The role of Chinese vocabulary knowledge in composition writing among upper elementary school students

The present study aims to investigate the role of vocabulary knowledge in composition writing among Chinese children. Drawing on Nation’s (2001) vocabulary framework, this study operationalized Chinese vocabulary knowledge from receptive and productive perspectives and in form, meaning, and use domain, respectively. A total of five measures assessing receptive vocabulary knowledge, productive vocabulary knowledge (form, meaning, and use), and composition writing skills were administered to 249 Chinese students in grade 4 (N = 91), grade 5 (N = 90), and grade 6 (N = 68). Hierarchical regression results showed that across upper elementary grades, productive vocabulary knowledge made a significant and substantial contribution to Chinese writing performance after controlling for age and receptive vocabulary knowledge. Inspections on vocabulary knowledge in each individual domain further revealed that knowledge of vocabulary form was the strongest predictor of writing performance at grade 4, while knowledge of vocabulary meaning and use make increasing contributions to composition writing at higher grades. Findings from this study underline the relative importance of productive vocabulary knowledge in form, meaning, and use at different developmental stages and extend writing models to non-alphabetical languages. Pedagogical implications were also drawn from the present study to inform better educational practices on scaffolding beginning writers with specific aspects of vocabulary knowledge

A century of Chinese research on Islamic Central Asian history in retrospect

The term Central Asia is not precisely defined. In this paper, we will consider it to cover the territory of the present-day Chinese province of Xinjiang, former Soviet Central Asia, the northern parts of Pakistan, Afghanistan and the eastern parts of Iran. We will concentrate on Xinjiang and the areas that border on it. The term Islamic Central Asian History covers the period from the Arab conquest until the end of the 19th century. China has a long tradition of Islamic Central Asian studies..

A century of Chinese research on Islamic Central Asian history in retrospect

The term Central Asia is not precisely defined. In this paper, we will consider it to cover the territory of the present-day Chinese province of Xinjiang, former Soviet Central Asia, the northern parts of Pakistan, Afghanistan and the eastern parts of Iran. We will concentrate on Xinjiang and the areas that border on it. The term Islamic Central Asian History covers the period from the Arab conquest until the end of the 19th century. China has a long tradition of Islamic Central Asian studies..

The Effect of Hospital Vertical Integration on Health Care Quality in China

The rapid growth of hospital integration activities in China has made it critical to understand whether integration in health care markets enhanced or damaged quality. The purpose of this study is to analyze the effect of hospital integration on health care quality in Shanghai. Using difference-in-difference analysis, the authors analyze cure rate and length of stay for gastric ulcer patients. The data indicates that hospital integration has positive impact on cure rate 4 years after integration at the 10% significant, but has no significant impact on length of stay. The authors also discuss the implications of these findings and offer directions for future research

In Vivo Cancer Targeting and Imaging-Guided Surgery with Near Infrared-Emitting Quantum Dot Bioconjugates

Abstract Early detection and subsequent complete surgical resection are among the most efficient methods for treating cancer. However, low detection sensitivity and incomplete tumor resection are two challenging issues. Nanoparticle-based imaging-guided surgery has proven promising for cancer-targeted imaging and subsequent debulking surgery. Particularly, the use of near infrared (NIR) fluorescent probes such as NIR quantum dots (QDs) allows deep penetration and high sensitivity for tumor detection. In this study, NIR-emitting CdTe QDs (maximum fluorescence emission peak at 728 nm) were synthesized with a high quantum yield (QY) of 38%. The tumor-specific QD bioconjugates were obtained by attaching cyclic Arg-Gly-Asp peptide (cRGD) to the surface of synthesized QDs, and then injected into U87 MG tumor-bearing mice via tail veins for tumor-targeted imaging. The tumor and its margins were visualized and distinguished by NIR QD bioconjugates, and tumor resection was successfully accomplished via NIR guidance using a Fluobeam-700 NIR imaging system. Our work indicates that the synthesized tumor-specific NIR QDs hold great promise as a potential fluorescent indicator for intraoperative tumor imaging

Research on Traffic Congestion Based on System Dynamics: The Case of Chongqing, China

With the rapid development of society, urban traffic congestion has gradually become an important social problem that many cities need to solve. For Chongqing, traffic congestion not only affects residents’ normal travel but also brings more serious environmental pollution. Aiming at the problem of urban traffic congestion and automobile exhaust pollution, this paper adopts the system dynamics method to establish a model for studying urban traffic congestion system from the perspectives of private cars, trucks, and public transportation. First, we determine city motor vehicle trips as an indicator of the degree of traffic congestion in this paper. Second, we analyze the causal relationship between the growth of private cars, the travel of trucks, public transportation, population, and other factors and then build a model and test the stability of the model. Then, we add some practical policies to the model for policy analysis. Finally, it is concluded that the private car restriction policy is effective in controlling the amount of private car travel, and the purchase restriction policy controls the growth of the number of private cars from the root cause, but the development of public transportation is the most effective treatment measure in the long run

Case report: A collision tumor of clear cell renal cell carcinoma and clear cell papillary renal cell tumor

We report the case of a 51-year-old woman who was initially hospitalized in the respiratory department with cough and fever. Urinary computed tomography (CT) showed two different incidental masses in the right kidney. The patient underwent a radical right nephrectomy without lymph node dissection and postoperative adjuvant treatment. The pathological examination of the surgical specimens showed a collision tumor composed of a clear cell renal cell carcinoma (CCRCC) and a clear cell papillary renal cell tumor (CCPRCT). To the best of our knowledge, this is the first such case reported to date. No recurrence of local or distant metastasis was found during routine follow-up 14 months after the operation

PairNet: Predicting Correlation Energies with Correlated Features

We proposed a molecular orbital based machine learning model for predicting accurate CCSD(T) correlation energies. The model, named as PairNet, shows excellent transferability on several public data sets using features inspired by pair natural orbitals(PNOs). Though additional computational costs were required to calculate PNOs, the improvement reveals the direct and physical inspired features are essential for a successful deployment of machine learning models in computational chemistry

Deep Reinforcement Learning Based Freshness-Aware Path Planning for UAV-Assisted Edge Computing Networks with Device Mobility

As unmanned aerial vehicles (UAVs) can provide flexible and efficient services concerning the sparse network distribution, we study a UAV-assisted mobile edge computing (MEC) network. To satisfy the freshness requirement of IoT applications, the age of information (AoI) is incorporated as an important performance metric. Then, the path planning problem is formulated to simultaneously minimize the AoIs of mobile devices and the energy consumption of the UAV, where the movement randomness of IoT devices are taken into account. Concerning the dimension explosion, the deep reinforcement learning (DRL) framework is exploited, and a double deep Q-learning network (DDQN) algorithm is proposed to realize the intelligent and freshness-aware path planning of the UAV. Extensive simulation results validate the effectiveness of the proposed freshness-aware path planning scheme and unveil the effects of the moving speed of devices and the UAV on the achieved AoI