Prevalence and Factors Associated with Overweight and Obesity among Public Secondary School Teachers in Parakou, Benin, in 2021

Introduction: Overweight and obesity represent a public health problem in Africa due to the epidemiological transition. The objectives of this work were to determine the prevalence of overweight and obesity and to identify associated factors among public secondary school teachers in Parakou, Benin in 2021. Methods: We conducted a descriptive and analytical cross-sectional study. Teachers working in public secondary schools in Parakou during the 2020-2021 academic year, present at work and who gave their written informed consent, were included. A two-stage random sampling was carried out. Data were collected during an individual interview using a questionnaire followed by the measurement of anthropometric parameters and blood pressure. Overweight and obesity were defined by a body mass index ≥ 25 kg/m2. Multivariable logistic regression was performed to identify associated factors. Results: A sample of 325 teachers, including 88.6% of men, was recruited with an average age of 36.2 ± 6.8 years. The prevalence of overweight and obesity was 43.7% (95% CI [38.1%-44.8%]). It increased significantly with income (p Conclusion: The results show a high prevalence of overweight and obesity. Actions are necessary to prevent overweight and obesity among secondary school teachers in Parakou, in Benin.

An attention-based teacher-student model for multivariate short-term landslide displacement prediction incorporating weather forecast data

Predicting the displacement of landslide is of utmost practical importance as the landslide can pose serious threats to both human life and property.However,traditional methods have the limitation of random selection in sliding window selection and seldom incorporate weather forecast data for displacement prediction,while a single structural model cannot handle input sequences of different lengths at the same time.In order to solve these limitations,in this study,a new approach is proposed that utilizes weather forecast data and incorporates the maximum information coefficient(MIC),long short-term memory network(LSTM),and attention mechanism to establish a teacher-student coupling model with parallel structure for short-term landslide displacement prediction.Through MIC,a suitable input sequence length is selected for the LSTM model.To investigate the influence of rainfall on landslides during different seasons,a parallel teacher-student coupling model is developed that is able to learn sequential information from various time series of different lengths.The teacher model learns sequence information from rainfall intensity time series while incorporating reliable short-term weather forecast data from platforms such as China Meteorological Administration(CMA)and Reliable Prognosis(https://rp5.ru)to improve the model’s expression capability,and the student model learns sequence information from other time series.An attention module is then designed to integrate different sequence information to derive a context vector,representing seasonal temporal attention mode.Finally,the predicted displacement is obtained through a linear layer.The proposed method demonstrates superior prediction accuracies,surpassing those of the support vector machine(SVM),LSTM,recurrent neural network(RNN),temporal convolutional network(TCN),and LSTM-Attention models.It achieves a mean absolute error(MAE)of 0.072 mm,root mean square error(RMSE)of 0.096 mm,and pearson correlation coefficients(PCCS)of 0.85.Additionally,it exhibits enhanced prediction stability and interpretability,rendering it an indispensable tool for landslide disaster prevention and mitigation.

LDAS&ET-AD:Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation

Adversarial distillation(AD)has emerged as a potential solution to tackle the challenging optimization problem of loss with hard labels in adversarial training.However,fixed sample-agnostic and student-egocentric attack strategies are unsuitable for distillation.Additionally,the reliability of guidance from static teachers diminishes as target models become more robust.This paper proposes an AD method called Learnable Distillation Attack Strategies and Evolvable Teachers Adversarial Distillation(LDAS&ET-AD).Firstly,a learnable distillation attack strategies generating mechanism is developed to automatically generate sample-dependent attack strategies tailored for distillation.A strategy model is introduced to produce attack strategies that enable adversarial examples(AEs)to be created in areas where the target model significantly diverges from the teachers by competing with the target model in minimizing or maximizing the AD loss.Secondly,a teacher evolution strategy is introduced to enhance the reliability and effectiveness of knowledge in improving the generalization performance of the target model.By calculating the experimentally updated target model’s validation performance on both clean samples and AEs,the impact of distillation from each training sample and AE on the target model’s generalization and robustness abilities is assessed to serve as feedback to fine-tune standard and robust teachers accordingly.Experiments evaluate the performance of LDAS&ET-AD against different adversarial attacks on the CIFAR-10 and CIFAR-100 datasets.The experimental results demonstrate that the proposed method achieves a robust precision of 45.39%and 42.63%against AutoAttack(AA)on the CIFAR-10 dataset for ResNet-18 and MobileNet-V2,respectively,marking an improvement of 2.31%and 3.49%over the baseline method.In comparison to state-of-the-art adversarial defense techniques,our method surpasses Introspective Adversarial Distillation,the top-performing method in terms of robustness under AA attack for the CIFAR-10 dataset,with enhancements of 1.40%and 1.43%for ResNet-18 and MobileNet-V2,respectively.These findings demonstrate the effectiveness of our proposed method in enhancing the robustness of deep learning networks(DNNs)against prevalent adversarial attacks when compared to other competing methods.In conclusion,LDAS&ET-AD provides reliable and informative soft labels to one of the most promising defense methods,AT,alleviating the limitations of untrusted teachers and unsuitable AEs in existing AD techniques.We hope this paper promotes the development of DNNs in real-world trust-sensitive fields and helps ensure a more secure and dependable future for artificial intelligence systems.

How to promote cooperative innovation in environmentally friendly technology:a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China.First,we constructed an evolutionary game model comprising the factors of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies.Using MATLAB simulation,we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’willingness to cooperate.Results showed that when the values of net income of cooperative innovation,net income of independent innovation,market constraints,and government subsidies exceeded the threshold,innovators’willingness to cooperate was significantly enhanced.Furthermore,the proportion of innovators who cooperated with others gradually increased to 100%;otherwise,it gradually decreased to 0%.Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China,we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation,low income from cooperative innovation,weak profitability of innovators,and weak market constraints.

Professional Development of Rural PE Teachers from the Perspective of PCK:A Case Study of Huaiji County

Based on the four dimensions of PCK,this paper investigates the professional development of rural PE teachers in Huaiji County by using the research methods of literature,questionnaire,interview and mathematical statistics.Based on PCK related theories,this paper analyzes the current situation of professional development of rural PE teachers in Huaiji County,explores the problems existing in the process of professional development,and provides an optimal path for the professional development of rural PE teachers,so as to improve the teaching ability and classroom quality of rural PE teachers,and promote the further development of rural PE education under the background of new curriculum reform.Through the research,it is found that the shortcomings of rural PE teachers are:lack of situational knowledge;lack of understanding of the course content;not flexible use of teaching representation;low ability to identify the differences of students learning styles;lack of understanding of social environment,etc.

Commuting Space of Primary and Secondary Schools in the Context of Child Friendly Cities:A Case Study of Bajiao Street of Shijingshan District

With the continuous promotion of the construction of child friendly cities,the school commuting space is an important component of the construction of child friendly roads.Based on the background of child friendly cities,the commuting space of 11 primary and secondary schools in Bajiao Street is analyzed through literature analysis and field research methods.Firstly,the relevant literature on school commuting space is sorted out,and the characteristics of school commuting space are summarized,including transportation,landscape,culture,leisure,and security.Secondly,the characteristics of commuting space of primary and secondary schools in Bajiao Street are analyzed from three aspects:in front of the school gate,path space,and node space.This paper aims to provide reference and guidance for the future construction of children’s walking school commuting and promote the construction of a child friendly city.

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.

The Appeals,Dilemmas,and Pathways of Enabling Rural Teachers’Professional Development Through Emerging Technologies

With the rapid advancements in technology,especially in digitalization and intelligence,numerous modern technologies have poured into rural schools,effectively improving their informatization conditions.Nevertheless,these technologies remain detached from rural teachers,failing to significantly enhance the quality of education and teaching in rural areas.Rural education is a crucial aspect of ensuring balanced development in education.The question of how to enhance rural teachers’technological application abilities and fully leverage the positive role of technology in rural education and teaching has become a significant topic of current research on rural education issues.To better address this question,this study conducted a thorough examination of the specific appeals of rural teachers in the process of technology enablement.It was discovered that rural teachers generally face dilemmas such as insufficient technological application abilities,difficulties in obtaining quality teaching resources,and the lack of continuous technical support and update mechanisms.Based on these findings,specific pathways such as strengthening rural teacher training,optimizing the allocation of educational resources,and establishing mechanisms for continuous technical support and updates are proposed to aid in the high-quality development of rural education.

Effects of Perceived Teacher Support on Student Behavioral Engagement in the Blended Learning Environment:Learning Experience as a Mediator

Blended learning(BL)has been widely adopted to improve students’academic achievements in higher education.However,its success relies mainly on student engagement,which plays an essential role in active learning and provides a rich understanding of students’experiences.The study utilized three self-designed scales-the Teacher Support Scale,Student Engagement Scale,and Student Learning Experience Scale-to gauge and examine the impact and relationship between perceived teacher support,student behavioral engagement,and the intermediary role of learning experiences.A cohort of 899 college students undertaking the obligatory College English course through BL modes across five Chinese universities actively participated by completing a comprehensive questionnaire.The results showed significant correlations between perceived teacher support,learning experience,and behavioral engagement.Perceived teacher support significantly predicted students’behavioral engagement,with socio-affective support exerting the most substantial predictive effects.All predictive effects were partially mediated by learning experience(learning mode,online resources,overall LMS-based learning,interaction with their instructor and peers,and learning outcome).The influence of perceived teacher support on behavioral engagement differed between students who reported the most positive(vs.negative)learning experiences.Suggestions for further research are offered for consideration.

Exploration of Teaching Development Strategies for Double-Qualified Teachers in University- Affiliated Hospitals Based on Role Conflict Theory

This study draws on the classic theories and research achievements of university teacher development,and from the perspective of role conflict in social psychology,proposes policy recommendations for the development of clinical teachers in medical colleges,including following different stages of teacher development and designing teaching development strategies at different levels;designing the content and form of teaching development activities to meet the temporal and spatial needs of clinical teachers;and building an academic community for clinical teachers to promote the creation of teaching development behaviors.

Current Situation and Countermeasures of the Construction of “Double-Qualified” Teachers in Higher Vocational Colleges

The construction of“double-qualified”teachers is the basic premise for the high-quality development of higher vocational education,and it is also the key force for higher vocational colleges to cultivate high-quality skilled talents.This paper probes into the positioning of the construction of“double-qualified”teachers in higher vocational colleges,deeply analyzes the current situation of the construction of“double-qualified”teachers in higher vocational colleges,and provides the countermeasures of the construction of“double-qualified”teachers.

Research on the Status Quo and Improvement Needs of Foreign Language Teachers’ Teaching Competence in Curriculum-Based Ideological Education in Xinjiang Colleges and Universities

This study investigated the status quo and further improvement needs of foreign language teachers’teaching competence in curriculum-based ideological education(CIE)in Xinjiang colleges and universities.The results show that the teachers’teaching competence in CIE is generally good,with the“cultivating quality”being the highest and the“scientific research quality”the lowest;there still exist several problems,such as teachers’lack of theoretical knowledge in CIE,lack of teaching resources,and insufficient abilities in teaching design and research.It is hoped that with the support and efforts from university administrations,teachers can improve their teaching competence in CIE through various approaches adopted and multiple measures taken,thus optimizing their teaching effectiveness,promoting the construction of CIE in Xinjiang colleges and universities in the new era,and contributing to Xinjiang’s high-quality development.

Utilization of Basalt Saw Mud as a Spherical Porous Functional Aggregate for the Preparation of Ordinary Structure Concrete

To promote the production and application of artificial aggregates,save natural sand resources and protect the ecological environment,we evaluated the feasibility of using spherical porous functional aggregates(SPFAs) formed by basalt saw mud under autoclave curing in ordinary structural concrete.In our work,two types of prewetted functional aggregates were taken as replacements for natural aggregates with different volume substitution rates(0%,5%,10%,15%,20%,25%,and 30%) in the preparation of ordinary structural concrete with water-to-binder ratios(W/B) of 0.48 and 0.33.The effects of the functional aggregate properties and content,W/B,and curing age on the fluidity,density,mechanical properties and autogenous shrinkage of ordinary concrete were analyzed.The experimental results showed that the density of concrete declined at a rate of not more than 5%,and the 28 d compressive strength could reach 31.0-68.2 MPa.Low W/B,long curing age and high-quality functional aggregates were conducive to enhancing the mechanical properties of SPFAs concrete.Through the rolling effects,SPFAs can optimize the particle gradation of aggregate systems and improve the fluidity of concrete,and the water stored inside SPFAs provides an internal curing effect,which prolongs the cement hydration process and considerably reduces the autogenous shrinkage of concrete.SPFAs exhibits high strength and high density,as well as being more cost-effective and ecological,and is expected to be widely employed in ordinary structural concrete.

A Novel Graph Structure Learning Based Semi-Supervised Framework for Anomaly Identification in Fluctuating IoT Environment

With the rapid development of Internet of Things(IoT)technology,IoT systems have been widely applied in health-care,transportation,home,and other fields.However,with the continuous expansion of the scale and increasing complexity of IoT systems,the stability and security issues of IoT systems have become increasingly prominent.Thus,it is crucial to detect anomalies in the collected IoT time series from various sensors.Recently,deep learning models have been leveraged for IoT anomaly detection.However,owing to the challenges associated with data labeling,most IoT anomaly detection methods resort to unsupervised learning techniques.Nevertheless,the absence of accurate abnormal information in unsupervised learning methods limits their performance.To address these problems,we propose AS-GCN-MTM,an adaptive structural Graph Convolutional Networks(GCN)-based framework using a mean-teacher mechanism(AS-GCN-MTM)for anomaly identification.It performs better than unsupervised methods using only a small amount of labeled data.Mean Teachers is an effective semi-supervised learning method that utilizes unlabeled data for training to improve the generalization ability and performance of the model.However,the dependencies between data are often unknown in time series data.To solve this problem,we designed a graph structure adaptive learning layer based on neural networks,which can automatically learn the graph structure from time series data.It not only better captures the relationships between nodes but also enhances the model’s performance by augmenting key data.Experiments have demonstrated that our method improves the baseline model with the highest F1 value by 10.4%,36.1%,and 5.6%,respectively,on three real datasets with a 10%data labeling rate.

Written Speech of Deputy Speaker of the 49th National Assembly of Bulgaria Tsoncho Ganev to the Civilisation Lecture

Distinguished guests,Dear Chinese friends,I wish to extend my most sincere greetings and congratulations to the Civilisation Lecture.The traditional friendship between Bulgaria and China has been upgraded to a strategic partnership.This year marks the 75th anniversary of the establishment of diplomatic relationship between Bulgaria and China.I believe that the traditional friendship between our civilisations and nations will lay a solid foundation for future bilateral exchanges and cooperation.

An Assessment of English Instruction for Elementary-Level Students in Jeddah Governorate, as Perceived by English Supervisors and Educators

This study investigated the perceptions of English educators and supervisors in Jeddah Governorate regarding the process of teaching English to elementary students.A survey was conducted using a sample size of 94 educators and 10 supervisors.The data indicate that respondents considered English instruction at the elementary level essential for expanding kids’perspectives,improving academic performance,and promoting international involvement.The main advantages cited are the development of English language skills and the promotion of early education.Although not as easily noticeable,the disadvantages include potential negative impacts on an individual’s proficiency in Arabic and their sense of national identification.The highlighted challenges encompass insufficient teacher training,student reluctance towards English,limited resources,and school disparities.The proposed techniques focused on prioritizing English instructors’training,ensuring the use of appropriate content,utilizing technology,and promoting awareness of students and educators.The current research found different obstacles in teaching English at elementary stages.To overcome these obstacles,it will be essential to enhance teacher competencies,develop efficient teaching methods,get the backing of stakeholders,assign adequate resources,and carry out continuous evaluations.Further research can also contribute to a better understanding of how early English learning impacts on Arabic identity and proficiency.

An Interview-Based Study of the Factors Influencing the Quality of Professional Training of Science Education Graduates

The proposal of the strategy of developing the country through science education has clarified China’s demand for the development of the science and education industry and the cultivation of science and education talents,and the birth of Science Education majors is an important link in the cultivation of scientific literacy.Based on the grounded theory,we interviewed three Science Education graduates from a university and coded the interview data by using NVivo 12.0 to find eight important factors affecting their professional training and employment choices.The factors are“social factors,”“individual career choice factors,”“campus resources,”“employment advantages,”“professional self-development,”“teacher factors,”“planning for further education and employment,”and“student motivation.”This study analyzes the interaction between the influencing factors,constructs a theoretical model of the influencing factors of the quality of Science Education professional training,explores the problems of the training process of Science Education majors and employment dilemmas,and puts forward corresponding suggestions.

混合研修对中小学教师教学能力影响因素研究--基于PAST视域的探析

混合式研修活动已成为新时代提升教师专业素养和核心能力的重要途径。基于PAST理论,从教学法设计、研修空间、研修评价和技术支持四维度,探讨中小学教师在混合研修活动中信息化教学能力提升的影响因素,并构建结构方程模型,采用最大似然法、多群组分析等方法对数据进行分析与验证。研究发现,PAST四维度是影响教师参与混合研修的关键因素,其中教学法设计(0.411)与研修空间(0.234)影响较大;性别和任教年资在教师参与混合研修中发挥着重要的调节作用。基于此,研究提出构建“点一面一体”相结合的研修空间结构、创新设计AI支持下的混合研修模式、建立“线上+线下”混合研修协同管理机制等建议,以期为促进教师专业发展提供借鉴。

集体教学活动中实习教师与熟手教师的师幼互动差异研究——基于CLASS评估系统的课堂观察

运用CLASS课堂互动评估系统对集体教学活动中新手、熟手两类教师进行差异研究。两类教师的互动氛围整体积极,差异在于活动准备及活动组织效率、互动反馈质量等方面。新手教师应当积极增加教学经验,提高集体教学能力;转变教学教育观念,注重幼儿创新思维发展;观摩学习互动能力,增强语言示范作用。

A Lightweight IoT Malware Detection and Family Classification Method

A lightweight malware detection and family classification system for the Internet of Things (IoT) was designed to solve the difficulty of deploying defense models caused by the limited computing and storage resources of IoT devices. By training complex models with IoT software gray-scale images and utilizing the gradient-weighted class-activated mapping technique, the system can identify key codes that influence model decisions. This allows for the reconstruction of gray-scale images to train a lightweight model called LMDNet for malware detection. Additionally, the multi-teacher knowledge distillation method is employed to train KD-LMDNet, which focuses on classifying malware families. The results indicate that the model’s identification speed surpasses that of traditional methods by 23.68%. Moreover, the accuracy achieved on the Malimg dataset for family classification is an impressive 99.07%. Furthermore, with a model size of only 0.45M, it appears to be well-suited for the IoT environment. By training complex models using IoT software gray-scale images and utilizing the gradient-weighted class-activated mapping technique, the system can identify key codes that influence model decisions. This allows for the reconstruction of gray-scale images to train a lightweight model called LMDNet for malware detection. Thus, the presented approach can address the challenges associated with malware detection and family classification in IoT devices.