Topographic Images Research Articles

Study of Structural Defects in Sapphire Ribbons using X-Ray Topography and Coherent Imaging in Synchrotron Radiation

Study of Structural Defects in Sapphire Ribbons using X-Ray Topography and Coherent Imaging in Synchrotron Radiation

Aeromagnetic surveys for the location of undocumented orphaned wells

The U.S. Department of Energy's National Energy Technology Laboratory (NETL) conducted research to field test the ability of airborne methods to locate existing wells quickly and accurately with minimal landowner impact. Helicopter surveys with two boom-mounted atomic magnetometers were used to locate wells at two oil fields in Wyoming and at four large oil and gas producing areas in Pennsylvania. At the two Wyoming oil fields, the helicopter magnetic survey identified 91%–96% of the wells located by exhaustive ground search. A different validation was used for the thickly forested Pennsylvania flight areas where well picks from the helicopter magnetic survey were used to direct the ground search to potential well locations for verification. The number and location of verified well locations were then compared to well records in the state database. For the oldest wells (circa 1860–1880), the number of wells in the state database exceeded the number of wells identified by the helicopter magnetic survey because many early wells had wood casing (nonmagnetic). For wells drilled between 1880 and 1950, the helicopter surveys found two to five undocumented wells for each well in the state database. The best results were achieved at a gas storage field where wells were drilled after 1950. There, 98% of the wells located by the helicopter magnetic survey were documented. In 2017, NETL used an atomic magnetometer on a small uncrewed aircraft system (sUAS) to refly an area previously flown with a crewed helicopter. The magnetic map from the sUAS survey was equal to that obtained with a crewed helicopter. High-resolution topographic images developed from sUAS LiDAR surveys were found to be helpful in locating very early wells with wood casing. When the wood casing decayed, soil subsided into the well void, leaving a circular depression that is easily recognized in high-resolution LiDAR imagery.

LAND ARRANGEMENT PLANNING ON RECLAMATION LAND OF PT. MEGA MULTI ENERGY, NORTH BARITO, CENTRAL KALIMANTAN

PT. Mega Multi Energi (PT MME) operates in the coal mining industry which causes land changes, so planning for land reclamation is carried out. This research aims to determine the slope, landform management, and reclamation planning. Results of slope stability analysis to design single slope and overall slope dimensions. A detailed topographic survey has been carried out by PT. MME uses LiDAR mapping with a total work area of ± 5000 Ha. This technology uses the latest advanced LiDAR or Light Detection and Ranging sensor which is designed for activities in the form of topographic surveys and 3-dimensional imaging, operated by plotting millions of laser beam points on objects at one time and then modeling them in the form of a 3-dimensional point cloud. The rocks that make up the slopes in the mining area of PT. MME is dominated by claystone and sandstone. An individual slope design with a height of 10 meters and a slope of 60° shows a safety factor (FK) value of > 1.5. Landform regulation is intended to reduce the speed of runoff, erosion sedimentation, and landslides, the shape and design of the slope must be gentle. Implementation of the reclamation plan starts with land preparation, erosion and sedimentation control, topsoil management, and revegetation.

Unmanned Aerial Vehicle Derived DEM Using in Accurate Geometric Analysis for Water Harvesting in Small-Scale Depressions

Due to significant progress in remote sensing over the past few decades, topographic data is now widely available on a global scale. Recent advancements in unmanned aerial vehicle technology have made it possible to get high resolution topographic images on a scale of less than a meter. Making it perfect for small sites survey. Conducted an assessment of the unmanned aerial vehicle ability to estimate various geometric elements by generating a digital elevation model and subsequently analyzing the depression geometrically. The study area in focus was in AL-Sherqat, which consists of a small valley. Upon analysis of the generated digital elevation model, we were able to determine the valley's maximum capacity volume to be 18365.91 m3 at a water level of 186.8 m above sea level. The analysis also yielded other important elements, such as positive volume, negative and positive surface areas, negative and positive planar areas, residual capacity, average depression depth, and average island thickness. The interrelationships among these geometric elements were plotted for further analysis. Based on the results, we conclude that the unmanned aerial vehicle structure from the motion (SFM) algorithm and the produced digital elevation model are suitable for surveying small topographic depressions. This technique could prove valuable for water harvesting purposes.

Predicting the placement of biomolecular structures on AFM substrates based on electrostatic interactions

Atomic force microscopy (AFM) and high-speed AFM allow direct observation of biomolecular structures and their functional dynamics. Based on scanning the molecular surface of a sample deposited on a supporting substrate by a probing tip, topographic images of its dynamic shape are obtained. Critical to successful AFM observations is a balance between immobilization of the sample while avoiding too strong perturbations of its functional conformational dynamics. Since the sample placement on the supporting substrate cannot be directly controlled in experiments, the relative orientation is a priori unknown, and, due to limitations in the spatial resolution of images, difficult to infer from a posteriori analysis, thus hampering the interpretation of measurements. We present a method to predict the macromolecular placement of samples based on electrostatic interactions with the AFM substrate and demonstrate applications to HS-AFM observations of the Cas9 endonuclease, an aptamer-protein complex, the Monalysin protein, and the ClpB molecular chaperone. The model also allows predictions of imaging stability taking into account buffer conditions. We implemented the developed method within the freely available BioAFMviewer software package. Predictions based on available structural data can therefore be made even prior to an actual experiment, and the method can be applied for post-experimental analysis of AFM imaging data.

Cardiac interoception in Anorexia Nervosa: A resting-state heartbeat-evoked potential study.

A deficit in interoception - the ability to perceive, interpret and integrate afferent signals about the physiological state of the body - has been shown in Anorexia Nervosa (AN), and linked to altered hunger sensations, body dysmorphia, and abnormal emotional awareness. The present high-density electroencephalography (hdEEG) study aims to assess cardiac interoception in AN and to investigate its neural correlates, using an objective neurophysiological measure. Heartbeat-evoked potentials (HEPs) were computed from 5min of resting-state EEG and electrocardiogram (ECG) data and compared between individuals with AN (N=22) and healthy controls (HC) (N=19) with waveform, topographic, and source imaging analyses. Differences in the cortical representation of heartbeats were present between AN and HC at a time window of 332-348ms after the ECG R-peak. Source imaging analyses revealed a right-sided hypoactivation in AN of brain regions linked to interoceptive processing, such as the anterior cingulate and orbitofrontal areas. To the best of our knowledge, this is the first study using hdEEG to localise the underlying sources of HEPs in AN. Results point to altered interoceptive processing during resting-state in AN. As our participants had a short duration of illness, this might not be the consequence of prolonged starvation. Interventions targeted at interoception could provide an additional tool to facilitate recovery.

Computer-aided diagnosis of keratoconus through VAE-augmented images using deep learning

Detecting clinical keratoconus (KCN) poses a challenging and time-consuming task. During the diagnostic process, ophthalmologists are required to review demographic and clinical ophthalmic examinations in order to make an accurate diagnosis. This study aims to develop and evaluate the accuracy of deep convolutional neural network (CNN) models for the detection of keratoconus (KCN) using corneal topographic maps. We retrospectively collected 1758 corneal images (978 normal and 780 keratoconus) from 1010 subjects of the KCN group with clinically evident keratoconus and the normal group with regular astigmatism. To expand the dataset, we developed a model using Variational Auto Encoder (VAE) to generate and augment images, resulting in a dataset of 4000 samples. Four deep learning models were used to extract and identify deep corneal features of original and synthesized images. We demonstrated that the utilization of synthesized images during training process increased classification performance. The overall average accuracy of the deep learning models ranged from 99% for VGG16 to 95% for EfficientNet-B0. All CNN models exhibited sensitivity and specificity above 0.94, with the VGG16 model achieving an AUC of 0.99. The customized CNN model achieved satisfactory results with an accuracy and AUC of 0.97 at a much faster processing speed compared to other models. In conclusion, the DL models showed high accuracy in screening for keratoconus based on corneal topography images. This is a development toward the potential clinical implementation of a more enhanced computer-aided diagnosis (CAD) system for KCN detection, which would aid ophthalmologists in validating the clinical decision and carrying out prompt and precise KCN treatment.

Optimization of Functional Toothpaste Formulation Containing Nano-Hydroxyapatite and Birch Extract for Daily Oral Care.

This research work aims to develop functional toothpastes with combined enamel remineralization and antibacterial effects using nano-hydroxyapatites (nHAPs) and birch extract. Eleven toothpastes (notated as P1-P11) were designed featuring different concentrations of birch extract and a constant concentration of pure nHAPs or substituted nHAPs (HAP-5%Zn, HAP-0.23%Mg-3.9%Zn-2%Si-10%Sr, and HAP-2.5%Mg-2.9%Si-1.34%Zn). In vitro assessments involved treating artificially demineralized enamel slices and analyzing surface repair and remineralization using Atomic Force Microscopy (AFM). The Agar Disk Diffusion method was used to measure antibacterial activity against Enterococcus faecalis, Escherichia coli, Porphyromonas gingivalis, Streptococcus mutans, and Staphylococcus aureus. Topographic images of enamel structure and surface roughness, as well as the ability of nHAP nanoparticles to form self-assembled layers, revealed excellent restorative properties of the tested toothpastes, with enamel nanostructure normalization occurring as soon as 10 days after treatment. The outcomes highlighted enamel morphology improvements due to the toothpaste treatment also having various efficacious antibacterial effects. Promising results were obtained using P5 toothpaste, containing HAP-5%Zn (3.4%) and birch extract (1.3%), indicating notable remineralization and good antibacterial properties. This study represents a significant advancement in oral care by introducing toothpaste formulations that simultaneously promote enamel health through effective remineralization and bacterial inhibition.

Scanning probe microscopy in the age of machine learning

Scanning probe microscopy (SPM) has revolutionized our ability to explore the nanoscale world, enabling the imaging, manipulation, and characterization of materials at the atomic and molecular level. However, conventional SPM techniques suffer from limitations, such as slow data acquisition, low signal-to-noise ratio, and complex data analysis. In recent years, the field of machine learning (ML) has emerged as a powerful tool for analyzing complex datasets and extracting meaningful patterns and features in multiple fields. The combination of ML with SPM techniques has the potential to overcome many of the limitations of conventional SPM methods and unlock new opportunities for nanoscale research. In this review article, we will provide an overview of the recent developments in ML-based SPM, including its applications in topography imaging, surface characterization, and secondary imaging modes, such as electrical, spectroscopic, and mechanical datasets. We will also discuss the challenges and opportunities of integrating ML with SPM techniques and highlight the potential impact of this interdisciplinary field on various fields of science and engineering.

Green-synthetized β-amino-α-carbethoxy ethyl acrylates as corrosion inhibitors for mild steel in acid media: Experimental performance evaluation and atomic/molecular-level modeling

Two β-amino acrylate derivatives were synthesized through a solvent- and heating-free mechanochemical procedure. Those substances were tested as corrosion inhibitors for mild steel in acidic environment (1 mol/L HCl). Weight Loss Study demonstrated that both molecules mitigate corrosion with 85 and 90 % efficiencies. Electrochemical experiments proved that the corrosion mechanism is charge transfer and that the presence of EOAB and DBMM at any tested concentration in the electrolyte significantly increases the polarization resistance and lowers the corrosion density current. This phenomenon is due to the adsorption of the molecules on the mild steel surface, leading to the formation of a protection film that prevents the corrosion reaction, as suggested by Atomic Force Microscopy topographic images. The self-consistent-charge density-functional tight-binding method (SCC-DFTB) revealed that their adsorption strength on the iron surface followed well the corrosion inhibition performance. Both inhibitor molecules formed covalent bonds with iron atoms as evidenced from stable adsorption geometries and projected density of states. Quantum chemical parameters seem to fail in predicting the experimental performance. Outcomes from the present study confirmed the fact that an additional functional group would lead to an increased inhibition performance is not a granted correlation.

Extraction of landslide morphology based on Topographic Profile along the Direction of Slope Movement using UAV images

The landslide morphology is quickly and accurately extracted from Unmanned Air Vehicle (UAV) images. It is of great significance for emergency rescue and quantitative evaluation of landslide disasters. However, due to the complexity of landslide morphology, choosing the reasonable extraction thresholds is a challenging issue. A threshold selection method of Topographic Profile along the Direction of Slope Movement (TP-DSM) was proposed. Firstly, a hierarchical extraction rule sets for landslide morphology was constructed by integrating multi-feature information such as spectral, texture, geometry, topography and space of UAV images. Second, TP-DSM was proposed to select the optimal elevation thresholds for classifying different landslide morphology. Finally, the thresholds were introduced into the rule sets to achieve effective extraction of landslide morphology. This study uses Digital Orthophoto Map (DOM) and Digital Elevation Model (DEM) generated by UAV images as data sources, and the landslide in Luquan County, Yunnan Province, China as the Study area, the results show that the overall accuracy (OA) of landslide morphology extraction was 89.58%, and the Kappa coefficient was 0.88, which is effective and more consistent with the reality. The proposed method can also be applied to other potential locations.

Miniaturized high-resolution dual 2D MEMS mirror scanning confocal Raman microscopy for topographic and Raman mapping

A novel dual 2D MEMS mirror scanning confocal Raman microscopy (D-2D-MEMS-CRM) method is proposed to realize the miniaturized design of the confocal Raman microscopy. This method uses two 2D MEMS mirrors to realize beam telecentric scanning, which eliminates the relay system consisting of a scan lens and tube lens, significantly shortens the optical length of the system, and improves the detection efficiency of Raman signal. Moreover, this method uses reflected light to construct a real-time focus tracking system, which improves the spatial resolution of the confocal Raman detection system. Based on this method, a miniaturized D-2D-MEMS-CRM system was established, which had an axial focusing capability of 50 nm using an objective lens with NA of 0.6, and the lateral resolution of 500 nm for both topographic and Raman mapping. In addition, the system achieved simultaneous topographic imaging and Raman mapping of carbonaceous chondrite, demonstrating its effectiveness in extraterrestrial sample detection.

New design, construction and evaluation of a stable scanning tunneling microscope with large-area searching and accurate positioning ability

Investigating micron-sized sample with high spatial resolution and energy resolution greatly promotes the development of materials science. Here we present a novel scanning tunneling microscope (STM) that offers a smaller tip-sample mechanical loop, increased stability, a novel searching method, accurate positioning ability and compatibility with low temperature and high magnetic fields. The piezoelectric tube of the motor not only provides the driving force, but also allows adjustment of the sample position by applying opposite voltages on its external electrodes. The piezoelectric tube based X-Y motor is omitted from the mechanical loop to increase the stability of the STM, as evidenced by low rates of 23.5 pm/min and 36.2 pm/min in the X-Y plane and Z direction. The STM’s controllable searching ability is convincingly demonstrated through continuous large-area topographical images acquired on a graphite surface, and its positioning precision is exemplified by acquiring an atomic image of a 20 μm isolated triangular graphite flake. The new STM is also capable of working at 1.8 K low temperature and in a 12 T cryogen-free superconducting magnet, as demonstrated by the atomic image of charge density wave on TaS2 surface, dI/dV spectrums of NbSe2, and atomically resolved images in sweeping the magnet fields from 0 T to 11.5 T. These unique advantages offer new opportunities for exploring micron-sized materials and devices.

Interaction of βL- and γ-Crystallin with Phospholipid Membrane Using Atomic Force Microscopy.

Highly concentrated lens proteins, mostly β- and γ-crystallin, are responsible for maintaining the structure and refractivity of the eye lens. However, with aging and cataract formation, β- and γ-crystallin are associated with the lens membrane or other lens proteins forming high-molecular-weight proteins, which further associate with the lens membrane, leading to light scattering and cataract development. The mechanism by which β- and γ-crystallin are associated with the lens membrane is unknown. This work aims to study the interaction of β- and γ-crystallin with the phospholipid membrane with and without cholesterol (Chol) with the overall goal of understanding the role of phospholipid and Chol in β- and γ-crystallin association with the membrane. Small unilamellar vesicles made of Chol/1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (Chol/POPC) membranes with varying Chol content were prepared using the rapid solvent exchange method followed by probe tip sonication and then dispensed on freshly cleaved mica disk to prepare a supported lipid membrane. The βL- and γ-crystallin from the cortex of the bovine lens was used to investigate the time-dependent association of βL- and γ-crystallin with the membrane by obtaining the topographical images using atomic force microscopy. Our study showed that βL-crystallin formed semi-transmembrane defects, whereas γ-crystallin formed transmembrane defects on the phospholipid membrane. The size of semi-transmembrane defects increases significantly with incubation time when βL-crystallin interacts with the membrane. In contrast, no significant increase in transmembrane defect size was observed in the case of γ-crystallin. Our result shows that Chol inhibits the formation of membrane defects when βL- and γ-crystallin interact with the Chol/POPC membrane, where the degree of inhibition depends upon the amount of Chol content in the membrane. At a Chol/POPC mixing ratio of 0.3, membrane defects were observed when both βL- and γ-crystallin interacted with the membrane. However, at a Chol/POPC mixing ratio of 1, no association of γ-crystallin with the membrane was observed, which resulted in a defect-free membrane, and the severity of the membrane defect was decreased when βL-crystallin interacted with the membrane. The semi-transmembrane or transmembrane defects formed by the interaction of βL- and γ-crystallin on phospholipid membrane might be responsible for light scattering and cataract formation. However, Chol suppressed the formation of such defects in the membrane, likely maintaining lens membrane homeostasis and protecting against cataract formation.

Multipoint surface electromyography measurement using bull’s-eye electrodes for wide-area topographic analysis

BackgroundSurface electromyography (sEMG) is primarily used to analyze individual and neighboring muscle activity. However, using a broader approach can enable simultaneous measurement of multiple muscles, which is essential for understanding muscular coordination. Using the “bull’s-eye electrode,” which allows bipolar derivation without directional dependence, enables wide-area multipoint sEMG measurements. This study aims to establish a multipoint measurement system and demonstrate its effectiveness and evaluates forearm fatigue and created topographic maps during a grasping task.MethodsNine healthy adults with no recent arm injuries or illnesses participated in this study. They performed grasping tasks using their dominant hand, while bull’s-eye electrodes recorded their muscle activity. To validate the effectiveness of the system, we calculated the root mean squares of muscle activity and entropy, an indicator of muscle activity distribution, and compared them over time.ResultsThe entropy analysis demonstrated a significant time-course effect with increased entropy over time, suggesting increased forearm muscle uniformity, which is possibly indicative of fatigue. Topographic maps visually displayed muscle activity, revealing notable intersubject variations.DiscussionBull’s-eye electrodes facilitated the capture of nine homogeneous muscle activity points, enabling the creation of topographic images. The entropy increased progressively, suggesting an adaptive muscle coordination response to fatigue. Despite some limitations, such as inadequate measurement of the forearm muscles’ belly, the system is an unconventional measurement method.ConclusionThis study established a robust system for wide-area multipoint sEMG measurements using a bull’s-eye electrode setup. This system effectively evaluates muscle fatigue and provides a comprehensive topographic view of muscle activity. These results mark a significant step towards developing a future multichannel sEMG system with enhanced measurement points and improved wearability.Trial registrationThis study was approved by the Ethics Committee of Chiba University Graduate School of Engineering (acceptance number: R4-12, Acceptance date: November 04, 2022).

94 GHz Radar Backscatter Characteristics of Alpine Glacier Ice

AbstractMeasuring the radar backscatter characteristics of glacier ice at different frequencies and incidence angles is fundamental to predicting the glacier mapping performance of a sensor. However, such measurements at 94 GHz do not exist. To address this knowledge gap, we collected 94 GHz radar backscatter data from the surface of Rhônegletscher in Switzerland using the All‐Weather Volcano Topography Imaging Sensor (AVTIS2) real‐aperture Frequency Modulated Continuous Wave radar. We determine the mean normalized radar cross section to be −9.9 dB. The distribution closely follows a log‐normal distribution with a high goodness of fit (R2 = 0.99) which suggests that radar backscatter is diffuse and driven by surface roughness. Further, we quantified the uncertainty of AVTIS2 3D point clouds to be 1.30–3.72 m, which is smaller than other ground‐based glacier surface mapping radars. These results demonstrate that glacier surfaces are an efficient scattering target at 94 GHz, hence demonstrating the suitability of millimeter‐wave radar for glacier monitoring.

The on-chip scanning probe with dual niobium nitride nanoscale superconducting quantum interference devices for magnetic imaging at the high temperature

The scanning superconducting quantum interference device (SQUID) microscope is a powerful tool for investigating the microscale magnetic properties of quantum materials. However, the low operating temperature of SQUIDs limits the application of the microscope. In this work, we developed an on-chip probe with dual niobium nitride (NbN) nano-SQUIDs for scanning SQUID microscope. The working temperature of the NbN nano-SQUID on-chip probe was up to 8 K, and it enabled the magnetic imaging of samples at the temperature up to 128 K. We used a gradiometric readout scheme for dual nano-SQUIDs in one probe to reduce the influence of the background magnetic field. Furthermore, we demonstrated the capabilities of both topographic and current imaging by the on-chip probe with spatial resolutions of 1 μm and 2 μm, respectively. The advantage of the probe at the high temperature was also demonstrated by the investigation of the superconducting vortices distribution in the yttrium-barium-copper-oxide film.

Ag Nanocluster Production through DC Magnetron Sputtering and Inert Gas Condensation: A Study of Structural, Kelvin Probe Force Microscopy, and Optical Properties.

Silver nanoclusters are valuable for a variety of applications. A combination of direct current (DC) magnetron sputtering and inert gas condensation methods, employed within an ultra-high vacuum (UHV) system, was used to generate Ag nanoclusters with an average size of 4 nm. Various analytical techniques, including Scanning Probe Microscopy (SPM), X-ray Diffraction (XRD), Kelvin Probe Force Microscopy (KPFM), UV-visible absorption, and Photoluminescence, were employed to characterize the produced Ag nanoclusters. AFM topographic imaging revealed spherical nanoparticles with sizes ranging from 3 to 6 nm, corroborating data from a quadrupole mass filter (QMF). The XRD analysis verified the simple cubic structure of the Ag nanoclusters. The surface potential was assessed using KPFM, from which the work function was calculated with a reference highly ordered pyrolytic graphite (HOPG). The UV-visible absorption spectra displayed peaks within the 350-750 nm wavelength range, with a strong absorption feature at 475 nm. Additionally, lower excitation wavelengths resulted in a sharp peak emission at 370 nm, which became weaker and broader when higher excitation wavelengths were used.

Overcoming Challenges and Limitations Regarding the Atomic Force Microscopy Imaging and Mechanical Characterization of Nanofibers

Atomic force microscopy (AFM) is a powerful tool that enables imaging and nanomechanical properties characterization of biological materials. Nanofibers are the structural units of many biological systems and their role in the development of advanced biomaterials is crucial. AFM methods have proven to be effective towards the characterization of fibers with respect to biological and bioengineering applications at the nanoscale. However, both the topographical and mechanical properties’ nanocharacterizations of single fibers using AFM are challenging procedures. In particular, regarding imaging procedures, significant artifacts may arise from tip convolution effects. The geometrical characteristics of the AFM tip and the nanofibers, and the fact that they have similar magnitudes, may lead to significant errors regarding the topographical imaging. In addition, the determination of the mechanical properties of nanofibers is also challenging due to their small dimensions and heterogeneity (i.e., the elastic half-space assumption is not valid in most cases). This review elucidates the origins of errors in characterizing individual nanofibers, while also providing strategies to address limitations in experimental procedures and data processing.

Study of the paleochannel in the southeastern part of Pyongyang by using topographic and satellite image analysis: A possibility for successful survey of paleolithic site

AbstractThere are Quaternary paleochannels in the left bank of the lower reaches of the Taedong River in the southeastern side of Pyongyang. We aimed to determine the possibility to find Paleolithic sites by locating terraces and paleochannels using digital elevation models (DEM) and Landsat ETM+. The study on paleochannels focused on survey of terrace of the 80–100 m high, associated with the Paleolithic site, performing topography (elevation, slope and aspect) analysis with DEM data and FCC (False Color Component), BR (Band Ratio), PCA (Principal Component Analysis), ISODATA, and SAM with Landsat ETM+ image. The results show that the analysis method using DEM and ETM+ is effective to find Paleolithic sites through surveys of terrace and paleochannel and analysis of facies.