Engineering and Information Technology Collected Works - Research Publications
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ItemPrediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches(BMC, 2019-11-13)BACKGROUND: Recent reports of the National Ministry of Health and Treatment of Iran (NMHT) show that Gilan has a higher annual incidence rate of leptospirosis than other provinces across the country. Despite several efforts of the government and NMHT to eradicate leptospirosis, it remains a public health problem in this province. Modelling and Prediction of this disease may play an important role in reduction of the prevalence. METHODS: This study aims to model and predict the spatial distribution of leptospirosis utilizing Geographically Weighted Regression (GWR), Generalized Linear Model (GLM), Support Vector Machine (SVM) and Artificial Neural Network (ANN) as capable approaches. Five environmental parameters of precipitation, temperature, humidity, elevation and vegetation are used for modelling and predicting of the disease. Data of 2009 and 2010 are used for training, and 2011 for testing and evaluating the models. RESULTS: Results indicate that utilized approaches in this study can model and predict leptospirosis with high significance level. To evaluate the efficiency of the approaches, MSE (GWR = 0.050, SVM = 0.137, GLM = 0.118 and ANN = 0.137), MAE (0.012, 0.063, 0.052 and 0.063), MRE (0.011, 0.018, 0.017 and 0.018) and R2 (0.85, 0.80, 0.78 and 0.75) are used. CONCLUSION: Results indicate the practical usefulness of approaches for spatial modelling and predicting leptospirosis. The efficiency of models is as follow: GWR > SVM > GLM > ANN. In addition, temperature and humidity are investigated as the most influential parameters. Moreover, the suitable habitat of leptospirosis is mostly within the central rural districts of the province.
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ItemDynamic and Responsive Growth Factor Delivery from Electrospun and Hydrogel Tissue Engineering Materials(WILEY, 2018-01-10)Tissue engineering scaffolds are designed to mimic physical, chemical, and biological features of the extracellular matrix, thereby providing a constant support that is crucial to improved regenerative medicine outcomes. Beyond mechanical and structural support, the next generation of these materials must also consider the more dynamic presentation and delivery of drugs or growth factors to guide new and regenerating tissue development. These two aspects are explored expansively separately, but they must interact synergistically to achieve optimal regeneration. This review explores common tissue engineering materials types, electrospun polymers and hydrogels, and strategies used for incorporating drug delivery systems into these scaffolds.
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ItemRelationship between root water uptake and soil respiration: A modeling perspective(AMER GEOPHYSICAL UNION, 2017-08)Abstract Soil moisture affects and is affected by root water uptake and at the same time drives soil CO2 dynamics. Selecting root water uptake formulations in models is important since this affects the estimation of actual transpiration and soil CO2 efflux. This study aims to compare different models combining the Richards equation for soil water flow to equations describing heat transfer and air‐phase CO2 production and flow. A root water uptake model (RWC), accounting only for root water compensation by rescaling water uptake rates across the vertical profile, was compared to a model (XWP) estimating water uptake as a function of the difference between soil and root xylem water potential; the latter model can account for both compensation (XWPRWC) and hydraulic redistribution (XWPHR). Models were compared in a scenario with a shallow water table, where the formulation of root water uptake plays an important role in modeling daily patterns and magnitudes of transpiration rates and CO2 efflux. Model simulations for this scenario indicated up to 20% difference in the estimated water that transpired over 50 days and up to 14% difference in carbon emitted from the soil. The models showed reduction of transpiration rates associated with water stress affecting soil CO2 efflux, with magnitudes of soil CO2 efflux being larger for the XWPHR model in wet conditions and for the RWC model as the soil dried down. The study shows the importance of choosing root water uptake models not only for estimating transpiration but also for other processes controlled by soil water content.
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ItemTrends in the processing and manufacture of solid oxide fuel cells(Wiley, 2017-09-01)Electrochemical devices based on solid‐state ceramic materials such as solid oxide fuel cells (SOFCs) and solid oxide electrolysis cells (SOECs) are promising technologies which are gaining importance in today's rapidly developing energy frameworks. In particular, these high‐temperature variants offer further potential benefits such as increased fuel flexibility and higher system efficiencies. One of the significant challenges for SOFCs is the creation of robust, durable, and affordable cells. While the search for new materials remains an important research activity, the role of process development for fabrication and manufacture should not be underestimated. Indeed better understanding between materials, processing, and the resulting microstructure is vital for improving cell performance. The links between cell design and various processing techniques are explored. The most common approaches are based on thick film ceramic processes where recent trends include areas such as production of thinner tape cast layers and challenges in the application of aqueous systems to cell processing. Decoupling the processing and control of bulk and catalytic microstructures within the cell has recently been a very active area of development with techniques such as impregnation and exsolution showing increasingly promising results. Thin film techniques such as physical vapor deposition are also still being investigated for micro SOFCs or thin interfacial layers. In all cases, materials and process development should be closely linked, as high quality, reliable microstructures are essential to optimize the chemistry taking place on the materials and viable routes to manufacture are vital to transferring new materials into commercial devices. WIREs Energy Environ 2017, 6:e248. doi: 10.1002/wene.248 This article is categorized under: Fuel Cells and Hydrogen > Science and Materials
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ItemRight-sided aortic arch in the age of microarray(WILEY, 2017-05)
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ItemActivation and clustering of a Plasmodium falciparum var gene are affected by subtelomeric sequences(WILEY, 2017-01)The Plasmodium falciparum var multigene family encodes the cytoadhesive, variant antigen PfEMP1. P. falciparum antigenic variation and cytoadhesion specificity are controlled by epigenetic switching between the single, or few, simultaneously expressed var genes. Most var genes are maintained in perinuclear clusters of heterochromatic telomeres. The active var gene(s) occupy a single, perinuclear var expression site. It is unresolved whether the var expression site forms in situ at a telomeric cluster or whether it is an extant compartment to which single chromosomes travel, thus controlling var switching. Here we show that transcription of a var gene did not require decreased colocalisation with clusters of telomeres, supporting var expression site formation in situ. However following recombination within adjacent subtelomeric sequences, the same var gene was persistently activated and did colocalise less with telomeric clusters. Thus, participation in stable, heterochromatic, telomere clusters and var switching are independent but are both affected by subtelomeric sequences. The var expression site colocalised with the euchromatic mark H3K27ac to a greater extent than it did with heterochromatic H3K9me3. H3K27ac was enriched within the active var gene promoter even when the var gene was transiently repressed in mature parasites and thus H3K27ac may contribute to var gene epigenetic memory.
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ItemSMELL NO EVIL: COPPER DISRUPTS THE ALARM CHEMICAL RESPONSE IN A DIADROMOUS FISH, GALAXIAS MACULATUS(WILEY-BLACKWELL, 2016-09)
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ItemNoninvasive prenatal testing in routine clinical practice - An audit of NIPT and combined first-trimester screening in an unselected Australian population(WILEY, 2016-02)BACKGROUND: There are limited data regarding noninvasive prenatal testing (NIPT) in low-risk populations, and the ideal aneuploidy screening model for a pregnant population has yet to be established. AIMS: To assess the implementation of NIPT into clinical practice utilising both first- and second-line screening models. MATERIALS AND METHODS: Three private practices specialising in obstetric ultrasound and prenatal diagnosis in Australia offered NIPT as a first-line test, ideally followed by combined first-trimester screening (cFTS), or as a second-line test following cFTS, particularly in those with a calculated risk between 1:50 and 1:1000. RESULTS: NIPT screening was performed in 5267 women and as a first-line screening method in 3359 (63.8%). Trisomies 21 and 13 detection was 100% and 88% for trisomy 18. Of cases with known karyotypes, the positive predictive value (PPV) of the test was highest for trisomy 21 (97.7%) and lowest for monosomy X (25%). Ultrasound detection of fetal structural abnormality resulted in the detection of five additional chromosome abnormalities, two of which had high-risk cFTS results. For all chromosomal abnormalities, NIPT alone detected 93.4%, a contingent model detected 81.8% (P = 0.097), and cFTS alone detected 65.9% (P < 0.005). CONCLUSIONS: NIPT achieved 100% T21 detection and had a higher DR of all aneuploidy when used as a first-line test. Given the false-positive rate for all aneuploidies, NIPT is an advanced screening test, rather than a diagnostic test. The benefit of additional cFTS was the detection of fetal structural abnormalities and some unusual chromosomal abnormalities.
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ItemNo Preview AvailableShared and Subject-Specific Dictionary Learning (ShSSDL) Algorithm for Multisubject fMRI Data Analysis(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018-11)OBJECTIVE: Analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects is at the heart of many medical imaging studies, and approaches based on dictionary learning (DL) are recently noted as promising solutions to the problem. However, the DL-based methods for fMRI analysis proposed to date do not naturally extend to multisubject analysis. In this paper, we propose a DL algorithm for multisubject fMRI data analysis. METHODS: The proposed algorithm [named shared and subject-specific dictionary learning (ShSSDL)] is derived based on a temporal concatenation, which is particularly attractive for the analysis of multisubject task-related fMRI datasets. It differs from existing DL algorithms in both its sparse coding and dictionary update stages and has the advantage of learning a dictionary shared by all subjects as well as a set of subject-specific dictionaries. RESULTS: The performance of the proposed DL algorithm is illustrated using simulated and real fMRI datasets. The results show that it can successfully extract shared as well as subject-specific latent components. CONCLUSION: In addition to offering a new DL approach, when applied on multisubject fMRI data analysis, the proposed algorithm generates a group level as well as a set of subject-specific spatial maps. SIGNIFICANCE: The proposed algorithm has the advantage of learning simultaneously multiple dictionaries providing us with a shared as well discriminative source of information about the analyzed fMRI datasets.