Xiaolong Du, Shichen Jiang, Hongyue Zhang, Huiying Yu, Li Zhang, Kai Ren, Feng Ran
Physician-modified endografts (PMEGs) are increasingly used for complex abdominal aortic aneurysms (AAA), but the patient-specific flow consequences of the geometric reconstruction are not well quantified. This study evaluated PMEG-associated changes in hemodynamic and wall-mechanical surrogate markers. Eight patients were retrospectively analyzed. Pre- and post-PMEG geometries were reconstructed from computed tomography angiography and simulated with pulsatile computational fluid dynamics under matched inlet and outlet conditions. Time-averaged wall shear stress relative residence time and endothelial cell activation potential were quantified; one representative case underwent fluid-structure interaction analysis. Mean velocity increased from approximately 0.8–1.5 m/s ( P = 0.0021), pressure drop decreased ( P = 0.0183), low-shear regions became less extensive, and RRT and ECAP decreased significantly (both P < 0.05). FSI showed lower computed wall deformation after repair. At 1 year, all branch stents remained patent, with no endoleak or reported adverse event. Together with prior paired PMEG simulations, these findings support a favorable hemodynamic and wall-mechanical effect of PMEG in complex anatomy unsuitable for conventional infrarenal EVAR and suggest a less stasis-prone postoperative environment. Larger controlled cohorts remain necessary to determine whether these surrogate changes translate into fewer clinical thrombotic or rupture events. The observed changes arise from PMEG-induced geometric remodeling, which modifies local flow acceleration, separation, near-wall shear, and pressure-loss characteristics.
Rui Costa, William Hornsby, Daniel Kennedy, Lorenzo Zanisi, Nitesh Bhatia, Stanislas J. P. Pamela, Alejandra N. Gonzalez-Beltran, Robert Akers
Gyrokinetic simulations are central to the study of turbulent transport in magnetized fusion plasmas, but their output remains difficult to visualize because the data are complex and must be transformed into real space. This has limited the routine use of advanced three-dimensional visualization in gyrokinetic analysis. We present reproducible workflows for visualizing gyrokinetic simulation data, with a focus on post-processed quantities in three-dimensional physical space. These workflows are designed for use on high-performance computing systems and support a myriad of gyrokinetic codes including GKW, GyroSwin, GENE, CGYRO, and other workflows based on Pyrokinetics. In the proposed workflows, the magnetic-field-aligned data are transformed into real space and written as Visualization Toolkit (VTK) datasets. The intermediary Visualization Toolkit datasets provide flexibility and versatility to target different visualization platforms (e.g., ParaView, Blender, NVIDIA Omniverse) suited to different needs and end users. This flexibility allows for both single-field and multivariate views of potential, density, and temperature fluctuations, and enables the data to be shown within tokamak geometry. The workflows proposed in this work provide a practical basis for further visualization work in gyrokinetics.
The Liesegang phenomenon, conventionally used to explain geological banding, does not account for key features of natural agate, such as irregular band spacing and horizontal onyx structures, leaving its formation mechanism a long-standing enigma. This study demonstrates a two-dimensional (2D) periodic precipitation patterning system governed by a cyclic-voltage-driven reaction–transport–reaction (RTR) process to replicate and elucidate these complex architectures. By cyclically alternating between high and low potentials across diverse electrode configurations in agarose hydrogels, we tracked the spatiotemporal evolution of metal hydroxide precipitates. Systematically adjusting the configuration, number, and metal species (Fe and Cu) of the anodes enabled us to engineer a range of unique 2D striped morphologies. The generated patterns resemble natural agate and onyx, structures that were previously difficult to replicate. Our findings establish the 2D-RTR process as a powerful physicochemical framework complementary to the Liesegang phenomenon, providing key insights into geological morphogenesis driven by intermittent hydrothermal influxes.
Shiyam Alalmaei, Nikoly Hinov, Fadi Al-Turjman, Ramiz Salama, Hugo Alberto González López, Leandro Flórez Aristizábal, Dionicio Neira-Rodado, José Escorcia-Gutierrez, Darius Andriukaitis
Wireless networks are anticipated to continue connecting billions of devices and producing enormous amounts of data with the next sixth-generation (6G) technologies, propelling the development of artificial intelligence applications in a variety of industries. Unmanned aerial vehicles have shown promise in this regard as a way to deal with the problems brought on by the expanding environment. UAVs are especially well-suited for delivering on-demand services to mobile devices because of their special qualities, which include their mobility, flexibility, and capacity to create line-of-sight communication links. This is especially true in areas with limited terrestrial infrastructure, such as hot areas and disaster communication. Therefore, by acting as relaying points, aerial base stations, and data collectors, UAVs may greatly increase the capacity and reach of networks. To address the challenges of energy limitations, spectrum scarcity, and severe co-channel interference in device-to-device (D2D) communication networks supporting UAVs in passive eavesdropping environments, the concept of secrecy energy-efficiency was introduced by considering each user’s privacy level and transmission power limitations. Based on physical layer secure transmission theory, the common problem of optimizing spectrum multiplexing and energy management strategies to maximize the energy efficiency of network secrecy was studied. A resource allocation algorithm combining the two algorithms was proposed to ensure the convergence of the original problem to a global optimal solution using the Dinkelbach algorithm and to transform the non-convex optimization problem into a geometric planning problem using the convex approximation algorithm. The problem was non-linear and non-convex. Simulation results show that the recommended approach can effectively reduce co-channel interference, improve the energy efficiency of network privacy, and achieve a balance between network energy consumption and secure communication performance.
This paper presents a unified artificial periodic structure for multidirectional acoustic wave transmission along complex pathways. The structure employs a two-dimensional, three-component unit cell—consisting of a lead core, rubber cladding, and epoxy matrix—whose resonant dynamics are captured by a double-spring model extended with nonlocal inter-cell coupling corrections. Remarkably, a single lattice configuration, through modest tuning of lattice dimensions, array arrangement, and operating frequency, supports three distinct acoustic functions: negative-refraction-based multidirectional focusing via triangular and polygonal arrays, bandgap-confined directional transmission along straight and curved defect waveguides with switchable beam-splitting behavior, and topologically protected transport exploiting valley edge states. A theoretical framework based on effective-medium parameters and topological band theory (Berry phase and Chern number) is established to elucidate the underlying mechanisms. The predicted transmission characteristics are validated by 500 kHz underwater acoustic experiments on a three-dimensionally printed Z-shaped topological waveguide. The proposed approach is distinguished by its design economy, adaptability, and broad applicability, offering a promising strategy for advanced acoustic wave control with implications for acoustic communication, non-destructive evaluation, and signal detection.
