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Emerging acousto-mechanical metamaterials: From physics-guided design to coupling-driven performance
No full textThe growing demand for materials that simultaneously absorb airborne sound and sustain mechanical loads has catalyzed the rise of acousto-mechanical metamaterials (AMMs)—architected systems that embed acoustic resonances within mechanically efficient architectures, enabling multifunctionality beyond the reach of conventional materials. This review provides in-depth insights into the structural and physical principles that govern acoustic absorption—the central challenge in advancing AMMs. We classify existing architectures and reveal how tailored topologies can achieve superior resonant responses and dissipative pathways. To overcome causality-governed efficiency–thickness trade-offs, we consolidate three physics-informed enhancement strategies: coherent weak resonator coupling, geometry-driven impedance tuning, and intrinsic loss engineering—offering viable paths toward optimal absorption. Critically, we elucidate the structural origins of acousto-mechanical coupling by analyzing synergistic trends and mismatches arising from parent material, unit-cell scale, and topological interdependence. We introduce a three-tier coupling framework based on geometry-sharing levels, clarifying when acoustic and mechanical functions can be decoupled and when they demand co-optimization. Finally, we outline key challenges and propose future directions in functional integration, AI-driven development, and real-world deployment. Positioned at the intersection of geometry, physics, and multifunctionality, AMMs are poised to serve as a versatile platform for next-generation engineered systems.</p
Simultaneous Multiwavelength Observations of the Repeating Fast Radio Burst FRB 20190520B with Swift and FAST
No full textAmong several dozen known repeating fast radio bursts, those precisely localized offer the best opportunities to explore their multiwavelength counterparts, which are key to uncovering their origins. Here we report our X-ray, ultraviolet (UV), and optical observations with the Swift satellite of the repeating FRB 20190520B, in coordination with simultaneous radio observations with the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Our aim was to detect potentially associated multiwavelength bursts and identify any persistent multiwavelength counterparts to the associated persistent radio source (PRS). While a total of 10 radio bursts were detected by FAST during the Swift observations, we detected no X-ray, UV, or optical bursts in accompany with the radio bursts. We obtained the energy upper limits (3σ) on any multwavelength bursts as follows: 5.03 × 1047 erg in the hard X-ray band (15-150 keV), 7.98 × 1045 erg in the soft X-ray band (0.3-10 keV), and 4.51 × 1044 erg in the U band (3465 Å), respectively. The energy ratio between soft X-ray (0.3-10 keV) and radio emission of the bursts is constrained as 7, and the ratio between optical (U band) and radio as 6. We detect no multiwavelength counterpart to the PRS. The 3σ luminosity upper limits are 1.04 × 1047 (15-150 keV), 8.81 × 1042 (0.3-10 keV), 9.26 × 1042 (UVW1), and 2.54 × 1042 erg s−1 (U), respectively. We show that the PRS is much more radio-loud than representative pulsar wind nebulae, supernova remnants, extended jets of Galactic X-ray binaries, and ultraluminous X-ray sources, suggestive of boosted radio emission of the PRS.link_to_subscribed_fulltex
Shared properties of merger-driven long-duration gamma-ray bursts
No full textContext. The recent detections of bright optical/infrared kilonova signals following two long-duration gamma-ray bursts (LGRBs), GRBa 211211A and GRB 230307A, have significantly challenged the traditional classification of GRBs. These merger-driven LGRBs may represent a distinct GRB population, sparking interest in their progenitors and central engines. Aims. Traditional GRB classification methods often struggle to distinguish merger-driven LGRBs from traditional merger-driven short-duration GRBs resulting from compact object mergers and from collapse-driven LGRBs produced by massive stars. We thus aim to explore the shared properties in terms of hardness, energy, and duration among observed merger-driven LGRB events, thereby identifying their observed differences from the traditional GRB population. Methods. We collected a sample of merger-driven LGRBs with known redshifts, including observed information on their main emission (ME) and whole emission (WE) phases. Treating ME and WE properties as two independent sets of information, we applied several GRB classification methodologies to explore their potential shared properties. Results. Using the phenomenologically defined energy-hardness (EH) parameter, characterized by the intrinsic hardness and energy of GRBs, and the duration of GRBs, we identified a probable universal linear correlation across merger-driven LGRBs that holds regardless of whether their ME or WE phases are considered. Conclusions. We propose that such shared properties of merger-driven LGRBs are unlikely to arise from the low-redshift selection effect, and they become particularly intriguing when compared with the relatively weak correlations or lack of correlation observed in traditional merger-driven short-duration GRBs (with or without extended emissions) and collapse-driven LGRBs. Our newly proposed correlation highlights the necessity for further investigation into the observations of merger-driven LGRBs and the physical mechanisms underlying the empirical correlation.link_to_subscribed_fulltex
Hyperactive Repeating Fast Radio Bursts from Rotation-modulated Starquakes on Magnetars
No full textThe nondetection of periodicity related to rotation challenges magnetar models for fast radio bursts (FRBs) with FRB emission from close to the magnetar surface. Moreover, a bimodal distribution of the burst waiting times is widely observed in hyperactive FRBs, a significant deviation from the exponential distribution expected from stationary Poisson processes. By combining the epidemic-type aftershock sequence earthquake model and the rotating vector model involving the rotation of the magnetar and orientations of the spin and magnetic axes, we find that starquake events modulated by the rotation of FRB-emitting magnetar can explain the bimodal distribution of FRB waiting times, as well as the nondetection of periodicity in hyperactive repeating FRBs. We analyze data from multiple FRB sources, demonstrating that differences in waiting time distributions, and to some extent, observed energies can be explained by varying parameters related to geometric properties of the magnetar FRB emission and starquake dynamics. Our results show that the assumption that all FRBs are repeaters is compatible with our model. Notably, we find that hyperactive repeaters tend to have small magnetic inclination angles in order to hide their periodicity. We also show that our model can reproduce the waiting time distribution of a pulsar phase of the galactic magnetar SGR J1935+2154 with a larger inclination angle than the hyperactive repeaters, which could explain the detection of spin period and the relatively low observed energy for FRBs from the magnetar. The spin periods of hyperactive repeaters are not well constrained, but most likely fall in the valley region between the two peaks of the waiting time distributions.link_to_subscribed_fulltex
Designing Mathematics Hybrid Classrooms in High School: The Cases of Nicoletta and Lorenza
No full textOnline math videos are spreading in the world wide web, but little research in mathematics education focuses on the ways teachers use these videos in their teaching practices, if any. In particular, we claim that it is of crucial importance to investigate how teachers’ beliefs and goals influence their choices about planning and delivering mathematics lessons that resort to this kind of resource. In the present chapter we present two cases that add complexity to the case of Valeria, described in the previous chapter.link_to_subscribed_fulltex
Novel Partitioning-Based Approach for Electromigration Assessment With Neural Networks
No full textDue to continuing technology scaling, electromigration (EM) remains a prominent reliability concern in integrated circuit design. Traditional empirical methods often result in over-design in very large scale integration (VLSI) due to model inaccuracy. Recently, researchers have focused on analyzing EM susceptibility by tracking hydrostatic stress evolution in metal lines, governed by computationally expensive partial differential equations (PDEs). In this paper, we propose a partitioning-based approach using neural networks to efficiently forecast the stress evolution along interconnect trees during the void nucleation and growth phases. This approach begins by decomposing the interconnect tree into subcomponents, providing computationally efficient analytical solutions for predicting stress evolution within each subtree. Subsequently, we employ a lightweight neural network to reassemble these components with their corresponding solutions to the original structure, ensuring accurate stress prediction. This divide-and-conquer strategy can accommodate various tree structures, with offshoots at arbitrary junctions, and holds substantial promise for using NN-based methods to solve mesh-free stress evolution on much larger interconnect trees than previously possible, with reduced computational overhead and heightened accuracy. The proposed approach eliminates the need for time discretization and grid meshing typically required in numerical methods. Numerical results confirm its advantages in accuracy and computational efficiency
Multi-Objective Aerial Collaborative Secure Communication Optimization via Generative Diffusion Model-Enabled Deep Reinforcement Learning
No full textDue to flexibility and low-cost, unmanned aerial vehicles (UAVs) are increasingly crucial for enhancing coverage and functionality of wireless networks. However, incorporating UAVs into next-generation wireless communication systems poses significant challenges, particularly in sustaining high-rate and long-range secure communications against eavesdropping attacks. In this work, we consider a UAV swarm-enabled secure surveillance network system, where a UAV swarm forms a virtual antenna array to transmit sensitive surveillance data to a remote base station (RBS) via collaborative beamforming (CB) so as to resist mobile eavesdroppers. Specifically, we formulate an aerial secure communication and energy efficiency multi-objective optimization problem (ASCEE-MOP) to maximize the secrecy rate of the system and to minimize the flight energy consumption of the UAV swarm. To address the non-convex, NP-hard and dynamic ASCEE-MOP, we propose a generative diffusion model-enabled twin delayed deep deterministic policy gradient (GDMTD3) method. Specifically, GDMTD3 leverages an innovative application of diffusion models to determine optimal excitation current weights and position decisions of UAVs. The diffusion models can better capture the complex dynamics and the trade-off of the ASCEE-MOP, thereby yielding promising solutions. Simulation results highlight the superior performance of the proposed approach compared with traditional deployment strategies and some other deep reinforcement learning (DRL) benchmarks. Moreover, performance analysis under various parameter settings of GDMTD3 and different numbers of UAVs verifies the robustness of the proposed approach
Novel ductile and durable engineered cementitious composite columns reinforced with steel-FRP composite bars: Axial compression behavior and design
No full textNovel engineered cementitious composite (ECC) columns reinforced with hybrid reinforcement (longitudinal steel-FRP composite bars (SFCBs) and GFRP stirrups) exhibit superior load capacity, ductility, and corrosion resistance. However, the lack of research on their axial compression behavior and the key parameters seriously limits their safe application. To address this research gap, experimental investigations of 22 column specimens were conducted to evaluate their axial compression behavior. The effects of matrix type, ECC strength, hybrid reinforcement, longitudinal reinforcement type, longitudinal reinforcement ratio, and volumetric stirrup ratio were discussed. The test results show that, compared to concrete columns, unreinforced and reinforced ECC columns have 12.5 % and 10.7 % higher load capacity, respectively, with enhanced ductility characteristics. The use of ECC effectively reduces specimen damage. Longitudinal SFCBs can work synergistically with ECC, efficiently maintaining their integrity before ECC crushing. Notably, replacing longitudinal steel bars with equal-stiffness SFCBs leads to similar compression behavior of columns, including axial load capacity and ductility. The excellent tensile properties and fiber bridging effect of ECC slow the development of stirrup strain and prevent premature slip of GFRP stirrups. Furthermore, a modified prediction model of axial load capacity was proposed, which has excellent accuracy for this novel type of column.</p
A photoswitchable phase-reversible gel engine for systemic redox homeostasis remodeling and on-demand chemodynamic immunotherapy with sustainable immunostimulation
No full textChemodynamic therapy (CDT) efficacy in the tumor microenvironment (TME) remains compromised. Inspired by the potential of fever-like heat to activate a redox-favorable microenvironment, mild photothermal therapy (mPTT) is expected to sensitize tumors to CDT, turning “redox-cold” tumors into “redox-hot” ones. Herein, an injectable gel engine (LMFT@SG-R) is meticulously constructed based on the co-encapsulation of R848 and β-lapachone (LAP)-loaded metal–organic framework-199 (MOF-199) within a lipidic gel reservoir with the unique ability of thermally reversible sol–gel phase transformation. With mPTT reprogramming TME, the custom-designed LMFT@SG-R can realize systemic redox homeostasis remodeling through mPTT-activated chemodynamic immunotherapy (MPCIT). Once reaching the TME, LMFT@SG-R quickly hydrates into solid gel and subsequently undergoes gel-to-sol transformation under mild NIR laser irradiation, resulting in on-demand release of LMFT and R848 for controllable CDT and immunostimulation. LMFT undergoes stepwise degradation for sequential release of Fe3+, Cu2+ and LAP, which can promote ROS cascade amplification owing to the upregulation of HSP70/NQO1 axis upon mild hyperthermia, resulting in robust ICD effects and T lymphocytes infiltrations together with R848. Notably, the controllable immunostimulation can facilitate robust abscopal effects and prominent suppression of distal tumors. The well-designed LMFT@SG-R may represent an updated CDT catalyst with the highly-integrated gel engine for chained-cooperative MPCIT