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  1. Ramli N, Nair SR, Ramli NM, Lim SY
    Clin Radiol, 2015 May;70(5):555-64.
    PMID: 25752581 DOI: 10.1016/j.crad.2015.01.005
    The purpose of this review is to illustrate the differentiating features of multiple-system atrophy from Parkinson's disease at MRI. The various MRI sequences helpful in the differentiation will be discussed, including newer methods, such as diffusion tensor imaging, MR spectroscopy, and nuclear imaging.
  2. Cheah SKA, Yeow PHP, Nair SR, Tan FB
    Ergonomics, 2018 May;61(5):627-643.
    PMID: 29092687 DOI: 10.1080/00140139.2017.1397200
    Household electricity wastage poses a sustainability issue. Ergonomic interventions that prevent wastage through technological innovations are expensive and complex, making consumers unwilling to adopt them. The study aimed to investigate the motivations and impediments in avoiding electricity wastage. Thirteen Repertory Grid interviews were conducted on household electricity users relating to the behaviour of those living with them. The key motivational themes found were altruistic and egoistic reasons while the impediments were perceived behavioural control, hedonism and self-efficacy. Based on the research findings, a behavioural modification framework was developed to encourage consumers to adopt a higher level of responsible electricity practice through the following suggested interventions - (1) reframing sustainability from 'future-for-others' to 'present-for-us', (2) clarifying responsible consumption and (3) performance feedback. The research identified the key motivations and impediments of being a responsible household electricity user and provided a framework to encourage a higher responsibility level. Practitioner Summary: Household electricity wastage poses sustainability issue: excess CO2 & high costs. We developed a mindset changing behavioural modification framework. We investigated HFE issues: motivations & impediments of avoiding the wastage, i.e. altruistic, egoistic, behavioural control, hedonism & self-efficacy. The framework provides governments insights into strategies to address the wastage.
  3. Nair SR, Rahmat K, Alhabshi SM, Ramli N, Seong MK, Waran V
    Clin Neurol Neurosurg, 2013 Jul;115(7):1150-3.
    PMID: 23031746 DOI: 10.1016/j.clineuro.2012.09.014
  4. Nair SR, Tan LK, Mohd Ramli N, Lim SY, Rahmat K, Mohd Nor H
    Eur Radiol, 2013 Jun;23(6):1459-66.
    PMID: 23300042 DOI: 10.1007/s00330-012-2759-9
    OBJECTIVE: To develop a decision tree based on standard magnetic resonance imaging (MRI) and diffusion tensor imaging to differentiate multiple system atrophy (MSA) from Parkinson's disease (PD).

    METHODS: 3-T brain MRI and DTI (diffusion tensor imaging) were performed on 26 PD and 13 MSA patients. Regions of interest (ROIs) were the putamen, substantia nigra, pons, middle cerebellar peduncles (MCP) and cerebellum. Linear, volumetry and DTI (fractional anisotropy and mean diffusivity) were measured. A three-node decision tree was formulated, with design goals being 100 % specificity at node 1, 100 % sensitivity at node 2 and highest combined sensitivity and specificity at node 3.

    RESULTS: Nine parameters (mean width, fractional anisotropy (FA) and mean diffusivity (MD) of MCP; anteroposterior diameter of pons; cerebellar FA and volume; pons and mean putamen volume; mean FA substantia nigra compacta-rostral) showed statistically significant (P < 0.05) differences between MSA and PD with mean MCP width, anteroposterior diameter of pons and mean FA MCP chosen for the decision tree. Threshold values were 14.6 mm, 21.8 mm and 0.55, respectively. Overall performance of the decision tree was 92 % sensitivity, 96 % specificity, 92 % PPV and 96 % NPV. Twelve out of 13 MSA patients were accurately classified.

    CONCLUSION: Formation of the decision tree using these parameters was both descriptive and predictive in differentiating between MSA and PD.

    KEY POINTS: • Parkinson's disease and multiple system atrophy can be distinguished on MR imaging. • Combined conventional MRI and diffusion tensor imaging improves the accuracy of diagnosis. • A decision tree is descriptive and predictive in differentiating between clinical entities. • A decision tree can reliably differentiate Parkinson's disease from multiple system atrophy.

  5. Ooi EH, Lee KW, Yap S, Khattab MA, Liao IY, Ooi ET, et al.
    Comput Biol Med, 2019 03;106:12-23.
    PMID: 30665137 DOI: 10.1016/j.compbiomed.2019.01.003
    Effects of different boundary conditions prescribed across the boundaries of radiofrequency ablation (RFA) models of liver cancer are investigated for the case where the tumour is at the liver boundary. Ground and Robin-type conditions (electrical field) and body temperature and thermal insulation (thermal field) conditions are examined. 3D models of the human liver based on publicly-available CT images of the liver are developed. An artificial tumour is placed inside the liver at the boundary. Simulations are carried out using the finite element method. The numerical results indicated that different electrical and thermal boundary conditions led to different predictions of the electrical potential, temperature and thermal coagulation distributions. Ground and body temperature conditions presented an unnatural physical conditions around the ablation site, which results in more intense Joule heating and excessive heat loss from the tissue. This led to thermal damage volumes that are smaller than the cases when the Robin type or the thermal insulation conditions are prescribed. The present study suggests that RFA simulations in the future must take into consideration the choice of the type of electrical and thermal boundary conditions to be prescribed in the case where the tumour is located near to the liver boundary.
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