with a highly accurate computational method, the Gaussian expansion approach combined with the complex scaling technique. baryon-meson configurations in both singlet- and hidden-color channels are considered. The and signals can be well identified as molecular bound states with dominant components and for the lowest-energy case and for the highest-energy one. In addition, it seems that some narrow resonances can also be found in each allowed channel in the energy region of – GeV, except for the channel where a shallow bound state with dominant structure is obtained at 4673 MeV with binding energy MeV. These exotic states are expected to be confirmed in future high-energy experiments.
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(This article belongs to the Section Physics)
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Anisotropy and Asymptotic Degeneracy of the Physical-Hilbert-Space Inner-Product Metrics in an Exactly Solvable Unitary Quantum Model
by
Miloslav Znojil
Symmetry 2024, 16(3), 353; https://doi.org/10.3390/sym16030353 - 14 Mar 2024
Abstract
A unitary-evolution process leading to an ultimate collapse and to a complete loss of observability alias quantum phase transition is studied. A specific solvable state model is considered, characterized by a non-stationary non-Hermitian Hamiltonian. Our analysis uses quantum mechanics formulated in
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A unitary-evolution process leading to an ultimate collapse and to a complete loss of observability alias quantum phase transition is studied. A specific solvable state model is considered, characterized by a non-stationary non-Hermitian Hamiltonian. Our analysis uses quantum mechanics formulated in Schrödinger picture in which, in principle, only the knowledge of a complete set of observables (i.e., operators ) enables one to guarantee the uniqueness of the related physical Hilbert space (i.e., of its inner-product metric ). Nevertheless, for the sake of simplicity, we only assume the knowledge of just a single input observable (viz., of the energy-representing Hamiltonian ). Then, out of all of the eligible and Hamiltonian-dependent “Hermitizing” inner-product metrics , we pick up just the simplest possible candidate. Naturally, this slightly restricts the scope of the theory, but in our present model, such a restriction is more than compensated for by the possibility of an alternative, phenomenologically better motivated constraint by which the time-dependence of the metric is required to be smooth. This opens a new model-building freedom which, in fact, enables us to force the system to reach the collapse, i.e., a genuine quantum catastrophe as a result of the mere conventional, strictly unitary evolution.
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(This article belongs to the Special Issue The Benefits That Physics Derives from the Concept of Symmetry)
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Adaptive Feedback Control of Nonminimum Phase Boost Converter with Constant Power Load
by
Khalil Jouili, Monia Charfeddine and Mohammed Alqarni
Symmetry 2024, 16(3), 352; https://doi.org/10.3390/sym16030352 - 14 Mar 2024
Abstract
The inherent negative impedance characteristics of a Constant Power Load (CPL) pose a potential threat to the stability of the bus voltage in a DC microgrid consisting of a symmetrical parallel boost converter. We suggest an adaptive feedback control technique using the input–output
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The inherent negative impedance characteristics of a Constant Power Load (CPL) pose a potential threat to the stability of the bus voltage in a DC microgrid consisting of a symmetrical parallel boost converter. We suggest an adaptive feedback control technique using the input–output exact feedback linearization theory for a boost converter integrated into a DC microgrid to improve the stability of the DC bus voltage. This approach involves a transformation of the model into a Brunovsky canonical form, effectively addressing the nonlinear challenges arising from the CPL and the nonminimum phase characteristics of the boost converter. Subsequently, guided by the Lyapunov approach, an adaptation law is established to fine-tune the controller’s gain vector, facilitating the tracking of a predefined linearizing feedback control. We methodically create a method to choose the gains of the adaptive controller in order to guarantee an adequate output response. We validate our suggested controller’s performance using simulation.
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(This article belongs to the Special Issue Active Control of Asymmetrical Wake Flow in Wind Energy Systems)
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Open AccessArticle
Analytic Functions in a Complete Reinhardt Domain Having Bounded L-Index in Joint Variables
by
Andriy Bandura, Tetyana Salo and Oleh Skaskiv
Symmetry 2024, 16(3), 351; https://doi.org/10.3390/sym16030351 - 14 Mar 2024
Abstract
The manuscript is an initiative to construct a full and exhaustive theory of analytical multivariate functions in any complete Reinhardt domain by introducing the concept of -index in joint variables for these functions for a given continuous, non-negative, non-vanishing, vector-valued mapping
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The manuscript is an initiative to construct a full and exhaustive theory of analytical multivariate functions in any complete Reinhardt domain by introducing the concept of -index in joint variables for these functions for a given continuous, non-negative, non-vanishing, vector-valued mapping defined in an interior of the domain with some behavior restrictions. The complete Reinhardt domain is an example of a domain having a circular symmetry in each complex dimension. Our results are based on the results obtained for such classes of holomorphic functions: entire multivariate functions, as well as functions which are analytical in the unit ball, in the unit polydisc, and in the Cartesian product of the complex plane and the unit disc. For a full exhaustion of the domain, polydiscs with some radii and centers are used. Estimates of the maximum modulus for partial derivatives of the functions belonging to the class are presented. The maximum is evaluated at the skeleton of some polydiscs with any center and with some radii depending on the center and the function and, at most, it equals a some constant multiplied by the partial derivative modulus at the center of the polydisc. Other obtained statements are similar to the described one.
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(This article belongs to the Section Mathematics)
Open AccessArticle
Fringe Projection Profilometry for Three-Dimensional Measurement of Aerospace Blades
by
Ze Chen, Mulun Zhu, Chuanzhi Sun, Yongmeng Liu and Jiubin Tan
Symmetry 2024, 16(3), 350; https://doi.org/10.3390/sym16030350 - 14 Mar 2024
Abstract
The aero-engine serves as the “heart” of an aircraft and is a primary factor determining the aircraft’s performance. Among the crucial components in the core of aero-engines, aero-engine compressor blades stand out as extremely important. They are not only numerous but also characterized
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The aero-engine serves as the “heart” of an aircraft and is a primary factor determining the aircraft’s performance. Among the crucial components in the core of aero-engines, aero-engine compressor blades stand out as extremely important. They are not only numerous but also characterized by a multitude of parameters, making them the most complex parts in an aero-engine. This paper aims to address the trade-off between accuracy and efficiency in the existing measurement methods for asymmetric blades. Non-contact measurements were conducted using a structured light system composed of a stereo camera and a DLC projector. The point cloud data of the blades are processed using methods such as the PCA (Principal Component Analysis) algorithm, binary search, and least squares fitting. This paper established a fringe-projection profilometry light sensor system for the multi-view measurement of the blades. High-precision rotary tables are utilized to rotate and extract complete spatial point cloud data of aviation blades. Finally, measurements and comparative experiments on the blade body are conducted. The obtained blade point cloud data undergo sorting and denoising processes, resulting in improved measurement accuracy. The measurement error of the blade chord length is 0.001%, the measurement error of blade maximum thickness is 0.895%, compared to CMM (Coordinate Measuring Machine), where the measurement error of chord is 0.06%.
Full article
(This article belongs to the Section Engineering and Materials)
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