Terahertz Wave Guiding by Femtosecond Laser Filament in Air

Femtosecond laser filament generates strong terahertz (THz) pulse in air. In this paper, THz pulse waveform generated by femtosecond laser filament has been experimentally investigated as a function of the length of the filament. Superluminal propagation of THz pulse has been uncovered, indicating that the filament creates a THz waveguide in air. Numerical simulation has confirmed that the waveguide is formed because of the radially non-uniform refractive index distribution inside the filament. The underlying physical mechanisms and the control techniques of this type THz pulse generation method might be revisited based on our findings. It might also potentially open a new approach for long-distance propagation of THz wave in air.Comment: 5 pages, 6 figure

In-sample Curriculum Learning by Sequence Completion for Natural Language Generation

Curriculum learning has shown promising improvements in multiple domains by training machine learning models from easy samples to hard ones. Previous works which either design rules or train models for scoring the difficulty highly rely on task-specific expertise, and cannot generalize. Inspired by the ``easy-to-hard'' intuition, we propose to do in-sample curriculum learning for natural language generation tasks. Our learning strategy starts training the model to generate the last few words, i.e., do sequence completion, and gradually extends to generate the whole output sequence. Comprehensive experiments show that it generalizes well to different tasks and achieves significant improvements over strong baselines

In-situ Construction of Superhydrophilic g-C3N4 Film by Vapor-Assisted Confined Deposition for Photocatalysis

Herein, we report an improved strategy for the synthesis of superhydrophilic g-C3N4 film by vapor-assisted confined deposition method. With minimum amount of precursor, the vapor could be confined in the microenvironment for facilitating the film growth on both sides of the substrates. The obtained films showed similar physiochemical properties with the bulk counterpart and could be peeled off from the substrates by soaking in hot water. The free-standing film is flexible and superhydrophilic, featuring many microfibers atop. The g-C3N4 film from both sides of the substrates could be used in the photocatalytic dye degradation in a repeated manner and showed excellent performance and stability. The current work should shed light on the optimized growth of the g-C3N4 film and could find more application in future device field

Multi-turn Response Selection using Dialogue Dependency Relations

Multi-turn response selection is a task designed for developing dialogue agents. The performance on this task has a remarkable improvement with pre-trained language models. However, these models simply concatenate the turns in dialogue history as the input and largely ignore the dependencies between the turns. In this paper, we propose a dialogue extraction algorithm to transform a dialogue history into threads based on their dependency relations. Each thread can be regarded as a self-contained sub-dialogue. We also propose Thread-Encoder model to encode threads and candidates into compact representations by pre-trained Transformers and finally get the matching score through an attention layer. The experiments show that dependency relations are helpful for dialogue context understanding, and our model outperforms the state-of-the-art baselines on both DSTC7 and DSTC8*, with competitive results on UbuntuV2.Comment: Accepted for publication as a long paper in EMNLP202

The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions

Recent progress in Large Language Models (LLMs) has produced models that exhibit remarkable performance across a variety of NLP tasks. However, it remains unclear whether the existing focus of NLP research accurately captures the genuine requirements of human users. This paper provides a comprehensive analysis of the divergence between current NLP research and the needs of real-world NLP applications via a large-scale collection of user-GPT conversations. We analyze a large-scale collection of real user queries to GPT. We compare these queries against existing NLP benchmark tasks and identify a significant gap between the tasks that users frequently request from LLMs and the tasks that are commonly studied in academic research. For example, we find that tasks such as ``design'' and ``planning'' are prevalent in user interactions but are largely neglected or different from traditional NLP benchmarks. We investigate these overlooked tasks, dissect the practical challenges they pose, and provide insights toward a roadmap to make LLMs better aligned with user needs.Comment: EMNLP 202

Protective Role of Shiitake Mushroom-Derived Exosome-Like Nanoparticles in D-Galactosamine and Lipopolysaccharide-Induced Acute Liver Injury in Mice

Fulminant hepatic failure (FHF) is a rare, life-threatening liver disease with a poor prognosis. Administration of D-galactosamine (GalN) and lipopolysaccharide (LPS) triggers acute liver injury in mice, simulating many clinical features of FHF in humans; therefore, this disease model is often used to investigate potential therapeutic interventions to treat FHF. Recently, suppression of the nucleotide-binding domain and leucine-rich repeat related (NLR) family, pyrin domain containing 3 (NLRP3) inflammasome, was shown to alleviate the severity of GalN/LPS-induced liver damage in mice. Therefore, the goal of this study was to find dietary exosome-like nanoparticles (ELNs) with therapeutic potential in curbing FHF by suppressing the NLRP3 inflammasome. Seven commonly consumed mushrooms were used to extract ELNs. These mushrooms were found to contain ELNs composed of RNAs, proteins, and lipids. Among these mushroom-derived ELNs, only shiitake mushroom-derived ELNs (S-ELNs) substantially inhibited NLRP3 inflammasome activation by preventing inflammasome formation in primary macrophages. S-ELNs also suppressed the secretion of interleukin (IL)-6, as well as both protein and mRNA levels of the Il1b gene. Remarkably, pre-treatment with S-ELNs protected mice from GalN/LPS-induced acute liver injury. Therefore, S-ELNs, identified as potent new inhibitors of the NLRP3 inflammasome, represent a promising class of agents with the potential to combat FHF

Synthesis of Organic Super-Electron-Donors by Reaction of Nitrous Oxide with N‐Heterocyclic Olefins

The reaction of nitrous oxide (N2O) with N-heterocyclic olefins (NHOs) results in cleavage of the N–O bond and formation of azo-bridged NHO dimers. The latter represent very electron-rich compounds with a low ionization energy. Cyclic voltammetry studies show that the dimers can be classified as new organic super-electron-donors, with a reducing power similar to what is found for tetraazafulvalene derivatives. Mild oxidants are able to convert the neutral dimers into radical cations, which can be isolated. Further oxidation gives stable dications

Ellipticity-dependent sequential over-barrier ionization of cold rubidium

We perform high-resolution measurements of momentum distribution on Rb$^{n+}$ recoil ions up to charge state $n=4$, where laser-cooled rubidium atoms are ionized by femtosecond elliptically polarized lasers with the pulse duration of 35 fs and the intensity of 3.3$\times$10$^{15}$ W/cm$^2$ in the over-barrier ionization (OBI) regime. The momentum distributions of the recoil ions are found to exhibit multi-band structures as the ellipticity varies from the linear to circular polarizations. The origin of these band structures can be explained quantitatively by the classical OBI model and dedicated classical trajectory Monte Carlo simulations with Heisenberg potential. Specifically, with back analysis of the classical trajectories, we reveal the ionization time and the OBI geometry of the sequentially released electrons, disentangling the mechanisms behind the tilted angle of the band structures. These results indicate that the classical treatment can describe the strong-field multiple ionization processes of alkali atoms