Displaying publications 1 - 20 of 92 in total

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  1. Kamarudin KR, Rehan MM
    Trop Life Sci Res, 2015 Apr;26(1):87-99.
    PMID: 26868593 MyJurnal
    This preliminary study aimed to identify a commercial gamat species, Stichopus horrens Selenka, 1867, and a timun laut species, Holothuria (Mertensiothuria) leucospilota (Brandt, 1835), from Pangkor Island, Perak, Malaysia, employing morphological techniques based on the shape of the ossicles and molecular techniques based on the cytochrome c oxidase I (COI) mitochondrial DNA (mtDNA) gene. In Malaysia, a gamat is defined as a sea cucumber species of the family Stichopodidae with medicinal value, and timun laut refers to non-gamat species. S. horrens is very popular on Pangkor Island as a main ingredient in the traditional production of air gamat and minyak gamat, while H. leucospilota is the most abundant species in Malaysia. In contrast to previous studies, internal body parts (the respiratory tree and gastrointestine) were examined in this study to obtain better inferences based on morphology. The results showed that there were no ossicles present in the gastrointestine of H. leucospilota, and this characteristic is suggested as a unique diagnostic marker for the timun laut species. In addition, the presence of Y-shaped rods in the respiratory tree of S. horrens subsequently supported the potential to use internal body parts to identify the gamat species. Phylogenetic analysis of the COI mtDNA gene of the sea cucumber specimens using the neighbour-joining method and maximum likelihood methods further confirmed the species status of H. leucospilota and S. horrens from Pangkor Island, Perak, Malaysia. The COI mtDNA gene sequences were registered with GenBank, National Center for Biotechnology Information (NCBI), US National Library of Medicine (GenBank accession no.: KC405565-KC405568). Although additional specimens from various localities will be required to produce more conclusive results, the current findings provide better insight into the importance of complementary approaches involving morphological and molecular techniques in the identification of the two Malaysian sea cucumber species.
    Matched MeSH terms: Likelihood Functions
  2. Mohammad NA, Al-Mekhlafi HM, Anuar TS
    Trop Biomed, 2018 Dec 01;35(4):849-860.
    PMID: 33601835
    Blastocystis is one of the most common parasites inhabiting the intestinal tract of human and animals. Currently, human Blastocystis isolates are classified into nine subtypes (STs) based on the phylogeny of their small subunit ribosomal RNA (SSU rRNA) gene. Although its pathogenicity remains controversial, the possibility of zoonotic transmission was recognized since eight of the nine STs (except for ST9) have been reported in both humans and animals. A cross-sectional study was conducted to determine the prevalence and subtype distribution of Blastocystis isolated from humans and associated animals in an indigenous community with poor hygiene in Malaysia, where the risk of parasitic infection is high. A total of 275 stool samples were collected, subjected to DNA extraction and amplified by PCR assay. The Blastocystis-positive amplicons were then purified and sequenced. Phylogenetic tree of positive isolates, reference strains and outgroup were constructed using maximum likelihood method based on Hasegawa-KishinoYano+G+I model. The prevalence of Blastocystis infection among humans and domestic animals by PCR assay were 18.5% (45/243) and 6.3% (2/32), respectively. Through molecular phylogeny, 47 isolates were separated into five clusters containing isolates from both hosts. Among human isolates, ST3 (53.3%) was the predominant subtype, followed by ST1 (31.1%) and ST2 (15.6%). Chicken and cattle had lower proportions of ST6 (50%) and ST10 (50%), that were barely seen in humans. The distinct distributions of the most important STs among the host animals as well as humans examined demonstrate that there is various host-specific subtypes in the lifecycle of Blastocystis.
    Matched MeSH terms: Likelihood Functions
  3. Hossain MA, Roslan HA
    ScientificWorldJournal, 2014;2014:186029.
    PMID: 25165734 DOI: 10.1155/2014/186029
    beta-D-N-Acetylhexosaminidase, a family 20 glycosyl hydrolase, catalyzes the removal of β-1,4-linked N-acetylhexosamine residues from oligosaccharides and their conjugates. We constructed phylogenetic tree of β-hexosaminidases to analyze the evolutionary history and predicted functions of plant hexosaminidases. Phylogenetic analysis reveals the complex history of evolution of plant β-hexosaminidase that can be described by gene duplication events. The 3D structure of tomato β-hexosaminidase (β-Hex-Sl) was predicted by homology modeling using 1now as a template. Structural conformity studies of the best fit model showed that more than 98% of the residues lie inside the favoured and allowed regions where only 0.9% lie in the unfavourable region. Predicted 3D structure contains 531 amino acids residues with glycosyl hydrolase20b domain-I and glycosyl hydrolase20 superfamily domain-II including the (β/α)8 barrel in the central part. The α and β contents of the modeled structure were found to be 33.3% and 12.2%, respectively. Eleven amino acids were found to be involved in ligand-binding site; Asp(330) and Glu(331) could play important roles in enzyme-catalyzed reactions. The predicted model provides a structural framework that can act as a guide to develop a hypothesis for β-Hex-Sl mutagenesis experiments for exploring the functions of this class of enzymes in plant kingdom.
    Matched MeSH terms: Likelihood Functions
  4. Solarin SA, Bello MO
    Sci Total Environ, 2020 Apr 10;712:135594.
    PMID: 31787295 DOI: 10.1016/j.scitotenv.2019.135594
    Environmental degradation remains a huge obstacle to sustainable development. Research on the factors that promote or degrade the environment has been extensively conducted. However, one important variable that has conspicuously received very limited attention is energy innovations. To address this gap in the literature, this study investigated the effects of energy innovations on environmental quality in the U.S. for the period 1974 to 2016. We have incorporated GDP and immigration as additional regressors. Three indices comprising of CO2 emissions, ecological footprint and carbon footprint were used to proxy environmental degradation. The cointegration tests established long-run relationships between the variables. Using a maximum likelihood approach with a break, the results showed evidence that energy innovations significantly improve environmental quality while GDP degrades the quality of the environment, and immigration has no significant effect on the environment. Policy implications of the results are discussed in the body of the manuscript.
    Matched MeSH terms: Likelihood Functions
  5. Cai L, Xi Z, Amorim AM, Sugumaran M, Rest JS, Liu L, et al.
    New Phytol, 2019 Jan;221(1):565-576.
    PMID: 30030969 DOI: 10.1111/nph.15357
    Whole-genome duplications (WGDs) are widespread and prevalent in vascular plants and frequently coincide with major episodes of global and climatic upheaval, including the mass extinction at the Cretaceous-Tertiary boundary (c. 65 Ma) and during more recent periods of global aridification in the Miocene (c. 10-5 Ma). Here, we explore WGDs in the diverse flowering plant clade Malpighiales. Using transcriptomes and complete genomes from 42 species, we applied a multipronged phylogenomic pipeline to identify, locate, and determine the age of WGDs in Malpighiales using three means of inference: distributions of synonymous substitutions per synonymous site (Ks ) among paralogs, phylogenomic (gene tree) reconciliation, and a likelihood-based gene-count method. We conservatively identify 22 ancient WGDs, widely distributed across Malpighiales subclades. Importantly, these events are clustered around the Eocene-Paleocene transition (c. 54 Ma), during which time the planet was warmer and wetter than any period in the Cenozoic. These results establish that the Eocene Climatic Optimum likely represents a previously unrecognized period of prolific WGDs in plants, and lends further support to the hypothesis that polyploidization promotes adaptation and enhances plant survival during episodes of global change, especially for tropical organisms like Malpighiales, which have tight thermal tolerances.
    Matched MeSH terms: Likelihood Functions
  6. Liversidge HM, Peariasamy K, Folayan MO, Adeniyi AO, Ngom PI, Mikami Y, et al.
    J Forensic Odontostomatol, 2017 Dec 01;35(2):97-108.
    PMID: 29384741
    BACKGROUND: The nature of differences in the timing of tooth formation between ethnic groups is important when estimating age.

    AIM: To calculate age of transition of the mandibular third (M3) molar tooth stages from archived dental radiographs from sub-Saharan Africa, Malaysia, Japan and two groups from London UK (Whites and Bangladeshi).

    MATERIALS AND METHODS: The number of radiographs was 4555 (2028 males, 2527 females) with an age range 10-25 years. The left M3 was staged into Moorrees stages. A probit model was fitted to calculate mean ages for transitions between stages for males and females and each ethnic group separately. The estimated age distributions given each M3 stage was calculated. To assess differences in timing of M3 between ethnic groups, three models were proposed: a separate model for each ethnic group, a joint model and a third model combining some aspects across groups. The best model fit was tested using Bayesian and Akaikes information criteria (BIC and AIC) and log likelihood ratio test.

    RESULTS: Differences in mean ages of M3 root stages were found between ethnic groups, however all groups showed large standard deviation values. The AIC and log likelihood ratio test indicated that a separate model for each ethnic group was best. Small differences were also noted between timing of M3 between males and females, with the exception of the Malaysian group. These findings suggests that features of a reference data set (wide age range and uniform age distribution) and a Bayesian statistical approach are more important than population specific convenience samples to estimate age of an individual using M3.

    CONCLUSION: Some group differences were evident in M3 timing, however, this has some impact on the confidence interval of estimated age in females and little impact in males because of the large variation in age.

    Matched MeSH terms: Likelihood Functions
  7. Yuan YM, Wohlhauser S, Möller M, Klackenberg J, Callmander M, Küpfer P
    Syst Biol, 2005 Feb;54(1):21-34.
    PMID: 15805008
    Disjunctive distributions across paleotropical regions in the Indian Ocean Basin (IOB) often invoke dispersal/vicariance debates. Exacum (Gentianaceae, tribe Exaceae) species are spread around the IOB, in Africa, Madagascar, Socotra, the Arabian peninsula, Sri Lanka, India, the Himalayas, mainland Southeast Asia including southern China and Malaysia, and northern Australia. The distribution of this genus was suggested to be a typical example of vicariance resulting from the breakup of the Gondwanan supercontinent. The molecular phylogeny of Exacum is in principle congruent with morphological conclusions and shows a pattern that resembles a vicariance scenario with rapid divergence among lineages, but our molecular dating analysis demonstrates that the radiation is too recent to be associated with the Gondwanan continental breakup. We used our dating analysis to test the results of DIVA and found that the program predicted impossible vicariance events. Ancestral area reconstruction suggests that Exacum originated in Madagascar, and divergence dating suggests its origin was not before the Eocene. The Madagascan progenitor, the most recent common ancestor of Exacum, colonized Sri Lanka and southern India via long-distance dispersals. This colonizer underwent an extensive range expansion and spread to Socotra-Arabia, northern India, and mainland Southeast Asia in the northern IOB when it was warm and humid in these regions. This widespread common ancestor retreated subsequently from most parts of these regions and survived in isolation in Socotra-Arabia, southern India-Sri Lanka, and perhaps mainland Southeast Asia, possibly as a consequence of drastic climatic changes, particularly the spreading drought during the Neogene. Secondary diversification from these surviving centers and Madagascar resulted in the extant main lineages of the genus. The vicariance-like pattern shown by the phylogeny appears to have resulted from long-distance dispersals followed by extensive range expansion and subsequent fragmentation. The extant African species E. oldenlandioides is confirmed to be recently dispersed from Madagascar.
    Matched MeSH terms: Likelihood Functions
  8. 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
  9. Nashwan MS, Shahid S, Chung ES
    Sci Data, 2019 07 31;6(1):138.
    PMID: 31366936 DOI: 10.1038/s41597-019-0144-0
    This study developed 0.05° × 0.05° land-only datasets of daily maximum and minimum temperatures in the densely populated Central North region of Egypt (CNE) for the period 1981-2017. Existing coarse-resolution datasets were evaluated to find the best dataset for the study area to use as a base of the new datasets. The Climate Prediction Centre (CPC) global temperature dataset was found to be the best. The CPC data were interpolated to a spatial resolution of 0.05° latitude/longitude using linear interpolation technique considering the flat topography of the study area. The robust kernel density distribution mapping method was used to correct the bias using observations, and WorldClim v.2 temperature climatology was used to adjust the spatial variability in temperature. The validation of CNE datasets using probability density function skill score and hot and cold extremes tail skill scores showed remarkable improvement in replicating the spatial and temporal variability in observed temperature. Because CNE datasets are the best available high-resolution estimate of daily temperatures, they will be beneficial for climatic and hydrological studies.
    Matched MeSH terms: Likelihood Functions
  10. Hashibah Hamid, Long MM, Sharipah Soaad Syed Yahaya
    Sains Malaysiana, 2017;46:1001-1010.
    The location model proposed in the past is a predictive discriminant rule that can classify new observations into one
    of two predefined groups based on mixtures of continuous and categorical variables. The ability of location model to
    discriminate new observation correctly is highly dependent on the number of multinomial cells created by the number
    of categorical variables. This study conducts a preliminary investigation to show the location model that uses maximum
    likelihood estimation has high misclassification rate up to 45% on average in dealing with more than six categorical
    variables for all 36 data tested. Such model indicated highly incorrect prediction as this model performed badly for
    large categorical variables even with large sample size. To alleviate the high rate of misclassification, a new strategy
    is embedded in the discriminant rule by introducing nonlinear principal component analysis (NPCA) into the classical
    location model (cLM), mainly to handle the large number of categorical variables. This new strategy is investigated
    on some simulation and real datasets through the estimation of misclassification rate using leave-one-out method. The
    results from numerical investigations manifest the feasibility of the proposed model as the misclassification rate is
    dramatically decreased compared to the cLM for all 18 different data settings. A practical application using real dataset
    demonstrates a significant improvement and obtains comparable result among the best methods that are compared. The
    overall findings reveal that the proposed model extended the applicability range of the location model as previously it
    was limited to only six categorical variables to achieve acceptable performance. This study proved that the proposed
    model with new discrimination procedure can be used as an alternative to the problems of mixed variables classification,
    primarily when facing with large categorical variables.
    Matched MeSH terms: Likelihood Functions
  11. 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
  12. Chris Bambey Guure, Noor Akma Ibrahim
    Sains Malaysiana, 2014;43:1433-1437.
    One of the most important lifetime distributions that is used for modelling and analysing data in clinical, life sciences and engineering is the Weibull distribution. The main objective of this paper was to determine the best estimator for the two-parameter Weibull distribution. The methods under consideration are the frequentist maximum likelihood estimator, least square regression estimator and the Bayesian estimator by using two loss functions, which are squared error and linear exponential. Lindley approximation is used to obtain the Bayes estimates. Comparisons are made through simulation study to determine the performance of these methods. Based on the results obtained from this simulation study the Bayesian approach used in estimating the Weibull parameters under linear exponential loss function is found to be superior as compared to the conventional maximum likelihood and least squared methods.
    Matched MeSH terms: Likelihood Functions
  13. Abu Hassan Shaari Mohd Nor, Ahmad Shamiri, Zaidi Isa
    In this research we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model.
    Matched MeSH terms: Likelihood Functions
  14. Seyed Ehsan Saffari, Robiah Adnan
    Sains Malaysiana, 2012;41:1483-1487.
    A Poisson model typically is assumed for count data, but when there are so many zeroes in the response variable, because of overdispersion, a negative binomial regression is suggested as a count regression instead of Poisson regression. In this paper, a zero-inflated negative binomial regression model with right truncation count data was developed. In this model, we considered a response variable and one or more than one explanatory variables. The estimation of regression
    parameters using the maximum likelihood method was discussed and the goodness-of-fit for the regression model was examined. We studied the effects of truncation in terms of parameters estimation, their standard errors and the goodnessof-fit statistics via real data. The results showed a better fit by using a truncated zero-inflated negative binomial regression model when the response variable has many zeros and it was right truncated.
    Matched MeSH terms: Likelihood Functions
  15. 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
  16. Adilah Abdul Ghapor, Yong Zulina Zubairi, Rahmatullah Imon A
    Sains Malaysiana, 2017;46:317-326.
    Missing value problem is common when analysing quantitative data. With the rapid growth of computing capabilities, advanced methods in particular those based on maximum likelihood estimation has been suggested to best handle the missing values problem. In this paper, two modern imputing approaches namely expectation-maximization (EM) and expectation-maximization with bootstrapping (EMB) are proposed in this paper for two kinds of linear functional relationship (LFRM) models, namely LFRM1 for full model and LFRM2 for linear functional relationship model when slope parameter is estimated using a nonparametric approach. The performance of EM and EMB are measured using mean absolute error, root-mean-square error and estimated bias. The results of the simulation study suggested that both EM and EMB methods are applicable to the LFRM with EMB algorithm outperforms the standard EM algorithm. Illustration using a practical example and a real data set is provided.
    Matched MeSH terms: Likelihood Functions
  17. 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
  18. Ibrahim N, Rampal L, Jamil Z, Zain AM
    Prev Med, 2012 Nov;55(5):505-10.
    PMID: 22982947 DOI: 10.1016/j.ypmed.2012.09.003
    OBJECTIVE: Develop, implement and evaluate the effectiveness of a peer-led education program related to HIV/AIDS among university students.
    METHOD:
    DESIGN: randomized controlled trial with 276 university students at Faculty of Medicine and Health Sciences University Putra Malaysia (UPM), Serdang in 2011.
    INTERVENTION: A peer-led education program on HIV prevention by university students.
    OUTCOME: differences in knowledge, attitude and risk behavior practices related to HIV between baselines, immediate follow-up after intervention and after three months.
    RESULTS: Significant improvement in sound knowledge in the intervention group as compared to the control group (Odds ratio, 1.75; 95% CI 1.01, 3.00; p=0.04) and improvement in good attitude related to HIV (Odds ratio 2.22; 95% CI 1.37, 3.61; p=0.01). The odds of high substance risk behavior was significantly reduced in the intervention group as compared to the control group (Odds ratio 0.07; 95% CI 0.02, 0.34; p=0.01). The association between good knowledge and intervention was modified by the different time points (baseline, immediately after intervention and 3 months after intervention), ethnicity and gender.
    CONCLUSION:
    Peer-led education program in HIV prevention improves knowledge, attitude and substance risk behavior. Changes in sexual risk behavior may require a longer follow-up.
    Matched MeSH terms: Likelihood Functions
  19. Cheong HT, Ng KT, Ong LY, Chook JB, Chan KG, Takebe Y, et al.
    PLoS One, 2014;9(10):e111236.
    PMID: 25340817 DOI: 10.1371/journal.pone.0111236
    A novel HIV-1 recombinant clade (CRF51_01B) was recently identified among men who have sex with men (MSM) in Singapore. As cases of sexually transmitted HIV-1 infection increase concurrently in two socioeconomically intimate countries such as Malaysia and Singapore, cross transmission of HIV-1 between said countries is highly probable. In order to investigate the timeline for the emergence of HIV-1 CRF51_01B in Singapore and its possible introduction into Malaysia, 595 HIV-positive subjects recruited in Kuala Lumpur from 2008 to 2012 were screened. Phylogenetic relationship of 485 amplified polymerase gene sequences was determined through neighbour-joining method. Next, near-full length sequences were amplified for genomic sequences inferred to be CRF51_01B and subjected to further analysis implemented through Bayesian Markov chain Monte Carlo (MCMC) sampling and maximum likelihood methods. Based on the near full length genomes, two isolates formed a phylogenetic cluster with CRF51_01B sequences of Singapore origin, sharing identical recombination structure. Spatial and temporal information from Bayesian MCMC coalescent and maximum likelihood analysis of the protease, gp120 and gp41 genes suggest that Singapore is probably the country of origin of CRF51_01B (as early as in the mid-1990s) and featured a Malaysian who acquired the infection through heterosexual contact as host for its ancestral lineages. CRF51_01B then spread rapidly among the MSM in Singapore and Malaysia. Although the importation of CRF51_01B from Singapore to Malaysia is supported by coalescence analysis, the narrow timeframe of the transmission event indicates a closely linked epidemic. Discrepancies in the estimated divergence times suggest that CRF51_01B may have arisen through multiple recombination events from more than one parental lineage. We report the cross transmission of a novel CRF51_01B lineage between countries that involved different sexual risk groups. Understanding the cross-border transmission of HIV-1 involving sexual networks is crucial for effective intervention strategies in the region.
    Matched MeSH terms: Likelihood Functions
  20. 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
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