A Hermeneutic Phenomenological Investigation Of Teachers’ Perspectives Towards Integrating Culture Into Chinese-As-Aforeign-Language (Cfl) Curricula And Instruction In American High Schools

The importance of integrating culture into foreign language teaching and learning has been acknowledged in the U.S. by the National Standards in Foreign Language Education Project and foreign language professionals. However, it remains challenging for Chinese-as-a-Foreign-Language (CFL) teachers to embrace this concept thoroughly and implement it effectively in their CFL classes. The study explores six CFL teachers’ perceptions and experiences towards culture and language integration into their CFL curricula and instruction in American high schools. This study aims to describe the overall landscape of culture-language integration in the CFL discipline in American high schools by revealing the essential knowledge of CFL curriculum and pedagogy; the difficulties in developing a culture-language integrated curriculum; the processes CFL teachers use to respond to the difficulties; and the experiences, relationships, structures, and/or resources shaping CFL teachers’ practices of integrating culture into CFL curriculum and instruction. The researcher adopted the hermeneutic phenomenological approach to probe the research questions and utilized questionnaires and in-depth interviews to collect data. The data analysis revealed a gap between recognizing the significance of integrating culture in CFL courses and implementing this integration in the CFL curricula and instruction among the participants. The participants appealed for support in academic knowledge of cultural teaching, and for social and cultural capital to fulfill culture-language integration in the CFL classes in American high schools. The findings underscore pedagogies and techniques the participants used to integrate culture into CFL curriculum and course instruction, including cultural comparison, contextualization, and project-based methods. Compared with the academic factors which impact the Chinese teachers’ integration of culture into the CFL curricula and instruction, the research found that structural and cultural factors played a much more fundamental role in determining Chinese teachers’ choices and dedication to integrating culture into the CFL class in America. These findings might shed light on comprehending what contextual influences were narrated by CFL teachers as influencing their choices and implementation of culture-language integration in CFL classes in American schools. Study findings provide useful information to educators in the area of CFL instruction in particular and, more generally, the teaching of world languages

Personalized Dialogue Generation with Diversified Traits

Endowing a dialogue system with particular personality traits is essential to deliver more human-like conversations. However, due to the challenge of embodying personality via language expression and the lack of large-scale persona-labeled dialogue data, this research problem is still far from well-studied. In this paper, we investigate the problem of incorporating explicit personality traits in dialogue generation to deliver personalized dialogues. To this end, firstly, we construct PersonalDialog, a large-scale multi-turn dialogue dataset containing various traits from a large number of speakers. The dataset consists of 20.83M sessions and 56.25M utterances from 8.47M speakers. Each utterance is associated with a speaker who is marked with traits like Age, Gender, Location, Interest Tags, etc. Several anonymization schemes are designed to protect the privacy of each speaker. This large-scale dataset will facilitate not only the study of personalized dialogue generation, but also other researches on sociolinguistics or social science. Secondly, to study how personality traits can be captured and addressed in dialogue generation, we propose persona-aware dialogue generation models within the sequence to sequence learning framework. Explicit personality traits (structured by key-value pairs) are embedded using a trait fusion module. During the decoding process, two techniques, namely persona-aware attention and persona-aware bias, are devised to capture and address trait-related information. Experiments demonstrate that our model is able to address proper traits in different contexts. Case studies also show interesting results for this challenging research problem.Comment: Please contact [zhengyinhe1 at 163 dot com] for the PersonalDialog datase

A multicomponent assembly approach for the design of deep desulfurization heterogeneous catalysts

Deep desulfurization is a challenging task and global efforts are focused on the development of new approaches for the reduction of sulfur-containing compounds in fuel oils. In this work, we have proposed a new design strategy for the development of deep desulfurization heterogeneous catalysts. Based on the adopted design strategy, a novel composite material of polyoxometalate (POM)-based ionic liquid-grafted layered double hydroxides (LDHs) was synthesized by an exfoliation/grafting/assembly process. The structural properties of the as-prepared catalyst were characterized using FT-IR, XRD, TG, NMR, XPS, BET, SEM and HRTEM. The heterogeneous catalyst exhibited high activity in deep desulfurization of DBT (dibenzothiophene), 4,6-DMDBT (4,6-dimethyldibenzothiophene) and BT (benzothiophene) at 70 °C in 25, 30 and 40 minutes, respectively. The catalyst can be easily recovered and reused at least ten times without obvious decrease of its catalytic activity. Such excellent sulfur removal ability as well as the cost efficiency of the novel heterogeneous catalyst can be attributed to the rational design, where the spatial proximity of the substrate and the active sites, the immobilization of ionic liquid onto the LDHs via covalent bonding and the recyclability of the catalyst are carefully considered

Environmental Information Disclosure of Listed Company Study on the Cost of Debt Capital Empirical Data: Based on Thermal Power Industry

Environmental pollution incidents in recent years, at the cost of sacrificing the environment’s mode of economic development are facing a deep review. This 2008 year to 2012 year in Shanghai and Shenzhen-listed power companies for the study, from the point of view of debt financing effect of environmental information disclosure on corporate debt, the cost of capital. Study: Environmental information disclosure levels significantly impact corporate debt financing costs, full environmental disclosure of listed companies of their lower unit cost of debt capital; overall low level of environmental disclosure in the thermal power industry, but increasing trend. Theoretical study and institution-building, as well as enterprise autonomy make relevant recommendations.

Indexing Metric Spaces for Exact Similarity Search

With the continued digitalization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the data are often viewed as the main sources of challenges when attempting to enable value creation from big data: volume, velocity and variety. Many studies address volume or velocity, while much fewer studies concern the variety. Metric space is ideal for addressing variety because it can accommodate any type of data as long as its associated distance notion satisfies the triangle inequality. To accelerate search in metric space, a collection of indexing techniques for metric data have been proposed. However, existing surveys each offers only a narrow coverage, and no comprehensive empirical study of those techniques exists. We offer a survey of all the existing metric indexes that can support exact similarity search, by i) summarizing all the existing partitioning, pruning and validation techniques used for metric indexes, ii) providing the time and storage complexity analysis on the index construction, and iii) report on a comprehensive empirical comparison of their similarity query processing performance. Here, empirical comparisons are used to evaluate the index performance during search as it is hard to see the complexity analysis differences on the similarity query processing and the query performance depends on the pruning and validation abilities related to the data distribution. This article aims at revealing different strengths and weaknesses of different indexing techniques in order to offer guidance on selecting an appropriate indexing technique for a given setting, and directing the future research for metric indexes