A Comparative Analysis of English Education Between Chinese and Japanese Universities

With the strengthening of the trend of global integration, the world needs more and more bilingual talents. English, as the first common language in the world, is undoubtedly important. Both China and Japan are in Asia, so there are many similarities in education that can be borrowed from each other. This article makes a comparative analysis in Chinese and Japanese college English education from the following three perspectives: educator, educatee and educational influence. In this paper, documentation method, comparison analytic method and logic reasoning are used to study Chinese and Japanese college English education which includes faculty, student source, students’ attitude, instructional objectives and educational evaluation. The result makes a reference to the college English education reform in the future. It also helps to improve the English teaching method and the quality of teaching

Wind Tunnel Study on the Aerodynamic Performance of Deflectors with Different Shapes

The continuously increasing gasoline and diesel fuel costs generated immense interest in road vehicle efficiency. Because the aerodynamic drag of road vehicles is a major contributor to the fuel consumption at highway speeds, renewed interests are focusing on attempts to find novel drag-reducing technology. In this project, a newly designed air deflector with the shape of three concave surfaces was proposed. The effect of the deflector shape on the aerodynamic performance of a truck model, such as drag coefficient, was investigated. The results were compared to the same truck model with conventional convex deflector and without deflector. The relationship between the deflector shape and the drag force coefficient, as well as Reynolds number was revealed in all cases. The impact of deflector details on the characteristics of the airflow around the truck model, focusing on the wake area behind the trailer was also investigated

Fund family tournament and performance consequences: evidence from the UK fund industry

By applying tournament analysis to the UK Unit Trusts data, the results support significant risk shifting in the family tournament; i.e. interim winning managers tend to increase their level of risk exposure more than losing managers. It also shows that the risk-adjusted returns of the winners outperform those of the losers following the risk taking, which implies that risk altering can be regarded as an indication of managers’ superior ability. However, the tournament behaviour can still be a costly strategy for investors, since winners can be seen to beat losers in the observed returns due to the deterioration in the performance of their major portfolio holdings

Immobilized biocatalytic process to prepare enantiopure pregabalin intermediate using engineered hydantoinase

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CityFlow: A Multi-Agent Reinforcement Learning Environment for Large Scale City Traffic Scenario

Traffic signal control is an emerging application scenario for reinforcement learning. Besides being as an important problem that affects people's daily life in commuting, traffic signal control poses its unique challenges for reinforcement learning in terms of adapting to dynamic traffic environment and coordinating thousands of agents including vehicles and pedestrians. A key factor in the success of modern reinforcement learning relies on a good simulator to generate a large number of data samples for learning. The most commonly used open-source traffic simulator SUMO is, however, not scalable to large road network and large traffic flow, which hinders the study of reinforcement learning on traffic scenarios. This motivates us to create a new traffic simulator CityFlow with fundamentally optimized data structures and efficient algorithms. CityFlow can support flexible definitions for road network and traffic flow based on synthetic and real-world data. It also provides user-friendly interface for reinforcement learning. Most importantly, CityFlow is more than twenty times faster than SUMO and is capable of supporting city-wide traffic simulation with an interactive render for monitoring. Besides traffic signal control, CityFlow could serve as the base for other transportation studies and can create new possibilities to test machine learning methods in the intelligent transportation domain.Comment: WWW 2019 Demo Pape

A Systematic Review on Different Treatment Methods of Bone Metastasis from Cancers

Background and objective Skeletal metastase is one of the most common complications related to advanced cancer. The aim of this study is to analyze the effectiveness and safety of radiotherapy plus intravenous bisphosphonates versus radiotherapy alone for treating bone metastasis. Methods We searched the Cochrane Library, PubMed, EMBASE, CBM, CNKI and VIP, as well as the reference lists of reports and reviews. The quality of included trials was evaluated by the Cochrane Handbook. Data were extracted and evaluated by two reviewers independently. The Cochrane Collaboration’s Rev-Man 5.0 was used for data analysis. Results Twenty-two trials involving 1 585 patients were included. Compared with radiotherapy alone, radiotherapy plus intravenous bisphosphonates was more effective in total effective rate of pain relive (RR=1.21, 95%CI: 1.13-1.30, P < 0.001), average abated time (WMD=16.00, 95%CI: 10.12-21.88, P < 0.001), and quality of life (RR=1.25, 95%CI: 1.08-1.45, P=0.003, with significant differences. Side effects have no significant differences between the two groups except fever (RR=5.61, 95%CI: 3.11-10.13, P < 0.001). Conclusion Current evidence supports more effective of radiotherapy plus intravenous bisphosphonates for bone metastases. The combine treatment is safe and effective

Surgical treatment of the osteoporotic spine with bone cement-injectable cannulated pedicle screw fixation: technical description and preliminary application in 43 patients

OBJECTIVES: To describe a new approach for the application of polymethylmethacrylate augmentation of bone cement-injectable cannulated pedicle screws. METHODS: Between June 2010 and February 2013, 43 patients with degenerative spinal disease and osteoporosis (T-scor

Particle velocity measurement of binary mixtures in the riser of a circulating fluidized bed by the combined use of electrostatic sensing and high-speed imaging

Zhang WB acknowledges the financial supports from the National Natural Science Foundation of China (No. 61403138) and Beijing Natural Science Foundation (No. 3202028). Zhan W and Wang CH acknowledge the research programme funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme. Grant Number R-706-001-102–281, National University of Singapore.Peer reviewedPublisher PD

Continual Learning for Abdominal Multi-Organ and Tumor Segmentation

The ability to dynamically extend a model to new data and classes is critical for multiple organ and tumor segmentation. However, due to privacy regulations, accessing previous data and annotations can be problematic in the medical domain. This poses a significant barrier to preserving the high segmentation accuracy of the old classes when learning from new classes because of the catastrophic forgetting problem. In this paper, we first empirically demonstrate that simply using high-quality pseudo labels can fairly mitigate this problem in the setting of organ segmentation. Furthermore, we put forward an innovative architecture designed specifically for continuous organ and tumor segmentation, which incurs minimal computational overhead. Our proposed design involves replacing the conventional output layer with a suite of lightweight, class-specific heads, thereby offering the flexibility to accommodate newly emerging classes. These heads enable independent predictions for newly introduced and previously learned classes, effectively minimizing the impact of new classes on old ones during the course of continual learning. We further propose incorporating Contrastive Language-Image Pretraining (CLIP) embeddings into the organ-specific heads. These embeddings encapsulate the semantic information of each class, informed by extensive image-text co-training. The proposed method is evaluated on both in-house and public abdominal CT datasets under organ and tumor segmentation tasks. Empirical results suggest that the proposed design improves the segmentation performance of a baseline neural network on newly-introduced and previously-learned classes along the learning trajectory.Comment: MICCAI-202

Preparation of AuNPs/GQDs/SiO 2

Composites of gold nanoparticles and graphene quantum dots (AuNPs/GQDs) exhibit excellent dispersibility in aqueous solutions. Thus, it is difficult to separate them from wet reaction systems when they are used as catalysts. To resolve this issue, in this study, an AuNPs/GQDs composite was immobilized on silicon dioxide through the hydrothermal method, which involved the formation of an amide bond between the surface GQDs of the AuNPs/GQDs composite and the amino group of the silane. The as-synthesized AuNPs/GQDs/SiO2 composite was found to be suitable for use as a heterogeneous catalyst for the oxidation of veratryl alcohol in water and exhibited catalytic activity comparable to that of bare AuNPs/GQDs as well as better recyclability