The Effectiveness of English Writing Teaching in Junior Middle School Based on Production-Oriented Approach

Production-oriented Approach (POA) proposed by Chinese scholar Wen Qiufang has been widely used in English teaching in recent years, but there are few studies on its application in junior middle school English teaching. This study analyzed the impact of the application of Production-oriented Approach on junior middle school students’ English learning attitude and English writing performance. In the experimental design, both quantitative and qualitative methods were adopted. Writing tests, questionnaire, interview were used as instruments. A total of 116 Chinese students from Year 8 of Yangzhou Shiyan Junior Middle School, Jiangsu Province in China were invited to participate in an 8-week pre- and post-test experiment. By comparing the writing scores before and after the test, it is found that the English writing scores of the students in the experimental class are higher than those of the students in the control class. Through the analysis of the results of questionnaires and interview, it is found that the students’ attitude towards English writing teaching in the experimental class has improved significantly. The implications and suggestions for dissemination and implementation of POA for junior middle school students are discussed

On the equivalence between Value-at-Risk and Expected Shortfall in non-concave optimization

This paper studies an optimal asset allocation problem for a surplus-driven financial institution facing a Value-at-Risk (VaR) or an Expected Shortfall (ES) constraint corresponding to a non-concave optimization problem under constraints. We obtain the closed-form optimal wealth with the ES constraint as well as with the VaR constraint respectively, and explicitly calculate the optimal trading strategy for constant relative risk aversion (CRRA) utility functions. We find that both VaR and ES-based regulation can effectively reduce the probability of default for a surplus-driven financial institution. However, the liability holders' benefits cannot be fully protected under either VaR- or ES-based regulation. In addition, we show that the VaR and ES-based regulation can induce the same optimal portfolio choice for a surplus-driven financial institution. This differs from the conclusion drawn in Basak and Shapiro 2001 where the financial institution aims at maximizing the expected utility of the total assets, and ES provides better loss protection

Carbon Trading in BRICS Countries: Challenges and Recommendations

As one of the world’s largest emerging economies, BRICS countries are playing an increasingly important role in addressing the global issue of climate change. To achieve their emissions reduction targets, these nations are actively promoting the construction of carbon trading markets. However, they face multiple challenges and obstacles in this endeavor, including issues related to market norms, financial support, technical capacity, social participation, and development needs. This research investigates the problems and challenges faced by BRICS countries in terms of building carbon trading markets through literature reviews and case studies. To address these challenges, this research strengthening international cooperation and technical support, improving market norms and provide following recommendations: conducting regulatory measures, enhancing social participation and communication, and balancing the relationship between economic development and environmental protection requirements. Furthermore, it is crucial for these nations to continue to strengthen international cooperation and collaboration, working together to promote the construction of carbon trading markets, achieving their emissions reduction targets, and ensuring long-term sustainability and economic development

Personalized PageRank on Evolving Graphs with an Incremental Index-Update Scheme

{\em Personalized PageRank (PPR)} stands as a fundamental proximity measure in graph mining. Since computing an exact SSPPR query answer is prohibitive, most existing solutions turn to approximate queries with guarantees. The state-of-the-art solutions for approximate SSPPR queries are index-based and mainly focus on static graphs, while real-world graphs are usually dynamically changing. However, existing index-update schemes can not achieve a sub-linear update time. Motivated by this, we present an efficient indexing scheme to maintain indexed random walks in expected $O(1)$ time after each graph update. To reduce the space consumption, we further propose a new sampling scheme to remove the auxiliary data structure for vertices while still supporting $O(1)$ index update cost on evolving graphs. Extensive experiments show that our update scheme achieves orders of magnitude speed-up on update performance over existing index-based dynamic schemes without sacrificing the query efficiency

Far-Infrared Spectroscopy of Cationic Polycyclic Aromatic Hydrocarbons: Zero Kinetic Energy Photoelectron Spectroscopy of Pentacene Vaporized from Laser Desorption

doi:10.1088/0004-637X/715/1/485The distinctive set of infrared (IR) emission bands at 3.3, 6.2, 7.7, 8.6, and 11.3 μm are ubiquitously seen in a wide variety of astrophysical environments. They are generally attributed to polycyclic aromatic hydrocarbon (PAH) molecules. However, not a single PAH species has yet been identified in space, as the mid-IR vibrational bands are mostly representative of functional groups and thus do not allow one to fingerprint individual PAH molecules. In contrast, the far-IR (FIR) bands are sensitive to the skeletal characteristics of a molecule, hence they are important for chemical identification of unknown species. With an aim to offer laboratory astrophysical data for the Herschel Space Observatory, Stratospheric Observatory for Infrared Astronomy, and similar future space missions, in this work we report neutral and cation FIR spectroscopy of pentacene (C22H14), a five-ring PAH molecule. We report three IR active modes of cationic pentacene at 53.3, 84.8, and 266 μm that may be detectable by space missions such as the SAFARI instrument on board SPICA. In the experiment, pentacene is vaporized from a laser desorption source and cooled by a supersonic argon beam. We have obtained results from two-color resonantly enhanced multiphoton ionization and two-color zero kinetic energy photoelectron (ZEKE) spectroscopy. Several skeletal vibrational modes of the first electronically excited state of the neutral species and those of the cation are assigned, with the aid of ab initio and density functional calculations. Although ZEKE is governed by the Franck-Condon principle different from direct IR absorption or emission, vibronic coupling in the long ribbon-like molecule results in the observation of a few IR active modes. Within the experimental resolution of ~7 cm-1, the frequency values from our calculation agree with the experiment for the cation, but differ for the electronically excited intermediate state. Consequently, modeling of the intensity distribution is difficult and may require explicit inclusion of vibronic interactions.This work is supported by the National Aeronautics and Space Administration under award No. NNX09AC03G. A.L. is supported in part by the NSF grant AST 07-07866, a Spitzer Theory grant and a Herschel Theory grant

LightFR: Lightweight Federated Recommendation with Privacy-preserving Matrix Factorization

Federated recommender system (FRS), which enables many local devices to train a shared model jointly without transmitting local raw data, has become a prevalent recommendation paradigm with privacy-preserving advantages. However, previous work on FRS performs similarity search via inner product in continuous embedding space, which causes an efficiency bottleneck when the scale of items is extremely large. We argue that such a scheme in federated settings ignores the limited capacities in resource-constrained user devices (i.e., storage space, computational overhead, and communication bandwidth), and makes it harder to be deployed in large-scale recommender systems. Besides, it has been shown that transmitting local gradients in real-valued form between server and clients may leak users' private information. To this end, we propose a lightweight federated recommendation framework with privacy-preserving matrix factorization, LightFR, that is able to generate high-quality binary codes by exploiting learning to hash technique under federated settings, and thus enjoys both fast online inference and economic memory consumption. Moreover, we devise an efficient federated discrete optimization algorithm to collaboratively train model parameters between the server and clients, which can effectively prevent real-valued gradient attacks from malicious parties. Through extensive experiments on four real-world datasets, we show that our LightFR model outperforms several state-of-the-art FRS methods in terms of recommendation accuracy, inference efficiency and data privacy.Comment: Accepted by ACM Transactions on Information Systems (TOIS