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

A study of the problems associated with Dalangdian reservoir, China

There are over 2,300 lakes over 1 km2 in China (total area 80 000 km2). In addition there are approximately 87 000 reservoirs with a storage capacity of 413 billion m3. These form the main supply of drinking water as well as water for industrial and agricultural production and aquaculture. Because of a lack of understanding of the frailty of lake ecosystems and poor environmental awareness, human activities have greatly affected freshwater systems. This article focuses on the problems of one water supply reservoir, Dalangdian Reservoir, and considers options for improving its management. Dalangdian Reservoir is described and occurrence of algal genera given. The authors conclude with remarks on the future of the Dalangdian Reservoir

Boundness of Some Multilinear Fractional Integral Operators in Generalized Morrey Spaces on Stratified Lie Groups

In this paper, the main aim is to consider the Spanne-type boundedness of the multiliinear fractional integral operator $\mathcal{I}_{\alpha,m}$ and multiliinear fractional maximal operator $\mathcal{M}_{\alpha,m}$ in the generalized Morrey spaces over some stratified Lie group $\mathbb{G}$.Comment: arXiv admin note: substantial text overlap with arXiv:2206.0834

Critical Current Density and Resistivity of MgB2 Films

The high resistivity of many bulk and film samples of MgB2 is most readily explained by the suggestion that only a fraction of the cross-sectional area of the samples is effectively carrying current. Hence the supercurrent (Jc) in such samples will be limited by the same area factor, arising for example from porosity or from insulating oxides present at the grain boundaries. We suggest that a correlation should exist, Jc ~ 1/{Rho(300K) - Rho(50K)}, where Rho(300K) - Rho(50K) is the change in the apparent resistivity from 300 K to 50 K. We report measurements of Rho(T) and Jc for a number of films made by hybrid physical-chemical vapor deposition which demonstrate this correlation, although the "reduced effective area" argument alone is not sufficient. We suggest that this argument can also apply to many polycrystalline bulk and wire samples of MgB2.Comment: 11 pages, 3 figure

Numerical Study on Indoor Wideband Channel Characteristics with Different Internal Wall

Effects of material and configuration of the internal wall on the performance of wideband channel are investigated by using the Finite Difference Time-Domain (FDTD) method. The indoor wideband channel characteristics, such as the path-loss, Root-Mean-Square (RMS) delay spread and number of the multipath components (MPCs), are presented. The simulated results demonstrate that the path-loss and MPCs are affected by the permittivity, dielectric loss tangent and thickness of the internal wall, while the RMS delay spread is almost not relevant with the dielectric permittivity. Furthermore, the comparison of simulated result with the measured one in a simple scenario has validated the simulation study

A Palette of Deepened Emotions: Exploring Emotional Challenge in Virtual Reality Games

Recent work introduced the notion of ‘emotional challenge’promising for understanding more unique and diverse player experiences (PX). Although emotional challenge has immediately attracted HCI researchers’ attention, the concept has not been experimentally explored, especially in virtual reality (VR), one of the latest gaming environments. We conducted two experiments to investigate how emotional challenge affects PX when separately from or jointly with conventional challenge in VR and PC conditions. We found that relatively exclusive emotional challenge induced a wider range of different emotions in both conditions, while the adding of emotional challenge broadened emotional responses only in VR. In both experiments, VR significantly enhanced the measured PX of emotional responses, appreciation, immersion and presence. Our findings indicate that VR may be an ideal medium to present emotional challenge and also extend the understanding of emotional (and conventional) challenge in video games

Radiation and Potential Barriers of a 5D Black String Solution

By using a massless scalar field we examine the effect of an extra dimension on black hole radiation. Because the equations are coupled, we find that the structure of the fifth dimension (as for membrane and induced-matter theory) affects the nature of the radiation observed in four-dimensional spacetime. In the case of the Schwarzschild-de Sitter solution embedded in a Randall-Sundrum brane model, the extension of the black hole along the fifth dimension looks like a black string. Then it is shown that, on the brane, the potential barrier surrounding the black hole has a quantized as well as a continuous spectrum. In principle, Hawking radiation may thus provide a probe for higher dimensions.Comment: 9 pages, 3 figures, accepted for publication on MPL

Fast Determination of Lycopene Content and Soluble Solid Content of Cherry Tomatoes Using Metal Oxide Sensors Based Electronic Nose

Lycopene content (LC) and soluble solid content (SSC) are important quality indicators for cherry tomatoes. This study attempted simultaneous analysis of inner quality of cherry tomato by Electronic nose (E-nose) using multivariate analysis. E-nose was used for data acquisition, the response signals were regressed by multiple linear regression (MLR) and partial least square regression (PLS) to build predictive models. The performances of the predictive models were tested according to root mean square and correlation coefficient (R2) in the training set and prediction set. The results showed that MLR models were superior to PLS model, with higher value of R2 and lower values of for RMSE firmness, pH, SSC, and LC. Together with MLR, E-nose could be used to obtain firmness, pH, soluble solid and lycopene contents in cherry tomatoes

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