Search Results (2,234)

In the field of parallel robots, traditional rigid joints compromise motion accuracy owing to inherent friction and backlash, thus driving the demand for high-performance compliant joints. This paper proposes a parametric design method for a two-axis compliant joint that employs flexure leaf springs (FLSs) as rigid joint alternatives. The joint configuration consists of four FLSs arranged in a revolute–revolute (RR) layout. Based on Euler–Bernoulli beam theory and the deformation superposition principle, linear analytical models for the compliance and stress characteristics of both the flexure leaf spring (FLS) and the compliant joint are derived. These models are validated through finite element analysis (FEA) and rotational motion experiments. The results indicate that the relative errors between the analytical model (AM) and finite element model (FEM) are below 8%, while the relative errors between the AM and experimental data are within 12%. The proposed parametric design method enables rapid preliminary design and the performance evaluation of the two-axis compliant joint, which is intended as a rotational joint for six degrees of freedom (6-DOF) parallel robots with typical applications in high-precision optical alignment. Full article

Data in multi-tenant cloud environments is increasingly shared across organizations, making strong in-memory isolation a critical requirement. Existing confidential computing mechanisms such as AMD SEV provide hardware-enforced protection, but they require specialized processors and incur non-trivial performance overhead, which limits their deployment in heterogeneous clouds. This paper presents DASPRI, a software-based approach that constructs an isolated execution environment for trusted virtual machines by combining dual address spaces with privilege restriction. DASPRI partitions physical memory into a normal region and an isolated region on NUMA systems, and steers all memory allocations of trusted VMs into the isolated region by monitoring page faults and kernel allocation paths. It further hardens the isolated region by mediating direct and dynamic kernel mappings and by maintaining separate page caches for trusted and normal VMs. Remote attestation is integrated to protect the integrity of metadata used to identify trusted VMs. We implement DASPRI on a HUAWEI Kunpeng AArch64 server running OpenEuler and evaluate it using microbenchmarks and UnixBench. Experimental results show that DASPRI enforces strong memory isolation with less than 5% overhead on basic system operations and only 1.3% degradation in overall host performance. Full article

Local path tracking is a critical challenge for autonomous vehicles, requiring precise trajectory following under nonlinear dynamics, strict constraints, and real-time execution. While Nonlinear Model Predictive Control (NMPC) has emerged as a leading approach, many existing methods decouple velocity planning from tracking, lack formal stability guarantees, or do not demonstrate feasibility on embedded platforms. We present a unified NMPC framework that integrates curvature-aware velocity adaptation directly into the cost function. The controller makes use of cubic spline paths, recursive feasibility constraints, and Lyapunov-based terminal costs to ensure stability. The nonlinear optimization problem is implemented in CasADi and solved using IPOPT, with warm-starting and efficient discretization techniques enabling real-time performance. Our approach has been validated in the CARLA simulator across a variety of urban scenarios, including straight roads, intersections, and roundabouts. The controller achieves a mean cross-track error of 0.10 m on straight roads, 0.44 m on roundabouts, and 1.36 m on tight intersections, while maintaining smooth control inputs and bounded actuator effort. A curvature-aware cost term yields a 14.4% reduction in lateral tracking error compared to the curvature-unaware baseline. Benchmarking results indicate that the Raspberry Pi 5 outperforms the NVIDIA Xavier AGX by 1.5–1.6×, achieving mean execution times of 38–45 ms across all scenarios. This demonstrates that advanced NMPC can run in real time on low-cost consumer hardware ($80 vs. $700). Systematic ablation studies reveal the critical role of state weighting (Q) and input regularization (R): removing Q degrades tracking by 10% and destabilizes control effort (+54% acceleration, +477% steering), while omitting R induces oscillatory behavior with +907% acceleration effort. Euler integration provides no computational benefit (+8% solver time) while degrading accuracy by 25%, confirming RK4 as strictly superior. Sensitivity analysis via Latin Hypercube Sampling identifies the prediction horizon (N) and discretization timestep ($\mathrm{\Delta }t$) as dominant parameters. Per-scenario Pareto analysis yields a balanced operating point ($N=15, \mathrm{\Delta }t=0.055$ s) used for all primary evaluations, while a global sweep identifies a robust alternative ($N=12, \mathrm{\Delta }t=0.086$ s) suitable for general deployment tuning. This framework bridges the gap between spline-based local planning and stability-guaranteed NMPC, offering a simulation-validated, real-time solution for embedded autonomous driving research. Future work will focus on hardware-in-the-loop and full-vehicle deployment, integration with high-level decision-making, and learning-enhanced MPC. Full article

Professors, students, and researchers from universities around the world use software distributed under licenses for numerical simulation purposes, which requires a computer with considerable hardware capabilities. This implies a high cost of simulations in engineering applications that require dynamic modeling using numerical methods, particularly in robotics and nonlinear control. This article compares and analyzes the performance of a frugal simulation scheme based on the use of low-cost, free, and open-source technology, specifically a low-power, single-board minicomputer (Raspberry Pi) in conjunction with GNU-Octave software. The benchmark is a numerical simulation of trajectory tracking control in the joint space of a Selective Conformal Assembly Robot Arm (SCARA). To perform this task, a system of coupled nonlinear differential equations is solved in matrix form using a numerical method known as an ODE solver. This solution includes the control law and the dynamic system model derived from Euler–Lagrange formalism. The time complexity and accuracy are analyzed to compare the performance of the frugal simulation tool with that of a conventional simulation setup consisting of a personal computer and MATLAB^TM running the same simulation code. The analysis shows minimal deviations in the numerical solutions and reasonable time complexity. Moreover, the frugality score of this approach and the low acquisition cost of the simulation tool enable the creation of simulation laboratories at universities with limited budgets for education and research. Full article

This manuscript presents a study of the Stress-Driven integral Model (SDM) for the bending response of Bernoulli–Euler nanobeams. Unlike conventional approaches that reformulate the nonlocal integral problem into an equivalent differential form, a direct numerical strategy is developed to solve the integral equation. The proposed framework enables a systematic comparison of six different convolution kernels (Helmholtz, Gaussian, Lorentzian, triangular, Bessel and hyperbolic cosine), highlighting how their mathematical properties influence the structural response. To address issues related to long-range interactions and the potential ill-posedness of the integral operator, an adaptive regularization procedure based on the Morozov discrepancy principle is introduced. Furthermore, a local clipping and renormalization technique is proposed to properly account for boundary effects while preserving the weighted averaging property of the kernels. Validation against available analytical solutions for the Helmholtz kernel demonstrates high accuracy, with errors below 1%. The results show that the nonlocal parameter significantly affects structural rigidity depending on the kernel shape and that the proposed approach ensures consistent convergence to the local solution as the nonlocal parameter tends to zero. Full article

In this work, we derive necessary optimality conditions for a class of fractional variational problems involving Caputo-type derivatives. We consider functionals defined on appropriate spaces of absolutely continuous functions and study both periodic and antiperiodic boundary conditions, treated in a unified framework. The analysis covers the cases $0<\alpha <1$ and $1<\alpha <2$, leading to fractional Euler–Lagrange equations supplemented by suitable transversality conditions. We further extend the results to problems with integral constraints and holonomic constraints, as well as to a fractional Herglotz variational principle. Full article

This study numerically investigates the effects of red blood cell (RBC) volume fraction (hematocrit) and RBC diameter on cell distribution, cell-free layer (CFL) thickness and pressure drop in a microchannel with sudden expansion. Hematocrit levels of 0.2, 0.3, 0.4 and 0.5, together with RBC diameters of 4, 8 and 11 µm, are considered, where deviations from the physiological diameter of 8 μm represent pathological conditions. An Euler–Euler approach is employed to model the multiphase flow, treating RBCs as rigid spherical particles, while the non-Newtonian viscosity of blood is represented using a modified Carreau–Yasuda model. The numerical predictions are validated against existing experimental and numerical data. The effect of volumetric flow rate on RBC distribution is found to be limited; therefore, a representative flow rate of 100 μL/min is adopted for the subsequent analysis. The results show that RBC migration and the resulting cell distribution are strongly governed by RBC size and hematocrit. The pressure drop is primarily influenced by hematocrit, while the effect of RBC size is relatively weak. A minimum value for pressure drop is observed at a hematocrit of 0.3, indicating an optimal hematocrit level for minimizing flow resistance. A parabolic correlation is proposed for predicting the pressure drop as a function of hematocrit, with a maximum relative error of 1.13%. This study contributes to the understanding of pathological RBC size variations and their impact on microscale hemodynamics. Full article

Standard numerical methods such as Runge–Kutta and Euler methods have been widely used to approximate solutions to nonlinear systems. These methods converge to the solution only for small step sizes; for larger time steps, they generally generate spurious or chaotic solutions. In this paper, we consider a malaria propagation model with control for which we construct a second-order nonstandard finite difference scheme that preserves the important mathematical properties of the continuous model, which are positivity, boundedness, and stability of solutions irrespective of the step size. Moreover, we show that the equilibrium points of the discrete model are the same as those of the continuous model. By applying the double mesh principle, we provide evidence that the second-order NSFD scheme approximates the true solution with small errors. Theoretical assertions and numerical results show the advantages of the developed second-order nonstandard finite difference method. Full article

Background: Advanced therapy medicinal products require rigorous preclinical testing to exclude tumorigenicity. Human articular cartilage cells expanded at low density with human platelet lysate show enhanced proliferation, matrix production, and immunomodulatory properties, supporting their use for diffuse cartilage lesions in osteoarthritic joints. This study evaluated tumorigenicity and biodistribution of cartilage cell spheroids generated using two platelet lysate sources. Methods: Cartilage cells were expanded at low density with two platelet lysates and assembled into spheroids. Cytogenetic stability was assessed by metaphase karyotyping following expansion. Immunodeficient mice received subcutaneous implantation and were monitored for 180 days. Human colon carcinoma cells and mouse fibroblasts were used as controls. Clinical follow-up, full organ histopathology, and immunohistochemistry were performed to detect human cell persistence. Results: Expanded cartilage cells showed predominantly normal karyotypes, with rare low-level mosaic chromosomal alterations not detected at the previous passage. Cartilage cell spheroids were well tolerated in vivo, with complete survival and no evidence of tumorigenicity, inflammation, or human cell persistence at implantation sites or distant organs. Control experiments confirmed the sensitivity of the model, and no systemic toxicity was observed. Conclusions: Spheroids derived from cartilage cells are non-tumorigenic, non-migratory, and biologically safe in immunodeficient mice. These findings support their development as cell-based cartilage therapies and align with regulatory recommendations for non-clinical safety evaluation. Full article

We argue that turbulent irreversibility is best explained as an asymptotic feature of a singular inviscid limit—a reclassification of admissible entities and balances at $\nu \to 0$—rather than as a mere residual effect of molecular viscosity. Tracing a conceptual line from Euler and Kármán–Howarth to Onsager, Duchon–Robert, Kato/Prandtl, and modern convex integration results, we show that the limit theory reclassifies the admissible entities: from smooth Euler fields (energy conserving) to rough weak solutions equipped with a positive defect measure in the energy balance. The constant inter-scale process (energy flux) observed at high-Reynolds number therefore persists at $\nu =0$ as a structural feature of the limit ontology. We articulate three selection principles—the local energy inequality, the exact third-order law, and scale-locality—as ontological constraints that reconcile mathematical non-uniqueness with physical uniqueness. A brief conceptual history clarifies how the arrow of time in turbulence emerged through successive shifts of entities and invariants, and a comparison with other singular limit explanations (Boltzmannian irreversibility, shocks, renormalization) situates the account within general foundations of physics. Methodologically, we recast LES/closures as asymptotic mediators validated by flux plateaus and viscosity-free diagnostics, not microscopic subgrid fidelity. Full article

The two most severe cosmological tensions in the Hubble constant $H_0$ and the matter clustering amplitude $S_8$ have the same relative discrepancy of 8.3%, which suggests that they may have a common origin. Modifications of gravity and exotic dark fields with numerous free parameters introduced in the Einstein field equations often struggle to simultaneously alleviate both tensions; thus, we need to look for a common cause within the standard $\Lambda$CDM framework. At the same time, linear perturbation analyses of matter in the expanding $\Lambda$CDM universe have always neglected the impact of comoving peculiar velocities $\mathbf{v}$ (generally thought to be a second-order effect), the same velocities that, in physical space, cannot be fully accounted for in the observed late-time universe when the cosmic distance ladder is used to determine the local value of $H_0$. We have reworked the linear density perturbation equations in the conformal Newtonian gauge (sub-horizon limit) by introducing an additional drag force per unit mass $-\Gamma \left(t\right)\mathbf{v}$ in the Euler equation with $\Gamma \equiv \gamma \left(2H\right)$, where $\gamma \ll 1$ is a positive dimensionless constant and $2H\left(t\right)$ is the time-dependent Hubble friction. We find that a damping parameter of $\gamma =0.083$ is sufficient to resolve the $S_8$ tension by suppressing the growth of structure at low redshifts, starting at $z_{★}\simeq 3.5–6.5$ to achieve $S_8\simeq 0.78–0.76$, respectively. Furthermore, we argue that the physical source causing this additional friction (a tidal field generated by nonlinear structures in the late-time universe) is also responsible for a systematic error in the local determinations of $H_0$—the inability to subtract peculiar tidal velocities along the lines of sight when determining the Hubble flow via the cosmic distance ladder. Finally, the dual action of the tidal field on the expanding background—reducing both the matter and the dark energy sources of the squared Hubble rate $H^2$, thereby holding back the cosmic acceleration $\ddot{a}$—is of fundamental importance in resolving cosmological tensions and can also substantially alleviate the density coincidence problem. Full article

In high-speed parachuting, complex turbulent phenomena (i.e., deadly vortices) may cause problems such as parachute inflation delay or even deployment failure. To address these issues, this study develops a high-precision numerical simulation dummy model in which adaptive mesh generation techniques, combined with Euler–Lagrange bidirectional coupling based on a large eddy simulation, are employed to model the multiphase flow field during parachute descent. The key parameters are adjusted, and the numerical model is refined based on wind tunnel experiments and User-Defined Functions. The bidirectional validation of the experimental and simulated data reveals the mechanism of turbulent flow formation and its evolutionary patterns around the parachutist–parachute system for different lateral and descent velocities during the high-speed descent phase. A prediction model based on a multi-information fusion neural network algorithm is further established to address the challenge in special parachuting scenarios whereby vortices in the flow field around the parachutist prevent the parachute from opening. The model integrates the Haar wavelet to extract global low-frequency features that characterize the overall structure and trends, an energy valley optimization algorithm, a convolutional neural network, a bidirectional long short-term memory network, and a self-attention mechanism to achieve one-second-ahead turbulence prediction. With nine physical quantities as inputs and descent velocity as the output indicator, the model has a Root Mean Square Error of 0.085, a Mean Absolute Error of 0.051, and a Mean Absolute Percentage Error of 0.0021. Full article

In this paper, we establish a new hybrid class of special polynomials, the Gould–Hopper–Fubini-based Appell polynomials. Using the monomiality principle, we derive their generating function and explore related properties and identities. We also investigate symmetry identities and obtain a determinant representation for these polynomials. Finally, we present and discuss results for several special cases of this family and support the derived results with computational studies and visual representations. Full article

Positivity of a linear control system is interpreted as a symmetry with respect to transformations preserving the nonnegative cone of the state space. We study systems on arbitrary time scales and compare positivity criteria for different time scales. This allows us to establish conditions under which Euler discretization of a continuous-time positive system gives rise to a positive system on a discrete time scale. Then we study positive reachability and accessibility of positive systems on various time scales and show invariance of these properties with respect to Euler discretization. Full article

In this paper, we introduce and investigate a new class of analytic functions generated by Euler polynomials through a suitable normalization. Using classical tools from geometric function theory, including coefficient monotonicity, Fejér-type inequalities, MacGregor’s criteria, and Ozaki’s close-to-convexity condition, we establish sufficient conditions for the univalence, starlikeness, convexity, and close-to-convexity of the proposed Euler-polynomial-based normalized function. Sharp radius results for starlikeness, convexity, and close-to-convexity in the disk ${\mathbb{D}}_{1/2}$ are derived by exploiting refined coefficient bounds involving higher-order Euler polynomial terms. Several illustrative examples and graphical demonstrations are provided to verify the theoretical findings. The results obtained extend the known geometric properties of special function-based analytic classes and offer a new perspective on the geometric behavior of Euler polynomials in the unit disk. Full article