Effective Techniques for Teaching Phrasal Verbs to Improve the Communicative Competence of Chinese English Learners

This project provides a teaching guidebook for both English as a Second Language (ESL) students and teachers. Most learners do not know how to use phrasal verbs in their daily conversation even if they have already learned them. Moreover, it is hard for students to remember phrasal verbs they learned if they don’t practice them in meaningful contexts. This project will address the problem of the ineffective instruction of English in China and the exclusion of two-word verbs from the Chinese curriculum. Due to the differences in linguistic and education backgrounds, ESL teachers and students desire a guidebook that is appropriate for them; ESL teachers should be provided with professional teaching methods and materials in delivering lectures too. In order to help ESL students better their skills of using phrasal verbs, systematic learning topics are applied within the book. ESL teachers can benefit from this book by learning various teaching strategies. This guidebook should be used in an ESL university/ community college ESL classroom to enhance student academic performance

Effective Techniques for Teaching Phrasal Verbs to Improve Communicate Competence of Chinese English learners

Effective Techniques for Teaching Phrasal Verbs to Improve Communicate Competence of Chinese English learner

The Effectiveness of Using Multimedia for Teaching Phrasal Verbs in Community-College ESL Classes

This mixed-methods study investigated the effectiveness of multimedia instruction for phrasal-verb education with community-college English as a second-language learners (ESL) in Northern California. Previous researchers have found that ESL learners have difficulties and barriers in learning phrasal verbs, and other researchers have found that how using multimedia teaching techniques in different fields of education have been effective, but no studies have investigated using multimedia instruction with community-college ESL students in learning phrasal verbs for second-language acquisition. In this mixed-methods research, there were 35 community-college ESL students, including 22 students in the multimedia-treatment group and 13 students in the text-based-comparison group, who participated in this study. The multimedia-treatment group was instructed through the phrasal-verb multimedia lessons for 12 sessions with 48 new phrasal verbs. The text-based-comparison group was instructed through the phrasal-verb text-based lessons for 12 sessions with the same 48 new phrasal verbs. Two-way analysis of variance was used to analyze the pretest, posttest, test-score difference, questionnaire, and engagement data. All participants’ learning interest, usefulness, and success were measured through the MUSIC model questionnaire and individual interviews. The quantitative findings revealed a statistically significant difference in terms of prior knowledge and learning engagement between the comparison and treatment groups. Qualitative findings revealed that students in the multimedia-treatment group had positive opinions about the phrasal-verb multimedia lessons. Most participants enjoyed the phrasal-verb multimedia lessons and expressed interests in using multimedia techniques for furthering their English learning. Thus, the qualitative and quantitative findings suggested a new conceptual framework in second-language acquisition. Based on the evidence of this dissertation’s research, the text-based techniques had positive effects on the community-college ESL students’ phrasal-verb learning. This study has implications for the fields of distance learning and English phrasal-verb instruction. Additional research on using multimedia instruction, such as using comics, pictures, music, animation, and movies, for different age ranges and different ESL group levels, and for online-synchronized and asynchronized class settings would further expand the current findings of the effects on phrasal-verb multimedia instruction

Study of alfalfa somatic embryos for recombinant protein production

Transgenic plants have been explored as a potentially inexpensive expression system for recombinant protein production. However, improvement in protein yield is still the most challenging problem limiting the commercial utilization of plant expression systems. In this study, alfalfa (Medicago sativa L.) somatic embryo was evaluated as a tissue for increased recombinant protein expression. Three heterologous genes: fi- glucuronidase (GUS), cholera toxin B subunit (CTB), and human interleukin 13 (hIL-13) were independently introduced into alfalfa via Agrobacterium-mediated transformation. Induced alfalfa somatic embryos store approximately two-fold more ectopically expressed proteins (as a percentage of total soluble protein) than vegetative organs such as roots, stems, and leaves. The foreign proteins CTB and hIL-13 could accumulate up to 0.15% and 0.18% of total soluble protein in alfalfa somatic embryos, respectively. These .... • ..... ... results indicate that alfalfa somatic embryos can serve as an efficient expression system to accumulate heterologous proteins

A 12-Lead ECG Database to Identify Origins of Idiopathic Ventricular Arrhythmia Containing 334 Patients

Cardiac catheter ablation has shown the effectiveness of treating the idiopathic premature ventricular complex and ventricular tachycardia. As the most important prerequisite for successful therapy, criteria based on analysis of 12-lead ECGs are employed to reliably speculate the locations of idiopathic ventricular arrhythmia before a subsequent catheter ablation procedure. Among these possible locations, right ventricular outflow tract and left outflow tract are the major ones. We created a new 12-lead ECG database under the auspices of Chapman University and Ningbo First Hospital of Zhejiang University that aims to provide high quality data enabling detection of the distinctions between idiopathic ventricular arrhythmia from right ventricular outflow tract to left ventricular outflow tract. The dataset contains 334 subjects who successfully underwent a catheter ablation procedure that validated the accurate origins of idiopathic ventricular arrhythmia

An Efficient Protocol for the Commit-Prove-Fair-Open functionality

In TCC 2006, Garay et al. introduced the notion of commit-prove-fair-open functionality in order to achieve what they called resource fairness of secure multi-party computation(MPC) with corrupted majority. The protocol realizing this notion of fairness follows the gradual release approach and, further, it can be proven secure in the simulation paradigm and enjoys composition properties. In this paper, we show a more efficient resource-fair protocol of FCPFO based on a new variant of Garay et al. time-lines and simplified Camenisch-Shoup(sCS) commitment,whose communication and computation complexity are less than 1/5 of Garay et al. construction. In addition, our new protocol allows commitment to value 0, which is not possible in the plain Garay et al. construction

An Artificial Intelligence-Based Noninvasive Solution to Estimate Pulmonary Artery Pressure

Aims: Design to develop an artificial intelligence (AI) algorithm to accurately predict the pulmonary artery pressure (PAP) waveform using non-invasive signal inputs. Methods and results: We randomly sampled training, validation, and testing datasets from a waveform database containing 180 patients with pulmonary atrial catheters (PACs) placed for PAP waves collection. The waveform database consisted of six hemodynamic parameters from bedside monitoring machines, including PAP, artery blood pressure (ABP), central venous pressure (CVP), respiration waveform (RESP), photoplethysmogram (PPG), and electrocardiogram (ECG). We trained a Residual Convolutional Network using a training dataset containing 144 (80%) patients, tuned learning parameters using a validation set including 18 (10%) patients, and tested the performance of the method using 18 (10%) patients, respectively. After comparing all multi-stage algorithms on the testing cohort, the combination of the residual neural network model and wavelet scattering transform data preprocessing method attained the highest coefficient of determination R2 of 90.78% as well as the following other performance metrics and corresponding 95% confidence intervals (CIs): mean square error of 11.55 (10.22–13.5), mean absolute error of 2.42 (2.06–2.85), mean absolute percentage error of 0.91 (0.76–1.13), and explained variance score of 90.87 (85.32–93.31). Conclusion: The proposed analytical approach that combines data preprocessing, sampling method, and AI algorithm can precisely predict PAP waveform using three input signals obtained by noninvasive approaches

A High Precision Machine Learning-Enabled System for Predicting Idiopathic Ventricular Arrhythmia Origins

Background: Radiofrequency catheter ablation (CA) is an efficient antiarrhythmic treatment with a class I indication for idiopathic ventricular arrhythmia (IVA), only when drugs are ineffective or have unacceptable side effects. The accurate prediction of the origins of IVA can significantly increase the operation success rate, reduce operation duration and decrease the risk of complications. The present work proposes an artificial intelligence-enabled ECG analysis algorithm to estimate possible origins of idiopathic ventricular arrhythmia at a clinical-grade level accuracy. Method: A total of 18,612 ECG recordings extracted from 545 patients who underwent successful CA to treat IVA were proportionally sampled into training, validation and testing cohorts. We designed four classification schemes responding to different hierarchical levels of the possible IVA origins. For every classification scheme, we compared 98 distinct machine learning models with optimized hyperparameter values obtained through extensive grid search and reported an optimal algorithm with the highest accuracy scores attained on the testing cohorts. Results: For classification scheme 4, our pioneering study designs and implements a machine learning-based ECG algorithm to predict 21 possible sites of IVA origin with an accuracy of 98.24% on a testing cohort. The accuracy and F1-score for the left three schemes surpassed 99%. Conclusion: In this work, we developed an algorithm that precisely predicts the correct origins of IVA (out of 21 possible sites) and outperforms the accuracy of all prior studies and human experts

Emission of PAHs, NPAHs and OPAHs from residential honeycomb coal briquette combustion

Coal combustion is one of the most significant sources of air pollution in China. In this study, emission factors (EFs) of 15 polycyclic aromatic hydrocarbons (PAHs), 26 nitrated PAHs (NPAHs) and 6 oxygenated PAHs (OPAHs) were determined in five different coals with different geological maturity (vitrinite reflectance <i>R</i>_O = 0.77–1.88%) burned in the form of honeycomb briquettes. The total EFs ranged from 9.82 to 215 mg kg^–1 for PAHs, 0.14 to 1.88 mg kg^–1 for NPAHs and 4.47 to 20.8 mg kg^–1 for OPAHs. Measured EFs and gas-particle partitioning varied depending on the geological maturity. The lowest EFs were found in anthracite. The proportion of PAHs, NPAHs and OPAHs in gaseous phase increasing with increased geological maturity. The coal with higher geological maturity produced more 3-ring PAHs. On the basis of the statistical analysis for the residential sector of China in 2008, PAHs, NPAHs and OPAHs emitted from residential honeycomb coal briquettes were 4.36 Gg, 0.03 Gg and 0.47 Gg in 2007, respectively. By 2020, the emission would decrease to 2.18 Gg, 0.02 Gg and 0.24 Gg for PAHs, NPAHs and OPAHs due to the increasing usage of new energy resources. If only anthracite is used as the residential coal, 93% PAHs, 87% NPAHs and 71% OPAHs would be reduced in 2020