Spatial variation of perceived equity and its determinants in a gateway community of Giant Panda National Park, China

Unidad de excelencia María de Maeztu CEX2019-000940-MSocial equity is essential in the governance of protected areas (PAs), as ignoring such consideration can lead to resistance and jeopardize conservation objectives. However, more research is required to understand the spatial heterogeneity of perceived social equity and its underlying spatial factors. Using a survey of 361 respondents, we presented spatial distribution patterns of perceived equity by kernel density estimation (KDE) in Giant Panda National Park, China. The regression analysis showed that local residents who live closer to the PA boundary are more likely to develop negative responses and those who with easy access to tourism spots have more positive procedural and distributional perceptions. Notably, the proximity to the PA authority decreases locals' perceptions of fairness in all aspects, which is potentially due to the opaque participative channels provided by the PA authority. We argue that those spatial differentials in fairness perceptions are driven by the intrinsic discrepancy of biodiversity protection requirements and the unevenly distributed consequences of management policies. Key steps to advance social equity considerations include multi-industry guidance, extending participative channels, and co-producing better compensation plans. Herein, this study appeals to a greater focus on the spatial aspect of social equity issues in PAs

Direct Observation of Photoinduced Charge Separation in Ruthenium Complex/Ni(OH)\u3csub\u3e2\u3c/sub\u3e Nanoparticle Hybrid

Ni(OH)2 have emerged as important functional materials for solar fuel conversion because of their potential as cost-effective bifunctional catalysts for both hydrogen and oxygen evolution reactions. However, their roles as photocatalysts in the photoinduced charge separation (CS) reactions remain unexplored. In this paper, we investigate the CS dynamics of a newly designed hybrid catalyst by integrating a Ru complex with Ni(OH)2 nanoparticles (NPs). Using time resolved X-ray absorption spectroscopy (XTA), we directly observed the formation of the reduced Ni metal site (~60 ps), unambiguously demonstrating CS process in the hybrid through ultrafast electron transfer from Ru complex to Ni(OH)2 NPs. Compared to the ultrafast CS process, the charge recombination in the hybrid is ultraslow (≫50 ns). These results not only suggest the possibility of developing Ni(OH)2 as solar fuel catalysts, but also represent the first time direct observation of efficient CS in a hybrid catalyst using XTA

XTQA: Span-Level Explanations of the Textbook Question Answering

Textbook Question Answering (TQA) is a task that one should answer a diagram/non-diagram question given a large multi-modal context consisting of abundant essays and diagrams. We argue that the explainability of this task should place students as a key aspect to be considered. To address this issue, we devise a novel architecture towards span-level eXplanations of the TQA (XTQA) based on our proposed coarse-to-fine grained algorithm, which can provide not only the answers but also the span-level evidences to choose them for students. This algorithm first coarsely chooses top $M$ paragraphs relevant to questions using the TF-IDF method, and then chooses top $K$ evidence spans finely from all candidate spans within these paragraphs by computing the information gain of each span to questions. Experimental results shows that XTQA significantly improves the state-of-the-art performance compared with baselines. The source code is available at https://github.com/keep-smile-001/opentqaComment: 10 page

Electrical instability of amorphous indium-gallium-zinc oxide thin film transistors under monochromatic light illumination

The electrical instability behaviors of a positive-gate-bias-stressed amorphous indium-gallium-zinc oxide (a-IGZO) thin film transistor(TFT) are studied under monochromatic light illumination. It is found that as the wavelength of incident light reduces from 750 nm to 450 nm, the threshold voltage of the illuminated TFT shows a continuous negative shift, which is caused by photo-excitation of trapped electrons at the channel/dielectric interface. Meanwhile, an increase of the sub-threshold swing (SS) is observed when the illumination wavelength is below 625 nm (∼2.0 eV). The SS degradation is accompanied by a simultaneous increase of the field effect mobility (μFE) of the TFT, which then decreases at even shorter wavelength beyond 540 nm (∼2.3 eV). The variation of SS and μFE is explained by a physical model based on generation of singly ionized oxygen vacancies (Vo⁺) and double ionized oxygen vacancies (Vo²⁺) within the a-IGZO active layer by high energy photons, which would form trap states near the mid-gap and the conduction band edge, respectively.This work was supported by the State Key Program for Basic Research of China under Grant Nos. 2010CB327504, 2011CB922100, 2011CB301900; the National Natural Science Foundation of China under Grant Nos. 60825401, 60936004, 11104130, BK2011556, and BK2011050

A Frustratingly Easy Plug-and-Play Detection-and-Reasoning Module for Chinese Spelling Check

In recent years, Chinese Spelling Check (CSC) has been greatly improved by designing task-specific pre-training methods or introducing auxiliary tasks, which mostly solve this task in an end-to-end fashion. In this paper, we propose to decompose the CSC workflow into detection, reasoning, and searching subtasks so that the rich external knowledge about the Chinese language can be leveraged more directly and efficiently. Specifically, we design a plug-and-play detection-and-reasoning module that is compatible with existing SOTA non-autoregressive CSC models to further boost their performance. We find that the detection-and-reasoning module trained for one model can also benefit other models. We also study the primary interpretability provided by the task decomposition. Extensive experiments and detailed analyses demonstrate the effectiveness and competitiveness of the proposed module.Comment: Accepted for publication in Findings of EMNLP 202

1,3-Bis(1-benzyl-1H-benzimidazol-2-yl)-2-oxapropane

In the title compound, C30H26N4O, the dihedral angle between the two benzimidazole rings is 69.35 (9)°. The dihedral angles between the benzimidazole ring system and the phenyl ring are 76.79 (12) and 86.10 (11)° in the two benzyl­benzimidazole moieties

Research progress on the role and mechanism of ADAMTS9 in atherosclerosis

Atherosclerosis is an inflammatory disease of arterial stenosis caused by the imbalance of lipid metabolism and atherosclerotic plaques clustered on the arterial wall. It is the main pathological process of vascular diseases， such as stroke and coronary heart disease， etc. Atherosclerotic diseases yield high disability and death rates. Recent relevant studies have reported that ADAMTS9 is closely correlated with vascular pathophysiological processes. ADAMTS9 can degrade and assemble extracellular matrix， enhance vascular smooth muscle cell proliferation and migration， provoke pro-inflammatory response， promote intimal thickening， accelerate plaque rupture， and exert anti-angiogenesis effect. In this article， the role and mechanism of ADAMTS9 in the incidence and development of atherosclerosis were mainly summarized

Automatic Context Pattern Generation for Entity Set Expansion

Entity Set Expansion (ESE) is a valuable task that aims to find entities of the target semantic class described by given seed entities. Various NLP and IR downstream applications have benefited from ESE due to its ability to discover knowledge. Although existing bootstrapping methods have achieved great progress, most of them still rely on manually pre-defined context patterns. A non-negligible shortcoming of the pre-defined context patterns is that they cannot be flexibly generalized to all kinds of semantic classes, and we call this phenomenon as "semantic sensitivity". To address this problem, we devise a context pattern generation module that utilizes autoregressive language models (e.g., GPT-2) to automatically generate high-quality context patterns for entities. In addition, we propose the GAPA, a novel ESE framework that leverages the aforementioned GenerAted PAtterns to expand target entities. Extensive experiments and detailed analyses on three widely used datasets demonstrate the effectiveness of our method. All the codes of our experiments will be available for reproducibility.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl