Isolation and structural elucidation of novel fusicoccan dehydroxypericonicin A from Roussoella sp.

A potent antifungal fusicoccane dehydroxypericonicin A (1) was isolated from Roussoella sp. along with known allantofuranone (2). The relative structure of 1 was fully elucidated by NMR spectroscopic manner. The suggested relative structure was confirmed by DFT (density functional theory)-based 13C NMR chemical shift calculations. The absolute configuration was investigated by a spectral comparison of the experimental ECD (electronic circular dichroism) spectrum with that based on the DFT calculations.

Unsupervised Identification of Targeted Spectra Applying Rank1-NMF and FCC Algorithms in Long-Wave Hyperspectral Infrared Imagery

Clustering methods unequivocally show considerable influence on many recent algorithms and play an important role in hyperspectral data analysis. Here, we challenge the clustering for mineral identification using two different strategies in hyperspectral long wave infrared (LWIR, 7.7–11.8 μm). For that, we compare two algorithms to perform the mineral identification in a unique dataset. The first algorithm uses spectral comparison techniques for all the pixel-spectra and creates RGB false color composites (FCC). Then, a color based clustering is used to group the regions (called FCC-clustering). The second algorithm clusters all the pixel-spectra to directly group the spectra. Then, the first rank of non-negative matrix factorization (NMF) extracts the representative of each cluster and compares results with the spectral library of JPL/NASA. These techniques give the comparison values as features which convert into RGB-FCC as the results (called clustering rank1-NMF). We applied K-means as clustering approach, which can be modified in any other similar clustering approach. The results of the clustering-rank1-NMF algorithm indicate significant computational efficiency (more than 20 times faster than the previous approach) and promising performance for mineral identification having up to 75.8% and 84.8% average accuracies for FCC-clustering and clustering-rank1 NMF algorithms (using spectral angle mapper (SAM)), respectively. Furthermore, several spectral comparison techniques are used also such as adaptive matched subspace detector (AMSD), orthogonal subspace projection (OSP) algorithm, principal component analysis (PCA), local matched filter (PLMF), SAM, and normalized cross correlation (NCC) for both algorithms and most of them show a similar range in accuracy. However, SAM and NCC are preferred due to their computational simplicity. Our algorithms strive to identify eleven different mineral grains (biotite, diopside, epidote, goethite, kyanite, scheelite, smithsonite, tourmaline, pyrope, olivine, and quartz).

Identification of 5-Fluoro-5-Deoxy-Ribulose as a Shunt Fluorometabolite in Streptomyces sp. MA37

A fluorometabolite, 5-fluoro-5-deoxy-D-ribulose (5-FDRul), from the culture broth of the soil bacterium Streptomyces sp. MA37, was identified through a combination of genetic manipulation, chemo-enzymatic synthesis and NMR comparison. Although 5-FDRul has been chemically synthesized before, it was not an intermediate or a shunt product in previous studies of fluorometalism in S. cattleya. Our study of MA37 demonstrates that 5-FDRul is a naturally occurring fluorometabolite, rendering it a new addition to this rare collection of natural products. The genetic inactivation of key biosynthetic genes involved in the fluorometabolisms in MA37 resulted in the increased accumulation of unidentified fluorometabolites as observed from 19F-NMR spectral comparison among the wild type (WT) of MA37 and the mutated variants, providing evidence of the presence of other new biosynthetic enzymes involved in the fluorometabolite pathway in MA37.

APPLICATION OF OFF-NADIR SATELLITE IMAGERY IN EARTHQUAKE DAMAGE ASSESSMENT USING OBJECT-BASED HOG FEATURE DESCRIPTOR

<p><strong>Abstract.</strong> One of the most crutial applications of very-high-resolution (VHR) satellite images is disaster management. In disaster management, time is of great importance. Therefore, it is vital to acquire satellite images as quickly as possible and benefit from automatic change detection to speed up the process. Automatic damage map generation is performed by overlaying the co-registered before and after images of the area of interest and, compring them to highlight the affected infrastructures. For speeding up image capture, satellites tilt their imaging sensor and take images from oblique angles. However, this kind of image acquisition causes severe geometric distortion in the images, which hinders image co-registration in automatic change detection. In this study, a Patch-Wise Co-Registration (PWCR) solution is used. In this algorithm, the before and after images are co-registered in a segment-by-segment manner. From the literature, this algorithm is followed by a spectral comparison to detect changes. However, due to the complicated structure of debris in damage detection applications, spectral comparison methods cannot perform well. In this work, we developed an object-based method using Histogram of Oriented Gradient descriptor to detect damges and compared our results to different existing spectral and textural change detection methods. The algorithm is tested on images from the 2010-Heidi earthquake, captured by DigitalGlobe. The achieved highly accurate results demonstrate the potential of using off-nadir remote sensing images for automatic urban damage detection possibly in early response systems as it speeds up the damage map generation by providing flexibility to utilize images taken from different anlges.</p>

MALDI-TOF MS protein fingerprinting of mixed samples

Analytical techniques currently available for the characterization of mixtures of microorganisms are generally based on next-generation sequencing. Motivated to develop practical and less-expensive methods for characterizing such mixtures, we propose, as an alternative or complement, the use of matrix-assisted laser-desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS), which is capable of high-resolution discrimination between species and even between biotypes within species. Potential approaches employing this technique for such characterization are discussed along with impediments to their successful employment. As a consequence, our rationale has been to capitalize on the powerful algorithms currently available for spectral comparison. Following this rationale, the first priority is to ensure the generation of MALDI-TOF MS spectra from mixtures of microorganisms that contain manageable peak complexities and that can be handled by the existing spectral comparison algorithms, preferably with the option to archive and re-run sample preparations and to pipette replicates of these onto MALDI-TOF MS sample plates. The second priority is to ensure that database entry is comparably facile to sample preparation so that large databases of known microorganism mixture MALDI-TOF MS spectra could be readily prepared for comparison with the spectra of unknown mixtures. In this article, we address the above priorities and generate illustrative MALDI-TOF MS spectra to demonstrate the utility of this approach. In addition, we investigate methods aimed at chemically modulating the peak complexity of the obtained MALDI-TOF MS spectra.