Chatbot for education has great potential to complement human educators and education administrators. For example, it can be around the clock tutor to answer and clarify any questions from students who may have missed class. A chatbot can be implemented either by ruled based or artificial intel-ligence based. However, unlike the ruled-based chatbots, artificial intelli-gence based chatbots can learn and become smarter overtime and is more scalable and has become the popular choice for chatbot researchers recently. Recurrent Neural Network based Sequence-to-sequence (Seq2Seq) model is one of the most commonly researched model to implement artificial intelli-gence chatbot and has shown great progress since its introduction in 2014. However, it is still in infancy and has not been applied widely in educational chatbot development. Introduced originally for neural machine translation, the Seq2Seq model has been adapted for conversation modelling including question-answering chatbots. However, in-depth research and analysis of op-timal settings of the various components of Seq2Seq model for natural an-swer generation problem is very limited. Additionally, there has been no ex-periments and analysis conducted to understand how Seq2Seq model handles variations is questions posed to it to generate correct answers. Our experi-ments add to the empirical evaluations on Seq2Seq literature and provides insights to these questions. Additionally, we provide insights on how a cu-rated dataset can be developed and questions designed to train and test the performance of a Seq2Seq based question-answer model.

This systematic review and meta-analysis examines the effects of strength training (ST) and plyometric training (PT) on vertical jump (VJ), linear sprint (LS), and change-of-direction speed (CODS) in female adolescent team sport athletes. Additionally, it explores potential moderator variables, such as programming variables and participant characteristics, that may influence these training effects. Eligibility criteria: Randomized controlled trials examining the effects of ST or PT interventions lasting ≥4 weeks on VJ, LS, or CODS in female adolescent team sport athletes (aged 10-19 years) were included. A systematic search was conducted in PubMed, Web of Science, Cochrane, Embase, and SPORTDiscus from inception to August 28, 2024. The risk of bias of the included studies was assessed using the latest version of the Cochrane risk-of-bias tool for randomized trials (ROB-2). Meta-analyses were performed in Stata15.0 using random-effects models. Subgroup analyses were conducted based on the participant characteristics (age, height, weight, and type of sports) and programming variables (duration, frequency, and total sessions). Twenty-six studies involving 705 female adolescent team sport athletes were included. Meta-analyses revealed that ST and PT exhibited significant (p < 0.05) and moderate to large effects on VJ (ST, ES: 0.74, moderate; PT, ES: 0.87, moderate), LS (ST, ES: -1.26, large; PT, ES: -1.23, large), and CODS (ST, ES: -1.16, moderate; PT, ES: -1.20, moderate). Subgroup analysis indicated that for ST, training protocols of ≥ 10 weeks, ≤ 2 sessions/week, or ≤ 20 sessions were more effective. ST also showed greater benefits for athletes > 15 years old (LS), ≥ 163 cm (LS, CODS), ≥ 63 kg, and handball players. For PT, protocols of > 9 weeks, > 14 sessions (VJ), or ≥ 18 sessions (CODS) were more effective, with handball players responding best to PT. The overall risk of bias of the included studies was judged as moderate. The certainty of evidence was rated as moderate to high based on the GRADE approach. Both ST and PT are effective in improving VJ, LS, and CODS in female adolescent team sport athletes. Longer duration, lower frequency, or fewer sessions of ST produce better effects. Older and more mature athletes are better adapted to ST, likely due to increased muscle mass, hormonal factors, and neuromuscular adaptations. Longer duration or more sessions of PT produce better effects. Handball players showed a greater response to both ST and PT than athletes of other sports, according to observed trends.

With an increasing number of studies delving into the impact of dietary supplements on combat sports performance, researchers are actively seeking a more efficient dietary supplement for use in these sports. Nonetheless, controversies persist. Hence, we undertook a systematic review and Bayesian network meta-analysis to discern the most effective dietary supplements in combat sports by synthesizing the available evidence. We conducted a comprehensive search across PubMed, Web of Science, Cochrane, Embase, and SPORTDiscus, covering the period from their establishment to November 2, 2023. Our aim was to identify randomized controlled trials that evaluated the benefits of various dietary supplements for elite combat sports athletes. The risk of bias in these trials was assessed using the revised Cochrane Risk of Bias Tool for Randomized Trials. Subsequently, we employed Bayesian network meta-analysis through R software and Stata 15.0. During the analysis, we performed subgroup analysis based on the type of combat, distinguishing between striking and grappling disciplines. The analysis is based on 67 randomized controlled trials that meet all the inclusion criteria, involving 1026 elite combat sports athletes randomly assigned to 26 different dietary supplements or placebos. Results from the 50 trials included in the network meta-analysis indicate that compared to a placebo, sodium bicarbonate combined with caffeine (SMD: 2.3, 95% CrI: 1.5, 3.2), caffeine (SMD: 0.72, 95% CrI: 0.53, 0.93), beta-alanine (SMD: 0.58, 95% CrI: 0.079, 1.1), and sodium bicarbonate (SMD: 0.54, 95% CrI: 0.30, 0.81) was associated with a statistically significant increase in blood lactate concentrations. Compared to placebo, caffeine (SMD: 0.27, 95% CrI: 0.12, 0.41) was associated with a statistically significant increase in the final heart rate. Compared to placebo, creatine combined with sodium bicarbonate (SMD: 2.2, 95% CrI: 1.5, 3.1), creatine (SMD: 1.0, 95% CrI: 0.38, 1.6), and sodium bicarbonate (SMD: 0.42, 95% CrI: 0.18, 0.66) was associated with a statistically significant increase in mean power. Compared to placebo, creatine combined with sodium bicarbonate (SMD: 1.6, 95% CrI: 0.85, 2.3), creatine (SMD: 1.1, 95% CrI: 0.45, 1.7), and sodium bicarbonate (SMD: 0.35, 95% CrI: 0.11, 0.57) was associated with a statistically significant increase in peak power. Compared to placebo, caffeine (SMD: 1.4, 95% CrI: 0.19, 2.7) was associated with a statistically significant increase in the number of kicks. Compared to placebo, caffeine (SMD: 0.35, 95% CrI: 0.081, 0.61) was associated with a statistically significant increase in the number of throws. This study suggests that a range of dietary supplements, including caffeine, sodium bicarbonate, sodium bicarbonate combined with caffeine, creatine, creatine combined with sodium bicarbonate, and beta-alanine can improve the athletic performance of elite combat sports athletes.

As dietary supplements play a crucial role in meeting the unique nutritional needs of soccer players, a growing body of studies are exploring the effects of dietary supplements on athletic performance in soccer players. The effectiveness of certain supplements, such as caffeine and creatine, remains debated due to inconsistent results across studies. Therefore, this systematic review and Bayesian network meta-analysis was conducted to tentatively identify the most effective dietary supplements for soccer players. We searched PubMed, Web of Science, Cochrane, Embase, and SPORTDiscus from database establishment to 5 February 2024 to identify randomized controlled trials (RCTs) evaluating the effects of different dietary supplements on athletic performance in soccer players. The risk of bias was assessed using the revised Cochrane risk-of-bias tool for randomized trials. A Bayesian network meta-analysis was performed using the R software and Stata 18.0. A subgroup analysis was conducted based on the competitive level of the athletes. Eighty RCTs were included, with 1,425 soccer players randomly receiving 31 different dietary supplements or placebo. The network meta-analysis showed that compared with placebo, carbohydrate + protein (SMD: 2.2, very large), carbohydrate + electrolyte (SMD: 1.3, large), bovine colostrum (SMD: moderate) and caffeine (SMD: 0.29, small) were associated with a significant effect on increasing the distance covered. Kaempferia parviflora (SMD: 0.46, small) was associated with a significant effect on enhancing muscular strength. Beta-alanine (SMD: 0.83, moderate), melatonin (SMD: 0.75, moderate), caffeine (SMD: 0.37, small), and creatine (SMD: 0.33, small) were associated with a significant effect on enhancing jump height. Magnesium creatine chelate (SMD: -3.0, very large), melatonin (SMD: -1.9, large), creatine + sodium bicarbonate (SMD: -1.4, large), and arginine (SMD: -1.2, moderate) were associated with a significant effect on decreasing sprint time. Creatine + sodium bicarbonate (SMD: -2.3, very large) and caffeine (SMD: -0.38, small) were associated with a significant effect on improving agility. Sodium pyruvate (SMD: 0.50, small) was associated with a significant effect on increasing peak power. Magnesium creatine chelate (SMD: 1.3, large) and sodium pyruvate (SMD: 0.56, small) were associated with a significant effect on increasing mean power. Carbohydrate + electrolyte (SMD: -0.56, small) was associated with a significant effect on improving the rating of perceived exertion. This study suggests that a range of dietary supplements, including caffeine, creatine, creatine + sodium bicarbonate, magnesium creatine chelate, carbohydrate + electrolyte, carbohydrate + protein, arginine, beta-alanine, bovine colostrum, Kaempferia parviflora, melatonin, and sodium pyruvate, can improve athletic performance in soccer players. This review provides evidence-based guidance for soccer coaches and nutritionists on using dietary supplements to enhance specific performance measures.

Many teaching and learning tools incorporate current technologies for the learners to gain new knowledge thus increasing the efficiency of learning. Some of the technologies adopted in the mobile-based education systems are virtual reality, augmented reality, and mixed reality. In the Biology field, one of the problems faced by the learners is the difficulties in visualizing the human cell division process in the topic of mitosis and meiosis. Thus, many innovations which adopt these technologies are created to improve the understanding and interest of the learners. In this work, an interactive mobile learning application with virtual reality technology has been designed and developed to help learners visualize the human cell division process. The mobile application which is known as InCell VR also includes mini games which can help to test and improve the learners’ understanding. The InCell VR was developed using Unity, a game engine platform for developing high performance commercial game. The final evaluation assesses two parts: the learners’ knowledge gain after using the application and usability evaluation of the application. The usage of the proposed application was seen to give positive impact on the development of learners’ knowledge from the pre- and post-test testing sessions. The usability study showed that InCell VR application is useful, easy to be used and learnt, and give satisfactions to the users.

Many fruit recognition approaches today are designed to classify different type of fruits but there is little effort being done for content-based fruit recognition specifically focuses on durian species. Durian, known as the king of tropical fruits, have few similar characteristics between different species where the skin have almost the same colour from green to yellowish brown with just slightly different shape and pattern of thorns. Therefore, it is hard to differentiate them with the current methods. It would be valuable to have an automated content-based recognition framework that can automatically represent and recognise a durian species given a durian image as the input. Therefore, this work aims to contribute to a new representation method based on multiple features for effective durian recognition. Two features based on shape and texture is considered in this work. Simple shape signatures which include area, perimeter, and circularity are used to determine the shape of the fruit durian and its base while the texture of the fruit is constructed based on Local Binary Pattern. We extracted these features from 240 durian images and trained this proposed method using few classifiers. Based on 10-fold cross validation, it is found that Logistic Regression, Gaussian Naïve Bayesian, and Linear Discriminant Analysis classifiers performed equally well with 100% achievement of accuracy, precision, recall, and F1-score. We further tested the proposed algorithm on larger dataset which consisted of 42337 fruit images (64 various categories). Experimental results based on larger and more general dataset have shown that the proposed multiple features trained on Linear Discriminant Analysis classifier able to achieve 72.38% accuracy, 73% precision, 72% recall, and 72% F1-score.