Possible Luttinger liquid behavior of edge transport in monolayer transition metal dichalcogenide crystals.

In atomically-thin two-dimensional (2D) semiconductors, the nonuniformity in current flow due to its edge states may alter and even dictate the charge transport properties of the entire device. However, the influence of the edge states on electrical transport in 2D materials has not been sufficiently explored to date. Here, we systematically quantify the edge state contribution to electrical transport in monolayer MoS2/WSe2 field-effect transistors, revealing that the charge transport at low temperature is dominated by the edge conduction with the nonlinear behavior. The metallic edge states are revealed by scanning probe microscopy, scanning Kelvin probe force microscopy and first-principle calculations. Further analyses demonstrate that the edge-state dominated nonlinear transport shows a universal power-law scaling relationship with both temperature and bias voltage, which can be well explained by the 1D Luttinger liquid theory. These findings demonstrate the Luttinger liquid behavior in 2D materials and offer important insights into designing 2D electronics

ConFiguRe: Exploring Discourse-level Chinese Figures of Speech

Figures of speech, such as metaphor and irony, are ubiquitous in literature works and colloquial conversations. This poses great challenge for natural language understanding since figures of speech usually deviate from their ostensible meanings to express deeper semantic implications. Previous research lays emphasis on the literary aspect of figures and seldom provide a comprehensive exploration from a view of computational linguistics. In this paper, we first propose the concept of figurative unit, which is the carrier of a figure. Then we select 12 types of figures commonly used in Chinese, and build a Chinese corpus for Contextualized Figure Recognition (ConFiguRe). Different from previous token-level or sentence-level counterparts, ConFiguRe aims at extracting a figurative unit from discourse-level context, and classifying the figurative unit into the right figure type. On ConFiguRe, three tasks, i.e., figure extraction, figure type classification and figure recognition, are designed and the state-of-the-art techniques are utilized to implement the benchmarks. We conduct thorough experiments and show that all three tasks are challenging for existing models, thus requiring further research. Our dataset and code are publicly available at https://github.com/pku-tangent/ConFiguRe.Comment: Accepted to Coling 202

Retrieval-based Full-length Wikipedia Generation for Emergent Events

In today's fast-paced world, the growing demand to quickly generate comprehensive and accurate Wikipedia documents for emerging events is both crucial and challenging. However, previous efforts in Wikipedia generation have often fallen short of meeting real-world requirements. Some approaches focus solely on generating segments of a complete Wikipedia document, while others overlook the importance of faithfulness in generation or fail to consider the influence of the pre-training corpus. In this paper, we simulate a real-world scenario where structured full-length Wikipedia documents are generated for emergent events using input retrieved from web sources. To ensure that Large Language Models (LLMs) are not trained on corpora related to recently occurred events, we select events that have taken place recently and introduce a new benchmark Wiki-GenBen, which consists of 309 events paired with their corresponding retrieved web pages for generating evidence. Additionally, we design a comprehensive set of systematic evaluation metrics and baseline methods, to evaluate the capability of LLMs in generating factual full-length Wikipedia documents. The data and code are open-sourced at WikiGenBench

Study of spatio-temporal modeling in video quality assessment

Video quality assessment (VQA) has received remarkable attention recently. Most of the popular VQA models employ recurrent neural networks (RNNs) to capture the temporal quality variation of videos. However, each long-term video sequence is commonly labeled with a single quality score, with which RNNs might not be able to learn long-term quality variation well. A natural question then arises: What’s the real role of RNNs in learning the visual quality of videos? Does it learn spatio-temporal representation as expected or just aggregating spatial features redundantly? In this study, we conduct a comprehensive study by training a family of VQA models with carefully designed frame sampling strategies and spatio-temporal fusion methods. Our extensive experiments on four publicly available in-the-wild video quality datasets lead to two main findings. First, the plausible spatio-temporal modeling module ( i.e ., RNNs) does not facilitate quality-aware spatio-temporal feature learning. Second, sparsely sampled video frames are capable of obtaining the competitive performance against using all video frames as the input. In other words, spatial features play a vital role in capturing video quality variation for VQA. To our best knowledge, this is the first work to explore the issue of spatio-temporal modeling in VQA

Characteristics and driving factors of power generation performance in microbial fuel cells: an analysis based on the CNKI database

Microbial fuel cells (MFCs) have become one of the most promising technologies in the field of ecology and environmental science due to their dual functions of power generation and pollutant removal. However, the generally low power generation performance of MFCs is one of the bottlenecks constraining their development, and numerous studies have focused on the improvement of power generation performance. The majority of previous empirical studies were based on single experimental data, which means there may be large differences in experimental conditions and settings, leading to various or even contradictory conclusions. In this study, we collected a total of 10,826 cases from 186 publications in the China National Knowledge Infrastructure Database to quantitatively and systematically investigate the general patterns and driving factors of power generation performance in MFCs. Our results showed that (1) the power density, voltage, and reaction duration were significantly lower (~25%) in this study, while the coulombic efficiency and ambient temperature were significantly higher (13.4–33.1%) than those reported in other meta-analyses or review papers; (2) reaction chamber volume and cathode surface area were stronger predictors for the majority of power generation performance indices than other device configuration indices, especially cathode chamber volume, which explained >70% of the variances in power density and coulombic efficiency; (3) ambient temperature, external resistance, and reaction duration had greater effects on power generation performance than other reaction conditions; and (4) substrates with pre-treatment, especially with biological treatment, showed 10–40% higher values for the majority of power generation performance indices compared to pre-treatment with physical and chemical methods, and solid substrates showed better power generation performance than liquid and fluid substrates for the majority of indices. Our results suggest that dual-chamber systems, larger cathode surface areas, neutral pH levels, ambient temperatures of 30–35°C, and biological pre-treatment of substrates may be helpful in improving the power generation performance of MFCs

Chemotherapy combined with radiotherapy can benefit more unresectable HCC patients with portal and/or hepatic vein invasion: a retrospective analysis of the SEER database

BackgroundThe purpose of this study is to evaluate the effects of chemotherapy and radiotherapy on the prognosis of unresectable HCC patients with portal and/or hepatic vein invasion.MethodsA retrospective analysis of unresectable HCC patients with portal and/or hepatic vein invasion registered in the Surveillance, Epidemiology, End Results (SEER) database was performed. The propensity score-matching (PSM) method was used to balance differences between groups. Overall survival (OS) and cancer-specific survival (CSS) were the interesting endpoints. OS was calculated from the date of diagnosis to the date of death caused by any cause or the last follow-up. CSS was defined as the interval between the date of diagnosis and date of death due only to HCC or last follow-up. OS and CSS were analyzed by using Kaplan-Meier analysis, Cox proportional hazards model, and Fine-Gray competing-risk model.ResultsA total of 2,614 patients were included. 50.2% patients received chemotherapy or radiotherapy and 7.5% patients received both chemotherapy and radiotherapy. Compared to the untreated group, chemotherapy or radiotherapy (COR) (HR = 0.538, 95% CI 0.495-0.585, p < 0.001) and chemotherapy and radiotherapy (CAR) (HR = 0.371, 95% CI 0.316-0.436, p < 0.001) showed better OS. In the COR group, Cox analysis results showed AFP, tumor size, N stage and M stage were independent risk factor of OS. Competing-risk analysis results showed AFP, tumor size and M stage were independent risk factor of CSS. In the CAR group, AFP and M stage were independent risk factors of OS. Competing-risk analysis results showed M stage were independent risk factor of CSS. Kaplan Meier analysis showed chemotherapy combined with radiotherapy significantly improves OS (10.0 vs. 5.0 months, p < 0.001) and CSS (10.0 vs. 6.0 months, p = 0.006) than monotherapy.ConclusionAFP positive and distant metastasis are the main risk factors affecting OS and CSS of unresectable HCC patients with portal and/or hepatic vein invasion. Chemotherapy combined with radiotherapy significantly improves OS and CSS of unresectable HCC patients with portal and/or hepatic vein invasion

Satellites in the Ti 1s core level spectra of SrTiO3 and TiO2

Satellites in core level spectra of photoelectron spectroscopy (PES) can provide crucial information on the electronic structure and chemical bonding in materials, particularly in transition metal oxides. This paper explores satellites of the Ti 1s and 2p core level spectra of SrTiO3 and TiO2. Conventionally, soft x-ray PES (SXPS) probes the Ti 2p core level; however, it is not ideal to fully capture satellite features due to its inherent spin-orbit splitting (SOS). Here, hard x-ray PES (HAXPES) provides access to the Ti 1s spectrum instead, which allows us to study intrinsic charge responses upon core-hole creation without the complication from SOS and with favorable intrinsic linewidths. The experimental spectra are theoretically analyzed by two impurity models, including an Anderson impurity model (AIM) built on local density approximation (LDA) and dynamical mean-field theory (DMFT), and a conventional TiO6 cluster model. The theoretical results emphasize the importance of explicit inclusion of higher-order Ti-O charge-transfer processes beyond the nearest-neighboring Ti-O bond to simulate the core level spectra of SrTiO3 and TiO2. The AIM approach with continuous bath orbitals provided by LDA+DMFT represents the experimental spectra well. Crucially, with the aid of the LDA+DMFT method, this paper provides a robust prescription of how to use the computationally cheap cluster model in fitting analyses of core level spectra