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With the increasing number of COVID-19 cases and related deaths worldwide, we decided to share the development of this condition in Singapore and Malaysia. First few cases were diagnosed in the two countries at the end of January 2020, and the numbers have surged to thousands by end of March 2020. We will focus on strategies adopted by the government and also the Orthopaedic community of the two countries up till the beginning of April 2020. We hope that by sharing of relevant information and knowledge on how we are managing the COVID-19 condition, we can help other communities, and health care workers to more effectively overcome this pandemic.

This paper investigates the influence of different combinations of second-order (β2), fourth-order (β4) and sixth-order (β6) dispersion coefficient signs (negativity/positivity) to the fiber optical parametric amplifier gain performance. The numerical simulation has exploited the fourth-order Runge-Kutta method to solve the coupled amplitude equations which basically represent the parametric process of four-wave mixing. In the normal regime at which β2 is positive, the fiber optical parametric amplifier exhibits a poor gain spectrum and it is well performed once the pump is presumed to be in anomalous regime i.e. β2 is negative. The effect of β4 is significant when the signal wavelength is further from the pump wavelength and a wide amplification bandwidth is produced when the fiber have positive β4 in the anomalous regime. As for β6, unfortunately in this simulation its influences are hardly can be seen probably because of its small value regardless its sign, but, from phase-mismatch equation it is shown that its impact is prominent when the signal is positioned way far from the pump. All in all, this shown that the signs combination of the higher-order dispersion coefficients are significant in order to optimize the FOPA amplification bandwidth.

The application of turmeric powder as a natural product-based material for removing Hg2+ from water was demonstrated. In this study, carbon disulfide-modified turmeric (MT) was synthesized and incorporated into silica gel to create a selective sorbent (SiO2-MT). Infrared spectroscopy and energy-dispersive X-ray spectroscopy confirmed that MT was successfully incorporated into the silica gel matrix. Morphological studies revealed that SiO2-MT was porous with a pore size of 1.87 nm. SiO2-MT exhibited selectivity for the adsorption of Hg2+. The overall performance of SiO2-MT in adsorbing Hg2+ significantly improved with increasing SiO2-MT dosage, ranging from 5 to 20 mg. After reaching a dosage of 20 mg of SiO2-MT, no further significant improvement was observed. The optimal pH for Hg2+ removal ranged from four to five, with approximately 90% Hg2+ removal, and the adsorption process reached equilibrium at 180 min. The adsorption data were well-fitted to the Langmuir isotherm and pseudo-second-order kinetics models, indicating that SiO2-MT adsorbed Hg2+ through monolayer adsorption and chemisorption. The maximum adsorption capacity of the synthesized SiO2-MT was 37.6 mg g−1, which is higher than that of other reported biomasses, including bamboo leaves and garlic powder. In conclusion, this study demonstrates the potential use of turmeric powder, a natural product, for effective Hg2+ removal during water treatment. [ABSTRACT FROM AUTHOR]

Rubber producers, consumers, traders, and those who are involved in the rubber industry face major risks of rubber price fluctuations. As a result, decision-makers are required to make an accurate estimation of the price of rubber. This paper aims to propose hybrid intelligent models, which can be utilized to forecast the price of rubber in Malaysia by employing monthly Malaysia's rubber pricing data, spanning from January 2016 to March 2021. The projected hybrid model consists of different algorithms with the symbolic Radial Basis Functions Neural Network k-Satisfiability Logic Mining (RBFNN-kSAT). These algorithms, including GreyWolf Optimization Algorithm, Artificial Bee Colony Algorithm, and Particle Swarm Optimization Algorithm were utilized in the forecasting data analysis. Several factors, which affect the monthly price of rubber, such as rubber production, total exports of rubber, total imports of rubber, stocks of rubber, currency exchange rate, and crude oil prices were also considered in the analysis. To evaluate the results of the introduced model, a comparison has been conducted for each model to identify the most optimum model for forecasting the price of rubber. The findings showed that GWO with RBFNN-kSAT represents the most accurate and efficient model compared with ABC with RBFNNkSAT and PSO with RBFNN-kSAT in forecasting the price of rubber. The GWOwithRBFNN-kSAT obtained the greatest average accuracy (92%), with a better correlation coefficient R = 0.983871 than ABC with RBFNN-kSAT and PSO with RBFNN-kSAT. Furthermore, the empirical results of this study provided several directions for policymakers to make the right decision in terms of devising proper measures in the industry to address frequent price changes so that the Malaysian rubber industry maintains dominance in the international markets. [ABSTRACT FROM AUTHOR]

Opportunities to improve skills and opportunities to teach or train others may be associated with job satisfaction, work engagement and organizational commitment. The analysis reported in this paper used a subsample of 823 employees within two Japanese and three American worksites. We tested not only the direct relationships of each type of training opportunity (to improve skills and to teach or train others) with each of three outcomes (job satisfaction, work engagement and organizational commitment) but also the potential moderating roles of performance orientation, job security and age. The relationships were assessed separately for Japanese and American respondents. The results highlight the importance of opportunities to improve skills for all three outcomes and of opportunities to teach and train for job satisfaction and work engagement. Performance orientation, job security and age generally were not significant moderators and, when they were, the effects were typically restricted to one country. The consistently positive coefficients for training opportunities should provide insight for cross-national organizations seeking to identify human resource policies effective across varying cultural, economic and demographic contexts.