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Zhao Jiang

Publications and source records attributed to Zhao Jiang.

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Topographic Modulation of Martian Near-Surface Winds: Insights from Perseverance Measurements and CFD Modeling in Jezero Crater

Near-surface wind fields on Mars are profoundly modulated by complex topography, yet fine-scale wind field characteristics remain poorly resolved for key geomorphological units such as deltas, valleys, and impact craters, due to the spatial constraints of lander-based wind observations. To address this, we identified three dominant wind directions using measured near-surface wind data from the Perseverance rover at Jezero Crater and then integrated in-situ wind measurements with high-resolution numerical modeling. We established a high-resolution three-dimensional (3D) terrain model encompassing key local geomorphic units, including the delta, an impact crater, and nearby mesas, and performed Computational Fluid Dynamics (CFD) simulations under the above-mentioned three dominant wind directions. The results reveal a robust coupling mechanism between local topography and near-surface wind field structures. We demonstrate that wind speed is significantly enhanced over windward slopes but evidently attenuated within depressions and crater floors. Crucially, significant wind direction deflection angles were particularly evident in areas characterized by steeper slopes. For instance, wind flow exhibited a symmetrical deflection pattern along the opposing inner walls of the modeled impact crater, but stabilizing on the crater floor. Spatial comparisons indicate that wind deflection is most pronounced over steeper slopes, while sector-based distributions within the impact crater reveal a consistent symmetry between opposing wall and floor regions. These findings offer new and critical insights into the intimate connection between Martian surface aeolian erosion/deposition processes and local topographic evolution, which is vital for interpreting the sedimentary history of Jezero Crater.

physics.geo-ph

UFO2: The Desktop AgentOS

Recent Computer-Using Agents (CUAs), powered by multimodal large language models (LLMs), offer a promising direction for automating complex desktop workflows through natural language. However, most existing CUAs remain conceptual prototypes, hindered by shallow OS integration, fragile screenshot-based interaction, and disruptive execution. We present UFO2, a multiagent AgentOS for Windows desktops that elevates CUAs into practical, system-level automation. UFO2 features a centralized HostAgent for task decomposition and coordination, alongside a collection of application-specialized AppAgent equipped with native APIs, domain-specific knowledge, and a unified GUI--API action layer. This architecture enables robust task execution while preserving modularity and extensibility. A hybrid control detection pipeline fuses Windows UI Automation (UIA) with vision-based parsing to support diverse interface styles. Runtime efficiency is further enhanced through speculative multi-action planning, reducing per-step LLM overhead. Finally, a Picture-in-Picture (PiP) interface enables automation within an isolated virtual desktop, allowing agents and users to operate concurrently without interference. We evaluate UFO2 across over 20 real-world Windows applications, demonstrating substantial improvements in robustness and execution accuracy over prior CUAs. Our results show that deep OS integration unlocks a scalable path toward reliable, user-aligned desktop automation.

cs.AI

Efficient short-wave infrared upconversion by self-sensitized holmium-doped nanoparticles

Photon upconversion, combining several low-energy photons to generate one high-energy photon is of wide interest for biomedical, catalytic and photonic applications. Lanthanide-doped nanoparticles (LnNP) are a unique type of upconversion nanoconverter, which can realize ultralarge anti-Stokes shift (>1000 nm) and high photostability, without photo-bleaching and photo-blinking. The excitation wavelength of LnNPs has been limited to the second near-infrared window (1000-1700 nm), mainly sensitized by erbium ions with absorption centered around 1.5 $\mu$m. Here, we demonstrate novel self-sensitized holmium (Ho)-doped nanoconverters to further expand the sensitization range to the short-wave infrared at 2 $\mu$m and achieve efficient upconversion to 640 nm. We show that this upconversion is a 4-photon conversion process with an underlying energy transfer upconversion mechanism. Via careful control of dopant concentration and shelling we achieve a relative upconversion-to-downconversion efficiency up to 15.2%, more than half the theoretical maximum. The placement of the Ho doped LnNPs into a plasmonic nanocavity device enables large gains in emission intensity (up to 32-fold), due to the dramatic shortening of the emission lifetime of Ho from 29 $\mu$s to <1 ns, indicating a high Purcell-enhancement factor of 3x10$^4$. These results open new possibilities at the frontier of short-wave infrared upconversion and the nanoplasmonic enhancement of LnNP emission, with potential applications in detection, theranostics, photonics and optoelectronics.

physics.optics

CropCraft: Complete Structural Characterization of Crop Plants From Images

The ability to automatically build 3D digital twins of plants from images has countless applications in agriculture, environmental science, robotics, and other fields. However, current 3D reconstruction methods fail to recover complete shapes of plants due to heavy occlusion and complex geometries. In this work, we present a novel method for 3D modeling of agricultural crops based on optimizing a parametric model of plant morphology via inverse procedural modeling. Our method first estimates depth maps by fitting a neural radiance field and then optimizes a specialized loss to estimate morphological parameters that result in consistent depth renderings. The resulting 3D model is complete and biologically plausible. We validate our method on a dataset of real images of agricultural fields, and demonstrate that the reconstructed canopies can be used for a variety of monitoring and simulation applications.

cs.CV

Demonstration of topological wireless power transfer

Recent advances in non-radiative wireless power transfer (WPT) technique essentially relying on magnetic resonance and near-field coupling have successfully enabled a wide range of applications. However, WPT systems based on double resonators are severely limited to short- or mid-range distance, due to the deteriorating efficiency and power with long transfer distance. WPT systems based on multi-relay resonators can overcome this problem, which, however, suffer from sensitivity to perturbations and fabrication imperfections. Here, we experimentally demonstrate a concept of topological wireless power transfer (TWPT), where energy is transferred efficiently via the near-field coupling between two topological edge states localized at the ends of a one-dimensional radiowave topological insulator. Such a TWPT system can be modelled as a parity-time-symmetric Su-Schrieffer-Heeger (SSH) chain with complex boundary potentials. Besides, the coil configurations are judiciously designed, which significantly suppress the unwanted cross-couplings between nonadjacent coils that could break the chiral symmetry of the SSH chain. By tuning the inter- and intra-cell coupling strengths, we theoretically and experimentally demonstrate high energy transfer efficiency near the exceptional point of the topological edge states, even in the presence of disorder. The combination of topological metamaterials, non-Hermitian physics, and WPT techniques could promise a variety of robust, efficient WPT applications over long distances in electronics, transportation, and industry.

physics.app-ph