In the "Big Data" era, many real-world applications like search involve the ranking problem for a large number of items. It is important to obtain e ective ranking results and at the same time obtain the results e ciently in a timely manner for providing good user experience and saving computational costs. Valuable prior research has been conducted for learning to e ciently rank like the cascade ranking (learning) model, which uses a sequence of ranking functions to progressively lter some items and rank the remaining items. However, most existing research of learning to e ciently rank in search is studied in a relatively small computing environments with simulated user queries.is paper presents novel research and thorough study of designing and deploying a Cascade model in a Large-scale Operational Ecommerce Search application (CLOES), which deals with hundreds of millions of user queries per day with hundreds of servers. e challenge of the real-world application provides new insights for research: 1). Real-world search applications o en involve multiple factors of preferences or constraints with respect to user experience and computational costs such as search accuracy, search latency, size of search results and total CPU cost, while most existing search solutions only address one or two factors; 2). E ectiveness of ecommerce search involves multiple types of user behaviors such as click and purchase, while most existing cascade ranking in search only models the click behavior. Based on these observations, a novel cascade ranking model is designed and deployed in an operational e-commerce search application. An extensive set of experiments demonstrate the advantage of the proposed work to address multiple factors of e ectiveness, e ciency and user experience in the real-world application. KEYWORDScascade ranking; operational e-commerce search system; e ectiveness and e ciency; user experience * Both authors contributed equally to this study Permission to make digital

The factor structure of the MRAI-R in this sample of Chinese college students did not replicate the structure found in American adults. Although the SDIS subscale of the MRAI-R appeared to be a reliable instrument among the four subscales of the MRAI-R, the reliabilities of the INSE, PRRT and SUDB subscales were low. Continuing investigations of the utility of the MRAI-R in Chinese culture is needed. Attitude instruments based on Chinese culture may be developed.

Objectives: The objective of this study was to gain insight into how Chinese special education teachers 1 conceptualize individual education plan (IEP) and how IEP is implemented in their daily work. Method: Fourteen administrators and teachers from several special education schools in three metropolitan cities in China were interviews about their perspective of IEP and IEP practice at their work. Results: The results suggested that despite remaining concerns about the implementation of IEP Chinese teachers highly commit to the value of IEP. It is noted that the IEP process in Chinese schools is quite similar to that of US schools in terms of some major requirements and yet some adaptions are made given the different social-cultural context and that the IEP practice is influenced by a variety of factors such as schools' policy, curriculum, and the paucity of educational resources. Conclusion: There is a need for developing a systematic guideline of IEP considering inconsistency of implementing IEP in schools. Improving teachers' professional competence is critical to the effectiveness of IEP practice in China, and local governments should put in more efforts in ensuring adequate resource being provided to schools and teachers regarding the implementation of IEPs.

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