There has been substantial research on megaprojects in project management literature. However, there is dearth of studies empirically investigating performance of new launched megaproject of Thailand that named as "Phuket sandbox". The core purpose of this project is to normalize covid-19 situation and resuming tourism in Thailand. Therefore, the evaluation of project performance is essential to achieve the targeted goal for success. The purpose of this study is to investigate the factors that affect project performance (Phuket sandbox) in Thailand. This study used quantitative approach based on structured questionnaire and the data was collected from Phuket, Thailand. The survey conducted from team members which are tourism stake holders' team, immigration team and public service teams including hospitals and hotels who were supposed for the management of Phuket tourism sandbox operations. The study got 222 valid responses only as the members were so busy and partial lockdowns in Thailand hindered the data collection process. The proposed hypothetical model tested by partial least square structural equation modelling. The results of the study found mix findings. The independent variables are team knowledge management, interpersonal conflict, organizational trust, and as significant and dependent variable as project performance through the mediation of psychological capital. The all relationships found to be significant except problem solving competence which have insignificant relationship with project performance as well as problem solving competence and organizational trust have insignificant relation with psychological capital.
M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.
Two new xanthones, characterized as 4-(1,1-dimethylprop-2-enyl)-1,3,5,8-tetrahydroxyxanthone (1) and penangianaxanthone (2), with three known xanthones, cudratricusxanthone H (3), macluraxanthone C (4) and gerontoxanthone C (5), as well as friedelin and stigmasterol were isolated from the leaves of Garcinia penangiana. Their structures were elucidated by analysis of spectroscopic data and comparison of the NMR data with the literature ones. Significant cytotoxicity against DU-145, MCF-7 and NCI-H460 cancer cell lines was demonstrated by compounds 1-5, with IC50 values ranging from 3.5 to 72.8 microM.
In order to invent a porcine gelatine detection device using microbial resources, bacterial enzymes with a preference towards porcine gelatine and their candidate genes were evaluated. Five (n = 5) bacterial strains isolated from hot spring water and wet clay, Malaysia were screened for their gelatinase activity. The gelatinase enzyme was extracted and purified using ammonium sulphate precipitation prior to performing gelatinase assay on porcine, bovine and fish gelatine medium substrates. The G2 strain or Enterobacter aerogenes (Strain EA1) was selected for whole genome sequenced after showing a consistent trend of preference towards porcine gelatine. The gelatinase candidate gene gelEA1_9 was cloned and expressed. Based on one-way analysis of variance (ANOVA) with POST-HOC Duncan test (α = 0.05), the final product of gelEA1_9 was identified as a novel gelatinase. This gelatinase presented no significant difference in activity towards porcine gelatine. Hence, the present study demonstrated an enzyme-substrate interaction for porcine gelatine identification.
Carboxylic acid reductases (CARs) are attracting burgeoning attention as biocatalysts for organic synthesis of aldehydes and their follow-up products from economic carboxylic acid precursors. The CAR enzyme class as a whole, however, is still poorly understood. To date, relatively few CAR sequences have been reported, especially from fungal sources. Here, we sought to increase the diversity of the CAR enzyme class. Six new CAR sequences from the white-rot fungus Pycnoporus cinnabarinus were identified from genome-wide mining. Genome and gene clustering analysis suggests that these PcCAR enzymes play different natural roles in Basidiomycete systems, compared to their type II Ascomycete counterparts. The cDNA sequences of all six Pccar genes were deduced and analysis of their corresponding amino acid sequence showed that they encode for proteins of similar properties that possess a conserved modular functional tri-domain arrangement. Phylogenetic analyses showed that all PcCAR enzymes cluster together with the other type IV CARs. One candidate, PcCAR4, was cloned and over-expressed recombinantly in Escherichia coli. Subsequent biotransformation-based screening with a panel of structurally-diverse carboxylic acid substrates suggest that PcCAR4 possessed a more pronounced substrate specificity compared to previously reported CARs, preferring to reduce sterically-rigid carboxylic acids such as benzoic acid. These findings thus present a new functionally-distinct member of the CAR enzyme class.