PAD Class教学模式对英语专业学生写作焦虑影响的实证研究

本研究以英语专业大一120名学生为实验对象,进行了为期16周的实证研究,以探讨PAD class教学模式对英语专业学生写作焦虑的影响。基于《二语写作焦虑量表》调查问卷结果表明:英语专业学生总体焦虑处于中等焦虑水平,PAD Class能有效降低学生的写作总体焦虑,其中课堂焦虑、构思焦虑、自信焦虑明显降低,但回避焦虑没有达到显著水平;PAD Class模式对高中低不同写作水平学生的写作焦虑都有影响,对中、低水平学生的写作焦虑缓解比对高水平学生的影响效果更明显。

Hybrid treatment of varied orthodontic appliances for a patient with skeletal class II and temporomandibular joint disorders:A case report and review of literature

BACKGROUND The relation between orthodontic treatment and temporomandibular disorders(TMDs)is under debate;the management of TMD during orthodontic treatment has always been a challenge.If TMD symptoms occur during orthodontic treatment,an immediate pause of orthodontic adjustments is recommended;the treatment can resume when the symptoms are managed and stabilized.CASE SUMMARY This case report presents a patient(26-year-old,female)with angle class I,skeletal class II and TMDs.The treatment was a hybrid of clear aligners,fixed appliances and temporary anchorage devices(TADs).After 3 mo resting and treatment on her TMD,the patient’s TMD symptom alleviated,but her anterior occlusion displayed deep overbite.Therefore,the fixed appliances with TAD were used to correct the anterior deep-bite and level maxillary and mandibular deep curves.After the levelling,the patient showed dual bite with centric relation and maximum intercuspation discrepancy on her occlusion.After careful examination of temporomandibular joints(TMJ)position,the stable bite splint and Invisible Mandibular Advancement appliance were used to reconstruct her occlusion.Eventually,the improved facial appearance and relatively stable occlusion were achieved.The 1-year follow-up records showed there was no obvious change in TMJ morphology,and her occlusion was stable.CONCLUSION TMD screening and monitoring is of great clinical importance in the TMD susceptible patients.Hybrid treatment with clear aligners and fixed appliances and TADs is an effective treatment modality for the complex cases.

Literature classification and its applications in condensed matter physics and materials science by natural language processing

The exponential growth of literature is constraining researchers’access to comprehensive information in related fields.While natural language processing(NLP)may offer an effective solution to literature classification,it remains hindered by the lack of labelled dataset.In this article,we introduce a novel method for generating literature classification models through semi-supervised learning,which can generate labelled dataset iteratively with limited human input.We apply this method to train NLP models for classifying literatures related to several research directions,i.e.,battery,superconductor,topological material,and artificial intelligence(AI)in materials science.The trained NLP‘battery’model applied on a larger dataset different from the training and testing dataset can achieve F1 score of 0.738,which indicates the accuracy and reliability of this scheme.Furthermore,our approach demonstrates that even with insufficient data,the not-well-trained model in the first few cycles can identify the relationships among different research fields and facilitate the discovery and understanding of interdisciplinary directions.

Extensive numerical simulations on competitive growth between the Edwards–Wilkinson and Kardar–Parisi–Zhang universality classes

Extensive numerical simulations and scaling analysis are performed to investigate competitive growth between the linear and nonlinear stochastic dynamic growth systems, which belong to the Edwards–Wilkinson(EW) and Kardar–Parisi–Zhang(KPZ) universality classes, respectively. The linear growth systems include the EW equation and the model of random deposition with surface relaxation(RDSR), the nonlinear growth systems involve the KPZ equation and typical discrete models including ballistic deposition(BD), etching, and restricted solid on solid(RSOS). The scaling exponents are obtained in both the(1 + 1)-and(2 + 1)-dimensional competitive growth with the nonlinear growth probability p and the linear proportion 1-p. Our results show that, when p changes from 0 to 1, there exist non-trivial crossover effects from EW to KPZ universality classes based on different competitive growth rules. Furthermore, the growth rate and the porosity are also estimated within various linear and nonlinear growths of cooperation and competition.

World Class Elite Breaststrokers Downward Kick EMG Muscle Activity of the Gluteus Maximus, Quadriceps Femoris, Hamstring, Gastrocnemius Medialis, Rectus Abdominal, and Erector Spinae

This study analyzed the difference between using a downward breaststroke kick and a horizontal breaststroke kick in a sample of world class elite swimmers.We compared average muscle activity of the gluteus maximus,quadriceps femoris(vastus medialis and rectus femoris),hamstring/long head of the biceps femoris,gastrocnemius medialis,rectus abdominal,and erector spinae when using the downward breaststroke kick technique.We find that when this sample of swimmers utilized the downward breaststroke kick,max speed and velocity per stroke increased,measured by 12,788 EMG samples,where the results are highly correlated to duration of the aerodynamic buoyant force in breaststroke kick technique.The increases in performance observed from measuring the world class elite swimmers is highly correlated to the duration of the kick aerodynamic buoyant force.Among this sample of elite swimmers,the longer a swimmer demonstrates a buoyant force breaststroke kick,the lower the time in a 100 breaststroke.

Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. However, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier.

The Alienation of Nature in Emily Dickinson’s Poems through the Prism of Taoism

In the poems created by the renowned American poet Emily Dickinson,those related to nature constitute a considerable proportion.However,Dickinson’s attitude toward nature is,in fact,contradictory.On the one hand,Dickinson perceives nature as gentle and kind,akin to a mother.Nature is regarded as“heaven”and embodies harmony.On the other hand,nature possesses its own operational principles and harbors inherent cruelty.According to Dickinson,humans should refrain from excessive interference in the natural order.This article attempts to analyze the similarities in attitude towards nature between Dickinson’s poetry and Taoist philosophy.

Problems and Development Suggestions of Nature Education in Jiangxi Province

The forest coverage rate of Jiangxi Province ranks second in China.It has rich natural resources,a long history of ancient color culture and rich red culture.In the development of nature education,Jiangxi Province has great potential and advantages.This paper introduces the development conditions of nature education in Jiangxi Province,summarizes the problems existing in the development of nature education in Jiangxi Province from the aspects of the types of nature education and the construction of nature education base,such as simple content and single form,imperfect infrastructure and lack of professionals,and puts forward some suggestions on the development of nature education in Jiangxi Province.

The Integration Strategy of Class Teacher Management and Mathematics Teaching

The professional and moral education of high school mathematics teachers will make classroom management work better,but their work pressure will also lead to classroom management problems.To do a good job in high school class teacher management and organically integrate it with mathematics teaching,we need to start from two aspects:mathematics teaching class teachers and class teacher work teaching,and penetrate mathematical thinking into daily classroom management,moral education,and classroom culture construction.Based on the attributes of the subject,we guide high school students to reflect after class to stimulate their self-management initiative through the cultivation of qualified class representatives.In addition,it is necessary to skillfully resolve classroom generative problems,change the roles of teachers and students,and integrate classroom management with mathematics teaching.

《Nature》子刊:苏佳琪等开发基于牛奶的水凝胶,用作酒精中毒的解毒剂

近日,苏黎世联邦理工学院Raffaele Mezzenga、苏佳琪等人在《Nature》子刊《Nature Nanotechnology》上发表的一篇研究显示,该研究开发了一种口服的、基于牛奶蛋白的水凝胶——FeSA@FibBLG,或可作为急性酒精中毒的有效解毒剂,能够稳定耐受胃酸消化且持续显著降低酒精中毒小鼠血液中的酒精水平,同时避免额外积累有毒的乙醛,还可增强肝脏保护,并显著减轻肠道损伤和生态失调,强调了其作为酒精相关疾病的新疗法的潜力。

Nature’s Gift

NATURAL WONDERS IN CHINA AND AFRICA Qilian Mountains National Park Located in Northwest China’s Gansu and Qinghai provinces,Qilian Mountains National Park spans 50,200 square km,serving as a vital ecological security barrier and water source conservation area in west China.Established in 2017 to address ecosystem damage,intensive food chain protection and wildlife monitoring in the area began in early 2011.

Spatiotemporal Evolution of Ecological Quality in Alpine Freshwater Lake Nature Reserves in the Past 20 Years

The Caohai Nature Reserve is one of the three major plateau freshwater lakes in China.Since the 1950s,human activities such as land reclamation and population relocation have greatly damaged Caohai.A rapid evaluation of the spatiotemporal evolution trend of the ecological quality of the Caohai Nature Reserve is significant for the maintenance and construction of the ecosystem in this area.The research is based on the Google Earth Engine(GEE)remote sensing cloud computing platform.Landsat TM/OLI images from May to October in five time periods:2000-2002,2004-2006,2009-2011,2014-2016,and 2019-2021 were obtained to reconstruct the optimal cloud image set by averaging the images in each time period.By constructing four ecological indicators:Greenness(NDVI),Wetness(Wet),Hotness(LST),and Dryness(NDBSI),and using Principal Component Analysis(PCA)method to obtain the Remote Sensing Ecological Index(RSEI)for the corresponding years,the spatiotemporal variation of ecological quality in the Caohai Nature Reserve over 20 years was analyzed.The results indicate:①the mean value of RSEI increased from 0.460 in 2000-2002 to 0.772 in 2019-2021,a 67.83%increase,indicating a significant improvement in the ecological quality of the reserve over the 20 years;②from the perspective of functional zoning of the Caohai Nature Reserve,the ecological quality of the core area showed a degrading trend,while the ecological quality of the buffer zone and experimental zone significantly improved;③with the implementation of ecological restoration projects,the ecological quality of the reserve gradually recovered and improved from 2014 to 2021.The trend of RSEI value changes is well correlated with human interventions,indicating that the PCA-based RSEI model can be effectively used for ecological quality assessment in lake areas.

《Nature》:新开发的可穿戴超声贴片可连续、无创监测大脑血流

近日,一篇发表在《Nature》上的研究显示,研究人员开发出一种可穿戴超声贴片(wearable ultrasound patch),其可对大脑血流进行连续、无创的监测。该研究将贴片在36名健康志愿者身上进行了测试,以检验其测量脑部主要动脉血流速度(收缩期峰值、平均流速和舒张末期速度)的能力,发现测量结果与传统超声探头的测量结果非常吻合。

基于CLASS促进幼儿教师提升师幼互动能力的策略

师幼互动是学前教育课程实施的主要过程,也是学前儿童在幼儿园一日活动中的生活体验、学习体验和情感体验的重要载体。师幼互动的质量对学前教育的质量起决定性作用。CLASS(课堂评价评分系统)不仅可以用来评价课堂师幼互动的质量,还可以用于提升教师师幼互动的能力。基于CLASS,文章提出了一系列提升教师师幼互动能力的相关策略。

利用绘本故事对小班幼儿进行情感支持的探究——基于CLASS评价系统的观察分析

随着师幼互动质量成为学前教育领域的研究热点话题,CLASS评价系统也逐渐被幼儿园教师熟知,其中“情感支持”维度的评估指标为教师如何与幼儿建立温馨、和谐的师幼关系提供了指引。教师借鉴CLASS评价系统,以绘本故事《鸡蛋哥哥》为载体,通过创设情境、角色代入等方式对小班幼儿进行情感支持的实践,帮助幼儿对教师、同伴、班级产生信任感、安全感及归属感。

《Nature》:科学家发现能驱动患者狼疮发生的两种细胞缺陷

近日,一篇发表在《Nature》上的研究显示,研究发现了一种特殊的分子缺陷或会促进系统性红斑狼疮的病理性免疫反应,同时揭示了逆转这一缺陷或有望逆转疾病。该研究中,研究人员报道了驱动狼疮发生的新通路,研究者表示,患者体内血液中的多种分子都会发生疾病相关的改变,最终,这些变化会导致芳香烃受体(aryl hydrocarbon receptor,AHR)所控制的通路激活不足,AHR能调节细胞对环境污染物、细菌或代谢产物的反应。

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

Least Squares One-Class Support Tensor Machine

One-class classification problem has become a popular problem in many fields, with a wide range of applications in anomaly detection, fault diagnosis, and face recognition. We investigate the one-class classification problem for second-order tensor data. Traditional vector-based one-class classification methods such as one-class support vector machine (OCSVM) and least squares one-class support vector machine (LSOCSVM) have limitations when tensor is used as input data, so we propose a new tensor one-class classification method, LSOCSTM, which directly uses tensor as input data. On one hand, using tensor as input data not only enables to classify tensor data, but also for vector data, classifying it after high dimensionalizing it into tensor still improves the classification accuracy and overcomes the over-fitting problem. On the other hand, different from one-class support tensor machine (OCSTM), we use squared loss instead of the original loss function so that we solve a series of linear equations instead of quadratic programming problems. Therefore, we use the distance to the hyperplane as a metric for classification, and the proposed method is more accurate and faster compared to existing methods. The experimental results show the high efficiency of the proposed method compared with several state-of-the-art methods.

“Eternal Motion” as a “Form of Movement of a Special Nature” and the Main Condition for the Creation of the Universe

The article hypothesizes that DE and DM (UCM) are a “Form of Motion of a Special Nature”, where “Form of Motion” means “Eternal Motion” as the power of dynamics of different levels and varying degrees of self-sufficiency, and by “Special Nature”, gravitational and two other properties of matter, “tied” to the “Eternal Movement” and completely dependent on it. Carriers of key properties of a “Special Nature” have been established: “0”-DE particles and “3”-DM particles (UDM). The unity of their inherent “motionally-gravitational” properties and the peculiarity of the relationship between “motion” and “gravity” are revealed: the higher the intensity of “Eternal Motion”, the stronger the gravitational properties of matter are manifested (and vice versa). The relationship of “time” with the “vibration frequency” and the “mass” of photons with the “degree of bonding and deformation properties of the field” is shown. The maximum level of gravity has been determined, which allows Nature to successfully create the Universe: such a landmark is the proximity to the property of the Primary Source—the “pure graviton” of the OSP space, the most powerful “motionally-gravitational” particle of the Universe. The reasons for the emergence of such an identity of the gravitational properties of particles with the indicators of a “pure graviton” are established: for “0”-DE particles, this is the acquisition of the function of “freedom of movement”;for “3”-DM particles (UDM), the creation of a special structure—a “double field” (“Main” and “Small”). The presence in the “double field” of specific “tools” for the creation of the worlds of the Universe—gravitational “waves” gives rise to impulses (shocks) of varying intensity and shape. A list of functions performed by “waves” in the “Main” and “Small” fields has been compiled. The specific conditions for the formation of “UDM Streams”, their transformation into a “Vortex” and, under the influence of a powerful Initial Impulse (push), sending them to the “place” of the creation of galaxies, are shown. It is suggested that there is a “Cycle of Matter in Nature” in the closed structure of our Universe due to the “work” of “waves” and the functioning of special “factories” in the form of exotic space objects—Black holes.

教师特征对托班师幼互动质量的影响——基于CLASS Toddler的实证研究

构建“数量”和“质量”双重保障的托育服务体系是解决“托育难”“幼无所托”等民生难题以及实现人口发展战略重要配套措施。师幼互动是托育服务质量的核心指标,影响婴幼儿身心发展的多个方面。托班师幼互动质量水平不高,尤其不能提供适宜的学习支持,而教师学历是影响师幼互动质量的重要因素。因此,需要提高托班教师“学历”门槛,建立职前职后“师幼互动”一体化培训体系,重视师幼互动质量的评估,切实提高教师师幼互动能力。