Displaying publications 1 - 20 of 36 in total

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  1. Chong VH, Telisinghe PU, Lim E, Abdullah MS, Idris F, Chong CF
    Asian Pac J Cancer Prev, 2015;16(16):7097-101.
    PMID: 26514496
    BACKGROUND: Nasopharyngeal carcinoma (NPC) is linked to Epstein Barr virus infection and is particularly common in the Far East, particularly among some Chinese groups. Certain ethnicities have been reported to have low incidence of NPC. This study looked at NPC in Brunei Darussalam over a three decade period.

    MATERIALS AND METHODS: The cancer registry from 1986 to 2014 maintained by the State Laboratory was retrospectively reviewed. The age standardized rates (ASR) and the age specific incidence rates (ASIR) were calculated. Non NPC tumors were excluded from the study.

    RESULTS: Altogether, there were a total of 450 NPC cases diagnosed accounting for 4.4% of all total cancer cases over the study period, declining from 10.3% in 1986-1990 to 2.3% in 2011-2014. The most common tumor type was the undifferentiated carcinoma (96.4%). The case characteristics were mean age 50.4 ± 14.4 years old, male 69%, and predominately Malays 74.4%, followed by Chinese 16.7%. The mean age of diagnosis increased over the study period from 45.6 ± 17.1 years (1986-1989) to 54.1 ± 12.5 years (ANOVA, p<0.01 for trend). There were no differences in the mean age of diagnosis between the ethnic groups or genders. The ASR showed a declining trend from 11.1 per 100,000 in 1986-1990 to 5.95 per 100,000 in 2011-2014, similar trends been observedfor both genders. Among the age groups, declining trends were seen in all the other age groups apart from the >70 years group. The overall ASRs for the Malays and Chinese were 7.92/100,000 and 8.83/100,000 respectively, both showing declining trends.

    CONCLUSIONS: The incidence of NPC in Brunei Darussalam is comparable to rates reported from Singapore and Malaysia, but higher than rates reported from the other Southeast Asian nations. Unlike higher rates reported for Chinese compared to the Malays in other countries, the rates between the Malays and Chinese in our study was comparable. Importantly, the ASR is declining overall and for both genders and ethnic groups.

    Matched MeSH terms: Spatio-Temporal Analysis
  2. Chan TC, Hwang JS, Chen RH, King CC, Chiang PH
    BMC Public Health, 2014 Jan 08;14:11.
    PMID: 24400725 DOI: 10.1186/1471-2458-14-11
    BACKGROUND: Severe epidemics of enterovirus have occurred frequently in Malaysia, Singapore, Taiwan, Cambodia, and China, involving cases of pulmonary edema, hemorrhage and encephalitis, and an effective vaccine has not been available. The specific aim of this study was to understand the epidemiological characteristics of mild and severe enterovirus cases through integrated surveillance data.

    METHODS: All enterovirus cases in Taiwan over almost ten years from three main databases, including national notifiable diseases surveillance, sentinel physician surveillance and laboratory surveillance programs from July 1, 1999 to December 31, 2008 were analyzed. The Pearson's correlation coefficient was applied for measuring the consistency of the trends in the cases between different surveillance systems. Cross correlation analysis in a time series model was applied for examining the capability to predict severe enterovirus infections. Poisson temporal, spatial and space-time scan statistics were used for identifying the most likely clusters of severe enterovirus outbreaks. The directional distribution method with two standard deviations of ellipse was applied to measure the size and the movement of the epidemic.

    RESULTS: The secular trend showed that the number of severe EV cases peaked in 2008, and the number of mild EV cases was significantly correlated with that of severe ones occurring in the same week [r = 0.553, p spatio-temporal clusters in June 2008, the mild cases had begun to rise since May 2008, and the outbreak spread from south to north.

    CONCLUSIONS: Local public health professionals can monitor the temporal and spatial trends plus spatio-temporal clusters and isolation rate of EV-71 in mild and severe EV cases in a community when virus transmission is high, to provide early warning signals and to prevent subsequent severe epidemics.

    Matched MeSH terms: Spatio-Temporal Analysis
  3. Oong XY, Ng KT, Takebe Y, Ng LJ, Chan KG, Chook JB, et al.
    Emerg Microbes Infect, 2017 Jan 04;6(1):e3.
    PMID: 28050020 DOI: 10.1038/emi.2016.132
    Human coronavirus OC43 (HCoV-OC43) is commonly associated with respiratory tract infections in humans, with five genetically distinct genotypes (A to E) described so far. In this study, we obtained the full-length genomes of HCoV-OC43 strains from two previously unrecognized lineages identified among patients presenting with severe upper respiratory tract symptoms in a cross-sectional molecular surveillance study in Kuala Lumpur, Malaysia, between 2012 and 2013. Phylogenetic, recombination and comparative genomic analyses revealed two distinct clusters diverging from a genotype D-like common ancestor through recombination with a putative genotype A-like lineage in the non-structural protein (nsp) 10 gene. Signature amino acid substitutions and a glycine residue insertion at the N-terminal domain of the S1 subunit of the spike gene, among others, exhibited further distinction in a recombination pattern, to which these clusters were classified as genotypes F and G. The phylogeographic mapping of the global spike gene indicated that the genetically similar HCoV-OC43 genotypes F and G strains were potentially circulating in China, Japan, Thailand and Europe as early as the late 2000s. The transmission network construction based on the TN93 pairwise genetic distance revealed the emergence and persistence of multiple sub-epidemic clusters of the highly prevalent genotype D and its descendant genotypes F and G, which contributed to the spread of HCoV-OC43 in the region. Finally, a more consistent nomenclature system for non-recombinant and recombinant HCoV-OC43 lineages is proposed, taking into account genetic recombination as an important feature in HCoV evolution and classification.
    Matched MeSH terms: Spatio-Temporal Analysis
  4. Sheikhy Narany T, Ramli MF, Aris AZ, Sulaiman WN, Fakharian K
    Environ Monit Assess, 2014 Sep;186(9):5797-815.
    PMID: 24891071 DOI: 10.1007/s10661-014-3820-8
    In recent years, groundwater quality has become a global concern due to its effect on human life and natural ecosystems. To assess the groundwater quality in the Amol-Babol Plain, a total of 308 water samples were collected during wet and dry seasons in 2009. The samples were analysed for their physico-chemical and biological constituents. Multivariate statistical analysis and geostatistical techniques were applied to assess the spatial and temporal variabilities of groundwater quality and to identify the main factors and sources of contamination. Principal component analysis (PCA) revealed that seven factors explained around 75% of the total variance, which highlighted salinity, hardness and biological pollution as the dominant factors affecting the groundwater quality in the Plain. Two-way analysis of variance (ANOVA) was conducted on the dataset to evaluate the spatio-temporal variation. The results showed that there were no significant temporal variations between the two seasons, which explained the similarity between six component factors in dry and wet seasons based on the PCA results. There are also significant spatial differences (p > 0.05) of the parameters under study, including salinity, potassium, sulphate and dissolved oxygen in the plain. The least significant difference (LSD) test revealed that groundwater salinity in the eastern region is significantly different to the central and western side of the study area. Finally, multivariate analysis and geostatistical techniques were combined as an effective method for demonstrating the spatial structure of multivariate spatial data. It was concluded that multiple natural processes and anthropogenic activities were the main sources of groundwater salinization, hardness and microbiological contamination of the study area.
    Matched MeSH terms: Spatio-Temporal Analysis
  5. Lim JH, Lee CW, Kudo I
    Environ Monit Assess, 2015 May;187(5):246.
    PMID: 25864082 DOI: 10.1007/s10661-015-4487-5
    Phytoplankton growth (μ) and grazing loss (g) rates were measured monthly by the Landry-Hassett dilution method over a 2-year period at both estuarine (Klang) and coastal water (Port Dickson) systems along the Straits of Malacca. Chlorophyll a (Chl a) concentration ranged from 0.20 to 4.47 μg L(-1) at Klang except on two occasions when Chl a spiked above 10 μg L(-1). In contrast, Chl a concentrations were relatively stable at Port Dickson (0.14 to 2.76 μg L(-1)). From the rate measurements, μ was higher (t = 2.01, df = 43, p  0.80). g ranged from 0.30 to 1.50 and 0.21 to 1.51 day(-1) at Klang and Port Dickson, respectively. In this study, grazing loss was coupled to phytoplankton growth, and the ratio of g/μ or grazing pressure which estimates the proportion of primary production grazed was 50% at Klang and lower than at Port Dickson (68%; t = 2.213, df = 36, p 
    Matched MeSH terms: Spatio-Temporal Analysis
  6. Aburas MM, Ho YM, Ramli MF, Ash'aari ZH
    Environ Monit Assess, 2018 Feb 20;190(3):156.
    PMID: 29464400 DOI: 10.1007/s10661-018-6522-9
    The identification of spatio-temporal patterns of the urban growth phenomenon has become one of the most significant challenges in monitoring and assessing current and future trends of the urban growth issue. Therefore, spatio-temporal and quantitative techniques should be used hand in hand for a deeper understanding of various aspects of urban growth. The main purpose of this study is to monitor and assess the significant patterns of urban growth in Seremban using a spatio-temporal built-up area analysis. The concentric circles approach was used to measure the compactness and dispersion of built-up area by employing Shannon's Entropy method. The spatial directions approach was also utilised to measure the sustainability and speed of development, while the gradient approach was used to measure urban dynamics by employing landscape matrices. The overall results confirm that urban growth in Seremban is dispersed, unbalanced and unsustainable with a rapid speed of regional development. The main contribution of using existing methods with other methods is to provide several spatial and statistical dimensions that can help researchers, decision makers and local authorities understand the trend of growth and its patterns in order to take the appropriate decisions for future urban planning. For example, Shannon's Entropy findings indicate a high value of dispersion between the years 1990 and 2000 and from 2010 to 2016 with a growth rate of approximately 94 and 14%, respectively. Therefore, these results can help and support decision makers to implement alternative urban forms such as the compactness form to achieve an urban form that is more suitable and sustainable. The results of this study confirm the importance of using spatio-temporal built-up area and quantitative analysis to protect the sustainability of land use, as well as to improve the urban planning system via the effective monitoring and assessment of urban growth trends and patterns.
    Matched MeSH terms: Spatio-Temporal Analysis
  7. Nguyen TTN, Pham HV, Lasko K, Bui MT, Laffly D, Jourdan A, et al.
    Environ Pollut, 2019 Dec;255(Pt 1):113106.
    PMID: 31541826 DOI: 10.1016/j.envpol.2019.113106
    Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R2 = 0.81) and VIIRS AOD (R2 = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.
    Matched MeSH terms: Spatio-Temporal Analysis*
  8. Tan KK, Nellis S, Zulkifle NI, Sulaiman S, AbuBakar S
    Epidemiol Infect, 2018 10;146(13):1635-1641.
    PMID: 29860959 DOI: 10.1017/S0950268818001425
    Dengue virus type 3 genotype III (DENV-3/III) is widely distributed in most dengue-endemic regions. It emerged in Malaysia in 2008 and autochthonously spread in the midst of endemic DENV-3/I circulation. The spread, however, was limited and the virus did not cause any major outbreak. Spatiotemporal distribution study of DENV-3 over the period between 2005 and 2011 revealed that dengue cases involving DENV-3/III occurred mostly in areas without pre-existing circulating DENV-3. Neutralisation assays performed using sera of patients with the respective infection showed that the DENV-3/III viruses can be effectively neutralised by sera of patients with DENV-3 infection (50% foci reduction neutralisation titres (FRNT50) > 1300). Sera of patients with DENV-1 infection (FRNT50 ⩾ 190), but not sera of patients with DENV-2 infection (FRNT50 ⩽ 50), were also able to neutralise the virus. These findings highlight the possibility that the pre-existing homotypic DENV-3 and the cross-reacting heterotypic DENV-1 antibody responses could play a role in mitigating a major outbreak involving DENV-3/III in the Klang Valley, Malaysia.
    Matched MeSH terms: Spatio-Temporal Analysis
  9. Mortaza N, Abu Osman NA, Mehdikhani N
    Eur J Phys Rehabil Med, 2014 Dec;50(6):677-91.
    PMID: 24831570
    Fall is a common and a major cause of injuries. It is important to find elderlies who are prone to falls. The majority of serious falls occur during walking among the older adults. Analyzing the spatio-temporal parameters of walking is an easy way of assessment in the clinical setting, but is it capable of distinguishing a faller from a non-faller elderly? Through a systematic review of the literature, the objective of this systematic review was to identify and summarize the differences in the spatio-temporal parameters of walking in elderly fallers and non-fallers and to find out if these parameters are capable of distinguishing a faller from a non-faller. All original research articles which compared any special or temporal walking parameters in faller and non-faller elderlies were systematically searched within the Scopus and Embase databases. Effect size analysis was also done to standardize findings and compare the gait parameters of fallers and non-fallers across the selected studies. The electronic search led to 5381 articles. After title and abstract screening 30 articles were chosen; further assessment of the full texts led to 17 eligible articles for inclusion in the review. It seems that temporal measurements are more sensitive to the detection of risk of fall in elderly people. The results of the 17 selected studies showed that fallers have a tendency toward a slower walking speed and cadence, longer stride time, and double support duration. Also, fallers showed shorter stride and step length, wider step width and more variability in spatio-temporal parameters of gait. According to the effect size analysis, step length, gait speed, stride length and stance time variability were respectively more capable of differentiating faller from non-faller elderlies. However, because of the difference of methodology and number of studies which investigated each parameter, these results are prone to imprecision. Spatio-temporal analysis of level walking is not sufficient and cannot act as a reliable predictor of falls in elderly individuals.
    Matched MeSH terms: Spatio-Temporal Analysis
  10. Ling CY, Gruebner O, Krämer A, Lakes T
    Geospat Health, 2014 Nov;9(1):131-40.
    PMID: 25545931
    Spatio-temporal patterns of dengue risk in Malaysia were studied both at the address and the sub-district level in the province of Selangor and the Federal Territory of Kuala Lumpur. We geocoded laboratory-confirmed dengue cases from the years 2008 to 2010 at the address level and further aggregated the cases in proportion to the population at risk at the sub-district level. Kulldorff's spatial scan statistic was applied for the investigation that identified changing spatial patterns of dengue cases at both levels. At the address level, spatio-temporal clusters of dengue cases were concentrated at the central and south-eastern part of the study area in the early part of the years studied. Analyses at the sub-district level revealed a consistent spatial clustering of a high number of cases proportional to the population at risk. Linking both levels assisted in the identification of differences and confirmed the presence of areas at high risk for dengue infection. Our results suggest that the observed dengue cases had both a spatial and a temporal epidemiological component, which needs to be acknowledged and addressed to develop efficient control measures, including spatially explicit vector control. Our findings highlight the importance of detailed geographical analysis of disease cases in heterogeneous environments with a focus on clustered populations at different spatial and temporal scales. We conclude that bringing together information on the spatio-temporal distribution of dengue cases with a deeper insight of linkages between dengue risk, climate factors and land use constitutes an important step towards the development of an effective risk management strategy.
    Matched MeSH terms: Spatio-Temporal Analysis
  11. Sham NM, Krishnarajah I, Ibrahim NA, Lye MS
    Geospat Health, 2014 May;8(2):503-7.
    PMID: 24893027
    Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.
    Matched MeSH terms: Spatio-Temporal Analysis
  12. Phang WK, Hamid MHA, Jelip J, Mudin RN, Chuang TW, Lau YL, et al.
    PMID: 33322414 DOI: 10.3390/ijerph17249271
    The life-threatening zoonotic malaria cases caused by Plasmodium knowlesi in Malaysia has recently been reported to be the highest among all malaria cases; however, previous studies have mainly focused on the transmission of P. knowlesi in Malaysian Borneo (East Malaysia). This study aimed to describe the transmission patterns of P. knowlesi infection in Peninsular Malaysia (West Malaysia). The spatial distribution of P. knowlesi was mapped across Peninsular Malaysia using Geographic Information System techniques. Local indicators of spatial associations were used to evaluate spatial patterns of P. knowlesi incidence. Seasonal autoregressive integrated moving average models were utilized to analyze the monthly incidence of knowlesi malaria in the hotspot region from 2012 to 2017 and to forecast subsequent incidence in 2018. Spatial analysis revealed that hotspots were clustered in the central-northern region of Peninsular Malaysia. Time series analysis revealed the strong seasonality of transmission from January to March. This study provides fundamental information on the spatial distribution and temporal dynamic of P. knowlesi in Peninsular Malaysia from 2011 to 2018. Current control policy should consider different strategies to prevent the transmission of both human and zoonotic malaria, particularly in the hotspot region, to ensure a successful elimination of malaria in the future.
    Matched MeSH terms: Spatio-Temporal Analysis
  13. GBD 2017 Child and Adolescent Health Collaborators, Reiner RC, Olsen HE, Ikeda CT, Echko MM, Ballestreros KE, et al.
    JAMA Pediatr, 2019 06 01;173(6):e190337.
    PMID: 31034019 DOI: 10.1001/jamapediatrics.2019.0337
    Importance: Understanding causes and correlates of health loss among children and adolescents can identify areas of success, stagnation, and emerging threats and thereby facilitate effective improvement strategies.

    Objective: To estimate mortality and morbidity in children and adolescents from 1990 to 2017 by age and sex in 195 countries and territories.

    Design, Setting, and Participants: This study examined levels, trends, and spatiotemporal patterns of cause-specific mortality and nonfatal health outcomes using standardized approaches to data processing and statistical analysis. It also describes epidemiologic transitions by evaluating historical associations between disease indicators and the Socio-Demographic Index (SDI), a composite indicator of income, educational attainment, and fertility. Data collected from 1990 to 2017 on children and adolescents from birth through 19 years of age in 195 countries and territories were assessed. Data analysis occurred from January 2018 to August 2018.

    Exposures: Being under the age of 20 years between 1990 and 2017.

    Main Outcomes and Measures: Death and disability. All-cause and cause-specific deaths, disability-adjusted life years, years of life lost, and years of life lived with disability.

    Results: Child and adolescent deaths decreased 51.7% from 13.77 million (95% uncertainty interval [UI], 13.60-13.93 million) in 1990 to 6.64 million (95% UI, 6.44-6.87 million) in 2017, but in 2017, aggregate disability increased 4.7% to a total of 145 million (95% UI, 107-190 million) years lived with disability globally. Progress was uneven, and inequity increased, with low-SDI and low-middle-SDI locations experiencing 82.2% (95% UI, 81.6%-82.9%) of deaths, up from 70.9% (95% UI, 70.4%-71.4%) in 1990. The leading disaggregated causes of disability-adjusted life years in 2017 in the low-SDI quintile were neonatal disorders, lower respiratory infections, diarrhea, malaria, and congenital birth defects, whereas neonatal disorders, congenital birth defects, headache, dermatitis, and anxiety were highest-ranked in the high-SDI quintile.

    Conclusions and Relevance: Mortality reductions over this 27-year period mean that children are more likely than ever to reach their 20th birthdays. The concomitant expansion of nonfatal health loss and epidemiological transition in children and adolescents, especially in low-SDI and middle-SDI countries, has the potential to increase already overburdened health systems, will affect the human capital potential of societies, and may influence the trajectory of socioeconomic development. Continued monitoring of child and adolescent health loss is crucial to sustain the progress of the past 27 years.

    Matched MeSH terms: Spatio-Temporal Analysis
  14. Sanchez-Bezanilla S, Hood RJ, Collins-Praino LE, Turner RJ, Walker FR, Nilsson M, et al.
    J Cereb Blood Flow Metab, 2021 09;41(9):2439-2455.
    PMID: 33779358 DOI: 10.1177/0271678X211005877
    There is emerging evidence suggesting that a cortical stroke can cause delayed and remote hippocampal dysregulation, leading to cognitive impairment. In this study, we aimed to investigate motor and cognitive outcomes after experimental stroke, and their association with secondary neurodegenerative processes. Specifically, we used a photothrombotic stroke model targeting the motor and somatosensory cortices of mice. Motor function was assessed using the cylinder and grid walk tasks. Changes in cognition were assessed using a mouse touchscreen platform. Neuronal loss, gliosis and amyloid-β accumulation were investigated in the peri-infarct and ipsilateral hippocampal regions at 7, 28 and 84 days post-stroke. Our findings showed persistent impairment in cognitive function post-stroke, whilst there was a modest spontaneous motor recovery over the investigated period of 84 days. In the peri-infarct region, we detected a reduction in neuronal loss and decreased neuroinflammation over time post-stroke, which potentially explains the spontaneous motor recovery. Conversely, we observed persistent neuronal loss together with concomitant increased neuroinflammation and amyloid-β accumulation in the hippocampus, which likely accounts for the persistent cognitive dysfunction. Our findings indicate that cortical stroke induces secondary neurodegenerative processes in the hippocampus, a region remote from the primary infarct, potentially contributing to the progression of post-stroke cognitive impairment.
    Matched MeSH terms: Spatio-Temporal Analysis*
  15. Abdul Shakor AS, Pahrol MA, Mazeli MI
    J Environ Public Health, 2020;2020:1561823.
    PMID: 32351580 DOI: 10.1155/2020/1561823
    Particulate matter with an aerodynamic diameter of 10 μm or less (PM10) pollution poses a considerable threat to human health, and the first step in quantifying health impacts of human exposure to PM10 pollution is exposure assessment. Population-weighted exposure level (PWEL) estimation is one of the methods that provide a more refined exposure assessment as it includes the spatiotemporal distribution of the population into the pollution concentration estimation. This study assessed the population weighting effects on the estimated PM10 concentrations in Malaysia for years 2000, 2008, and 2013. Estimated PM10 annual mean concentrations with a spatial resolution of 5 kilometres retrieved from satellite data and population count obtained from the Gridded Population of the World version 4 (GPWv4) from the Centre for International Earth Science Information Network (CIESIN) were overlaid to generate the PWEL of PM10 for each state. The calculated PWEL of PM10 concentrations were then classified based on the World Health Organization (WHO) and the national Air Quality Guidelines (AQG) and interim targets (IT) for comparison. Results revealed that the annual mean PM10 concentrations in Malaysia ranged from 31 to 73 µg/m3 but became generally lower, ranging from 20 to 72 µg/m3 after population weighting, suggesting that the PM10 population exposure in Malaysia might have been overestimated. PWEL of PM10 distribution showed that the majority of the population lived in areas that complied with the national AQG, but were vulnerable to exposure level 3 according to the WHO AQG and IT, indicating that the population was nevertheless potentially exposed to significant health effects from long-term exposure to PM10 pollution.
    Matched MeSH terms: Spatio-Temporal Analysis
  16. Behera MR, Chun C, Palani S, Tkalich P
    Mar Pollut Bull, 2013 Dec 15;77(1-2):380-95.
    PMID: 24139643 DOI: 10.1016/j.marpolbul.2013.09.043
    The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales.
    Matched MeSH terms: Spatio-Temporal Analysis
  17. Abdullah P, Abdullah SMS, Jaafar O, Mahmud M, Khalik WMAWM
    Mar Pollut Bull, 2015 Dec 15;101(1):378-385.
    PMID: 26476861 DOI: 10.1016/j.marpolbul.2015.10.014
    Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed.
    Matched MeSH terms: Spatio-Temporal Analysis
  18. Ibrahim RW, Nashine HK, Kamaruddin N
    Math Biosci, 2017 10;292:10-17.
    PMID: 28728968 DOI: 10.1016/j.mbs.2017.07.007
    A biological dynamic system carries engineering properties such as control systems and signal processing (or image processing) addicted to molecular biology at the level of bio-molecular communication networks. Dynamical system features and signal reply functions of cellular signaling pathways are some of the main topics in biological dynamic systems (for example the biological segmentation). In the present paper, we introduce new generalized hybrid time-space dynamical systems of growing bacteria. We impose the approximate analytic solution for the system. The generalization adapted the concepts of the Riemann-Liouville fractional operators for time and the Srivastava-Owa fractional operators for space. Moreover, we introduce a numerical perturbation method of two operators to obtain the approximate solutions. We establish the existence and uniqueness results and impose some applications in the sequel. Moreover, we study the Ulam stability and apply these stable solutions to improve the segmentation of a class of growing bacteria.
    Matched MeSH terms: Spatio-Temporal Analysis
  19. Asghar MA, Khan MJ, Rizwan M, Shorfuzzaman M, Mehmood RM
    Multimed Syst, 2021 Apr 21.
    PMID: 33897112 DOI: 10.1007/s00530-021-00782-w
    Classification of human emotions based on electroencephalography (EEG) is a very popular topic nowadays in the provision of human health care and well-being. Fast and effective emotion recognition can play an important role in understanding a patient's emotions and in monitoring stress levels in real-time. Due to the noisy and non-linear nature of the EEG signal, it is still difficult to understand emotions and can generate large feature vectors. In this article, we have proposed an efficient spatial feature extraction and feature selection method with a short processing time. The raw EEG signal is first divided into a smaller set of eigenmode functions called (IMF) using the empirical model-based decomposition proposed in our work, known as intensive multivariate empirical mode decomposition (iMEMD). The Spatio-temporal analysis is performed with Complex Continuous Wavelet Transform (CCWT) to collect all the information in the time and frequency domains. The multiple model extraction method uses three deep neural networks (DNNs) to extract features and dissect them together to have a combined feature vector. To overcome the computational curse, we propose a method of differential entropy and mutual information, which further reduces feature size by selecting high-quality features and pooling the k-means results to produce less dimensional qualitative feature vectors. The system seems complex, but once the network is trained with this model, real-time application testing and validation with good classification performance is fast. The proposed method for selecting attributes for benchmarking is validated with two publicly available data sets, SEED, and DEAP. This method is less expensive to calculate than more modern sentiment recognition methods, provides real-time sentiment analysis, and offers good classification accuracy.
    Matched MeSH terms: Spatio-Temporal Analysis
  20. Usinowicz J, Chang-Yang CH, Chen YY, Clark JS, Fletcher C, Garwood NC, et al.
    Nature, 2017 10 05;550(7674):105-108.
    PMID: 28953870 DOI: 10.1038/nature24038
    The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.
    Matched MeSH terms: Spatio-Temporal Analysis*
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