Exploring the College EFL Self-access Writing Mode Based on Automated Feedback

The present study is intended to construct a college EFL self-access writing mode based on automated feedback under the guidance of Formative Assessment Theory and Autonomous Learning Theory and attempts to apply it into college EFL teaching practice. Findings of this empirical-based study suggest that this self-access writing mode contributes to the enhancement of students’ English writing competence, English writing motivation as well as their autonomy in self-revision

The list-coloring function of signed graphs

It is known that, for any $k$-list assignment $L$ of a graph $G$, the number of $L$-list colorings of $G$ is at least the number of the proper $k$-colorings of $G$ when $k>(m-1)/\ln(1+\sqrt{2})$. In this paper, we extend the Whitney's broken cycle theorem to $L$-colorings of signed graphs, by which we show that if $k> \binom{m}{3}+\binom{m}{4}+m-1$ then, for any $k$-assignment $L$, the number of $L$-colorings of a signed graph $\Sigma$ with $m$ edges is at least the number of the proper $k$-colorings of $\Sigma$. Further, if $L$ is $0$-free (resp., $0$-included) and $k$ is even (resp., odd), then the lower bound $\binom{m}{3}+\binom{m}{4}+m-1$ for $k$ can be improved to $(m-1)/\ln(1+\sqrt{2})$.Comment: 13 page

Clinical value of preferred endoscopic ultrasound-guided antegrade surgery in the treatment of extrahepatic bile duct malignant obstruction

Objectives: To explore the clinical value of preferred ultrasound endoscopic guided biliary drainage in patients with extrahepatic biliary obstruction with intrahepatic biliary ectasis. Methods: A total of 58 patients with malignant obstruction and intrahepatic bile duct expansion, including 32 males, 26 females and median age 65 (58‒81) were selected. A prospective randomized controlled study was randomized into EUS-AG and ERCP-BD, with 28 patients in EUS-AG and 30 in ERCP-BD. The efficacy of the two treatments, operation success rate, operation time, the incidence of complications, hospitalization days, cost, unimpeded stent duration, and survival time were compared. Results: 1) The surgical success rate in group EUS-AG was 100%, and in group, ERCP-BD was 96.67%. There was no statistical difference in surgical success rate in the two groups (p>0.05). 2) Average operating time in EUS-AG was (23.69±11.57) min, and in ERCP-BD was (36.75±17.69) min. The difference between the two groups has statistical significance (p<0.05). 3) The clinical symptoms of successful patients were significantly relieved. Compared with the preoperative procedure, the differences in group levels had statistical significance (p<0.05); TBIL, ALP, WBC and CRP levels, no statistical significance difference in groups (p>0.05). Conclusion: EUS-AG operation has short time, low incidence of complications, safe, effective, and can be used as the preferred treatment plan for patients with extrahepatic biliary duct malignant obstruction associated with intrahepatic biliary duct expansion; EUS-AG operation has more unique clinical advantages for patients with altered gastrointestinal anatomy or upper gastrointestinal obstruction

Task-Based Flipped Classroom in Chinese College EFL Teaching: An Empirical Study in Oral English Course

As a new teaching model, the flipped classroom inverts the sequence of imparting knowledge and internalizing knowledge. On the basis of flipped classroom concept and previous empirical research, the present study is intended to construct task-based college EFL flipped classroom model and put it into Chinese college oral English teaching practice. The design of the study involves contrastive experiments, questionnaires and in-depth interview. The results suggest that the task-based flipped classroom teaching model has a remarkably better effect on boosting students’ communicative competence of English

An asymptotically optimal public parking lot location algorithm based on intuitive reasoning

In order to solve the problems of road traffic congestion and the increasing parking time caused by the imbalance of parking lot supply and demand, this paper proposes an asymptotically optimal public parking lot location algorithm based on intuitive reasoning to optimize the parking lot location problem. Guided by the idea of intuitive reasoning, we use walking distance as indicator to measure the variability among location data and build a combinatorial optimization model aimed at guiding search decisions in the solution space of complex problems to find optimal solutions. First, Selective Attention Mechanism (SAM) is introduced to reduce the search space by adaptively focusing on the important information in the features. Then, Quantum Annealing (QA) algorithm with quantum tunneling effect is used to jump out of the local extremum in the search space with high probability and further approach the global optimal solution. Experiments on the parking lot location dataset in Luohu District, Shenzhen, show that the proposed method has improved the accuracy and running speed of the solution, and the asymptotic optimality of the algorithm and its effectiveness in solving the public parking lot location problem are verified

Recent Advances in Electrocatalytic Nitrogen Reduction to Produce Ammonia Under Ambient Conditions

Ammonia (NH3) is one of the most widely used chemicals in industry and agriculture, which is very important to the global economy. At present, the Haber Bosch process is adopted for ammonia synthesis in industry. The experimental temperature and pressure used in this process are relatively high, the process energy consumption is high, the one-way conversion of the hydrogen is low, and a large amount of carbon dioxide is discharged into the atmosphere, causing pollution to the environment. To solve its shortcomings, researchers began a new exploration. Electrocatalytic nitrogen reduction (NRR), as a clean and sustainable method of ammonia synthesis, has attracted extensive attention. However, the low activity and selectivity of electrocatalysts are one of the important challenges. Therefore, the search for cost-effective electrocatalysts has become one of the research hotspots of electrochemical ammonia synthesis. For enhancing the catalytic performance and selective performance of catalysts, scientists have carried out a lot of research on electrochemical nitrogen fixation catalysts. In this review article, electrolytic experimental devices, common ammonia detection research methods, and the electrocatalytic NRR mechanism are summarized, and then the research progress in electrocatalysts (precious metals, transition metals, and non-precious metals) is summarized. Then, the research progress of metal-based electrocatalysts is introduced, and the relevant theoretical calculations are given. The discussion of different catalytic systems provides ideas for the development and improvement of subsequent NRR electrocatalysts

Research on recognition algorithm for gesture page turning based on wireless sensing

When a human body moves within the coverage range of Wi-Fi signals, the reflected Wi-Fi signals by the various parts of the human body change the propagation path, so analysis of the channel state data can achieve the perception of the human motion. By extracting the Channel State Information (CSI) related to human motion from the Wi-Fi signals and analyzing it with the introduced machine learning classification algorithm, the human motion in the spatial environment can be perceived. On the basis of this theory, this paper proposed an algorithm of human behavior recognition based on CSI wireless sensing to realize deviceless and over-the-air slide turning. This algorithm collects the environmental information containing upward or downward wave in a conference room scene, uses the local outlier factor detection algorithm to segment the actions, and then the time domain features are extracted to train Support Vector Machine (SVM) and eXtreme Gradient Boosting (XGBoost) classification modules. The experimental results show that the average accuracy of the XGBoost module sensing slide flipping can reach 94%, and the SVM module can reach 89%, so the module could be extended to the field of smart classroom and significantly improve speech efficiency

Evidence for an intermediate line region in AGN's inner torus region and its evolution from narrow to broad line Seyfert I galaxies

A two-components model for Broad Line Region (BLR) of Active Galactic Nuclei (AGN) has been suggested for many years but not widely accepted (e.g., Hu et al. 2008; Sulentic et al. 2000; Brotherton et al. 1996; Mason et al. 1996). This model indicates that the broad line can be described with superposition of two Gaussian components (Very Broad Gaussian Component (VBGC) and InterMediate Gaussian Component (IMGC)) which are from two physically distinct regions; i.e., Very Broad Line Region (VBLR) and InterMediate Line Region (IMLR). We select a SDSS sample to further confirm this model and give detailed analysis to the geometry, density and evolution of these two regions. Micro-lensing result of BLR in J1131-1231 and some unexplained phenomena in Reverberation Mapping (RM) experiment provide supportive evidence for this model. Our results indicate that the radius obtained from the emission line RM normally corresponds to the radius of the VBLR, and the existence of the IMGC may affect the measurement of the black hole masses in AGNs. The deviation of NLS1s from the M-sigma relation and the Type II AGN fraction as a function of luminosity can be explained in this model in a coherent way. The evolution of the two emission regions may be related to the evolutionary stages of the broad line regions of AGNs from NLS1s to BLS1s. Based on the results presented here, a unified picture of hierarchical evolution of black hole, dust torus and galaxy is proposed.Comment: 58 pages, 19 figures, 1 table. Matches the published versio

Target dose conversion modeling from pencil beam (PB) to Monte Carlo (MC) for lung SBRT

Background: A challenge preventing routine clinical implementation of Monte Carlo (MC)-based lung SBRT is the difficulty of reinterpreting historical outcome data calculated with inaccurate dose algorithms, because the target dose was found to decrease to varying degrees when recalculated with MC. The large variability was previously found to be affected by factors such as tumour size, location, and lung density, usually through sub-group comparisons. We hereby conducted a pilot study to systematically and quantitatively analyze these patient factors and explore accurate target dose conversion models, so that large-scale historical outcome data can be correlated with more accurate MC dose without recalculation. Methods: Twenty-one patients that underwent SBRT for early-stage lung cancer were replanned with 6MV 360° dynamic conformal arcs using pencil-beam (PB) and recalculated with MC. The percent D95 difference (PB-MC) was calculated for the PTV and GTV. Using single linear regression, this difference was correlated with the following quantitative patient indices: maximum tumour diameter (MaxD); PTV and GTV volumes; minimum distance from tumour to soft tissue (dmin); and mean density and standard deviation of the PTV, GTV, PTV margin, lung, and 2 mm, 15 mm, 50 mm shells outside the PTV. Multiple linear regression and artificial neural network (ANN) were employed to model multiple factors and improve dose conversion accuracy. Results: Single linear regression with PTV D95 deficiency identified the strongest correlation on mean-density (location) indices, weaker on lung density, and the weakest on size indices, with the following R2 values in decreasing orders: shell2mm (0.71), PTV (0.68), PTV margin (0.65), shell15mm (0.62), shell50mm (0.49), lung (0.40), dmin (0.22), GTV (0.19), MaxD (0.17), PTV volume (0.15), and GTV volume (0.08). A multiple linear regression model yielded the significance factor of 3.0E-7 using two independent features: mean density of shell2mm (P = 1.6E-7) and PTV volume (P = 0.006). A 4-feature ANN model slightly improved the modeling accuracy. Conclusion: Quantifiable density features were proposed, replacing simple central/peripheral location designation, which showed strong correlations with PB-to-MC target dose conversion magnitude, followed by lung density and target size. Density in the immediate outer and inner areas of the PTV showed the strongest correlations. A multiple linear regression model with one such feature and PTV volume established a high significance factor, improving dose conversion accuracy