MyMedR

Displaying publications 21 - 40 of 92 in total

Abstract:

Sort:

Fulltext Determinants of the willingness to participate in biobanking among Malaysian stakeholders in the Klang Valley

Amin L, Hashim H, Mahadi Z, Ismail K

BMC Med Res Methodol, 2018 12 05;18(1):163.
PMID: 30518344 DOI: 10.1186/s12874-018-0619-2

BACKGROUND: The demand in biobanking for the collection and maintenance of biological specimens and personal data from civilians to improve the prevention, diagnosis and treatment of diseases has increased notably. Despite the advancement, certain issues, specifically those related to privacy and data protection, have been critically discussed. The purposes of this study are to assess the willingness of stakeholders to participate in biobanking and to determine its predictors.

METHODS: A survey of 469 respondents from various stakeholder groups in the Klang Valley region of Malaysia was carried out. Based on previous research, a multi-dimensional instrument measuring willingness to participate in biobanking, and its predictors, was constructed and validated. A single step Structural Equation Modelling was performed to analyse the measurements and structural model using the International Business Machines Corporation Software Package for Social Sciences, Analysis of Moment Structures (IBM SPSS Amos) version 20 with a maximum likelihood function.

RESULTS: Malaysian stakeholders in the Klang Valley were found to be cautious of biobanks. Although they perceived the biobanks as moderately beneficial (mean score of 4.65) and were moderately willing to participate in biobanking (mean score of 4.10), they professed moderate concern about data and specimen protection issues (mean score of 4.33). Willingness to participate in biobanking was predominantly determined by four direct predictors: specific application-linked perceptions of their benefits (β = 0.35, p

Matched MeSH terms: Likelihood Functions
A Comparison Between Bayesian and Maximum Likelihood Estimations in Estimating Finite Mixture Model for Financial Data

Seuk-Yen Phoong, Mohd Tahir Ismail

Sains Malaysiana, 2015;44:1033-1039.

Over the years, maximum likelihood estimation and Bayesian method became popular statistical tools in which applied to fit finite mixture model. These trends begin with the advent of computer technology during the last decades. Moreover, the asymptotic properties for both statistical methods also act as one of the main reasons that boost the popularity of the methods. The difference between these two approaches is that the parameters for maximum likelihood estimation are fixed, but unknown meanwhile the parameters for Bayesian method act as random variables with known prior distributions. In the present paper, both the maximum likelihood estimation and Bayesian method are applied to investigate the relationship between exchange rate and the rubber price for Malaysia, Thailand, Philippines and Indonesia. In order to identify the most plausible method between Bayesian method and maximum likelihood estimation of time series data, Akaike Information Criterion and Bayesian Information Criterion are adopted in this paper. The result depicts that the Bayesian method performs better than maximum likelihood estimation on financial data.

Matched MeSH terms: Likelihood Functions
Spatial analysis of infant mortality in peninsular malaysia over three decades using mixture models

Nuzlinda Abdul Rahman, Abdul Aziz Jemain

Sains Malaysiana, 2013;42:1003-1010.

Infant mortality is one of the central public issues in most of the developing countries. In Malaysia, the infant mortality rates have improved at the national level over the last few decades. However, the issue concerned is whether the improvement is uniformly distributed throughout the country. The aim of this study was to investigate the geographical distribution of infant mortality in Peninsular Malaysia from the year 1970 to 2000 using a technique known as disease mapping. It is assumed that the random variable of infant mortality cases comes from Poisson distribution. Mixture models were used to find the number of optimum components/groups for infant mortality data for every district in Peninsular Malaysia. Every component is assumed to have the same distribution, but different parameters. The number of optimum components were obtained by maximum likelihood approach via the EM algorithm. Bayes theorem was used to determine the probability of belonging to each district in every components of the mixture distribution. Each district was assigned to the component that had the highest posterior probability of belonging. The results obtained were visually presented in maps. The analysis showed that in the early year of 1970, the spatial heterogeneity effect was more prominent; however, towards the end of 1990, this pattern tended to disappear. The reduction in the spatial heterogeneity effect in infant mortality data indicated that the provisions of health services throughout the Peninsular Malaysia have improved over the period of the study, particularly towards the year 2000.

Matched MeSH terms: Likelihood Functions
Fulltext The Malacca Strait separates distinct faunas of poorly-flying Cautires net-winged beetles

Jiruskova A, Motyka M, Bocek M, Bocak L

PeerJ, 2019;7:e6511.
PMID: 30863675 DOI: 10.7717/peerj.6511

We investigated the spatial and temporal patterns of Cautires diversification on the Malay Peninsula and Sumatra to understand if the narrow and frequently dry Malacca Strait separates different faunas. Moreover, we analyzed the origin of Cautires in Malayan and Sumatran mountains. We sampled 18 localities and present the mtDNA-based phylogeny of 76 species represented by 388 individuals. The phylogenetic tree was dated using mtDNA evolution rates and the ancestral ranges were estimated using the maximum likelihood approach. The phylogeny identified multiple lineages on the Malay Peninsula since the Upper Eocene (35 million years ago, mya) and a delayed evolution of diversity in Sumatra since the Upper Oligocene (26 mya). A limited number of colonization events across the Malacca Strait was identified up to the Pliocene and more intensive faunal exchange since the Pleistocene. The early colonization events were commonly followed by in situ diversification. As a result, the Malacca Strait now separates two faunas with a high species-level turnover. The montane fauna diversified in a limited space and seldom took part in colonization events across the Strait. Besides isolation by open sea or a savannah corridor, mimetic patterns could decrease the colonization capacity of Cautires. The Malay fauna is phylogenetically more diverse and has a higher value if conservation priorities should be defined.

Matched MeSH terms: Likelihood Functions
Fulltext Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

Zafar R, Dass SC, Malik AS

PLoS One, 2017;12(5):e0178410.
PMID: 28558002 DOI: 10.1371/journal.pone.0178410

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Matched MeSH terms: Likelihood Functions
Fulltext Severity-based adaptation with limited data for ASR to aid dysarthric speakers

Mustafa MB, Salim SS, Mohamed N, Al-Qatab B, Siong CE

PLoS One, 2014;9(1):e86285.
PMID: 24466004 DOI: 10.1371/journal.pone.0086285

Automatic speech recognition (ASR) is currently used in many assistive technologies, such as helping individuals with speech impairment in their communication ability. One challenge in ASR for speech-impaired individuals is the difficulty in obtaining a good speech database of impaired speakers for building an effective speech acoustic model. Because there are very few existing databases of impaired speech, which are also limited in size, the obvious solution to build a speech acoustic model of impaired speech is by employing adaptation techniques. However, issues that have not been addressed in existing studies in the area of adaptation for speech impairment are as follows: (1) identifying the most effective adaptation technique for impaired speech; and (2) the use of suitable source models to build an effective impaired-speech acoustic model. This research investigates the above-mentioned two issues on dysarthria, a type of speech impairment affecting millions of people. We applied both unimpaired and impaired speech as the source model with well-known adaptation techniques like the maximum likelihood linear regression (MLLR) and the constrained-MLLR(C-MLLR). The recognition accuracy of each impaired speech acoustic model is measured in terms of word error rate (WER), with further assessments, including phoneme insertion, substitution and deletion rates. Unimpaired speech when combined with limited high-quality speech-impaired data improves performance of ASR systems in recognising severely impaired dysarthric speech. The C-MLLR adaptation technique was also found to be better than MLLR in recognising mildly and moderately impaired speech based on the statistical analysis of the WER. It was found that phoneme substitution was the biggest contributing factor in WER in dysarthric speech for all levels of severity. The results show that the speech acoustic models derived from suitable adaptation techniques improve the performance of ASR systems in recognising impaired speech with limited adaptation data.

Matched MeSH terms: Likelihood Functions
Sex differences from fingerprint ridge density in Chinese and Malaysian population

Nayak VC, Rastogi P, Kanchan T, Yoganarasimha K, Kumar GP, Menezes RG

Forensic Sci Int, 2010 Apr 15;197(1-3):67-9.
PMID: 20071110 DOI: 10.1016/j.forsciint.2009.12.055

The fingerprints are very typical for a human being. The present study was undertaken to study the gender differences in fingerprint ridge density in Chinese and Malaysian population. The study done on 200 subjects (100 males and 100 females) of Chinese origin and 100 subjects (50 males and 50 females) of Malaysian origin revealed that significant gender differences occur in the finger ridge density. Fingerprint mean ridge density of 12 ridges/25 mm(2) or less is found to be more likely to be of males and a mean ridge count of more the 13 ridges/25 mm(2) is more likely of female origin in Chinese subjects. Fingerprint mean ridge density of 11 ridges/25 mm(2) or less is found to be more likely to be of males and a mean ridge count of more the 13 ridges/25 mm(2) is more likely of female origin in Malaysian subjects.

Matched MeSH terms: Likelihood Functions
Evolutionary origin of Ceratonova shasta and phylogeny of the marine myxosporean lineage

Fiala I, Hlavničková M, Kodádková A, Freeman MA, Bartošová-Sojková P, Atkinson SD

Mol Phylogenet Evol, 2015 May;86:75-89.
PMID: 25797924 DOI: 10.1016/j.ympev.2015.03.004

In order to clarify the phylogenetic relationships among the main marine myxosporean clades including newly established Ceratonova clade and scrutinizing their evolutionary origins, we performed large-scale phylogenetic analysis of all myxosporean species from the marine myxosporean lineage based on three gene analyses and statistical topology tests. Furthermore, we obtained new molecular data for Ceratonova shasta, C. gasterostea, eight Ceratomyxa species and one Myxodavisia species. We described five new species: Ceratomyxa ayami n. sp., C. leatherjacketi n. sp., C. synaphobranchi n. sp., C. verudaensis n. sp. and Myxodavisia bulani n. sp.; two of these formed a new, basal Ceratomyxa subclade. We identified that the Ceratomyxa clade is basal to all other marine myxosporean lineages, and Kudoa with Enteromyxum are the most recently branching clades. Topologies were least stable at the nodes connecting the marine urinary clade, the marine gall bladder clade and the Ceratonova clade. Bayesian inference analysis of SSU rDNA and the statistical tree topology tests suggested that Ceratonova is closely related to the Enteromyxum and Kudoa clades, which represent a large group of histozoic species. A close relationship between Ceratomyxa and Ceratonova was not supported, despite their similar myxospore morphologies. Overall, the site of sporulation in the vertebrate host is a more accurate predictor of phylogenetic relationships than the morphology of the myxospore.

Matched MeSH terms: Likelihood Functions
Fulltext The whole genome sequence data analyses of a Mycobacterium tuberculosis strain SBH321 isolated in Sabah, Malaysia, belongs to Ural family of Lineage 4

Jani J, Mustapha ZA, Ling CK, Hui ASM, Teo R, Ahmed K

Data Brief, 2020 Dec;33:106388.
PMID: 33102655 DOI: 10.1016/j.dib.2020.106388

In 2019, 10 million new cases of tuberculosis have been reported worldwide. Our data reports genetic analyses of a Mycobacterium tuberculosis strain SBH321 isolated from a 31-year-old female with pulmonary tuberculosis. The genomic DNA of the strain was extracted from pure culture and subjected to sequencing using Illumina platform. M. tuberculosis strain SBH321 consists of 4,374,895 bp with G+C content of 65.59%. The comparative analysis by SNP-based phylogenetic analysis using maximum-likelihood method showed that our strain belonging to sublineage of the Ural family of Europe-America-Africa lineage (Lineage 4) and clustered with M. tuberculosis strain OFXR-4 from Taiwan. The whole genome sequence is deposited at DDBJ/ENA/GenBank under the accession WCJH00000000 (SRR10230353).

Matched MeSH terms: Likelihood Functions
Fulltext Plant DNA barcodes and assessment of phylogenetic community structure of a tropical mixed dipterocarp forest in Brunei Darussalam (Borneo)

Heckenhauer J, Abu Salim K, Chase MW, Dexter KG, Pennington RT, Tan S, et al.

PLoS One, 2017;12(10):e0185861.
PMID: 29049301 DOI: 10.1371/journal.pone.0185861

DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m) of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia). The combined matrix (rbcL + matK) comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016), making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI) and nearest taxon index (NTI). In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals into analyses.

Matched MeSH terms: Likelihood Functions
Fulltext Whole genome sequencing data and analysis of a rifampicin-resistant Mycobacterium tuberculosis strain SBH162 from Sabah, Malaysia

Jani J, Mustapha ZA, Jamal NB, Stanis CS, Ling CK, Avoi R, et al.

Data Brief, 2019 Oct;26:104445.
PMID: 31534995 DOI: 10.1016/j.dib.2019.104445

A Mycobacterium tuberculosis strain SBH162 was isolated from a 49-year-old male with pulmonary tuberculosis. GeneXpert MDR/RIF identified the strain as rifampicin-resistant M. tuberculosis. The whole genome sequencing was performed using Illumina HiSeq 4000 system to further investigate and verify the mutation sites of the strain through genetic analyses namely variant calling using bioinformatics tools. The de novo assembly of genome generated 100 contigs with N50 of 156,381bp. The whole genome size was 4,343,911 bp with G + C content of 65.58% and consisted of 4,306 predicted genes. The mutation site, S450L, for rifampicin resistance was detected in the rpoB gene. Based on the phylogenetic analysis using the Maximum Likelihood method, the strain was identified as belonging to the Europe America Africa lineage (Lineage 4). The genome dataset has been deposited at DDBJ/ENA/GenBank under the accession number SMOE00000000.

Matched MeSH terms: Likelihood Functions
Fulltext The satisfaction with life scale: Psychometric properties in Pakistani population

Barki N, Choudhry FR, Munawar K

Med J Islam Repub Iran, 2020;34:159.
PMID: 33500886 DOI: 10.47176/mjiri.34.159

Background: The construct of satisfaction with life has been studied across various cultures through the Satisfaction with Life Scale. The Satisfaction with Life Scale (SWLS) has been validated across several populations and languages. There are no published psychometric properties of its Urdu version. Hence, the aim of this study was to ascertain the psychometric properties of the Urdu version of the SWLS among the Urdu speaking population of Pakistan. Methods: The SWLS has already been translated into Urdu, and the Urdu version is available on the author's website however there is no information about its psychometric properties. To establish the psychometric properties especially the factor structure of the already translated Urdu SWLS, the SWLS-Urdu was administered to Urdu speaking population residing in Pakistan. The statistical analyses (i.e., normality through skewness and kurtosis, Kaiser-Meyer-Olkin (KMO) and Bartlett's test of sphericity, and test and re-test reliability) were conducted through SPSS version 25.0. Structure Equation Modelling via maximum likelihood method of estimation was used to perform confirmatory factor analysis on the data using AMOS 20.0. The significance level was set at p < 0.05. Results: The study was completed by recruiting 120 participants from different universities in Lahore, Pakistan. The sample was equally divided between male and female participants. The mean age of participants was 22.7(3.6) years. Test of the adequacy of the sample through Kaiser-Mayer-Olkin showed KMO=0.88 and Bartlett's test of sphericity (p<0.001). The Cronbach's alpha reliability of the scale was 0.90 and Confirmatory Factor Analysis confirmed a one-factor model as a good fit with strong statistical evidence. No factorial group variances were noticed in male and female participants. Conclusion: This study shows that Urdu SWLS has sound psychometric properties, is linguistically and culturally acceptable, and equally useful in assessing satisfaction with life in the Urdu speaking population.

Matched MeSH terms: Likelihood Functions
Fulltext PHYLOGENETIC ANALYSIS OF Komagataeibacter sp.: A CELLULOSE-PRODUCER BACTERIA BASED ON 16S rRNA GENE SEQUENCES+-

Nur Aisyah Atikah Alizan, Sarah S. Zakaria

Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2021;9(1):97-105.
MyJurnal

Bacteria of the genus Komagataeibacter are described to be the most noteworthy for having several of its species being efficient and strong cellulose producers. The 16S ribosomal RNA (rRNA) gene analysis is often used for the identification and taxonomic classification of these bacteria species. In order to observe the phylogenetic relationship among Komagataeibacter sp., twelve sequences of the 16S rRNA gene with three sequences each for species namely Komagataeibacter europaeus, Komagataeibacter hansenii, Komagataeibacter intermedius and Komagataeibacter xylinus were retrieved from NCBI GenBank database. The sequences were aligned and analysed using PAUP, OrthoANI and BLAST, followed by the phylogenetic tree construction using a Maximum Likelihood method. The parsimony character diagnostic analysis showed very few numbers of parsimony- informative characters present in the aligned sequences which is only 1.5% of the total characters. The inferred phylogenetic relationships demonstrated the unexpected positioning of K. xylinus (GQ240638: Gluconacetobacter xylinus strain) and K. xylinus (KC11853: G. xylinus strain) into the clades of K. europaeus and K. hansenii respectively. The also very low bootstrap values of the branch points linking the K. europaeus species indicated low support for the produced topologies. The findings of this study indicate that more phylogenies information can be attained by increasing the taxon sampling. In addition, more robust molecular data are needed to infer the phylogenetic relationships between the Komagataeibacter species more accurately.

Matched MeSH terms: Likelihood Functions
Fulltext Comparison between two fast threshold strategies: SPARK and SITA in normal subjects

Foo SK, Cubbidge RP, Heitmar R

Eur J Ophthalmol, 2021 Jul;31(4):1870-1876.
PMID: 32468855 DOI: 10.1177/1120672120926455

BACKGROUND: Numerous fast threshold strategies have been developed in perimetry which use maximum likelihood approaches to estimate the threshold. A recent approach to threshold estimation has been developed estimating the threshold from a limited number of test points which further reduces examination time. This strategy, SPARK, has not been compared to the SITA strategy. The aim of this study was to compare SPARK with SITA in a normal cohort to evaluate within and between strategy agreement in threshold estimates.
METHODS: A total of 83 normal subjects each underwent two visual field examinations with SITA and SPARK on two separate occasions on a randomly selected eye. The eye examined and the order of strategy examined first was randomised but remained constant over the two perimetry visits.
RESULTS: Visual field examination with SPARK Precision was on average 33% faster than SITA Standard. A positive correlation between group mean sensitivities of SITA Standard and SPARK Precision (rho = 0.713, p

Matched MeSH terms: Likelihood Functions
Spatial identification and temporal prediction of air pollution sources using conditional bivariate probability function and time series signature

Althuwaynee OF, Pokharel B, Aydda A, Balogun AL, Kim SW, Park HJ

J Expo Sci Environ Epidemiol, 2021 07;31(4):709-726.
PMID: 33159165 DOI: 10.1038/s41370-020-00271-8

Accurate identification of distant, large, and frequent sources of emission in cities is a complex procedure due to the presence of large-sized pollutants and the existence of many land use types. This study aims to simplify and optimize the visualization mechanism of long time-series of air pollution data, particularly for urban areas, which is naturally correlated in time and spatially complicated to analyze. Also, we elaborate different sources of pollution that were hitherto undetectable using ordinary plot models by leveraging recent advances in ensemble statistical approaches. The high performing conditional bivariate probability function (CBPF) and time-series signature were integrated within the R programming environment to facilitate the study's analysis. Hourly air pollution data for the period between 2007 to 2016 is collected using four air quality stations, (ca0016, ca0058, ca0054, and ca0025), situated in highly urbanized locations that are characterized by complex land use and high pollution emitting activities. A conditional bivariate probability function (CBPF) was used to analyze the data, utilizing pollutant concentration values such as Sulfur dioxide (SO2), Nitrogen oxides (NO2), Carbon monoxide (CO) and Particulate Matter (PM10) as a third variable plotted on the radial axis, with wind direction and wind speed variables. Generalized linear model (GLM) and sensitivity analysis are applied to verify and visualize the relationship between Air Pollution Index (API) of PM10 and other significant pollutants of GML outputs based on quantile values. To address potential future challenges, we forecast 3 months PM10 values using a Time Series Signature statistical algorithm with time functions and validated the outcome in the 4 stations. Analysis of results reveals that sources emitting PM10 have similar activities producing other pollutants (SO2, CO, and NO2). Therefore, these pollutants can be detected by cross selection between the pollution sources in the affected city. The directional results of CBPF plot indicate that ca0058 and ca0054 enable easier detection of pollutants' sources in comparison to ca0016 and ca0025 due to being located on the edge of industrial areas. This study's CBPF technique and time series signature analysis' outcomes are promising, successfully elaborating different sources of pollution that were hitherto undetectable using ordinary plot models and thus contribute to existing air quality assessment and enhancement mechanisms.

Matched MeSH terms: Likelihood Functions
Comprehensive multi-locus phylogeny of Old World tree frogs (Anura: Rhacophoridae) reveals taxonomic uncertainties and potential cases of over- and underestimation of species diversity

Chan KO, Grismer LL, Brown RM

Mol Phylogenet Evol, 2018 10;127:1010-1019.
PMID: 30030179 DOI: 10.1016/j.ympev.2018.07.005

The family Rhacophoridae is one of the most diverse amphibian families in Asia, for which taxonomic understanding is rapidly-expanding, with new species being described steadily, and at increasingly finer genetic resolution. Distance-based methods frequently have been used to justify or at least to bolster the recognition of new species, particularly in complexes of "cryptic" species where obvious morphological differentiation does not accompany speciation. However, there is no universally-accepted threshold to distinguish intra- from interspecific genetic divergence. Moreover, indiscriminant use of divergence thresholds to delimit species can result in over- or underestimation of species diversity. To explore the range of variation in application of divergence scales, and to provide a family-wide assessment of species-level diversity in Old-World treefrogs (family Rhacophoridae), we assembled the most comprehensive multi-locus phylogeny to date, including all 18 genera and approximately 247 described species (∼60% coverage). We then used the Automatic Barcode Gap Discovery (ABGD) method to obtain different species-delimitation schemes over a range of prior intraspecific divergence limits to assess the consistency of divergence thresholds used to demarcate current species boundaries. The species-rich phylogeny was able to identify a number of taxonomic errors, namely the incorrect generic placement of Chiromantis inexpectatus, which we now move to the genus Feihyla, and the specific identity of Rhacophorus bipunctatus from Peninsular Malaysia, which we tentatively reassign to R. rhodopus. The ABGD analysis demonstrated overlap between intra- and interspecific divergence limits: genetic thresholds used in some studies to synonymize taxa have frequently been used in other studies to justify the recognition of new species. This analysis also highlighted numerous groups that could potentially be split or lumped, which we earmark for future examination. Our large-scale and en bloc approach to species-level phylogenetic systematics contributes to the resolution of taxonomic uncertainties, reveals possible new species, and identifies numerous groups that require critical examination. Overall, we demonstrate that the taxonomy and evolutionary history of Old-World tree frogs are far from resolved, stable or adequately characterized at the level of genus, species, and/or population.

Matched MeSH terms: Likelihood Functions
Fulltext Norm-dist Monte-Carlo integrative method for the improvement of fuzzy analytic hierarchy process

Wicaksono FD, Arshad YB, Sihombing H

Heliyon, 2020 Apr;6(4):e03607.
PMID: 32346625 DOI: 10.1016/j.heliyon.2020.e03607

This paper presents the novel approach of the Norm-dist Monte-Carlo fuzzy analytic hierarchy process (NMCFAHP) to incorporate probabilistic and epistemic uncertainty due to human's judgment vagueness in multi-criteria decision analysis. Normal distribution is applied as the most appropriate distribution model to approximate the probability distribution function of the criteria and alternatives within Monte-Carlo simulation. To test the applicability of the proposed NMCFAHP, the case study of non-destructive test (NDT) technology selection is performed in the Petroleum Company in Borneo, Indonesia. When compared with the conventional triangular fuzzy-AHP, the proposed NMCFAHP method reduces the standard error of mean values by 90.4-99.8% at the final evaluation scores. This means that the proposed NMCFAHP significantly involves fewer errors when dealing with fuzzy uncertainty and stochastic randomness. The proposed NMCFAHP delivers reliable performance to overcome probabilistic uncertainty and epistemic vagueness in the group decision making process.

Matched MeSH terms: Likelihood Functions
Fulltext Utilization of a Mixture Cure Rate Model based on the Generalized Modified Weibull Distribution for the Analysis of Leukemia Patients

Omer ME, Abu Bakar M, Adam M, Mustafa M

Asian Pac J Cancer Prev, 2021 Apr 01;22(4):1045-1053.
PMID: 33906295 DOI: 10.31557/APJCP.2021.22.4.1045

OBJECTIVE: Cure rate models are survival models, commonly applied to model survival data with a cured fraction. In the existence of a cure rate, if the distribution of survival times for susceptible patients is specified, researchers usually prefer cure models to parametric models. Different distributions can be assumed for the survival times, for instance, generalized modified Weibull (GMW), exponentiated Weibull (EW), and log-beta Weibull. The purpose of this study is to select the best distribution for uncured patients' survival times by comparing the mixture cure models based on the GMW distribution and its particular cases.
MATERIALS AND METHODS: A data set of 91 patients with high-risk acute lymphoblastic leukemia (ALL) followed for five years from 1982 to 1987 was chosen for fitting the mixture cure model. We used the maximum likelihood estimation technique via R software 3.6.2 to obtain the estimates for parameters of the proposed model in the existence of cure rate, censored data, and covariates. For the best model choice, the Akaike information criterion (AIC) was implemented.
RESULTS: After comparing different parametric models fitted to the data, including or excluding cure fraction, without covariates, the smallest AIC values were obtained by the EW and the GMW distributions, (953.31/969.35) and (955.84/975.99), respectively. Besides, assuming a mixture cure model based on GMW with covariates, an estimated ratio between cure fractions for allogeneic and autologous bone marrow transplant groups (and its 95% confidence intervals) were 1.42972 (95% CI: 1.18614 - 1.72955).
CONCLUSION: The results of this study reveal that the EW and the GMW distributions are the best choices for the survival times of Leukemia patients.
.

Matched MeSH terms: Likelihood Functions
Factors associated with the enactment of safety belt and motorcycle helmet laws

Law TH, Noland RB, Evans AW

Risk Anal, 2013 Jul;33(7):1367-78.
PMID: 23106188 DOI: 10.1111/j.1539-6924.2012.01916.x

It has been shown that road safety laws, such as motorcycle helmet and safety belt laws, have a significant effect in reducing road fatalities. Although an expanding body of literature has documented the effects of these laws on road safety, it remains unclear which factors influence the likelihood that these laws are enacted. This study attempts to identify the factors that influence the decision to enact safety belt and motorcycle helmet laws. Using panel data from 31 countries between 1963 and 2002, our results reveal that increased democracy, education level, per capita income, political stability, and more equitable income distribution within a country are associated with the enactment of road safety laws.

Matched MeSH terms: Likelihood Functions
Fulltext Multilocus phylogenetic analyses reveal unexpected abundant diversity and significant disjunct distribution pattern of the Hedgehog Mushrooms (Hydnum L.)

Feng B, Wang XH, Ratkowsky D, Gates G, Lee SS, Grebenc T, et al.

Sci Rep, 2016 May 06;6:25586.
PMID: 27151256 DOI: 10.1038/srep25586

Hydnum is a fungal genus proposed by Linnaeus in the early time of modern taxonomy. It contains several ectomycorrhizal species which are commonly consumed worldwide. However, Hydnum is one of the most understudied fungal genera, especially from a molecular phylogenetic view. In this study, we extensively gathered specimens of Hydnum from Asia, Europe, America and Australasia, and analyzed them by using sequences of four gene fragments (ITS, nrLSU, tef1α and rpb1). Our phylogenetic analyses recognized at least 31 phylogenetic species within Hydnum, 15 of which were reported for the first time. Most Australasian species were recognized as strongly divergent old relics, but recent migration between Australasia and the Northern Hemisphere was also detected. Within the Northern Hemisphere, frequent historical biota exchanges between the Old World and the New World via both the North Atlantic Land Bridge and the Bering Land Bridge could be elucidated. Our study also revealed that most Hydnum species found in subalpine areas of the Hengduan Mountains in southwestern China occur in northeastern/northern China and Europe, indicating that the composition of the mycobiota in the Hengduan Mountains reigion is more complicated than what we have known before.

Matched MeSH terms: Likelihood Functions

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links