scholarly journals Scanning Magnetic Microscope Using a Gradiometric Configuration for Characterization of Rock Samples

Materials ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4154 ◽  
Author(s):  
Jefferson F. D. F. Araujo ◽  
Andre L. A. Reis ◽  
Angela A. P. Correa ◽  
Elder Yokoyama ◽  
Vanderlei C. Oliveira ◽  
...  
Keyword(s):  
Rock Magnetism ◽  
Magnetization Distribution ◽  
Data Set ◽  
Magnetic Interpretation ◽  
Magnetic Carriers ◽  
Moment Distribution ◽  
Good Spatial Resolution ◽  
Comprehensive Information ◽  
Magnetic Microscopy

Scanning magnetic microscopy is a tool that has been used to map magnetic fields with good spatial resolution and field sensitivity. This technology has great advantages over other instruments; for example, its operation does not require cryogenic technology, which reduces its operational cost and complexity. Here, we presented a spatial domain technique based on an equivalent layer approach for processing the data set produced by magnetic microscopy. This approach estimated a magnetic moment distribution over a fictitious layer composed by a set of dipoles located below the observation plane. For this purpose, we formulated a linear inverse problem for calculating the magnetic vector and its amplitude. Vector field maps are valuable tools for the magnetic interpretation of samples with a high spatial variability of magnetization. These maps could provide comprehensive information regarding the spatial distribution of magnetic carriers. In addition, this approach might be useful for characterizing isolated areas over samples or investigating the spatial magnetization distribution of bulk samples at the micro and millimeter scales. This technique could be useful for many applications that require samples that need to be mapped without a magnetic field at room temperature, including rock magnetism.

scholarly journals Scanning Magnetic Microscope Using A Hall-Effect Sensor for Images of Remanent Magnetization Fields

2019 ◽  
Author(s):  
Jefferson F. D. F. Araujo ◽  
Angela A. P. Correa ◽  
Elder Yokoyama ◽  
Andre L. A. dos Reis ◽  
Vanderlei C. Oliveira Jr. ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Hall Effect ◽  
Spatial Resolution ◽  
Room Temperature ◽  
Rock Magnetism ◽  
Magnetization Distribution ◽  
Geological Samples ◽  
Thin Sections ◽  
Magnetic Carriers ◽  
Magnetic Microscopy

Scanning magnetic microscopy is a new tool that has recently been used to map magnetic fields with good spatial resolution and field sensitivity. This technology has great advantages over other instruments; for example, its operation does not require cryogenic technology, which reduces its operational cost and complexity. Here, we describe the construction of a customizing scanning magnetic microscope based on commercial Hall-effect sensors at room temperature that achieves a spatial resolution of 200 µm. Two scanning stages on the x- and y-axes of precision, consisting of two coupled actuators, control the position of the sample, and this microscope can operate inside or outside a magnetic shield. We obtained magnetic field sensitivities better than 521 nTrms/√Hz between 1 and 10 Hz, which correspond to a magnetic momentum sensitivity of 9.20 × 10–10 Am2. In order to demonstrate the capability of the microscopy, polished thin sections of geological samples, samples containing microparticles and magnetic nanoparticles were measured. For the geological samples, a theoretical model was adapted from the magnetic maps obtained by the equipment. Vector field maps are valuable tools for the magnetic interpretation of samples with a high spatial variability of magnetization. These maps can provide comprehensive information regarding the spatial distribution of magnetic carriers. In addition, this model may be useful for characterizing isolated areas over samples or investigating the spatial magnetization distribution of bulk samples at the micro and millimeter scales. As an auxiliary technique, a magnetic sweep map was created using Raman spectroscopy; this map allowed the verification of different minerals in the samples. This equipment can be useful for many applications that require samples that need to be mapped without a magnetic field at room temperature, including rock magnetism, the nondestructive testing of steel materials and the testing of biological samples. The equipment can not only be used in cutting-edge research but also serve as a teaching tool to introduce undergraduate, master's and Ph.D. students to the measurement methods and processing techniques used in scanning magnetic microscopy.

Character selection and the quantification of morphological disparity

Paleobiology ◽  
2016 ◽  
Vol 43 (1) ◽  
pp. 68-84 ◽  
Author(s):  
Bradley Deline ◽  
William I. Ausich
Keyword(s):  
A Priori ◽  
Morphological Diversity ◽  
Small Subset ◽  
Early Paleozoic ◽  
Data Set ◽  
Rarefaction Analysis ◽  
Morphological Studies ◽  
Body Regions ◽  
Scientific Hypotheses

AbstractA priori choices in the detail and breadth of a study are important in addressing scientific hypotheses. In particular, choices in the number and type of characters can greatly influence the results in studies of morphological diversity. A new character suite was constructed to examine trends in the disparity of early Paleozoic crinoids. Character-based rarefaction analysis indicated that a small subset of these characters (~20% of the complete data set) could be used to capture most of the properties of the entire data set in analyses of crinoids as a whole, noncamerate crinoids, and to a lesser extent camerate crinoids. This pattern may be the result of the covariance between characters and the characterization of rare morphologies that are not represented in the primary axes in morphospace. Shifting emphasis on different body regions (oral system, calyx, periproct system, and pelma) also influenced estimates of relative disparity between subclasses of crinoids. Given these results, morphological studies should include a pilot analysis to better examine the amount and type of data needed to address specific scientific hypotheses.

scholarly journals Data set on the characterization of the phytoestrogenic extract and isolated compounds of the roots of Inula racemosa Hook F (Asteraceae)

Data in Brief ◽  
2018 ◽  
Vol 17 ◽  
pp. 770-773
Author(s):  
Mangathayaru Kalachaveedu ◽  
Divya Raghavan ◽  
Srivani Telapolu ◽  
Sarah Kuruvilla ◽  
Balakrishna Kedike
Keyword(s):  
Data Set ◽  
Inula Racemosa

AMS of strained shales fragments: a fast way to quantify the matrix damage

2021 ◽  
Author(s):  
Francho Gracia Puzo ◽  
Charles Aubourg ◽  
Antonio Casas Sainz
Keyword(s):  
Rock Magnetism ◽  
Magnetic Fabric ◽  
Magnetic Minerals ◽  
Statistical Characterization ◽  
Main Thrust ◽  
Rock Fragments ◽  
Scalar Data ◽  
The Matrix ◽  
Degree Of Anisotropy

<p>With the objective of mapping strain on the footwall of a thrust in an orogenic context (Leyre thrust, South Pyrenean Range), more than 1500 unoriented shale fragments (0.7-6.2 g) have been collected. Scalar data (degree of anisotropy P and shape parameter T), together with ellipse of confidence of individual axes provide a proxy of strain acquired by shales in the footwall of the main thrust (Saur et al. 2020).</p><p>Normally, sampling is done by two methods: collecting oriented decimetric hand specimens; or drilling 2.5 cm diameter cylinders. This presents the advantage to deal with oriented samples. However, those techniques are time consuming and it is difficult to collect numerous samples in loose materials such as shales. On the contrary, collecting rock fragments presents the net advantage to provide a much better statistical characterization of the site.</p><p>All samples belong to the Eocene shaly formations from the Jaca Basin. Rock fragments are mostly fractured according to the bedding and/or cleavage surfaces. We demonstrate that the anisotropy parameters P and T maintain their values, regardless the shape and size of fragments. Rock magnetism indicates that AMS is primarily governed by illite, with little contribution of magnetite. AMS provides therefore a proxy of illite organisation within the matrix.</p><p>In the footwall of the Sierra de Leyre we have defined up to 7 parallel sampling sections, whose traces are perpendicular to the direction of the main thrust. On average, each section is made up of about 10 sampling sites and about 15 fragments are collected per site, covering a few square meters.</p><p>We are restricted by the dimensions of AGICO holders (8cm<sup>3</sup> for cubes, or 10 cm<sup>3</sup> for cylinders). It is possible to use an empty 10 cm<sup>3</sup> cylinder, which can be filled with smaller fragments of rock. The automatic rotator allows a fast and precise description of the AMS tensor. We removed from analysis low susceptibility, carbonate-rich samples, that show a higher variety of magnetic minerals. All sites present homogenous results at the site scale, but with significant differences with respect to strain. P and T parameters are very sensitive to strain as illite is the dominant carrier. In addition, the ellipse of confidence of the minimum AMS axis (K3) provides a sensitive proxy to characterize the competition between bedding and cleavage.</p><p>The comparison between the different sections allows to map the areas of damage linked to the propagation of faults associated with the folds. 5 stages of development of the magnetic fabric allows the detection of damage gradients. The mapping has allowed the identification of hidden faults.    </p><p>This new approach is very promising, and allows much more detailed samplings in difficult areas, providing more robust statistical description of scalar AMS data. This methodology could be useful for the study of outcrops that are difficult to access, and more interestingly, from borehole cuttings.</p>

scholarly journals A search for transiting planets in the β Pictoris system

2018 ◽  
Vol 615 ◽  
pp. A145 ◽  
Author(s):  
M. Mol Lous ◽  
E. Weenk ◽  
M. A. Kenworthy ◽  
K. Zwintz ◽  
R. Kuschnig
Keyword(s):  
Signal To Noise Ratio ◽  
Large Fraction ◽  
Young Star ◽  
High Signal ◽  
Data Set ◽  
Transiting Planets ◽  
Using Data ◽  
Exoplanet Systems ◽  
Transit Signals

Context. Transiting exoplanets provide an opportunity for the characterization of their atmospheres, and finding the brightest star in the sky with a transiting planet enables high signal-to-noise ratio observations. The Kepler satellite has detected over 365 multiple transiting exoplanet systems, a large fraction of which have nearly coplanar orbits. If one planet is seen to transit the star, then it is likely that other planets in the system will transit the star too. The bright (V = 3.86) star β Pictoris is a nearby young star with a debris disk and gas giant exoplanet, β Pictoris b, in a multi-decade orbit around it. Both the planet’s orbit and disk are almost edge-on to our line of sight. Aims. We carry out a search for any transiting planets in the β Pictoris system with orbits of less than 30 days that are coplanar with the planet β Pictoris b. Methods. We search for a planetary transit using data from the BRITE-Constellation nanosatellite BRITE-Heweliusz, analyzing the photometry using the Box-Fitting Least Squares Algorithm (BLS). The sensitivity of the method is verified by injection of artificial planetary transit signals using the Bad-Ass Transit Model cAlculatioN (BATMAN) code. Results. No planet was found in the BRITE-Constellation data set. We rule out planets larger than 0.6 RJ for periods of less than 5 days, larger than 0.75 RJ for periods of less than 10 days, and larger than 1.05 RJ for periods of less than 20 days.

scholarly journals Characterization of Road Condition with Data Mining Based on Measured Kinematic Vehicle Parameters

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Johannes Masino ◽  
Jakob Thumm ◽  
Guillaume Levasseur ◽  
Michael Frey ◽  
Frank Gauterin ◽  
...  
Keyword(s):  
Data Mining ◽  
Support Vector ◽  
Matlab Toolbox ◽  
Data Set ◽  
The Road ◽  
Acceleration Sensors ◽  
Road Surfaces ◽  
Road Condition ◽  
Sensor Signals

This work aims at classifying the road condition with data mining methods using simple acceleration sensors and gyroscopes installed in vehicles. Two classifiers are developed with a support vector machine (SVM) to distinguish between different types of road surfaces, such as asphalt and concrete, and obstacles, such as potholes or railway crossings. From the sensor signals, frequency-based features are extracted, evaluated automatically with MANOVA. The selected features and their meaning to predict the classes are discussed. The best features are used for designing the classifiers. Finally, the methods, which are developed and applied in this work, are implemented in a Matlab toolbox with a graphical user interface. The toolbox visualizes the classification results on maps, thus enabling manual verification of the results. The accuracy of the cross-validation of classifying obstacles yields 81.0% on average and of classifying road material 96.1% on average. The results are discussed on a comprehensive exemplary data set.

scholarly journals Characterizing Malignant Melanoma Clinically Resembling Seborrheic Keratosis Using Deep Knowledge Transfer

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6300
Author(s):  
Panagiota Spyridonos ◽  
George Gaitanis ◽  
Aristidis Likas ◽  
Ioannis Bassukas
Keyword(s):  
Public Access ◽  
Classification Model ◽  
Bayesian Optimization ◽  
Support Vector ◽  
Seborrheic Keratosis ◽  
Convolutional Network ◽  
Data Set ◽  
Computer Based ◽  
Hyperparameter Selection

Malignant melanomas resembling seborrheic keratosis (SK-like MMs) are atypical, challenging to diagnose melanoma cases that carry the risk of delayed diagnosis and inadequate treatment. On the other hand, SK may mimic melanoma, producing a ‘false positive’ with unnecessary lesion excisions. The present study proposes a computer-based approach using dermoscopy images for the characterization of SΚ-like MMs. Dermoscopic images were retrieved from the International Skin Imaging Collaboration archive. Exploiting image embeddings from pretrained convolutional network VGG16, we trained a support vector machine (SVM) classification model on a data set of 667 images. SVM optimal hyperparameter selection was carried out using the Bayesian optimization method. The classifier was tested on an independent data set of 311 images with atypical appearance: MMs had an absence of pigmented network and had an existence of milia-like cysts. SK lacked milia-like cysts and had a pigmented network. Atypical MMs were characterized with a sensitivity and specificity of 78.6% and 84.5%, respectively. The advent of deep learning in image recognition has attracted the interest of computer science towards improved skin lesion diagnosis. Open-source, public access archives of skin images empower further the implementation and validation of computer-based systems that might contribute significantly to complex clinical diagnostic problems such as the characterization of SK-like MMs.

Using orthorhombic depth imaging to image fractures in tight reservoirs of the RDG Field, Barmer Basin, India

2019 ◽  
Vol 38 (4) ◽  
pp. 268-273
Author(s):  
Maheswara Phani ◽  
Sushobhan Dutta ◽  
Kondal Reddy ◽  
Sreedurga Somasundaram
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
Substantial Improvement ◽  
Natural Fractures ◽  
Data Set ◽  
Depth Migration ◽  
Velocity Modeling ◽  
Barmer Basin ◽  
Induced Fractures

Raageshwari Deep Gas (RDG) Field is situated in the southern part of the Barmer Basin in Rajasthan, India, at a depth of 3000 m. With both clastic and volcanic lithologies, the main reservoirs are tight, and hydraulic fracturing is required to enhance productivity, especially to improve permeability through interaction of induced fractures with natural fractures. Therefore, optimal development of the RDG Field reservoirs requires characterization of faults and natural fractures. To address this challenge, a wide-azimuth 3D seismic data set over the RDG Field was processed to sharply define faults and capture anisotropy related to open natural fractures. Anisotropy was indicated by the characteristic sinusoidal nature of gather reflection events processed using conventional tilted transverse imaging (TTI); accordingly, we used orthorhombic imaging to correct for these, to quantify fracture-related anisotropy, and to yield a more correct subsurface image. During prestack depth migration (PSDM) processing of the RDG data, TTI and orthorhombic velocity modeling was done with azimuthal sectoring of reflection arrivals. The resultant PSDM data using this velocity model show substantial improvement in image quality and vertical resolution at the reservoir level compared to vintage seismic data. The improved data quality enabled analysis of specialized seismic attributes like curvature and thinned fault likelihood for more reliable characterization of faults and fractures. These attributes delineate the location and distribution of probable fracture networks within the volcanic reservoirs. Interpreted subtle faults, associated with fracture zones, were validated with microseismic, production, and image log data.

Chemometric Evaluation of Ultraviolet–Visible (UV–Vis) Spectra for Characterization of Silver Nanowire Diameter and Yield

2019 ◽  
Vol 74 (2) ◽  
pp. 204-209
Author(s):  
Clifford S. Todd ◽  
Xiaoyun Chen
Keyword(s):  
Main Tool ◽  
Wire Diameter ◽  
Silver Nanowire ◽  
Diameter Distribution ◽  
Distribution Data ◽  
Data Set ◽  
Nanowire Diameter ◽  
Particle Yield ◽  
Vis Spectroscopy

The main tool used for routine screening of silver nanowire diameter and wire-to-particle yield is ultraviolet–visible (UV–Vis) spectroscopy. The normalized absorbance near 500 nm is generally taken to correlate with wire yield (lower absorbance means fewer particles and higher wire yield). The location of the UV–Vis peak near 375 nm is generally believed to correlate with wire diameter. These qualitative assessments are of unknown uncertainty. Improved microscopy-based analysis of wire diameter distribution and wire yield had recently been developed and were used to characterize synthesis products in parallel with UV–Vis data collection. Here we present results of leveraging this quantitative wire yield and diameter distribution data to quantitatively calibrate the UV–Vis methods for characterizing wire diameter and yield. Chemometric analysis was also applied to this UV–Vis data set and resulted in statistically significant models that can predict average wire diameter and wire/particle yield slightly better than the univariate method.

scholarly journals Seasonal changes in gravity wave activity measured by lidars at mid-latitudes

2008 ◽  
Vol 8 (22) ◽  
pp. 6775-6787 ◽  
Author(s):  
M. Rauthe ◽  
M. Gerding ◽  
F.-J. Lübken
Keyword(s):  
Gravity Wave ◽  
Gravity Waves ◽  
Low Frequency ◽  
Weather Conditions ◽  
Wave Activity ◽  
Data Set ◽  
Atmospheric Physics ◽  
Adverse Weather Conditions ◽  
Comprehensive Information ◽  
Adverse Weather

Abstract. More than 230 nights of temperature measurements between 1 and 105 km have been performed at the Leibniz-Institute of Atmospheric Physics in Kühlungsborn with a combination of two different lidars, i.e. a Rayleigh-Mie-Raman lidar and a potassium lidar. About 1700 h of measurements have been collected between 2002 and 2006. Apart from some gaps due to the adverse weather conditions the measurements are well distributed throughout the year. Comprehensive information about the activity of medium- and low-frequency gravity waves was extracted from this data set. The dominating vertical wavelengths found are between 10 and 20 km and do not show any seasonal variation. In contrast the temperature fluctuations due to gravity waves experience a clear annual cycle with a maximum in winter. The most significant differences exist around 60 km where the fluctuations in winter are more than two times larger than they are in summer. Only small seasonal differences are observed above 90 km and below 35 km. Generally, the fluctuations grow from about 0.5 K up to 8 K between 20 and 100 km. Damping of waves is observed at nearly all altitudes and in all seasons. The planetary wave activity shows a similar structure in altitude and season as the gravity wave activity which indicates that similar mechanisms influencing different scales. Combining the monthly mean temperatures and the fluctuations we show that the transition between winter and summer season and vice versa seems to start in the mesopause region and to penetrate downward.

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