Neural activity dissociation between thought-based and perception-based response conflict

Based on the idea that intentions have different penetrability to perception and thought (Fodor, 1983), four Stroop-like tasks, AA, AW, WA, and WW are used, where the A represents an arrow and the CPPR (closest processing prior to response) is perception, and the W represents a word and the CPPR is thought. Event-related brain potentials were recorded as participants completed these tasks, and sLORETA (standardized low resolution brain electromagnetic tomography) was used to localize the sources at specific time points. These results showed that there is an interference effect in the AA and WA tasks, but not in the AW or WW tasks. The activated brain areas related to the interference effect in the AA task were the PFC and ACC, and PFC activation took place prior to ACC activation; but only PFC in WA task. Combined with previous results, a new neural mechanism of cognitive control is proposed

A new approach to the chronology of caves 268/272/275 in the Dunhuang Mogao Grottoes: combining radiocarbon dates and archaeological information within a Bayesian statistical framework

The construction chronology of three of the earliest Dunhuang Mogao Grottoes (Caves 268, 272, and 275) has been the subject of ongoing debate for over half a century. This chronology is a crucial topic in terms of further understanding of the establishment of the Dunhuang Mogao Grottoes, early Buddhism in the Gansu corridor, and its relationship with Buddhism developed in the Central Plains. Building upon archaeological, art historical and radiocarbon (14C) dating studies, we integrate new 14C data with these previously published findings utilizing Bayesian statistical modeling to improve the chronological resolution of this issue. Thus, we determine that all three of these caves were constructed around AD 410–440, suggesting coeval rather than sequential construction

New extended method for ψ′\psi^{\prime} scaling function of inclusive electron scattering

Scaling analyses have been successfully applied to study the inclusive electron scattering $(\textit{e}, \textit{e}^{\prime})$ over the past few decades. In this paper, we utilize the $\psi^{\prime}$ scaling function in momentum space to analyze the $(\textit{e}, \textit{e}^{\prime})$ cross sections, where the nucleon momentum distributions are derived from self-consistent mean-field calculations. By further introducing the energy and momentum conservation in the scaling analysis, an improved $\psi^{\prime}$ scaling function is proposed to investigate the high-momentum part of the momentum distributions. Using the proposed scaling function, we systematically explore the effects of the nucleon-nucleon short-range correlation ($\textit{NN}$-SRC) on the $(\textit{e}, \textit{e}^{\prime})$ cross sections. From the experimental $(\textit{e}, \textit{e}^{\prime})$ data, the \textit{NN}-SRC strength is further extracted within the framework of the improved $\psi^{\prime}$ scaling function. The studies in this paper offer a new method to investigate the nucleon momentum distributions and the $\textit{NN}$-SRC effects in nuclei

Physical environment research of the family ward for a healthy residential environment

Climate change and population aging are two of the most important global health challenges in this century. A 2020 study by the Environmental Protection Agency showed that average people, particularly older adults, spent 90% of their time at home. This is even more evident during the coronavirus disease 2019 (COVID-19) pandemic. Home-based care models have become a new trend. The health and comfort of the living environment profoundly impacts the well-being of older adults. Therefore, research on the physical environment of the family wards has become an inevitable part of promoting the health of older adults; however, current research is still lacking. Based on the study and analysis of continuous monitoring data related to elements of the physical environment (thermal comfort, acoustic quality, lighting quality, and indoor air quality) of family wards, this paper explores the living behaviors of the participants in this environmental research (open or closed windows, air conditioning, artificial lighting, and television) on the indoor physical environment. (1) While referring to the requirements of international standards for an indoor aging-friendly physical environment, we also discuss and analyze the physical environment parameter values according to Chinese standards. (2) People's life behaviors have different degrees of influence on the elements of indoor physical environments. For example, opening doors and windows can alleviate the adverse effects of indoor environmental quality on the human body better than simply turning on the air conditioner. (3) Owing to the decline in physical function, older adults need special care. Studying the status quo of physical environmental elements and proposing suitable environmental improvement measures for aging are of great significance. (4) This research aims to address global warming and severe aging and to contribute to sustainable environmental development

Oxidation-Resistant, Solution-Processed Plasmonic Ni Nanochain-SiO\u3csub\u3ex\u3c/sub\u3e (x \u3c 2) Selective Solar Thermal Absorbers

Metal oxidation at high temperatures has long been a challenge in cermet solar thermal absorbers, which impedes the development of atmospherically stable, high-temperature, high-performance concentrated solar power (CSP) systems. In this work, we demonstrate solution-processed Ni nanochain-SiOx (x \u3c 2) and Ni nanochain-SiO2 selective solar thermal absorbers that exhibit a strong anti-oxidation behavior up to 600 °C in air. The thermal stability is far superior to previously reported Ni nanoparticle-Al2O3 selective solar thermal absorbers, which readily oxidize at 450 °C. The SiOx (x \u3c 2) and SiO2 matrices are derived from hydrogen silsesquioxane and tetraethyl orthosilicate precursors, respectively, which comprise Si-O cage-like structures and Si-O networks. Fourier transform infrared spectroscopy shows that the dissociation of Si-O cage-like structures and Si-O networks at high temperatures have enabled the formation of new bonds at the Ni/SiOx interface to passivate the surface of Ni nanoparticles and prevent oxidation. X-ray photoelectron spectroscopy and Raman spectroscopy demonstrate that the excess Si in the SiOx (x \u3c 2) matrices reacts with Ni nanostructures to form silicides at the interfaces, which further improves the anti-oxidation properties. As a result, Ni-SiOx (x \u3c 2) systems demonstrate better anti-oxidation performance than Ni-SiO2 systems. This oxidation-resistant Ni nanochain-SiOx (x \u3c 2) cermet coating also exhibits excellent high-temperature optical performance, with a high solar absorptance of ∼90% and a low emittance ∼18% measured at 300 °C. These results open the door towards atmospheric stable, high temperature, high-performance solar selective absorber coatings processed by low-cost solution-chemical methods for future generations of CSP systems

Meeting Action Item Detection with Regularized Context Modeling

Meetings are increasingly important for collaborations. Action items in meeting transcripts are crucial for managing post-meeting to-do tasks, which usually are summarized laboriously. The Action Item Detection task aims to automatically detect meeting content associated with action items. However, datasets manually annotated with action item detection labels are scarce and in small scale. We construct and release the first Chinese meeting corpus with manual action item annotations. In addition, we propose a Context-Drop approach to utilize both local and global contexts by contrastive learning, and achieve better accuracy and robustness for action item detection. We also propose a Lightweight Model Ensemble method to exploit different pre-trained models. Experimental results on our Chinese meeting corpus and the English AMI corpus demonstrate the effectiveness of the proposed approaches.Comment: 5 pages, 2 figures. Paper accepted to the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023), Rhodes, Greec

Improving Long Document Topic Segmentation Models With Enhanced Coherence Modeling

Topic segmentation is critical for obtaining structured documents and improving downstream tasks such as information retrieval. Due to its ability of automatically exploring clues of topic shift from abundant labeled data, recent supervised neural models have greatly promoted the development of long document topic segmentation, but leaving the deeper relationship between coherence and topic segmentation underexplored. Therefore, this paper enhances the ability of supervised models to capture coherence from both logical structure and semantic similarity perspectives to further improve the topic segmentation performance, proposing Topic-aware Sentence Structure Prediction (TSSP) and Contrastive Semantic Similarity Learning (CSSL). Specifically, the TSSP task is proposed to force the model to comprehend structural information by learning the original relations between adjacent sentences in a disarrayed document, which is constructed by jointly disrupting the original document at topic and sentence levels. Moreover, we utilize inter- and intra-topic information to construct contrastive samples and design the CSSL objective to ensure that the sentences representations in the same topic have higher similarity, while those in different topics are less similar. Extensive experiments show that the Longformer with our approach significantly outperforms old state-of-the-art (SOTA) methods. Our approach improve $F_1$ of old SOTA by 3.42 (73.74 -> 77.16) and reduces $P_k$ by 1.11 points (15.0 -> 13.89) on WIKI-727K and achieves an average relative reduction of 4.3% on $P_k$ on WikiSection. The average relative $P_k$ drop of 8.38% on two out-of-domain datasets also demonstrates the robustness of our approach.Comment: Accepted by EMNLP 2023. Codes is available at https://github.com/alibaba-damo-academy/SpokenNLP