Constrained structure of ancient Chinese poetry facilitates speech content grouping

Ancient Chinese poetry is constituted by structured language that deviates from ordinary language usage [1, 2]; its poetic genres impose unique combinatory constraints on linguistic elements [3]. How does the constrained poetic structure facilitate speech segmentation when common linguistic [4, 5, 6, 7, 8] and statistical cues [5, 9] are unreliable to listeners in poems? We generated artificial Jueju, which arguably has the most constrained structure in ancient Chinese poetry, and presented each poem twice as an isochronous sequence of syllables to native Mandarin speakers while conducting magnetoencephalography (MEG) recording. We found that listeners deployed their prior knowledge of Jueju to build the line structure and to establish the conceptual flow of Jueju. Unprecedentedly, we found a phase precession phenomenon indicating predictive processes of speech segmentation—the neural phase advanced faster after listeners acquired knowledge of incoming speech. The statistical co-occurrence of monosyllabic words in Jueju negatively correlated with speech segmentation, which provides an alternative perspective on how statistical cues facilitate speech segmentation. Our findings suggest that constrained poetic structures serve as a temporal map for listeners to group speech contents and to predict incoming speech signals. Listeners can parse speech streams by using not only grammatical and statistical cues but also their prior knowledge of the form of language

Deep Learning for Single Image Super-Resolution: A Brief Review

Single image super-resolution (SISR) is a notoriously challenging ill-posed problem, which aims to obtain a high-resolution (HR) output from one of its low-resolution (LR) versions. To solve the SISR problem, recently powerful deep learning algorithms have been employed and achieved the state-of-the-art performance. In this survey, we review representative deep learning-based SISR methods, and group them into two categories according to their major contributions to two essential aspects of SISR: the exploration of efficient neural network architectures for SISR, and the development of effective optimization objectives for deep SISR learning. For each category, a baseline is firstly established and several critical limitations of the baseline are summarized. Then representative works on overcoming these limitations are presented based on their original contents as well as our critical understandings and analyses, and relevant comparisons are conducted from a variety of perspectives. Finally we conclude this review with some vital current challenges and future trends in SISR leveraging deep learning algorithms.Comment: Accepted by IEEE Transactions on Multimedia (TMM

The developments of anaerobic baffled reactor for wastewater treatment: A review

With the increasing deterioration of world water resources, configuring a technical and economic viable wastewater treatment and recycle technology to satisfying the increasing complexity of wastewater and stringent environmental regulation has been a great challenge over the past decades. Developing reliable technologies for wastewater treatment is of urgent importance. In recent years, anaerobic baffled reactor (ABR) treating wastewaters effectively, have received considerable attention in the literature. This paper reviews the development and application, performance and characteristics, modeling of the ABR for wastewater treatment and the combination of ABR with other processes during the last decade. This paper provides a critical review on the ABR for treatment of refractory wastewaters. It was indicated that ABR had become a promising alternative for wastewaters treatment with great further development potential

Cultivating Interdisciplinary Foreign Language Talents in Higher Education in Western China under the Background of the “B&R”

There is an increasing demand for interdisciplinary foreign language talents who master multiple foreign languages and cultures, innovation ability, and management ability, especially under the “Belt and Road” background. However, cultivating interdisciplinary foreign language talents in western China is facing many dilemmas. In order to meet the interdisciplinary foreign language talents demand of the international economic development along the “Belt and Road”, the author puts forward some strategies based on symbiosis theory adopting a comparative method. This article aims to explore methods of cultivating interdisciplinary foreign language talents in higher education in western China and supply high-quality interdisciplinary foreign language talents for the “Belt and Road”