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

FungalRV: adhesin prediction and immunoinformatics portal for human fungal pathogens

<p>Abstract</p> <p>Background</p> <p>The availability of sequence data of human pathogenic fungi generates opportunities to develop Bioinformatics tools and resources for vaccine development towards benefitting at-risk patients.</p> <p>Description</p> <p>We have developed a fungal adhesin predictor and an immunoinformatics database with predicted adhesins. Based on literature search and domain analysis, we prepared a positive dataset comprising adhesin protein sequences from human fungal pathogens <it>Candida albicans, Candida glabrata, Aspergillus fumigatus, Coccidioides immitis, Coccidioides posadasii, Histoplasma capsulatum, Blastomyces dermatitidis, Pneumocystis carinii, Pneumocystis jirovecii and Paracoccidioides brasiliensis</it>. The negative dataset consisted of proteins with high probability to function intracellularly. We have used 3945 compositional properties including frequencies of mono, doublet, triplet, and multiplets of amino acids and hydrophobic properties as input features of protein sequences to Support Vector Machine. Best classifiers were identified through an exhaustive search of 588 parameters and meeting the criteria of best Mathews Correlation Coefficient and lowest coefficient of variation among the 3 fold cross validation datasets. The "FungalRV adhesin predictor" was built on three models whose average Mathews Correlation Coefficient was in the range 0.89-0.90 and its coefficient of variation across three fold cross validation datasets in the range 1.2% - 2.74% at threshold score of 0. We obtained an overall MCC value of 0.8702 considering all 8 pathogens, namely, <it>C. albicans, C. glabrata, A. fumigatus, B. dermatitidis, C. immitis, C. posadasii, H. capsulatum </it>and <it>P. brasiliensis </it>thus showing high sensitivity and specificity at a threshold of 0.511. In case of <it>P. brasiliensis </it>the algorithm achieved a sensitivity of 66.67%. A total of 307 fungal adhesins and adhesin like proteins were predicted from the entire proteomes of eight human pathogenic fungal species. The immunoinformatics analysis data on these proteins were organized for easy user interface analysis. A Web interface was developed for analysis by users. The predicted adhesin sequences were processed through 18 immunoinformatics algorithms and these data have been organized into MySQL backend. A user friendly interface has been developed for experimental researchers for retrieving information from the database.</p> <p>Conclusion</p> <p>FungalRV webserver facilitating the discovery process for novel human pathogenic fungal adhesin vaccine has been developed.</p

Landslide susceptibility mapping using support vector machine and GIS at the Golestan province, Iran

The main goal of this study is to produce landslide susceptibility map using GIS-based support vector machine (SVM) at Kalaleh Township area of the Golestan province, Iran. In this paper, six different types of kernel classifiers such as linear, polynomial degree of 2, polynomial degree of 3, polynomial degree of 4, radial basis function (RBF) and sigmoid were used for landslide susceptibility mapping. At the first stage of the study, landslide locations were identified by aerial photographs and field surveys, and a total of 82 landslide locations were extracted from various sources. Of this, 75% of the landslides (61 landslide locations) are used as training dataset and the rest was used as (21 landslide locations) the validation dataset. Fourteen input data layers were employed as landslide conditioning factors in the landslide susceptibility modelling. These factors are slope degree, slope aspect, altitude, plan curvature, profile curvature, tangential curvature, surface area ratio (SAR), lithology, land use, distance from faults, distance from rivers, distance from roads, topographic wetness index (TWI) and stream power index (SPI). Using these conditioning factors, landslide susceptibility indices were calculated using support vector machine by employing six types of kernel function classifiers. Subsequently, the results were plotted in ArcGIS and six landslide susceptibility maps were produced. Then, using the success rate and the prediction rate methods, the validation process was performed by comparing the existing landslide data with the six landslide susceptibility maps. The validation results showed that success rates for six types of kernel models varied from 79% to 87%. Similarly, results of prediction rates showed that RBF (85%) and polynomial degree of 3 (83%) models performed slightly better than other types of kernel (polynomial degree of 2 = 78%, sigmoid = 78%, polynomial degree of 4 = 78%, and linear = 77%) models. Based on our results, the differences in the rates (success and prediction) of the six models are not really significant. So, the produced susceptibility maps will be useful for general land-use planning

The spin label amino acid TOAC and its uses in studies of peptides: chemical, physicochemical, spectroscopic, and conformational aspects

We review work on the paramagnetic amino acid 2,2,6,6-tetramethyl-N-oxyl-4-amino-4-carboxylic acid, TOAC, and its applications in studies of peptides and peptide synthesis. TOAC was the first spin label probe incorporated in peptides by means of a peptide bond. In view of the rigid character of this cyclic molecule and its attachment to the peptide backbone via a peptide bond, TOAC incorporation has been very useful to analyze backbone dynamics and peptide secondary structure. Many of these studies were performed making use of EPR spectroscopy, but other physical techniques, such as X-ray crystallography, CD, fluorescence, NMR, and FT-IR, have been employed. The use of double-labeled synthetic peptides has allowed the investigation of their secondary structure. A large number of studies have focused on the interaction of peptides, both synthetic and biologically active, with membranes. In the latter case, work has been reported on ligands and fragments of GPCR, host defense peptides, phospholamban, and β-amyloid. EPR studies of macroscopically aligned samples have provided information on the orientation of peptides in membranes. More recent studies have focused on peptide–protein and peptide–nucleic acid interactions. Moreover, TOAC has been shown to be a valuable probe for paramagnetic relaxation enhancement NMR studies of the interaction of labeled peptides with proteins. The growth of the number of TOAC-related publications suggests that this unnatural amino acid will find increasing applications in the future

The Endoplasmic Reticulum Stress Response in Neuroprogressive Diseases: Emerging Pathophysiological Role and Translational Implications

The endoplasmic reticulum (ER) is the main cellular organelle involved in protein synthesis, assembly and secretion. Accumulating evidence shows that across several neurodegenerative and neuroprogressive diseases, ER stress ensues, which is accompanied by over-activation of the unfolded protein response (UPR). Although the UPR could initially serve adaptive purposes in conditions associated with higher cellular demands and after exposure to a range of pathophysiological insults, over time the UPR may become detrimental, thus contributing to neuroprogression. Herein, we propose that immune-inflammatory, neuro-oxidative, neuro-nitrosative, as well as mitochondrial pathways may reciprocally interact with aberrations in UPR pathways. Furthermore, ER stress may contribute to a deregulation in calcium homoeostasis. The common denominator of these pathways is a decrease in neuronal resilience, synaptic dysfunction and even cell death. This review also discusses how mechanisms related to ER stress could be explored as a source for novel therapeutic targets for neurodegenerative and neuroprogressive diseases. The design of randomised controlled trials testing compounds that target aberrant UPR-related pathways within the emerging framework of precision psychiatry is warranted

Diabetic ketoacidosis

Diabetic ketoacidosis (DKA) is the most common acute hyperglycaemic emergency in people with diabetes mellitus. A diagnosis of DKA is confirmed when all of the three criteria are present — ‘D’, either elevated blood glucose levels or a family history of diabetes mellitus; ‘K’, the presence of high urinary or blood ketoacids; and ‘A’, a high anion gap metabolic acidosis. Early diagnosis and management are paramount to improve patient outcomes. The mainstays of treatment include restoration of circulating volume, insulin therapy, electrolyte replacement and treatment of any underlying precipitating event. Without optimal treatment, DKA remains a condition with appreciable, although largely preventable, morbidity and mortality. In this Primer, we discuss the epidemiology, pathogenesis, risk factors and diagnosis of DKA and provide practical recommendations for the management of DKA in adults and children

A next-generation liquid xenon observatory for dark matter and neutrino physics

The nature of dark matter and properties of neutrinos are among the most pressing issues in contemporary particle physics. The dual-phase xenon time-projection chamber is the leading technology to cover the available parameter space for weakly interacting massive particles, while featuring extensive sensitivity to many alternative dark matter candidates. These detectors can also study neutrinos through neutrinoless double-beta decay and through a variety of astrophysical sources. A next-generation xenon-based detector will therefore be a true multi-purpose observatory to significantly advance particle physics, nuclear physics, astrophysics, solar physics, and cosmology. This review article presents the science cases for such a detector

Current status of freshwater prawn culture in Vietnam and the development and transfer of seed production technology

In Vietnam, the giant freshwater prawn Macrobrachium rosenbergii is becoming an increasingly important targeted species, as its culture, especially in rice fields, is considered to have the potential to raise income among impoverished farmers. The production of M. rosenbergii based on aquaculture reached over 10 000 tons per year in 2002, having increased from about 2500 tons since the 1990s. Until recently, lack of a stable supply of seed had been an important obstacle to the further expansion and development of M. rosenbergii culture, but cumulative research on larval rearing, especially in the 1990s, has led to the development of new seed production technology based on the 'modified stagnant green water system'. Following its dissemination by the efforts of provincial authorities, hatchery operators, and farmers, the freshwater prawn seed production industry developed rapidly in the Mekong Delta with over 90 hatcheries producing 76.5 million postlarvae in 2003. This is considered to have affected the expansion of rice-prawn farming in the Mekong Delta, leading to increased aquacultural production in the region. This paper reviews the current status of freshwater prawn culture in Vietnam and background history, and presents a socioeconomic evaluation of seed production technology implementation

Genetic characterization of a rare H12N3 avian influenza virus isolated from a green-winged teal in Japan

This study reports on the genetic characterization of an avian influenza virus, subtype H12N3, isolated from an Eurasian green-winged teal (Anas crecca) in Japan in 2009. The entire genome sequence of the isolate was analyzed, and phylogenetic analyses were conducted to characterize the evolutionary history of the isolate. Phylogenetic analysis of the hemagglutinin and neuraminidase genes indicated that the virus belonged to the Eurasian-like avian lineage. Molecular dating indicated that this H12 virus is likely a multiple reassortant influenza A virus. This is the first reported characterization of influenza A virus subtype H12N3 isolated in Japan and these data contribute to the accumulation of knowledge on the genetic diversity and generation of novel influenza A viruses.National Institute of Allergy and Infectious Diseases (U.S.) (Contracts HHSN266200700009C and HHSN266200700007)Japan Society for the Promotion of Science. Grant-in-Aid for the Bilateral Joint ProjectsHeiwa Nakajima Foundatio