Tootfinder

Vision-Language-Action Models Meet World Models: Embodied Agentic AI for Low-Altitude Wireless Networks
Feibo Jiang, Li Dong, Lei Mao, Kezhi Wang, Cunhua Pan, Dong In Kim, Naofal Al-Dhahir
https://arxiv.org/abs/2606.11618 https://arxiv.org/pdf/2606.11618 https://arxiv.org/html/2606.11618
arXiv:2606.11618v1 Announce Type: new
Abstract: Low-Altitude Wireless Networks (LAWNs), composed of Unmanned Aerial Vehicles (UAVs) and other aerial platforms, provide integrated perception, communication, and computation services in low-altitude airspace. However, deploying large generative models in this domain faces three major challenges: 1) Limited embodied action mapping; 2) Inadequate physical environment modeling; 3) Insufficient closed-loop optimization. To address these challenges, this study proposes an Embodied Agentic UAV framework. Centered on a Vision-Language-Action (VLA) model as the execution core, the framework establishes an end-to-end embodied decision-making pipeline from multimodal environmental perception to continuous control generation. In addition, a World Model (WM) is introduced to capture the coupling between UAV actions and environmental state evolution, thereby supporting environment prediction, policy verification, and dynamic optimization. Furthermore, memory and reflection mechanisms are incorporated to form an adaptive closed-loop optimization paradigm of decision, execution, evaluation, and update, thereby enhancing the system's autonomous decision-making capability and continual evolution ability in complex dynamic environments. Experimental results validate its effectiveness in enabling robust, predictive, and sustainable autonomous control in LAWNs.
toXiv_bot_toot

Dream Big, Move Fast
A progressive, contemporary conversation on what it takes to be a dynamic thinker, leader and role model...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/dream-big-move-fast/

How effective normal stress oscillations advance failure in fault gouge: frequency dependence, non-failure window, and the role of dilation
Pritom Sarma, Einat Aharonov, Renaud Toussaint, Stanislav Parez
https://arxiv.org/abs/2607.01448 https://arxiv.org/pdf/2607.01448 https://arxiv.org/html/2607.01448
arXiv:2607.01448v1 Announce Type: new
Abstract: Cyclic pore-pressure or normal stress variations arise both in relation to natural earthquakes and in engineered subsurface systems, yet their effect on fault stability remains poorly constrained at the grain scale. Here we numerically model, using a coupled Discrete Element--fluid dynamics model, the response of a sheared, fluid-saturated or dry, gouge-filled fault to effective normal stress oscillations over a wide frequency range (0.5-10000 Hz). The effective normal stress is oscillated either by cycling the pore-pressure or by directly cycling the normal stress, while keeping the stress state below the Mohr-Coulomb threshold measured in continuous loading. Despite this sub-critical loading, we observe failure across most frequencies, with a non-monotonic frequency dependence. A distinct non-failure window emerges at intermediate frequencies (30-200 Hz), bounded by failure at both lower and higher frequencies; the system exhibits four regimes from cyclic failure-and-arrest to continuous sliding. Pore-pressure and normal stress oscillations produce the same regime structure, confirming that they act as equivalent forcings via Terzaghi's principle, with fluid coupling adding only a delay due to dilatant hardening. Sub-critical failure arises from dilation-induced strength deterioration via two mechanisms: (i) low-frequency cycles allow sufficient time for shear-driven ratcheting dilation, while (ii) high-frequency cycles induce dynamic dilation (acoustic fluidization) via amplified seepage forces, stress gradients and inertial forces. The intermediate non-failure window represents the gap between these mechanisms. These results identify frequency as a controlling parameter for failure in granular materials, with implications for dynamic earthquake triggering and cyclic injection protocols.
toXiv_bot_toot

MazzikaAI: A knowledge-based performance-to-prompt compiler for real-time Arabic maqam accompaniment with a streaming text-to-music model
Jiaxin Du, Boulbaba Abdeljaouad, Yong Zhuang, Haoyu Li
https://arxiv.org/abs/2608.10360 https://arxiv.org/pdf/2608.10360 https://arxiv.org/html/2608.10360
arXiv:2608.10360v1 Announce Type: new
Abstract: Arabic maqam music microtonal, modal, and built on ornamented call and response is among the traditions most underserved by generative music models, whose training frameworks remain predominantly Western and equaltempered. Real time accompaniment sharpens this gap: an AI partner must listen, adapt dynamically, and respect idiomatic microtonal structures. Streaming text to music models provide strong generative capabilities but lack precise control interfaces. We present MazzikaAI, a knowledge based system that uses natural language as the actuator of a realtime control loop. By compiling live MIDI, gesture, and inferred harmony into continuously updated text prompts, MazzikaAI steers an unmodified streaming generator, Google Lyria RealTime, without requiring model finetuning. The system embeds expert knowledge of six core maqamat, characteristic ornaments, and ensemble dynamics, maintaining realtime responsiveness with subsecond keytoaudibleupdate latency. Empirical evaluations demonstrate that dynamic prompt compilation reliably grounds generation in microtonal scales, significantly increasing offgrid quartertone content over baseline generation. Beyond its core implementation, MazzikaAI illustrates how deterministic knowledgebased rules can effectively bridge expert, nonWestern musical traditions and unfinetuned foundation models. This architecture establishes a scalable paradigm for realtime humanAI cocreation, offering a generalizable blueprint for interactive accompaniment, adaptive music education, and culturally inclusive generative audio across diverse global idioms.
toXiv_bot_toot

Bright Galaxies at Cosmic Dawn: A Cloud-Scale Star Formation Model Unifying Variable SFE, IMFs, and Stochasticity
Elie Cueto, Anne Hutter
https://arxiv.org/abs/2607.18868 https://arxiv.org/pdf/2607.18868 https://arxiv.org/html/2607.18868
arXiv:2607.18868v1 Announce Type: new
Abstract: To investigate the origins of the high abundance of UV-bright galaxies at z > 10, we present a new semi-analytic model that bridges the gap between small-scale star formation physics and large-scale galaxy evolution by explicitly tracking discrete star-forming clouds within smoothly evolving dark matter potentials. Unlike conventional semi-analytic models, our approach naturally captures the stochasticity of star formation, allowing us to isolate how cloud properties, star formation efficiencies (SFEs), and stellar initial mass functions (IMFs) shape the star-formation burstiness of early galaxies. Clouds are drawn sequentially from a cloud mass distribution, assigned an SFE and IMF depending on cloud mass, metallicity, and redshift, and evolve under the influence of short-timescale stellar feedback. We identify three distinct star formation regimes arising from the interplay between cloud masses, densities, and feedback timescales: a stochastic, feedback-limited regime in low-mass halos with long quiescent phases; a bursty regime regulated by the cloud mass distribution; and a smooth, continuous regime in massive halos. Our fiducial model adopts a dynamic IMF, an SFE linked to cloud properties and the IMF, and massive, moderately dense clouds. Varying assumptions reveals that top-heavy IMFs and enhanced SFEs in massive clouds amplify burstiness, while altering the upper cloud mass or density normalisation is secondary. Among model ingredients, the IMF most strongly impacts the UV luminosity function (LF), while switching to a constant SFE boosts the faint end, and reducing the maximum cloud mass decreases the bright end. These results demonstrate that cloud-scale physics critically shape early galaxy UV luminosity distributions.
toXiv_bot_toot

A High-Order Flux Reconstruction Actuator-Line Framework for Rotating-Blade Aerodynamics on Fixed Cartesian Grids
Abdullah Al Imran, Meilin Yu
https://arxiv.org/abs/2607.20347 https://arxiv.org/pdf/2607.20347 https://arxiv.org/html/2607.20347
arXiv:2607.20347v1 Announce Type: new
Abstract: This work couples a high-order flux reconstruction/correction procedure via reconstruction (FR/CPR) solver with a rotating actuator-line model (ALM) to simulate rotating-blade aerodynamics on fixed Cartesian grids. Blade loading is represented by volumetric body force source terms projected through an isotropic Gaussian kernel in a blade-attached frame, eliminating the need to resolve blade geometry. Vertical-axis wind turbines (VAWTs) serve as the demonstration configuration, with a modified Boeing-Vertol dynamic stall model incorporated to capture unsteady lift and drag. A mesh-resolution criterion for the Gaussian projection kernel on reasonably coarse meshes is derived. It shows that cost-effective coarse meshes can operate in a mesh-controlled regime with negligible induction feedback, motivating a Double Multiple Streamtube (DMST) correction to recover the physical inflow. Simulations are carried out over a range of tip-speed ratios at a chord-based Reynolds number of Re_c ~ 3.6 x 10^5. The framework is validated against experimental near-wake measurements and previously reported LES-ALM results, and the mean wake profile shows good agreement. The predicted power-coefficient curve matches high-fidelity three-dimensional LES-ALM data to within 6% around the optimal VAWT operation conditions. The framework also captures the regime-dependent influence of dynamic stall, azimuthal blade loading, lift hysteresis, and characteristic wake structures. These results demonstrate that the FR/CPR-ALM framework provides an accurate and computationally efficient geometry-free approach for VAWT analysis, making it well suited for parametric studies and large-scale wind energy applications.
toXiv_bot_toot

ETAS: An Effect-Typed Language for Agent Systems
Huiri Tan, Yikun Wang, Puyang Zhang, Shangyu Li, Jiasi Shen
https://arxiv.org/abs/2607.17780 https://arxiv.org/pdf/2607.17780 https://arxiv.org/html/2607.17780
arXiv:2607.17780v1 Announce Type: new
Abstract: ETAS is a programming language for agent systems that treats model-backed agents, tool calls, prompts, typed memory, human approvals, policies, and execution traces as semantic program elements rather than library conventions. It separates deterministic computation from agentic nondeterminism and externally visible actions while preserving a direct programming style.
We present the core design of ETAS. Its static semantics assigns ordinary types through spec conformance and tracks each computation with two behavioral indices: an escaping effect row and a persistent abstraction of the typed action trace it may request. Specs form a terminating compile-time constraint calculus: type specs provide evidence for polymorphism and resource facts, callable specs constrain function and stage shapes, and trace specs express allow, deny, and temporal constraints. Typing checks requested traces against compiled monitors and emits residual obligations when dynamic resources preclude a complete static proof. The dynamic semantics distinguish requested, handled, denied, and committed events; handlers interpret typed actions without making their requests invisible to authorization or audit.
We formalize a core calculus and state preservation, progress, type/effect soundness, handler trace-transparency, and policy safety. We also implement ETAS in Rust with a command-line interface, typed HIR checks, effect and policy diagnostics, handler checks, and trace-aware execution hooks. ETAS provides a programming-language foundation for reasoning about authorization, nondeterminism, recovery, and audit evidence before and during agent execution.
toXiv_bot_toot

Replaced article(s) found for physics.med-ph. https://arxiv.org/list/physics.med-ph/new
[1/1]:
- An in vivo validation dataset for dynamic volumetric MRI
van Riel, Heesterbeek, Froeling, van den Berg, Sbrizzi
https://arxiv.org/abs/2602.08918 https://mastoxiv.page/@arXiv_physicsmedph_bot/116045795560424625
- Theoretical derivation of blood velocity from TOF-MRA based artery centerline
Abrar Faiyaz
https://arxiv.org/abs/2607.16498 https://mastoxiv.page/@arXiv_physicsmedph_bot/116956889403490719
- Spatiotemporally decoupled super-oscillatory microscopy enables label-free reconstruction of huma...
Xu, Bohndiek, Spicer, Jiang, Wang, Xu, Tan, Williams
https://arxiv.org/abs/2512.13432 https://mastoxiv.page/@arXiv_physicsoptics_bot/115729015904764528
- The Wulff bio-heat transfer model revisited: directional blood enthalpy transport, the biological...
Valerio D'Alessandro, Matteo Falone, Luca Giammichele, Renato Ricci
https://arxiv.org/abs/2607.14017 https://mastoxiv.page/@arXiv_physicssocph_bot/116928575095561464
toXiv_bot_toot