High-resolution Imaging Research Articles

Building Height Extraction Based on Satellite GF-7 High-Resolution Stereo Image

Abstract. High-resolution remote sensing images can distinguish objects of smaller size, so as to more clearly express the texture features and structural information of objects, and provide a data source for the development of large-scale mapping, high-precision stereo measurement and other fields. The purpose of this paper is to complete the height estimation of the buildings by analyzing the stereoscopic observation formed by the front and rear view images of the Gaofen-7 line array CCD. After determining the roof profile of the building on the rear-view image, assuming a series of object elevations of the building, that is, searching for elevations with a certain step distance within a certain elevation search range, adopt the object-based image matching VLL algorithm, Through the RFM imaging model of the Gaofen-7 sensor, the rear-view contour is projected to the front-view image, and then the PSNR is selected as the similarity measure of the window, and the similarity of the image block area corresponding to the front- and rear-view contour is calculated. Corresponds to the hypothetical object elevation as the estimated height of the building. Under the technical route of this paper, the height of buildings on high-resolution images can be estimated to a level within 3 meters of accuracy.

High-resolution vessel wall imaging for quantitatively and qualitatively evaluating in-stent stenosis of intracranial aneurysms.

It is critical to accurately and noninvasively evaluate the stented parent artery of intracranial aneurysms (IAs) with endovascular treatment. To investigate high-resolution vessel wall imaging (HR-VWI) for quantitative and qualitative evaluation of in-stent stenosis (ISS) in IAs treated with stent placement (SP). Fifty-five patients (58 aneurysms) underwent HR-VWI, contrast-enhanced (CE)-HR-VWI, CE-MR angiography (MRA), time-of-flight (TOF)-MRA, and digital subtraction angiography (DSA) six months after SP, and the reliability of quantitative stent lumen measurements was evaluated by intraclass correlation coefficient (ICC) analysis. Agreement and correlation of quantitative evaluation were estimated by comparing the four MR imaging modalities with DSA. The diagnostic performance for >0%, ≥25%, and ≥50% of ISS degrees and overall diagnostic accuracy for the ISS degrees of the four MR imaging modalities were calculated to qualitative evaluation. The reliability of CE-HR-VWI and HR-VWI for ISS quantitative measurements was excellent (ICC 0.955-0.989). The agreement and correlation of CE-HR-VWI, HR-VWI versus DSA for ISS quantitative measurements were better than those of CE-MRA and TOF-MRA (p < 0.05). The diagnostic performance for distinguishing the degree of ISS >0%, ≥25%, and ≥50% by CE-HR-VWI and HR-VWI was superior to CE-MRA and TOF-MRA, and their overall diagnostic accuracy was 96.55 and 94.83%, respectively. HR-VWI and CE-HR-VWI were not statistically significant in the quantitative and qualitative evaluation of ISS performance (p > 0.05). HR-VWI and CE-HR-VWI have similar performance and value in the quantitative and qualitative evaluation of ISS, and HR-VWI without contrast media could be used as an ideal long-term follow-up approach after SP treatment for IAs.

FeCuNbSiB thin films with sub-Oersted coercivity

We investigated the microstructural and magnetic properties of nanocrystalline FeCuNbSiB thin films produced through magnetron sputtering followed by heat treatment. Our research focused on film thicknesses (80 nm and 160 nm) and heat treatment temperatures (490 °C–520 °C) that resulted in samples characterized by low coercivity and high effective magnetization. Conducting a comprehensive microstructural examination, we employed X-ray diffraction and transmission electron microscopy techniques, including selected area electron diffraction, high-resolution imaging and Fourier transform analysis. Magnetic properties were investigated using an alternating gradient field magnetometer and broadband ferromagnetic resonance. Structural analysis revealed, for all our heat-treated films, a well-defined microstructure characterized by nanograins, with a Fe3Si ferromagnetic phase, embedded within an amorphous matrix. Our films exhibit sub-Oe coercivity, reaching as low as 0.51 Oe, along with an increase in effective magnetization from 1170 emu/cm3 for the amorphous phase to a maximum of 1260 emu/cm3 in the nanocrystalline phase.

Full-Stokes polarization detection enabled by a terahertz all-dielectric metasurface

Metasurface has the ability to flexibly modulate the wavefront and detect the polarization states, thus receiving widespread research attention. The combination of polarization multiplexing techniques and focused beams with polarization information provides a new approach to compact polarization detection behavior. Here, an all-dielectric metasurface based on polarization multiplexing encoding technique is demonstrated and assigns the independent phase distributions to x- and y-polarized channels to separate different polarized components. Combining Stokes parameters and visualized polarization ellipses, realizing one-to-one mapping of the incident polarization states with far-field images. We obtain the Poincaré sphere and visualized polarization ellipses based on Stokes parameters to verify the polarization detection ability of the designed metasurface. The proposed scheme is expected to provide potential applications in fields such as full-Stokes polarization detection, high-resolution imaging, and terahertz communication.

Evaluating nickel removal efficacy of Filtralite under laboratory conditions: Implications for sustainable urban drainage systems

Our study deals with the critical issue of heavy metal pollution in urban runoff; we focused particularly on the threat posed by heavy metals such as nickel to living organisms and water resources owing to their toxicity at low concentrations and non-biodegradability. In this study, we evaluated the efficacy of Filtralite, a filtration medium with excellent hydraulic properties, in removing nickel from water through laboratory experiments and advanced simulation tools. We analysed the geochemical processes involved in nickel removal, including precipitation and adsorption. Importantly, we implemented an innovative approach for numerical modelling using HP1, by combining HYDRUS-1D and PHREEQC for modelling solute transport in porous media and geochemical reactions, respectively. The experimental results revealed that the Filtralite-laden column achieved a removal efficiency of 93.5 % for injected nickel. We observed a significant increase in the effluent pH from 7.0 to 11.5 during the interaction with Filtralite, affecting the solubility of the nickel phases. The model showed the highest nickel concentration in the initial column layers because of rapid chemical precipitation and adsorption upon contact with Filtralite. High-resolution scanning electron microscopy images confirmed the presence of amorphous precipitates around the soil particles, aligning with the changes in pH. This study contributes significantly to environmental engineering and urban water management by introducing an innovative numerical model in HP1 to accurately simulate the removal of nickel using Filtralite. These findings validate the efficiency of Filtralite in extracting nickel from aqueous solutions. Thus, Filtralite is a strong candidate for inclusion in sustainable urban drainage systems.

Cryo-EM combined with image deconvolution to determine ZIF-8 crystal structure

Abstract Metal-organic frameworks (MOFs) are crystalline porous materials with tunable properties, exhibiting great potential in gas adsorption, separation and catalysis.[1, 2] It is challenging to visualize MOFs with transmission electron microscopy (TEM) due to their inherent instability under electron beam irradiation. Here, we employ cryo-electron microscopy (cryo-EM) to capture images of MOF ZIF-8, revealing inverted-space structural information at a resolution of up to about 1.7 Å and enhancing its critical electron dose to around 20 e-/Å2. In addition, it is confirmed by electron-beam irradiation experiments that the high voltage could effectively mitigate the radiolysis, and the structure of ZIF-8 is more stable along the [100] direction under electron beam irradiation. Meanwhile, since the high-resolution electron microscope images is modulated by contrast transfer function (CTF) and it is difficult to determine the positions corresponding to the atomic columns directly from the images. We employ image deconvolution to eliminate the impact of CTF and obtain the structural images of ZIF-8. As a result, the heavy atom Zn and the organic imidazole ring within the organic framework can be distinguished from structural images.

Learning content-aware feature fusion for guided depth map super-resolution

RGB-D data including paired RGB color images and depth maps is widely used in downstream computer vision tasks. However, compared with the acquisition of high-resolution color images, the depth maps captured by consumer-level sensors are always in low resolution. Within decades of research, the most state-of-the-art (SOTA) methods of depth map super-resolution cannot adaptively tune the guidance fusion for all feature positions by channel-wise feature concatenation with spatially sharing convolutional kernels. This paper proposes JTFNet to resolve this issue, which simulates the traditional Joint Trilateral Filter (JTF). Specifically, a novel JTF block is introduced to adaptively tune the fusion pattern between the color features and the depth features for all feature positions. Moreover, based on the variant of JTF block whose target features and guidance features are in the cross-scale shape, the fusion for depth features is performed in a bi-directional way. Therefore, the error accumulation along scales can be effectively mitigated by iteratively HR feature guidance. Compared with the SOTA methods, the sufficient experiment is conducted on the mainstream synthetic datasets and real datasets, i.e., Middlebury, NYU and ToF-Mark, which shows remarkable improvement of our JTFNet.

Simultaneous Calibration of Multiple Cameras and Generation of Omnidirectional Images

Abstract. Omnidirectional images are increasingly being used in various areas, such as urban mapping, virtual reality, agriculture, and robotics. These images can be generated by different acquisition systems, including multi-camera systems, which can acquire higher-resolution images. Stitching techniques are often used and can be suitable for non-metric applications, but rigorous photogrammetric processing is recommended when having more accurate requirements. The main challenges related to this kind of product are the system calibration and the generation of the final omnidirectional images. When using multi-camera systems, the displacement of the cameras' perspective centres can affect the generation of the omnidirectional images and the resulting accuracy. A common approach to minimising the resulting parallax error is to establish a value for the projection cylinder radius as close as possible to the object's depth. This work proposes a highly accurate simultaneous calibration technique for multiple camera systems using self-calibrating bundle adjustment with constraints of stability of the relative orientation parameters. These parameters are later used to generate a projecting cylindrical surface, maintaining the original camera perspective centres and relative orientation angles. The experiments show that using constraints improved both the calibration results and the final omnidirectional images. Residual mismatches between points in overlapping areas are subpixel.

Microcracking in On-Chip Interconnect Stacks: FEM Simulation and Concept for Fatigue Test

AbstractThe semiconductor industry is continuing the scaling down of both device and on-chip interconnect features, for performance and economic reasons. This trend has implications for the design of guard ring structures, i.e. metallic non-functional structures in the back-end-of-line (BEoL) stack designed to be efficient to stop microcracks. In this work, we present a sample design for an in situ experiment to study mechanical degradation and failure mechanisms of crack stop structures in the BEoL stack, to ensure the mechanical robustness of microchips for future technology nodes. Additional finite element method (FEM) simulations provide supplementary understanding of the crack kinetics. To examine the effects of mechanical loading on crack stop elements of the BEoL stack, a novel sample geometry for an in situ fatigue experiment using x-ray microscopy was developed. The x-ray microscope (ZEISS Xradia 800 Ultra) enables high-resolution imaging of the 3D-patterned sample structures and defects such as microcracks. The tailored sample geometry allows the application of a tensile load to a BEoL specimen by a lever mechanism. The feasibility of the sample design is shown by mode-I loading of a pure interconnect sample. Post-mortem analysis by scanning electron microscopy (SEM), confirming planar microcrack propagation from the notch through the dielectric layer with small deflections of the crack path near cone shaped copper vias. FEM simulations focusing on the stress-strain fields around a crack tip indicate the beginning of copper plasticity as major mechanism starting the redirection of cracks due to resulting material compression in front of the obstacle.

Enhancing unsupervised rock CT image super-resolution with non-local attention

Traditional low-resolution rock core images fail to capture the details and features of rocks, limiting the accurate analysis of rock properties. Therefore, researchers have proposed supervised and unsupervised digital rock super-resolution reconstruction methods. Supervised methods require paired data and manual annotation, while unsupervised methods generate high-resolution images through self-learning that are suitable for real-world scenarios with a lack of paired data. However, the current unsupervised methods still face challenges in terms of consistency and feature capturing. To address this problem, a novel unsupervised single-image super-resolution model called NL-CycleGAN is proposed. This model employs a non-local attention-guided CycleGAN framework to effectively capture low-level pixel variations between unpaired source and target images while preserving the overall tone. To evaluate the performance of NL-CycleGAN, we conduct both quantitative and qualitative tests using the DeepRock-SR dataset. In terms of quantitative evaluation, our method achieved the lowest perceptual loss (LPIPS) metric compared to existing methods. Additionally, our model obtained the highest performance in peak signal-to-noise ratio (PSNR), and multi-scale structural similarity index measure (MS-SSIM). In qualitative testing, the comparison images clearly show that our model accurately captures the intricate details of pores in carbonate and sandstone, as well as the complex crack patterns in coal. In conclusion, our model contributes to improving rock resolution and provides more accurate image processing techniques for rock property analysis and geological research.

Consistent land use and land cover classification across 20 years of various high-resolution images for detecting soil sealing in Murcia, Spain

Artificial human-induced soil sealing has numerous negative consequences. The extent of impervious surfaces is a key indicator of the location and intensity of human activity; however, it is also proof of damage to the natural environment as a result of the sealing and modification of ecosystems. Remote sensing techniques can help detect and monitor changes in land use and cover over an extended period. However, the limited availability of consistent satellite images with high spatiotemporal resolutions covering several decades poses major challenges for achieving high overall classification accuracy. An accurate methodology for the multitemporal detection of artificial land cover classes was developed and applied to a case study of the metropolitan area of Murcia (Spain) with its challenging landscape conditions due to the frequent presence of bare soil. For this purpose, a variety of high-resolution satellite images from SPOT 5, Rapid Eye, and PlanetScope covering a period of 20 years were used. To improve the automated detection of built-up areas, the reflectance values of the images, normalised difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), and a building surface digital model were used as inputs for the supervised classification model. We applied a random forest algorithm to non-public, high-resolution images in the Google Earth Engine (GEE) as a processing environment to identify eight target land cover classes. The results show that the proposed methodology leads to a substantial improvement, after including the indices and the digital building model, in the overall accuracy (from 93.16 to 95.97%) and in all classes. This improvement was significant for the artificial classes and was particularly noticeable for the built-up areas (from 91.1 to 95.64%) because their confusion with bare soil was considerably reduced. This work demonstrates the effectiveness of the building-surface digital model as a tool for training the classification model, as it reduces uncertainty in confusion with other spectrally similar classes and its applicability to multisource imagery.

Precise immunofluorescence canceling for highly multiplexed imaging to capture specific cell states

Cell states are regulated by the response of signaling pathways to receptor ligand-binding and intercellular interactions. High-resolution imaging has been attempted to explore the dynamics of these processes and, recently, multiplexed imaging has profiled cell states by achieving a comprehensive acquisition of spatial protein information from cells. However, the specificity of antibodies is still compromised when visualizing activated signals. Here, we develop Precise Emission Canceling Antibodies (PECAbs) that have cleavable fluorescent labeling. PECAbs enable high-specificity sequential imaging using hundreds of antibodies, allowing for reconstruction of the spatiotemporal dynamics of signaling pathways. Additionally, combining this approach with seq-smFISH can effectively classify cells and identify their signal activation states in human tissue. Overall, the PECAb system can serve as a comprehensive platform for analyzing complex cell processes.

An Improved Synchrosqueezing S-Transform and Its Application in a GPR Detection Task.

The S-transform is a fundamental time-frequency (T-F) domain analysis method in ground penetrating radar (GPR) data processing and can be used for identifying targets, denoising, extracting thin layers, and high-resolution imaging. However, the S-transform spectrum experiences energy leakage near the instantaneous frequency. This phenomenon causes frequency components to erroneously spread over a wider range, impacting the accuracy and precision of GPR data processing. Synchrosqueezing is an effective method to prevent spectrum leakage. In this work, we introduce the synchrosqueezing generalized phase-shifting S-transform (SS-GPST). Initially, it resolves the compatibility issue between the S-transform and the synchrosqueezing strategy through phase-shifting. Subsequently, the SS-GPST accomplishes spectral energy focusing and resolution enhancement via a generalized parameter and synchrosqueezing. A synthetic signal test shows that the SS-GPST excels over other methods at focusing degree, spectral resolution, and signal reconstruction accuracy and speed. In actual GPR tunnel detection data processing, we assess the adaptability of the SS-GPST from three aspects: spectral energy distribution, thin layer identification, and data denoising. The results indicate: (1) compared to other methods, the SS-GPST accurately expresses spectral components with a strong focusing degree and fewer interference components; (2) high-frequency slices of the SS-GPST accurately detect the top and bottom interfaces of a 3.0-3.5 cm reinforcement protection layer; and (3) due to fewer interference components in the SS-GPST spectrum, reconstructing GPR profiles through the SS-GPST inverse transform is an efficient denoising technique. The SS-GPST demonstrates adaptability to different data processing purposes, offers high-resolution T-F spectra, and shows potential to supersede the S-transform.

Lens-free reflective topography for high-resolution wafer inspection

The demand for high-resolution and large-area imaging systems for non-destructive wafer inspection has grown owing to the increasing complexity and extremely fine nature of semiconductor processes. Several studies have focused on developing high-resolution imaging systems; however, they were limited by the tradeoff between image resolution and field of view. Hence, computational imaging has arisen as an alternative method to conventional optical imaging, aimed at enhancing the aforementioned parameters. This study proposes a method for improving the resolution and field of view of an image in a lens-less reflection-type system. Our method was verified by computationally restoring the final image from diffraction images measured at various illumination positions using a visible light source. We introduced speckle illumination to expand the numerical aperture of the entire system, simultaneously improving image resolution and field of view. The image reconstruction process was accelerated by employing a convolutional neural network. Using the reconstructed phase images, we implemented high-resolution topography and demonstrated its applicability in wafer surface inspection. Furthermore, we demonstrated an ideal diffraction-limited spatial resolution of 1.7 μm over a field of view of 1.8 × 1.8 mm2 for the topographic imaging of targets with various surface roughness. The proposed approach is suitable for applications that simultaneously require high throughput and resolution, such as wafer-wide integrated metrology, owing to its compact design, cost-effectiveness, and mechanical robustness.

Multi-Scale Fusion Siamese Network Based on Three-Branch Attention Mechanism for High-Resolution Remote Sensing Image Change Detection

Remote sensing image change detection (CD) is an important means in remote sensing data analysis tasks, which can help us understand the surface changes in high-resolution (HR) remote sensing images. Traditional pixel-based and object-based methods are only suitable for low- and medium-resolution images, and are still challenging for complex texture features and detailed image detail processing in HR images. At present, the method based on deep learning has problems such as inconsistent fusion and difficult model training in the combination of the difference feature information of the deep and shallow layers and the attention mechanism, which leads to errors in the distinction between the changing region and the invariant region, edge detection and small target detection. In order to solve the above problems of inconsistent fusions of feature information aggregation and attention mechanisms, and indistinguishable change areas, we propose a multi-scale feature fusion Siamese network based on attention mechanism (ABMFNet). To tackle the issues of inconsistent fusion and alignment difficulties when integrating multi-scale fusion and attention mechanisms, we introduce the attention-based multi-scale feature fusion module (AMFFM). This module not only addresses insufficient feature fusion and connection between different-scale feature layers, but also enables the model to automatically learn and prioritize important features or regions in the image. Additionally, we design the cross-scale fusion module (CFM) and the difference feature enhancement pyramid structure (DEFPN) to assist the AMFFM module in integrating differential information effectively. These modules bridge the spatial disparity between low-level and high-level features, ensuring efficient connection and fusion of spatial difference information. Furthermore, we enhance the representation and inference speed of the feature pyramid by incorporating a feature enhancement module (FEM) into DEFPN. Finally, the BICD dataset proposed by the laboratory and public datasets LEVIR-CD and BCDD are compared and tested. We use F1 score and MIoU values as evaluation metrics. For AMBMFNet, the F1 scores on the three datasets are 77.69%, 81.57%, and 77.91%, respectively, while the MIoU values are 84.65%, 85.84%, and 84.54%, respectively. The experimental results show that ABMFNet has better effectiveness and robustness.

A new method of high-resolution NPP estimation and its implementation in caragana shrublands on the Loess Plateau, China

ABSTRACT Accurate estimation for vegetation net primary production (NPP) at high resolution is essential for ecosystem management and at local to global scales. However, no reliable methods are available to achieve fine-resolution estimation. In this study, a new NPP estimation system was developed by integrating high spatial resolution remote sensing images, tree ring measurements, and process-based model CASA. The system was illustrated by estimating the historical NPP of caragana shrublands from 2011 to 2021 in Dingbian County, China. The results showed that: (1) by employing the biomass model and tree ring measurements, an NPP-crown width model was established to enable a large number of samples for calibrating the CASA model on high spatial resolution images without continuous field measurements. The calibrated parameters, including maximum NDVI, minimum NDVI, and maximum light use efficiency, were determined to be 0.415, 0.022 and 0.025, respectively; (2) according to the estimation by the calibrated CASA model, the NPP in Dingbian County revealed an increasing trend from 2011 to 2021, and the NPP in southern hilly and gully regions was significantly higher than the other regions; (3) among the different indices, max temperature of warmest month had a significant negative effect on the NPP of cagarana shrublands, whereas annual precipitation had a positive effect. In the northern and central regions, air temperature predominantly influenced NPP, while in the southern regions, both temperature and precipitation played a joint role. The implementation in this study illustrated that the NPP estimation system could provide reliable NPP with high resolution and efficient to monitor and detect dominant factors affecting NPP for ecosystem management.

High-frequency photoacoustic and ultrasound imaging for skin evaluation: Pilot study for the assessment of a chemical burn.

Skin architecture and its underlying vascular structure could be used to assess the health status of skin. A non-invasive, high resolution and deep imaging modality able to visualize skin subcutaneous layers and vasculature structures could be useful for determining and characterizing skin disease and trauma. In this study, a multispectral high-frequency, linear array-based photoacoustic/ultrasound (PAUS) probe is developed and implemented for the imaging of rat skin in vivo. The study seeks to demonstrate the probe capabilities for visualizing the skin and its underlying structures, and for monitoring changes in skin structure and composition during a 5-day course of a chemical burn. We analayze composition of lipids, water, oxy-hemoglobin, and deoxy-hemoglobin (for determination of oxygen saturation) in the skin tissue. The study successfully demonstrated the high-frequency PAUS imaging probe was able to provide 3D images of the rat skin architecture, underlying vasculature structures, and oxygen saturation, water, lipids and total hemoglobin.

A study of two young multipolar planetary nebulae: Hen 2-73 and Hen 2-96

We perform an infrared (IR) spectral and visible morphological study of two young planetary nebulae (YPNe) Hen 2-73 and Hen 2-96 using archival Spitzer Space Telescope and Hubble Space Telescope (HST) observations to understand their dust properties and nebular structures. High-resolution HST images of these nebulae show several bipolar lobes and ionised tori in the central regions of both objects. The presence of these multi-lobe structures suggests that the formation process of these nebulae is complex. To search for a possible link between the central sources and multipolar appearances of these objects, the Transiting Exoplanet Survey Satellite (TESS) observations are used to examine whether their central stars (CSs) exhibit periodic photometric variations. In the TESS observations, the CS light curve of Hen 2-96 shows a photometric variation with a period of 2.23 hr. The IR spectra of these two YPNe suggest that the nebulae have mixed dust environments, which are associated with the presence of dense tori created by central binary interactions in these objects. Two three-dimensional models are constructed to study the complex nebular structures of the YPNe. These simulations suggest that the number of multipolar YPNe may be larger than observed. In addition, we analyse the spectral energy distributions of these nebulae to study their gas, dust, and photospheric components.

Lagrangian characterization of the southwestern Atlantic from a dense surface drifter deployment

The Southwestern Atlantic (SWA) is characterized by its large Eddy Kinetic Energy as the result of the confluence of two major western boundary currents, the northward flowing Malvinas Current (MC) and the southward flowing Brazil Current. The SWA study was addressed in the literature based on altimetry data, in situ measurements, regional models and ocean reanalysis. The present study constitutes the first effort to sample a portion of the SWA, with a dense drifter array (N = 62) deployment. The drifters, drogued at 15 m depths, were deployed across the MC and the Argentine Continental Shelf along two zonal transects located at 47°S and 47.25°S, between the 8th and the September 9, 2021. Drifters were set to deliver their position every 10 and 60 min, providing accurate Lagrangian trajectories that provide information on a large range of space and time scales of the surface currents. Three regions are clearly identified based on the analysis of the speed of the drifters, of their trajectories and of the spectral density of their velocities: the continental shelf, the slope and the open ocean. The comparison of the trajectories of the drifters with satellite altimetry images shows that, in general, drifters follow mesoscale features that are detectable in satellite altimetry maps. The analysis of the drifter trajectories also allowed us the study of submesoscale features of the flow (1–10 km) that are not observable in satellite altimetry data. Comparison with cloud-free, high-resolution color images, shows that drifter trajectories organized by the mesoscale flow might also locally follow sub-mesoscale features. In frontal regions it was found that drifter velocities double satellite altimetry geostrophic velocities, which suggests that the dynamics at those regions is largely dominated by ageostrophic components. The ageostrophic Ekman component might explain the direction of the drifters when strong winds from a given direction prevail for several days and the drifters are not in a region with large sea surface height (SSH) gradients. The joint analysis of drifters’ trajectory and SSH clearly depicts that mesoscale features on the open ocean region control the cross-shelf exchanges between the MC and open ocean regions as well as the strength and width of the MC. Finally, the spatial density distribution of the drifters during the first hours after deployment and within a small eddy also allowed us to characterize the flow in terms of its divergence, vorticity and strain, indicating that the MC is geostrophic and has a jet-like behavior while the eddy is largely ageostrophic and has a dominant vorticity component over strain. We conclude observing that the analysis of a dense array of drifters provides valuable information of the flow that cannot be attained solely based on satellite data.

A novel STM for quality atomic resolution with piezoelectric motor of high compactness and simplicity

Scanning tunneling microscope (STM) is a renowned scientific tool for obtaining high-resolution atomic images of materials. Herein, we present an innovative design of the scanning unit with a compact yet powerful inertial piezoelectric motor inspired by the Spider Drive motor principle. The scanning unit mainly consists of a small 9 mm long piezoelectric tube scanner (PTS), one end of which is coaxially connected to the main sapphire body of the STM. Of particular emphasis in this design is the piezoelectric shaft (PS), constructed from piezoelectric material instead of conventional metallic or zirconium materials. The PS is a rectangular piezoelectric stack composed of two piezoelectric plates, which are elastically clamped on the inner wall of the PTS via a spring strip. The PTS and PS expand and contract independently with each other to improve the inertial force and reduce the threshold voltage. To ensure the stability of the PS and balance the stepping performance of the inertial motor, a counterweight, and a matching conical spring are fixed at the tail of the PS. This innovative design allows for the assessment of scanning unit performance by applying a driving signal, threshold voltage is 50 V at room temperature. Step sizes vary from 0.1 to 1 µm by changing the driving signal at room temperature. Furthermore, we successfully obtained atomic-resolution images of a highly oriented pyrolytic graphite (HOPG) sample and low drift rates of 23.4 pm/min and 34.6 pm/min in X-Y plane and Z direction, respectively, under ambient conditions. This small, compact STM unit has the potential for the development of a rotatable STM for use in cryogen-free magnets, and superconducting magnets.