Search Results (23)

The purpose of this study is to describe Thich Nhat Hanh’s naturalism and nondualism and to situate his views in a “trans-different” perspective. I ask whether his thoughts are compatible with other worldviews that work with the notion of justice. I first describe Nhat Hanh’s attitude towards nature. I then demonstrate how his non-separation from nature paves the way for an interconnectedness with all and how his nonduality leads him to a universal belonging. Finally, juxtaposing Nhat Hanh’s nondualism and a justice-oriented approach, I argue that in a “trans-different” perspective different approaches to suffering and peace may learn from each other and complement each other. Full article

Turbulent flows over a semi-circular cylinder (a limiting case of a thick airfoil with a chord equal to the diameter base) are investigated using high-fidelity large-eddy simulations at a diameter-based Reynolds number, Re = 130,000, Mach number, M = 0.05, and a zero angle of attack. The aerodynamic flow control system, designed with two trapped vortex cells, achieves a complete non-separated flow over the bluff body, except for low-scale turbulence effects, reaching approximately 80% of the theoretical lift coefficient limit ($2\pi$ for the half-circular airfoil). Viscous effects are analyzed using the conventional Reynolds-averaged Navier–Stokes approach for a broad range of Reynolds numbers, 75,000 ≤ Re ≤ 1,000,000. Numerical results demonstrate that the aerodynamic properties of the implemented concept are independent of the Reynolds number within this interval, highlighting its significant potential for further development. Full article

Background: Klippel–Feil disease is a condition characterized by a defect in the spine, consisting of the fusion or non-separation of two or more vertebrae of the cervical tract. It affects 1 in every 50,000 newborns, and the pathogenesis remains unknown to date, although the role of certain genes that are involved in segmentation processes is being studied. A single case of a genetic Myosin Heavy Chain 3 (MYH3) mutation is described here. Affected patients are typically distinguished by a relatively short neck, which leads to limited mobility, a low hairline, and obesity; they may also experience various other health issues. The common occurrence of comorbidities further diminishes the quality of life of these young individuals. Methods: The following case report describes the synergistic effect of Incobotulinum toxin type A and physiotherapy in a 7-year-old patient with MYH3 mutation-related Klippel–Feil syndrome (KFS) complicated by bilateral paraplegia to improve the spasticity condition of the lower limbs. To assess improvements over time, the patient underwent rating scales to determine spasticity (Modified Ashworth Scale: MAS), the neck’s range of motion (ROM), and muscle tone by using MyotonPro^®. Specifically, measurements were taken on the day of the first medical examination (T0), the month after the injection and the startup of therapeutic exercise (T1), at three months (T2), and then once a month for a total of 6 months (T3, T4, and T5). Results: This therapeutic approach resulted in highly satisfactory outcomes for the child’s well-being, which was maintained until the sixth month and was accompanied by a complete absence of any side effects. Full article

Semiparametric panel data models are powerful tools for analyzing data with complex characteristics such as linearity and nonlinearity of covariates. This study aims to investigate the estimation and testing of a random effects semiparametric model (RESPM) with serially and spatially correlated nonseparable error, utilizing a combination of profile quasi-maximum likelihood estimation and local linear approximation. Profile quasi-maximum likelihood estimators (PQMLEs) for unknowns and a generalized F-test statistic $F_{NT}$ are built to determine the beingness of nonlinear relationships. The asymptotic properties of PQMLEs and $F_{NT}$ are proven under regular assumptions. The Monte Carlo results imply that the PQMLEs and $F_{NT}$ performances are excellent on finite samples; however, missing the spatially and serially correlated error leads to estimator inefficiency and bias. Indonesian rice-farming data is used to illustrate the proposed approach, and indicates that $landarea$ exhibits a significant nonlinear relationship with $riceyield$, in addition, $high$-$yieldvarieties$, $mixed$-$yield$$varieties$, and $seedweight$ have significant positive impacts on rice yield. Full article

In this paper, the fixed-time and preassigned-time synchronization issues of fully quaternion-valued fuzzy memristive neural networks are studied based on the dynamic event-triggered control mechanism. Initially, the fuzzy rules are defined within the quaternion domain and the relevant properties are established through rigorous analysis. Subsequently, to conserve resources and enhance the efficiency of the controller, a kind of dynamic event-triggered control mechanism is introduced for the fuzzy memristive neural networks. Based on the non-separation analysis, fixed-time and preassigned-time synchronization criteria are presented and the Zeno phenomenon under the event-triggered mechanism is excluded successfully. Finally, the effectiveness of the theoretical results is verified through numerical simulations. Full article

This article is concerned with fixed-time synchronization and preassigned-time synchronization of Cohen–Grossberg quaternion-valued neural networks with discontinuous activation functions and generalized time-varying delays. Firstly, a dynamic model of Cohen–Grossberg neural networks is introduced in the quaternion field, where the time delay successfully integrates discrete-time delay and proportional delay. Secondly, two types of discontinuous controllers employing the quaternion-valued signum function are designed. Without utilizing the conventional separation technique, by developing a direct analytical approach and using the theory of non-smooth analysis, several adequate criteria are derived to achieve fixed-time synchronization of Cohen–Grossberg neural networks and some more precise convergence times are estimated. To cater to practical requirements, preassigned-time synchronization is also addressed, which shows that the drive-slave networks reach synchronization within a specified time. Finally, two numerical simulations are presented to validate the effectiveness of the designed controllers and criteria. Full article

Nondipole terms in the atom–laser interaction arising due to the presence of a magnetic component in an electromagnetic wave and its inhomogeneity lead to the nonseparability of the center-of-mass (CM) and electron variables in the neutral atom and, as a consequence, to its acceleration. We investigate this effect and the accompanying excitation and ionization processes for the hydrogen atom in strong (${10}^{12}$ – $2\times {10}^{14}$ W/cm²) linearly polarized short-wavelength (5 eV $\lesssim \hslash \omega \lesssim$ 27 eV) electromagnetic pulses of about 8 fs duration. The study was carried out within the framework of a hybrid quantum-quasiclassical approach in which the coupled time-dependent Schrödinger equation for an electron and the classical Hamilton equations for the CM of an atom were simultaneously integrated. Optimal conditions with respect to the frequency and intensity of the electromagnetic wave for the acceleration of atoms without their noticeable ionization were found in the analyzed region. Full article

In this paper, the general-decay synchronization issue of a class of quaternion-valued neural networks with mixed time delays is investigated. Firstly, unlike some previous works where the quaternion-valued model is separated into four real-valued networks or two complex-valued networks, we consider the mixed-delayed quaternion-valued neural network model as a whole and introduce a novel nonlinear feedback controller for the corresponding response system. Then, by introducing a suitable Lyapunov–Krasovskii functional and employing a novel inequality technique, some easily verifiable sufficient conditions are obtained to ensure the general-decay synchronization for the considered drive-response networks. Finally, the feasibility of the established theoretical results is verified by carrying out Matlab numerical simulations. Full article

This article explores complex-valued inertial neural networks (CVINNs) with distributed delays (DDs). By constructing two new feedback controllers, some novel results on fixed-time stabilization (FTS) and preassigned-time stabilization (PTS) of CVINNs are established. Unlike most of the previous works, FTS and PTS obtained here are explored without dividing the original complex-valued system into two separate real valued subsystems. Eventually, to verify the effectiveness and reliability of the results of this article, we provide several numerical examples. The FTS and PTS of CVINNs are successfully implemented at T = 6, 5.5, and 5, and the settling time is not affected by system parameters and initial values. Full article

Tastes change over time. People’s tastes are distorted through two channels: satiation formation and habit formation. In this paper, we develop a theoretical foundation of satiation and habituation by an axiomatic approach. Our theory is based on a hierarchy of preference conditions called compensation independence. The behavioral assumption underlying the preference conditions are the psychological compensation of human beings. I flesh out an axiomatic system for general models of satiation and habit formation, which contains many functional forms in the literature as special cases. Moreover, I advance the axiomatization to accommodate the linear representations of satiation and habit formation that are prevailing in the literature. This paper contributes to the birth of a new generation of the behavioral foundation for modeling satiation and habit formation, which might improve on the current state of the art in understanding people’s tastes over time and preferences. Theoretically, this study contributes to the vein of time-nonseparable preferences. Full article

Polymeric nanoparticles have been introduced as a delivery vehicle for active compounds in a broad range of medical applications due to their biocompatibility, stability, controlled release of active compounds, and reduced toxicity. The oral route is the most used approach for delivery of biologics to the body. The homeostasis and function of oral cavity tissues are dependent on the activity of stem cells. The present work focuses, for the first time, on the interaction between two types of polymeric nanoparticles, poly (lactic-co-glycolic acid) or PLGA and PLGA/chitosan, and two stem cell populations, oral keratinocyte stem cells (OKSCs) and stem cells from human exfoliated deciduous teeth (SHEDs). The main results show that statistical significance was observed in OKSCs uptake when compared with normal keratinocytes and transit amplifying cells after 24 h of incubation with 5 and 10 µg/mL PLGA/chitosan. The CD117⁺ SHED subpopulation incorporated more PLGA/chitosan nanoparticles than nonseparated SHED. The uptake for PLGA/chitosan particles was better than for PLGA particles with longer incubation times, yielding better results in both cell types. The present results demonstrate that nanoparticle uptake depends on stem cell type, incubation time, particle concentration, and surface properties. Full article

An enhanced interpolation approach is developed for simulating nonseparable nonstationary ground motions on the basis of the spectral representation method, which mainly contains two steps of interpolations and an optimization. Firstly, the interpolation technique is utilized to reduce the Cholesky decomposition time of the lagged coherence matrix. The square root of the evolutionary power spectral density is then decoupled into several time and frequency discrete functions using the proper orthogonal decomposition (POD) interpolation technique, which results in the availability of the fast Fourier transform (FFT) technique in the simulation. Compared with existing decoupling schemes, the POD interpolation achieves a significant efficiency improvement with a slight accuracy reduction. Finally, the simulation formula is further optimized to reduce the number of FFT operations. The accuracy and efficiency of this method are verified with the numerical examples of nonstationary ground motions simulation. Results show that the error introduced by two-step interpolations is fairly small and the simulation agrees with the targets very well. Furthermore, the efficiency generating sample function is significantly enhanced. Full article

The parameter estimation (PE) of biochemical reactions is one of the most challenging tasks in systems biology given the pivotal role of these kinetic constants in driving the behavior of biochemical systems. PE is a non-convex, multi-modal, and non-separable optimization problem with an unknown fitness landscape; moreover, the quantities of the biochemical species appearing in the system can be low, making biological noise a non-negligible phenomenon and mandating the use of stochastic simulation. Finally, the values of the kinetic parameters typically follow a log-uniform distribution; thus, the optimal solutions are situated in the lowest orders of magnitude of the search space. In this work, we further elaborate on a novel approach to address the PE problem based on a combination of adaptive swarm intelligence and dilation functions (DFs). DFs require prior knowledge of the characteristics of the fitness landscape; therefore, we leverage an alternative solution to evolve optimal DFs. On top of this approach, we introduce surrogate Fourier modeling to simplify the PE, by producing a smoother version of the fitness landscape that excludes the high frequency components of the fitness function. Our results show that the PE exploiting evolved DFs has a performance comparable with that of the PE run with a custom DF. Moreover, surrogate Fourier modeling allows for improving the convergence speed. Finally, we discuss some open problems related to the scalability of our methodology. Full article

In the theory of wavelet frames, the known Daubechies wavelet bases have been generalized to compactly supported (Daubechies-like) wavelet frames, while the known bandlimited Meyer wavelet bases have not been generalized to date. In this study, we will generalize known Meyer wavelet basis into non-separable Meyer-like wavelet frames. By using a characteristic function to mask the Fourier transform of the one-dimensional Meyer scaling function with a width parameter, we can produce a family of Meyer-like frame scaling functions and associated Meyer-like wavelet frames. After that, by inserting a real-valued function into the width parameter of a one-dimensional Meyer-like frame scaling function, we propose a novel approach to construct non-separable Meyer-like frame scaling functions with unique circular symmetry. Finally, we construct the corresponding non-separable Meyer-like wavelet frames. Full article

A new hybrid metaheuristic method for optimizing the objective function on a parallelepiped set of admissible solutions is proposed. It mimics the behavior of a school of river perch when looking for food. The algorithm uses the ideas of several methods: a frog-leaping method, migration algorithms, a cuckoo algorithm and a path-relinking procedure. As an application, a wide class of problems of finding the optimal control of deterministic discrete dynamical systems with a nonseparable performance criterion is chosen. For this class of optimization problems, it is difficult to apply the discrete maximum principle and its generalizations as a necessary optimality condition and the Bellman equation as a sufficient optimality condition. The desire to extend the class of problems to be solved to control problems of trajectory bundles and stochastic problems leads to the need to use not only classical adaptive random search procedures, but also new approaches combining the ideas of migration algorithms and swarm intelligence methods. The efficiency of this method is demonstrated and an analysis is performed by solving several optimal deterministic discrete control problems: two nonseparable problems (Luus–Tassone and LiHaimes) and five classic linear systems control problems with known exact solutions. Full article