FLOOD SUSCEPTIBILITY MODELLING USING GEOSPATIAL-BASED MULTI-CRITERIA DECISION MAKING IN LARGE SCALE AREAS

Flood is one of the most hazardous natural disasters that cause damages and poses a major threat to human lives and infrastructures worldwide, and its prevention is almost unfeasible. Thus, the detection of flood susceptible areas can be a key to lessen the amount of destruction and mortality. This study aims to implement a framework to identify flood potential zones in an ungauged large-scale area with frequent flood events in recent years. We used two Multi-Criteria Decision Making (MCDM) approaches combined with geospatial analysis, and remote sensing observations for this susceptibility analysis. Nine geomorphological and environmental factors that have an impact on flood behaviour were selected and used for susceptibility modelling. At first, the criteria’s weights were estimated using two MCDM approaches and based on experts’ knowledge. The resultant weights revealed that Flow Accumulation, Topographic wetness index, and Distance to River were the most influential flood susceptibility criteria. After calculating these weights, the criteria’s layers were aggregated through geospatial analysis, which resulted in generating flood susceptibility map. The area under the curve (AUC) and statistical measures such as the Kappa index were used to evaluate the proposed method's efficiency. The validation results illustrate that hybrid FAHP, with AUC= 96.68 and Kappa = 81.36 performed more efficiently than standard AHP, with AUC= 94.53 and Kappa=76.35. Overlaying these maps with the historical flood inventory dataset revealed that 86.43% of flooded areas were categorized as “high” and “very high”. Therefore, the flood susceptibility maps generated through the proposed approach can help the decision-makers and managers allocate the mitigation equipment and facility in data-scarce and ungauged large-scale areas

IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING

Mangroves provide numerous environmental benefits, such as carbon sequestration, water purification, climate change mitigation, and flood and Tsunami impact reduction. Despite these unique advantages, mangroves are threatened by the combined adverse impacts of human activities and climate change. Therefore, it is essential to implement reasonable practices to avoid further degradation of mangroves and provide efficient workflows to increase their extent. Accordingly, better plantation policies are principally required for their conservation and rehabilitation. In this study, we desired to detect suitable locations for mangrove plantation in coastal areas of Hormozgan Province, Iran. We considered a relatively new Multi Criteria Decision Making (MCDM) technique to combine ten criteria derived from remote sensing in a GIS environment. The Best Worst Method (BWM), as an MDCM technique, was implemented to determine the relative importance of each criterion. Afterward, all criteria were aggregated using the Weighted Linear Combination (WLC) method to produce a mangrove plantation suitability map. Statistical measures, including Overall Accuracy (OA = 95%), Kappa Coefficient (KC = 87.9%), and Area Under Curve (AUC = 98.79%), indicated the high applicability of the implemented method for mangrove plantation site allocation. The produced map could give managers a profound insight into finding optimal spots to plant mangroves

CemOrange2 fusions facilitate multifluorophore subcellular imaging in C. elegans

Due to its ease of genetic manipulation and transparency, Caenorhabditis elegans (C. elegans) has become a preferred model system to study gene function by microscopy. The use of Aequorea victoria green fluorescent protein (GFP) fused to proteins or targeting sequences of interest, further expanded upon the utility of C. elegans by labeling subcellular structures, which enables following their disposition during development or in the presence of genetic mutations. Fluorescent proteins with excitation and emission spectra different from that of GFP accelerated the use of multifluorophore imaging in real time. We have expanded the repertoire of fluorescent proteins for use in C. elegans by developing a codon-optimized version of Orange2 (CemOrange2). Proteins or targeting motifs fused to CemOrange2 were distinguishable from the more common fluorophores used in the nematode; such as GFP, YFP, and mKate2. We generated a panel of CemOrange2 fusion constructs, and confirmed they were targeted to their correct subcellular addresses by colocalization with independent markers. To demonstrate the potential usefulness of this new panel of fluorescent protein markers, we showed that CemOrange2 fusion proteins could be used to: 1) monitor biological pathways, 2) multiplex with other fluorescent proteins to determine colocalization and 3) gain phenotypic knowledge of a human ABCA3 orthologue, ABT-4, trafficking variant in the C. elegans model organism

IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING

Mangroves provide numerous environmental benefits, such as carbon sequestration, water purification, climate change mitigation, and flood and Tsunami impact reduction. Despite these unique advantages, mangroves are threatened by the combined adverse impacts of human activities and climate change. Therefore, it is essential to implement reasonable practices to avoid further degradation of mangroves and provide efficient workflows to increase their extent. Accordingly, better plantation policies are principally required for their conservation and rehabilitation. In this study, we desired to detect suitable locations for mangrove plantation in coastal areas of Hormozgan Province, Iran. We considered a relatively new Multi Criteria Decision Making (MCDM) technique to combine ten criteria derived from remote sensing in a GIS environment. The Best Worst Method (BWM), as an MDCM technique, was implemented to determine the relative importance of each criterion. Afterward, all criteria were aggregated using the Weighted Linear Combination (WLC) method to produce a mangrove plantation suitability map. Statistical measures, including Overall Accuracy (OA = 95%), Kappa Coefficient (KC = 87.9%), and Area Under Curve (AUC = 98.79%), indicated the high applicability of the implemented method for mangrove plantation site allocation. The produced map could give managers a profound insight into finding optimal spots to plant mangroves

A pilot study of demographic and dopaminergic genetic contributions to weight change in kidney transplant recipients

Kidney transplant recipients often experience a significant amount of weight gain in the first year post-transplantation. While demographic factors such as age, race, and sex have been associated with weight gain in this population, these factors do not explain all of the variability seen. A number of studies have suggested that genetics also plays a critical role in weight changes. Recently, alterations in the activity of the neurotransmitter dopamine have been associated with weight change, and gene expression studies in kidney transplant recipients have supported this association. The purpose of this pilot study is to first examine the feasibility and methodology, and then to examine the associations of age, race, sex, and genotype for 13 SNPs and 3 VNTRs in 9 dopaminergic pathway genes (ANKK1, DRD2, DRD3, DRD4, SLC6A3/DAT1, MAOA, MAOB, COMT, CPE) for associations with percent weight change at 12 months post-transplantation. Seventy kidney transplant recipients had demographic and clinical data collected as a part of a larger observational study. DNA was extracted from repository buffy coat samples taken at the time of transplant, and genotyped using Taqman and PCR based methods. Three SNPs were independently associated with percent weight change: ANKK1 rs1800497 (r = -0.28, p = 0.05), SLC6A3/DAT1 rs6347 (p = 0.046), and CPE rs1946816 (p = 0.028). Stepwise regression modelling confirmed the combined associations of age (p = 0.0021), DRD4 VNTR 4/5 genotype (p = 0.0074), and SLC6A3/DAT1 rs6347 CC genotype (p = 0.0009) and TT genotype (p = 0.0004) with percent weight change in a smaller sample (n = 35) of these kidney transplant recipients that had complete genotyping. These associations indicate that there may be a genetic, and an age component to weight changes post transplantation

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology

Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data. In particular, we perform the first study that involves more than two datasets. We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue types due to different dosages of an experimental panPPAR agonist in mouse. This study is of interest in toxicology because, whilst PPARs form potential therapeutic targets for diabetes, it is known that they can induce serious side-effects. Our results show that the practical simultaneous non-negative matrix factorization developed here can add value to the data analysis. In particular, we find that factorizing the data as a single object allows us to distinguish between the four tissue types, but does not correctly reproduce the known dosage level groups. Applying our new approach, which treats the four tissue types as providing distinct, but related, datasets, we find that the dosage level groups are respected. The new algorithm then provides separate gene list orderings that can be studied for each tissue type, and compared with the ordering arising from the single factorization. We find that many of our conclusions can be corroborated with known biological behaviour, and others offer new insights into the toxicological effects. Overall, the algorithm shows promise for early detection of toxicity in the drug discovery process

The Sloan Digital Sky Survey Reverberation Mapping Project : UV–optical accretion disk measurements with the Hubble Space Telescope

Funding: Y.H., J.R.T., and G.F.A. acknowledge support from NASA grants HST-GO-15650 and 18-2ADAP18-0177 and NSF grant CAREER-1945546. K.H. acknowledges support from STFC grant ST/R000824/1. C.J.G. acknowledges support from NSF grant AST-2009949. Y.S. acknowledges support from NSF grants AST-1715579 and AST-2009947. P.H. acknowledges support from the Natural Sciences and Engineering Research Council of Canada (NSERC), funding reference number 2017-05983. L.C.H. was supported by the National Science Foundation of China (11721303, 11991052) and the National Key R&D Program of China (2016YFA0400702).We present accretion-disk structure measurements from UV–optical reverberation mapping (RM) observations of a sample of eight quasars at 0.24 < z < 0.85. Ultraviolet photometry comes from two cycles of Hubble Space Telescope monitoring, accompanied by multiband optical monitoring by the Las Cumbres Observatory network and Liverpool Telescopes. The targets were selected from the Sloan Digital Sky Survey Reverberation Mapping project sample with reliable black hole mass measurements from Hβ RM results. We measure significant lags between the UV and various optical griz bands using JAVELIN and CREAM methods. We use the significant lag results from both methods to fit the accretion-disk structure using a Markov Chain Monte Carlo approach. We study the accretion disk as a function of disk normalization, temperature scaling, and efficiency. We find direct evidence for diffuse nebular emission from Balmer and Fe ii lines over discrete wavelength ranges. We also find that our best-fit disk color profile is broadly consistent with the Shakura & Sunyaev disk model. We compare our UV–optical lags to the disk sizes inferred from optical–optical lags of the same quasars and find that our results are consistent with these quasars being drawn from a limited high-lag subset of the broader population. Our results are therefore broadly consistent with models that suggest longer disk lags in a subset of quasars, for example, due to a nonzero size of the ionizing corona and/or magnetic heating contributing to the disk response.Publisher PDFPeer reviewe

The Sloan Digital Sky Survey Reverberation Mapping Project : the MBH–host relations at 0.2 ∼< z ∼< 0.6 from reverberation mapping and Hubble Space Telescope imaging

Funding: Y.S. acknowledges support from an Alfred P. Sloan Research Fellowship and NSF grants AST-1715579, AST-2009947. Support for Program number HST-GO-14109 was provided through a grant from the STScI under NASA contract NAS5-26555. L.C.H. was supported by the National Key R&D Program of China (2016YFA0400702) and the National Science Foundation of China (11721303, 11991052). E.D.B. is supported by Padua University grants DOR1715817/17, DOR1885254/18, and DOR1935272/19 and by MIUR grant PRIN 201720173ML3WW_001. J.V.H.S.and K.H. acknowledge funds from a Science and Technology Facilities Council grant ST/R000824/1.We present the results of a pilot Hubble Space Telescope (HST) imaging study of the host galaxies of ten quasars from the Sloan Digital Sky Survey Reverberation Mapping (SDSS-RM) project. Probing more than an order of magnitude in BH and stellar masses, our sample is the first statistical sample to study the BH-host correlations beyond z>0.3 with reliable BH masses from reverberation mapping rather than from single-epoch spectroscopy. We perform image decomposition in two HST bands (UVIS-F606W and IR-F110W) to measure host colors and estimate stellar masses using empirical relations between broad-band colors and the mass-to-light ratio. The stellar masses of our targets are mostly dominated by a bulge component. The BH masses and stellar masses of our sample broadly follow the same correlations found for local RM AGN and quiescent bulge-dominant galaxies, with no strong evidence of evolution in the MBH-M*bulge relation to z~0.6. We further compare the host light fraction from HST imaging decomposition to that estimated from spectral decomposition. We found a good correlation between the host fractions derived with both methods. However, the host fraction derived from spectral decomposition is systematically smaller than that from imaging decomposition by ~30%, indicating different systematics in both approaches. This study paves the way for upcoming more ambitious host galaxy studies of quasars with direct RM-based BH masses at high redshift.PostprintPeer reviewe

The Sloan Digital Sky Survey Reverberation Mapping Project : how broad emission line widths change when luminosity changes

Funding: National Science Foundation of China (11721303, 11890693, 11991052) and the National Key R&D Program of China (2016YFA0400702, 2016YFA0400703). YS acknowledges support from an Alfred P. Sloan Research Fellowship and NSF grant AST-1715579. CJG, WNB, JRT, and DPS acknowledge support from NSF grants AST-1517113 and AST-1516784. KH acknowledges support from STFC grant ST/R000824/1. PBH acknowledges support from NSERC grant 2017-05983. YH acknowledges support from NASA grant HST-GO-15650.Quasar broad emission lines are largely powered by photoionization from the accretion continuum. Increased central luminosity will enhance line emissivity in more distant clouds, leading to increased average distance of the broad-line-emitting clouds and decreased averaged line width, known as the broad-line region (BLR) "breathing". However, different lines breathe differently, and some high-ionization lines, such as C IV, can even show "anti-breathing" where the line broadens when luminosity increases. Using multi-year photometric and spectroscopic monitoring data from the Sloan Digital Sky Survey Reverberation Mapping project, we quantify the breathing effect (Δlog W=αΔlog L) of broad Hα, Hβ, Mg II, C IV,and C III] for statistical quasar samples over z≈0.1−2.5. We found that Hβ displays the most consistent normal breathing expected from the virial relation (α∼−0.25), Mg II and Hα on average show no breathing (α∼0), and C IV (and similarly C III] and Si IV mostly shows anti-breathing (α>0). The anti-breathing of C IV can be well understood by the presence of a non-varying core component in addition to a reverberating broad-base component, consistent with earlier findings. The deviation from canonical breathing introduces extra scatter (aluminosity-dependent bias) in single-epoch virial BH mass estimates due to intrinsic quasar variability, which underlies the long argued caveats of C IV single-epoch masses. Using the line dispersion instead of FWHM leads to less, albeit still substantial, deviations from canonical breathing in most cases. Our results strengthen the need for reverberation mapping to provide reliable quasar BH masses, and quantify the level of variability-induced bias in single-epoch BH masses based on various lines.PostprintPeer reviewe