The Implication of Gagne’s Five Categories of Learning on Designing English Teaching Objectives

Robert Mills Gagne's five categories of learning have a profound influence on the many aspects of educational field.This essay attempts to differentiate and analyze the five categories of learning:motor skills,verbal information,intellectual skills,cognitive strategies,and attitudes.And then applies Gagne's five categories of learning to design English teaching objectives.

Machine learning as a tool predicting short-term postoperative complications in Crohn’s disease patients undergoing intestinal resection: What frontiers?

The recent study,“Predicting short-term major postoperative complications in intestinal resection for Crohn’s disease:A machine learning-based study”invest-igated the predictive efficacy of a machine learning model for major postoperative complications within 30 days of surgery in Crohn’s disease(CD)patients.Em-ploying a random forest analysis and Shapley Additive Explanations,the study prioritizes factors such as preoperative nutritional status,operative time,and CD activity index.Despite the retrospective design’s limitations,the model’s robu-stness,with area under the curve values surpassing 0.8,highlights its clinical potential.The findings align with literature supporting preoperative nutritional therapy in inflammatory bowel diseases,emphasizing the importance of compre-hensive assessment and optimization.While a significant advancement,further research is crucial for refining preoperative strategies in CD patients.

Forecasting S&P 500 Stock Index Using Statistical Learning Models

Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Comparison and development of machine learning for thalidomideinduced peripheral neuropathy prediction of refractory Crohn’s disease in Chinese population

BACKGROUND Thalidomide is an effective treatment for refractory Crohn’s disease(CD).However,thalidomide-induced peripheral neuropathy(TiPN),which has a large individual variation,is a major cause of treatment failure.TiPN is rarely predictable and recognized,especially in CD.It is necessary to develop a risk model to predict TiPN occurrence.AIM To develop and compare a predictive model of TiPN using machine learning based on comprehensive clinical and genetic variables.METHODS A retrospective cohort of 164 CD patients from January 2016 to June 2022 was used to establish the model.The National Cancer Institute Common Toxicity Criteria Sensory Scale(version 4.0)was used to assess TiPN.With 18 clinical features and 150 genetic variables,five predictive models were established and evaluated by the confusion matrix receiver operating characteristic curve(AUROC),area under the precision-recall curve(AUPRC),specificity,sensitivity(recall rate),precision,accuracy,and F1 score.RESULTS The top-ranking five risk variables associated with TiPN were interleukin-12 rs1353248[P=0.0004,odds ratio(OR):8.983,95%confidence interval(CI):2.497-30.90],dose(mg/d,P=0.002),brainderived neurotrophic factor(BDNF)rs2030324(P=0.001,OR:3.164,95%CI:1.561-6.434),BDNF rs6265(P=0.001,OR:3.150,95%CI:1.546-6.073)and BDNF rs11030104(P=0.001,OR:3.091,95%CI:1.525-5.960).In the training set,gradient boosting decision tree(GBDT),extremely random trees(ET),random forest,logistic regression and extreme gradient boosting(XGBoost)obtained AUROC values>0.90 and AUPRC>0.87.Among these models,XGBoost and GBDT obtained the first two highest AUROC(0.90 and 1),AUPRC(0.98 and 1),accuracy(0.96 and 0.98),precision(0.90 and 0.95),F1 score(0.95 and 0.98),specificity(0.94 and 0.97),and sensitivity(1).In the validation set,XGBoost algorithm exhibited the best predictive performance with the highest specificity(0.857),accuracy(0.818),AUPRC(0.86)and AUROC(0.89).ET and GBDT obtained the highest sensitivity(1)and F1 score(0.8).Overall,compared with other state-of-the-art classifiers such as ET,GBDT and RF,XGBoost algorithm not only showed a more stable performance,but also yielded higher ROC-AUC and PRC-AUC scores,demonstrating its high accuracy in prediction of TiPN occurrence.CONCLUSION The powerful XGBoost algorithm accurately predicts TiPN using 18 clinical features and 14 genetic variables.With the ability to identify high-risk patients using single nucleotide polymorphisms,it offers a feasible option for improving thalidomide efficacy in CD patients.

Strategies on Promoting Transformative Learning of College English Teachers

Based on the previous case study in promoting transformative learning of college English teachers,who participated in a three-month online training courses,the article made a further research and concluded four strategies on promoting transformative learning of college English Teachers.

Design and Application of English Learning System based on B/S Structure

This paper analyzes advantages and disadvantages of the current several popular computer-aided English learning software. combined with modem English teaching philosophy, proposed learning system with synchronization, interactivity, intelligence, and incentives in one of the English to students. System uses JavaEE framework to build, each module uses a low coupling between the way facilitate future extensions. The system can help students build confidence and motivate its progress.

Design and study of computer aided English learning system

Use the Internet for online learning has become one of the directions of the development of education, the traditional classroom learning, the breakthrough time and geographical constraints, more convenient interaction between teachers and students, learning resources are more abundant, more diverse learning styles, has broad application prospects. System uses B / S mode, the application of Java language, together with the MySQL database, high security and good performance.

Effects of Panax notoginseng saponins in a rat model of Alzheimer's disease

BACKGROUND： Modem pharmacological studies have demonstrated that Panax notoginseng saponins （PNS） can ameliorate and protect from neuropathological impairment. Whether PNS can improve the abnormality in memory and behavior of rats with Alzheimer＇s disease （AD） remains unclear. OBJECTIVE： Based on a Morris water maze test, this study aimed to measure improvements of spatial learning and memory by PNS in a rat model of AD, and to compare effects with huperzine A. DESIGN： A completely randomized grouping design, controlled animal experiment. SETTING： Center of Research ＆ Development of New Drugs, Guangxi Traditional Chinese Medical University. MATERIALS： Ninety healthy Wistar rats of both genders, 15-month-old （n =75） and 3-month-old rats as young controls （n =15）, were used for this study. The study was performed in accordance with animal ethics guidelines for the use and care of animals. PNS was provided by Weihe Pharmaceutical Co., Ltd （permission No. Z53021485, Yuxi, Yunan Province, China）. Morris water maze equipment was provided by the Institute of Physiology, Chinese Academy of Science. METHODS： This study was performed at the Center of Research ＆ Development of New Drugs, Guangxi Traditional Chinese Medical University from June 2003 to April 2005. Of the included rats, 15 healthy aged rats were randomly chosen as aged controls, and the remaining 60 aged rats were randomly divided into 4 groups with 15 rats in each： model group, PNS high- and low-dose groups, and an huperzine A group. Rats in the model group and the 3 treated groups were treated with intraperitoneal infusion of 9.6 g/L D-galactose （5 mL/kg） every day for 6 weeks successively to induce a subacute aging model. During week 7, animals received 1 μ L ibotenic acid （5 g/L） bilaterally into the nucleus basalis of Meynert to create a rat model of AD. The young and old rat controls received, in parallel, a corresponding volume of saline. Two weeks later, rats in the PNS high- and low-dose groups were gavaged with 200 and 100 mg/kg PNS suspension, respectively. Huperzine A suspension （0.3 mg/kg） was used in the huperzine A group. Rats in the other 3 groups were gavaged with a corresponding volume of normal saline. In each group, administration was carried out once per day for 4 consecutive weeks. MAIN OUTCOME MEASURES： After administration, learning and memory abilities were measured by place navigation and spatial probe tests. Recording indices consisted of escape latency （time-to-platform）, number of times to find the platform within 2 minutes, number of times the animal crosses the original platform location, and the percent of swimming time in each quadrant. RESULTS： Several rats died due to inflammatory reactions following brain lesion or intragastric administration; therefore, 61 rats were included in the final analysis. Results of spatial navigation test： Escape latency of rats in the model group was significantly prolonged, and number of times to find the platform within 2 minutes were significantly reduced compared with other groups （both P 〈 0.05）. No significant differences in these two indices were measured among the administration groups （all P 〉 0.05）. Results of spatial probe test： Times for crossing the original platform location and percent of time spent in the quadrant of original platform location were significantly less in the model group than in the other groups （P 〈 0.05）. There were no significant differences in these two indices among the administration groups （P 〉 0.05）. CONCLUSION： PNS can remarkably improve spatial learning and memory abilities of rats with AD. The therapeutic effect of PNS is not dose-dependent and is equivalent to the effect of huperzine A.

Three Models of English Education in China＇s Universities ——-A Historical Perspective

In the present paper, a comparison is made of the three formats in the history of EECU （English education in China＇s universities）. In the first period （1904-1949）, English education was conducted separately in government-managed educational institutions and in institutions sponsored by church-related organizations; English education was well-knit with both general education and specialty education; and self-motivating learning was encouraged. In the second period （1950-1966）, almost everything was tinted with a shady color of politics： A halt was addressed drastically to EEC （English education in China） in 1952. In the gradual recovery that started four years later, the second format was sawed and hammered, showing the following features： All non-government-mamaged institutions vanished from the stage; English was taught solely as a language or a system of verbal parts, almost deprived of all cultural loading. The third period （1978 onwards） has witnessed a barrier-free and rapid development of over three decades, resulting in the unprecedented pervasion of EECU. Yet in the third tbrmat, learners＇ efforts have turned wholly test-oriented, degenerating into the saddening disintegrity of learning as a process into isolated charges to the target of a test at a time; the ignorant reduction of the learning methods to ＂Vocabulary Booklets Plus Collections of Test Papers＂. Such a comparison not only provides a multi-dimensional perspective of EECU and a better understanding of it, but also offers some important experiences and lessons for the search of an effective solution to the pervasive problem of＂Time-Consumingness and Low-Efficiency＂.

Simulation modeling on the growth of firm's safety management capability

Aiming to the deficiency of safety management measure,established simulation model about firm's safety management capability(FSMC) based on organizational learning theory.The system dynamics(SD) method was used,in which level and rate system,vari- able equation and system structure flow diagram was concluded.Simulation model was verified from two aspects: first,model's sensitivity to variable was tested from the gross of safety investment and the proportion of safety investment;second,variables dependency was checked up from the correlative variable of FSMC and organizational learning.The feasibility of simulation model is verified though these processes.

Functionalized Data Operator Model for System Analysis and Forecasting

A deconvolution data processing is developed for obtaining a Functionalized Data Operator (FDO) model that is trained to approximate past and present, input-output data relations. The FDO model is designed to predict future output features for deviated input vectors from any expected, feared of conceivable, future input for optimum control, forecast, or early-warning hazard evaluation. The linearized FDO provides fast analytical, input-output solution in matrix equation form. If the FDO is invertible, the necessary input for a desired output may be explicitly evaluated. A numerical example is presented for FDO model identification and hazard evaluation for methane inflow into the working face in an underground mine: First, a Physics-Based Operator (PBO) model to match monitored data. Second, FDO models are identified for matching the observed, short-term variations with time in the measured data of methane inflow, varying model parameters and simplifications following the parsimony concept of Occam’s Razor. The numerical coefficients of the PBO and FDO models are found to differ by two to three orders of magnitude for methane release as a function of short-time barometric pressure variations. As being data-driven, the significantly different results from an FDO versus PBO model is either an indication of methane release processes poorly understood and modeled in PBO, missing some physics for the pressure spikes;or of problems in the monitored data fluctuations, erroneously sampled with time;or of false correlation. Either way, the FDO model is originated from the functionalized form of the monitored data, and its result is considered experimentally significant within the specified RMS error of model matching.

探究早期帕金森病Thy 1-SNCA模型小鼠运动学习障碍的时间特征

目的本实验通过建立早期帕金森病(Parkinson s disease,PD)小鼠模型,以探究PD模型出现运动学习障碍的时间特征。方法选用6月龄Thy 1-SNC A转基因(transgenic,TG)小鼠作为早期PD模型,与同龄野生型(wild type,WT)小鼠进行对比分析。通过旷场实验、爬杆实验和Y迷宫等行为学手段来评估小鼠的运动功能和空间工作记忆能力,并以经典的匀加速转棒实验作为运动学习的行为学范式,来评估其运动学习能力。结果6月龄的Thy 1-SNC A TG小鼠在运动功能和空间记忆能力方面并未显示出异常,却呈现出明显的运动学习障碍。结论在早期PD模型小鼠上存在着特定的运动学习障碍,可作为早期PD的一个重要诊断指标;同时匀加速转棒测试可作为检测PD运动学习障碍的一种重要的行为学手段。

3种拟痴呆动物模型在Morris水迷宫行为学测试中学习记忆行为的差异

目的 Morris水迷宫实验是一种评价空间学习记忆能力的经典方法,是评价痴呆动物模型复制结果的客观指标。近年来痴呆动物模型已成为研究老年性痴呆的重要手段。文中评价3种常见拟痴呆动物模型在Morris水迷宫行为学测试中学习记忆行为的差异。方法分别使用SD大鼠、昆明种小鼠以及快速老化小鼠制备Aβ脑室注射致痴呆模型、东莨菪碱腹腔注射致记忆障碍模型、快速老化模型。采用Morris水迷宫行为学测试方法,将这3种模型通过与其相应的对照组比较,考察其行为学差异。结果东莨菪碱模型与快速老化模型逃避潜伏期时间短于相应对照组,其中以东莨菪碱模型差异尤为显著[(35.47±3.78)s vs(50.61±3.94)s,P<0.01];快速老化组模型与对照组差异有统计学意义[(17.39±4.71)s vs(33.79±7.81)s,P<0.05];Aβ致痴呆模型与其对照组比较,模型定位航行实验成绩差异无统计学意义(P>0.05)。结论东莨菪碱腹腔注射致记忆障碍模型较其他2种常用模型更为理想。Morris水迷宫行为学测试方法是一种评价拟痴呆动物的理想方法。

水下机器人T-S型模糊神经网络控制

针对水下机器人模糊神经网络控制器运算量大和对强外界扰动的鲁棒性差及存在滞后性的问题,提出基于混合学习算法的水下机器人T-S型模糊神经网络控制方法。采用免疫遗传算法离线优化和神经网络自学习在线调整隶属函数的参数,从而减少神经网络的运算量,增强水下机器人对环境变化的反应能力。采用T-S模型,由后件网络动态调整模糊规则,提高控制系统的适应性。通过某微小型水下机器人的仿真和外场实验验证方法的可行性和优越性。实验结果表明,控制器对外界扰动具有较强的鲁棒性,保证即使在恶劣情况下,控制性能仍保持在较高水平。

基于T-S模糊模型的间歇过程的迭代学习容错控制

间歇过程不仅具有强非线性,同时还会受到诸如执行器等故障影响,研究非线性间歇过程在具有故障的情况下依然稳定运行至关重要。针对执行器增益故障及系统所具有的强非线性,提出一种新的基于间歇过程的T-S模糊模型的复合迭代学习容错控制方法。首先根据间歇过程的非线性模型,利用扇区非线性方法建立其T-S模糊故障模型,再利用间歇过程的二维特性与重复特性,在2D系统理论框架内,设计2D复合ILC容错控制器,进而构建此T-S模糊模型的等价二维Rosser模型,接着利用Lyapunov方法给出系统稳定充分条件并求解控制器增益。针对强非线性的连续搅拌釜进行仿真,结果表明所提出方法具有可行性与有效性。

基于T-S模型的迭代学习控制算法及其在机器人点位控制中的仿真研究

考虑了一类特殊的迭代学习控制问题,即用迭代学习方法解决机器人的点位控制问题。采用T-S模型描述机器人系统,在T-S模型的基础上,运用并行分配补偿方法(PDC)确定T-S模型的迭代学习控制器结构,并给出了误差收敛条件。为避免迭代过程的初始定位操作,文中还设计了模糊循环迭代学习律。最后以在垂直面内运动的单关节的机器人为例说明了所提出方法的有效性。

水泥分解炉出口温度T-S建模

为利用基于模型的方法研究水泥分解炉温度控制问题,提出了一种水泥分解炉出口温度Takagi-Sugeno(T-S)建模方法。首先,在水泥预分解工艺分析的基础上,结合现场采集的数据,采用回归分析和极限学习机(ELM)的学习算法建立了水泥分解炉不同工况下的数学模型;然后,在此基础上,结合水泥预分解工作特点划分隶属度曲线,建立其T-S模糊模型;最后,仿真结果表明所提方法的有效性。

感知交互性对在线学习者持续学习意愿的影响:基于S-O-R视角

以"刺激-机体-反应"(S-O-R)模型为理论基础,深入探讨感知交互性对在线学习者持续学习意愿的影响,将感知交互性分为四个维度:感知控制、感知响应性、感知个性化和感知互助。以某师范大学的部分在校生为研究对象,采用问卷调查的方法收集数据,利用AMOS和SPSS软件对数据进行处理从而对已建构的理论模型进行检验和分析。研究结果表明,感知控制、感知响应、感知互助均正向影响社会临场感;感知控制直接影响学习者的心流体验;社会临场感通过心流体验对学习者的持续学习意愿存在显著影响;而感知个性化对社会临场感和心流体验的影响在本研究中没有得到证实;不同受教育程度、学习动机的在线学习者在持续学习意愿上无显著差异。

快速老化小鼠SAMP10的老化特征及其研究进展

快速老化小鼠(senescence-accelerated mouse,SAM)是日本京都大学Takeda教授从AKR/J系小白鼠中通过表型选择培育出的快速老化模型。根据老化速度和病状特征,SAM鼠可以分为快速衰老的P系和抗快速老化的R系。快速老化小鼠SAMP10作为P系的一种,主要特征表现为与衰老相关的学习记忆障碍,具有β-淀粉样蛋白沉积、脑萎缩、神经DNA损伤、星形胶质细胞及小胶质细胞增生等病理变化,在行为学、神经递质以及分子水平方面均表现出一定的衰老变化,是目前较理想的研究阿尔采末病(AD)的动物模型。同龄对照组SAMR1具有正常的衰老特征,常用于SAMP10的正常对照。目前SAMP10是比较理想的用于研究学习记忆障碍的发病机制、评价抗衰老药物以及抗抑郁药的动物模型。