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Symmetries and Dynamics of Generalized Biquaternionic Julia Sets Defined by Various Polynomials
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Reciprocity and Representations for Wave Fields in 3D Inhomogeneous Parity-Time Symmetric Materials
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Complexes of Tetravalent Actinides with DOTA
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Lateral Bias in Visual Working Memory
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A Symmetry In-between the Shapes, Shells, and Clusters of Nuclei
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)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 14.2 days after submission; acceptance to publication is undertaken in 4.7 days (median values for papers published in this journal in the second half of 2022).
- 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.
- Sections: published in 6 topical sections.
- Testimonials: See what our editors and authors say about Symmetry.
Impact Factor:
2.940 (2021);
5-Year Impact Factor:
2.834 (2021)
Latest Articles
Program Source-Code Re-Modularization Using a Discretized and Modified Sand Cat Swarm Optimization Algorithm
Symmetry 2023, 15(2), 401; https://doi.org/10.3390/sym15020401 (registering DOI) - 02 Feb 2023
Abstract
One of expensive stages of the software lifecycle is its maintenance. Software maintenance will be much simpler if its structural models are available. Software module clustering is thought to be a practical reverse engineering method for building software structural models from source code.
[...] Read more.
One of expensive stages of the software lifecycle is its maintenance. Software maintenance will be much simpler if its structural models are available. Software module clustering is thought to be a practical reverse engineering method for building software structural models from source code. The most crucial goals in software module clustering are to minimize connections between created clusters, maximize internal connections within clusters, and maximize clustering quality. It is thought that finding the best software clustering model is an NP-complete task. The key shortcomings of the earlier techniques are their low success rates, low stability, and insufficient modularization quality. In this paper, for effective clustering of software source code, a discretized sand cat swarm optimization (SCSO) algorithm has been proposed. The proposed method takes the dependency graph of the source code and generates the best clusters for it. Ten standard and real-world benchmarks were used to assess the performance of the suggested approach. The outcomes show that the quality of clustering is improved when a discretized SCSO algorithm was used to address the software module clustering issue. The suggested method beats the previous heuristic approaches in terms of modularization quality, convergence speed, and success rate.
Full article
(This article belongs to the Section Computer Science and Symmetry/Asymmetry)
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Open AccessArticle
Analytical Investigation of the Heat Transfer Effects of Non-Newtonian Hybrid Nanofluid in MHD Flow Past an Upright Plate Using the Caputo Fractional Order Derivative
by
and
Symmetry 2023, 15(2), 399; https://doi.org/10.3390/sym15020399 (registering DOI) - 02 Feb 2023
Abstract
The objective of this paper is to examine the augmentation of the heat transfer rate utilizing graphene (Gr) and multi-walled carbon nanotubes (MWCNTs) as nanoparticles, and water as a host fluid in magnetohydrodynamics (MHD) flow through an upright plate using Caputo fractional derivatives
[...] Read more.
The objective of this paper is to examine the augmentation of the heat transfer rate utilizing graphene (Gr) and multi-walled carbon nanotubes (MWCNTs) as nanoparticles, and water as a host fluid in magnetohydrodynamics (MHD) flow through an upright plate using Caputo fractional derivatives with a Brinkman model on the convective Casson hybrid nanofluid flow. The performance of hybrid nanofluids is examined with various shapes of nanoparticles. The Caputo fractional derivative is utilized to describe the governing fractional partial differential equations with initial and boundary conditions on the flow model. Exact solutions are obtained for flow transport, temperature distribution besides that heat transfer rate and friction drag in terms of Mittag-Leffler function by using Fourier sine and Laplace techniques as hybrid methods. Further, we provided the limiting case solutions for classic partial differential equations on obtained governing fluid flow models. The influence of various physical parameters with different fractional orders are investigated on hybrid nanofluid’s fractional momentum and energy by plotting velocity and energy curves. Few of the findings suggest that fractional parameters have significant effect on flow parameters and that blade-shaped nanoparticles have a high heat transfer rate. The graphical results reveal that the Grashof number shows a symmetry effect in the case of cooling and heating the plate. Furthermore, the performance of hybrid nanofluid is considerably more effective with the Caputo-fractional derivatives rather than in the classic derivative approach.
Full article
(This article belongs to the Topic Fractional Calculus: Theory and Applications)
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Open AccessArticle
EMSI-BERT: Asymmetrical Entity-Mask Strategy and Symbol-Insert Structure for Drug–Drug Interaction Extraction Based on BERT
Symmetry 2023, 15(2), 398; https://doi.org/10.3390/sym15020398 (registering DOI) - 02 Feb 2023
Abstract
Drug-drug interaction (DDI) extraction has seen growing usage of deep models, but their effectiveness has been restrained by limited domain-labeled data, a weak representation of co-occurring entities, and poor adaptation of downstream tasks. This paper proposes a novel EMSI-BERT method for drug–drug interaction
[...] Read more.
Drug-drug interaction (DDI) extraction has seen growing usage of deep models, but their effectiveness has been restrained by limited domain-labeled data, a weak representation of co-occurring entities, and poor adaptation of downstream tasks. This paper proposes a novel EMSI-BERT method for drug–drug interaction extraction based on an asymmetrical Entity-Mask strategy and a Symbol-Insert structure. Firstly, the EMSI-BERT method utilizes the asymmetrical Entity-Mask strategy to address the weak representation of co-occurring entity information using the drug entity dictionary in the pre-training BERT task. Secondly, the EMSI-BERT method incorporates four symbols to distinguish different entity combinations of the same input sequence and utilizes the Symbol-Insert structure to address the week adaptation of downstream tasks in the fine-tuning stage of DDI classification. The experimental results showed that EMSI-BERT for DDI extraction achieved a 0.82 F1-score on DDI-Extraction 2013, and it improved the performances of the multi-classification task of DDI extraction and the two-classification task of DDI detection. Compared with baseline Basic-BERT, the proposed pre-training BERT with the asymmetrical Entity-Mask strategy could obtain better effects in downstream tasks and effectively limit “Other” samples’ effects. The model visualization results illustrated that EMSI-BERT could extract semantic information at different levels and granularities in a continuous space.
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(This article belongs to the Special Issue Symmetry/Asymmetry and Fuzzy Systems)
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Chiral Magnetic Interactions in Small Fe Clusters Triggered by Symmetry-Breaking Adatoms
Symmetry 2023, 15(2), 397; https://doi.org/10.3390/sym15020397 - 02 Feb 2023
Abstract
The chirality of the interaction between the local magnetic moments in small transition-metal alloy clusters is investigated in the framework of density-functional theory. The Dzyaloshinskii–Moriya (DM) coupling vectors between the Fe atoms in Fe2X and Fe3X
[...] Read more.
The chirality of the interaction between the local magnetic moments in small transition-metal alloy clusters is investigated in the framework of density-functional theory. The Dzyaloshinskii–Moriya (DM) coupling vectors between the Fe atoms in Fe2X and Fe3X with X = Cu, Pd, Pt, and Ir are derived from independent ground-state energy calculations for different noncollinear orientations of the local magnetic moments. The local-environment dependence of and the resulting relative stability of different chiral magnetic orders are analyzed by contrasting the results for different adatoms X and by systematically varying the distance between the adatom X and the Fe clusters. One observes that the adatoms trigger most significant DM couplings in Fe2X, often in the range of 10–30 meV. Thus, the consequences of breaking the inversion symmetry of the Fe dimer are quantified. Comparison between the symmetric and antisymmetric Fe-Fe couplings shows that the DM couplings are about two orders of magnitude weaker than the isotropic Heisenberg interactions. However, they are in general stronger than the anisotropy of the symmetric couplings. In Fe3X, alloying induces interesting changes in both the direction and strength of the DM couplings, which are the consequence of breaking the reflection symmetry of the Fe trimer and which depend significantly on the adatom-trimer distance. A local analysis of the chirality of the electronic energy shows that the DM interactions are dominated by the spin-orbit coupling at the adatoms and that the contribution of the Fe atoms is small but not negligible.
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(This article belongs to the Special Issue Chiral Symmetry and Spin Dynamics)
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Image Denoising Based on Quantum Calculus of Local Fractional Entropy
Symmetry 2023, 15(2), 396; https://doi.org/10.3390/sym15020396 - 02 Feb 2023
Abstract
Images are frequently disrupted by noise of all kinds, making image restoration very challenging. There have been many different image denoising models proposed over the last few decades. Some models preserve the image’s smooth region, while others preserve the texture margin. One of
[...] Read more.
Images are frequently disrupted by noise of all kinds, making image restoration very challenging. There have been many different image denoising models proposed over the last few decades. Some models preserve the image’s smooth region, while others preserve the texture margin. One of these methods is by using quantum calculus. Quantum calculus is a branch of mathematics that deals with the manipulation of functions and operators in a quantum mechanical setting. It has been used in image processing to improve the speed and accuracy of image-processing algorithms. In quantum computing, entropy can be defined as a measure of the disorder or randomness of a quantum state. The concept of local fractional entropy has been used to study a wide range of quantum systems. In this study, an image denoising model is proposed based on the quantum calculus of local fractional entropy (QC-LFE) to remove a Gaussian noise. The local fractional entropy is used to estimate the image pixel probability, while the quantum calculus is used to estimate the convolution window mask for image denoising. A processing fractional mask with n x n elements was used in the suggested denoising algorithm. The proposed image denoising algorithm uses mask convolution to process each corrupted pixel one at a time. The proposed denoising algorithm’s effectiveness is assessed using peak signal-to-noise ratio and visual perception (PSNR). The experimental findings show that, compared to other similar fractional operators, the proposed method can better preserve texture details when denoising.
Full article
(This article belongs to the Special Issue Symmetry in Mathematical Functional Equations)
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Contextual Embeddings-Based Web Page Categorization Using the Fine-Tune BERT Model
Symmetry 2023, 15(2), 395; https://doi.org/10.3390/sym15020395 - 02 Feb 2023
Abstract
The World Wide Web has revolutionized the way we live, causing the number of web pages to increase exponentially. The web provides access to a tremendous amount of information, so it is difficult for internet users to locate accurate and useful information on
[...] Read more.
The World Wide Web has revolutionized the way we live, causing the number of web pages to increase exponentially. The web provides access to a tremendous amount of information, so it is difficult for internet users to locate accurate and useful information on the web. In order to categorize pages accurately based on the queries of users, methods of categorizing web pages need to be developed. The text content of web pages plays a significant role in the categorization of web pages. If a word’s position is altered within a sentence, causing a change in the interpretation of that sentence, this phenomenon is called polysemy. In web page categorization, the polysemy property causes ambiguity and is referred to as the polysemy problem. This paper proposes a fine-tuned model to solve the polysemy problem, using contextual embeddings created by the symmetry multi-head encoder layer of the Bidirectional Encoder Representations from Transformers (BERT). The effectiveness of the proposed model was evaluated by using the benchmark datasets for web page categorization, i.e., WebKB and DMOZ. Furthermore, the experiment series also fine-tuned the proposed model’s hyperparameters to achieve 96.00% and 84.00% F1-Scores, respectively, demonstrating the proposed model’s importance compared to baseline approaches based on machine learning and deep learning.
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(This article belongs to the Section Computer Science and Symmetry/Asymmetry)
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On the Modified Laplace Homotopy Perturbation Method for Solving Damped Modified Kawahara Equation and Its Application in a Fluid
Symmetry 2023, 15(2), 394; https://doi.org/10.3390/sym15020394 - 02 Feb 2023
Abstract
The manuscript solves a modified Kawahara equation (mKE) within two cases with and without a damping term by applying the Laplace homotopy perturbation method (LHPM). Since the damped mKE is non-integrable (i.e., it does not have analytic integrals) and does not have exact
[...] Read more.
The manuscript solves a modified Kawahara equation (mKE) within two cases with and without a damping term by applying the Laplace homotopy perturbation method (LHPM). Since the damped mKE is non-integrable (i.e., it does not have analytic integrals) and does not have exact initial conditions, this challenge makes many numerical methods fail to solve non-integrable equations. In this article, we suggested a new modification at LHPM by setting a perturbation parameter and an embedding parameter as the damping parameter and using the initial condition for mKE as the initial condition for non-damped mKE. The results proved that this mathematical approach is an effective method for solving damped mKE. Thus, we believe that the presented method will be helpful for solving many non-integrable equations that describe phenomena in sciences, such as nonlinear symmetrical wave propagation in plasma.
Full article
(This article belongs to the Special Issue On the Analytical and Numerical Methods for Modeling (A)symmetrical Nonlinear Waves and Oscillations in a Plasma)
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Open AccessArticle
Image Inpainting Anti-Forensics Network via Attention-Guided Hierarchical Reconstruction
Symmetry 2023, 15(2), 393; https://doi.org/10.3390/sym15020393 - 02 Feb 2023
Abstract
Privacy security and property rights protection have gradually attracted the attention of people. Users not only hope that the images edited by themselves will not be forensically investigated, but also hope that the images they share will not be tampered with. Aiming at
[...] Read more.
Privacy security and property rights protection have gradually attracted the attention of people. Users not only hope that the images edited by themselves will not be forensically investigated, but also hope that the images they share will not be tampered with. Aiming at the problem that inpainted images can be located by forensics, this paper proposes a general anti-forensics framework for image inpainting with copyright protection. Specifically, we employ a hierarchical attention model to symmetrically reconstruct the inpainting results based on existing deep inpainting methods. The hierarchical attention model consists of a structural attention stream and a texture attention stream in parallel, which can fuse hierarchical features to generate high-quality reconstruction results. In addition, the user’s identity information can be symmetrically embedded and extracted to protect copyright. The experimental results not only had high-quality structural texture information, but also had homologous features with the original region, which could mislead the detection of forensics analysis. At the same time, the protection of users’ privacy and property rights is also achieved.
Full article
(This article belongs to the Special Issue Security, Communication and Privacy in Internet of Things: Symmetry and Advances)
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Open AccessReview
Dilepton Program with Time-of-Flight Detector at the STAR Experiment
by
, , , , , , and
Symmetry 2023, 15(2), 392; https://doi.org/10.3390/sym15020392 - 02 Feb 2023
Abstract
Pairs of lepton and antilepton (dilepton) in a continuous mass range are one of the most experimentally challenging and golden probes of the quark-gluon plasma (QGP) produced in heavy ion collisions because they do not strongly interact with the hot and dense medium,
[...] Read more.
Pairs of lepton and antilepton (dilepton) in a continuous mass range are one of the most experimentally challenging and golden probes of the quark-gluon plasma (QGP) produced in heavy ion collisions because they do not strongly interact with the hot and dense medium, and reflect the properties of the medium at the time the dilepton is generated. The measurements of dileptons require lepton identification with high purity and high efficiency at large detector acceptance. STAR is one of two large experiments at the relativistic heavy ion collider with a primary goal of searching for the QGP and studying its properties. The STAR experiment launched a comprehensive dielectron ( ) program enabled by the time-of-flight (TOF) detector that had been fully installed in 2010. In this article, we review the decade-long , the construction and performance of the STAR TOF detector, and dielectron measurements, including thermal dielectron production and dielectron production from the Breit–Wheeler process. Future perspectives are also discussed.
Full article
(This article belongs to the Special Issue Heavy-Ion Collisions and Multiparticle Production)
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A Study of Positivity Analysis for Difference Operators in the Liouville–Caputo Setting
by
, , , , and
Symmetry 2023, 15(2), 391; https://doi.org/10.3390/sym15020391 - 02 Feb 2023
Abstract
The class of symmetric function interacts extensively with other types of functions. One of these is the class of positivity of functions, which is closely related to the theory of symmetry. Here, we propose a positive analysis technique to analyse a class of
[...] Read more.
The class of symmetric function interacts extensively with other types of functions. One of these is the class of positivity of functions, which is closely related to the theory of symmetry. Here, we propose a positive analysis technique to analyse a class of Liouville–Caputo difference equations of fractional-order with extremal conditions. Our monotonicity results use difference conditions and to derive the corresponding relative minimum and maximum, respectively. We find alternative conditions corresponding to the main conditions in the main monotonicity results, which are simpler and stronger than the existing ones. Two numerical examples are solved by achieving the main conditions to verify the obtained monotonicity results.
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(This article belongs to the Special Issue Global Meet on Condensed Matter Physics)
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More Insights into Symmetries in Multisymplectic Field Theories
Symmetry 2023, 15(2), 390; https://doi.org/10.3390/sym15020390 - 01 Feb 2023
Abstract
This work provides a general overview for the treatment of symmetries in classical field theories and (pre)multisymplectic geometry. The geometric characteristics of the relation between how symmetries are interpreted in theoretical physics and in the geometric formulation of these theories are clarified. Finally,
[...] Read more.
This work provides a general overview for the treatment of symmetries in classical field theories and (pre)multisymplectic geometry. The geometric characteristics of the relation between how symmetries are interpreted in theoretical physics and in the geometric formulation of these theories are clarified. Finally, a general discussion is given on the structure of symmetries in the presence of constraints appearing in singular field theories. Symmetries of some typical theories in theoretical physics are analyzed through the construction of the relevant multimomentum maps which are the conserved quantities (by Noether’s theorem) on the (pre)multisymplectic phase spaces.
Full article
(This article belongs to the Special Issue Symmetry in Geometric Mechanics and Mathematical Physics)
Open AccessArticle
Analytical Solutions for Fractional Differential Equations Using a General Conformable Multiple Laplace Transform Decomposition Method
by
Symmetry 2023, 15(2), 389; https://doi.org/10.3390/sym15020389 - 01 Feb 2023
Abstract
In this paper, a new analytical technique is proposed for solving fractional partial differential equations. This method is referred to as the general conformal multiple Laplace transform decomposition method. It is a combination of the multiple Laplace transform method and the Adomian decomposition
[...] Read more.
In this paper, a new analytical technique is proposed for solving fractional partial differential equations. This method is referred to as the general conformal multiple Laplace transform decomposition method. It is a combination of the multiple Laplace transform method and the Adomian decomposition method. The main theoretical results of using this method are presented. In addition, illustrative examples are provided to demonstrate the validity and symmetry of the presented method.
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(This article belongs to the Special Issue Differential Equations and Applied Mathematics)
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Open AccessReview
Particle-Laden and Droplet-Laden Two-Phase Flows Past Bodies (a Review)
Symmetry 2023, 15(2), 388; https://doi.org/10.3390/sym15020388 - 01 Feb 2023
Abstract
A review of computational–theoretical and experimental works devoted to the study of the flow of bodies by two-phase (dispersed) flows is carried out. The features of particle motion in the vicinity of bodies of various shapes, as well as the effect of the
[...] Read more.
A review of computational–theoretical and experimental works devoted to the study of the flow of bodies by two-phase (dispersed) flows is carried out. The features of particle motion in the vicinity of bodies of various shapes, as well as the effect of the dispersed phase on resistance and heat transfer, are considered. Some consequences of the interaction of particles and droplets with the surface of streamlined bodies (erosive destruction, gas-dynamic spraying, icing, glowing) are analyzed.
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(This article belongs to the Special Issue Plasma and Thermal Physics)
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Open AccessArticle
A Novel GDMD-PROMETHEE Algorithm Based on the Maximizing Deviation Method and Social Media Data Mining for Large Group Decision Making
Symmetry 2023, 15(2), 387; https://doi.org/10.3390/sym15020387 - 01 Feb 2023
Abstract
Multi-attribute group decision making is widely used in the real world, and many scholars have done a lot of research on it. The public’s focus on emergencies can provide an important reference for emergency handling decision making in the social media big data
[...] Read more.
Multi-attribute group decision making is widely used in the real world, and many scholars have done a lot of research on it. The public’s focus on emergencies can provide an important reference for emergency handling decision making in the social media big data environment. Due to the complexity of emergency handling decision making, the asymmetry of user evaluation information is easy to cause the loss of important information. It is very important to mine valuable information for decision making through online reviews. Then, a generalized extended hybrid distance measure method between the probabilistic linguistic term sets is proposed. Based on this, an extended GDMD-PROMETHEE large-scale multi-attribute group decision-making method is proposed as well, which can be used to decision making under symmetric information and asymmetric information. Firstly, web crawler technology is used to explore the topics of public concern of emergency handling on social media platforms, and use -means cluster analysis to classify the crawling variables, then the attributes and subjective weights of emergency handling plans are obtained by TF-IDF and Word2vec technology. Secondly, in order to better retain the linguistic evaluation information from decision-makers, a new generalized probabilistic hybrid distance measure method based on Hamming distance is proposed. Considering the difference of decision makers’ evaluation, the objective weight of decision makers is calculated by combining the maximum deviation method with the new extended hybrid Euclidean distance. On this basis, the comprehensive weights of the attributes are calculated by combining subjective and objective factors. Meanwhile, this paper realizes the distance measures and information fusion of probabilistic linguistic term sets under cumulative prospect theory, and the ranking results of the emergency handling plans based on the extended GDMD-PROMETHEE algorithm are given. Finally, the feasibility and effectiveness of the extended GDMD-PROMETHEE algorithm are verified by the case study of the explosion accident handling decision making of Shanghai “6.18” Petrochemical, and the comparative analyses between the several traditional algorithms demonstrate the extended GDMD-PROMETHEE algorithm is more scientific and superior in this paper.
Full article
(This article belongs to the Special Issue Research on Fuzzy Logic and Mathematics with Applications II)
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Open AccessArticle
Twin Supersymmetric Dark Matter in Light of the First LZ Results
Symmetry 2023, 15(2), 386; https://doi.org/10.3390/sym15020386 - 01 Feb 2023
Abstract
We review the status of dark matter (DM) candidates in supersymmetric Twin Higgs models in light of the first results of the LUX-ZEPLIN (LZ) experiment. We found that, for twin bino-dominated DM, the new results strengthened the lower bound on the higgsino mass.
[...] Read more.
We review the status of dark matter (DM) candidates in supersymmetric Twin Higgs models in light of the first results of the LUX-ZEPLIN (LZ) experiment. We found that, for twin bino-dominated DM, the new results strengthened the lower bound on the higgsino mass. However, a large part of the parameter space consistent with natural electroweak symmetry breaking is still allowed. In the case of twin-stau DM, the new results imply that, if the thermal abundance of the twin-stau LSP fits the observed density of DM, the twin stau cannot have a large left-handed component anymore.
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(This article belongs to the Special Issue Nature and Origin of Dark Matter and Dark Energy)
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Open AccessArticle
Thermal Onsets of Viscous Dissipation for Radiative Mixed Convective Flow of Jeffery Nanofluid across a Wedge
by
, , , , and
Symmetry 2023, 15(2), 385; https://doi.org/10.3390/sym15020385 - 01 Feb 2023
Abstract
The current analysis discusses Jeffery nanofluid’s thermally radiative flow with convection over a stretching wedge. It takes into account the Brownian movement and thermophoresis of the Buongiorno nanofluid model. The guiding partial differential equations (PDEs) are modified by introducing the symmetry variables, leading
[...] Read more.
The current analysis discusses Jeffery nanofluid’s thermally radiative flow with convection over a stretching wedge. It takes into account the Brownian movement and thermophoresis of the Buongiorno nanofluid model. The guiding partial differential equations (PDEs) are modified by introducing the symmetry variables, leading to non-dimensional ordinary differential equations (ODEs). To solve the generated ODEs, the MATLAB function bvp4c is implemented. Examined are the impacts of different flow variables on the rate of transmission of heat transfer (HT), temperature, mass, velocity, and nanoparticle concentration (NC). It has been noted that the velocity and mass transfer were increased by the pressure gradient factor. Additionally, the thermal boundary layer (TBL) and nanoparticle concentration are reduced by the mixed convection (MC) factor. In order to validate the present research, the derived numerical results were compared to previous findings from the literature while taking into account the specific circumstances. It was found that there was good agreement in both sets of data.
Full article
(This article belongs to the Special Issue Recent Advances in Conjugate Heat Transfer)
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Open AccessArticle
Containment Control Problem of Linear Multiagent Systems with External Disturbance and DoS Attacks
Symmetry 2023, 15(2), 384; https://doi.org/10.3390/sym15020384 - 01 Feb 2023
Abstract
This work investigates the containment control for linear multiagent systems. We assume that the systems are subject to periodic energy-limited denial-of-service (DoS) attacks, which prevent agent-to-agent data transmission. It is assumed that the DoS attacks occur periodically based on the time sequence method.
[...] Read more.
This work investigates the containment control for linear multiagent systems. We assume that the systems are subject to periodic energy-limited denial-of-service (DoS) attacks, which prevent agent-to-agent data transmission. It is assumed that the DoS attacks occur periodically based on the time sequence method. It is also assumed that some devices can be used to predict the duration of DoS attacks and uniform lower bound of communication areas. To achieve containment control, state and disturbance estimators are proposed for each following agent to estimate the relative state information. Under suitable conditions, the containment control problem can be solved with the designed controllers and observers. Finally, we provide a simulation result to confirm the theoretical analysis.
Full article
(This article belongs to the Section Mathematics and Symmetry/Asymmetry)
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Open AccessArticle
On the Traversable Yukawa–Casimir Wormholes
by
, , and
Symmetry 2023, 15(2), 383; https://doi.org/10.3390/sym15020383 - 01 Feb 2023
Abstract
Wormholes require negative energy, and therefore an exotic matter source. Since Casimir’s energy is negative, it has been speculated as a good candidate to source those objects a long time ago. However, only very recently a full solution for dimensions
[...] Read more.
Wormholes require negative energy, and therefore an exotic matter source. Since Casimir’s energy is negative, it has been speculated as a good candidate to source those objects a long time ago. However, only very recently a full solution for dimensions has been found by Garattini, thus the Casimir energy can be a source of traversable wormholes. We have recently shown that this can be generalized to higher dimensional spacetimes. Lately, Garattini sought to analyze the effects of Yukawa-type terms on shape functions and obtained promising results. However, his approach breaks down the usual relation between the energy density and the radial pressure of the Casimir field. In this work, we study the effects of the same three Yukawa-type corrective factors on the shape function of the Casimir wormhole keeping the usual way to obtain the radial pressure from the energy density. We show that, in addition to being able to construct traversable wormholes that satisfy all the necessary conditions, it is possible to obtain adequate constraints on the constants to recover the standard case with no double limit used by Garatinni. We show that, for some values of the Yukawa parameter, it is possible to generate a repulsive gravitational wormhole. Finally, we analyze the stability of the solutions and find the upper bounds for the Yukawa factor.
Full article
(This article belongs to the Special Issue Extreme Regimes of Classical and Quantum Gravity Models. Theory, Observations, and the Role of Symmetries)
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Open AccessArticle
On Laplacian Energy of r-Uniform Hypergraphs
Symmetry 2023, 15(2), 382; https://doi.org/10.3390/sym15020382 - 01 Feb 2023
Abstract
The matrix representations of hypergraphs have been defined via hypermatrices initially. In recent studies, the Laplacian matrix of hypergraphs, a generalization of the Laplacian matrix, has been introduced. In this article, based on this definition, we derive bounds depending pair-degree, maximum degree, and
[...] Read more.
The matrix representations of hypergraphs have been defined via hypermatrices initially. In recent studies, the Laplacian matrix of hypergraphs, a generalization of the Laplacian matrix, has been introduced. In this article, based on this definition, we derive bounds depending pair-degree, maximum degree, and the first Zagreb index for the greatest Laplacian eigenvalue and Laplacian energy of r-uniform hypergraphs and r-uniform regular hypergraphs. As a result of these bounds, Nordhaus–Gaddum type bounds are obtained for the Laplacian energy.
Full article
(This article belongs to the Special Issue Combinatorics, Discrete Mathematics, Symmetry and Regularity in Graphs, Graph Indices, Graph Parameters and Applications of Graph Theory)
Open AccessArticle
Modelling of Phase Diagrams and Continuous Cooling Transformation Diagrams of Medium Manganese Steels
Symmetry 2023, 15(2), 381; https://doi.org/10.3390/sym15020381 - 01 Feb 2023
Abstract
The aim of this manuscript was to study the influence of alloying elements on the phase transformation behavior in advanced high-strength multiphase steels. Continuous cooling transformation (CCT) and time–temperature–transformation (TTT) diagrams were calculated to analyze the stability of phases at variable time–temperature processing
[...] Read more.
The aim of this manuscript was to study the influence of alloying elements on the phase transformation behavior in advanced high-strength multiphase steels. Continuous cooling transformation (CCT) and time–temperature–transformation (TTT) diagrams were calculated to analyze the stability of phases at variable time–temperature processing parameters. The analyzed materials were lean-alloyed transformation induced plasticity (TRIP) medium manganese steels. The simulations of the phase diagrams, the stability of the phases during simulated heat treatments, and the chemical composition evolution diagrams were made using Thermo-Calc and JMatPro material simulation softwares. The influence of alloying elements, i.e., Mn and C, were studied in detail. The computational and modelling results allowed the influence of alloying elements on equilibrium and non-equilibrium phase diagrams and microstructural and chemical composition evolutions to be studied. Good symmetry and correlation between computational softwares were achieved. The study allows for future optimization of the heat-treatment temperature and time conditions of modern medium-Mn automotive sheet steels.
Full article
(This article belongs to the Special Issue Advances in Metallic Material and Symmetry/Asymmetry)
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Topics
Topic in
Applied Sciences, Electronics, Entropy, Mathematics, Symmetry
Quantum Information and Quantum Computing
Topic Editors: Durdu Guney, David PetrosyanDeadline: 20 March 2023
Topic in
Applied Sciences, Coatings, Energies, Sensors, Symmetry
IOT, Communication and Engineering
Topic Editors: Chun-Yen Chang, Teen-Hang Meen, Charles Tijus, Po-Lei LeeDeadline: 31 March 2023
Topic in
Applied Sciences, Energies, Mathematics, Signals, Symmetry
Engineering Mathematics
Topic Editors: Ioannis Dassios, Clemente CesaranoDeadline: 30 April 2023
Topic in
Fractal Fract, Mathematics, Axioms, Symmetry
Analysis and Controls of Time-Delay Systems with Perturbations: Theory and Application
Topic Editors: Chang-Hua Lien, Hamid Reza Karimi, Sundarapandian VaidyanathanDeadline: 15 May 2023

Conferences
Special Issues
Special Issue in
Symmetry
Dark Matter and Neutrino Physics
Guest Editor: Lorenzo PagnaniniDeadline: 15 February 2023
Special Issue in
Symmetry
Nature and Origin of Dark Matter and Dark Energy
Guest Editors: André Maeder, Vesselin G. GueorguievDeadline: 28 February 2023
Special Issue in
Symmetry
Advances in Theoretical and Computational Chemistry
Guest Editor: Miroslav IliašDeadline: 15 March 2023
Special Issue in
Symmetry
Advances in Symmetric Tensor Decomposition Methods
Guest Editor: Rafał ZdunekDeadline: 31 March 2023
Topical Collections
Topical Collection in
Symmetry
Symmetry in Ordinary and Partial Differential Equations and Applications
Collection Editor: Calogero Vetro