Determinants of Postgraduate Students of Fine Arts’ Satisfaction and Performance of e-Learning in Chengdu Region of China

Purpose: The purpose of this study is to investigate the determinants of e-learning satisfaction and performance of fine arts’ postgraduate students in five universities in Chengdu, China. The conceptual framework proposed causal relationships between self-efficacy, perceived usefulness, perceived ease of use, compatibility, task-technology fit, satisfaction, and performance. Research design, data, and methods: The researchers used quantitative methods to distributing questionnaires to 500 respondents via offline and online channels. Judgmental, quota and convenience samplings were employed to collect the data. Before the large-scale data collection, Item Objective Congruence (IOC) Index was applied confirm content validity, and Cronbach’s Alpha reliability test was used to approve all constructs in a pilot test of 30 participants. The data were analyzed by confirmatory factor analysis and structural equation modeling to verify the goodness of fit of the model and to confirm the causal relationships between variables for hypotheses testing. Results: Perceived ease of use significant affected satisfaction and perceived usefulness. The relationship between self-efficacy, perceived ease of use and perceived usefulness was supported. Compatibility and task-technology fit significantly affected student satisfaction. Furthermore, satisfaction is a predictor of performance. Conclusion: This study recommends that office of academic affairs in higher education should improve e-learning system in order to enhance student satisfaction and performance

Investigation on Satisfaction and Performance of Online Education Among Fine Arts Major Undergraduates in Chengdu Public Universities

Purpose: This research investigates factors affecting satisfaction and performance of online education among undergraduate fine art students in three public universities in Chengdu, China. The variables include perceived usefulness, perceived ease of use, self-efficacy, task-technology fit, compatibility, satisfaction and performance. Research design, data, and methods: Through a quantitative research approach, questionnaires were distributed via online and offline channels to 500 target respondents. Judgmental, quota and convenience samplings were used to collect the data. The data previously examined by Item Objective Congruence (IOC) Index to confirm content validity, and by Cronbach’s Alpha coefficient value to approve constructs’ reliability in a pilot test of 30 participants. Statistical analysis involves confirmatory factor analysis (CFA) and structural equation model (SEM), including the test of factor loadings, validity, reliability and goodness of fit model. Results: The results showed that perceived ease of use significant affected satisfaction and perceived usefulness. The relationship between self-efficacy, perceived ease of use and perceived usefulness was supported. Compatibility and task-technology fit significantly affected student satisfaction. Furthermore, satisfaction is a predictor of performance. Conclusion: For online education providers, the system should be designed to be easy, useful, self-control, compatibility and task-fit to gain higher student satisfaction and performance

Concurrent fNIRS and EEG for brain function investigation: A systematic, methodology-focused review

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Localization and distribution of goose astrovirus 2 antigens in different tissues at different times

Abstract Goose astrovirus 2 (GAstV-2) causes visceral gout in goslings and has resulted in significant economic losses in the goose industry of China since its outbreak in 2017. To further investigate the distribution and localization of GAstV-2 in different tissues at different times, a monoclonal antibody (mAb)-based immunohistochemical (IHC) assay was developed to detect GAstV-2. A total of 80 1-day-old healthy goslings were inoculated with GAstV-2 via the oral (n = 40) and intramuscular routes (n = 40). GAstV-2 in the tissues of interest was detected using the established IHC assay. The results showed that positive signals were detected in most tissues at 1 day post-infection (dpi). Viral antigens were mainly distributed in the cytoplasm, and the staining intensity was higher in the renal tubular epithelial cells than in other cells. Taken together, our data demonstrated that GAstV-2 has a broad tissue tropism and primarily targets the kidneys. These results are likely to provide a scientific basis for further elucidation of the pathogenesis of GAstV-2

Compact plasmonic dichroic splitting with high splitting ratio based on a cascaded-grating structure

A compact dichroic surface plasmon polariton (SPP) splitting scheme composed of two cascaded subgratings of different dimensions is proposed and investigated. The normal incident photons illuminated on the dichroic splitting structure are converted to surface plasmons traveling to the left or right depending on the wavelength. The operation principle is clarified and a coupled-mode model is developed to facilitate structure design. The generated SPPs propagating to the left and right directions on the metal surface can be manipulated nearly independently by altering the left and right subgrating, respectively. Proof-of-principle demonstrations show that a remarkable property of high splitting ratios is achieved with 43.0 dB at wavelength 1310 nm (left:right power contrast) and 35.7 dB at wavelength 1550 nm (right:left power contrast). The proposed splitting concept has general applicability across other operating wavelengths, such as the visible and near-infrared range

An extended nonstrict partially ordered set-based configurable linear sorter on FPGAs

Sorting is essential for many scientific and data processing problems. It is significant to improve the efficiency of sorting. Taking advantage of specialized hardware, parallel sorting, e.g., sorting networks and linear sorters, implements sorting in lower time complexity. However, most of them are designed based on the parallelization of algorithms, lacking consideration of specialized hardware structures. In this article, we propose an extended nonstrict partially ordered set-based configurable linear sorter on field-programmable gate arrays (FPGAs). First, we extend nonstrict partial order to the binary tuple and n-tuple nonstrict partial orders. Then, the linear sorting algorithm is defined based on them, with the consideration of hardware performance. It has 4N/n time complexity varying from 4 to 2 N as the tuple size varies. The number of comparisons reduces to N/2 in binary tuple-based sorting, which is half of the state-of-the-art insertion linear sorting. Finally, we implement the linear sorter on FPGAs. It consists of multiple customizable micro-cores, named sorting units (SUs). The SU packages the storage and comparison of the tuple. All the SUs are connected into a chain with simple communication, which makes the sorter fully configurable in length, bandwidth, and throughput. They also act the same in each clock cycle, so that the achieved frequency of the sorter improves. In our experiment, the sorter achieves at most 660-MHz frequency, 5.6 Gb/s throughput, and 87 times speed-up compared with the quick sort algorithm on general processors.NSFC - National Natural Science Foundation of China(20160204022GX). publication February 28, 2020; date of current version April 21, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 61472159, Grant 61572227, and Grant 61772227, and in part by the Development Project of Jilin Province of China under Grant 20160204022GX, Grant 20170101006JC, Grant 20170203002GX, Grant 20180201045GX, Grant 2017C030-1, and Grant 2017C03

Economic Evaluation of CCUS Retrofitting of Coal-fired Power Plants Based on Net Cash Flow

Carbon Capture, Utilization and Storage (CCUS) is one of the key technologies for realizing large-scale low-carbon utilization of coal-fired power plants in service. How to evaluate its economics is crucial to the decision-making of traditional coal-fired power enterprises. This paper analyzes the changes in the physical, emission and economic parameters of in-service coal-fired power plants without and with the CCUS retrofit. A method for evaluating the economic feasibility of coal-fired power plants retrofitting based on net cash flow is proposed, which compares the impact of CCUS retrofit on the net present value of the remaining life cycle of the power plant. The impact of uncertain parameters such as carbon dioxide sales unit price, carbon capture device operating cost, free carbon quota, and carbon emission right price on the evaluation results are analyzed