Artificial intelligent based teaching and learning approaches: A comprehensive review

The goal of this study is to investigate the potential effects that Artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study’s emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates

Carbon nanotube four-terminal devices for pressure sensing applications

Carbon nanotubes (CNTs) are of high interest for sensing applications,owing to their superior mechanical strength, high Young’s modulus and low density. In this work, we report on a facile approach for the fabrication of carbon nanotube devices using a four terminal configuration. Oriented carbon nanotube films were pulled out from a CNT forest wafer and then twisted into a yarn. Both the CNT film and yarn were arranged on elastomer membranes/diaphragms which were arranged on a laser cut acrylic frame to form pressure sensors. The sensors were calibrated using a precisely controlled pressure system, showing a large change of the output voltage of approximately 50 mV at a constant supply current of 100 μA and under a low applied pressure of 15 mbar. The results indicate the high potential of using CNT films and yarns for pressure sensing applications

Gender differences in climate change perception and adaptation strategies: A case study on three provinces in Vietnam’s Mekong River Delta

This brief summarizes the findings of a project output for the Policy Information and Response Platform on Climate Change and Rice in ASEAN and its Member Countries (PIRCCA), being implemented by the International Rice Research Institute (IRRI). The report focuses on the results of the survey conducted in the first half of 2015 on climate change perception and adaptation strategies of male and female farmers in three selected provinces across the Mekong River Delta (MRD) region in Vietnam: An Giang, Bac Lieu, and Tra Vihn. The survey gathered information on current climate change perceptions and adaptation strategies and gaps between the identified male and female respondents

Fracture behaviour assessment of high-performance fibre-reinforced concrete at high strain rates using interpretable modelling approaches

High-performance fibre-reinforced concrete (HPFRC), a type of cementitious composite material known for its exceptional mechanical performance, has widespread applications in structures exposed to severe dynamic loading conditions. However, understanding nonlinear HPFRC fracture behaviour, particularly under high strain rates, remains challenging given the complexities of assessment procedures and cost-intensive nature of experiments. This study presents an interpretable framework for modelling and analysing HPFRC fracture strength at high strain rates. A wide range of machine learning methods, including ensemble techniques, were employed to capture multivariate effects of eight essential input features (e.g., mortar compressive strength, fibre physical and mechanical properties, cross-sectional area, and strain rate) on fracture strength response. To assess the derived models, a novel evaluation procedure was proposed involving a data-based analysis, employing established metrics (i.e., coefficient of determination, root mean squared error, and mean absolute error via K-fold cross-validation) and a domain experts-involved evaluation utilising global sensitivity analysis to discern first-order and higher-order interactions among input factors. The proposed approach efficiently yielded both quantitative and qualitative insights into crucial input factors governing HPFRC fracture strength with limited experimental data. The obtained findings highlight the significance of multivariate effects, such as the interaction between strain rate and fibre tensile strength, and between fibre volume and fibre diameter, on fracture behaviour. The proposed interpretable framework aims to provide a powerful tool for proactive material failure analysis by understanding fracture behaviour and identifying potential weak and strong interactions among input factors of HPFRC-based samples. Moreover, the utilisation of the proposed approach enables researchers and civil engineers to efficiently focus on the most critical input parameters during the early design stage and ensuring the structural integrity and safety of HPFRC-based constructions

Deep auto-encoders with sequential learning for multimodal dimensional emotion recognition

Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a significant progress in this area. However, several questions still remain unanswered for most of existing approaches including: (i) how to simultaneously learn compact yet representative features from multimodal data, (ii) how to effectively capture complementary features from multimodal streams, and (iii) how to perform all the tasks in an end-to-end manner. To address these challenges, in this paper, we propose a novel deep neural network architecture consisting of a two-stream auto-encoder and a long short term memory for effectively integrating visual and audio signal streams for emotion recognition. To validate the robustness of our proposed architecture, we carry out extensive experiments on the multimodal emotion in the wild dataset: RECOLA. Experimental results show that the proposed method achieves state-of-the-art recognition performance

Factors associated with antenatal care adequacy in rural and urban contexts-results from two health and demographic surveillance sites in Vietnam

<p>Abstract</p> <p>Background</p> <p>Antenatal Care (ANC) is universally considered important for women and children. This study aims to identify factors, demographic, social and economic, possibly associated with three ANC indicators: number of visits, timing of visits and content of services. The aim is also to compare the patterns of association of such factors between one rural and one urban context in northern Vietnam.</p> <p>Methods</p> <p>Totally 2,132 pregnant women were followed from identification of pregnancy until birth in two Health and Demographic Surveillance Sites (HDSS). Information was obtained through quarterly face to face interviews.</p> <p>Results</p> <p>Living in the rural area was significantly associated with lower adequate use of ANC compared to living in the urban area, both regarding quantity (number and timing of visits) and content. Low education, living in poor households and exclusively using private sector ANC in both sites and self employment, becoming pregnant before 25 years of age and living in poor communities in the rural area turned out to increase the risk for overall inadequate ANC. High risk pregnancy could not be demonstrated to be associated with ANC adequacy in either site. The medical content of services offered was often inadequate, in relation to the national recommendations, especially in the private sector.</p> <p>Conclusion</p> <p>Low education, low economic status, exclusive use of private ANC and living in rural areas were main factors associated with risk for overall inadequate ANC use as related to the national recommendations. Therefore, interventions focussing on poor and less educated women, especially in rural areas should be prioritized. They should focus the importance of early attendance of ANC and sufficient use of core services. Financial support for poor and near poor women should be considered. Providers of ANC should be educated and otherwise influenced to provide sufficient core services. Adherence to ANC content guidelines must be improved through enhanced supervision, particularly in the private sector.</p

Is this pill an antibiotic or a painkiller? Improving the identification of oral antibiotics for better use

In this Viewpoint, we discuss how the identification of oral antibiotics and their distinction from other commonly used medicines can be challenging for consumers, suppliers, and health-care professionals. There is a large variation in the names that people use to refer to antibiotics and these often relate to their physical appearance, although antibiotics come in many different physical presentations. We also reflect on how the physical appearance of medicine influences health care and public health by affecting communication between patients and health-care professionals, dispensing , medicine use, and the public understanding of health campaigns. Furthermore, we report expert and stakeholder consultations on improving the identification of oral antibiotics and discuss next steps towards a new identification system for antibiotics. We propose to use the physical appearance as a tool to support and nudge awareness about antibiotics and their responsible use

Conceptualizing pathways linking women's empowerment and prematurity in developing countries.

BackgroundGlobally, prematurity is the leading cause of death in children under the age of 5. Many efforts have focused on clinical approaches to improve the survival of premature babies. There is a need, however, to explore psychosocial, sociocultural, economic, and other factors as potential mechanisms to reduce the burden of prematurity. Women's empowerment may be a catalyst for moving the needle in this direction. The goal of this paper is to examine links between women's empowerment and prematurity in developing settings. We propose a conceptual model that shows pathways by which women's empowerment can affect prematurity and review and summarize the literature supporting the relationships we posit. We also suggest future directions for research on women's empowerment and prematurity.MethodsThe key words we used for empowerment in the search were "empowerment," "women's status," "autonomy," and "decision-making," and for prematurity we used "preterm," "premature," and "prematurity." We did not use date, language, and regional restrictions. The search was done in PubMed, Population Information Online (POPLINE), and Web of Science. We selected intervening factors-factors that could potentially mediate the relationship between empowerment and prematurity-based on reviews of the risk factors and interventions to address prematurity and the determinants of those factors.ResultsThere is limited evidence supporting a direct link between women's empowerment and prematurity. However, there is evidence linking several dimensions of empowerment to factors known to be associated with prematurity and outcomes for premature babies. Our review of the literature shows that women's empowerment may reduce prematurity by (1) preventing early marriage and promoting family planning, which will delay age at first pregnancy and increase interpregnancy intervals; (2) improving women's nutritional status; (3) reducing domestic violence and other stressors to improve psychological health; and (4) improving access to and receipt of recommended health services during pregnancy and delivery to help prevent prematurity and improve survival of premature babies.ConclusionsWomen's empowerment is an important distal factor that affects prematurity through several intervening factors. Improving women's empowerment will help prevent prematurity and improve survival of preterm babies. Research to empirically show the links between women's empowerment and prematurity is however needed