A novel hybrid swarm optimized multilayer neural network for spatial prediction of flash floods in tropical areas using sentinel-1 SAR imagery and geospatial data

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Flash floods are widely recognized as one of the most devastating natural hazards in the world, therefore prediction of flash flood-prone areas is crucial for public safety and emergency management. This research proposes a new methodology for spatial prediction of flash floods based on Sentinel-1 SAR imagery and a new hybrid machine learning technique. The SAR imagery is used to detect flash flood inundation areas, whereas the new machine learning technique, which is a hybrid of the firefly algorithm (FA), Levenberg–Marquardt (LM) backpropagation, and an artificial neural network (named as FA-LM-ANN), was used to construct the prediction model. The Bac Ha Bao Yen (BHBY) area in the northwestern region of Vietnam was used as a case study. Accordingly, a Geographical Information System (GIS) database was constructed using 12 input variables (elevation, slope, aspect, curvature, topographic wetness index, stream power index, toposhade, stream density, rainfall, normalized difference vegetation index, soil type, and lithology) and subsequently the output of flood inundation areas was mapped. Using the database and FA-LM-ANN, the flash flood model was trained and verified. The model performance was validated via various performance metrics including the classification accuracy rate, the area under the curve, precision, and recall. Then, the flash flood model that produced the highest performance was compared with benchmarks, indicating that the combination of FA and LM backpropagation is proven to be very effective and the proposed FA-LM-ANN is a new and useful tool for predicting flash flood susceptibility

Enhanced sensitivity and detection of near-infrared refractive index sensor with plasmonic multilayers

In this work, the multilayer of the surface plasmon resonance (SPR) sensor was optimized to achieve the maximum sensor sensitivity. By optimizing the thickness of the silver layer (Ag) and dielectric films (TiO2 and AlAs), the optimum sensitivity of the SPR sensor could be obtained. The performance of the SPR sensor proposed was compared with control simulations utilizing zinc oxide (ZnO) and molybdenum oxide (MoO3 ). The numerical results indicate that the figure-of-merits (FOM) of the SPR sensor was achieved around 150/RIU, corresponding to the sensor sensitivity of 162.79◦/RIU with the optimized thicknesses of the TiO2, Ag, and AlAs layers of 140 nm, 60 nm, and 25 nm, respectively. This refractive index sensor shows the FOM to have high detection accuracy and high sensitivity that lead to finding potential application in bio-chemical detection with a small volume of liquid used in biological diagnosis

Antibody landscapes after influenza virus infection or vaccination.

We introduce the antibody landscape, a method for the quantitative analysis of antibody-mediated immunity to antigenically variable pathogens, achieved by accounting for antigenic variation among pathogen strains. We generated antibody landscapes to study immune profiles covering 43 years of influenza A/H3N2 virus evolution for 69 individuals monitored for infection over 6 years and for 225 individuals pre- and postvaccination. Upon infection and vaccination, titers increased broadly, including previously encountered viruses far beyond the extent of cross-reactivity observed after a primary infection. We explored implications for vaccination and found that the use of an antigenically advanced virus had the dual benefit of inducing antibodies against both advanced and previous antigenic clusters. These results indicate that preemptive vaccine updates may improve influenza vaccine efficacy in previously exposed individuals.This is the author’s version of the work. It will be under embargo for 6 months following publication. It is posted here by permission of the AAAS for personal use, not for redistribution. The final version is available from AAAS in Science at http://www.sciencemag.org/content/346/6212/996.long

Mutagenesis and Functional Studies with Succinate Dehydrogenase Inhibitors in the Wheat Pathogen Mycosphaerella graminicola

A range of novel carboxamide fungicides, inhibitors of the succinate dehydrogenase enzyme (SDH, EC 1.3.5.1) is currently being introduced to the crop protection market. The aim of this study was to explore the impact of structurally distinct carboxamides on target site resistance development and to assess possible impact on fitness

Effectiveness of sofosbuvir based direct-acting antiviral regimens for chronic hepatitis C virus genotype 6 patients: Real-world experience in Vietnam

Background: Hepatitis C virus (HCV) genotype 6 is the commonest cause of chronic hepatitis C infection in much of southeast Asia, but data on the effectiveness of direct-acting antiviral agents (DAAs) against this genotype are limited. We conducted a retrospective cohort study of patients attending the Hospital for Tropical Diseases (HTD), Ho Chi Minh City, Vietnam, to define the effectiveness of DAAs in the treatment of chronic HCV genotype 6 in actual practice. Methods: We included all patients with genotype 6 infections attending our hospital between March 2016 and October 2017 who received treatment with sofosbuvir-based DAA treatment regimens, and compared their responses with those with genotype 1 infections. Results: 1758 patients (1148 genotype 6, 65.4%; 610 genotype 1, 34.6%) were analyzed. The majority of patients (1480, 84.2%) received sofosbuvir/ledipasvir (SOF/LDV) ± ribavirin (RBV); 278 (15.8%) received sofosbuvir/Daclatasvir (SOF/DCV) ± RBV. The median age of the patients was 57 years, (interquartile range (IQR) 46–64 years) The baseline HCV viral load (log IU/ml) was significantly higher in patients infected with genotype 6 compared with those infected with genotype 1 (6.8, 5.3–6.6 versus 6.3, 5.3–6.5 log10 IU/ml, p = Conclusions: Our study suggests that patients with HCV genotype 6 infection in Vietnam may respond less well to treatment with sofosbuvir based DAAs than patients with genotype 1 infections. Further studies are needed to confirm this observation and to define whether it is driven by genotype-specific mutations.</br

Association between Hemagglutinin Stem-Reactive Antibodies and Influenza A/H1N1 Virus Infection during the 2009 Pandemic

UNLABELLED: The discovery of influenza virus broadly neutralizing (BrN) antibodies prompted efforts to develop universal vaccines. Influenza virus stem-reactive (SR) broadly neutralizing antibodies have been detected by screening antibody phage display libraries. However, studies of SR BrN antibodies in human serum, and their association with natural infection, are limited. To address this, pre- and postpandemic sera from a prospective community cohort study in Vietnam were assessed for antibodies that inhibit SR BrN monoclonal antibody (MAb) (C179) binding to H1N1 pandemic 2009 virus (H1N1pdm09). Of 270 households, 33 with at least one confirmed H1N1pdm09 illness or at least two seroconverters were included. The included households comprised 71 infected and 41 noninfected participants. Sera were tested as 2-fold dilutions between 1:5 and 1:40. Fifty percent C179 inhibition (IC50) titers did not exceed 10, although both IC50 titers and percent C179 inhibition by sera diluted 1:5 or 1:10 correlated with hemagglutination inhibition (HI) and microneutralization (MN) titers (all P < 0.001). Thirteen (12%) participants had detectable prepandemic IC50 titers, but only one reached a titer of 10. This proportion increased to 44% after the pandemic, when 39 participants had a titer of 10, and 67% of infected compared to 44% of noninfected had detectable IC50 titers (P < 0.001). The low levels of SR antibodies in prepandemic sera were not associated with subsequent H1N1pdm09 infection (P = 0.241), and the higher levels induced by H1N1pdm09 infection returned to prepandemic levels within 2 years. The findings indicate that natural infection induces only low titers of SR antibodies that are not sustained. IMPORTANCE: Universal influenza vaccines could have substantial health and economic benefits. The focus of universal vaccine research has been to induce antibodies that prevent infection by diverse influenza virus strains. These so-called broadly neutralizing antibodies are readily detected in mice and ferrets after infection with a series of distinct influenza virus strains. The 2009 H1N1 pandemic provided an opportunity to investigate whether infection with a novel strain induced broadly neutralizing antibodies in humans. We found that broadly neutralizing antibodies were induced, but levels were low and poorly maintained. This could represent an obstacle for universal vaccine development and warrants further investigation