Towards Innovative Research Approaches to Investigating the Role of Emotional Variables in Promoting Language Teachers’ and Learners’ Mental Health

The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process.Simply said,emotional factors play a key role in improving the quality of language teaching and learning.Furthermore,these emotional factors also promote the well-being of language teachers and learners and place them in a suitable mental condition.In view of the favorable impact of emotional factors on the mental health of language teachers and learners,many educational scholars around the world have studied these factors,their background,and their pedagogical consequences.Nonetheless,the majority of previous studies have employed traditional research methods in assessing these variables and their influences on language teachers’and learners’mental health.Because of the complex and dynamic quality of emotional factors,traditional research approaches often fail to evaluate these factors and their dynamic,non-linear connections with teachers’and learners’mental health and well-being.Accordingly,some novel research approaches are required to measure the dynamicity and complexity of emotional factors in language education settings.To address this call,the current state-of-the-art conceptual article seeks to provide new insights for investigating emotional factors and their potential impact on language teachers’and learners’mental states.This study also intends to offer a comprehensive list of emerging methods that take into account the complex and dynamic nature of emotional variables.Finally,the study outlines the potential implications of this review for educational researchers.

What are Different Research Approaches?Comprehensive Review of Qualitative,Quantitative,and Mixed Method Research,Their Applications,Types,and Limitations

There are different ways to examine and explain a study and its findings based on using numbers as a measure,a descriptive style,or a mixture of both.These three research approaches are quantitative,qualitative,and mixed methods that are commonly used by researchers in various research studies.However,with many options regarding the research design,it seems challenging for researchers to select the most appropriate approach based on the study and realize differences.This study provides a comprehensive review of qualitative,quantitative,and mixed-method research methods.Each method is clearly defined and specifically discussed based on applications,types,advantages,and limitations to help researchers identify select the most relevant type based on each study and navigate accordingly.

Research approaches to mass casualty incidents response：development from routine perspectives to complexity science

Objective To review the research methods of mass casualty incident （MCI） systematically and introduce the concept and characteristics of complexity science and artificial system,computational experiments and parallel execution （ACP） method.Data sources We searched PubMed,Web of Knowledge,China Wanfang and China Biology Medicine （CBM） databases for relevant studies.Searches were performed without year or language restrictions and used the combinations of the following key words：“mass casualty incident”,“MCI”,“research method”,“complexity science”,“ACP”,“approach”,“science”,“model”,“system” and “response”.Study selection Articles were searched using the above keywords and only those involving the research methods of mass casualty incident （MCI） were enrolled.Results Research methods of MCI have increased markedly over the past few decades.For now,dominating research methods of MCI are theory-based approach,empirical approach,evidence-based science,mathematical modeling and computer simulation,simulation experiment,experimental methods,scenario approach and complexity science.Conclusions This article provides an overview of the development of research methodology for MCI.The progresses of routine research approaches and complexity science are briefly presented in this paper.Furthermore,the authors conclude that the reductionism underlying the exact science is not suitable for MCI complex systems.And the only feasible alternative is complexity science.Finally,this summary is followed by a review that ACP method combining artificial systems,computational experiments and parallel execution provides a new idea to address researches for complex MCI.

EXPLORING THE VARIOUS APPROACHES OF A RESEARCH INSTITUTE'S ENTRY INTO THE MARKET

To meet the demands posed by the socialist market economy, to foster the close integration of science & technology with the national economy and thus to promote the development of the forces of production are targets pursued by the current drive of restructuring China’s existing S&T system.For this,the CAS Shenyang Branch has conducted rewarding exploration by diversifying various approaches when moving into the market.As a result,it is not only boosting its own development,but also increasing the strength of the local economy.

The ethics of exercise in eating disorders:Can an ethical principles approach guide the next generation of research and clinical practice?

1.Introduction Eating disorders(ED)are the most common psychiatric disorders afflicting young women^1 and contribute to great detriments in psychological,social,and physical health.^(2,3)Unfortunately,ED treatments tend to be long lasting,intensive,and expensive.~4Additionally,individuals with ED seeking treatment use healthcare services more frequently than non-ED individu-

AN^2 APPLICATION IN THE METRODS OF POPULATION GEOGRAPHY

This paper tries to present another theoretical view in the study of population geography by applying the principle of artificial neural network.It is our view that the approach to population geography study is of two kinds so far: the synthetic analysis and An2 synthetic analysis.

Transitioning from paternalism to empowerment of farmers in lowincome countries: Farming components to systems

Reasons for the initiation of farming systems/participatory approaches in non-Green Revolution（i.e., in more heterogeneous and less favourable production environments） areas in low-income countries is followed by a discussion of their evolution.Four phases are described along, with a brief description of some of the significant methods in which farmer participation has been sought, accessed and evaluated.They enabled/facilitated the evolutionary process.Although, over the last 40 years there has been a progress in making small-scale farmers much more visible in driving the agricultural research/development agenda through using the four basic stages embodied in the farming systems approach（i.e., descriptive, diagnosis, testing/evaluation and finally dissemination）, much still needs to be done.This leads on to a discussion as to some of the barriers still inhibiting true farmer empowerment and why further, such empowerment is imperative, if the agricultural challenges of this century are to be addressed successfully, namely substantially increasing agricultural productivity in an ecologically sustainable manner.Given the heterogeneity of the production environments and that many identified improvements are likely to be incremental rather than revolutionary in nature, this will require farmers＇ intimate involvement in their identification, evaluation and dissemination.Discussion in the paper recognizes that there is increasing globalization/commercialization of agriculture and is predicated on the need to consider the whole farmer-research-development continuum involving multiple stakeholders（i.e., farmers, scientists, extension workers, input/output service providers and policymakers）.Such a continuum has been explicitly recognized in the operational plans for the recently reformed international agricultural research（i.e., CGIAR） system.The paper concludes with a short discussion on the potential role of formal modelling.

Exploring noncoding variants in genetic diseases:from detection to functional insights

Previous studies on genetic diseases predominantly focused on protein-coding variations, overlooking the vast noncoding regions in the human genome. The development of high-throughput sequencing technologies and functional genomics tools has enabled the systematic identification of functional noncoding variants. These variants can impact gene expression, regulation, and chromatin conformation, thereby contributing to disease pathogenesis. Understanding the mechanisms that underlie the impact of noncoding variants on genetic diseases is indispensable for the development of precisely targeted therapies and the implementation of personalized medicine strategies. The intricacies of noncoding regions introduce a multitude of challenges and research opportunities. In this review, we introduce a spectrum of noncoding variants involved in genetic diseases, along with research strategies and advanced technologies for their precise identification and in-depth understanding of the complexity of the noncoding genome. We will delve into the research challenges and propose potential solutions for unraveling the genetic basis of rare and complex diseases.

Exploration of Approaches and Factors for Healthy City Planning

Planning and design for healthy cities has drawn increasingly extensive attention. On the one hand, urban environmental issues have become prominent, especially air pollution caused by industrialization in developing countries; on the other hand, urban residents' demand for physical and mental health calls for physical space to promote the quality of life. Based on theoretical and empirical researches, this paper explores significant environmental factors in healthy city planning and their correlation with public health in different approaches. The research discusses the correlations between planning factors and public health from four aspects including land use, spatial form, transportation modes, and green open space so as to reduce pollution and its impact on humans as well as how they encourage physical activity. It aims to provide basis for healthy city planning and its related studies.

Research on predicting prosodic parameters for Chinese synthesis by data mining approach

Prosodic control is an important part of speech synthesis system. Prosodic parameters choice right or wrong influences the quality of synthetic speech directly. At present, text to speech system has less effective describe to reflect data relationships in the corpus. A new research approach - data mining technology to discover those relationships by association rules modeling is presented. And a new algorithm for generating association rules of prosodic parameters including pitch parameters and duration parameters from corpus is developed. The output rules improve the correctness of syllable choice in text to speech system.