ALBERT

Description: We propose a derivative-free iterative method with fifth order of convergence for solving systems of nonlinear equations. The scheme is composed of three steps, of which the first two steps are that of third order Traub-Steffensen-type method and the last is derivative-free modification of Chebyshev’s method. Computational efficiency is examined and comparison between the efficiencies of presented technique with existing techniques is performed. It is proved that, in general, the new method is more efficient. Numerical problems, including those resulting from practical problems viz. integral equations and boundary value problems, are considered to compare the performance of the proposed method with existing methods. Calculation of computational order of convergence shows that the order of convergence of the new method is preserved in all the numerical examples, which is not so in the case of some of the existing higher order methods. Moreover, the numerical results, including the CPU-time consumed in the execution of program, confirm the accurate and efficient behavior of the new technique.

Description: The elementary symmetric functions play a crucial role in the study of zeros of non-zero polynomials in C [ x ] , and the problem of finding zeros in Q [ x ] leads to the definition of algebraic and transcendental numbers. Recently, Marques studied the set of algebraic numbers in the form P ( T ) Q ( T ) . In this paper, we generalize this result by showing the existence of algebraic numbers which can be written in the form P 1 ( T ) Q 1 ( T ) ⋯ P n ( T ) Q n ( T ) for some transcendental number T, where P 1 , … , P n , Q 1 , … , Q n are prescribed, non-constant polynomials in Q [ x ] (under weak conditions). More generally, our result generalizes results on the arithmetic nature of z w when z and w are transcendental.

Description: Machine learning algorithms have been widely used in the field of client credit assessment. However, few of the algorithms have focused on and solved the problems of concept drift and class imbalance. Due to changes in the macroeconomic environment and markets, the relationship between client characteristics and credit assessment results may change over time, causing concept drift in client credit assessments. Moreover, client credit assessment data are naturally asymmetric and class imbalanced because of the screening of clients. Aiming at solving the joint research issue of concept drift and class imbalance in client credit assessments, in this paper, a novel sample-based online learning ensemble (SOLE) for client credit assessment is proposed. A novel multiple time scale ensemble classifier and a novel sample-based online class imbalance learning procedure are proposed to handle the potential concept drift and class imbalance in the client credit assessment data streams. The experiments are carried out on two real-world client credit assessment cases, which present a comprehensive comparison between the proposed SOLE and other state-of-the-art online learning algorithms. In addition, the base classifier preference and the computing resource consumption of all the comparative algorithms are tested. In general, SOLE achieves a better performance than other methods using fewer computing resources. In addition, the results of the credit scoring model and the Kolmogorov–Smirnov (KS) test also prove that SOLE has good practicality in actual client credit assessment applications.

Description: This paper adapts the multivariate optimal control theory to a Riemannian setting. In this sense, a coherent correspondence between the key elements of a standard optimal control problem and several basic geometric ingredients is created, with the purpose of generating a geometric version of Pontryagin’s maximum principle. More precisely, the local coordinates on a Riemannian manifold play the role of evolution variables (“multitime”), the Riemannian structure, and the corresponding Levi–Civita linear connection become state variables, while the control variables are represented by some objects with the properties of the Riemann curvature tensor field. Moreover, the constraints are provided by the second order partial differential equations describing the dynamics of the Riemannian structure. The shift from formal analysis to optimal Riemannian control takes deeply into account the symmetries (or anti-symmetries) these geometric elements or equations rely on. In addition, various submanifold integral cost functionals are considered as controlled payoffs.

Description: Positioning devices allow users’ movement to be recorded. The GPS (Global Positioning System) trajectory data typically consists of spatiotemporal points, which make up the major part of the big data concerning urban life. Existing knowledge extraction methods about the trajectory share a general limitation—they only investigate data from a spatiotemporal aspect, but fail to take the semantic information of trajectories into consideration. Therefore, extracting the semantic information of trajectories with the context of big data is challenging pattern recognition task that has practical application prospects. In this paper, a system is proposed to extract the semantic trajectory patterns of positioning device users. Firstly, a spatiotemporal threshold and clustering based pre-processing model is proposed to process the raw data. Then, we design a probabilistic generative model to annotate the semantic information of each trajectory after the pre-processing procedure. Finally, we apply the PrefixSpan algorithm to mine the semantic trajectory patterns. We verify our system on a large dataset of users’ real trajectories over a period of 5 years in Beijing, China. The results of the experiment indicate that our system produces meaningful patterns.

Description: Three-way decisions, as a decision-making mode which is consistent with human cognition, have been widely used in various fields. In this paper, we fuse the theory of reliability into the three-way decisions method, replace the conditional probability in the three-way decisions method with reliability, and then propose a novel three-way decisions method. We also describe the loss functions with single-valued triangular neutrosophic numbers (SVTNNs) and propose an operator to calculate the score function of triangular neutrosophic numbers. Then, the result of decision is attained according to the principle of minimizing loss. Finally, we apply this method to the overhaul of machines in a factory, which proves the practicability and effectiveness of the proposed methods.

Description: The solutions for many real life problems may be obtained by interpreting the given problem mathematically in the form f ( x ) = x . One such example is that of the famous Borsuk–Ulam theorem in which, using some fixed point argument, it can be guaranteed that at any given time we can find two diametrically opposite places in a planet with same temperature. Thus, the correlation of symmetry is inherent in the study of fixed point theory. In this article, some new results concerning coincidence and a common fixed point for an A φ -contraction and a generalized ϕ -type weak contraction are established. We prove our results for set valued maps without using continuity of the corresponding maps and completeness of the relevant space. Our results generalize and extend several existing results. Some new examples are given to demonstrate the generality and non-triviality of our results.

Description: Studies related to pattern recognition and visualization using computer technology have been introduced. In particular, deep neural networks (DNNs) provide good performance for image, speech, and pattern recognition. However, a poisoning attack is a serious threat to a DNN’s security. A poisoning attack reduces the accuracy of a DNN by adding malicious training data during the training process. In some situations, it may be necessary to drop a specifically chosen class of accuracy from the model. For example, if an attacker specifically disallows nuclear facilities to be selectively recognized, it may be necessary to intentionally prevent unmanned aerial vehicles from correctly recognizing nuclear-related facilities. In this paper, we propose a selective poisoning attack that reduces the accuracy of only the chosen class in the model. The proposed method achieves this by training malicious data corresponding to only the chosen class while maintaining the accuracy of the remaining classes. For the experiment, we used tensorflow as the machine-learning library as well as MNIST, Fashion-MNIST, and CIFAR10 as the datasets. Experimental results show that the proposed method can reduce the accuracy of the chosen class by 43.2%, 41.7%, and 55.3% in MNIST, Fashion-MNIST, and CIFAR10, respectively, while maintaining the accuracy of the remaining classes.

Description: We define a family of observables for abelian Yang-Mills fields associated to compact regions U ⊆ M with smooth boundary in Riemannian manifolds. Each observable is parametrized by a first variation of solutions and arises as the integration of gauge invariant conserved current along admissible hypersurfaces contained in the region. The Poisson bracket uses the integration of a canonical multisymplectic current.

Description: Video analysis is currently the main non-intrusive method for the study of collective behavior. However, 3D-to-2D projection leads to overlapping of observed objects. The situation is further complicated by the absence of stall shapes for the majority of living objects. Fortunately, living objects often possess a certain symmetry which was used as a basis for morphological fingerprinting. This technique allowed us to record forms of symmetrical objects in a pose-invariant way. When combined with image skeletonization, this gives a robust, nonlinear, optimization-free, and fast method for detection of overlapping objects, even without any rigid pattern. This novel method was verified on fish (European bass, Dicentrarchus labrax, and tiger barbs, Puntius tetrazona) swimming in a reasonably small tank, which forced them to exhibit a large variety of shapes. Compared with manual detection, the correct number of objects was determined for up to almost 90 % of overlaps, and the mean Dice-Sørensen coefficient was around 0.83 . This implies that this method is feasible in real-life applications such as toxicity testing.

Description: In this paper, we are concerned with a nonlinear system containing some essential symmetrical structures (e.g., cross-diffusion) in the two-dimensional setting, which is proposed to model the biological transport networks. We first provide an a priori blow-up criterion of strong solution of the corresponding Cauchy problem. Based on this, we also establish a priori upper bounds to strong solution for all positive times.

Description: We first formulate the mixed backward in time problem in the context of thermoelasticity for dipolar materials. To prove the consistency of this mixed problem, our first main result is regarding the uniqueness of the solution for this problem. This is obtained based on some auxiliary results, namely, four integral identities. The second main result is regarding the temporal behavior of our thermoelastic body with a dipolar structure. This behavior is studied by means of some relations on a partition of various parts of the energy associated to the solution of the problem.

Description: Feature interaction is a newly proposed feature relevance relationship, but the unintentional removal of interactive features can result in poor classification performance for this relationship. However, traditional feature selection algorithms mainly focus on detecting relevant and redundant features while interactive features are usually ignored. To deal with this problem, feature relevance, feature redundancy and feature interaction are redefined based on information theory. Then a new feature selection algorithm named CMIFSI (Conditional Mutual Information based Feature Selection considering Interaction) is proposed in this paper, which makes use of conditional mutual information to estimate feature redundancy and interaction, respectively. To verify the effectiveness of our algorithm, empirical experiments are conducted to compare it with other several representative feature selection algorithms. The results on both synthetic and benchmark datasets indicate that our algorithm achieves better results than other methods in most cases. Further, it highlights the necessity of dealing with feature interaction.

Description: A chaotic system and two Nonlinear Feadback Shift Registers (NFSRs) are used to generate a new stream cipher in this paper. This design can be used for efficient encryption in resource-constrained devices or environments. The chaotic system is quantified and integrated with two NFSRs based on the technology of Field Programmable Gate Array (FPGA). Many analyses are made from the angle of entropy in order to verify the cryptographic characteristics of the stream cipher, and National Institute of Standards and Technology (NIST) statistical test is completed to analyze the cipher. The test results show that the stream cipher here has good cryptographic characteristics.

Description: In this paper, we present a new computational method for solving linear Fredholm integral equations of the second kind, which is based on the use of B-spline quasi-affine tight framelet systems generated by the unitary and oblique extension principles. We convert the integral equation to a system of linear equations. We provide an example of the construction of quasi-affine tight framelet systems. We also give some numerical evidence to illustrate our method. The numerical results confirm that the method is efficient, very effective and accurate.

Description: The security issue on the physical layer is of significant challenge yet of paramount importance for 5G communications. In some previous works, transmit power allocation has already been studied for orthogonal frequency division multiplexing (OFDM) secure communication with Gaussian channel inputs for both a single user and multiple users. Faced with peak transmission power constraints, we adopt discrete channel inputs (e.g., equiprobable Quadrature Phase Shift Keying (QPSK) with symmetry) in a practical communication system, instead of Gaussian channel inputs. Finite-alphabet inputs impose a more significant challenge as compared with conventional Gaussian random inputs for the multiuser wiretap OFDM systems. This paper considers the joint resource allocation in frequency-domain artificial noise (AN) assisted multiuser wiretap OFDM channels with discrete channel inputs. This security problem is formulated as nonconvex sum secrecy rate optimization by jointly optimizing the subcarrier allocation, information-bearing power, and AN-bearing power. To this end, with a suboptimal subcarrier allocation scheme, we propose an efficient iterative algorithm to allocate the power between the information and the AN via the Lagrange duality method. Finally, we carry out some numerical simulations to demonstrate the performance of the proposed algorithm.

Description: A Friedmann–Robertson–Walker Universe was studied with a dark energy component represented by a quintessence field. The Lagrangian for this system, hereafter called the Friedmann–Robertson–Walker–quintessence (FRWq) system, was presented. It was shown that the classical Lagrangian reproduces the usual two (second order) dynamical equations for the radius of the Universe and for the quintessence scalar field, as well as a (first order) constraint equation. Our approach naturally unified gravity and dark energy, as it was obtained that the Lagrangian and the equations of motion are those of a relativistic particle moving on a two-dimensional, conformally flat spacetime. The conformal metric factor was related to the dark energy scalar field potential. We proceeded to quantize the system in three different schemes. First, we assumed the Universe was a spinless particle (as it is common in literature), obtaining a quantum theory for a Universe described by the Klein–Gordon equation. Second, we pushed the quantization scheme further, assuming the Universe as a Dirac particle, and therefore constructing its corresponding Dirac and Majorana theories. With the different theories, we calculated the expected values for the scale factor of the Universe. They depend on the type of quantization scheme used. The differences between the Dirac and Majorana schemes are highlighted here. The implications of the different quantization procedures are discussed. Finally, the possible consequences for a multiverse theory of the Dirac and Majorana quantized Universe are briefly considered.

Description: The main contribution in this paper is to construct an implicit fixed coefficient Block Backward Differentiation Formulas denoted as A ( α ) -BBDF with equal intervals for solving stiff ordinary differential equations (ODEs). To avoid calculating the differentiation coefficients at each step of the integration, the coefficients of the formulas will be stored, with the intention of optimizing the performance in terms of precision and computational time. The plots of their A ( α ) stability region are provided, and the order of the method is also verified. The necessary conditions for convergence, such as the consistency and zero stability of the method, are also discussed. The numerical results clearly showed the efficiency of the method in terms of accuracy and execution time as compared to other existing methods in the scientific literature.

Description: Each loop in a multi-loop rail network consists of two segments, both of which have roughly the same conditions and mileage and are approximately symmetrical. This paper is devoted to optimizing the paths of trains formed at the loading area in a multi-loop rail network. To attain this goal, three different situations are analyzed, and two models are proposed for networks with adequate and inadequate capabilities. Computational experiments are also carried out using the commercial software Lingo, with the branch and bound algorithm. The results show that the models can achieve the same solution with different solution times. To solve the problem of path selection for large-scale train flows, a genetic algorithm is also designed and proves to perform well in a set of computational experiments.

Description: This paper is concerned with the design of an improved El-Gamal cryptosystem based on chaos synchronization. The El-Gamal cryptosystem is an asymmetric encryption algorithm that must use the public and private keys, respectively, in the encryption and decryption processes. However, in our design, the public key does not have to appear in the public channel. Therefore, this proposed improved El-Gamal cryptosystem becomes a symmetric-like encryption algorithm. First, a discrete sliding mode controller is proposed to ensure the synchronization of master and slave chaotic systems; next, a novel improved El-Gamal cryptosystem is presented. In the traditional El-Gamal cryptosystem, the public key is static and needs to be open which provides an opportunity to attack. However, in this improved design, due to the chaos synchronization, the public key becomes dynamic and does not appear in public channels. As a result, drawbacks of long cipher text and time-consuming calculation in the traditional El-Gamal cryptosystem are all removed. Finally, several performance tests and comparisons have shown the efficiency and security of the proposed algorithm.

Description: In this paper, we focus on methods to prevent shoulder-surfing attacks. We initially adopted digraph substitution rules from PlayFair cipher as our proposed method. PlayFair cipher is a modern cryptography method, which exists at the intersection of the disciplines of mathematics and computer science. However, according to our preliminary study it was insufficient to prevent shoulder-surfing attacks. Thus, a new method had to be proposed. In this new proposed method, we improvised the digraph substitution rules and used these rules together with an output feedback method to determine a pass-image. Our proposed method was evaluated with a user study. The results showed our proposed method was robust against both direct observation and video-recorded shoulder-surfing attacks.

Description: In this paper, by applying the decision theorem of the Schur-power convex function, the Schur-power convexity of a class of complete symmetric functions are studied. As applications, some new inequalities are established.

Description: A competing risks model under progressively type II censored data following the Rayleigh distribution is considered. We establish the maximum likelihood estimation for unknown parameters and compute the observed information matrix and the expected Fisher information matrix to construct the asymptotic confidence intervals. Moreover, we obtain the Bayes estimation based on symmetric and non-symmetric loss functions, that is, the squared error loss function and the general entropy loss function, and the highest posterior density intervals are also derived. In addition, a simulation study is presented to assess the performances of different methods discussed in this paper. A real-life data set analysis is provided for illustration purposes.

Description: A Couette-Poiseuille flow between parallel plates saturated with porous medium is studied with emphasis on viscous dissipation effect on the temperature field; assuming a fully developed flow, with both plates subjected to unequal and uniform heat flux. Temperature field and Nusselt number are derived as a function of Brinkman number and porous medium shape factor. By specifying the ratio of wall to mean velocity as one, the resulting velocity and temperature fields attribute to a significant increase in Nusselt number for the moving wall as the permeability of porous medium increases. Increased permeability signifies competing effect between enhanced convection in the proximity of the moving wall and higher local viscous dissipation. When the former effect dominates, heat transfer coefficient increases. Effects of Reynolds number on the temperature field is elucidated, including a comparison between a microchannel and conventional duct to evaluate the characteristic length scale effect. As Reynolds number goes up in a microchannel, heat generation in the form of viscous dissipation intensifies and overrides the convection effect, causing an increase in the highest temperature along the duct on the contrary to the findings in conventional duct.

Description: In this study, we present an analytical study on blood flow analysis through with a tapered porous channel. The blood flow was driven by the peristaltic pumping. Thermal radiation effects were also taken into account. The convective and slip boundary conditions were also applied in this formulation. These conditions are very helpful to carry out the behavior of particle movement which may be utilized for cardiac surgery. The tapered porous channel had an unvarying wave speed with dissimilar amplitudes and phase. The non-dimensional analysis was utilized for some approximations such as the proposed mathematical modelling equations were modified by using a lubrication approach and the analytical solutions for stream function, nanoparticle temperature and volumetric concentration profiles were obtained. The impacts of various emerging parameters on the thermal characteristics and nanoparticles concentration were analyzed with the help of computational results. The trapping phenomenon was also examined for relevant parameters. It was also observed that the geometric parameters, like amplitudes, non-uniform parameters and phase difference, play an important role in controlling the nanofluids transport phenomena. The outcomes of the present model may be applicable in the smart nanofluid peristaltic pump which may be utilized in hemodialysis.

Description: The purpose of this article is to define almost ( α , F σ ) -contractions and establish some generalized fixed-point results for a new class of contractive conditions in the setting of complete metric spaces. In application, we apply our fixed-point theorem to prove the existence theorem for Fredholm integral inclusions ϖ ( t ) ∈ f ( t ) + ∫ 0 1 K ( t , s , x ( s ) ) ϑ s , t ∈ [ 0 , 1 ] where f ∈ C [ 0 , 1 ] is a given real-valued function and K : [ 0 , 1 ] × [ 0 , 1 ] × R → K c v ( R ) is a given multivalued operator, where K c v represents the family of nonempty compact and convex subsets of R and ϖ ∈ C [ 0 , 1 ] is the unknown function. We also provide a non-trivial example to show the significance of our main result.

Description: Composite quantile regression (CQR) estimation and inference are studied for varying coefficient models with response data missing at random. Three estimators including the weighted local linear CQR (WLLCQR) estimator, the nonparametric WLLCQR (NWLLCQR) estimator, and the imputed WLLCQR (IWLLCQR) estimator are proposed for unknown coefficient functions. Under some mild conditions, the proposed estimators are asymptotic normal. Simulation studies demonstrate that the unknown coefficient estimators with IWLLCQR are superior to the other two with WLLCQR and NWLLCQR. Moreover, bootstrap test procedures based on the IWLLCQR fittings is developed to test whether the coefficient functions are actually varying. Finally, a type of investigated real-life data is analyzed to illustrated the applications of the proposed method.

Description: This paper reports on the Walnut Digital Signature Algorithm (WalnutDSA), which is an asymmetric signature scheme recently presented for standardization at the NIST call for post-quantum cryptographic constructions. WalnutDSA is a group theoretical construction, the security of which relies on the hardness of certain problems related to an action of a braid group on a finite set. In spite of originally resisting the typical attacks succeeding against this kind of construction, soon different loopholes were identified rendering the proposal insecure (and finally, resulting in it being excluded from Round 2 of the NIST competition). Some of these attacks are related to the well-structured and symmetric masking of certain secret elements during the signing process. We explain the design principles behind this proposal and survey the main attack strategies that have succeeded, contradicting its claimed security properties, as well as the recently-proposed ideas aimed at overcoming these issues.

Description: Analysis of motion symmetry constitutes an important area with many applications in engineering, robotics, neurology and biomedicine. This paper presents the use of microelectromechanical sensors (MEMS), including accelerometers and gyrometers, to acquire data via mobile devices so as to monitor physical activities and their irregularities. Special attention is devoted to the analysis of the symmetry of the motion of the body when the same exercises are performed by the right and the left limb. The analyzed data include the motion of the legs on a home exercise bike under different levels of load. The method is based on signal analysis using the discrete wavelet transform and the evaluation of signal segment features such as the relative energy at selected decomposition levels. The subsequent classification of the evaluated features is performed by k-nearest neighbours, a Bayesian approach, a support vector machine, and neural networks. The highest average classification accuracy attained is 91.0% and the lowest mean cross-validation error is 0.091, resulting from the use of a neural network. This paper presents the advantages of the use of simple sensors, their combination and intelligent data processing for the numerical evaluation of motion features in the rehabilitation and monitoring of physical activities.

Description: Multipath diversity significantly impacts multipath transmission quality. Enough multipath diversity would minimize the negative influence brought by an individual path, thus improving tolerance capability of network congestion and failure. However, multipath diversity is hard to guarantee on overlay networks because of inaccurate awareness of underlay network and multipath generating methods considering little about underlay diversity. In this paper, we design a multi-dimension spatial method for topology awareness and multipath generating. Analyzing that the complicated underlay networks with multiple autonomous systems reduce the accuracy of network positioning for topology awareness, we decompose the underlay networks into multiple dimensions, namely intra and inter autonomous system dimensions. We generate independent views for each autonomous system and merge views by embedding exchange points. Then, we design some spatial mechanisms to evaluate link diversity and to constrain multipath generating. Based on the multi-dimensional view, multipath generating is conducted in inter and intra autonomous system phases. Experiments demonstrate that the proposed method improves topology awareness accuracy and guarantees multipath diversity better and the transmission quality is improved.

Description: In this paper, a kernel recursive maximum Versoria-like criterion (KRMVLC) algorithm has been constructed, derived, and analyzed within the framework of nonlinear adaptive filtering (AF), which considers the benefits of logarithmic second-order errors and the symmetry maximum-Versoria criterion (MVC) lying in reproducing the kernel Hilbert space (RKHS). In the devised KRMVLC, the Versoria approach aims to resist the impulse noise. The proposed KRMVLC algorithm was carefully derived for taking the nonlinear channel equalization (NCE) under different non-Gaussian interferences. The achieved results verify that the KRMVLC is robust against non-Gaussian interferences and performs better than those of the popular kernel AF algorithms, like the kernel least-mean-square (KLMS), kernel least-mixed-mean-square (KLMMN), and Kernel maximum Versoria criterion (KMVC).

Description: GOX (3QVR), glucose oxidase, is an oxidoreductase enzyme, which has found many applications in biotechnology and modern diagnostics with typical assays including biosensors useful in the determination of free glucose in body fluids. PEI (polyethylenimines) are polymer molecules made up of amine groups and two aliphatic carbons, which are cyclically repeated. PEI are transfection reagents which, using positively charged units, bind well to anionic DNA residues. During the studies on GOX, PEI were used both in their linear and branched structures. Rhombellanes, RBL, are structures decorated with rhombs/squares. The aim of the paper is to study the interactions of two kinds of linear ligands: PEIs (Polyethylenimines) and CHRs (ethers of Hexahydroxy-cyclohexane) with the glucose oxidase enzyme, GOX (3QVR). To understand the structure-activity relationship between the GOX enzyme and the linear ligands PEI and CHR, two steps of docking simulation were performed; mapping the whole area of the 3QVR enzyme and docking on the first and second surface of the enzyme, separately. The studied ligands interacted with amino acids of GOX inside the protein and on its surface, with stronger and shorter bonds inside of the protein. However, long chain ligands can only interact with amino acids on the external protein surface. After the study, two domains of the enzyme were clearly evidenced; the external surface domain more easily creates interactions with ligands, particularly with CHR ligands.

Description: In this article, we study an extension of the sinh Cauchy model in order to obtain asymmetric bimodality. The behavior of the distribution may be either unimodal or bimodal. We calculate its cumulative distribution function and use it to carry out quantile regression. We calculate the maximum likelihood estimators and carry out a simulation study. Two applications are analyzed based on real data to illustrate the flexibility of the distribution for modeling unimodal and bimodal data.

Description: Cisplatin (cisPt) is one of the strongest anticancer agents with proven clinical activity against a wide range of solid tumors. Its mode of action has been linked to its ability to crosslink with the canonical purine bases, primarily with guanine. Theoretical studies performed at the molecular level suggest that such nonspecific interactions can also take place with many competitive compounds, such as vitamins of the B group, containing aromatic rings with lone-pair orbitals. This might be an indicator of reduction of the anticancer therapeutic effects of the Cisplatin drug in the presence of vitamins of the B group inside the cell nucleus. That is why it seems to be important to connect CisPt with nanostructures and in this way prevent the drug from combining with the B vitamins. As a proposal for a new nanodrug, an attempt was made to implement Cispaltin (CisPt) ligand on functionalized C60 fullerenes and on a cube rhombellane homeomorphic surface. The symmetry of the analyzed nanostructures is an important factor determining the mutual affinity of the tested ligand and nanocarriers. The behavior of Cisplatin with respect to rhombellane homeomorphs and functionalized fullerenes C60, in terms of their (interacting) energy, geometry and topology was studied and a detailed analysis of structural properties after docking showed many interesting features.

Description: It is known that every element in the alternating group A n , with n ≥ 5 , can be written as a product of at most two Engel words of arbitrary length. However, it is still unknown if every element in an alternating group is an Engel word of Arbitrary length. In this paper, a different approach to this problem is presented, getting new results for small alternating groups.

Description: As a global-optimized and naturally inspired algorithm, particle swarm optimization (PSO) is characterized by its high quality and easy application in practical optimization problems. However, PSO has some obvious drawbacks, such as early convergence and slow convergence speed. Therefore, we introduced some appropriate improvements to PSO and proposed a novel chaotic PSO variant with arctangent acceleration coefficient (CPSO-AT). A total of 10 numerical optimization functions were employed to test the performance of the proposed CPSO-AT algorithm. Extensive contrast experiments were conducted to verify the effectiveness of the proposed methodology. The experimental results showed that the proposed CPSO-AT algorithm converges quickly and has better stability in numerical optimization problems compared with other PSO variants and other kinds of well-known optimal algorithms.

Description: Race walking has been theoretically described as a walking gait in which no flight time is allowed and high travelling speed, comparable to running (3.6–4.2 m s−1), is achieved. The aim of this study was to mechanically understand such a “hybrid gait” by analysing the ground reaction forces (GRFs) generated in a wide range of race walking speeds, while comparing them to running and walking. Fifteen athletes race-walked on an instrumented walkway (4 m) and three-dimensional GRFs were recorded at 1000 Hz. Subjects were asked to performed three self-selected speeds corresponding to a low, medium and high speed. Peak forces increased with speeds and medio-lateral and braking peaks were higher than in walking and running, whereas the vertical peaks were higher than walking but lower than running. Vertical GRF traces showed two characteristic patterns: one resembling the “M-shape” of walking and the second characterised by a first peak and a subsequent plateau. These different patterns were not related to the athletes’ performance level. The analysis of the body centre of mass trajectory, which reaches its vertical minimum at mid-stance, showed that race walking should be considered a bouncing gait regardless of the presence or absence of a flight phase.

Description: This paper deals with separable and entangled qudits | ψ d 〉 (quantum states in dimension d) constructed from Dicke states made of N = d − 1 qubits. Such qudits present the property to be totally symmetric under the interchange of the N qubits. We discuss the notion of perma-concurrence P d for the qudit | ψ d 〉 , introduced by the authors (Entropy 2018, 20, 292), as a parameter for characterizing the entanglement degree of | ψ d 〉 . For d = 3 , the perma-concurrence P 3 constitutes an alternative to the concurrence C for symmetric two-qubit states. We give several expressions of P d (in terms of matrix permanent and in terms of unit vectors of R 3 pointing on the Bloch sphere) and precise the range of variation of P d (going from separable to maximally entangled states). Numerous examples are presented for P d . Special attention is devoted to states of W type and to maximally entangled states of Bell and Greenberger–Horne–Zeilinger type.

Description: In social and health sciences, many statistical procedures and estimation techniques rely on the underlying distributional assumption of normality of the data. Non-normality may lead to incorrect statistical inferences. This study evaluates the performance of selected normality tests within the stringency framework for skewed alternative space. The stringency concept allows us to rank the tests uniquely. The Bonett and Seier test (Tw) turns out to represent the best statistics for slightly skewed alternatives and the Anderson–Darling (AD); Chen–Shapiro (CS); Shapiro–Wilk (W); and Bispo, Marques, and Pestana (BCMR) statistics are the best choices for moderately skewed alternative distributions. The maximum loss of Jarque–Bera (JB) and its robust form (RJB), in terms of deviations from the power envelope, is greater than 50%, even for large sample sizes, which makes them less attractive in testing the hypothesis of normality against the moderately skewed alternatives. On balance, all selected normality tests except Tw and Daniele Coin’s COIN-test performed exceptionally well against the highly skewed alternative space.

Description: With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users.

Description: Metric learning aims to measure the similarity among samples while using an optimal distance metric for learning tasks. Metric learning methods, which generally use a linear projection, are limited in solving real-world problems demonstrating non-linear characteristics. Kernel approaches are utilized in metric learning to address this problem. In recent years, deep metric learning, which provides a better solution for nonlinear data through activation functions, has attracted researchers' attention in many different areas. This article aims to reveal the importance of deep metric learning and the problems dealt with in this field in the light of recent studies. As far as the research conducted in this field are concerned, most existing studies that are inspired by Siamese and Triplet networks are commonly used to correlate among samples while using shared weights in deep metric learning. The success of these networks is based on their capacity to understand the similarity relationship among samples. Moreover, sampling strategy, appropriate distance metric, and the structure of the network are the challenging factors for researchers to improve the performance of the network model. This article is considered to be important, as it is the first comprehensive study in which these factors are systematically analyzed and evaluated as a whole and supported by comparing the quantitative results of the methods.

Description: Aviation bearing assembled detection is the final barrier to quality and safety. Therefore, an accurate detection method of aviation bearing that is based on local characteristics is designed to solve the detection problem of mis-assembly and miss-assembly of balls in aviation bearing assembled. When considering the spatial limitation of aviation bearing assembled image acquisition, the dynamic distribution of balls and the interference of lubricating grease on the surface, a dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is designed to achieve the accurate segmentation of the local ball region of aviation bearing. Subsequently, an incomplete circle fitting algorithm is designed based on the segmented local ball image and Hough transform principle. These two algorithms make the measurement error of aviation bearing ball size less than 100 μm. Using bearings validates the algorithm. The results show that the accuracy of dynamic local ball segmentation model that is based on U-Net network with symmetrical structure is over 99%. At the same time, on the basis of accurate segmentation in aviation bearing local ball, the designed Hough circle algorithm is used for circle detection. The experimental results show that the false detection rate of mis-assembly and miss-assembly of balls is less than 3%. Further, the goal of zero-missed detection of mis-assembly and miss-assembly of balls in aviation bearing is achieved. The accurate segmentation of aviation bearing local ball and the effective identification of mis-assembly and miss-assembly of balls are realized. This method can provide a theory for the improvement of mis-assembly and miss-assembly of balls detection in aviation bearing. Furthermore, it has high application value.

Description: A key aspect of modern drug research is the development of delivery methods that ensure the possibility of implementing targeted therapy for a specific biological target. The use of nanocarriers enables to achieve this objective, also allowing to reduce the toxicity of used substances and often extending their bioavailability. Through the application of docking methods, the possibility of using cube rhombellanes as potential carriers for two oxindole derivatives was analyzed. In the studies, compounds identified as inhibitors of the CDK2 enzyme and a set of nanostructures proposed by the Topo Cluj Group were used. The popular fullerene molecule C60 was used as the reference system. The estimated binding affinities and structures of obtained complexes show that use of functionalized cube rhombellanes containing hydrogen bond donors and acceptors in their external molecular shell significantly increases ligand affinity toward considered nanocariers, compared to classic fullerenes. The presented values also allow to state that an important factor determining the mutual affinity of the tested ligands and nanostructures is the symmetry of the analyzed nanocarriers and its influence on the distribution of binding groups (aromatic systems, donors and acceptors of hydrogen bonds) on the surface of nanoparticles.

Description: In the integrated services digital broadcasting-terrestrial (ISDB-T) system, the combination of digital terrestrial transmission and MPEG-4 advanced video coding (MPEG-4 AVC) has offered ways to provide a variety of digital high-definition television (HDTV) programs. Using band segmented transmission orthogonal frequency division multiplexing (BST-OFDM), the delivery of innovative video-on-demand and HDTV services is supported. To take full advantage of the attractive benefits of BST-OFDM, it is important to estimate integer frequency offset (IFO) without a priori knowledge on the segment type that is transmitted over transmission and the multiplexing configuration control (TMCC) signal. To address this issue, an efficient IFO detection method is proposed for the ISDB-T system employing BST-OFDM. To enable IFO detection independent of the segment type, information-bearing TMCC signals that are asymmetrically distributed in the frequency domain are used as pilot symbols. Numerical analysis is performed to present the relationship between error probability and design parameter. We show via the numerical results that the multiple transmitted TMCC information is efficiently used for blind estimation of the IFO, achieving robust estimation in the presence of the fractional frequency offset.

Description: In the present work we consider a numerical solution for laminar, incompressible, and steady oblique stagnation point flow of Cu − water nanofluid over a stretching/shrinking sheet with mass suction S . We make use of the Cattaneo–Christov heat flux model to develop the equation of energy and investigate the qualities of surface heat transfer. The governing flow and energy equations are modified into the ordinary differential equations by similarity method for reasonable change. The subsequent ordinary differential equations are illuminated numerically through the function bvp4c in MATLAB. The impact of different flow parameters for example thermal relaxation parameter, suction parameter, stretching/shrinking parameter, free stream parameter, and nanoparticles volume fraction on the skin friction coefficient, local Nusselt number, and streamlines are contemplated and exposed through graphs. It turns out that the lower branch solution for the skin friction coefficient becomes singular in shrinking area, although the upper branch solution is smooth in both stretching and shrinking domain. For oblique stagnation-point flow the streamlines pattern are not symmetric, and reversed phenomenon are detected close to the shrinking surface. Also, we observed that the free stream parameter changes the direction of the oncoming flow and controls the obliqueness of the flow. The existing work mostly includes heat and mass transfer as a mechanism for improving the heat transfer rate, which is the main objective of the authors.

Description: The most popular way of learning oriental calligraphy has been by practicing the calligraphy under the supervision of a human teacher, but finding a good instructor can be difficult. There are a number of studies in the literature that have evaluated calligraphic characters in holistic ways, but such systems do not support detailed supervision of scripting errors. This study proposes a Kanji calligraphy learning system with computerized supervision and analyzes the learning efficiency of the system, where the supervision includes symmetries between strokes. The proposed system compares a written calligraphic character of a user to the model of a human expert, and indicates error spots with explanations. An experiment with 22 participants proved that this system was more efficient at reducing the number of scripting errors in comparison to the traditional manner of a human expert. The main contribution of this paper was to identify and reveal the efficacy of computerized supervision in comparison to a human supervisor. The proposed system decreased the writing-error-rates of learners from 32.7% to 3.4%, whereas the traditional practice reduced the error rates from 31.0% to 6.8%. This result shows that computerized supervision is more efficient than human supervision for learning calligraphy.

Description: A balance (symmetry) between socio-cultural and socio-economic benefits as a part of the economic, social, and cultural development policy of each city and country should be assured when converting built heritage. To anticipate building conversion priorities and opportunities, modern technologies can be employed. However, currently the activity of reconstruction of heritage buildings is part of the construction domain wherein modern digital technologies have been the least ever applied. Therefore, photogrammetry and the 3D modeling of existing heritage buildings was suggested. A case study of Sapieha Palace, built in the Baroque style in 1689–1691 in Vilnius, Lithuania was explored in this research. The applied technologies and software (Agisoft Photoscan, Autodesk ReCap and Autodesk Revit) allowed for the creation of a high quality and accurate model involving both the textured exterior of the building and the interior layout. In addition, the valuable features of a building were identified and marked in a three-dimensional digital model. Based on the model, the authors formulated possible conversion alternatives of the building and identified the associated decision-making criteria, as well as determined their relative significance by an expert survey method. The authors suggested the application of the multiple criteria decision making (MCDM) method under uncertainty, namely the rough weighted aggregated sum product assessment (WASPAS), for ranking alternatives according to multiple criteria. Therefore, the suggested integration of modern digital technologies and decision-making models helps to assure the rational conversion decision of built cultural heritage based on high accuracy data as well as contributing to the sustainable development of engineering processes.

Description: Thermodynamic properties of the s–wave symmetry superconducting phase in three selected structures of the BaGe 3 compound ( P 6 3 / m m c , A m m 2 , and I 4 / m m m ) were discussed in the context of DFT results obtained for the Eliashberg function. This compound may enable the implementation of systems for quantum information processing. Calculations were carried out within the Eliashberg formalism due to the fact that the electron–phonon coupling constant falls within the range λ ∈ 0.73 , 0.86 . The value of the Coulomb pseudopotential was assumed to be 0.122 , in accordance with the experimental results. The value of the Coulomb pseudopotential was assumed to be 0.122 , in accordance with the experimental results. The existence of the superconducting state of three different critical temperature values, namely, 4.0 K, 4.5 K and 5.5 K, depending on the considered structure, was stated. We determined the differences in free energy ( Δ F ) and specific heat ( Δ C ) between the normal and the superconducting states, as well as the thermodynamic critical field ( H c ) as a function of temperature. A drop in the H c value to zero at the temperature of 4.0 K was observed for the P 6 3 / m m c structure, which is in good accordance with the experimental data. Further, the values of the dimensionless thermodynamic parameters of the superconducting state were estimated as: R Δ = 2 Δ ( 0 ) / k B T c ∈ { 3.68 , 3.8 , 3.8 } , R C = Δ C ( T c ) / C N ( T c ) ∈ { 1.55 , 1.71 , 1.75 } , and R H = T c C N ( T c ) / H c 2 ( 0 ) ∈ { 0.168 , 0.16 , 0.158 } , which are slightly different from the predictions of the Bardeen–Cooper–Schrieffer theory ( [ R Δ ] B C S = 3.53 , [ R C ] B C S = 1.43 , and [ R H ] B C S = 0.168 ). This is caused by the occurrence of small retardation and strong coupling effects.

Description: A review. The question of homochirality is an intriguing problem in the field of chemistry, and is deeply related to the origin of life. Though amphiphiles and their supramolecular assembly have attracted less attention compared to biomacromolecules such as RNA and proteins, the lipid world hypothesis sheds new light on the origin of life. This review describes how amphiphilic molecules are possibly involved in the scenario of homochirality. Some prebiotic conditions relevant to amphiphilic molecules will also be described. It could be said that the chiral properties of amphiphilic molecules have various interesting features such as compositional information, spontaneous formation, the ability to exchange components, fission and fusion, adsorption, and permeation. This review aims to clarify the roles of amphiphiles regarding homochirality, and to determine what kinds of physical properties of amphiphilic molecules could have played a role in the scenario of homochirality.

Description: A calculation program based on the density functional theory (DFT) is applied to study the structural, mechanical, and electronic properties of TiV alloys with symmetric structure under high pressure. We calculate the dimensionless ratio, elastic constants, shear modulus, Young’s modulus, bulk modulus, ductile-brittle transition, material anisotropy, and Poisson’s ratio as functions of applied pressure. Results suggest that the critical pressure of structural phase transition is 42.05 GPa for the TiV alloy, and structural phase transition occurs when the applied pressure exceeds 42.05 GPa. High pressure can improve resistance to volume change, as well as the ductility and atomic bonding, but the strongest resistances to elastic and shear deformation occur at P = 5   GPa for TiV alloy. Furthermore, the results of the density of states (DOS) indicate that the TiV alloy presents metallicity. High pressure disrupts the structural stability of the TiV alloy with symmetry, thereby inducing structural phase transition.

Description: In this paper, we investigate the class of quasi-homogeneous production models, obtaining the classification of such models with constant elasticity with respect to an input as well as with respect to all inputs. Moreover, we prove that a quasi-homogeneous production function f satisfies the proportional marginal rate of substitution property if and only f reduces to some symmetric production functions.

Description: Oxindole derivatives are a large group of compounds that can play the role of Adenosine triphosphate (ATP) competitive inhibitors. The possibility of modification of such compounds by addition of active groups to both cyclic systems of oxindole allows the obtaining of derivatives showing significant affinity toward cyclin-dependent kinase (CDK) proteins. Overexpression of that enzyme is observed in the case of most cancers. The discovery of new efficient inhibitors, which could be used in the development of targeted therapies, is one of the current goals setting trends in recent research. In this research, an oxindole molecular core was used, which was modified by the addition of different substituents to both side chains. The realized procedure allowed the creation of a set of oxindole derivatives characterized by binding affinity values and molecular descriptors evaluated during docking procedures and QSAR calculations. The most promising structures characterized by best sets of parameters were used during the molecular dynamics stage. The analysis of structural and energetic properties of systems obtained during this stage of computation gives an indication of inhibitors creating the most stable complexes, characterized by the highest affinity. During this stage, two structures were selected, where affinity towards potential nanocarriers was evaluated. Realized calculations confirmed a significant role of stacking interactions in the stabilization of ligand complexes with fullerene molecules. Obtained data indicates that complexes of oxindole derivatives and considered nanocarriers exhibit significant potential in the creation of immobilized drugs, and can be used in the development of targeted therapies.

Description: The R packages MaxSkew and MultiSkew measure, test and remove skewness from multivariate data using their third-order standardized moments. Skewness is measured by scalar functions of the third standardized moment matrix. Skewness is tested with either the bootstrap or under normality. Skewness is removed by appropriate linear projections. The packages might be used to recover data features, as for example clusters and outliers. They are also helpful in improving the performances of statistical methods, as for example the Hotelling’s one-sample test. The Iris dataset illustrates the usages of MaxSkew and MultiSkew.

Description: Vibration signals are used to diagnosis faults of the rolling bearing which is symmetric structure. Stochastic resonance (SR) has been widely applied in weak signal feature extraction in recent years. It can utilize noise and enhance weak signals. However, the traditional SR method has poor performance, and it is difficult to determine parameters of SR. Therefore, a new second-order tristable SR method (STSR) based on a new potential combining the classical bistable potential with Woods-Saxon potential is proposed in this paper. Firstly, the envelope signal of rolling bearings is the input signal of STSR. Then, the output of signal-to-noise ratio (SNR) is used as the fitness function of the Seeker Optimization Algorithm (SOA) in order to optimize the parameters of SR. Finally, the optimal parameters are used to set the STSR system in order to enhance and extract weak signals of rolling bearings. Simulated and experimental signals are used to demonstrate the effectiveness of STSR. The diagnosis results show that the proposed STSR method can obtain higher output SNR and better filtering performance than the traditional SR methods. It provides a new idea for fault diagnosis of rotating machinery.

Description: This review is devoted to tight-binding (TB) modeling of nucleic acid sequences like DNA and RNA. It addresses how various types of order (periodic, quasiperiodic, fractal) or disorder (diagonal, non-diagonal, random, methylation et cetera) affect charge transport. We include an introduction to TB and a discussion of its various submodels [wire, ladder, extended ladder, fishbone (wire), fishbone ladder] and of the process of renormalization. We proceed to a discussion of aperiodicity, quasicrystals and the mathematics of aperiodic substitutional sequences: primitive substitutions, Perron–Frobenius eigenvalue, induced substitutions, and Pisot property. We discuss the energy structure of nucleic acid wires, the coupling to the leads, the transmission coefficients and the current–voltage curves. We also summarize efforts aiming to examine the potentiality to utilize the charge transport characteristics of nucleic acids as a tool to probe several diseases or disorders.

Description: The fuzzy order convergence in fuzzy Riesz spaces is defined only for fuzzy order bounded nets. The aim of this paper is to define and study unbounded fuzzy order convergence and some of its applications. Furthermore, some theoretical concepts like the fuzzy weak order unit and fuzzy ideals are studied in relation to unbounded fuzzy order convergence.

Description: Based on the G. Goldin’s quantum current algebra symmetry representation theory, have succeeded in explaining a hidden relationship between the quantum many-particle Hamiltonian operators, defined in the Fock space, their factorized structure and integrability. Interesting for applications quantum oscillatory Hamiltonian operators are considered, the quantum symmetries of the integrable quantum Calogero-Sutherland model are analyzed in detail.

Description: Nowadays, with rapid advancement of both the upcoming 5G architecture construction and emerging Internet of Things (IoT) scenarios, Device-to-Device (D2D) communication provides a novel paradigm for mobile networking. By facilitating continuous and high data rate services between physically proximate devices without interconnection with access points (AP) or service network (SN), spectral efficiency of the 5G network can be drastically increased. However, due to its inherent open wireless communicating features, security issues and privacy risks in D2D communication remain unsolved in spite of its benefits and prosperous future. Hence, proper D2D authentication mechanisms among the D2D entities are of great significance. Moreover, the increasing proliferation of smartphones enables seamlessly biometric sensor data collecting and processing, which highly correspond to the user’s unique behavioral characteristics. For the above consideration, we present a secure certificateless D2D authenticating mechanism intended for extreme scenarios in this paper. In the assumption, the key updating mechanism only requires a small modification in the SN side, while the decryption information of user equipment (UEs) remains constant as soon as the UEs are validated. Note that a symmetric key mechanism is adopted for the further data transmission. Additionally, the user activities data from smartphone sensors are analyzed for continuous authentication, which is periodically conducted after the initial validation. Note that in the assumed scenario, most of the UEs are out of the effective range of cellular networks. In this case, the UEs are capable of conducting data exchange without cellular connection. Security analysis demonstrates that the proposed scheme can provide adequate security properties as well as resistance to various attacks. Furthermore, performance analysis proves that the proposed scheme is efficient compared with state-of-the-art D2D authentication schemes.

Description: In this paper we extend one of the main problems of near-rings to the framework of algebraic hypercompositional structures. This problem states that every near-ring is isomorphic with a near-ring of the transformations of a group. First we endow the set of all multitransformations of a hypergroup (not necessarily abelian) with a general hypernear-ring structure, called the multitransformation general hypernear-ring associated with a hypergroup. Then we show that any hypernear-ring can be weakly embedded into a multitransformation general hypernear-ring, generalizing the similar classical theorem on near-rings. Several properties of hypernear-rings related with this property are discussed and illustrated also by examples.

Description: In this paper, we promote the refinement method for estimating asymptotic expression of the fundamental solutions of a fourth order linear differential equation with discontinuous weight function and transmission conditions. These refinement solutions utilize more accurate asymptotic formulas for the eigenvalues and eigenfunctions for the problem.

Description: In this work, we construct a family of seventh order iterative methods for finding multiple roots of a nonlinear function. The scheme consists of three steps, of which the first is Newton’s step and last two are the weighted-Newton steps. Hence, the name of the scheme is ‘weighted-Newton methods’. Theoretical results are studied exhaustively along with the main theorem describing convergence analysis. Stability and convergence domain of the proposed class are also demonstrated by means of using a graphical technique, namely, basins of attraction. Boundaries of these basins are fractal like shapes through which basins are symmetric. Efficacy is demonstrated through numerical experimentation on variety of different functions that illustrates good convergence behavior. Moreover, the theoretical result concerning computational efficiency is verified by computing the elapsed CPU time. The overall comparison of numerical results including accuracy and CPU-time shows that the new methods are strong competitors for the existing methods.

Description: Engineering design optimization in real life is a challenging global optimization problem, and many meta-heuristic algorithms have been proposed to obtain the global best solutions. An excellent meta-heuristic algorithm has two symmetric search capabilities: local search and global search. In this paper, an improved Butterfly Optimization Algorithm (BOA) is developed by embedding the cross-entropy (CE) method into the original BOA. Based on a co-evolution technique, this new method achieves a proper balance between exploration and exploitation to enhance its global search capability, and effectively avoid it falling into a local optimum. The performance of the proposed approach was evaluated on 19 well-known benchmark test functions and three classical engineering design problems. The results of the test functions show that the proposed algorithm can provide very competitive results in terms of improved exploration, local optima avoidance, exploitation, and convergence rate. The results of the engineering problems prove that the new approach is applicable to challenging problems with constrained and unknown search spaces.

Description: The naturally occurring radionuclides (radium-226, thorium-232, potassium-40 and radon-222) were investigated in the alkaline rocks of Abu Khuruq Ring, southern Eastern Desert, Egypt. A high-resolution germanium detector was used for the detection of 40K, 232Th, and 226Ra (Canberra, GR4020 model) while 222Rn concentration was measured by the Alpha-Guard Saphymo GmbH system, model PQ 2000 (AG). Major and rare earth elements (REEs) were assessed using the inductively coupled plasma mass spectrometry and atomic emission spectrometry techniques. Positive correlations were observed between REEs, indicating symmetrical chemical properties and their overall presence in the parent material—also, a positive correlation was observed between effective radium content and radon concentrations pointing to the strong linear dependency between both contents in the studied rocks. The average values of activity concentration of 40K, 232Th, 226Ra, and 222Rn were less than the suggested level by a factor of 1.38%, 3.16%, 2.09%, and 1.16%, respectively. Significant variations were found among the radiological hazards parameters, e.g., the mean value of the annual effective dose (0.55 mSv y−1) was more than the global reference value (0.41 mSv y−1) by a factor of 1.34. The calculated average value of the gamma index was 0.90, and that of the alpha index was 0.37. Hex, Hin and Raeq showed fewer average values than the standard values of unity and 370 Bq kg−1, respectively.

Description: The use of apron buses has become a common practice at many European airports. Previous studies related to airplane boarding rarely apply when apron buses are used, leaving airlines with no well-researched option except to use the random boarding method. In this paper, we test the time to complete boarding a two-door airplane using various boarding methods with two apron buses. These methods were inspired by the classical outside-in, back-to-front, and reverse-pyramid methods considering the limited number of boarding groups corresponding to the limited number of apron buses used for transporting passengers from the terminal to the aircraft. Unlike earlier publications, we test these methods under partial aircraft occupancy. Furthermore, we test the boarding methods under conditions involving: different passenger occupancy rates, different luggage situations, and with two types of seating assignments—random and based upon passenger seating preferences—by considering the advantages brought by the symmetric layout of the aircraft. Experimental results indicate that the best performing method can reduce the boarding time by up to 38.6% compared to the time resulting from the random boarding method. When the airplane is partially occupied, the best performing methods are reverse pyramid–A, hybrid–A, and hybrid–B, all with similar performances.

Description: In this paper, we studied symmetries of string scattering amplitudes in the high energy limits of both the fixed angle or Gross regime (GR) and the fixed momentum transfer or Regge regime (RR). We calculated high energy string scattering amplitudes (SSA) at arbitrary mass levels for both regimes. We discovered the infinite linear relations among fixed angle string amplitudes and the ifinite recurrence relations among Regge string amplitudes. The linear relations we obtained in the GR corrected the saddle point calculations by Gross, Gross and Mende. In addition, for the high energy closed string scatterings, our results differ from theirs by an oscillating prefactor which was crucial to recover the KLT relation valid for all energies. We showed that all the high energy string amplitudes can be solved using the linear or recurrence relations, so that all the string amplitudes can be expressed in terms of a single string amplitude. We further found that, at each mass level, the ratios among the fixed angle amplitudes can be extracted from the Regge string scattering amplitudes. Finally, we reviewed the recent developments on the discovery of infinite number of recurrence relations valid for all energies among Lauricella SSA. The symmetries or relations among SSA at various limits obtained previously can be exactly reproduced. It leads us to argue that the known S L ( K + 3 , C ) dynamical symmetry of the Lauricella function may be crucial to probe spacetime symmetry of string theory.

Description: We investigate the particle creation, as well as the thermodynamics phenomenon of viscous generalized cosmic Chaplygin gas as a cosmic fluid by assuming the flat FRW universe. For this purpose, we extract various parameters such as the energy density ( ρ ) , Hubble parameter ( H ) , declaration parameter ( q ) , temperature ( T f ) , and particle number density ( n ) in the presence of three different models of the particle creation rate ( Γ ). We discuss the validity of the generalized second law of thermodynamics and thermal equilibrium condition under three models of Γ and discuss the graphical behavior of above-mentioned terms.

Description: Key management is a central problem in information security. The development of quantum computation could make the protocols we currently use unsecure. Because of that, new structures and hard problems are being proposed. In this work, we give a proposal for a key exchange in the context of NIST recommendations. Our protocol has a twisted group ring as setting, jointly with the so-called decomposition problem, and we provide a security and complexity analysis of the protocol. A computationally equivalent cryptosystem is also proposed.

Description: Automatic speech recognition, especially large vocabulary continuous speech recognition, is an important issue in the field of machine learning. For a long time, the hidden Markov model (HMM)-Gaussian mixed model (GMM) has been the mainstream speech recognition framework. But recently, HMM-deep neural network (DNN) model and the end-to-end model using deep learning has achieved performance beyond HMM-GMM. Both using deep learning techniques, these two models have comparable performances. However, the HMM-DNN model itself is limited by various unfavorable factors such as data forced segmentation alignment, independent hypothesis, and multi-module individual training inherited from HMM, while the end-to-end model has a simplified model, joint training, direct output, no need to force data alignment and other advantages. Therefore, the end-to-end model is an important research direction of speech recognition. In this paper we review the development of end-to-end model. This paper first introduces the basic ideas, advantages and disadvantages of HMM-based model and end-to-end models, and points out that end-to-end model is the development direction of speech recognition. Then the article focuses on the principles, progress and research hotspots of three different end-to-end models, which are connectionist temporal classification (CTC)-based, recurrent neural network (RNN)-transducer and attention-based, and makes theoretically and experimentally detailed comparisons. Their respective advantages and disadvantages and the possible future development of the end-to-end model are finally pointed out. Automatic speech recognition is a pattern recognition task in the field of computer science, which is a subject area of Symmetry.

Description: Quantum behavior of two oscillator modes, with mutually balanced gain and loss and coupled via linear coupling (including energy conserving as well as energy non-conserving terms) and nonlinear cross-Kerr effect, is investigated. Stationary states are found and their stability analysis is given. Exceptional points for PT -symmetric cases are identified. Quantum dynamics treated by the model of linear operator corrections to a classical solution reveals nonclassical properties of individual modes (squeezing) as well as their entanglement.

Description: In road construction, environmental protection issues often become a challenge, both in the case of new routes and the existing network expansion projects. A number of specific issues are involved in severing of bat commuting routes and the relevant mitigation measures are still in the experimental stage. One of the measures are bat gantries installed on the established bat flyways aligned with the linear features of the landscape used by bats for echolocation calls, which is an example of the structures installed near Szczecin in Poland. The bat activity surveys revealed different levels of acceptance of the respective structures. The available studies identify the following factors as being relevant to relocated or modified commuting routes: road traffic volume, traffic noise, and light pollution. The article discusses which factors are the most likely to have a significant bearing on accepting specific structures by bats. The analyses show that a gantry structure can turn out to be acceptable to bats even on a completely new route if the landscape features are symmetrical and friendly to bats on both sides of the road and on both sides of their flyway as well. Conversely, without such a symmetry along the approach section, the structure may fail to perform.

Description: We study differential systems for which it is possible to establish a correspondence between symmetries and conservation laws based on Noether identity: quasi-Noether systems. We analyze Noether identity and show that it leads to the same conservation laws as Lagrange (Green–Lagrange) identity. We discuss quasi-Noether systems, and some of their properties, and generate classes of quasi-Noether differential equations of the second order. We next introduce a more general version of quasi-Lagrangians which allows us to extend Noether theorem. Here, variational symmetries are only sub-symmetries, not true symmetries. We finally introduce the critical point condition for evolution equations with a conserved integral, demonstrate examples of its compatibility, and compare the invariant submanifolds of quasi-Lagrangian systems with those of Hamiltonian systems.

Description: We present an efficient linear second-order method for a Swift–Hohenberg (SH) type of a partial differential equation having quadratic-cubic nonlinearity on surfaces to simulate pattern formation on surfaces numerically. The equation is symmetric under a change of sign of the density field if there is no quadratic nonlinearity. We introduce a narrow band neighborhood of a surface and extend the equation on the surface to the narrow band domain. By applying a pseudo-Neumann boundary condition through the closest point, the Laplace–Beltrami operator can be replaced by the standard Laplacian operator. The equation on the narrow band domain is split into one linear and two nonlinear subequations, where the nonlinear subequations are independent of spatial derivatives and thus are ordinary differential equations and have closed-form solutions. Therefore, we only solve the linear subequation on the narrow band domain using the Crank–Nicolson method. Numerical experiments on various surfaces are given verifying the accuracy and efficiency of the proposed method.

Description: We explore the cosmic evolution of the accelerating universe in the framework of dynamical Chern–Simons modified gravity in an interacting scenario by taking the flat homogeneous and isotropic model. For this purpose, we take some parametrizations of the equation of state parameter. This parametrization may be a Taylor series extension in the redshift, a Taylor series extension in the scale factor or any other general parametrization of ω . We analyze the interaction term which calculates the action of interaction between dark matter and dark energy. We explore various cosmological parameters such as deceleration parameter, squared speed of sound, Om-diagnostic and statefinder via graphical behavior.

Description: Let G / H be a homogeneous space of a compact simple classical Lie group G. Assume that the maximal torus T H of H is conjugate to a torus T β whose Lie algebra t β is the kernel of the maximal root β of the root system of the complexified Lie algebra g c . We prove that such homogeneous space is formal. As an application, we give a short direct proof of the formality property of compact homogeneous 3-Sasakian spaces of classical type. This is a complement to the work of Fernández, Muñoz, and Sanchez which contains a full analysis of the formality property of S O ( 3 ) -bundles over the Wolf spaces and the proof of the formality property of homogeneous 3-Sasakian manifolds as a corollary.

Description: This article addresses virtual and physical prototyping of some symmetrical patterns collected from the Ainu cultural heritage. The indigenous people living in the northern part of Japan (e.g., Hokkaido), known as Ainu, often decorate their houses, clothing, ornaments, utensils, and spiritual goods using some unique patterns. The patterns carry their identity as well as their sense of aesthetics. Nowadays, different kinds of souvenirs and cultural artifacts crafted with Ainu patterns are cherished by many individuals in Japan and abroad. Thus, the Ainu patterns carry both cultural and commercial significance. A great deal of craftsmanship is needed to produce the Ainu patterns precisely. There is a lack of human resources having such craftsmanship. It will remain the same in the foreseeable future. Thus, there is a pressing need to preserve such craftsmanship. Digital manufacturing technology can be used to preserve the Ainu pattern-making craftsmanship. From this perspective, this article presents a methodology to create both virtual and physical prototypes of Ainu patterns using digital manufacturing technology. In particular, a point cloud-based approach was adopted to model the patterns. A point cloud representing a pattern was then used to create a virtual prototype of the pattern in the form of a solid CAD model. The triangulation data of each solid CAD model were then used to run a 3D printer to produce a physical prototype (replica of the pattern). The virtual and physical prototypes of both basic (Hokkaido) Ainu motifs and some synthesized patterns were reproduced using the presented methodology. The findings of this study will help those who want to digitize the craftsmanship of culturally significant artifacts without using a 3D scanner or image processing.

Description: Epilepsy is a central nervous system disorder that results in asymmetries of brain regional activation and connectivity patterns. The detection of these abnormalities is oftentimes challenging and requires identification of robust bio-markers that are representative of disease activity. Functional Magnetic Resonance Imaging (fMRI) is one of the several methods that can be used to detect such bio-markers. fMRI has a high spatial resolution which makes it a suitable candidate for designing computational methods for computer-aided biomarker discovery. In this paper, we present a computational framework for analyzing fMRI data consisting of 100 epileptic and 80 healthy patients, with an overall goal to produce a novel bio-marker that is predictive of epilepsy. The proposed method is primarily based on Dissimilarity of Activity (DoA) analysis. We demonstrate that the bio-marker presented in this study can be used to capture asymmetries in activities by detecting any abnormalities in Blood Oxygenated Level Dependent (BOLD) signal. In order to represent all asymmetries (of connectivity and activation patterns), we used functional connectivity analysis (FCA) in conjunction with DoA to find underlying connectivity patterns of the regions. Subsequently, these biomarkers were used to train a Support Vector Machine (SVM) classifier that was able to distinguish between healthy and epileptic patients with 87.8% accuracy. These results demonstrate the applicability of computer-aided methods in complex disease diagnosis by simply utilizing the existing data. With the advent of all modern sensing and imaging techniques, the use of intelligent algorithms and advanced computational methods are increasingly becoming the future of computer-aided diagnosis.

Description: Indirubin derivatives and analogues are a large group of compounds which are widely and successfully used in treatment of many cancer diseases. In particular, the ChEMBL474807 molecule, which has confirmed inhibiting abilities against CDK2 and GSK3B enzymes, can be included in this group. The immobilization of inhibitors with the use of nanocarriers is an often used strategy in creation of targeted therapies. Evaluations were made of the possibility of immobilizing ligand molecules on different types of nanocarrier, such as carbon nanotubes (CNT), functionalized fullerene C60 derivatives (FF_X), and functionalized cube rhombellanes, via the use of docking methods. All results were compared with a reference system, namely C60 fullerene. The realized calculations allowed indication of a group of compounds that exhibited significant binding affinity relative to the ligand molecule. Obtained data shows that structural modifications, such as those related to the addition of functional groups or changes of structure symmetry, realized in particular types of considered nanostructures, can contribute to increases of their binding capabilities. The analysis of all obtained nano complexes clearly shows that the dominant role in stabilization of such systems is played by stacking and hydrophobic interactions. The realized research allowed identification of potential nanostructures that, together with the ChEMBL474807 molecule, enable the creation of targeted therapy.

Description: The proliferation of Internet technology and balance of composition in major feature of many visual products have been advantageous for businesses and changed the distribution channels through which industries reach their consumers. The intensive development of Internet technology and the increasing popularity of online shopping have further changed customers’ purchasing behaviors and the methods by which companies disseminate their video advertisements. The main research question that this study intends to answer is, “What do users do when a YouTube advertisement appears? Do they avoid or confront them?” The aim of this study is to explore the perceptions and related behaviors of international purchasing and consumers’ trust of YouTube advertisements. Statistical analyses focus on the demographics of a sample population in Thailand. The findings are based on data obtained by a questionnaire, the results of which were analyzed by t-test and multiple regression. The results indicate that YouTube advertising has a significant effect on behavioral trends. Moreover, the subjects in the sample reported that they are more likely to avoid YouTube ads than confront them. The study subjects have low satisfaction with YouTube advertising, and males have significantly lower satisfaction than females. This study also analyzes the reliability of trust perception toward purchasing. The results indicate that the reliability is greater than 90% at an α level of 5% and a 95% confidence interval.

Description: The study of asymmetric structures and their applications in mathematics is interesting. One of the types of asymmetric structures on a metric space has been initiated by Kada et al. (1996) and is known as a w-distance. That lack of symmetry attracts many researchers in fixed point theory. In this manuscript, we introduce a new type of contraction named generalized ( α , ψ , M Ω ) -contractive mappings via w-distances, and then we prove some new related fixed point results, generalizing and improving the recent results of Lakzian et al. (2016) and others. At the end, we give some examples. To illustrate the usability of the new theory, we apply our obtained results to resolve a nonlinear Fredholm-integral-type equation.

Description: With the rapid development of high-speed railway (HSR) systems, the increasing demand for passenger traffic has put forward higher requirements for HSR train timetabling problems (HSRTTPs). This paper establishes two mathematical optimisation models with different optimisation objectives for an HSRTTP and solves these models through a column generation-based algorithm. However, the column generation-based algorithm has the disadvantage of a slow convergence rate, thus we put forward corresponding acceleration strategies for five stages of the algorithm: preprocessing, restricted master problem, pricing problem, branch-and-bound and postprocessing from a symmetry point between the computation efficiency and the accuracy. The effectiveness of the acceleration strategies was validated by a case study of the Beijing–Shanghai HSR. The results show that the proposed optimal acceleration strategies can increase the computation efficiency of the algorithm by 11.8× on average while ensuring the accuracy.

Description: With the recent increase in precision of our cosmological datasets, measurements of Λ CDM model parameter provided by high- and low-redshift observations started to be in tension, i.e., the obtained values of such parameters were shown to be significantly different in a statistical sense. In this work we tackle the tension on the value of the Hubble parameter, H 0 , and the weighted amplitude of matter fluctuations, S 8 , obtained from local or low-redshift measurements and from cosmic microwave background (CMB) observations. We combine the main approaches previously used in the literature by extending the cosmological model and accounting for extra systematic uncertainties. With such analysis we aim at exploring non standard cosmological models, implying deviation from a cosmological constant driven acceleration of the Universe expansion, in the presence of additional uncertainties in measurements. In more detail, we reconstruct the Dark Energy equation of state as a function of redshift, while we study the impact of type-Ia supernovae (SNIa) redshift-dependent astrophysical systematic effects on these tensions. We consider a SNIa intrinsic luminosity dependence on redshift due to the star formation rate in its environment, or the metallicity of the progenitor. We find that the H 0 and S 8 tensions can be significantly alleviated, or even removed, if we account for varying Dark Energy for SNIa and CMB data. However, the tensions remain when we add baryon acoustic oscillations (BAO) data into the analysis, even after the addition of extra SNIa systematic uncertainties. This points towards the need of either new physics beyond late-time Dark Energy, or other unaccounted systematic effects (particulary in BAO measurements), to fully solve the present tensions.

Description: Rolling bearings are the most important parts in rotating machinery, and one of the most vulnerable parts to failure. The rolling bearing is a cyclic symmetrical structure that is stable under normal operating conditions. However, when the rolling bearing fails, its symmetry is destroyed, resulting in unstable performance and causing major accidents. If the performance of rolling bearings can be monitored and evaluated in real time, maintenance strategies can be implemented promptly. In this paper, by using wavelet packet energy entropy (WPEE), the early fault-free features of bearing and the failure samples of similar bearings are decomposed firstly, and the energy value is extracted as the original feature, simultaneously. Secondly, a radial basis function (RBF) neural network model is established by using early fault-free features and similar bearing failure characteristics. The bearing full-life data characteristics of the extracted features are added into the RBF model in an iterative manner to obtain performance degradation Indicator. Boxplot was introduced as an adaptive threshold method to determine the failure threshold. Finally, the results are verified by empirical mode decomposition and Hilbert envelope demodulation. A bearing accelerated life experiment is performed to validate the feasibility and validity of the proposed method. The experimental results show that the method can diagnose early fault points in time and evaluate the degree of bearing degradation, which is of great significance for industrial practical applications.

Description: Energy efficiency and renewable energy are the two main research topics for sustainable energy. In the past ten years, countries around the world have invested a lot of manpower into new energy research. However, in addition to new energy development, energy efficiency technologies need to be emphasized to promote production efficiency and reduce environmental pollution. In order to improve power production efficiency, an integrated solution regarding the issue of electric power load forecasting was proposed in this study. The solution proposed was to, in combination with persistence and search algorithms, establish a new integrated ultra-short-term electric power load forecasting method based on the adaptive-network-based fuzzy inference system (ANFIS) and back-propagation neural network (BPN), which can be applied in forecasting electric power load in Taiwan. The research methodology used in this paper was mainly to acquire and process the all-day electric power load data of Taiwan Power and execute preliminary forecasting values of the electric power load by applying ANFIS, BPN and persistence. The preliminary forecasting values of the electric power load obtained therefrom were called suboptimal solutions and finally the optimal weighted value was determined by applying a search algorithm through integrating the above three methods by weighting. In this paper, the optimal electric power load value was forecasted based on the weighted value obtained therefrom. It was proven through experimental results that the solution proposed in this paper can be used to accurately forecast electric power load, with a minimal error.

Description: Non-standard Lagrangians play an important role in the systems of non-conservative dynamics or nonlinear differential equations, quantum field theories, etc. This paper deals with quasi-fractional dynamical systems from exponential non-standard Lagrangians and power-law non-standard Lagrangians. Firstly, the definition, criterion, and corresponding new conserved quantity of Mei symmetry in this system are presented and studied. Secondly, considering that a small disturbance is applied on the system, the differential equations of the disturbed motion are established, the definition of Mei symmetry and corresponding criterion are given, and the new adiabatic invariants led by Mei symmetry are proposed and proved. Examples also show the validity of the results.

Description: With the development of the social economy and enlarged volume of information, the application of multiple-attribute decision-making (MADM) has become increasingly complex, uncertain, and obscure. As a further generalization of hesitant fuzzy set (HFS), simplified neutrosophic hesitant fuzzy set (SNHFS) is an efficient tool to process the vague information and contains the ideas of a single-valued neutrosophic hesitant fuzzy set (SVNHFS) and an interval neutrosophic hesitant fuzzy set (INHFS). In this paper, we propose a decision-making approach based on the maximizing deviation method and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to solve the MADM problems, in which the attribute weight information is incomplete, and the decision information is expressed in simplified neutrosophic hesitant fuzzy elements. Firstly, we inaugurate an optimization model on the basis of maximizing deviation method, which is useful to determine the attribute weights. Secondly, using the idea of the TOPSIS, we determine the relative closeness coefficient of each alternative and based on which we rank the considered alternatives to select the optimal one(s). Finally, we use a numerical example to show the detailed implementation procedure and effectiveness of our method in solving MADM problems under simplified neutrosophic hesitant fuzzy environment.

Description: The maglev train is a whole new method of transportation without wheels, consisting of 20 groups of symmetry suspension units. The magnetic levitation system plays a major role in suspending the maglev train stably and following the track quickly with the desired gap. However, vertical track irregularity in the maglev train line has a dreadful effect on the tracking performance of the magnetic levitation system. The investigations carried out by our team have revealed that the fluctuation of the suspension gap becomes more and more serious with increases in running speed. In this paper, a mathematical model with consideration of vertical track irregularity is established. In order to overcome and suppress the fluctuation of the suspension gap, we propose a new strategy which includes installing an accelerometer on the electromagnet to address this problem. This strategy has already been successfully implemented and applied to the suspension controller for a magnetic levitation system in the Changsha maglev express. Real operation data indicates the tracking performance of the magnetic levitation system was obviously improved.

Description: We perform Lie symmetry analysis to a zero-coupon bond pricing equation whose price evolution is described in terms of a partial differential equation (PDE). As a result, using the computer software package SYM, run in conjunction with Mathematica, a new family of Lie symmetry group and generators of the aforementioned pricing equation are derived. We furthermore compute the exact invariant solutions which constitute the pricing models for the bond by making use of the derived infinitesimal generators and the associated similarity reduction equations. Using known solutions, we again compute more solutions via group point transformations.

Description: Nowadays, in the world of science, an important goal is to create new nanostructures that may act as potential drug carriers. Among different, real or hypothetical, polymeric networks, rhombellanes are very promising and, therefore, attempts were made to deposit polyethylenimines as possible nano-drug complexes on the cube rhombellane homeomorphs surface. For the search of ligand–fullerene interactions, was used AutoDockVina software. As a reference structure, the fullerene C60 was used. After the docking procedure, the ligands–fullerenes interactions were tested. The important factor determining the mutual affinity of the tested ligands and nanocarriers is the symmetry of the analyzed nanostructures. Here, this feature has the influence on the distribution of such groups like donors and acceptors of hydrogen bonds on the surface of nanoparticles. We calculated the best binding affinities of ligands, values of binding constants and differences relative to C60 molecules. The best binding efficiency was found for linear ligands. It was also found that the shorter the molecule, the better the binding performance, the more the particle grows and the lower the yield. Small structures of ligands react easily with small structures of nanoparticles. The highest positive percentage deviations were obtained for ligand–fullerene complexes showing the highest binding energy values. Detailed analysis of structural properties after docking showed that the values of affinity of the studied indolizine ligands to the rhombellanes surface are correlated with the strength/length of hydrogen bonds formed between them.

Description: Persisting tensions between high-redshift and low-redshift cosmological observations suggest the dark energy sector of the Universe might be more complex than the positive cosmological constant of the Λ CDM model. Motivated by string theory, wherein symmetry considerations make consistent AdS backgrounds (i.e., maximally-symmetric spacetimes with a negative cosmological constant) ubiquitous, we explore a scenario where the dark energy sector consists of two components: a negative cosmological constant, with a dark energy component with equation of state w ϕ on top. We test the consistency of the model against low-redshift baryon acoustic oscillation and Type Ia supernovae distance measurements, assessing two alternative choices of distance anchors: the sound horizon at baryon drag determined by the Planck collaboration and the Hubble constant determined by the SH0ES program. We find no evidence for a negative cosmological constant and mild indications for an effective phantom dark energy component on top. A model comparison analysis reveals that the Λ CDM model is favoured over our negative cosmological constant model. While our results are inconclusive, should low-redshift tensions persist with future data, it would be worth reconsidering and further refining our toy negative cosmological constant model by considering realistic string constructions.

Description: A self-consistent two-gap γ -model is used to quantitatively describe several thermodynamic properties of MgB 2 superconductor. The superconducting coupling matrix, ν i j , was obtained from the fitting of the superfluid density in the entire superconducting temperature range. Using this input, temperature-dependent superconducting gaps, specific heat, and upper critical fields were calculated with no adjustable parameters and compared with the experimental data as well as with the first-principles calculations. The observed agreement between fit and data shows that γ -model provides adequate quantitative description of the two-gap superconductivity in MgB 2 and may serve as a relatively simple and versatile self-consistent description of the thermodynamic quantities in multi-gap superconductors.

Description: In this manuscript, we propose several iterative methods for solving nonlinear equations whose common origin is the classical Chebyshev’s method, using fractional derivatives in their iterative expressions. Due to the symmetric duality of left and right derivatives, we work with right-hand side Caputo and Riemann–Liouville fractional derivatives. To increase as much as possible the order of convergence of the iterative scheme, some improvements are made, resulting in one of them being of 3 α -th order. Some numerical examples are provided, along with an study of the dependence on initial estimations on several test problems. This results in a robust performance for values of α close to one and almost any initial estimation.

Description: In this paper the model of infection diseases by Marchuk is considered. Mathematical questions which are important in its study are discussed. Among them there are stability of stationary points, construction of the Cauchy matrices of linearized models, estimates of solutions. The novelty we propose is in a distributed feedback control which affects the antibody concentration. We use this control in the form of an integral term and come to the analysis of nonlinear integro-differential systems. New methods for the study of stability of linearized integro–differential systems describing the model of infection diseases are proposed. Explicit conditions of the exponential stability of the stationary points characterizing the state of the healthy body are obtained. The method of the paper is based on the symmetry properties of the Cauchy matrices which allow us their construction.

Description: Data hiding in videos has been a big concern as their rich redundancy can be used for embedding a lot of secret information. Further, as high efficiency video coding (HEVC) introduces many innovative technologies compared with the previous standard, H.264, it has gradually become the mainstream. Therefore, it is valuable to develop new information hiding algorithms by using novel features of HEVC. A HEVC video data hiding algorithm based on prediction unit (PU) partition modes from inter prediction process is proposed in this paper. Firstly, code units (CUs) in two sizes of 8 × 8 and 16 × 16 are selected for embedding, then the PU partition modes in these CUs are coded by a spatial coding method. After that, two specific hiding algorithms by modifying coded PU partition modes in CUs of 8 × 8 and 16 × 16 are proposed, respectively. Experimental results show that the proposed algorithm has achieved excellent performance with high visual quality, and high embedding capacity and low bitrate increase in both high- and low-resolution videos compressed with different quantization parameters (QPs). Compared with the state-of-the-art work, the proposed algorithm achieves a much higher capacity while keeping quite high visual quality with little increase of bitrate.

Description: Development of railway infrastructure at the turn of the 20th and 21st centuries, as well as the speeds of trains in passenger and freight traffic are the result of improving the structure of modern rail vehicles and railway infrastructure optimization. The structure of the railway surface, which enables high speeds and transferring ever greater loads and pressures of up to 25–30 t/vehicle axis, must meet very strict strength and durability requirements. This paper discusses mathematical and numerical tools used in simulation and experimental tests of railway surfaces, as well as its selected elements. Issues addressed in this paper concern, among others, modeling of the railway track, calculations related to its static and dynamic loading, and simulation of the technological process of selected elements of railway turnout. Selected results of the simulation tests on numerical models showing their behavior under different loads are also presented in this paper. The concept of symmetry is included in the possibility of applying the method described in the article both for testing other sections of railway lines, as well as for testing other elements in which stresses occur.

Description: In this paper we extend earlier results on Hosoya entropy (H-entropy) of graphs, and establish connections between H-entropy and automorphisms of graphs. In particular, we determine the H-entropy of graphs whose automorphism group has exactly two orbits, and characterize some classes of graphs with zero H-entropy.

Description: Heat-treated high-strength rebar has many advantages, such as high strength, superior ductility, high yield ratio, excellent welding and cold bending performance, which can effectively reduce the amount of rebar and improve the project quality. Although heat-treated high-strength rebar has been successfully applied in many fields of civil engineering, its application in tunnel engineering is just getting started. In this study, the on-site test of axisymmetric heat-treated high-strength lattice girders in rail tunnels and road tunnels was carried out. Comparative analysis of the performance of axisymmetric heat-treated high-strength lattice girders and original-design I20b steel rib was conducted. The test results show that the settlement of high-strength lattice girders is decreased by about 7%~30% compared with the test section of original-design I20b steel rib. The surrounding rock pressure is similar, but the stress of high-strength lattice girders is slightly higher than that of I20b steel rib. Due to the better binding ability of the lattice girders and the concrete, the ultimate bearing capacity of the ‘lattice girders and shotcrete’ is greater than that of the ‘I20b steel rib and shotcrete’. Moreover, the steel consumption of lattice girder is about 36% less than I20b steel rib, which shows significant economic and social benefits.

Description: In this review, a short description of exceptional field theory and its application is presented. Exceptional field theories provide a U-duality covariant description of supergravity theories, allowing addressing relevant phenomena, such as non-geometricity. Some applications of the formalism are briefly described.

Description: In this paper, a high-precision image authentication scheme for absolute moment block truncation coding (AMBTC)-compressed images is presented. For each block, two sub-bitmaps are conducted using the symmetrical separation, and the six-bit authentication code is symmetrically assigned to two sub-codes, which is virtually embedded into sub-bitmaps using the matrix encoding later. To overcome distortion caused by modifications to the bitmap, the corresponding to-be-flipped bit-location information is recorded instead of flipping these bits of the bitmap directly. Then, the bit-location information is inserted into quantization levels based on adjusted quantization level matching. In contrast to previous studies, the proposed scheme offers a significantly improved tampering detection ability, especially in the first hierarchical tampering detection without remediation measures, with an average tampering detection rate of up to 98.55%. Experimental results show that our approach provides a more stable and reliable tampering detection performance and sustains an acceptable visual quality.

Description: Alcohol intoxication is a significant phenomenon, affecting many social areas, including work procedures or car driving. Alcohol causes certain side effects including changing the facial thermal distribution, which may enable the contactless identification and classification of alcohol-intoxicated people. We adopted a multiregional segmentation procedure to identify and classify symmetrical facial features, which reliably reflects the facial-temperature variations while subjects are drinking alcohol. Such a model can objectively track alcohol intoxication in the form of a facial temperature map. In our paper, we propose the segmentation model based on the clustering algorithm, which is driven by the modified version of the Artificial Bee Colony (ABC) evolutionary optimization with the goal of facial temperature features extraction from the IR (infrared radiation) images. This model allows for a definition of symmetric clusters, identifying facial temperature structures corresponding with intoxication. The ABC algorithm serves as an optimization process for an optimal cluster’s distribution to the clustering method the best approximate individual areas linked with gradual alcohol intoxication. In our analysis, we analyzed a set of twenty volunteers, who had IR images taken to reflect the process of alcohol intoxication. The proposed method was represented by multiregional segmentation, allowing for classification of the individual spatial temperature areas into segmentation classes. The proposed method, besides single IR image modelling, allows for dynamical tracking of the alcohol-temperature features within a process of intoxication, from the sober state up to the maximum observed intoxication level.

Description: In this work, we deal with a kinetic model of cell movement that takes into consideration the structure of the extracellular matrix, considering cell membrane reactions, haptotaxis, and chemotaxis, which plays a key role in a number of biological processes such as wound healing and tumor cell invasion. The modeling is performed at a microscopic scale, and then, a scaling limit is performed to derive the macroscopic model. We run some selected numerical experiments aimed at understanding cell movement and adhesion under certain documented situations, and we measure the alignment of the cells and compare it with the pathways determined by the extracellular matrix by introducing new alignment operators.