Principal Bands Research Articles

Seismic Fault Slip Behavior Predicted From Internal Microphysical Processes

AbstractEarthquake simulation and hazard prediction are strongly hampered by insufficient physical knowledge of the constitutive behavior of faults. Laboratory studies of carbonate fault friction suggest that seismogenic rupture on faults in carbonate terrains can be explained by a transition from high friction at low initial sliding velocities (V) to low friction at seismic slip velocities, that is, by rapid dynamic weakening. One proposed explanation for this weakening, invokes frictional heating resulting in deformation by grain boundary sliding accommodated by solid‐state diffusion (sometimes referred to as “viscous” or “superplastic” flow). We recently added this dynamic weakening mechanism to a microphysically based model addressing the (rate‐and‐state) frictional behavior of granular gouges undergoing low V shear characteristic of rupture nucleation and arrest. In the present study, we applied the full model to simulate seismic slip in laboratory carbonate faults. Assuming that slip localizes in a principal shear band within the fault (gouge) zone, and accounting for grain size evolution with velocity and temperature, the model reproduces the frictional, thermal and (micro‐)structural evolution observed during seismic slip experiments. In particular, it predicts spatial and temporal evolutions of grain size, porosity, and dominant deformation mechanisms, within and outside the assumed shear band, consistent with trends identified in the laboratory and natural fault zones.

Effect of protective agents on the storage stability of freeze-dried Ligilactobacillus salivarius CECT5713.

Ligilactobacillus salivarius is a lactic acid bacterium exhibiting several health benefits but remains commercially underexploited due to its inability to survive during long-term storage in the dried state. Our objective was to study the effect of various protective molecules (maltodextrin, trehalose, antioxidants, and fructooligosaccharides), being efficient on other bacteria, on the freeze-dried stability of L. salivarius CECT5713. The culturability was evaluated after freezing, freeze-drying, and subsequent storage at 37°C, as well as the biochemical composition of cells in an aqueous environment using Fourier transform infrared (FTIR) micro-spectroscopy. The assignment of principal absorption bands to cellular components was performed using data from the literature on bacteria. The membrane fatty acid composition was determined after freeze-drying and storage. Glass transition temperature of the liquid and freeze-dried bacterial suspensions and water activity of the freeze-dried samples were measured. The best storage stability was observed for the formulations involving maltodextrin and antioxidants. The analysis of the FTIR spectra of freeze-thawed cells and rehydrated cells after freeze-drying and storage revealed that freeze-drying induced damage to proteins, peptidoglycans of the cell wall and nucleic acids. Storage stability appeared to be dependent on the ability of the protective molecules to limit damage during freeze-drying. The inactivation rates of bacteria during storage were analyzed as a function of the temperature difference between the product temperature during sublimation or during storage and the glass transition temperature, allowing a better insight into the stabilization mechanisms of freeze-dried bacteria. Maintaining during the process a product temperature well below the glass transition temperature, especially during storage, appeared essential for L. salivarius CECT5713 storage stability. KEY POINTS: • L. salivarius CECT5713 highly resisted freezing but was sensitive to freeze-drying and storage. • Freeze-drying and storage mainly altered cell proteins, peptidoglycans, and nucleic acids. • A glassy matrix containing maltodextrin and an antioxidant ensured the highest storage stability.

Varvec{varepsilon }-Shading Operator on Riesz Spaces and Order Continuity of Orthogonally Additive Operators

Given a Riesz space E and 0 < e in E, we introduce and study an order continuous orthogonally additive operator which is an varepsilon -approximation of the principal lateral band projection Q_e (the order discontinuous lattice homomorphism Q_e :E rightarrow E which assigns to any element x in E the maximal common fragment Q_e(x) of e and x). This gives a tool for constructing an order continuous orthogonally additive operator with given properties. Using it, we provide the first example of an order discontinuous orthogonally additive operator which is both uniformly-to-order continuous and horizontally-to-order continuous. Another result gives sufficient conditions on Riesz spaces E and F under which such an example does not exist. Our next main result asserts that, if E has the principal projection property and F is a Dedekind complete Riesz space then every order continuous regular orthogonally additive operator T :E rightarrow F has order continuous modulus |T|. Finally, we provide an example showing that the latter theorem is not true for E = C[0,1] and some Dedekind complete F. The above results answer two problems posed in a recent paper by O. Fotiy, I. Krasikova, M. Pliev and the second named author.

Extraction optimization, characterization and anti- inflammatory activity of functional protein from Mangifera indica seeds kernel

Mango seed kernel (MSK) was observed to be a likely source of bioactive protein. Box-Behnken Design (BBD) was employed to optimize the protein extraction conditions. The optimum extraction conditions for maximum protein yield (68.336%) were corresponding to extraction temperature 54.53 °C, buffer-to-sample values 41.79 mL/g and extraction time 120 min with desirability value of 0.471%. The results of electrophoresis patterns of MSKP revealed two types of proteins; low molecular weight between 6 to 98 kDa explained the presence of globulin with type (2S) and another principal protein band of 27.6 kDa explained the presence of lectins. The extracted proteins under optimized conditions showed inhibition activity of nitric oxide (NO) release and pro-inflammatory inducers like (IL-6), (IL-1r3) and (TNF-a) in lipopolysaccharide (LPS)-induced RAW264.7 macrophages. These findings revealed that MSK could be used as a promising nutraceutical of functional and health-promoting proteins.

A Coarse‐To‐Fine Approach to Detect Shadows in the Chang’E−4 VNIS Hyperspectral Images

AbstractThe low value of shadow pixels in the images sensed by the Visible and Near‐infrared Imaging Spectrometers (VNIS) aboard Chang’E−4 Yutu‐2 rover leads to an unrealistic representation of lunar surface reflectance. Due to the shadow features and lack of additional information (e.g., topography and shadow labels), it is challenging to apply existing methods to detect shadows for VNIS data. Therefore, it is necessary to propose an effective way to detect and correct the shadows in the VNIS data. In this paper, a coarse‐to‐fine approach to detect shadows in the VNIS images is developed. First, to better resolve the shadows, they are enhanced based on principal component analysis and band combination. Second, in the coarse detection stage, two shadow indices, SId and SIs, based on the features extracted in shadow enhancement are constructed. Subsequently, they are segmented into shadow and nonshadow pixels individually using the Otsu method. Third, in the fine detection stage, by analyzing the performance of the two indices, the shadow and nonshadow pixels are further distinguished through the absolute z‐score to obtain the final results. The experimental results show that the average overall accuracy is 93.94%. The average F1‐score is 85.51%. By comparing with visual inspection and other detection methods, our approach yields a good precision and is expected to be applicable for other VNIS hyperspectral data. After detection, the shadow effect is corrected in the spectral dimension by estimating the loss of radiometric information. Our study can provide a reference for shadow detection of analogous lunar in‐situ observations.

Surface modification of polyimide films towards very low contact angles

Homogeneous plasma treatment was used as a viable approach to modulate the surface characteristics of two polyimide films obtained by high-temperature polycondenzation and conventional casting. Physicochemical transformations of the polymeric materials’ surface were addressed through an interconnected parallel between bulk features, surface chemistry, topography, and wettability before and after exposure to plasma. Rigorous FTIR investigations, further complemented by EDX analysis, were used to qualitatively assess mechanistic insights and plasma-triggered surface chemical modifications by monitoring the main changes in the position and integrated surface area of principal absorption bands. The film-forming conduct and surface specifics of pristine and modified materials were evaluated in terms of mechanical stability, flexibility, morphology, optical transmittance, and roughness fluctuations. The connection between the plasma-induced hydrophilization of the two films and severe changes in polar:dispersive surface components, work of adhesion, and surface energy were thoroughly analyzed. Short- and long-term cell proliferation studies of the pristine and activated films were employed to determine the effect of plasma-induced modifications upon fibroblast growth.

Prototyping Crop Traits Retrieval Models for CHIME: Dimensionality Reduction Strategies Applied to PRISMA Data.

In preparation for new-generation imaging spectrometer missions and the accompanying unprecedented inflow of hyperspectral data, optimized models are needed to generate vegetation traits routinely. Hybrid models, combining radiative transfer models with machine learning algorithms, are preferred, however, dealing with spectral collinearity imposes an additional challenge. In this study, we analyzed two spectral dimensionality reduction methods: principal component analysis (PCA) and band ranking (BR), embedded in a hybrid workflow for the retrieval of specific leaf area (SLA), leaf area index (LAI), canopy water content (CWC), canopy chlorophyll content (CCC), the fraction of absorbed photosynthetic active radiation (FAPAR), and fractional vegetation cover (FVC). The SCOPE model was used to simulate training data sets, which were optimized with active learning. Gaussian process regression (GPR) algorithms were trained over the simulations to obtain trait-specific models. The inclusion of PCA and BR with 20 features led to the so-called GPR-20PCA and GPR-20BR models. The 20PCA models encompassed over 99.95% cumulative variance of the full spectral data, while the GPR-20BR models were based on the 20 most sensitive bands. Validation against in situ data obtained moderate to optimal results with normalized root mean squared error (NRMSE) from 13.9% (CWC) to 22.3% (CCC) for GPR-20PCA models, and NRMSE from 19.6% (CWC) to 29.1% (SLA) for GPR-20BR models. Overall, the GPR-20PCA slightly outperformed the GPR-20BR models for all six variables. To demonstrate mapping capabilities, both models were tested on a PRecursore IperSpettrale della Missione Applicativa (PRISMA) scene, spectrally resampled to Copernicus Hyperspectral Imaging Mission for the Environment (CHIME), over an agricultural test site (Jolanda di Savoia, Italy). The two strategies obtained plausible spatial patterns, and consistency between the two models was highest for FVC and LAI (R2 = 0.91, R2 = 0.86) and lowest for SLA mapping (R2 = 0.53). From these findings, we recommend implementing GPR-20PCA models as the most efficient strategy for the retrieval of multiple crop traits from hyperspectral data streams. Hence, this workflow will support and facilitate the preparations of traits retrieval models from the next-generation operational CHIME.

Lithological mapping using remote sensing techniques: A case study of Alagbayan area, Dornogobi province, Mongolia

This study investigated the multispectral remote sensing techniques including ASTER, Landsat 8 OLI, and Sentinel 2A data in order to distinguish different lithological units in the Alagbayan area of Dornogobi province, Mongolia. Therefore, Principal component analysis (PCA), Band ratio (BR), and Support Vector Machine (SVM), which are widely used image enhancement methods, have been applied to the satellite images for lithological mapping. The result of supervised classification shows that Landsat data gives a better classification with an overall accuracy of 93.43% and a kappa coefficient of 0.92 when the former geologic map and thin section analysis were chosen as a reference for training samples. Moreover, band ratios of ((band 7 + band 9)/band 8) obtained from ASTER corresponds well with carbonate rocks. According to PCs, PC4, PC3 and PC2 in the RGB of Landsat, PC3, PC2, PC6 for ASTER data are chosen as a good indicator for different lithological units where Silurian, Carboniferous, Jurassic, and Cretaceous formations are easily distinguished. In terms of Landsat images, the most efficient BR was a ratio where BRs of 5/4 for alluvium, 4/7 for schist and 7/6 to discriminate granite. In addition, as a result of BR as well as PCA, Precambrian Khutag-Uul metamorphic complex and Norovzeeg formation can be identified but granite-gneiss and schist have not given satisfactory results.

X-ray, IR and SEM studies on some Li-Cd ferrites

Lithium-Cadmium ferrites with general formula Li0.5-x/2 Fe2.5-x/2 Cdx O4 (with x = 0,0.1,0.2....,0.7) were prepared by standard ceramic method. X-ray diffraction studies confirms single phase formation and lattice parameters were calculated. The crystal structure is cubic and lattice parameter increases with increasing Cd content. The infrared absorption (IR) spectra of all the samples were recorded in the range 200-800 cm-1 at room temperature in the KBr medium. Lithium ferrite shows four principal bands and some shoulders have been observed. The force constants Kt and Ko were calculated using Waldron's analysis. Scanning electron microscopy studies shows increase in grain size up to x = 0.1 and then the grain size decreases with increase in cadmium content.

Migrating rivers, consequent paleochannels: The unlikely partners and hotspots of flooding

Furious floods have become an omnipresent reality with the dawn of climate change and its transition to adulthood. Since climate change has now become an accepted reality, analysing the factors that favour or disfavour floods are an urgent requirement. Here we showcase the role of paleochannels, a product of migrating rivers, in a catastrophic flood in the south-western part of the Indian Peninsula. This study exposes whether these geomorphic features facilitate or impede floods. For the purpose of extracting paleochannels and floodwater mapping, we utilized multiple satellite datasets and took advantage of diversified feature selection algorithms. Paleochannels were demarcated viz., initial identification of a few paleochannels from literature and confirmation through high-resolution Google Earth (GE) images, followed by Principal Component Analysis (PCA) of Sentinel-2 images using Google Earth Engine (GEE), and a supervised classification of the principal bands 1, 2, and 3. False-positives were eliminated using Object-Oriented Analysis (OOA), which reduced the 964,254 polygons to 23,254. These polygons were visually affirmed using GE images that resulted in 115 paleochannels as the final collection. A few locations were verified through Vertical Electrical Sounding (VES) using the Schlumberger method. The features were analysed with the floodwaters of the 2018 catastrophic flood, extracted from Synthetic Aperture Radar (SAR) data, which was delineated for different temporal limits including the day of peak flood of August 17, 2018. During the peak flood, the inundation of the study area extended to 534.86 km2 with all the paleochannels getting immersed in floodwater. After 44 days of peak flood, the post-flood analysis revealed that when the floodwater receded 50%, the paleochannels emptied 87.39%, with the midland paleochannels discharging more than those of lowlands. Thus, such geomorphic features can be flood hotspots, but can be considered for discharging floodwater to mitigate flood risk in case of unprecedented rain.

Geohazard characterization using remote sensing to model flash floods of the southeast Sinai, Egypt

Flash floods have led to disruptions of human activities and the destruction of properties particularly in the Nuweiba region of southeast Sinai. Despite the arid nature of Sinai, flash floods still pose a great hazard to the region. Using remote sensing characterization, geohazard models were developed to identify flash flood areas; delineate and discriminate morphological features, active channels areas, and soil physiography with a view to categorize risk areas exposed to flash floods hazards in a hazard map; and proffer measures for mitigation. The characterization was achieved using a workflow model developed from spatial data sets of the Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) and the red-green-blue (RGB) composites from Landsat bands 7 Enhanced Thematic Mapper (ETM+). The data were used to investigate and assess flash flood areas for morphological attributes, watershed basin characterization, and generation of false color composite from the Landsat 7 ETM+ 7, 4, and 2 RGB bands, and the principal component analysis band from a composite of 742 RGB. Multivariate analysis of generated raster layer attributes provided enhancements and attribute discrimination for delineating areas of active flood channels, upslope zones, and soil physiography discrimination from their spectral reflectance. The results are presented in an integrated approach of remote sensing with geographic information systems (GIS) and indicate that the soil types and geologic units contribute greatly toward activation of these flash floods, which is triggered by intense rainstorms. Components of the generated map attributes of SRTM DEM, gradient of DEM, and Landsat 7 ETM+ composite of 742 bands in GIS were used to generate a hazard map using spatial analysis to depict the nature and scale of the issues identified. Due to the flash flood vulnerabilities, the study area was classified into stable/low-, moderate-, and high-risk areas. Mitigation measures to control flash floods were proposed to enable adequate preparations to mitigate impending flash flood disasters.

Geospatial Interpretation of Onshore Hydrocarbon Micro–Seepage Induced Alterations in Soils and Sediments by Spectral Enhancement Techniques

Hydrocarbon micro – seepages are light hydrocarbon that cause oxidation – reduction reaction on the earth’s surface, resulting in alterations and anomalies such as red bed bleaching, ferrous iron enrichment and increase in the concentration of clay minerals and carbonate in overlying soils and sediments. Remote sensing has become a valuable tool in hydrocarbon micro – seepage studies and have been successfully used to interpret surface alterations and anomalies of minerals. In this study, Landsat 7 ETM+ remotely sensed data was utilized for interpreting the onshore hydrocarbon micro – seepage induced alterations zone in Ugwueme. Spectral enhancements techniques such as the principal component analysis (PCA), band ratio (BR) and false color composite (FCC) were adopted for delineating alteration zones. With Landsat 7 ETM+ band selection, and for PCA, the 1457PC3, 1345PC2 and 3457PC4 are the most suitable PC image for spectral enhancement of ferric iron, ferrous iron and clay minerals. Band ratio index such as (3/1), (7/5) and (2+5)/(3+4) also yields better enhancement for anomalous micro – seepage. The study shows that PCA, BR, FCC are good spectral enhancement techniques for interpreting hydrocarbon micro – seepage alterations in overlying soils and sediments.

Determining effective water depth for total suspended solids (TSS) mapping using PlanetScope imagery

ABSTRACT The rapid development of remote sensing technology has increased the possibility to produce a spatially explicit estimation of Total Suspended Solids (TSS). However, factual information regarding the effective depth of waters where TSS can be effectively mapped using remote sensing data is rare. This information is essential to determine the effective depth of TSS mapping and the effect of the water column on the representativeness of the estimation results. This study aimed to (1) determine the effective water depths of TSS mapping using PlanetScope imagery, (2) map the spatial distribution of TSS at every effective depth using PlanetScope imagery, and (3) analyse the spatial distribution of the mapped TSS based on the best empirical modelling for every effective depth. PlanetScope image offered new opportunities in high spatial resolution remote sensing with daily revisit time. Four single bands of PlanetScope images (blue, green, red, and near-infrared) – corrected to the Bottom of Atmosphere (BOA) reflectance, 12 band ratios, and four Principal Component bands (PC-band) were inputted to the determination process of the effective water depths. Empirical modelling between the in-situ TSS at each effective water depth andures what was the issue, wasnt able to o PlanetScope pixels at the corresponding locations was conducted. However, only image bands that exceeded the significance limit (r) were used for modelling using linear, exponential, logarithmic, second-order polynomial, or power regressions. The results showed that the band ratios of PlanetScope images could record TSS up to the effective depth of 1.8 m. The best empirical modelling in each effective depth of waters was the band ratio which is dominated by the contribution of the blue bands (B1), red (B3), and NIR (B4). B4/B3 bands combination produced TSS information at the effective depths of 0–0.2 and 0–0.4 m, B3/B4 bands at 0–0.6 and 0–0.8 m, B1/B4 bands at 0–1 and 0–1.2 m, and B1/B3 bands at 0–1.4, 0–1.61, and 0–1.8 m. For all effective depths, the spatial distribution pattern of TSS in the study site (Menjer Lake, Central Java, Indonesia) showed that high concentrations evenly spread along the edge and became increasingly lower to the centre of the lake. Meanwhile, the vertical distribution showed that the deeper the cumulative water depth, the higher the TSS.

Enhancing the Surface Properties and Structure of MWNTs by Effective Ion Beam Irradiation

The effects of irradiating multiwalled carbon nanotubes (MWNTs) with 100 keV He ions on the surface morphology were examined. Due to irradiation effects, the tube diameter reduced as revealed by scanning electron microscopy (SEM). Raman spectroscopy was used to investigate MWNTs by analyzing the principal bands in the spectra of virgin and radiated MWNT specimens. The effects of irradiation fluences on the disorder (D-band) and the graphite (G-band) modes were investigated. The possibility and prospects of using ion irradiation for controlling the wettability of the MWNT surface were investigated. The irradiation facility produces an MWNT coating that is either hydrophobic or hydrophilic to certain liquids. This analysis demonstrates that ion beam irradiation could be used as an alternative tool to change the structure of CNT and enhancing their wettability application, especially in water treatment. According to Raman spectra, when the fluence increases, the MWNTs become disordered due to the defect produced. The amorphous state of MWNTs could be attained with greater ion irradiation fluences.

3D Clumps/Extracellular Matrix Complexes of Periodontal Ligament Stem Cells Ameliorate the Attenuating Effects of LPS on Proliferation and Osteogenic Potential.

Background: The effects of lipopolysaccharide (LPS) on cell proliferation and osteogenic potential (OP) of MSCs have been frequently studied. Objective: to compare the effects of LPS on periodontal-ligament-derived mesenchymal stem cells (PDLSCs) in monolayer and 3D culture. Methods: The PDLSCs were colorimetrically assessed for proliferation and osteogenic potential (OP) after LPS treatment. The 3D cells were manually prepared by scratching and allowing them to clump up. The clumps (C-MSCs) were treated with LPS and assessed for Adenosine triphosphate (ATP) and OP. Raman spectroscopy was used to analyze calcium salts, DNA, and proline/hydroxyproline. Multiplexed ELISA was performed to assess LPS induced local inflammation. Results: The proliferation of PDLSCs decreased with LPS. On Day 28, LPS-treated cells showed a reduction in their OP. C-MSCs with LPS did not show a decrease in ATP production. Principal bands identified in Raman analysis were the P–O bond at 960 cm−1 of the mineral component, 785 cm−1, and 855 cm−1 showing qualitative changes in OP, proliferation, and proline/hydroxyproline content, respectively. ELISA confirmed increased levels of IL-6 and IL-8 but with the absence of TNF-α and IL-1β secretion. Conclusions: These observations demonstrate that C-MSCs are more resistant to the effects of LPS than cells in monolayer cell culture. Though LPS stimulation of C-MSCs creates an early pro-inflammatory milieu by secreting IL-6 and IL-8, PDLSCs possess inactivated TNF promoter and an ineffective caspase-1 activating process.

The Effect of Principal Component Analysis Parameters on Solar-Induced Chlorophyll Fluorescence Signal Extraction

Solar-induced chlorophyll fluorescence (SIF), one of the three main releasing pathways of vegetation-absorbed photosynthetic active radiation, has been proven as an effective monitoring implementation of leaf photosynthesis, canopy growth, and ecological diversity. There exist three categories of SIF retrieval methods, and the principal component analysis (PCA) retrieval method is obtrusively eye-catching due to its brief, data-driven characteristics. However, we still lack a lucid understanding of PCA’s parameter settings. In this study, we examined if principal component numbers and retrieval band regions could have effects on the accuracy of SIF inversion under two controlled experiments. The results revealed that the near-infrared region could remarkably boost SIF’s retrieval accuracy, whereas red and near-infrared bands caused anomalous values, which subverted a traditional view that more retrieval regions might provide more photosynthetic information. Furthermore, the results demonstrated that three principal components would benefit more in PCA-based SIF retrieval. These arguments further help elucidate the more in-depth influence of the parameters on the PCA retrieval method, which unveil the potential effects of different parameters and give a parameter-setting foundation for the PCA retrieval method, in addition to assisting retrieval achievements.

Using reflectance spectroscopy and Advanced Spaceborne Thermal Emission and Reflection Radiometer data to identify bauxite deposits in vicinity of Az Zabirah, northern Saudi Arabia

Bauxite samples from deposits in northern Saudi Arabia were identified in the laboratory using spectral reflectance measurements (at 0.3–2.5 μm) and X-ray diffraction (XRD). The XRD results revealed that the bauxite deposits are composed mainly of goethite, gibbsite, and boehmite with small amounts of kaolinite, hematite, and quartz. The bauxite spectra revealed the presence of significant iron oxides (at 0.5 and 0.87 μm) accompanied by water (at 1.4 and 1.9 μm) and aluminum hydroxide (at 2.2 μm). The convolved Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) spectra of the bauxite samples were characterized by an aluminum hydroxide feature in ASTER band 6 (at 2.2 μm). The results demonstrated that principal components analysis band PC2 is the best component for delineating the bauxite deposits. Fractional abundances of bauxite were derived by using a matched-filtering method. This study demonstrates the applicability of reflectance spectroscopy and ASTER data to provide spectral information for distinguishing economically important minerals from visible and near-infrared and shortwave-infrared spectra in arid and semiarid environments such as in Saudi Arabia.

Fuzzy-based Integration of Sentinel-2 MSI Data for Locating Potential Hydrocarbon Microseepag

The vertical migration of hydrocarbons from oil and gas reservoirs to the surface and/or subsurface (i.e., microseepage) can induce mineral alteration that results in concentration of ferrous iron, clay, and carbonate minerals at the Earth’s surface. These altered zones may be detected in remote sensing imagery based on their specific reflectance spectral characteristics; zones where three types of mineral alteration occur simultaneously reflect possible hydrocarbon microseepage locations with the potential for underlying oil and gas reservoirs. In this study, a fuzzy set based approach was used to integrate the results of principal component analysis (PCA) and band ratios (BRs). First, each selected indicative principal component (PC) and BR was treated as a fuzzy set, and a corresponding fuzzy membership function defined. The membership degree of each pixel, which indicates the possibility of the presence of specific altered minerals, was then calculated. Subsequently, the Gamma operator was used to fuse all fuzzy sets to create a new fuzzy set, which was then defuzzied and used to indicate the possible locations of hydrocarbon microseepages. The Sentinel-2 MSI data were used to illustrate the approach and the zones of hydrocarbon microseepage mapped.

Satellite data based abundance mapping of mafic and ultramafic rocks in Mettupalayam, Tamil Nadu, India

The mafic and ultramafic rocks of Mettupalayam belong to the southern granulite terrain of India, which is concomitant with vital economic resources. The advantage of Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) data for mapping the litho units are exploited well here for differentiating the rock units with the aid of band combination (1, 3, 6), principal component analysis (5, 1, 6) and band ratioed band combination (2/3, 3/2, 1/5 and (9–8)/1, (8–6)/2, and (9–6)/3). As part of the field study, the collection of samples and ground control points were carried out and in addition to that, the generation of laboratory reflectance spectra for samples was achieved. The Spectral Angle Mapper (SAM) and Support Vector Machine (SVM) were performed using ASTER data with the aid of spectra obtained from the laboratory conditions to demarcate the abundance of mafic and ultramafic rocks of the area. The XRF method was used to retrieve the major oxides of the field-collected samples and the spectral absorption characters are validated with it. The results show a vibrant interpretation of the litho units.

How silicon and boron dopants govern the cryogenic scintillation properties of N-type GaAs

This paper is the first report describing how the concentrations of silicon and boron govern the cryogenic scintillation properties of n-type GaAs. It shows that valence band holes are promptly trapped on radiative centers and then combine radiatively with silicon donor band electrons at rates that increase with the density of free carriers. It also presents the range of silicon and boron concentrations needed for efficient light emission under X-ray excitation, which along with its low band gap and apparent absence of afterglow, make scintillating GaAs suitable for the detection of rare, low-energy electronic excitations from interacting dark matter particles. A total of 29 samples from four different suppliers were studied. Luminosities and timing responses were measured for the four principal emission bands centered at 860, 930, 1070, and 1335 nm, and for the total emissions. Excitation pulses of 40 kVp X-rays were provided by a light-excited X-ray tube driven by an ultra-fast laser. Scintillation emissions from 800 to 1350 nm were measured using an InGaAs photomultiplier. Within the concentration ranges of free carriers from 2 x 1016/cm3 to 6 x 1017/cm3 and boron from 1.5 × 1018/cm3 to 6 x 1018/cm3, nine samples have luminosities > 70 photons/keV and two have luminosities > 110 photons/keV. Other samples in that range have lower luminosities due to higher concentrations of non-radiative centers. The decay times decrease by typically a factor of ten with increasing free carrier concentrations from 1017/cm3 to 2 x 1018/cm3.