On the application of data assimilation in the Singapore Regional Model

Ph.DDOCTOR OF PHILOSOPH

Deriving intensity–duration–frequency (IDF) curves using downscaled in situ rainfall assimilated with remote sensing data

The rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations. © 2019, The Author(s)

NDVI With Artificial Neural Networks For SRTM Elevation Model Improvement – Hydrological Model Application

Digital elevation model (DEM) plays a substantial role in hydrological study, from understanding the catchment characteristics, setting up a hydrological model to mapping the flood risk in the region. Depending on the nature of study and its objectives, high resolution and reliable DEM is often desired to set up a sound hydrological model. However, such source of good DEM is not always available and it is generally high-priced. Obtained through radar based remote sensing, Shuttle Radar Topography Mission (SRTM) is a publicly available DEM with resolution of 92m outside US. It is a great source of DEM where no surveyed DEM is available. However, apart from the coarse resolution, SRTM suffers from inaccuracy especially on area with dense vegetation coverage due to the limitation of radar signals not penetrating through canopy. This will lead to the improper setup of the model as well as the erroneous mapping of flood risk. This paper attempts on improving SRTM dataset, using Normalised Difference Vegetation Index (NDVI), derived from Visible Red and Near Infra-Red band obtained from Landsat with resolution of 30m, and Artificial Neural Networks (ANN). The assessment of the improvement and the applicability of this method in hydrology would be highlighted and discussed

Homozygosity Mapping and Genetic Analysis of Autosomal Recessive Retinal Dystrophies in 144 Consanguineous Pakistani Families.

PurposeThe Pakistan Punjab population has been a rich source for identifying genes causing or contributing to autosomal recessive retinal degenerations (arRD). This study was carried out to delineate the genetic architecture of arRD in the Pakistani population.MethodsThe genetic origin of arRD in a total of 144 families selected only for having consanguineous marriages and multiple members affected with arRD was examined. Of these, causative mutations had been identified in 62 families while only the locus had been identified for an additional 15. The remaining 67 families were subjected to homozygosity exclusion mapping by screening of closely flanking microsatellite markers at 180 known candidate genes/loci followed by sequencing of the candidate gene for pathogenic changes.ResultsOf these 67 families subjected to homozygosity mapping, 38 showed homozygosity for at least one of the 180 regions, and sequencing of the corresponding genes showed homozygous cosegregating mutations in 27 families. Overall, mutations were detected in approximately 61.8 % (89/144) of arRD families tested, with another 10.4% (15/144) being mapped to a locus but without a gene identified.ConclusionsThese results suggest the involvement of unmapped novel genes in the remaining 27.8% (40/144) of families. In addition, this study demonstrates that homozygosity mapping remains a powerful tool for identifying the genetic defect underlying genetically heterogeneous arRD disorders in consanguineous marriages for both research and clinical applications

Hydrophobically associating polymers for enhanced oil recovery – Part B: A review of modelling approach to flow in porous media

Polymer flow in porous media represents an entirely different scenario compared to bulk flow analysis using viscometers. This is due to the geometry and configuration of the medium which is made up of converging-diverging flow paths. In this article, a review of the single-phase flow of hydrophobically associating polymers in porous media is presented. Hydrophobic association between these polymer chains have been reported to occur and vary under reservoir conditions (temperature, salinity, and ion concentration). However, under these conditions, the critical aggregation concentration of associating polymers has been observed to change and the extent of change is a function of the hydrophobe make-up of the polymer. The outcome of this would indicate that polymer injectivity and its oil recovery efficiency are affected. As such, an understanding of the mechanism, propagation and sustainability of these hydrophobic interactions in reservoirs remains a critical focus of research. This becomes even imperative as the in-situ rheological profile associated with the different flow regimes may be affected. A numerical approach to investigating the real-time hydrophobic interactions between associating polymer chains during flow in porous media remains the viable option. However, this would require modifying existing time-independent models to accurately predict the various flow regimes and the dispersion of associating polymers to account for hydrophobic interactions

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Sub-THz Small-Signal Equivalent Circuit Model and Parameter Extraction for 3 nm Gate-All-Around Nanosheet Transistor

This paper presents a novel RF small-signal equivalent circuit model and parameter extraction for 3 nm nanosheet gate-all-around field effect transistor (GAAFET). The extrinsic parasitic effect induced by ground-signal-ground (GSG) layout is evaluated by 3D full-wave electromagnetic simulation, and an improved five-step analytical parameter extraction method is proposed for such extrinsic GSG layout. The model parameters for the intrinsic device are analytically determined with the help of nonlinear rational function fitting. The accuracy of the proposed extraction method was confirmed via comparisons between device simulator and electromagnetic simulator with frequency responses up to 300 GHz. Excellent agreement is obtained between the simulated and modeled S-parameters, and the calculated error is lower than 2.689% for the extrinsic layout, and 0.897% for the intrinsic device in the whole frequency range among multi-bias points

Crystal structure of 4,4′-bipyridin-1,1′-dium poly[bis(μ4-benzene-1,3,5-triyltris(hydrogen phosphonato-κ4O:O′:O′′:O′′′))zinc(II)], C11H11NO9P3Zn

C11H11NO9P3Zn, monoclinic, P21/n (no. 14), a = 12.619(2) Å, b = 8.4948(12) Å, c = 13.954(2) Å, β = 90.588(3)°, V = 1495.7(4) Å3, Z = 4, Rgt(F) = 0.0413, wRref(F2) = 0.0965, T = 120(2) K