Displaying publications 81 - 100 of 240 in total

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  1. A unit root test based on the modified least squares estimator
    Wararit Panichkitkosolkul
    Sains Malaysiana, 2014;43:1623-1633.
    A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of type I error and powers of the unit root tests were estimated via Monte Carlo simulation. The simulation results showed that all unit root tests can control the probability of type I error for all situations. The empirical power of the test is higher than the other unit root tests, and Apart from that, the and tests also provide the highest empirical power. As an illustration, the monthly series of U.S. nominal interest rates on three-month treasury bills is analyzed.
    Matched MeSH terms: Probability
  2. Fulltext Land management strategies can increase oil palm plantation use by some terrestrial mammals in Colombia
    Pardo LE, Campbell MJ, Cove MV, Edwards W, Clements GR, Laurance WF
    Sci Rep, 2019 05 24;9(1):7812.
    PMID: 31127172 DOI: 10.1038/s41598-019-44288-y
    While the conservation role of remaining natural habitats in anthropogenic landscapes is clear, the degree to which agricultural matrices impose limitations to animal use is not well understood, but vital to assess species' resilience to land use change. Using an occupancy framework, we evaluated how oil palm plantations affect the occurrence and habitat use of terrestrial mammals in the Colombian Llanos. Further, we evaluated the effect of undergrowth vegetation and proximity to forest on habitat use within plantations. Most species exhibited restricted distributions across the study area, especially in oil palm plantations. Habitat type strongly influenced habitat use of four of the 12 more widely distributed species with oil palm negatively affecting species such as capybara and naked-tailed armadillo. The remaining species showed no apparent effect of habitat type, but oil palm and forest use probabilities varied among species. Overall, generalist mesocarnivores, white-tailed deer, and giant anteater were more likely to use oil palm while the remaining species, including ocelot and lesser anteater, showed preferences for forest. Distance to nearest forest had mixed effects on species habitat use, while understory vegetation facilitated the presence of species using oil palm. Our findings suggest that allowing undergrowth vegetation inside plantations and maintaining nearby riparian corridors would increase the likelihood of terrestrial mammals' occurrence within oil palm landscapes.
    Matched MeSH terms: Probability
  3. Predicting uncertainty of machine learning models for modelling nitrate pollution of groundwater using quantile regression and UNEEC methods
    Rahmati O, Choubin B, Fathabadi A, Coulon F, Soltani E, Shahabi H, et al.
    Sci Total Environ, 2019 Oct 20;688:855-866.
    PMID: 31255823 DOI: 10.1016/j.scitotenv.2019.06.320
    Although estimating the uncertainty of models used for modelling nitrate contamination of groundwater is essential in groundwater management, it has been generally ignored. This issue motivates this research to explore the predictive uncertainty of machine-learning (ML) models in this field of study using two different residuals uncertainty methods: quantile regression (QR) and uncertainty estimation based on local errors and clustering (UNEEC). Prediction-interval coverage probability (PICP), the most important of the statistical measures of uncertainty, was used to evaluate uncertainty. Additionally, three state-of-the-art ML models including support vector machine (SVM), random forest (RF), and k-nearest neighbor (kNN) were selected to spatially model groundwater nitrate concentrations. The models were calibrated with nitrate concentrations from 80 wells (70% of the data) and then validated with nitrate concentrations from 34 wells (30% of the data). Both uncertainty and predictive performance criteria should be considered when comparing and selecting the best model. Results highlight that the kNN model is the best model because not only did it have the lowest uncertainty based on the PICP statistic in both the QR (0.94) and the UNEEC (in all clusters, 0.85-0.91) methods, but it also had predictive performance statistics (RMSE = 10.63, R2 = 0.71) that were relatively similar to RF (RMSE = 10.41, R2 = 0.72) and higher than SVM (RMSE = 13.28, R2 = 0.58). Determining the uncertainty of ML models used for spatially modelling groundwater-nitrate pollution enables managers to achieve better risk-based decision making and consequently increases the reliability and credibility of groundwater-nitrate predictions.
    Matched MeSH terms: Probability
  4. Modelling for determination of fe uptake by brassica chinensis jusl var. Parachinensi (bailey) tsen & lee (flowering white cabbage)
    Ahmad Mahir R, Arfah A, Rozaimah Z, Siti Adyani S, Khairiah J, Ismail B
    Sains Malaysiana, 2017;46:2305-2313.
    The study was conducted to determine the best model suitable for the determination of ferrum uptake in Brassica chinensis (flowering white cabbage). A nonlinear regression model was selected to determine the amount of ferrum absorbed by each part of the Brassica chinensis plant namely the leaves, stems and roots. The Levenberg-Marquardt method was used to perform the nonlinear least square fit. This method employs information on the gradients and hence requires specification of the partial derivatives. A suitable model was obtained from the exponential regression model. The polynomial model was found to be appropriate for leaves, the mono-exponential model was suitable for stems and the simple exponential model for roots. The residual plots and the normal probability plots from each of the models indicated no substantial diagnostic problems, so it can be concluded that the polynomial and exponential regression models provide adequate fit to determine data on heavy metal uptake by the flowering white cabbage.
    Matched MeSH terms: Probability
  5. Maximum likelihood parentage assignment using quantitative genotypes
    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: Probability
  6. Fulltext Probability of Major Depression Classification Based on the SCID, CIDI, and MINI Diagnostic Interviews: A Synthesis of Three Individual Participant Data Meta-Analyses
    Wu Y, Levis B, Ioannidis JPA, Benedetti A, Thombs BD, DEPRESsion Screening Data (DEPRESSD) Collaboration
    Psychother Psychosom, 2021;90(1):28-40.
    PMID: 32814337 DOI: 10.1159/000509283
    INTRODUCTION: Three previous individual participant data meta-analyses (IPDMAs) reported that, compared to the Structured Clinical Interview for the DSM (SCID), alternative reference standards, primarily the Composite International Diagnostic Interview (CIDI) and the Mini International Neuropsychiatric Interview (MINI), tended to misclassify major depression status, when controlling for depression symptom severity. However, there was an important lack of precision in the results.

    OBJECTIVE: To compare the odds of the major depression classification based on the SCID, CIDI, and MINI.

    METHODS: We included and standardized data from 3 IPDMA databases. For each IPDMA, separately, we fitted binomial generalized linear mixed models to compare the adjusted odds ratios (aORs) of major depression classification, controlling for symptom severity and characteristics of participants, and the interaction between interview and symptom severity. Next, we synthesized results using a DerSimonian-Laird random-effects meta-analysis.

    RESULTS: In total, 69,405 participants (7,574 [11%] with major depression) from 212 studies were included. Controlling for symptom severity and participant characteristics, the MINI (74 studies; 25,749 participants) classified major depression more often than the SCID (108 studies; 21,953 participants; aOR 1.46; 95% confidence interval [CI] 1.11-1.92]). Classification odds for the CIDI (30 studies; 21,703 participants) and the SCID did not differ overall (aOR 1.19; 95% CI 0.79-1.75); however, as screening scores increased, the aOR increased less for the CIDI than the SCID (interaction aOR 0.64; 95% CI 0.52-0.80).

    CONCLUSIONS: Compared to the SCID, the MINI classified major depression more often. The odds of the depression classification with the CIDI increased less as symptom levels increased. Interpretation of research that uses diagnostic interviews to classify depression should consider the interview characteristics.

    Matched MeSH terms: Probability
  7. Fulltext Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer
    Tukkee AS, Bin Abdul Wahab NI, Binti Mailah NF, Bin Hassan MK
    PLoS One, 2024;19(2):e0298094.
    PMID: 38330067 DOI: 10.1371/journal.pone.0298094
    Recently, global interest in organizing the functioning of renewable energy resources (RES) through microgrids (MG) has developed, as a unique approach to tackle technical, economic, and environmental difficulties. This study proposes implementing a developed Distributable Resource Management strategy (DRMS) in hybrid Microgrid systems to reduce total net percent cost (TNPC), energy loss (Ploss), and gas emissions (GEM) while taking the cost-benefit index (CBI) and loss of power supply probability (LPSP) as operational constraints. Grey Wolf Optimizer (GWO) was utilized to find the optimal size of the hybrid Microgrid components and calculate the multi-objective function with and without the proposed management method. In addition, a detailed sensitivity analysis of numerous economic and technological parameters was performed to assess system performance. The proposed strategy reduced the system's total net present cost, power loss, and emissions by (1.06%), (8.69%), and (17.19%), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. This study gives a more detailed plan for evaluating the effectiveness of hybrid Microgrid systems from a technical, economic, and environmental perspective.
    Matched MeSH terms: Probability
  8. Fulltext An adaptive handover prediction scheme for seamless mobility based wireless networks
    Sadiq AS, Fisal NB, Ghafoor KZ, Lloret J
    ScientificWorldJournal, 2014;2014:610652.
    PMID: 25574490 DOI: 10.1155/2014/610652
    We propose an adaptive handover prediction (AHP) scheme for seamless mobility based wireless networks. That is, the AHP scheme incorporates fuzzy logic with AP prediction process in order to lend cognitive capability to handover decision making. Selection metrics, including received signal strength, mobile node relative direction towards the access points in the vicinity, and access point load, are collected and considered inputs of the fuzzy decision making system in order to select the best preferable AP around WLANs. The obtained handover decision which is based on the calculated quality cost using fuzzy inference system is also based on adaptable coefficients instead of fixed coefficients. In other words, the mean and the standard deviation of the normalized network prediction metrics of fuzzy inference system, which are collected from available WLANs are obtained adaptively. Accordingly, they are applied as statistical information to adjust or adapt the coefficients of membership functions. In addition, we propose an adjustable weight vector concept for input metrics in order to cope with the continuous, unpredictable variation in their membership degrees. Furthermore, handover decisions are performed in each MN independently after knowing RSS, direction toward APs, and AP load. Finally, performance evaluation of the proposed scheme shows its superiority compared with representatives of the prediction approaches.
    Matched MeSH terms: Probability
  9. Fulltext Population divergence in compensatory growth responses and their costs in sticklebacks
    Ab Ghani NI, Merilä J
    Ecol Evol, 2015 Jan;5(1):7-23.
    PMID: 25628860 DOI: 10.1002/ece3.1342
    Compensatory growth (CG) may be an adaptive mechanism that helps to restore an organisms' growth trajectory and adult size from deviations caused by early life resource limitation. Yet, few studies have investigated the genetic basis of CG potential and existence of genetically based population differentiation in CG potential. We studied population differentiation, genetic basis, and costs of CG potential in nine-spined sticklebacks (Pungitius pungitius) differing in their normal growth patterns. As selection favors large body size in pond and small body size in marine populations, we expected CG to occur in the pond but not in the marine population. By manipulating feeding conditions (viz. high, low and recovery feeding treatments), we found clear evidence for CG in the pond but not in the marine population, as well as evidence for catch-up growth (i.e., size compensation without growth acceleration) in both populations. In the marine population, overcompensation occurred individuals from the recovery treatment grew eventually larger than those from the high feeding treatment. In both populations, the recovery feeding treatment reduced maturation probability. The recovery feeding treatment also reduced survival probability in the marine but not in the pond population. Analysis of interpopulation hybrids further suggested that both genetic and maternal effects contributed to the population differences in CG. Hence, apart from demonstrating intrinsic costs for recovery growth, both genetic and maternal effects were identified to be important modulators of CG responses. The results provide an evidence for adaptive differentiation in recovery growth potential.
    Matched MeSH terms: Probability
  10. Fulltext Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound
    Liu H, Tan T, van Zelst J, Mann R, Karssemeijer N, Platel B
    J Med Imaging (Bellingham), 2014 Jul;1(2):024501.
    PMID: 26158036 DOI: 10.1117/1.JMI.1.2.024501
    We investigated the benefits of incorporating texture features into an existing computer-aided diagnosis (CAD) system for classifying benign and malignant lesions in automated three-dimensional breast ultrasound images. The existing system takes into account 11 different features, describing different lesion properties; however, it does not include texture features. In this work, we expand the system by including texture features based on local binary patterns, gray level co-occurrence matrices, and Gabor filters computed from each lesion to be diagnosed. To deal with the resulting large number of features, we proposed a combination of feature-oriented classifiers combining each group of texture features into a single likelihood, resulting in three additional features used for the final classification. The classification was performed using support vector machine classifiers, and the evaluation was done with 10-fold cross validation on a dataset containing 424 lesions (239 benign and 185 malignant lesions). We compared the classification performance of the CAD system with and without texture features. The area under the receiver operating characteristic curve increased from 0.90 to 0.91 after adding texture features ([Formula: see text]).
    Matched MeSH terms: Probability
  11. FT-IR, NBO, HOMO-LUMO, MEP analysis and molecular docking study of Methyl N-({[2-(2-methoxyacetamido)-4-(phenylsulfanyl)phenyl]amino}[(methoxycarbonyl) imino]methyl)carbamate
    Panicker CY, Varghese HT, Narayana B, Divya K, Sarojini BK, War JA, et al.
    Spectrochim Acta A Mol Biomol Spectrosc, 2015 Sep 5;148:29-42.
    PMID: 25863457 DOI: 10.1016/j.saa.2015.03.064
    The optimized molecular structure, vibrational frequencies, corresponding vibrational assignments of Methyl N-({[2-(2-methoxyacetamido)-4-(phenylsulfanyl) phenyl]amino} [(methoxycarbonyl)imino]methyl)carbamate have been investigated using HF and DFT levels of calculations. The geometrical parameters are in agreement with XRD data. The stability of the molecule arising from hyper-conjugative interaction and charge delocalization has been analyzed using NBO analysis. The HOMO and LUMO analysis is used to determine the charge transfer within the molecule. Molecular electrostatic potential study was also performed. The first and second hyperpolarizability was calculated in order to find its role in nonlinear optics. Molecular docking studies are also reported. Prediction of Activity Spectra analysis of the title compound predicts anthelmintic and antiparasitic activity as the most probable activity with Pa (probability to be active) value of 0.808 and 0.797, respectively. Molecular docking studies show that both the phenyl groups and the carbonyl oxygens of the molecule are crucial for bonding and these results draw us to the conclusion that the compound might exhibit pteridine reductase inhibitory activity.
    Matched MeSH terms: Probability
  12. Fulltext Association of Radiation Doses and Cancer Risks from CT Pulmonary Angiography Examinations in Relation to Body Diameter
    Harun HH, Abdul Karim MK, Abbas Z, Abdul Rahman MA, Sabarudin A, Ng KH
    Diagnostics (Basel), 2020 Sep 09;10(9).
    PMID: 32917029 DOI: 10.3390/diagnostics10090681
    In this study, we aimed to estimate the probability of cancer risk induced by CT pulmonary angiography (CTPA) examinations concerning effective body diameter. One hundred patients who underwent CTPA examinations were recruited as subjects from a single institution in Kuala Lumpur. Subjects were categorized based on their effective diameter size, where 19-25, 25-28, and >28 cm categorized as Groups 1, 2, and 3, respectively. The mean value of the body diameter of the subjects was 26.82 ± 3.12 cm, with no significant differences found between male and female subjects. The risk of cancer in breast, lung, and liver organs was 0.009%, 0.007%, and 0.005% respectively. The volume-weighted CT dose index (CTDIvol) was underestimated, whereas the size-specific dose estimates (SSDEs) provided a more accurate description of the radiation dose and the risk of cancer. CTPA examinations are considered safe but it is essential to implement a protocol optimized following the As Low as Reasonably Achievable (ALARA) principle.
    Matched MeSH terms: Probability
  13. Fulltext Customer waiting time in Labor Department, Kuala Terengganu: A queuing approach
    Norsyafiqah Mohamad, Masnita Misiran, Zahayu Md Yusof
    Journal of Academia Universiti Teknologi MARA Negeri Sembilan, 2020;8(2):22-32.
    MyJurnal
    Businesses adopt queuing mechanism as it can improve efficiency and provide economic use of
    resources. Some business segment that normally adapted queuing theory include assessing staff
    scheduling, productivity, performance, and customers waiting time. This article will adopt queuing
    theory to current service provided by Department of Labour, Kuala Terengganu. As the department is
    committed to provide quality services to its customer, the level of satisfaction and current queueing
    time need to be investigated. To achieve this, four elements in queueing theory – arrival rate, the
    queuing discipline, the service and also the cost structure are utilized. Arrival rate is measured as way
    in which customer arrives at this department and entered for receiving a service. Single server queuing
    model is known as infinite queue length model (exponential service) was used in this study. This model
    is based on certain assumptions about queuing, as the arrivals are described by Poisson probability
    distribution and arrive from infinite population. This study has demonstrated that, majority of the
    customers are dissatisfied with services offered and the major cause of dissatisfaction is the long waiting
    time. Sunday shows the busiest day at Department of Labour, Kuala Terengganu when there are too
    many customers and duty officer faced a hectic day on Sunday, followed by Thursday and Wednesday.
    Department of Labour, Kuala Terengganu needed to do the other internal procedures for reducing
    waiting times and thus ensuring an effective services system. This study recommended of adding a new
    checkout counter and hiring another employee to help duty officer improve the operation at Department
    of Labour, Kuala Terengganu.
    Matched MeSH terms: Probability
  14. Fulltext Developing a digital intervention for cancer survivors: an evidence-, theory- and person-based approach
    Bradbury K, Steele M, Corbett T, Geraghty AWA, Krusche A, Heber E, et al.
    NPJ Digit Med, 2019;2:85.
    PMID: 31508496 DOI: 10.1038/s41746-019-0163-4
    This paper illustrates a rigorous approach to developing digital interventions using an evidence-, theory- and person-based approach. Intervention planning included a rapid scoping review that identified cancer survivors' needs, including barriers and facilitators to intervention success. Review evidence (N = 49 papers) informed the intervention's Guiding Principles, theory-based behavioural analysis and logic model. The intervention was optimised based on feedback on a prototype intervention through interviews (N = 96) with cancer survivors and focus groups with NHS staff and cancer charity workers (N = 31). Interviews with cancer survivors highlighted barriers to engagement, such as concerns about physical activity worsening fatigue. Focus groups highlighted concerns about support appointment length and how to support distressed participants. Feedback informed intervention modifications, to maximise acceptability, feasibility and likelihood of behaviour change. Our systematic method for understanding user views enabled us to anticipate and address important barriers to engagement. This methodology may be useful to others developing digital interventions.
    Matched MeSH terms: Probability
  15. Fulltext The development of Adaptive Neuro-Fuzzy Inference System model to diagnosis diabetes disease data set
    Mamuda M, Sathasivam S
    MATEMATIKA, 2017;33(1):11-19.
    MyJurnal
    Medical diagnosis is the extrapolation of the future course and outcome of a disease and a sign of the likelihood of recovery from that disease. Diagnosis is important because it is used to guide the type and intensity of the medication to be administered to patients. A hybrid intelligent system that combines the fuzzy logic qualitative approach and Adaptive Neural Networks (ANNs) with the capabilities of getting a better performance is required. In this paper, a method for modeling the survival of diabetes patient by utilizing the application of the Adaptive NeuroFuzzy Inference System (ANFIS) is introduced with the aim of turning data into knowledge that can be understood by people. The ANFIS approach implements the hybrid learning algorithm that combines the gradient descent algorithm and a recursive least square error algorithm to update the antecedent and consequent parameters. The combination of fuzzy inference that will represent knowledge in an interpretable manner and the learning ability of neural network that can adjust the membership functions of the parameters and linguistic rules from data will be considered. The proposed framework can be applied to estimate the risk and survival curve between different diagnostic factors and survival time with the explanation capabilities.
    Matched MeSH terms: Probability
  16. Fulltext Effect of Biodegradable Binder Properties and Operating Conditions on Growth of Urea Particles in a Fluidized Bed Granulator
    Zhalehrajabi E, Lau KK, Ku Shaari KZ, Zahraee SM, Seyedin SH, Azeem B, et al.
    Materials (Basel), 2019 Jul 20;12(14).
    PMID: 31330846 DOI: 10.3390/ma12142320
    Granulation is an important step during the production of urea granules. Most of the commercial binders used for granulation are toxic and non-biodegradable. In this study, a fully biodegradable and cost-effective starch-based binder is used for urea granulation in a fluidized bed granulator. The effect of binder properties such as viscosity, surface tension, contact angle, penetration time, and liquid bridge bonding force on granulation performance is studied. In addition, the effect of fluidized bed process parameters such as fluidizing air inlet velocity, air temperature, weight of primary urea particles, binder spray rate, and binder concentration is also evaluated using response surface methodology. Based on the results, binder with higher concentration demonstrates higher viscosity and higher penetration time that potentially enhance the granulation performance. The viscous Stokes number for binder with higher concentration is lower than critical Stokes number that increases coalescence rate. Higher viscosity and lower restitution coefficient of urea particles result in elastic losses and subsequent successful coalescence. Statistical analysis indicate that air velocity, air temperature, and weight of primary urea particles have major effects on granulation performance. Higher air velocity increases probability of collision, whereby lower temperature prevents binder to be dried up prior to collision. Findings of this study can be useful for process scale-up and industrial application.
    Matched MeSH terms: Probability
  17. Fulltext The occurrence and distribution of bats in Qatar
    Abdulrahman M, Gardner A, Yamaguchi N
    J Arid Environ, 2021 Feb;185:104379.
    PMID: 33162623 DOI: 10.1016/j.jaridenv.2020.104379
    The distributions of bat species in Qatar have not previously been recorded. We conducted the first nation-wide survey of bats in Qatar. Based on sonogram analysis, we identified Asellia tridens, Otonycteris hemprichii, and Pipistrellus kuhlii. The most commonly recorded species was Asellia tridens, the only species recorded in the northern half of the country. Contrary to our prediction, the likelihood of recording bats was not higher in the northern half of the country where there are many irrigated farms. The distributions of the bat species may result from differences in human land use and disturbance, and from the distance to the main body of the Arabian Peninsula. A key habitat feature for Asellia tridens and Otonycteris hemprichii may be the presence of roosting sites in less disturbed sinkholes/caves, which are therefore crucial for bat conservation.
    Matched MeSH terms: Probability
  18. Fulltext Sociodemographic factors as determinants of fruit and vegetable consumption in Malaysia
    Lung, Wei Foon, Yong, Kang Cheah, Nor Azam Abdul Razak
    Jurnal Sains Kesihatan Malaysia, 2020;18(2):19-29.
    MyJurnal
    The present study examines the factors affecting fruit and vegetable (FV) consumption in Malaysia. A nationally representative data that consists of a large sample size is used. Hence, the findings can provide inferential information. The present study uses secondary data from the Malaysian Household Expenditure Survey 2009/2010. The survey was carried out using a two-stage stratified sampling. The first stage was based on Enumeration Blocks, while the second stage was based on Living Quarters. A lognormal hurdle model is used to estimate the consumption decision and amount decision of FV across ethnic groups. The results suggest that household size, income, gender, marital status, age and education play significant roles in FV consumption. The probability of consuming FV and amount spent increase with household size (p
    Matched MeSH terms: Probability
  19. Fulltext Covert Cognition in Disorders of Consciousness: A Meta-Analysis
    Schnakers C, Hirsch M, Noé E, Llorens R, Lejeune N, Veeramuthu V, et al.
    Brain Sci, 2020 Dec 02;10(12).
    PMID: 33276451 DOI: 10.3390/brainsci10120930
    Covert cognition in patients with disorders of consciousness represents a real diagnostic conundrum for clinicians. In this meta-analysis, our main objective was to identify clinical and demographic variables that are more likely to be associated with responding to an active paradigm. Among 2018 citations found on PubMed, 60 observational studies were found relevant. Based on the QUADAS-2, 49 studies were considered. Data from 25 publications were extracted and included in the meta-analysis. Most of these studies used electrophysiology as well as counting tasks or mental imagery. According to our statistical analysis, patients clinically diagnosed as being in a vegetative state and in a minimally conscious state minus (MCS-) show similar likelihood in responding to active paradigm and responders are most likely suffering from a traumatic brain injury. In the future, multi-centric studies should be performed in order to increase sample size, with similar methodologies and include structural and functional neuroimaging in order to identify cerebral markers related to such a challenging diagnosis.
    Matched MeSH terms: Probability
  20. Fulltext Relative age effect in U-16 Asian Championship Soccer Tournament
    Pathmanathan K. Suppiah, Jeffrey Low Fook Lee, Abdul Muiz Nor Azmi, Hasnol Noordin, Rabiu Muazu Musa
    Movement Health & Exercise, 2020;9(1):1-8.
    MyJurnal
    Athletes born at the beginning of the year may present advantages in terms of physical characteristics, motor ability or cognitive knowledge that could increase their chances for selection against their peers. This circumstance could lead to the over-representation of older athletes in an age-defined competition, a phenomenon commonly referred to as relative age effect (RAE). Although, a number of studies have demonstrated that RAE is apparent in youth soccer, such studies rarely investigate the performance advantage that likely exists across the birth month of the athletes. The current study aims to determine the presence of RAE in the under 16 Asian Football Confederation Championship (AFC); investigate the effect of RAE on the team qualification success; as well as ascertain the existence of RAE in choice of playing position amongst the soccer players. Data for the 2018 AFC under 16 qualifications matches were obtained from the AFC. A total of 719 players from 32 countries participated in the qualification competitions. Chi-square for goodness fit is used to determine the existence of the RAE across the players’ month of birth while logistic regression is applied to analyze the differences of the quartiles’ distribution with respect to the quartile, qualification status (qualifier or non-qualifier) as well as the playing position of the players. The results demonstrate the presence of RAE in the AFC under 16 soccer tournaments [χ2(4) = 21.53; p < 0.001] with the largest number of older players dominating the qualified team. Likewise, a substantial difference is observed with regards to the quartile and various playing positions of the players at p < 0.05.
    Matched MeSH terms: Probability
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