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Curcuma mangga and Bosenbergia rotunda which belongs to Zingiberaceae family are largely distributed in South East Asian countries including Malaysia. These plants have been traditionally used for treatment of various diseases. In this research we focused on determining the antioxidant and cytotoxic activity of C. mangga and B. rotunda ethanolic extracts. Initially, in this study, ethanolic extracts from rhizomes of C. mangga and B. rotunda were obtained through Soxhlet extraction method. 12.6% and 3.5% of crude extract were obtained from C. mangga and B. rotunda respectively. For MTT assay, the IC50 values are 207µg/ml and 31.96µg/ml for C. mangga and B. rotunda respectively. Meanwhile for the antioxidant activity using DPPH assay, C. mangga showed higher antioxidant activity with IC50 values of 1073µg/ml compared to B. rotunda with IC50 values of 578µg/ml. It can be concluded both extracts showed low inhibitory effect on MCF-7 cancer cells growth and DPPH free radical activity.

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Chatbots simulate human conversations through computer programs using natural language. They are developed for a variety of reasons and purposes, as virtual characters and animators or as an interactive game component. Today, Chatbots for education are widely used to allow students to engage with learning content on an ongoing basis. In this study, students use the Chatbot to query web programming learning content such as code description, coding and problem-solving. However, the Chatbot's successful responses to students' questions are unknown. The teachers also do not know the desired learning content of the students using the Chatbot. Thus, the objectives of this study are to explore the likelihood of a student getting successful responses in each conversation and to identify the learning content desired by the students. The learning analytics method is used to analyze the learning data from the Chatbot. The data analysis performed is descriptive analysis and binomial probability test. The results of the studies showed that the value of successful responses of the Chatbot is high. The learning content most desired by the students is related to three categories of web programming content, namely hypertext preprocessor (PHP), database and structured query language (SQL) and hypertext markup language (HTML). The Chatbot is updated based on the proposed actions to provide more efficient responses. [ABSTRACT FROM AUTHOR]

Background: Advanced cardiac life support provides healthcare professionals with knowledge and skills needed in dealing with cardiac emergencies. By incorporating e-learning in advanced cardiac life support courses, it allows for easier accessibility of learning materials and a more personalized learning schedule at a lower overall cost. Objectives: This study aims to compare the outcome of e-learning advanced cardiac life support versus conventional advanced cardiac life support among healthcare professionals and determine their attitude on e-learning. Methods: A total of 96 candidates attending advanced cardiac life support courses in Hospital Universiti Sains Malaysia between January 2016 and May 2017 were included in the study. In total, 48 candidates were enrolled on each arm. Candidates in conventional advanced cardiac life support undertook a 2-day face-to-face course. Participants in e-learning advanced cardiac life support completed 6 h of online lecture videos prior to 1-day modified face-to-face course. All candidates were assessed by pre- and post-course multiple-choice questions and practical cardiac arrest simulation test. Only post-course and cardiac arrest simulation test marks contribute to the passing or failure of the candidates. Results: Candidates in e-learning advanced cardiac life support courses had higher mean scores on the pre-course multiple-choice questions (69.1, SD: 19.1) compared to those in conventional advanced cardiac life support courses (58.6, SD: 16.6, p < 0.001). The cardiac arrest simulation test pass rate on e-learning advanced cardiac life support was higher than conventional advanced cardiac life support courses although statistically not significant (95.8% vs 87.5%; p = 0.134). The overall pass rate was 93.8% for e-learning advanced cardiac life support versus 83.3% in conventional advanced cardiac life support (p = 0.099). A majority of the candidates had positive attitude towards e-learning. Conclusion: E-learning advanced cardiac life support courses demonstrated better results in terms of knowledge compared to conventional advanced cardiac life support, with equivalent skill scores. Shorter course duration, lesser cost and participants' satisfaction were the added benefits. Further study can be done to explore the utilization of e-learning materials among healthcare professionals and its other advantages. [ABSTRACT FROM AUTHOR]

Sedimentation problem and water quality deterioration are the occurrences happened along the river basin especially at main river basin in Malaysia. The main objective of this study to review the sedimentation problems and water quality deterioration level in the Lata Sungai Limau, Terengganu, Malaysia. 11 sampling stations were chosen from upstream until downstream. There are four mains contributed in this study such as water quality parameters, distribution of sediment grain size, concentration of total suspended solids (TSS) and river discharge (Q) respectively. From leave-one-out method showed chemical oxygen demand and TSS are the most importance water quality variables with river discharge (Q). The formation of sediment load per day falls between 53.540 kg/d (Station 2) and 1,164.394 kg/d (Station 5) for all sampling stations contributed. The result showed the sizes of sediment recorded phi –0.011 and phi 0.768 with very rough particle sizes which are between phi 1.00 and phi 0.00. All parties involved need to take responsibility and be more aware to environmental deterioration and awareness. This research conducted to enlighten the public about the importance of the environment, especially river basins. [ABSTRACT FROM AUTHOR]

As a light structure, composite sandwich panels are distinguished by their significant bending stiffness that is rapidly used in the manufacture of aircraft bodies. This study focuses on the mechanical behaviour of through-thickness polymer, pin-reinforced foam core sandwich panels subjected to indentation and low impact loading. Experimental and computational approaches are used to study the global and internal behaviour of the sandwich panel. The samples for experimental testing were made from glass/polyester laminates as the face sheets and polyurethane foam as the foam core. To further reinforce the samples against bending, different sizes of polymeric pins were implemented on the sandwich panels. The sandwich panel was fabricated using the vacuum infusion process. Using the experimental data, a finite element model of the sample was generated in LS-DYNA software, and the effect of pin size and loading rate were examined. Results of the simulation were validated through a proper prediction compared to the test data. The results of the study show that using polymeric pins, the flexural strength of the panel significantly increased under impact loading. In addition, the impact resistance of the pin-reinforced foam core panel increased up to 20%. Moreover, the size of pins has a significant influence on the flexural behaviour while the sample was under a moderate strain rate. To design an optimum pin-reinforced sandwich panel a "design of experiment model" was generated to predict energy absorption and the maximum peak load of proposed sandwich panels. The best design of the panel is recommended with 1.8 mm face sheet thickness and 5 mm pins diameter. [ABSTRACT FROM AUTHOR]

Background: COVID-19 outbreak is being studied throughout the world. Adding more analysis to date strengthening the information about the illness. Here, we analysis the data of Malaysian Ministry of Health from February 15, 2020 until January 10, 2021 was analysed using linear regression model statistical analysis with aim to forecast the trend. Materials and Methods: This study reviewed the data by Malaysia Ministry of Health from February 15, 2020, until January 10, 2021. Linear regression model statistical analysis was used for predictive modelling. The forecasting of the linear trend of the Covid-19 outbreak prediction is purposed to estimate the number of confirm cases according to the number of recoveries patients. Results: Malaysia is currently anticipating another lockdown restriction as new confirmed case of COVID-19 hit new record high. The cumulative confirmed Covid-19 cases in MCO predicted a sharp increase. At the first of March, 2021, the predicted cumulative confirmed Covid-19 cases are 319,477 cases. Conclusions: Covid-19 cases projected to 315766 by end of February 2021 with 3000-4000 daily cases predicted. Initiative and proactive measurement by Malaysian government hopefully can reduce the number of cases and flatten the infection curve. [ABSTRACT FROM AUTHOR]