2-Benzyl-benzofurans from the tubers of Ophiopogon japonicus

Additional file 1. NMR spectra of compounds 1–3

TOWARDS SEMANTIC NETWORK OF PHILOSOPHY TERMINOLOGIES FOR LEARNING IN UNIVERSITY IN VIETNAM

Semantic network is so far an effective way for knowledge representation, especially if the matter deals with complexity of terminologies and concepts, which are not standalone, but connected by various relations. One among these fields of knowledge is philosophy, and one fact that the study students of university always face with difficulties when address the system of terminologies and concepts of philosophy. In practice, various tools are using by teachers for helping students understand philosophy terminologies and concepts, i.e. using mindmap tools. In this paper, we suggest a use of semantic network as a tool for representation of key terminologies in philosophy of Marxism that have been teaching in Vietnamese universities. For this purpose, the authors of the paper carefully investigate all materials of appropriate learning; make a selection and classification for setting up of terminologies; build a semantic network of these terminologies for a conceptional model. An effort is providing to design one software system with semantic updating, selecting and representing. These results are under the project “Studying and building semantic network of concepts in philosophy discipline for teaching and researching activities” ID: QG.18.46, in a University of Social Sciences and Humanities of Hanoi National University. Article visualizations

PRELIMINARY DETERMINATION OF POLYCYCLIC AROMATIC HYDROCARBON (PAHS) IN AIR ENVIRONMENT AT MAJOR TRAFFIC JOINTS OF HANOI

Joint Research on Environmental Science and Technology for the Eart

CONTRIBUTION ESTIMATE OF PAHS TOXIC COMPOUNDS IN AIR ENVIRONMENT AT MAJOR TRAFFIC JOINTS OF HANOI, VIETNAM

Joint Research on Environmental Science and Technology for the Eart

Calculation of nonlinear vibrations of piecewise-linear systems using the shooting method

In this paper, an explicit formulation of the shooting scheme for computation of multiple periodic attractors of a harmonically excited oscillator which is asymmetric with both stiffness and viscous damping piecewise linearities is derived. The numerical simulation by the shooting method is compared with that by the incremental harmonic balance method (IHB method), which shows that the shooting method is in many respects distinctively advantageous over the incremental harmonic balance method

User’s satisfaction with information system quality: An empirical study on the hospital information systems in Ho Chi Minh City, Vietnam

User satisfaction with information system quality has long been a substantial topic in the literature of information system (IS). Based on the key constructs of IS success model (including system quality and information quality) and technology acceptance model (including perceived ease of use and perceived usefulness), this paper builds and validates a theoretical framework to explain user satisfaction with information system quality. A survey study with AMOS-SEM analysis of 363 users of management information systems in 9 hospitals in HCMC, Vietnam showed that 12 of 14 hypotheses were empirically supported. The findings affirmed the direct influence of system quality, information quality and top management support on perceived ease of use, perceived usefulness and trust, and then on user satisfaction. The results also reinforced the impact of perceived ease of use on perceived usefulness, and the joint influence of perceived usefulness and trust on user satisfaction. The paper is among the first studies, in the healthcare sector, to empirically identify both information system quality and top management support in predicting user acceptance of and satisfaction with information system implementation in organizational settings. The theoretical and managerial implications of the paper were derived

Fast Temporal Wavelet Graph Neural Networks

Spatio-temporal signals forecasting plays an important role in numerous domains, especially in neuroscience and transportation. The task is challenging due to the highly intricate spatial structure, as well as the non-linear temporal dynamics of the network. To facilitate reliable and timely forecast for the human brain and traffic networks, we propose the Fast Temporal Wavelet Graph Neural Networks (FTWGNN) that is both time- and memory-efficient for learning tasks on timeseries data with the underlying graph structure, thanks to the theories of multiresolution analysis and wavelet theory on discrete spaces. We employ Multiresolution Matrix Factorization (MMF) (Kondor et al., 2014) to factorize the highly dense graph structure and compute the corresponding sparse wavelet basis that allows us to construct fast wavelet convolution as the backbone of our novel architecture. Experimental results on real-world PEMS-BAY, METR-LA traffic datasets and AJILE12 ECoG dataset show that FTWGNN is competitive with the state-of-the-arts while maintaining a low computational footprint. Our PyTorch implementation is publicly available at https://github.com/HySonLab/TWGNNComment: arXiv admin note: text overlap with arXiv:2111.0194

ViWikiFC: Fact-Checking for Vietnamese Wikipedia-Based Textual Knowledge Source

Fact-checking is essential due to the explosion of misinformation in the media ecosystem. Although false information exists in every language and country, most research to solve the problem mainly concentrated on huge communities like English and Chinese. Low-resource languages like Vietnamese are necessary to explore corpora and models for fact verification. To bridge this gap, we construct ViWikiFC, the first manual annotated open-domain corpus for Vietnamese Wikipedia Fact Checking more than 20K claims generated by converting evidence sentences extracted from Wikipedia articles. We analyze our corpus through many linguistic aspects, from the new dependency rate, the new n-gram rate, and the new word rate. We conducted various experiments for Vietnamese fact-checking, including evidence retrieval and verdict prediction. BM25 and InfoXLM (Large) achieved the best results in two tasks, with BM25 achieving an accuracy of 88.30% for SUPPORTS, 86.93% for REFUTES, and only 56.67% for the NEI label in the evidence retrieval task, InfoXLM (Large) achieved an F1 score of 86.51%. Furthermore, we also conducted a pipeline approach, which only achieved a strict accuracy of 67.00% when using InfoXLM (Large) and BM25. These results demonstrate that our dataset is challenging for the Vietnamese language model in fact-checking tasks

Aging in the Air: The Impact of Carbon Emissions on Health-Related Quality of Life

In this paper, we analyse the impacts of climate change, in particular greenhouse gases on people’s life quality in general, and physical and mental health in particular. These outcomes are taken from the Survey of Health, Ageing and Retirement in Europe which took place from 2004 to 2019. We provide a wealth of evidence that shows the adverse impacts of greenhouse gases emission. For instance, doubling the amount of carbon dioxide emission would reduce the quality of life of a person aged 50 by 3.8 percent. The effects on mental health are more noticeable than those on physical health. These effects are, however, not constant across ages. Middle-aged people are more vulnerable than older ones

COVID-19, lockdown and labor uncertainty

In this paper, we investigate the impact of containment and closure poli- cies amid the COVID-19 pandemic on the labor market. We show that these effects depend on the presence of labor uncertainty. In the absence of labor uncertainty, the containment and closure policy resulted in people applying fewer self-protection measures, facing lower income and saving more. We predict that workers will lose their job as a consequence of this policy if and only if the containment elasticity of labor demand is sufficiently large. By contrast, when labor uncertainty is introduced, our model predicts more self-protection, more job loss and fewer savings as a result of a lockdown. In addition, income loss occurs if and only if the elasticity of labor demand is large enough. We test our predictions by employing new survey data collected on representative samples across 6 countries: China, Japan, South Korea, Italy, the UK, and the U.S. The survey collected information from households about their work and living situations and their income and socio-demographic characteristics. We find that young, low-income workers and urban dwellers are more vulnerable to containment and closure policies as they are more likely to lose their jobs and income. More importantly, our data provides supporting evidence to all of the predictions of our model