Displaying publications 81 - 100 of 2380 in total

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  1. Bahari NI, Sutan R, Abdullah Mahdy Z
    PLoS One, 2024;19(2):e0297563.
    PMID: 38394134 DOI: 10.1371/journal.pone.0297563
    INTRODUCTION: The COVID-19 pandemic has exerted devastating effects on healthcare delivery systems, specifically those for pregnant women. The aim of this review was to determine the maternal perception of antenatal health care services during the COVID-19 pandemic critical phase.

    METHODS: Scopus, Web of Science, SAGE, and Ovid were systematically searched using the keywords "maternal", "COVID-19 pandemic", "maternal health service", and "maternal perception". Articles were eligible for inclusion if they were original articles, written in English, and published between January 1, 2020, and December 12, 2022. This review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligible articles were assessed using the Mixed Methods Appraisal Tool. Thematic analysis was used for data synthesis.

    RESULTS: Of 2683 articles identified, 13 fulfilled the inclusion criteria and were included in the narrative synthesis. Five themes emerged regarding the determinants of maternal perception of antenatal healthcare services during the COVID-19 pandemic critical phase: lack of psychosocial support, poor maternal healthcare quality, poor opinion of virtual consultation, health structure adaptation failure to meet women's needs, and satisfaction with maternal health services.

    CONCLUSION: Maternal perception, specifically pregnant women's psychosocial and maternal health needs, should be focused on the continuation of maternal care during the COVID-19 pandemic. It is critical to identify the maternal perception of maternal health services during the pandemic to ensure health service equity in the "new normal" future.

  2. Hatah E, Rahim N, Makmor-Bakry M, Mohamed Shah N, Mohamad N, Ahmad M, et al.
    PLoS One, 2020;15(11):e0241909.
    PMID: 33157549 DOI: 10.1371/journal.pone.0241909
    Medication non-adherence remains a significant barrier in achieving better health outcomes for patients with chronic diseases. Previous self-reported medication adherence tools were not developed in the context of the Malaysia population. The most commonly used tool, MMAS-8, is no longer economical because it requires a license and currently every form used is charged. Hence, there is a need to develop and validate a new medication adherence tool. The Malaysia Medication Adherence Assessment Tool (MyMAAT) was developed by a multidisciplinary team with expertise in medication adherence and health literacy. The face and content validities of the MyMAAT was established by a panel of experts. A total of 495 patients with type 2 diabetes were recruited from the Ministry of Health facilities consisting of five hospitals and five primary health clinics. A test-retest was conducted on 42 of the patients one week following their first data collection. Exploratory factor analysis was performed to evaluate the validity of the MyMAAT. The final item for MyMAAT was compared with SEAMS, HbA1c%, Medication Possession ratio (MPR) score, and pharmacist's subjective assessment for its hypothesis testing validity. The MyMAAT-12 achieved acceptable internal consistency (Cronbach's alpha = 0.910) and stable reliability as the test-retest score showed good to excellent correlation (Spearman's rho = 0.96, p = 0.001). The MyMAAT has significant moderate association with SEAMS (Spearman's rho = 0.44, p = < 0.001) and significant relationship with HbA1c (< 8% and ≥ 8%) (χ2(1) = 13.4, p < 0.001), MPR (χ2(1) = 13.6, p < 0.001) and pharmacist's subjective assessment categories (χ2(1) = 31, p < 0.001). The sensitivity of MyMAAT-12, tested against HbA1c% was 72.9% while its specificity was 43%. This study demonstrates that the MyMAAT-12 together with other methods of assessment may make a better screening tool to identify patients who were non-adherence to their medications.
  3. Hazim M, Anuar NB, Ab Razak MF, Abdullah NA
    PLoS One, 2018;13(6):e0198884.
    PMID: 29889897 DOI: 10.1371/journal.pone.0198884
    Product reviews are the individual's opinions, judgement or belief about a certain product or service provided by certain companies. Such reviews serve as guides for these companies to plan and monitor their business ventures in terms of increasing productivity or enhancing their product/service qualities. Product reviews can also increase business profits by convincing future customers about the products which they have interest in. In the mobile application marketplace such as Google Playstore, reviews and star ratings are used as indicators of the application quality. However, among all these reviews, hereby also known as opinions, spams also exist, to disrupt the online business balance. Previous studies used the time series and neural network approach (which require a lot of computational power) to detect these opinion spams. However, the detection performance can be restricted in terms of accuracy because the approach focusses on basic, discrete and document level features only thereby, projecting little statistical relationships. Aiming to improve the detection of opinion spams in mobile application marketplace, this study proposes using statistical based features that are modelled through the supervised boosting approach such as the Extreme Gradient Boost (XGBoost) and the Generalized Boosted Regression Model (GBM) to evaluate two multilingual datasets (i.e. English and Malay language). From the evaluation done, it was found that the XGBoost is most suitable for detecting opinion spams in the English dataset while the GBM Gaussian is most suitable for the Malay dataset. The comparative analysis also indicates that the implementation of the proposed statistical based features had achieved a detection accuracy rate of 87.43 per cent on the English dataset and 86.13 per cent on the Malay dataset.
  4. Khalilpourfarshbafi M, Devi Murugan D, Abdul Sattar MZ, Sucedaram Y, Abdullah NA
    PLoS One, 2019;14(6):e0218792.
    PMID: 31226166 DOI: 10.1371/journal.pone.0218792
    The increased prevalence of obesity and associated insulin resistance calls for effective therapeutic treatment of metabolic diseases. The current PPARγ-targeting antidiabetic drugs have undesirable side effects. The present study investigated the anti-diabetic and anti-obesity effects of withaferin A (WFA) in diet-induced obese (DIO) C57BL/6J mice and also the anti-adipogenic effect of WFA in differentiating 3T3- F442A cells. DIO mice were treated with WFA (6 mg/kg) or rosiglitazone (10 mg/kg) for 8 weeks. At the end of the treatment period, metabolic profile, liver function and inflammatory parameters were obtained. Expression of selective genes controlling insulin signaling, inflammation, adipogenesis, energy expenditure and PPARγ phosphorylation-regulated genes in epididymal fats were analyzed. Furthermore, the anti-adipogenic effect of WFA was evaluated in 3T3- F442A cell line. WFA treatment prevented weight gain without affecting food or caloric intake in DIO mice. WFA-treated group also exhibited lower epididymal and mesenteric fat pad mass, an improvement in lipid profile and hepatic steatosis and a reduction in serum inflammatory cytokines. Insulin resistance was reduced as shown by an improvement in glucose and insulin tolerance and serum adiponectin. WFA treatment upregulated selective insulin signaling (insr, irs1, slc2a4 and pi3k) and PPARγ phosphorylation-regulated (car3, selenbp1, aplp2, txnip, and adipoq) genes, downregulated inflammatory (tnf-α and il-6) genes and altered energy expenditure controlling (tph2 and adrb3) genes. In 3T3- F442A cell line, withaferin A inhibited adipogenesis as indicated by a decrease in lipid accumulation in differentiating adipocytes and protein expression of PPARγ and C/EBPα. The effect of rosiglitazone on physiological and lipid profiles, insulin resistance, some genes expression and differentiating adipocytes were markedly different. Our data suggest that WFA is a promising therapeutic agent for both diabetes and obesity.
  5. Mohd Abd Razak MR, Sastu UR, Norahmad NA, Abdul-Karim A, Muhammad A, Muniandy PK, et al.
    PLoS One, 2016;11(3):e0152415.
    PMID: 27023787 DOI: 10.1371/journal.pone.0152415
    Malaysia has a national goal to eliminate malaria by 2020. Understanding the genetic diversity of malaria parasites in residual transmission foci can provide invaluable information which may inform the intervention strategies used to reach elimination targets. This study was conducted to determine the genetic diversity level of P. falciparum isolates in malaria residual foci areas of Sabah. Malaria active case detection was conducted in Kalabakan and Kota Marudu. All individuals in the study sites were screened for malaria infection by rapid diagnostic test. Blood from P. falciparum-infected individuals were collected on filter paper prior to DNA extraction. Genotyping was performed using merozoite surface protein-1 (MSP-1), merozoite surface protein-2 (MSP-2), glutamate rich protein (GLURP) and 10 neutral microsatellite loci markers. The size of alleles, multiplicity of infection (MOI), mean number of alleles (Na), expected heterozygosity (He), linkage disequilibrium (LD) and genetic differentiation (FST) were determined. In Kalabakan, the MSP-1 and MSP-2 alleles were predominantly K1 and FC27 family types, respectively. The GLURP genotype VI (751-800 bp) was predominant. The MOI for MSP-1 and MSP-2 were 1.65 and 1.20, respectively. The Na per microsatellite locus was 1.70. The He values for MSP-1, MSP-2, GLURP and neutral microsatellites were 0.17, 0.37, 0.70 and 0.33, respectively. In Kota Marudu, the MSP-1 and MSP-2 alleles were predominantly MAD20 and 3D7 family types, respectively. The GLURP genotype IV (651-700 bp) was predominant. The MOI for both MSP-1 and MSP-2 was 1.05. The Na per microsatellite locus was 3.60. The He values for MSP-1, MSP-2, GLURP and neutral microsatellites were 0.24, 0.25, 0.69 and 0.30, respectively. A significant LD was observed in Kalabakan (0.495, p<0.01) and Kota Marudu P. falciparum populations (0.601, p<0.01). High genetic differentiation between Kalabakan and Kota Marudu P. falciparum populations was observed (FST = 0.532). The genetic data from the present study highlighted the limited diversity and contrasting genetic pattern of P. falciparum populations in the malaria declining areas of Sabah.
  6. Jawarneh S, Abdullah S
    PLoS One, 2015;10(7):e0130224.
    PMID: 26132158 DOI: 10.1371/journal.pone.0130224
    This paper presents a bee colony optimisation (BCO) algorithm to tackle the vehicle routing problem with time window (VRPTW). The VRPTW involves recovering an ideal set of routes for a fleet of vehicles serving a defined number of customers. The BCO algorithm is a population-based algorithm that mimics the social communication patterns of honeybees in solving problems. The performance of the BCO algorithm is dependent on its parameters, so the online (self-adaptive) parameter tuning strategy is used to improve its effectiveness and robustness. Compared with the basic BCO, the adaptive BCO performs better. Diversification is crucial to the performance of the population-based algorithm, but the initial population in the BCO algorithm is generated using a greedy heuristic, which has insufficient diversification. Therefore the ways in which the sequential insertion heuristic (SIH) for the initial population drives the population toward improved solutions are examined. Experimental comparisons indicate that the proposed adaptive BCO-SIH algorithm works well across all instances and is able to obtain 11 best results in comparison with the best-known results in the literature when tested on Solomon's 56 VRPTW 100 customer instances. Also, a statistical test shows that there is a significant difference between the results.
  7. Jaddi NS, Abdullah S
    PLoS One, 2019;14(1):e0208308.
    PMID: 30608936 DOI: 10.1371/journal.pone.0208308
    Optimization of an artificial neural network model through the use of optimization algorithms is the common method employed to search for an optimum solution for a broad variety of real-world problems. One such optimization algorithm is the kidney-inspired algorithm (KA) which has recently been proposed in the literature. The algorithm mimics the four processes performed by the kidneys: filtration, reabsorption, secretion, and excretion. However, a human with reduced kidney function needs to undergo additional treatment to improve kidney performance. In the medical field, the glomerular filtration rate (GFR) test is used to check the health of kidneys. The test estimates the amount of blood that passes through the glomeruli each minute. In this paper, we mimic this kidney function test and the GFR result is used to select a suitable step to add to the basic KA process. This novel imitation is designed for both minimization and maximization problems. In the proposed method, depends on GFR test result which is less than 15 or falls between 15 and 60 or is more than 60 a particular action is performed. These additional processes are applied as required with the aim of improving exploration of the search space and increasing the likelihood of the KA finding the optimum solution. The proposed method is tested on test functions and its results are compared with those of the basic KA. Its performance on benchmark classification and time series prediction problems is also examined and compared with that of other available methods in the literature. In addition, the proposed method is applied to a real-world water quality prediction problem. The statistical analysis of all these applications showed that the proposed method had a ability to improve the optimization outcome.
  8. Habib O, Mohd Sakri R, Ghazalli N, Chau DM, Ling KH, Abdullah S
    PLoS One, 2020;15(12):e0244386.
    PMID: 33347482 DOI: 10.1371/journal.pone.0244386
    CpG-free pDNA was reported to facilitate sustained transgene expression with minimal inflammation in vivo as compared to CpG-containing pDNA. However, the expression potential and impact of CpG-free pDNA in in vitro model have never been described. Hence, in this study, we analyzed the transgene expression profiles of CpG-free pDNA in vitro to determine the influence of CpG depletion from the transgene. We found that in contrast to the published in vivo studies, CpG-free pDNA expressed a significantly lower level of luciferase than CpG-rich pDNA in several human cell lines. By comparing novel CpG-free pDNA carrying CpG-free GFP (pZGFP: 0 CpG) to CpG-rich GFP (pRGFP: 60 CpGs), we further showed that the discrepancy was not influenced by external factors such as gene transfer agent, cell species, cell type, and cytotoxicity. Moreover, pZGFP exhibited reduced expression despite having equal gene dosage as pRGFP. Analysis of mRNA distribution revealed that the mRNA export of pZGFP and pRGFP was similar; however, the steady state mRNA level of pZGFP was significantly lower. Upon further investigation, we found that the CpG-free transgene in non-integrating CpG-free pDNA backbone acquired increased nucleosome enrichment as compared with CpG-rich transgene, which may explain the observed reduced level of steady state mRNA. Our findings suggest that nucleosome enrichment could regulate non-integrating CpG-free pDNA expression and has implications on pDNA design.
  9. Suresh Y, Azil AH, Abdullah SR
    PLoS One, 2024;19(1):e0295961.
    PMID: 38252615 DOI: 10.1371/journal.pone.0295961
    In some laboratories, mosquitoes' direct blood-feeding on live animals has been replaced with various membrane blood-feeding systems. The selection of blood meal sources used in membrane feeding is crucial in vector mass rearing as it influences the mosquitoes' development and reproductive fitness. Therefore, this scoping review aimed to evaluate the existing literature on the use of different blood sources and components in artificial membrane feeding systems and their effects on blood-feeding and the fecundity rate of Ae. aegypti. A literature review search was conducted by using PubMed, Scopus, and Web of Science databases according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-ScR). The EndNote version 20 software was used to import all searched articles. Relevant information was retrieved for analysis into a Microsoft Excel Spreadsheet. A total of 104 full-text articles were assessed for eligibility criteria, whereby the articles should include the comparison between different types of blood source by using the membrane feeding systems. Only 16 articles were finally included in the analysis. Several studies had reported that human blood was superior in blood-feeding Ae. aegypti as compared to sheep blood which resulted in lower fecundity due to accumulation of free fatty acids (FFA) in the cuticles. In contrast, cattle whole blood and pig whole blood showed no significant differences in the blood-feeding and fecundity rate as compared to human blood. This review also indicated that bovine whole blood and pig whole blood enhanced Ae. aegypti's vitellogenesis and egg production as compared to plasma and blood cells. In addition, human blood of up to 10 days after the expiration date could still be used to establish Ae. aegypti colonies with good blood-feeding rates and number of eggs produced. Thus, future studies must consider the importance of selecting suitable blood sources and components for membrane blood feeding especially in mosquito colonisation and control measure studies.
  10. Kolo MT, Khandaker MU, Amin YM, Abdullah WH
    PLoS One, 2016;11(6):e0158100.
    PMID: 27348624 DOI: 10.1371/journal.pone.0158100
    Following the increasing demand of coal for power generation, activity concentrations of primordial radionuclides were determined in Nigerian coal using the gamma spectrometric technique with the aim of evaluating the radiological implications of coal utilization and exploitation in the country. Mean activity concentrations of 226Ra, 232Th, and 40K were 8.18±0.3, 6.97±0.3, and 27.38±0.8 Bq kg-1, respectively. These values were compared with those of similar studies reported in literature. The mean estimated radium equivalent activity was 20.26 Bq kg-1 with corresponding average external hazard index of 0.05. Internal hazard index and representative gamma index recorded mean values of 0.08 and 0.14, respectively. These values were lower than their respective precautionary limits set by UNSCEAR. Average excess lifetime cancer risk was calculated to be 0.04×10-3, which was insignificant compared with 0.05 prescribed by ICRP for low level radiation. Pearson correlation matrix showed significant positive relationship between 226Ra and 232Th, and with other estimated hazard parameters. Cumulative mean occupational dose received by coal workers via the three exposure routes was 7.69 ×10-3 mSv y-1, with inhalation pathway accounting for about 98%. All radiological hazard indices evaluated showed values within limits of safety. There is, therefore, no likelihood of any immediate radiological health hazards to coal workers, final users, and the environment from the exploitation and utilization of Maiganga coal.
  11. Ayatollahitafti V, Ngadi MA, Mohamad Sharif JB, Abdullahi M
    PLoS One, 2016;11(1):e0146464.
    PMID: 26771586 DOI: 10.1371/journal.pone.0146464
    Body Area Networks (BANs) consist of various sensors which gather patient's vital signs and deliver them to doctors. One of the most significant challenges faced, is the design of an energy-efficient next hop selection algorithm to satisfy Quality of Service (QoS) requirements for different healthcare applications. In this paper, a novel efficient next hop selection algorithm is proposed in multi-hop BANs. This algorithm uses the minimum hop count and a link cost function jointly in each node to choose the best next hop node. The link cost function includes the residual energy, free buffer size, and the link reliability of the neighboring nodes, which is used to balance the energy consumption and to satisfy QoS requirements in terms of end to end delay and reliability. Extensive simulation experiments were performed to evaluate the efficiency of the proposed algorithm using the NS-2 simulator. Simulation results show that our proposed algorithm provides significant improvement in terms of energy consumption, number of packets forwarded, end to end delay and packet delivery ratio compared to the existing routing protocol.
  12. Samson S, Basri M, Fard Masoumi HR, Abdul Malek E, Abedi Karjiban R
    PLoS One, 2016;11(7):e0157737.
    PMID: 27383135 DOI: 10.1371/journal.pone.0157737
    A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. Four independent variables including the amount of VCO, Tween 80: Pluronic F68 (T80:PF68), xanthan gum and water were the inputs whereas particle size was taken as the response for the trained network. Genetic algorithms (GA) were used to model the data which were divided into training sets, testing sets and validation sets. The model obtained indicated the high quality performance of the neural network and its capability to identify the critical composition factors for the VCO nanoemulsion. The main factor controlling the particle size was found out to be xanthan gum (28.56%) followed by T80:PF68 (26.9%), VCO (22.8%) and water (21.74%). The formulation containing copper peptide was then successfully prepared using optimum conditions and particle sizes of 120.7 nm were obtained. The final formulation exhibited a zeta potential lower than -25 mV and showed good physical stability towards centrifugation test, freeze-thaw cycle test and storage at temperature 25°C and 45°C.
  13. Siddiqui MB, Ng CW, Low WY, Abid K
    PLoS One, 2023;18(12):e0278149.
    PMID: 38109305 DOI: 10.1371/journal.pone.0278149
    The majority (40%) of the world's under-five mortality burden is concentrated in nations like Nigeria (16.5%), India (16%), Pakistan (8%), and the Democratic Republic of the Congo (6%), where an undetermined number of under-five deaths go unrecorded. In low-resource settings throughout the world, the Verbal Autopsy-Social Autopsy (VASA) technique may assist assess under-five mortality estimates, assigning medical and social causes of death, and identifying relevant determinants. Uncertainty regarding missing data in high-burden nations like Pakistan necessitates a valid and reliable VASA instrument. This is the first study to validate Child Health Epidemiology Reference Group-CHERG's VASA tool globally. In Pakistan, data from such a valid and reliable tool is vital for policy. This paper reports on the VASA tool in Karachi, Pakistan. Validity and reliability of the CHERG VASA tool were tested using face, content, discriminant validation, and reliability tests on one hundred randomly selected mothers who had recently experienced an under-five child death event. Data were computed on SPSS (version-21) and R software. Testing revealed high Item-content Validity Index (I-CVI) (>81.43%); high Cronbach's Alpha (0.843); the accuracy of between 75-100% of the discriminants classifying births to live and stillbirths; and I-CVI (>82.07% and 88.98% respectively) with high accuracy (92% and 97% respectively) for assigning biological and social causes of child deaths, respectively. The CHERG VASA questionnaire was found relevant to the conceptual framework and valid in Pakistan. This valid tool can assign accurate medical and non-medical causes of child mortality cases occurring in Pakistan.
  14. Dehdasht G, Ferwati MS, Zin RM, Abidin NZ
    PLoS One, 2020;15(2):e0228746.
    PMID: 32023306 DOI: 10.1371/journal.pone.0228746
    Successful implementation of the lean concept as a sustainable approach in the construction industry requires the identification of critical drivers in lean construction. Despite this significance, the number of in-depth studies toward understanding the considerable drivers of lean construction implementation is quite limited. There is also a shortage of methodologies for identifying key drivers. To address these challenges, this paper presents a list of all essential drivers within three aspects of sustainability (social, economic, and environmental) and proposes a novel methodology to rank the drivers and identify the key drivers for successful and sustainable lean construction implementation. In this regard, the entropy weighted Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was employed in this research. Subsequently, an empirical study was conducted within the Malaysian construction industry to demonstrate the proposed method. Moreover, sensitivity analysis and comparison with the existing method were engaged to validate the stability and accuracy of the achieved results. The significant results obtained in this study are as follows: presenting, verifying and ranking of 63 important drivers; identifying 22 key drivers; proposing an MCDM model of key drivers. The outcomes show that the proposed method in this study is an effective and accurate tool that could help managers make better decisions.
  15. Salama M, Shalash A, Magdy A, Makar M, Roushdy T, Elbalkimy M, et al.
    PLoS One, 2018;13(5):e0196436.
    PMID: 29742117 DOI: 10.1371/journal.pone.0196436
    Neurodegenerative diseases including Alzheimer's disease (AD) and Parkinson's disease (PD) are characterized by progressive neuronal loss and pathological accumulation of some proteins. Developing new biomarkers for both diseases is highly important for the early diagnosis and possible development of neuro-protective strategies. Serum antibodies (AIAs) against neuronal proteins are potential biomarkers for AD and PD that may be formed in response to their release into systemic circulation after brain damage. In the present study, two AIAs (tubulin and tau) were measured in sera of patients of PD and AD, compared to healthy controls. Results showed that both antibodies were elevated in patients with PD and AD compared to match controls. Curiously, the profile of elevation of antibodies was different in both diseases. In PD cases, tubulin and tau AIAs levels were similar. On the other hand, AD patients showed more elevation of tau AIAs compared to tubulin. Our current results suggested that AIAs panel could be able to identify cases with neuro-degeneration when compared with healthy subjects. More interestingly, it is possible to differentiate between PD and AD cases through identifying specific AIAs profile for each neurodegenerative states.
  16. Yong HS, Song SL, Eamsobhana P, Goh SY, Lim PE, Chow WL, et al.
    PLoS One, 2015;10(7):e0134581.
    PMID: 26230642 DOI: 10.1371/journal.pone.0134581
    Angiostrongylus costaricensis is a zoonotic parasitic nematode that causes abdominal or intestinal angiostrongyliasis in humans. It is endemic to the Americas. Although the mitochondrial genome of the Brazil taxon has been published, there is no available mitochondrial genome data on the Costa Rica taxon. We report here the complete mitochondrial genome of the Costa Rica taxon and its genetic differentiation from the Brazil taxon. The whole mitochondrial genome was obtained from next-generation sequencing of genomic DNA. It had a total length of 13,652 bp, comprising 36 genes (12 protein-coding genes-PCGs, 2 rRNA and 22 tRNA genes) and a control region (A + T rich non-coding region). It is longer than that of the Brazil taxon (13,585 bp). The larger mitogenome size of the Costa Rica taxon is due to the size of the control region as the Brazil taxon has a shorter length (265 bp) than the Costa Rica taxon (318 bp). The size of 6 PCGs and the start codon for ATP6, CYTB and NAD5 genes are different between the Costa Rica and Brazil taxa. Additionally, the two taxa differ in the stop codon of 6 PCGs. Molecular phylogeny based on 12 PCGs was concordant with two rRNA, 22 tRNA and 36 mitochondrial genes. The two taxa have a genetic distance of p = 16.2% based on 12 PCGs, p = 15.3% based on 36 mitochondrial genes, p = 13.1% based on 2 rRNA genes and p = 10.7% based on 22 tRNA genes, indicating status of sibling species. The Costa Rica and Brazil taxa of A. costaricensis are proposed to be accorded specific status as members of a species complex.
  17. Abdul Rahman M, Sani NS, Hamdan R, Ali Othman Z, Abu Bakar A
    PLoS One, 2021;16(8):e0255312.
    PMID: 34339480 DOI: 10.1371/journal.pone.0255312
    The Multidimensional Poverty Index (MPI) is an income-based poverty index which measures multiple deprivations alongside other relevant factors to determine and classify poverty. The implementation of a reliable MPI is one of the significant efforts by the Malaysian government to improve measures in alleviating poverty, in line with the recent policy for Bottom 40 Percent (B40) group. However, using this measurement, only 0.86% of Malaysians are regarded as multidimensionally poor, and this measurement was claimed to be irrelevant for Malaysia as a country that has rapid economic development. Therefore, this study proposes a B40 clustering-based K-Means with cosine similarity architecture to identify the right indicators and dimensions that will provide data driven MPI measurement. In order to evaluate the approach, this study conducted extensive experiments on the Malaysian Census dataset. A series of data preprocessing steps were implemented, including data integration, attribute generation, data filtering, data cleaning, data transformation and attribute selection. The clustering model produced eight clusters of B40 group. The study included a comprehensive clustering analysis to meaningfully understand each of the clusters. The analysis discovered seven indicators of multidimensional poverty from three dimensions encompassing education, living standard and employment. Out of the seven indicators, this study proposed six indicators to be added to the current MPI to establish a more meaningful scenario of the current poverty trend in Malaysia. The outcomes from this study may help the government in properly identifying the B40 group who suffers from financial burden, which could have been currently misclassified.
  18. Jee Keen Raymond W, Illias HA, Abu Bakar AH
    PLoS One, 2017;12(1):e0170111.
    PMID: 28085953 DOI: 10.1371/journal.pone.0170111
    Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.
  19. Saadati F, Ahmad Tarmizi R, Mohd Ayub AF, Abu Bakar K
    PLoS One, 2015;10(7):e0129938.
    PMID: 26132553 DOI: 10.1371/journal.pone.0129938
    Because students' ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is 'value added' because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM) in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students' problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students.
  20. Ramatillah DL, Gan SH, Pratiwy I, Syed Sulaiman SA, Jaber AAS, Jusnita N, et al.
    PLoS One, 2022;17(1):e0262438.
    PMID: 35077495 DOI: 10.1371/journal.pone.0262438
    BACKGROUND AND AIM: Coronavirus Disease 2019 (COVID-19) has become a worldwide pandemic and is a threat to global health. Patients who experienced cytokine storms tend to have a high mortality rate. However, to date, no study has investigated the impact of cytokine storms.

    MATERIALS AND METHODS: This retrospective cohort study included only COVID-19 positive patients hospitalized in a Private Hospital in West Jakarta between March and September 2020. All patients were not vaccinated during this period and treatment was based on the guidelines by the Ministry of Health Indonesia. A convenience sampling method was used and all patients who met the inclusion criteria were enrolled.

    RESULTS: The clinical outcome of COVID-19 patients following medical therapy was either cured (85.7%) or died (14.3%), with 14.3% patients reported to have cytokine storm, from which 23.1% led to fatalities. A plasma immunoglobulin (Gammaraas®) and/or tocilizumab (interleukin-6 receptor antagonist; Actemra®) injection was utilised to treat the cytokine storm while remdesivir and oseltamivir were administered to ameliorate COVID-19. Most (61.5%) patients who experienced the cytokine storm were male; mean age 60 years. Interestingly, all patients who experienced the cytokine storm had hypertension or/ and diabetes complication (100%). Fever, cough and shortness of breath were also the common symptoms (100.0%). Almost all (92.3%) patients with cytokine storm had to be treated in the intensive care unit (ICU). Most (76.9%) patients who had cytokine storm received hydroxychloroquine and all had antibiotics [1) azithromycin + levofloxacin or 2) meropenam for critically ill patients] and vitamins such as vitamins C and B-complex as well as mineral. Unfortunately, from this group, 23.1% patients died while the remaining 70% of patients recovered. A significant (p<0.05) correlation was established between cytokine storms and age, the presence of comorbidity, diabetes, hypertension, fever, shortness of breath, having oxygen saturation (SPO2) less than 93%, cold, fatigue, ward of admission, the severity of COVID-19 disease, duration of treatment as well as the use of remdesivir, Actemra® and Gammaraas®. Most patients recovered after receiving a combination treatment (oseltamivir + remdesivir + Antibiotics + Vitamin/Mineral) for approximately 11 days with a 90% survival rate. On the contrary, patients who received oseltamivir + hydroxychloroquine + Gammaraas® + antibiotics +Vitamin/Mineral, had a 83% survival rate after being admitted to the hospital for about ten days.

    CONCLUSION: Factors influencing the development of a cytokine storm include age, duration of treatment, comorbidity, symptoms, type of admission ward and severity of infection. Most patients (76.92%) with cytokine storm who received Gammaraas®/Actemra®, survived although they were in the severe and critical levels (87.17%). Overall, based on the treatment duration and survival rate, the most effective therapy was a combination of oseltamivir + favipiravir + hydroxychloroquine + antibiotics + vitamins/minerals.

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