An Empirical Study of Affective Instruction in Comprehensive English Class for English Majors in China

The research aims at exploring that application of affective instruction in English as a foreign language class in China is conducive to students’ cognitive development and target language acquisition. The study involves both quantitative approach depending on the statistical data and qualitative approach to analyze the investigation results. The subjects are 64 sophomores of English majors from School of Foreign Languages at a university in southwestern China. The instruments of the investigation are questionnaires and tests for English majors. The results of the experiments (Research subjects were required to finish questionnaires and testing papers in Sep. 2006 and Jan. 2007 respectively.) indicated that in the pretest the students from two classes are approximately well-matched concerning affective factors and English proficiency, while in the posttest there are changes of students’ affective state between the students from the experimental class and the control class (t=3.405, P<0.001) and some differences of the two classes in English proficiency (t=3.239, P<0.01). Based on these research results, the conclusion is drawn that affective instruction contributes to cultivating students’ positive affect, and positive affect in turn helps students enhance their target language acquisition

External Field Effect on Electronic and Vibrational Properties of Carotenoids

Resonance Raman spectroscopy is one of the most popular molecular spectroscopy methods. Using this technique, carbon-carbon (CC) vibration can be well investigated and give much information on π-conjugated system. The CC vibration has a strong dependence on the π-electron band gap, which is able to be characterized by absorption spectroscopy. Electron-phonon coupling will strongly influence the Raman intensity and shows sensitivity to the surrounding environment. Through electron-phonon coupling, CC vibration can be modulated by the π-electron band gap. In this review, we present our absorption and Raman-scattering observations of all-trans-beta-carotene from different environment such as temperature, pressure, solvents, and phase transition. The relationship between π-electron band gap and CC vibration is studied. With the decreasing of the π-electron energy, the modulation on CC vibration and electron-phonon coupling is enhanced leading to spectral red-shift. This review has significant importance in understanding the resonance Raman scattering, structural properties of polyenes, and the physics behind it. The results are also valuable for the development of fine-quality photoelectric device

Studies on Metadiscourse since the 3rd Millennium

Metadiscourse refer to linguistic resources that are used to refer to the act and the context of writing about some subject matter. Study of metadiscourse provides a gateway for understanding interactional features of texts or speech, looking beyond the ideational dimension of texts at how writers characterize the world and function interpersonally. The ability of writers to use metadiscourse effectively, to control the level of personality in their texts by offering a credible representation of themselves and their ideas, is seen as a defining feature of successful writing (Hyland, 2008). This paper provides a literature review of the theories in modelling metadiscourse and the studies investigating metadiscourse for the past 15 years, and propose future research directions based on the review. Keywords: Metadiscourse, interactional features, literature revie

How Message Frames Promote People’s Willingness to Get Vaccinated? The Mediation Role of Perceived Net Benefits

Objectives: This study aims to evaluate the association among framed messages (egoism-, altruism-, and loss-framed information), perceived net benefits (PNB), and willingness to receive a COVID-19 vaccine.Methods: A between-subject survey experiment was designed to assess the above association. A total of 1,316 individuals were included in this study. The participants were randomly assigned to one control group (receiving non-framed information) and three experimental groups (receiving egoism-, altruism-, and loss-framed information). The participants then reported their vaccination willingness and perceived effectiveness and side effects of vaccination. PNB was determined by subtracting the perceived side effects from perceived effectiveness.Results: Compared with the control group, participants in the experimental groups exhibited stronger vaccination willingness. Higher PNB levels were associated with enhanced vaccination willingness. However, only loss-framed messages indirectly affected vaccination willingness through PNB.Conclusion: PNB can mediate the impact of message framing on vaccination willingness. However, the mediation effect of PNB was only found in the relationship between loss-framed messages and vaccination willingness

Distribution Fitting for Combating Mode Collapse in Generative Adversarial Networks

Mode collapse is a significant unsolved issue of generative adversarial networks. In this work, we examine the causes of mode collapse from a novel perspective. Due to the nonuniform sampling in the training process, some sub-distributions may be missed when sampling data. As a result, even when the generated distribution differs from the real one, the GAN objective can still achieve the minimum. To address the issue, we propose a global distribution fitting (GDF) method with a penalty term to confine the generated data distribution. When the generated distribution differs from the real one, GDF will make the objective harder to reach the minimal value, while the original global minimum is not changed. To deal with the circumstance when the overall real data is unreachable, we also propose a local distribution fitting (LDF) method. Experiments on several benchmarks demonstrate the effectiveness and competitive performance of GDF and LDF

Frequency Coupling Admittance Modeling of Quasi-PR Controlled Inverter and Its Stability Comparative Analysis under the Weak Grid

This paper intends to comparatively study the stabilities of grid-connected inverters with three closely related controllers: quasi-proportional resonance (quasi-PR), proportional integral (PI), and proportional resonance (PR) under the weak grid. Firstly, considering the influence of frequency coupling characteristic, a frequency coupling admittance model of quasi-PR controlled inverter is established. Then, the admittance characteristics of the quasi-PR, PI and PR controlled inverters are compared. Admittance characteristics of the PI and PR controlled inverters are similar while the quasi-PR controlled inverter is quite different: the amplitude of the quasi-PR controlled inverter is larger than that of the PI controlled inverter and the phase difference between the two inverters is obvious in the mid-high frequency areas, which are mainly caused by the resonance bandwidth of the quasi-PR controller. Furthermore, the stabilities of the quasi-PR, PI and PR controlled inverters are analyzed. The stabilities of the PI and PR controlled inverters are similar but the quasi-PR controlled inverter is more sensitive to weak grid and high inverter output power. To achieve the same system stability, the voltage outer-loop bandwidth of the quasi-PR controlled inverter should be designed narrower than that of the PI and PR controlled inverters. Finally, experiments verify the correctness of the analyses

SkipcrossNets: Adaptive Skip-cross Fusion for Road Detection

Multi-modal fusion is increasingly being used for autonomous driving tasks, as images from different modalities provide unique information for feature extraction. However, the existing two-stream networks are only fused at a specific network layer, which requires a lot of manual attempts to set up. As the CNN goes deeper, the two modal features become more and more advanced and abstract, and the fusion occurs at the feature level with a large gap, which can easily hurt the performance. In this study, we propose a novel fusion architecture called skip-cross networks (SkipcrossNets), which combines adaptively LiDAR point clouds and camera images without being bound to a certain fusion epoch. Specifically, skip-cross connects each layer to each layer in a feed-forward manner, and for each layer, the feature maps of all previous layers are used as input and its own feature maps are used as input to all subsequent layers for the other modality, enhancing feature propagation and multi-modal features fusion. This strategy facilitates selection of the most similar feature layers from two data pipelines, providing a complementary effect for sparse point cloud features during fusion processes. The network is also divided into several blocks to reduce the complexity of feature fusion and the number of model parameters. The advantages of skip-cross fusion were demonstrated through application to the KITTI and A2D2 datasets, achieving a MaxF score of 96.85% on KITTI and an F1 score of 84.84% on A2D2. The model parameters required only 2.33 MB of memory at a speed of 68.24 FPS, which could be viable for mobile terminals and embedded devices

Long-term effects of fire and harvest on carbon stocks of boreal forests in northeastern China

International audienceAbstractKey messageFire, harvest, and their spatial interactions are likely to affect boreal forest carbon stocks. Repeated disturbances associated with short fire return intervals and harvest rotations resulted in landscapes with a higher proportion of young stands that store less carbon than mature stands.ContextBoreal forests represent about one third of forest area and one third of forest carbon stocks on the Earth. Carbon stocks of boreal forests are sensitive to climate change, natural disturbances, and human activities.AimsThe objectives of this study were to evaluate the effects of fire, harvest, and their spatial interactions on boreal forest carbon stocks of northeastern China.MethodsWe used a coupled forest landscape model (LANDIS PRO) and a forest ecosystem model (LINKAGES) framework to simulate the landscape-level effects of fire, harvest, and their spatial interactions over 150 years.ResultsOur simulation suggested that aboveground carbon and soil organic carbon are significantly reduced by fire and harvest over the whole simulation period. The long-term effects of fire and harvest on carbon stocks were greater than the short-term effects. The combined effects of fire and harvest on carbon stocks are less than the sum of the separate effects of fire and harvest. The response of carbon stocks was impacted by the spatial variability of fire and harvest regimes.ConclusionThese results emphasize that the spatial interactions of fire and harvest play an important role in regulating boreal forest carbon stocks

Unified Chinese License Plate Detection and Recognition with High Efficiency

Recently, deep learning-based methods have reached an excellent performance on License Plate (LP) detection and recognition tasks. However, it is still challenging to build a robust model for Chinese LPs since there are not enough large and representative datasets. In this work, we propose a new dataset named Chinese Road Plate Dataset (CRPD) that contains multi-objective Chinese LP images as a supplement to the existing public benchmarks. The images are mainly captured with electronic monitoring systems with detailed annotations. To our knowledge, CRPD is the largest public multi-objective Chinese LP dataset with annotations of vertices. With CRPD, a unified detection and recognition network with high efficiency is presented as the baseline. The network is end-to-end trainable with totally real-time inference efficiency (30 fps with 640p). The experiments on several public benchmarks demonstrate that our method has reached competitive performance. The code and dataset will be publicly available at https://github.com/yxgong0/CRPD