Identification of Rocks and Their Quartz Content in Gua Musang Goldfield Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Imagery

© 2017 Kouame Yao et al. Quartz is an important mineral element and the most abundant rock-forming mineral that controls the mineralogy of a reservoir. At the surface, quartz is more stable than most other rock minerals because it is made up of interlocking silica that makes it quite resistant to mechanical weathering. Quartz abundance is an indication of mineralization in many metal deposits; therefore, identification and mapping of quartz in rocks are of great value for exploration and resource potential assessments. In this study, thermal infrared (TIR) bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery were used to identify quartz contained rocks in Gua Musang. First, the image was corrected for atmospheric effect and the study area subset for further processing. Thereafter, spectral transformation (principal component analysis (PCA)) was implemented on the TIR bands and the resulting principal component (PC) images were analysed. The three optimal PCs were selected using the strength of spectral interaction and the eigenvalues of each band. To discriminate between quartz-rich and quartz-poor rocks, RGB false colour composite and greyscale image of one of the PCs were analysed. The result shows that volcanogenic igneous rock and carbonate sedimentary rocks of Permian formation are quartz-poor while Triassic sedimentary rock made up of organic particles and sandstone is quartz-rich. On the contrary, the quartz content in the metamorphic rock varies across the area but is richer in quartz content than the igneous and carbonate rocks. Classification of the composite image classified using maximum likelihood (ML) supervised classification method produced overall accuracy and Kappa coefficient of 96.53%, and 0.95, respectively

Progression in Photocatalytic Materials for Efficient Performance

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In-Situ Synthesis of Nb2O5/g-C3N4 Heterostructures as Highly Efficient Photocatalysts for Molecular H2 Evolution under Solar Illumination

This work focuses on the synthesis of heterostructures with compatible band positions and a favourable surface area for the efficient photocatalytic production of molecular hydrogen (H2). In particular, 3-dimensional Nb2O5/g-C3N4 heterostructures with suitable band positions and high surface area have been synthesized employing a hydrothermal method. The combination of a Nb2O5 with a low charge carrier recombination rate and a g-C3N4 exhibiting high visible light absorption resulted in remarkable photocatalytic activity under simulated solar irradiation in the presence of various hole scavengers (triethanolamine (TEOA) and methanol). The following aspects of the novel material have been studied systematically: the influence of different molar ratios of Nb2O5 to g-C3N4 on the heterostructure properties, the role of the employed hole scavengers, and the impact of the co-catalyst and the charge carrier densities affecting the band alignment. The separation/transfer efficiency of the photogenerated electron-hole pairs is found to increase significantly as compared to that of pure Nb2O5 and g-C3N4, respectively, with the highest molecular H2 production of 110 mmol/g·h being obtained for 10 wt % of g-C3N4 over Nb2O5 as compared with that of g-C3N4 (33.46 mmol/g·h) and Nb2O5 (41.20 mmol/g·h). This enhanced photocatalytic activity is attributed to a sufficient interfacial interaction thus favouring the fast photogeneration of electron-hole pairs at the Nb2O5/g-C3N4 interface through a direct Z-scheme

Extraction of Sulfur Compounds from Model Petroleum Products using Fe3 O4 Nanoparticles and Acetic Acid-1-Butyl-3-Methylimidazolium Chloride based on Deep Eutectic Solvents

This research demonstrates that deep eutectic solvents (DESs) can eliminate sulfur compounds, which are corrosive and carcinogenic species, from model petroleum products through liquid-liquid extraction. Several monoprotic acids, including formic acid and acetic acid, are used to make DESs, along with 1-butyl-3-methylimidazolium chloride (BmimCl) as a hydrogen bond acceptor. These DESs are used for the first time to remove sulfur compounds (thiophene and dibenzothiophene) from an alkane as a model hydrocarbon (n-octane), which is used instead of crude oil as the latter contains a variety of species, including nitrogen compounds, hydrocarbons, and oxygen. The optimal parameters for the removal of sulfur are discussed, including the extraction temperature, reaction time, and mass ratio of DES to the model hydrocarbon, whilst the regeneration of DESs is also considered. H2O2 and iron oxide (Fe3O4) are also used as nanoparticle (NP) catalysts to enhance the sulfur removal process. Several characterization methods, including scanning electron microscopy, Fourier transform infrared, energy dispersive X-ray, and transmission electron microscopy, are used to determine the structural characteristics of the Fe3O4 NPs. The results show that acetic acid, as a monoprotic acid-based DES, is able to remove more than 86% of the sulfur molecules from model petroleum products when the mass ratio of DES to model petroleum products is 2:1, at 30°C and within 60 min. This research provides an important opportunity to advance our understanding of the role of DESs in removing carcinogenic and corrosive particles in industrial processes

Clinical scoring system: a valuable tool for decision making in cases of acute appendicitis

Objective: Decision making in cases of acute appendicitis poses a clinical challenge specially in developing countries where advanced radiological investigations do not appear cost effective and so clinical parameters remain the mainstay of diagnosis. The aim of our study was to devise a scoring system from our local database and test its accuracy in the preoperative diagnosis of acute appendicitis.Methods: Clinical data from 401 patients having undergone appendectomy were collected to identify predictive factors that distinguished those with appendicitis from those who had a negative appendectomy. Ten such factors were identified and using Bayesian probability a weight was assigned to each and the results summated to get an overall score. A cut-off point was identified to separate patients for surgery and those for observation. The scoring system was then retrospectively applied to a second population of 99 patients in order to compare suggested actions (derived from the scoring system) to those actually taken by surgeons. The sensitivity, specificity and accuracy for the level of decision was then calculated.Results: Of the 99 patients, the method suggested immediate surgery for 65 patients, 63 of whom had acute appendicitis (3.1% diagnostic error rate). Of the 33 patients in whom the score suggested active observation, 18 had appendicitis. The accuracy of our scoring system was 82%. The method had a sensitivity of 78%, specificity 89% and a positive predictive value of 97%. The negative appendectomy rate determined by our study was 7% and the perforation rate 13%.CONCLUSION: Scoring system developed from a local database can work effectively in routine practice as an adjunct to surgical decision making in questionable cases of appendicitis

Early Prediction of Lung Cancers Using Deep Saliency Capsule and Pre-Trained Deep Learning Frameworks

Lung cancer is the cellular fission of abnormal cells inside the lungs that leads to 72% of total deaths worldwide. Lung cancer are also recognized to be one of the leading causes of mortality, with a chance of survival of only 19%. Tumors can be diagnosed using a variety of procedures, including X-rays, CT scans, biopsies, and PET-CT scans. From the above techniques, Computer Tomography (CT) scan technique is considered to be one of the most powerful tools for an early diagnosis of lung cancers. Recently, machine and deep learning algorithms have picked up peak energy, and this aids in building a strong diagnosis and prediction system using CT scan images. But achieving the best performances in diagnosis still remains on the darker side of the research. To solve this problem, this paper proposes novel saliency-based capsule networks for better segmentation and employs the optimized pre-trained transfer learning for the better prediction of lung cancers from the input CT images. The integration of capsule-based saliency segmentation leads to the reduction and eventually reduces the risk of computational complexity and overfitting problem. Additionally, hyperparameters of pretrained networks are tuned by the whale optimization algorithm to improve the prediction accuracy by sacrificing the complexity. The extensive experimentation carried out using the LUNA-16 and LIDC Lung Image datasets and various performance metrics such as accuracy, precision, recall, specificity, and F1-score are evaluated and analyzed. Experimental results demonstrate that the proposed framework has achieved the peak performance of 98.5% accuracy, 99.0% precision, 98.8% recall, and 99.1% F1-score and outperformed the DenseNet, AlexNet, Resnets-50, Resnets-100, VGG-16, and Inception models.publishedVersio

Assessment of Geochemical Characteristics and Geomicrobiology of Cave Spring Water from Jaintia and East Khasi Hills of Meghalaya, India

The present study was undertaken to know the concentration of various trace elements and the condition of water quality parameters in the cave water samples besides studying the role the microbes play in the precipitation of minerals in caves. The results revealed that the concentration of various trace elements such as copper, zinc, nickel and cadmium were low and below the water quality standard limits given by WHO (2006). While that of manganese it was exceptionally high, may be due to erosion of the manganese minerals deposits by the spring cave water. The results also revealed that phosphates are present in very low concentration while sulfates are present in high concentration which again may be due to erosion of secondary sulfate minerals. The co-relation matrices and one tailed analysis of variance of physic-chemical factors have been computed and analyzed. The positive correlation coefficient was observed between pH and alkalinity, hardness and conductivity, sulfates and turbidity. The one tailed ANOVA confirms that site spatial variations have less significant effect on concentration of trace elements. Microbial analysis showed that various types of microbes are present in cave sample which may play an important role in mineral precipitation

Laser flash photolysis study of Nb2O5/g-C3N4 heterostructures as efficient photocatalyst for molecular H2 evolution

Improvements of visible light activity, slow recombination rate, stability, and efficiency are major challenges facing photocatalyst technologies today. Utilizing heterostructures of g-C3N4 (bandgap ∼2.7eV) with Nb2O5 (bandgap ∼3.4eV) as an alternative materials for the first time, we tried to overcome such challenges in this work. Heterostructures of Nb2O5/g-C3N4 have been synthesized via hydrothermal technique. And then a time-resolved laser flash photolysis of those heterostructures has been analyzed, focusing on seeking how to improve photocatalytic efficiency for molecular hydrogen (H2) evolution. The transient absorption spectra and the lifetime of charge carriers at different wavelengths have been observed for Nb2O5/g-C3N4, where g-C3N4 was used for a control. The role of hole scavenger (methanol) has also been investigated for the purpose of boosting charge trapping and H2 evolution. The long lifetime of Nb2O5/g-C3N4 heterostructures (6.54165 μs) compared to g-C3N4 (3.1651897 μs) has successfully supported the increased H2 evolution of 75 mmol/h.g. An enhancement in the rate of H2 evolution (160 mmol/h.g) in the presence of methanol has been confirmed. This study not only deepens our understanding of the role of scavenger, but also enables a rigorous quantification of the recombination rate crucial for photocatalytic applications in relation with efficient H2 production

Nucleotide identity and variability among different Pakistani hepatitis C virus isolates

<p>Abstract</p> <p>Background</p> <p>The variability within the hepatitis C virus (HCV) genome has formed the basis for several genotyping methods and used widely for HCV genotyping worldwide.</p> <p>Aim</p> <p>The aim of the present study was to determine percent nucleotide identity and variability in HCV isolates prevalent in different geographical regions of Pakistan.</p> <p>Methods</p> <p>Sequencing analysis of the 5'noncoding region (5'-NCR) of 100 HCV RNA-positive patients representing all the four provinces of Pakistan were carried out using ABI PRISM 3100 Genetic Analyzer.</p> <p>Results</p> <p>The results showed that type 3 is the predominant genotypes circulating in Pakistan, with an overall prevalence of 50%. Types 1 and 4 viruses were 9% and 6% respectively. The overall nucleotide similarity among different Pakistani isolates was 92.50% ± 0.50%. Pakistani isolates from different areas showed 7.5% ± 0.50% nucleotide variability in 5'NCR region. The percent nucleotide identity (PNI) was 98.11% ± 0.50% within Pakistani type 1 sequences, 98.10% ± 0.60% for type 3 sequences, and 99.80% ± 0.20% for type 4 sequences. The PNI between different genotypes was 93.90% ± 0.20% for type 1 and type 3, 94.80% ± 0.12% for type 1 and type 4, and 94.40% ± 0.22% for type 3 and type 4.</p> <p>Conclusion</p> <p>Genotype 3 is the most prevalent HCV genotype in Pakistan. Minimum and maximum percent nucleotide divergences were noted between genotype 1 and 4 and 1 and 3 respectively.</p

Large scale production of novel g-C3N4 micro strings with high surface area and versatile photodegradation ability

An easy, scalable and environmentally benign chemical method has been developed to synthesize micro strings of graphitic-C3N4 (msg-C3N4) through pre-treatment of melamine with HNO 3 in alkaline solvent at low temperature. This methodology results in a unique string type morphology of msg-C3N4 with higher surface area. These msg-C3N4 micro strings were used as a photocatalyst under visible light for photodegradation of rhodamine B, methyl blue and methyl orange. The msg-C3N4 shows enhanced photodegradation efficiency due to its high surface area and favourable bandgap. The first order rate constant for msg-C3N4 was measured which confirms the higher performance of msg-C3N4 in comparison to other reported materials such as g-C3N4, Fe2O3/g-C3N4 and TiO2 nanotubes. Thus, the method developed here is favourable for the synthesis of materials with higher surface area and unique morphology, which are favourable for high photodegradation activity. The Royal Society of Chemistry