Displaying publications 1 - 20 of 92 in total

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  1. Foo CH
    Math Biosci Eng, 2023 Jul 03;20(8):14487-14501.
    PMID: 37679145 DOI: 10.3934/mbe.2023648
    Crustaceans exhibit discontinuous growth as they shed hard shells periodically. Fundamentally, the growth of crustaceans is typically assessed through two key components, length increase after molting (LI) and time intervals between consecutive molts (TI). In this article, we propose a unified likelihood approach that combines a generalized additive model and a Cox proportional hazard model to estimate the parameters of LI and TI separately in crustaceans. This approach captures the observed discontinuity in individuals, providing a comprehensive understanding of crustacean growth patterns. Our study focuses on 75 ornate rock lobsters (Panulirus ornatus) off the Torres Strait in northeastern Australia. Through a simulation study, we demonstrate the effectiveness of the proposed models in characterizing the discontinuity with a continuous growth curve at the population level.
    Matched MeSH terms: Likelihood Functions
  2. Trimarsanto H, Amato R, Pearson RD, Sutanto E, Noviyanti R, Trianty L, et al.
    Commun Biol, 2022 Dec 23;5(1):1411.
    PMID: 36564617 DOI: 10.1038/s42003-022-04352-2
    Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection's country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs.
    Matched MeSH terms: Likelihood Functions
  3. Selvaraj S, Naing NN, Wan-Arfah N, de Abreu MHNG
    PMID: 34360201 DOI: 10.3390/ijerph18157910
    The aim of this study was to evaluate the performance of a set of sociodemographic and habits measures on estimating periodontal disease among south Indian adults. This cross-sectional study was carried out among 288 individuals above 18 years old in Tamil Nadu, India. The outcome of the study was periodontal disease, measured by WHO criteria. The covariates were age, ethnicity, smoking and alcohol habit. The assessment of factors predicting periodontal disease was carried out by multiple logistic regression analysis using R version 3.6.1. The demographic factors like age group (AOR = 3.56; 95% CI 1.69-7.85), ethnicity (AOR = 6.07; 95% CI 2.27-18.37), non-alcoholic (AOR = 0.31; 95% CI 0.13-0.64) and non-smoking (AOR = 0.33; 95% CI 0.15-0.67) were found to be associated with the outcome. The maximum log likelihood estimate value was -30.5 and AIC was 385 for the final model, respectively. Receiver operating characteristic (ROC) curve for the periodontal disease was 0.737. We can conclude that sociodemographic factors and habits were useful for predicting periodontal diseases.
    Matched MeSH terms: Likelihood Functions
  4. 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
  5. 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
  6. Hamilton MG
    Heredity (Edinb), 2021 06;126(6):884-895.
    PMID: 33692533 DOI: 10.1038/s41437-021-00421-0
    The cost of parentage assignment precludes its application in many selective breeding programmes and molecular ecology studies, and/or limits the circumstances or number of individuals to which it is applied. Pooling samples from more than one individual, and using appropriate genetic markers and algorithms to determine parental contributions to pools, is one means of reducing the cost of parentage assignment. This paper describes and validates a novel maximum likelihood (ML) parentage-assignment method, that can be used to accurately assign parentage to pooled samples of multiple individuals-previously published ML methods are applicable to samples of single individuals only-using low-density single nucleotide polymorphism (SNP) 'quantitative' (also referred to as 'continuous') genotype data. It is demonstrated with simulated data that, when applied to pools, this 'quantitative maximum likelihood' method assigns parentage with greater accuracy than established maximum likelihood parentage-assignment approaches, which rely on accurate discrete genotype calls; exclusion methods; and estimating parental contributions to pools by solving the weighted least squares problem. Quantitative maximum likelihood can be applied to pools generated using either a 'pooling-for-individual-parentage-assignment' approach, whereby each individual in a pool is tagged or traceable and from a known and mutually exclusive set of possible parents; or a 'pooling-by-phenotype' approach, whereby individuals of the same, or similar, phenotype/s are pooled. Although computationally intensive when applied to large pools, quantitative maximum likelihood has the potential to substantially reduce the cost of parentage assignment, even if applied to pools comprised of few individuals.
    Matched MeSH terms: Likelihood Functions
  7. 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
  8. Nur Aisyah Atikah Alizan, Sarah S. Zakaria
    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
  9. 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
  10. Nayeri ND, Goudarzian AH, Herth K, Naghavi N, Nia HS, Yaghoobzadeh A, et al.
    Int J Health Sci (Qassim), 2020 9 22;14(5):50-57.
    PMID: 32952505
    Objective: The psychological construct of hope is an important determinant for mental health and well-being. The availability of valid and reliable instruments to measure hope is, therefore, critical. Despite a large number of psychometric studies on the Herth Hope Index (HHI), its construct validity has not yet been determined. Therefore, this paper aimed to conduct a systematic review of the psychometric properties of the HHI.

    Methods: Databases such as PubMed, Science Direct, Google Scholar, Magiran, SID, IranDoc, and IranMedex were evaluated systematically using the terms "HHI," "psychometric," "validity," "reliability," and related terms (with the use of OR and AND operators) and no restrictions on the year of publication. A total of 13 eligible studies were found published between 1992 and 2018 in the USA, Portugal, Switzerland, Iran, Germany, Petersburg, Japan, the Netherlands, Lima, Peru, and Norway. The methodology used in the available studies included principal component analysis (n = 6), maximum likelihood estimation (n = 5), and principal axis factoring (n = 1). One study did not point the methodology.

    Results: Four studies reported the total extracted variances to be less than 50%, six studies reported variance between 50% and 60%, and three papers reported variance that exceeded 60%. Of the papers that examined the factor structure of the HHI, two studies reported a one-factor solution, seven reported two factors, and four reported a three-factor solution. Although the HHI is the most widely translated and psychometrically tested tool in languages other than English, psychometric variations in factor solutions remain inconsistent.

    Conclusion: Findings highlight the need for future research that appraises the validity of the HHI in different countries, and how the measure relates to other scales that evaluate hope.

    Matched MeSH terms: Likelihood Functions
  11. 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
  12. 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
  13. Müller-Sienerth N, Shilts J, Kadir KA, Yman V, Homann MV, Asghar M, et al.
    Malar J, 2020 Jan 17;19(1):31.
    PMID: 31952523 DOI: 10.1186/s12936-020-3111-5
    BACKGROUND: Malaria remains a global health problem and accurate surveillance of Plasmodium parasites that are responsible for this disease is required to guide the most effective distribution of control measures. Serological surveillance will be particularly important in areas of low or periodic transmission because patient antibody responses can provide a measure of historical exposure. While methods for detecting host antibody responses to Plasmodium falciparum and Plasmodium vivax are well established, development of serological assays for Plasmodium knowlesi, Plasmodium ovale and Plasmodium malariae have been inhibited by a lack of immunodiagnostic candidates due to the limited availability of genomic information.

    METHODS: Using the recently completed genome sequences from P. malariae, P. ovale and P. knowlesi, a set of 33 candidate cell surface and secreted blood-stage antigens was selected and expressed in a recombinant form using a mammalian expression system. These proteins were added to an existing panel of antigens from P. falciparum and P. vivax and the immunoreactivity of IgG, IgM and IgA immunoglobulins from individuals diagnosed with infections to each of the five different Plasmodium species was evaluated by ELISA. Logistic regression modelling was used to quantify the ability of the responses to determine prior exposure to the different Plasmodium species.

    RESULTS: Using sera from European travellers with diagnosed Plasmodium infections, antigens showing species-specific immunoreactivity were identified to select a panel of 22 proteins from five Plasmodium species for serological profiling. The immunoreactivity to the antigens in the panel of sera taken from travellers and individuals living in malaria-endemic regions with diagnosed infections showed moderate power to predict infections by each species, including P. ovale, P. malariae and P. knowlesi. Using a larger set of patient samples and logistic regression modelling it was shown that exposure to P. knowlesi could be accurately detected (AUC = 91%) using an antigen panel consisting of the P. knowlesi orthologues of MSP10, P12 and P38.

    CONCLUSIONS: Using the recent availability of genome sequences to all human-infective Plasmodium spp. parasites and a method of expressing Plasmodium proteins in a secreted functional form, an antigen panel has been compiled that will be useful to determine exposure to these parasites.

    Matched MeSH terms: Likelihood Functions
  14. 'Aaishah Radziah Jamaludin, Fadhilah Yusof, Suhartono
    MATEMATIKA, 2020;36(1):15-30.
    MyJurnal
    Johor Bahru with its rapid development where pollution is an issue that needs to be considered because it has contributed to the number of asthma cases in this area. Therefore, the goal of this study is to investigate the behaviour of asthma disease in Johor Bahru by count analysis approach namely; Poisson Integer Generalized Autoregressive Conditional Heteroscedasticity (Poisson-INGARCH) and Negative Binomial INGARCH (NB-INGARCH) with identity and log link function. Intervention analysis was conducted since the outbreak in the asthma data for the period of July 2012 to July 2013. This occurs perhaps due to the extremely bad haze in Johor Bahru from Indonesian fires. The estimation of the parameter will be done by quasi-maximum likelihood estimation. Model assessment was evaluated from the Pearson residuals, cumulative periodogram, the probability integral transform (PIT) histogram, log-likelihood value, Akaike’s Information Criterion (AIC) and Bayesian information criterion (BIC). Our result shows that NB-INGARCH with identity and log link function is adequate in representing the asthma data with uncorrelated Pearson residuals, higher in log likelihood, the PIT exhibits normality yet the lowest AIC and BIC. However, in terms of forecasting accuracy, NB-INGARCH with identity link function performed better with the smaller RMSE (8.54) for the sample data. Therefore, NB-INGARCH with identity link function can be applied as the prediction model for asthma disease in Johor Bahru. Ideally, this outcome can assist the Department of Health in executing counteractive action and early planning to curb asthma diseases in Johor Bahru.
    Matched MeSH terms: Likelihood Functions
  15. Barki N, Choudhry FR, Munawar K
    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
  16. 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
  17. Parsons MT, Tudini E, Li H, Hahnen E, Wappenschmidt B, Feliubadaló L, et al.
    Hum Mutat, 2019 Sep;40(9):1557-1578.
    PMID: 31131967 DOI: 10.1002/humu.23818
    The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.
    Matched MeSH terms: Likelihood Functions
  18. 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
  19. Balla SB, Banda TR, Galic I, N NM, Naishadham PP
    Forensic Sci Int, 2019 Apr;297:243-248.
    PMID: 30844636 DOI: 10.1016/j.forsciint.2019.02.009
    The aims of the present study were to validate the discriminatory potential of Cameriere's third molar maturity index (I3M) cut-off value of I3M 
    Matched MeSH terms: Likelihood Functions
  20. 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
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