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Abstract We report on the development of a highly sensitive electric field induced second harmonic generation diagnostic setup capable of measuring electric field strengths as low as 1 $\mathrm{V}{\mathrm{cm}}^{-1}$at the picosecond time scale under atmospheric pressure conditions. This unprecedented sensitivity is achieved through passive homodyne detection, which utilizes stray signals generated by an optical component in the beam path. Our detection limit of 0.3–0.5 $\mathrm{V}{\mathrm{cm}}^{-1}$represents an improvement of over 2–3 orders of magnitude compared to previous reports (100–1000 $\mathrm{V}{\mathrm{cm}}^{-1}$) in the literature. Additionally, we demonstrate sensitivity to the polarity of the electric field. Experimental results are corroborated by simulations of the 400 ps time-resolved homodyne process, offering deeper insights into the enhanced detection capabilities and the system’s ability to resolve the field sign. 

We report on the experimental observation of non-resonant, second-order optical sum-frequency generation (SFG) in five different atomic and molecular gases. The measured signal is attributed to a SFG process by characterizing its intensity scaling and its polarization behavior. We show that the electric quadrupole mechanism cannot explain the observed trends and suggest a mechanism based on symmetry breaking along the incident beam path arising from laser-induced species ground state number density gradients. Our results demonstrate that the SFG is about four orders of magnitude stronger than the third-harmonic generation (THG) and independent from any externally applied electric fields. These features make this method suitable for gas number density measurements at the picosecond time scale in reactive flows and plasmas. 

To address the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have become a critical tool for integrating large volumes of heterogeneous data to enable efficient information retrieval and automated knowledge discovery. However, transforming unstructured scientific literature into KGs remains a significant challenge, with previous methods unable to achieve human-level accuracy. Here we used an information extraction pipeline that won first place in the LitCoin Natural Language Processing Challenge (2022) to construct a large-scale KG named iKraph using all PubMed abstracts. The extracted information matches human expert annotations and significantly exceeds the content of manually curated public databases. To enhance the KG’s comprehensiveness, we integrated relation data from 40 public databases and relation information inferred from high-throughput genomics data. This KG facilitates rigorous performance evaluation of automated knowledge discovery, which was infeasible in previous studies. We designed an interpretable, probabilistic-based inference method to identify indirect causal relations and applied it to real-time COVID-19 drug repurposing from March 2020 to May 2023. Our method identified around 1,200 candidate drugs in the first 4 months, with one-third of those discovered in the first 2 months later supported by clinical trials or PubMed publications. These outcomes are very challenging to attain through alternative approaches that lack a thorough understanding of the existing literature. A cloud-based platform (https://biokde.insilicom.com) was developed for academic users to access this rich structured data and associated tools. 

Abstract Microbial biofilms are of critical concern because of their recalcitrance to antimicrobials. Cold atmospheric plasmas (CAP) represent a promising biofilm remediation strategy as they generate reactive oxygen and nitrogen species (RONS), but mechanisms underpinning CAP‐biofilm interactions remain unknown. We assess the impact of treatment modality on biofilm inactivation and show that CAP killing ofStaphylococcus aureusbiofilms is dependent on treatment conditions, including solution chemistry. In dry treatments, biofilms are locally ablated due to plasma‐produced O flux. For saline‐submerged biofilms, while we show that ClO⁻is generated at high concentrations in larger treatment volumes, CAP inactivation at low ClO⁻concentrations implicates other reaction pathways. Finally, we demonstrate CAP efficacy over conventional antimicrobials, underscoring its promise as a biofilm treatment approach. 

Abstract Mimicry is a biological camouflage phenomenon whereby an organism can change its shape and color to resemble another object. Herein, the idea of biological mimicry and rich degrees of freedom in metasurface designs are combined to realize holographic mimicry devices. A general mathematical method, called phase matrix transformation, to accomplish the holographic mimicry process is proposed. Based on this method, a dynamic metasurface hologram is designed, which shows an image of a “bird” in the air, and a distinct image of a “fish” when the environment is changed to oil. Furthermore, to make the mimicry behavior more generic, holographic mimicry operating at dual wavelengths is also designed and experimentally demonstrated. Moreover, the fully independent phase modulation realized by phase matrix transformation makes the working efficiency of the device relatively higher than the conventional multiwavelength holographic devices with off‐axis illumination or interleaved subarrays. The work potentially opens a new research paradigm interfacing bionics with nanophotonics, which may produce novel applications for optical information encryption, virtual/augmented reality (VR/AR), and military camouflage systems.