Reflection Imaging Research Articles

Construction of an upconversion luminescence composite nanoprobe for ratiometric single particle imaging detection of hydrogen peroxide in food

Hydrogen peroxide (H2O2) is associated with diseases and food safety. Thus, it is essential to achieve sensitive and efficient detection of H2O2. Herein, a ratiometric luminescence composite nanoprobe was designed for single particle imaging sensing of H2O2 by combining NaYbF4:Er@NaYbF4:Tm@NaGdF4:Yb upconversion nanoparticles (UCNPs) with cyanine dye IR-628. High brightness NaYbF4:Er@NaYbF4:Tm@NaGdF4:Yb UCNPs with double-peak emission (665 and 812 nm) were synthesised. Cyanine dye IR-628 with an absorption peak at 628 nm was synthesised and served as a recognition unit. More importantly, on the basis of the upconversion luminescence total internal reflection imaging technique, we developed a ratiometric single particle imaging quantitative analysis for sensing H2O2 with a limit of quantitation of 5 nM. This ratiometric single particle imaging method not only greatly eliminates the influence of the probe concentration and instrumental and environmental factors, but also reduces the dosage of the reagent used and improves the sensitivity of detection.

Controllable Seismic Velocity Synthesis Using Generative Diffusion Models

AbstractAccurate seismic velocity estimations are vital to understanding Earth's subsurface structures, assessing natural resources, and evaluating seismic hazards. Machine learning‐based inversion algorithms have shown promising performance in regional (i.e., for exploration) and global velocity estimations, while their effectiveness hinges on access to large and diverse training data sets whose distributions generally cover the target solutions. Additionally, enhancing the precision and reliability of velocity estimation also requires incorporating prior information, for example, geological classes, well logs, and subsurface structures, but current statistical or neural network‐based methods are not flexible enough to handle such multimodal information. To address both challenges, we propose to use conditional generative diffusion models for seismic velocity synthesis in which we readily incorporate those priors. This approach enables the generation of seismic velocities that closely match the expected target distribution, offering data sets informed by both expert knowledge and measured data to support training for data‐driven geophysical methods. We demonstrate the flexibility and effectiveness of our method through training diffusion models on the OpenFWI data set under various conditions, including class labels, well logs, reflectivity images, and the combination of these priors. The performance of the approach under out‐of‐distribution conditions further underscores its generalization ability, showcasing its potential to provide tailored priors for velocity inverse problems and create specific training data sets for machine learning‐based geophysical applications.

Development and prospect of acoustic reflection imaging logging processing and interpretation method

Acoustic reflection imaging logging technology can detect and evaluate the development of reflection anomalies, such as fractures, caves and faults, within a range of tens of meters from the wellbore, greatly expanding the application scope of well logging technology. This article reviews the development history of the technology and focuses on introducing key methods, software, and on-site applications of acoustic reflection imaging logging technology. Based on the analyses of major challenges faced by existing technologies, and in conjunction with the practical production requirements of oilfields, the further development directions of acoustic reflection imaging logging are proposed. Following the current approach that utilizes the reflection coefficients, derived from the computation of acoustic slowness and density, to perform seismic inversion constrained by well logging, the next frontier is to directly establish the forward and inverse relationships between the downhole measured reflection waves and the surface seismic reflection waves. It is essential to advance research in imaging of fractures within shale reservoirs, the assessment of hydraulic fracturing effectiveness, the study of geosteering while drilling, and the innovation in instruments of acoustic reflection imaging logging technology.

A hybrid radiative energy transfer and image source method for high-frequency vibrational coupled plates

A hybrid approach composed of the radiative energy transfer method (RETM) and image source method (ISM) is proposed in this study for estimating the vibrational energy of coupled plates loaded by high-frequency point excitation. The vibrational energy at a receiver is represented by energy density and intensity, which are superposed by incoherent rays emitted by the load point in the analyzed domain and reflected/transmitted by the domain boundaries. The energy rays reflected/transmitted at the boundaries are described by two modes: diffuse reflection/transmission, which is a basic assumption in RETM, and the other obeys Snell’s law of reflection/refraction, which is deduced by Fermat’s principle and often applied in ISM. The local energy response distribution in the loading subsystem is described by ISM. The energies in other subsystems are described by RETM. The energy transfer relationship between subsystems is expressed by the energy transfer coefficient. At the boundary of coupled plates, a Fredholm equation of the second type is established through the balance among the outgoing energy of the diffuse reflection fictitious sources and the incident energy of actual sources, other diffuse reflection sources, and specular reflection image sources, which can be used to determine the intensity of the diffuse reflection fictitious sources. The average energy transfer coefficient in the transmission direction half-space is used to express the energy transfer relationship associated with diffuse reflection sources, while the energy transfer relationship associated with specular reflection sources is expressed directly by the energy transfer coefficient. Numerical tests show that the energy distributions and energy flow fields of typical coupled plates are well predicted by the proposed hybrid RETM-ISM approach. Compared with RETM, hybrid RETM-ISM is more consistent with the FEM solution.

Reflective imaging of myelin integrity in the human and mouse central nervous systems.

The structural integrity of myelin sheaths in the central nervous system (CNS) is crucial for the maintenance of its function. Electron microscopy (EM) is the gold standard for visualizing individual myelin sheaths. However, the tissue processing involved can induce artifacts such as shearing of myelin, which can be difficult to distinguish from true myelin abnormalities. Spectral confocal reflectance (SCoRe) microscopy is an imaging technique that leverages the differential refractive indices of compacted CNS myelin in comparison to surrounding parenchyma to detect individual compact myelin internodes with reflected light, positioning SCoRe as a possible complementary method to EM to assess myelin integrity. Whether SCoRe is sensitive enough to detect losses in myelin compaction when myelin quantity is otherwise unaffected has not yet been directly tested. Here, we assess the capacity of SCoRe to detect differences in myelin compaction in two mouse models that exhibit a loss of myelin compaction without demyelination: microglia-deficient mice (Csf1r-FIRE Δ/Δ) and wild-type mice fed with the CSF1R inhibitor PLX5622. In addition, we compare the ability to detect compact myelin sheaths using SCoRe in fixed-frozen versus paraffin-embedded mouse tissue. Finally, we show that SCoRe can successfully detect individual sheaths in aged human paraffin-embedded samples of deep white matter regions. As such, we find SCoRe to be an attractive technique to investigate myelin integrity, with sufficient sensitivity to detect myelin ultrastructural abnormalities and the ability to perform equally well in tissue preserved using different methods.

Optical and electrochemical studies on single-phase ZnSnO3 nanostructures—A photosensitive approach

A sol-gel-combustion reaction approach is used to synthesize nanocrystalline, single-phase ZnSnO3 phosphor. XRD with the Rietveld refinement investigation reveals a previously unreported orthorhombic structure of ZnSnO3. FTIR analysis confirms the formation of the ZnSnO3 phase. Microstructural SEM and TEM examinations affirm the petal-like morphology of the ZnSnO3 nanostructure. UV-DRS analysis signifies ZnSnO3 as a semiconducting material with a lowest energy band gap of 2.94 eV, which has never been recorded before. Photoluminescence (PL) studies reveal defect-related emission in ZnSnO3. Cyclic voltammetry measurements confirm the redox process and photo-generated carrier recombination via defect levels. ZnSnO3 is identified as a p-type semiconductor by Mott-Schottky analysis. When irradiated with 397 nm UV light, the semiconducting nanostructures emit near-white light. Finally, the investigation of ZnSnO3 nanopowder for latent fingerprint impressions reveals an unusual diffuse reflection and high-resolution images under a sodium vapour lamp and LASER-LED illumination.

Integrated Technique Provides Effective Water Diagnostics in Tight Sand

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3864145, “Evaluating the Hydraulic Fracture Through Acoustic Reflection Imaging and Production Logging for Water Diagnostic Beyond the Wellbore: A Case Study From Chang 8 Tight Sand in the Ordos Basin, China,” by Guangsheng Liu, Dajian Li, and Gang Zheng, PetroChina, et al. The paper has not been peer reviewed. _ The Triassic Chang 8 tight sand reservoir in the Xifeng block of the Ordos Basin features low permeability, which means that hydraulic fracturing and subsequent waterflooding were performed during its development phase. Water breakthrough was encountered after a short period of oil production. A solution of borehole acoustic reflection imaging combined with production logging was proposed in a horizontal well suffering from high water cut. The objective was to determine which stages contributed most to water production, understand the cause, and, ultimately, create a water shutoff plan. Introduction The Ordos Basin, with an area of approximately 2.5×105 km2, is in North China. The Upper Triassic Yanchang formation is subdivided into the Chang 1 to 10 members, from top to bottom. It contains significant oil reserves in siltstone and sandstone reservoirs, especially in Chang 6 through Chang 8, that have been the major oil-producing resources in recent years. In the Triassic Chang 8 tight sand reservoir, horizontal well drilling and multiple-stage hydraulic fracturing have become common practice. In the study block, the well of interest was hydraulically fractured by coiled tubing with sand-jet perforation and fracturing operations in one run with a retrievable packer in the bottomhole assembly of the coiled tubing. In the study block, when some producing wells encountered water breakthrough, traditional water diagnostics using production logging was not enough; a survey to detect hydraulic fractures beyond the wellbore was needed. Theory and Methods Borehole Acoustic Reflection Imaging. The processing workflow for acoustic reflected waves mainly consists of two parts. The first is a filtering process to suppress the borehole mode and noise in order to preserve the reflected wave. The second is to migrate the reflected wave to the true position of a reflector. The conventional migration method used for acoustic reflection imaging normally requests previous information relating to reflector dip and produces 2D images, which show the reflector shape but have hard-to-extract precise quantitative information. A trial reflector-migration method covered in the literature was introduced in 2016 that does not require input of structure dip and is of high resolution. A 3D slowness-time-coherence method was developed in 2018, also covered in the literature, that could determine the true dip, azimuth, and distance of a reflector.

Hybrid calibration method for a single camera stereo digital image correlation system

In single camera stereo digital image correlation systems, the existing calibration methods have problems with poor accuracy and violation of theoretical constraints, so we have proposed a hybrid calibration method. In this study, we first explain the principles of the existing single camera stereo measurement calibration methods. Then, on the basis of the classical camera calibration method combined with the characteristics of planar mirror reflection imaging, a hybrid calibration method is proposed that not only satisfies the constraints of the same intrinsic parameters but also has higher accuracy. Next, we complete the mathematical model of the hybrid calibration method and explain the specific calibration process. Finally, the experimental results of point distance reconstruction and static displacement measurement show that, compared with the existing calibration methods, the hybrid calibration method has lower error and higher reconstruction accuracy.

Seismic and Potential Field Constraints on Upper Crustal Architecture of Inner Bering Shelf, Offshore Southwestern Alaska

Southwestern Alaska encompasses a group of fault-bounded tectonostratigraphic terranes that were accreted to North America during the Mesozoic and Paleogene. To characterize the offshore extension of these terranes and several significant faults identified onshore, we reprocessed three intersecting multichannel deep seismic reflection profiles totaling ∼750 line-km that were shot by the R/V Ewing across part of the inner Bering continental shelf in 1994. Since the uppermost seismic section is often contaminated by high amplitude water layer multiples from the hard and shallow seafloor, the migrated reflection images are supplemented with high-resolution P wave velocity models derived by traveltime tomography of the recorded first-arrivals to depths of up to 2000 m. Additionally, other geophysical datasets such as seismicity, well logs, high resolution satellite-altimetry gravity, air-borne magnetics, ship-board gravity and magnetics, are also incorporated into an integrated regional interpretation. We delineate the offshore extension of the major mapped geological elements, including the Togiak fault (TGF), East Kulukak fault (EKF), Chilchitna fault (CF), Lake Clark fault (LCF), Togiak terrane (TT), Goodnews terrane (GT), Peninsular terrane (PT), Northern Kahiltna flysch (NKF) and Southern Kahiltna flysch (SKF) deposits, and the regional suture zone. The geophysical evidence from this study suggest that the major faults and terrane boundaries of southwestern Alaska, excluding the LCF, not only extend beneath the Bering shelf offshore but also appear to rotate, forming a trend parallel to the inactive Beringian margin. The LCF extends offshore but likely terminates in the northeastern part of the Bristol Bay basin. Additionally, the constraints from seismicity data indicates that while the major faults in southwestern Alaska exihibit some activity onshore, they remain dormant in the offshore region. These new findings will contribute to a better understanding of terrane accretion processes and existing fault models of southwestern Alaska.

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

A seismic ambient noise data classification method based on waveform and frequency-wavenumber analysis: Application to reliable geological interpretation adjacent to Well Songke-2, Northeast China

Passive seismic interferometry techniques enable the retrieval of virtual shot gathers at receiver locations. However, it is difficult to distinguish body waves from surface waves in seismic ambient noise data, which leads to failed dispersion measurements, artificial deep reflections, and misleading geologic interpretations. We develop a new method that uses the waveforms and their corresponding f- k spectra to identify body waves and surface waves. Our technique functions as a data classification procedure before wavefield retrieval and subsequent imaging. A field data example is conducted to test the feasibility of this technique. The field data results demonstrate that our technique can reconstruct satisfactory high signal-to-noise-ratio wavefields for reliable imaging and interpretation purposes. The method can also serve as a validation tool for identifying surface wave-related artificial events in the obtained virtual source reflection image. The marker boundaries of the Songliao Basin in Northeast China are interpreted in the obtained profile and are in agreement with the well-logging data. In addition, two normal faults are detected, which correspond to the extensional rift environment during the early Cretaceous.

Non-contact leaf wetness measurement with laser-induced light reflection and RGB imaging

Leaf wetness duration is a crucial factor in plant disease management. Current optical methods use standard RGB images to classify leaf wetness as a binary problem, i.e., wet or dry. Green leaves absorb red light, whereas water reflects it. Based on this difference, an experimental platform was built to semi-automatically measure droplet deposition on grape leaves while capturing red laser images using an RGB camera. The setup measured changes in leaf mass and area of scanned leaves to determine the water mass per leaf area as a measure of leaf wetness. A sprayer was used to apply water droplets to the leaves. As the amount of deposited water increased, the mean red channel intensity decreased, with more bright spots in the images. These bright spots were more distinguishable as droplets in the green channel. Segmented leaf area, mean red channel intensity, and the number of identified droplets were used as image features. A generalised additive model was employed to predict the leaf wetness value with extracted features. The R-squared value for the prediction of the validation dataset was 0.71. Image resolution and leaf orientation were identified as factors that influenced the model accuracy. The measurement method introduced in this study shows potential for accurately quantifying leaf wetness, and implies that in practice detecting leaf wetness can be integrated into a multi-classification problem, thereby broadening the potential applications of optical methods.

Nonexcavation Localization Method for Buried PE Pipes Based on Elastic Wave Reflection Imaging and the BPA Method

Nonexcavation Localization Method for Buried PE Pipes Based on Elastic Wave Reflection Imaging and the BPA Method

A Retinex-based network for image enhancement in low-light environments.

Most of the existing low-light image enhancement methods suffer from the problems of detail loss, color distortion and excessive noise. To address the above-mentioned issues, this paper proposes a neural network-based low-light image enhancement network. The network is divided into three parts: decomposition network, reflection component denoising network, and illumination component enhancement network. In the decomposition network, the input image is decomposed into a reflection image and an illumination image. In the reflection component denoising network, the Unet3+ network improved by fusion CA attention is adopted to denoise the reflection image. In the illumination component enhancement network, the adaptive mapping curve is adopted to enhance the illumination image iteratively. Finally, the processed illumination and reflection images are fused based on Retinex theory to obtain the final enhanced image. The experimental results show that the proposed network achieves excellent visual effects in subjective evaluation. Additionally, it shows a significant improvement in objective evaluation metrics, including PSNR, SSIM, NIQE, and so on, when compared to the results in several public datasets.

A method for extracting corneal reflection images from multiple eye images

The incident light reflected from the cornea is rich in information about the human surroundings, and these reflected rays are imaged by the camera, which can be used for research on human consciousness and gaze analysis, and produce certain help in the fields of psychology, human computer interaction and disease diagnosis. However, limited by the low corneal reflection ability, when a high-definition camera captures corneal reflecting rays, a large amount of color and texture interference from the iris can seriously contaminate the corneal reflection images, resulting in low usability and ubiquity of corneal reflection images. In this paper, we propose a corneal reflection image extraction method with multiple eye images as input. We align the iris regions of multiple eye images with the help of iris localization method, and by comparing multiple iris regions, we obtain the complementary iris regions, so that the iris interference in the corneal reflection region can be stripped completely. A large number of experiments have demonstrated that our work can effectively mitigate iris interference and effectively improve the quality of corneal reflection images.

Breast Glandular and Ductal Volume Changes during the Menstrual Cycle: A Study in 48 Breasts Using Ultralow-Frequency Transmitted Ultrasound Tomography/Volography.

The aim of this study was to show for the first time that low-frequency 3D-transmitted ultrasound tomography (3D UT, volography) can differentiate breast tissue types using tissue properties, accurately measure glandular and ductal volumes in vivo, and measure variation over time. Data were collected for 400 QT breast scans on 24 women (ages 18-71), including four (4) postmenopausal subjects, 6-10 times over 2+ months of observation. The date of onset of menopause was noted, and the cases were further subdivided into three (3) classes: pre-, post-, and peri-menopausal. The ducts and glands were segmented using breast speed of sound, attenuation, and reflectivity images and followed over several menstrual cycles. The coefficient of variation (CoV) for glandular tissue in premenopausal women was significantly larger than for postmenopausal women, whereas this is not true for the ductal CoV. The glandular standard deviation (SD) is significantly larger in premenopausal women vs. postmenopausal women, whereas this is not true for ductal tissue. We conclude that ducts do not appreciably change over the menstrual cycle in either pre- or post-menopausal subjects, whereas glands change significantly over the cycle in pre-menopausal women, and 3D UT can differentiate ducts from glands in vivo.

High-sensitivity THz-ATR imaging of cerebral ischemia in a rat model.

The fast label-free detection of the extent and degree of cerebral ischemia has been the difficulty and hotspot for precise and accurate neurosurgery. We experimentally demonstrated that the fresh cerebral tissues at different ischemic stages within 24 hours can be well distinguished from the normal tissues using terahertz (THz) attenuated total reflection (ATR) imaging system. It was indicated that the total reflectivity of THz wave for ischemic cerebral tissues was lower than that for normal tissues. Especially, compared to the images stained with 2,3,5-triphenyl tetrazolium chloride (TTC), the ischemic tissues can be detected using THz wave with high sensitivity as early as the ischemic time of 2.5 hours, where THz images showed the ischemic areas became larger and diffused as the ischemic time increasing. Furthermore, the THz spectroscopy of cerebral ischemic tissues at different ischemic times was obtained in the range of 0.5-2.0 THz. The absorption coefficient of ischemic tissue increased with the increase of ischemic time, whereas the refractive index decreased with prolonging the ischemic time. Additionally, it was found from hematoxylin and eosin (H&E) staining microscopic images that, with the ischemic time increasing, the cell size and cell density of the ischemic tissues decreased, whereas the intercellular substance of the ischemic tissues increased. The result showed that THz recognition mechanism of the ischemia is mainly based on the increase of intercellular substance, especially water content, which has a stronger impact on absorption of THz wave than that of cell density. Thus, THz imaging has great potential for recognition of cerebral ischemia and it may become a new method for intraoperative real-time guidance, recognition in situ, and precise excision.

Relationship between radar reflectivity thresholds and very low frequency/low frequency total lightning for thunderstorm identification

AbstractTo improve our knowledge of the spatio‐temporal correspondence between radar reflectivity and VLF/LF total lightning data, this paper proposes indexes to quantify the horizontal distribution and temporal evolution characteristics between radar composite reflectivity images and total lightning density map, lightning clusters and radar cells with different radar reflectivity thresholds (30, 35, 40, 45 and 50 dBZ), respectively. It is found that the number of radar grid cells with radar reflectivity over 30 dBZ is ten times the number of lightning grid cells. At the identification stage, the lightning activity regions in a radar cell account for less than 30% using thresholds of 30, 35 and 40 dBZ, respectively, and the radar cell has more than one lightning cluster, which means that the mesoscale convective systems typically have more than one draft, and drafts are only small part of the convection. The majority of the centroid deviations is less than 10 km, indicating that there are some shifts between electrically active regions and convective regions. Results suggest that VLF/LF total lightning data are consistent with radar data and total lightning data can be used individually on a smaller spatio‐temporal scale than radar data.

Streak tube imaging lidar with kilohertz laser pulses and few-photons detection capability

Lidar using active light illumination is capable of capturing depth and reflectivity information of target scenes. Among various technologies, streak tube imaging lidar (STIL) has garnered significant attention due to its high resolution and excellent precision. The echo signals of a STIL system using single laser pulse are often overwhelmed by noise in complex environments, making it difficult to discern the range of the target. By combining high-frequency laser pulses with the repetitive sweep circuit, the STIL system enables efficient detection of few-photons signal in weak-light environments. Additionally, we have developed a robust algorithm for estimating the depth and reflectivity images of targets. The results demonstrate that this lidar system achieves a depth resolution better than 0.5 mm and a ranging accuracy of 95 um. Furthermore, the imaging of natural scenes also validates the exceptional 3D imaging capability of this system.

LED Junction Temperature Measurement: From Steady State to Transient State.

In this review, we meticulously analyze and consolidate various techniques used for measuring the junction temperature of light-emitting diodes (LEDs) by examining recent advancements in the field as reported in the literature. We initiate our exploration by delineating the evolution of LED technology and underscore the criticality of junction temperature detection. Subsequently, we delve into two key facets of LED junction temperature assessment: steady-state and transient measurements. Beginning with an examination of innovations in steady-state junction temperature detection, we cover a spectrum of approaches ranging from traditional one-dimensional methods to more advanced three-dimensional techniques. These include micro-thermocouple, liquid crystal thermography (LCT), temperature sensitive optical parameters (TSOPs), and infrared (IR) thermography methods. We provide a comprehensive summary of the contributions made by researchers in this domain, while also elucidating the merits and demerits of each method. Transitioning to transient detection, we offer a detailed overview of various techniques such as the improved T3ster method, an enhanced one-dimensional continuous rectangular wave method (CRWM), and thermal reflection imaging. Additionally, we introduce novel methods leveraging high-speed camera technology and reflected light intensity (h-SCRLI), as well as micro high-speed transient imaging based on reflected light (μ_HSTI). Finally, we provide a critical appraisal of the advantages and limitations inherent in several transient detection methods and offer prognostications on future developments in this burgeoning field.