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Solution-processed organic photodetectors (OPDs) with spectral response in the near-infrared (NIR) region have broad applications such as in industries, spectroscopic/medical instruments, communications, image sensing, and environmental monitoring. OPDs capable of selective spectral response are particularly appealing for applications including secure optical data link and color image sensing systems. Here, we report an organic photodetector with a highly selective spectral response to near-infrared radiation without the use of a color filter. The operation of the OPDs takes advantage of a charge collection narrowing effect, resulting in a narrowband response at 760 nm with a full width at half maximum of 47 nm and an external quantum efficiency of 46%. Owing to the features of the narrowband response in NIR, our organic photodetectors are used as optical signal receivers for an optical communication system, which achieves a data transmission rate of 12.6 kB/s with a low bit error rate on the order of 10−4. We further investigated the response bandwidth in devices with different active layer thicknesses and area size and their response bandwidth under different reverse bias conditions as well. The optimized device shows a −3 dB response bandwidth of 3.02 MHz and a data transmission rate of 1.41 Mbit/s. The results highlight the promising potential of the nonfiltered OPDs for a variety of applications, including light communication, short-range data transmission, and image sensing. [ABSTRACT FROM AUTHOR]

Electrothermal instability and its effect on the uniformity of discharge channels during underwater electrical wire explosions at different energy deposition rates have been investigated. According to the liquid–vapor transition mechanism, we classified underwater electrical explosion into "phase explosion mode" and "supercritical mode." Two sets of experiments corresponding to the two modes were conducted, and the exploding wires were observed by a shadow imaging system. Results showed that a bamboo-shaped discharge channel was formed in the phase explosion mode, whereas the discharge channel in the supercritical mode was a uniform cylinder. Self-consistent magnetohydrodynamic simulation results indicated that exploding wires transfer into liquid–vapor coexistence phase in the phase explosion mode, accompanied by a rapid increase in the density perturbation and the formation of bamboo-shaped structures. Moreover, a small perturbation model was derived to analyze the electrothermal instability in different thermodynamic states. It was indicated that the density perturbation is easier to grow in the liquid–vapor coexistence state than the supercritical state, which provides a theoretical explanation for the differences between the two electrical explosion modes. [ABSTRACT FROM AUTHOR]

The scanning electron microscope (SEM) recordings of dynamic nano-electromechanical systems (NEMS) are difficult to analyze due to the noise caused by low frame rate, insufficient resolution, and blurriness induced by applied electric potentials. Here, we develop an image processing platform enhanced by the physics of the underlying system to track the motion of buckling NEMS structures in the presence of high noise levels. The algorithm is composed of an image filter, two data filters, and a nonlinear regression model, which utilizes the expected form of the physical solution. The method was applied to the recordings of a NEMS beam about 150 nm wide, undergoing intra- and inter-well post-buckling states with a transition rate of approximately 0.5 Hz. The algorithm can track the dynamical motion of the NEMS and capture the dependency of deflection amplitude on the compressive force on the beam. With the help of the proposed algorithm, the transition from inter-well to intra-well motion is clearly resolved for buckling NEMS imaged under SEM. [ABSTRACT FROM AUTHOR]

The correction of chromatic aberration and achievement of high numerical aperture (NA) are two main issues for the realistic application of metalenses in imaging and display systems. In this work, we design a broadband achromatic metalens (BAM) with high NA, which is composed of hybrid all-dielectric meta-atoms in the visible region. By simultaneously and independently manipulating the geometric phase and propagation phase, meta-atoms can focus the incident lights on the same spot. Besides, a large phase compensation can be obtained through the variation in structural parameters of the hybrid meta-atom, which is essential to achieve high-NA BAM. For demonstration, the achromatic metalens with NA of 0.68 over the spectrum from 420 to 700 nm is numerically simulated. The metalens possessing high NA, broad bandwidth, and diffraction-limited achromatic focusing performance can be potentially applied in the field of imaging, spectroscopy, display, etc. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusions The accuracy of proton therapy and preclinical proton irradiation experiments is susceptible to proton range uncertainties, which partly stem from the inaccurate conversion between CT numbers and relative stopping power (RSP). Proton computed tomography (PCT) can reduce these uncertainties by directly acquiring RSP maps.This study aims to develop a novel PCT imaging system based on scintillator‐based proton range detection for accurate RSP reconstruction.The proposed PCT system consists of a pencil‐beam brass collimator with a 1 mm aperture, an object stage capable of translation and 360° rotation, a plastic scintillator for dose‐to‐light conversion, and a complementary metal oxide semiconductor (CMOS) camera for light distribution acquisition. A calibration procedure based on Monte Carlo (MC) simulation was implemented to convert the obtained light ranges into water equivalent ranges. The water equivalent path lengths (WEPLs) of the imaged object were determined by calculating the differences in proton ranges obtained with and without the object in the beam path. To validate the WEPL calculation, measurements of WEPLs for eight tissue‐equivalent inserts were conducted. PCT imaging was performed on a custom‐designed phantom and a mouse, utilizing both 60 and 360 projections. The filtered back projection (FBP) algorithm was employed to reconstruct the RSP from WEPLs. Image quality was assessed based on the reconstructed RSP maps and compared to reference and simulation‐based reconstructions.The differences between the calibrated and reference ranges of 110–150 MeV proton beams were within 0.18 mm. The WEPLs of eight tissue‐equivalent inserts were measured with accuracies better than 1%. Phantom experiments exhibited good agreement with reference and simulation‐based reconstructions, demonstrating average RSP errors of 1.26%, 1.38%, and 0.38% for images reconstructed with 60 projections, 60 projections after penalized weighted least‐squares algorithm denoising, and 360 projections, respectively. Mouse experiments provided clear observations of mouse contours and major tissue types. MC simulation estimated an imaging dose of 3.44 cGy for decent RSP reconstruction.The proposed PCT imaging system enables RSP map acquisition with high accuracy and has the potential to improve dose calculation accuracy in proton therapy and preclinical proton irradiation experiments. [ABSTRACT FROM AUTHOR]

Ultrasound and photoacoustic imaging are important imaging modalities with significant applications in clinical diagnosis and biomedical research. However, current capacitive and piezoelectric ultrasound detectors face challenges related to sensitivity and bandwidth, particularly at higher frequencies. These challenges can hinder their ability to achieve high spatial resolution and deep penetration for imaging purposes. Optical ultrasound sensors offer high sensitivity and show great potential for developing ultrasound/photoacoustic imaging systems. Among all methods of optical ultrasound detection, integrated photonics, with its superior advantages in miniaturization, sensitivity, and integration capability with electronics, could be next‐generation photoacoustic/ultrasound imaging technology. This review explores the device structure designs and applications of ultrasound/photoacoustic sensing based on integrated photonics, analyzes their performance metrics as ultrasound detectors, and discusses some perspectives on future developments and trends in this field. [ABSTRACT FROM AUTHOR]

The timely and accurate acquisition of crop-growth information is a prerequisite for implementing intelligent crop-growth management, and portable multispectral imaging devices offer reliable tools for monitoring field-scale crop growth. To meet the demand for obtaining crop spectra information over a wide band range and to achieve the real-time interpretation of multiple growth characteristics, we developed a novel portable snapshot multispectral imaging crop-growth sensor (PSMICGS) based on the spectral sensing of crop growth. A wide-band co-optical path imaging system utilizing mosaic filter spectroscopy combined with dichroic mirror beam separation is designed to acquire crop spectra information over a wide band range and enhance the device's portability and integration. Additionally, a sensor information and crop growth monitoring model, coupled with a processor system based on an embedded control module, is developed to enable the real-time interpretation of the aboveground biomass (AGB) and leaf area index (LAI) of rice and wheat. Field experiments showed that the prediction models for rice AGB and LAI, constructed using the PSMICGS, had determination coefficients (R²) of 0.7 and root mean square error (RMSE) values of 1.611 t/ha and 1.051, respectively. For wheat, the AGB and LAI prediction models had R² values of 0.72 and 0.76, respectively, and RMSE values of 1.711 t/ha and 0.773, respectively. In summary, this research provides a foundational tool for monitoring field-scale crop growth, which is important for promoting highquality and high-yield crops. [ABSTRACT FROM AUTHOR]

Two ideas, proposed by Thomas Young and James Clerk Maxwell, form the foundations of colour science: (i) three types of retinal receptors encode light under daytime conditions, and (ii) colour matching experiments establish the critical spectral properties of this encoding. Experimental quantification of these ideas is used in international colour standards. However, for many years, the field did not reach consensus on the spectral properties of the biological substrate of colour matching: the spectral sensitivity of the cone fundamentals. By combining auxiliary data (thresholds, inert pigment analyses), complex calculations, and colour matching from genetically analysed dichromats, the human cone fundamentals have now been standardized. Here, we describe a new computational method to estimate the cone fundamentals using only colour matching from the three types of dichromatic observers. We show that it is not necessary to include data from trichromatic observers in the analysis or to know the primary lights used in the matching experiments. Remarkably, it is even possible to estimate the fundamentals by combining data from experiments using different, unknown primaries. We then suggest how the new method may be applied to colour management in modern image systems. [ABSTRACT FROM AUTHOR]

Vertically stacked wavelength modulation bipolar response photodetectors are expected to be applied in various fields because they enable bipolar detection and transmission within one device and do not require harsh operating conditions. However, the as‐reported bipolar devices either need to change the detection mode (flipping the device or applying external bias) or have limited application effects. In this study, a self‐powered FAPbI3/silicon hybrid visible and near‐infrared bipolar response photodetector is reported, and the bipolar response is tuned by controlling the transmittance and interface contact of transparent electrodes. Moreover, unlike for photosensitive layers such as perovskites or organic compounds, the preparation of electrodes does not involve solvents, and array devices with different electrodes can be prepared in microregions without affecting adjacent regions. Then, an encrypted communication system that requires comprehensive consideration of the positive and negative states of different transparent electrode‐based devices caused by 650‐nm visible and 940‐nm near‐infrared transmission signals are designed, increasing the difficulty of decryption. A dual‐band spectral imaging system that does not require additional voltage driving by combining the reflection of visible light and the penetration ability of near‐infrared light is implemented, ensuring miniaturization and high integration of the visual imaging system. [ABSTRACT FROM AUTHOR]

Steganography technology which conceals a message in a carrier to make it invisible is critical for information security. Conventional optical image steganography using diffractive optical components or spatial light modulators suffers from less encoding channel and bulky volume. The emergence of multifunctional metasurface that can manipulate abundant physical dimensions of optical fields allows the multi‐channel image steganography in a compact volume. Here, the image hiding in a metasurface is demonstrated by modulating the amplitude, phase, and polarization states of terahertz (THz) waves completely. Especially, the phase channel can decouple from the amplitude channel based on a Fresnel‐diffraction‐based algorithm. By directly measuring the phase distribution using the homemade THz focal plane imaging system, the number of transmission channels can expand from N to 2N. As a proof of concept, it is shown that the secret images can encode in the phase channel and subsequently extract by using different keys, such as polarization states, detection distances, and its combinations. Moreover, different hiding strategies with different attacker behaviors are also demonstrated. The decoupling of the phase and amplitude channels with a single metasurface may open an avenue toward innovative optoelectronic devices for optical image steganography, data storage, and terahertz communication. [ABSTRACT FROM AUTHOR]

Understanding and preserving the deep sea ecosystems is paramount for marine conservation efforts. Automated object (deep-sea biota) classification can enable the creation of detailed habitat maps that not only aid in biodiversity assessments but also provide essential data to evaluate ecosystem health and resilience. Having a significant source of labelled data helps prevent overfitting and enables training deep learning models with numerous parameters. In this paper, we contribute to the establishment of a significant deep-sea remotely operated vehicle (ROV) image classification dataset with 3994 images featuring deep-sea biota belonging to 33 classes. We manually label the images through rigorous quality control with human-in-the-loop image labelling. Leveraging data from ROV equipped with advanced imaging systems, our study provides results using novel deep-learning models for image classification. We use deep learning models including ResNet, DenseNet, Inception, and Inception-ResNet to benchmark the dataset that features class imbalance with many classes. Our results show that the Inception-ResNet model provides a mean classification accuracy of 65%, with AUC scores exceeding 0.8 for each class. [ABSTRACT FROM AUTHOR]

Background: To analyse and compare the grading of diabetic retinopathy (DR) severity level using standard 35° ETDRS 7-fields photography and CLARUS™ 500 ultra-widefield imaging system. Methods: A cross-sectional analysis of retinal images of patients with type 2 diabetes (n = 160 eyes) was performed for this study. All patients underwent 7-fields colour fundus photography (CFP) at 35° on a standard Topcon TRC-50DX® camera, and ultra-widefield (UWF) imaging at 200° on a CLARUS™ 500 (ZEISS, Dublin, CA, USA) by an automatic montage of two 133° images (nasal and temporal). 35° 7-fields photographs were graded by two graders, according to the Early Treatment Diabetic Retinopathy Study (ETDRS). For CLARUS UWF images, a prototype 7-fields grid was applied using the CLARUS review software, and the same ETDRS grading procedures were performed inside that area only. Grading of DR severity level was compared between these two methods to evaluate the agreement between both imaging techniques. Results: Images of 160 eyes from 83 diabetic patients were considered for analysis. According to the 35° ETDRS 7-fields images, 22 eyes were evaluated as DR severity level 10–20, 64 eyes were evaluated as DR level 35, 41 eyes level 43, 21 eyes level 47, 7 eyes level 53, and 5 eyes level 61. The same DR severity level was achieved with CLARUS 500 UWF images in 92 eyes (57%), showing a perfect agreement (k > 0.80) with the 7-fields 35° technique. Fifty-seven eyes (36%) showed a higher DR level with CLARUS UWF images, mostly due to a better visualization of haemorrhages and a higher detection rate of intraretinal microvascular abnormalities (IRMA). Only 11 eyes (7%) showed a lower severity level with the CLARUS UWF system, due to the presence of artifacts or media opacities that precluded the correct evaluation of DR lesions. Conclusions: UWF CLARUS 500 device showed nearly perfect agreement with standard 35° 7-fields images in all ETDRS severity levels. Moreover, CLARUS images showed an increased ability to detect haemorrhages and IRMA helping with finer evaluation of lesions, thus demonstrating that a UWF photograph can be used to grade ETDRS severity level with a better visualization than the standard 7-fields images. Trial registration: Approved by the AIBILI - Association for Innovation and Biomedical Research on Light and Image Ethics Committee for Health with number CEC/009/17- EYEMARKER. [ABSTRACT FROM AUTHOR]

In a production environment, delayed stress recognition can impact yield. Imaging can rapidly and effectively quantify stress symptoms using indexes such as normalized difference vegetation index (NDVI). Commercial systems are effective but cannot be easily customized for specific applications, particularly post-processing. We developed a low-cost customizable imaging system and validated the code to analyze images. Our objective was to verify the image analysis code and custom system could successfully quantify the changes in plant canopy reflectance. 'Supercascade Red', 'Wave© Purple', and 'Carpet Blue' Petunias (Petunia × hybridia) were transplanted individually and subjected to increasing fertilizer treatments and increasing substrate pH in a greenhouse. Treatments for the first trial were the addition of a controlled release fertilizer at six different rates (0, 0.5, 1, 2, 4, and 8 g/pot), and for the second trial, fertilizer solution with four pHs (4, 5.5, 7, and 8.5), with eight replications with one plant each. Plants were imaged twice a week using a commercial imaging system for fertilizer and thrice a week with the custom system for pH. The collected images were analyzed using an in-house program that calculated the indices for each pixel of the plant area. All cultivars showed a significant effect of fertilizer on the projected canopy size and dry weight of the above-substrate biomass and the fertilizer rate treatments (p < 0.01). Plant tissue nitrogen concentration as a function of the applied fertilizer rate showed a significant positive response for all three cultivars (p < 0.001). We verified that the image analysis code successfully quantified the changes in plant canopy reflectance as induced by increasing fertilizer application rate. There was no relationship between the pH and NDVI values for the cultivars tested (p > 0.05). Manganese and phosphorus had no significance with chlorophyll fluorescence for 'Carpet Blue' and 'Wave© Purple' (p > 0.05), though 'Supercascade Red' was found to have significance (p < 0.01). pH did not affect plant canopy size. Chlorophyll fluorescence pixel intensity against the projected canopy size had no significance except in 'Wave© Purple' (p = 0.005). NDVI as a function of the projected canopy size had no statistical significance. We verified the ability of the imaging system with integrated analysis to quantify nutrient deficiency-induced variability in plant canopies by increasing pH levels. [ABSTRACT FROM AUTHOR]

One of the most advanced and versatile nanoscale diagnostic tools is atomic force microscopy. By enabling advanced imaging techniques, it allows us to determine various assets of a surface, including morphological, electrical, mechanical, magnetic, and thermal properties. Measuring local current flow is one of the very important methods of evaluation for, for instance, photovoltaic materials or semiconductor structures and other nanodevices. Due to contact areas, the current densities can easily reach above 1 kA/m2; therefore, special detection/measurement setups are required. They meet the required measurement range, sensitivity, noise level, and bandwidth at the measurement scale. Also, they prevent the sample from becoming damaged and prevent unwanted tip–sample issues. In this paper, we present three different nanoscale current measurement solutions, supported with test results, proving their performance. [ABSTRACT FROM AUTHOR]

Canopy imaging offers a non-destructive, efficient way to objectively measure canopy size, detect stress symptoms, and assess pigment concentrations. While it is faster and easier than traditional destructive methods, manual image analysis, including segmentation and evaluation, can be time-consuming. To make imaging more widely accessible, it's essential to reduce the cost of imaging systems and automate the analysis process. We developed a low-cost imaging system with automated analysis using an embedded microcomputer equipped with a monochrome camera and a filter for a total hardware cost of ~USD 500. Our imaging system takes images under blue, green, red, and infrared light, as well as chlorophyll fluorescence. The system uses a Python-based program to collect and analyze images automatically. The multi-spectral imaging system separates plants from the background using a chlorophyll fluorescence image, which is also used to quantify canopy size. The system then generates normalized difference vegetation index (NDVI, "greenness") images and histograms, providing quantitative, spatially resolved information. We verified that these indices correlate with leaf chlorophyll content and can easily add other indices by installing light sources with the desired spectrums. The low cost of the system can make this imaging technology widely available. [ABSTRACT FROM AUTHOR]

Traditional near-field synthetic aperture radar (SAR) imaging algorithms reveal target features by exploiting signal amplitude and phase information. However, electromagnetic wave propagation is constrained by short distance. Therefore, the spherical wave approximation needs to be considered. In addition, it is also limited by equipment ambient noise, azimuth-distance coupling, wave scattering, and transmission power. Both the amplitude and phase of the signal suffer from the interference of multiple clutter, so they cannot be effectively utilized. To address these issues, this paper introduces a covering penetration detection system based on an improved Range Migration Algorithm (IMRMA) imaging method. Firstly, the proposed method minimizes interferences from the front end of the system using an optimized window to balance denoising and information preservation. Next, interval non-uniform interpolation, instead of Stolt interpolation decoupling, is employed to reduce the computational overhead significantly. To minimize the effects due to wave scattering and propagation loss, distance information is enhanced using amplitude and phase compensation. This reduces scattering effects and enhances image quality. An experimental system is constructed based on a vector network analyzer (VNA) to image the target. The proposed method takes about half the time of traditional RMA. The PSNR in the chunky bowl experiment is higher than 14 dB, which is higher than all the compared methods in the paper. The test results show that the designed system and the reported method can effectively achieve high-resolution images by strengthening the target intensity and suppressing the environmental artifacts. [ABSTRACT FROM AUTHOR]

Efficient algorithms are being developed to search for strong gravitational lens systems owing to increasing large imaging surveys. Neural networks have been successfully used to discover galaxy-scale lens systems in imaging surveys such as the Kilo Degree Survey, Hyper-Suprime Cam (HSC) Survey, and Dark Energy Survey over the last few years. Thus, it has become imperative to understand how some of these networks compare, their strengths and the role of the training data sets which are essential in supervised learning algorithms used commonly in neural networks. In this work, we present the first-of-its-kind systematic comparison and benchmarking of networks from four teams that have analysed the HSC Survey data. Each team has designed their training samples and developed neural networks independently but coordinated a priori in reserving specific data sets strictly for test purposes. The test sample consists of mock lenses, real (candidate) lenses, and real non-lenses gathered from various sources to benchmark and characterize the performance of each of the network. While each team's network performed much better on their own constructed test samples compared to those from others, all networks performed comparable on the test sample with real (candidate) lenses and non-lenses. We also investigate the impact of swapping the training samples among the teams while retaining the same network architecture. We find that this resulted in improved performance for some networks. These results have direct implications on measures to be taken for lens searches with upcoming imaging surveys such as the Rubin-Legacy Survey of Space and Time, Roman, and Euclid. [ABSTRACT FROM AUTHOR]

Insomnia disorder with objective short sleep duration (ISS) phenotype is a more serious biological subtype than insomnia with objective normal sleep duration (INS) phenotype, and the neuroimaging data is helpful to understand the pathophysiology of the ISS phenotype. This study was to compare the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) between the ISS phenotype and the INS phenotype. In this cross-sectional study, 55 patients with insomnia disorder were recruited, and 22 of them were defined as the ISS phenotype by the objective cardiopulmonary coupling (CPC) technique. The blood oxygen level-dependent (BOLD) sequences of all participants were obtained using the 3.0 T magnetic resonance imaging system. We analyzed and compared the ALFF, ReHo, and FC between the ISS phenotype and the INS phenotype. We also conducted Pearson's correlation analysis between significant neuroimaging biomarkers and the CPC parameters. The differences were not significant in ALFF (P FWE-corr ＞0.05) or ReHo (P FWE-corr ＞0.05) between the ISS phenotype and the INS phenotype. For the FC analysis, the ISS phenotype had a Hub-node of the left inferior occipital gyrus (IOG.L), with significantly decreased connections (p＜0.001) in the bilateral occipital, parietal, and temporal regions. The significant FCs were closely related to sleep parameters. The left inferior occipital gyrus (IOG.L), as a Hub-node with decreased functional connections, may be a potential fMRI-based biomarker of the ISS phenotype. • The ISS phenotype may be characterized by a functional MRI-based biomarker. • The left inferior occipital gyrus (IOG.L) is a Hub-node. • This Hub-node has a number of significantly decreased functional connections. [ABSTRACT FROM AUTHOR]

Toxicology studies in early fish life stages serve an important function in measuring the impact of potentially harmful substances, such as crude oil, on marine life. Morphometric analysis of larvae can reveal the effects of such substances in retarding growth and development. These studies are labor intensive and time consuming, typically resulting in only a small number of samples being considered. An automated system for imaging and measurement of experimental animals, using flow-through imaging and an artificial neural network to allow faster sampling of more individuals, has been described previously and used in toxicity experiments. This study compares the performance of the automated imaging and analysis system with traditional microscopy techniques in measuring biologically relevant endpoints using two oil treatments as positive controls. We demonstrate that while the automated system typically underestimates morphometric measurements relative to analysis of manual microscopy images, it shows similar statistical results to the manual method when comparing treatments across most endpoints. It allows for many more individual specimens to be sampled in a shorter time period, reducing labor requirements and improving statistical power in such studies, and is noninvasive allowing for repeated sampling of the same population. [ABSTRACT FROM AUTHOR]

Objective: Recently, the nuclear area has attracted attention as a morphological parameter to differentiate high‐grade urothelial carcinoma (HGUC) cells from benign reactive cells. The nuclear long diameter (NLD) strongly correlates with the nuclear area and is easy to subjectively estimate. Therefore, this study examined the usefulness of the NLD‐to‐neutrophil diameter ratio for detecting HGUC cells in urine cytology. Methods: This study included 29, 26 and 18 patients with HGUC, glomerular disease and urolithiasis respectively. An image analysis system was used to measure the NLD of HGUC and benign reactive cells (reactive renal tubular cells and reactive urothelial cells) and the neutrophil diameter that appeared in the voided urine in these cases. The NLD index was calculated using the NLD‐to‐neutrophil diameter ratio. We subsequently compared HGUC and benign reactive cells with respect to NLD and NLD indices. In addition, the HGUC cell group and benign reactive cell group were compared by selecting the five cells with the largest NLD and NLD index on each slide. Results: The NLD and NLD indices of HGUC cells were significantly higher than those of benign reactive cells in all cells and in the five cells with the largest NLD and NLD indices. The cut‐off value of the NLD index for detecting HGUC cells was 1.25 in all cells and 1.80 in the five cells with the largest NLD index. Conclusions: The NLD index is a useful parameter that can be introduced into routine microscopic examinations to differentiate HGUC cells from benign reactive cells. [ABSTRACT FROM AUTHOR]

Mutation in oncogene KRas plays a crucial role in the occurrence and progression of numerous malignant tumors. Malignancy involves changes in cell mechanics for extensive cellular deformation during metastatic dissemination. We hypothesize that oncogene KRas mutations are intrinsic to alterations in cellular mechanics that promote malignant tumor generation and progression. Here, we demonstrate the use of optical tweezers coupled with a confocal fluorescence imaging system and gene interference technique to reveal that the mutant KRas protein can be transported between homogeneous and heterogeneous tumor cells by tunneling nanotubes (TNTs), resulting in a significant reduction of membrane tension and acceleration of membrane phospholipid flow in the recipient cells. Simultaneously, the changes in membrane mechanical properties of the tumor cells also enhance the metastatic and invasive ability of the tumors, which further contribute to the deterioration of the tumors. This finding helps to clarify the association between oncogene mutations and changes in the mechanical properties of tumor cells, which provides a theoretical basis for the development of cancer treatment strategies. Here, we present a laser confocal fluorescence system integrated with optical tweezers to observe the transfer of mutant KRasG12D protein from mutant cells to wild-type cells through TNTs. Malignancy involves changes in cell mechanics for extensive cellular deformation during metastatic dissemination. Our results demonstrate a significant decrease in membrane tension and an increase in membrane phospholipid flow in recipient cells. These alterations in mechanical properties augment the migration and invasive capabilities of tumor cells, contributing to tumor malignancy. Our findings propose that cellular mechanical properties could serve as new markers for tumor development, and targeting membrane tension may hold potential as a therapeutic strategy. [Display omitted] [ABSTRACT FROM AUTHOR]

Two-dimensional ultrasound (2D US) is commonly used in clinical settings for its cost-effectiveness and non-invasiveness, but it is limited by spatial orientation and operator dependency. Three-dimensional ultrasound (3D US) overcomes these limitations by adding a third dimension and enhancing integration with other imaging modalities. Advances in deep learning (DL) have further propelled the viability of freehand image-based 3D reconstruction, broadening clinical applications in intraoperative and point-of-care (POC) settings. This review evaluates state-of-the-art freehand 3D US reconstruction methods that eliminate the need for external tracking devices, focusing on experimental setups, data acquisition strategies, and reconstruction methodologies. PubMed, Scopus, and IEEE Xplore were searched for studies since 2014 following the PRISMA guidelines, excluding those using additional imaging or tracking systems other than inertial measurement units (IMUs). Fourteen eligible studies were analyzed, showing a shift from traditional speckle decorrelation towards DL-based methods, particularly convolutional neural networks (CNNs). Variability in datasets and evaluation methods hindered a comprehensive quantitative comparison, but notable accuracy improvements were observed with IMUs and integration of contextual and temporal information within CNNs. These advancements enhance freehand 3D US reconstruction feasibility, though variability limits definitive conclusions about the most effective methods. Future research should focus on improving precision in complex trajectories and adaptability across clinical scenarios. [ABSTRACT FROM AUTHOR]

Digital Surface Model (DSM) generation from high-resolution optical satellite images is an important topic of research in the remote sensing field. In optical satellite imaging systems, the attitude information of the cameras recorded by satellite sensors is often biased, which leads to errors in the Rational Polynomial Camera (RPC) model of satellite imaging. These errors in the RPC model can mislead the DSM generation. To solve the above problems, we propose an automatic DSM generation method from satellite images based on the Double-Penalty bundle adjustment (DPBA) optimization algorithm. In the proposed method, two penalty functions representing the camera's attitude and the spatial 3D points, respectively, are added to the reprojection error model of the traditional bundle adjustment optimization algorithm. Instead of acting on images directly, the penalty functions are used to adjust the reprojection error model and improve the RPC parameters. We evaluate the performance of the proposed method using high-resolution satellite image pairs and multi-date satellite images. Through some experiments, we compare the accuracy and completeness of the DSM generated by the proposed method, the Satellite Stereo Pipeline (S2P) method, and the traditional bundle adjustment (BA) method. Compared to the S2P method, the experiment results of the satellite image pair indicate that the proposed method can significantly improve the accuracy and the completeness of the generated DSM by about 1–5 m and 20%–60% in most cases. Compared to the traditional BA method, the proposed method improves the accuracy and completeness of the generated DSM by about 0.01–0.05 m and 1%–3% in most cases. The experiment results can be a testament to the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper investigates a new vortex wave imaging approach to improve the imaging quality of small metal targets of size less than 1.5 mm. Antennas with different spiral phase plates are designed to efficiently transmit vortex beams with orbital angular momentums (OAMs). By analyzing the OAM spectrum of the target, it was discovered that the predominant reflection contains a particular OAM mode that carries abundant azimuthal information. This can be explained by the OAM selectivity of the target and the guidance of the vortex transmitting beam. A simple reflection vortex imaging system was designed to capture the phase information. Measurement results show that the high image contrast reaches 14.9%, which is twice as high as that of the imaging without OAM. Both of simulations and experiments demonstrate that the vortex phase imaging approach proposed in this paper can effectively improve the imaging quality at 80 GHz. This approach is suitable for other millimeter wave imaging systems and is helpful to improve the resolution in anti-terrorism security checks. [ABSTRACT FROM AUTHOR]

A T/R-R (transmitting receiving-receiving) radar sparse aperture multi-view fusion imaging method based on the complex Bayesian compressed sensing (BCS) algorithm is proposed for the practical imaging of T/R-R configuration radar, taking into account the orbital priors of space targets and the advantages of the dual-rotation inverse synthetic aperture radar (ISAR) imaging system. On the basis of establishing a dual rotation radar fusion imaging modal, the proposed method utilizes Laplace priors to establish a sparse model of the target in the complex domain, improving the sparsity promotion effort of the algorithm and obtaining high-resolution target images. The stimulation experiment resets show that the proposed method can not only achieve multi-view fusion imaging of dual station radar, but also achieve multi-view fusion imaging of dual-station radar with sparse aperture respectively, further expanding the application scenarios and effectively improving azimuth resolution and imaging quality. [ABSTRACT FROM AUTHOR]

Cerebrospinal fluid (CSF) plays a critical role in metabolic waste clearance from the brain, requiring its circulation throughout various brain pathways, including the ventricular system, subarachnoid spaces, para‐arterial spaces, interstitial spaces, and para‐venous spaces. The complexity of CSF circulation has posed a challenge in obtaining noninvasive measurements of CSF dynamics. The assessment of CSF dynamics throughout its various circulatory pathways is possible using diffusion magnetic resonance imaging (MRI) with optimized sensitivity to incoherent water movement across the brain. This review presents an overview of both established and emerging diffusion MRI techniques designed to measure CSF dynamics and their potential clinical applications. The discussion offers insights into the optimization of diffusion MRI acquisition parameters to enhance the sensitivity and specificity of diffusion metrics on underlying CSF dynamics. Lastly, we emphasize the importance of cautious interpretations of diffusion‐based imaging, especially when differentiating between tissue‐ and fluid‐related changes or elucidating structural versus functional alterations. [ABSTRACT FROM AUTHOR]

For secure image communications, the Internet must be shielded against unauthorized acquisition or malevolent access. The need for image encryption methods with enough capacity and good efficiency is growing due to the current situation. The purpose of this research work is to solve the problems in today's communication security using a proposed image encryption algorithm. The proposed image encryption system includes the combination of a chaotic system, compressive sensing and Hyper optimization algorithm. The initial values of chaos are extracted using the SHA512. Discrete Wavelet Transform (DWT) is applied to sparse image pixels. The image is shuffled using a FAN transform with a circular map. Next, the image is divided into blocks to facilitate the application of block compressive sensing that utilized the Hadamard measurement matrix. These blocks are masked as one part to quantify the pixels. The logistic map is improved by a hybrid transform which is the combination of Discrete Cosine Transform, Arnold Transform and Discrete Wavelet Transform (CAW). The image is finally scrambled using a Circular Map with a Hyper Optimization that combines two meta-heuristics algorithms namely GWO and COOT. According to simulation experiment findings and security assessments, the algorithm was extremely resilient to differential, statistical, and interference assaults. Based on the experimental results, it was found that the average rate of PSNR was 33.8189, the rate of entropy was 7.99454, the average rate of SSIM was 0.96144, the rate of UACI was 99.62892 and the average rate of NPCI was 33.50304. The results showed that it is an effective method of encryption and strong enough against various types of attacks. [ABSTRACT FROM AUTHOR]

Parts with a large depth-to-diameter ratio play a critical role in the military, aerospace, and automotive industries. However, accurately measuring their inner surface profile remains challenging owing to the lack of adequate and accurate sensors. We developed a multi-ring structured light system to obtain three-dimensional data of inner contours, such as inner diameters, which are crucial for ensuring component performance and safety. In this study, we proposed three simple yet effective techniques to improve the multi-ring beam structured measurement system. First, we designed a distortion correction method to calibrate the imaging system. Second, a two-step calibration approach was used to calibrate the multi-ring projection. Meanwhile, we benchmarked the effects of different light sources on image speckles. The calibration results demonstrated that the coefficient of determination (R-2) used for line fitting exceeded 0.999. Moreover, the measurement experimental results show that the uncertainty of less than 10 µm and the smallest measurable pipe inner diameter can reach 15 mm, demonstrating that our methods are promising for improving the accuracy of structured light optical sensing systems. This system satisfies the measurement requirements and can be immediately utilized to meet the high demand for inner contour measurements in industrial applications. [ABSTRACT FROM AUTHOR]

Daylight photoluminescence imaging of crystalline silicon photovoltaic modules is demonstrated for modules embedded in rooftop and utility‐scale systems, using inverters to electrically switch the operating point of the array. The method enables rapid and high‐quality luminescence image acquisition during the day, unlocking efficient performance and quality monitoring without the need to connect specific electrical hardware or to make any modifications to the system wiring. The principle of the measurement approach is discussed, and experimental results from a 12‐kWDC residential rooftop system and from a 149 MWDC utility‐scale photovoltaic power plant are presented. Measurements were performed using commercial inverters without modifications to the inverter hardware or firmware. In the case of the utility‐scale power plant, the daylight photoluminescence image acquisition of modules connected to a central inverter was obtained from a remote piloted aircraft. Data analysis includes the conversion of photoluminescence image data into implied voltage differences. [ABSTRACT FROM AUTHOR]

Diffractive optical elements (DOEs) represent a revolutionary advancement in modern optics, offering unparalleled versatility and efficiency in various applications. Their significance lies in their ability to manipulate light waves with intricate patterns, enabling functionalities beyond what traditional refractive optics can achieve. DOEs find widespread use in fields such as laser beam shaping, holography, optical communications, and imaging systems. By precisely controlling the phase and amplitude of light, DOEs can generate complex optical structures, correct aberrations, and enhance the performance of optical systems. Moreover, their compact size, lightweight nature, and potential for mass production make them indispensable in designing compact and efficient optical devices for diverse industrial and scientific applications. From improving the performance of laser systems to enabling innovative display technologies, DOEs continue to drive advancements in modern optics, promising even more exciting possibilities in the future. In this review, the critical importance of DOEs is illuminated and explore their profound implications in the contemporary era. [ABSTRACT FROM AUTHOR]

Imaging technology based on detecting individual photons has seen tremendous progress in recent years, with broad applications in autonomous driving, biomedical imaging, astronomical observation, and more. Comparing with conventional methods, however, it takes much longer time and relies on sparse and noisy photon-counting data to form an image. Here we introduce Physics-Informed Masked Autoencoder (PI-MAE) as a fast and efficient approach for data acquisition and image reconstruction through hardware implementation of the MAE (Masked Autoencoder). We examine its performance on a single-photon LiDAR system when trained on digitally masked MNIST data. Our results show that, with 1.8 × 10 - 6 or less detected photons per pulse and down to 9 detected photons per pixel, it achieves high-quality image reconstruction on unseen object classes with 90% physical masking. Our results highlight PI-MAE as a viable hardware accelerator for significantly improving the performance of single-photon imaging systems in photon-starving applications. [ABSTRACT FROM AUTHOR]

Age-related macular degeneration (AMD) is a leading cause of blindness. It is associated with peripheral drusen which has not been categorized. We investigated peripheral drusen to validate an image grading system and to understand possible associations between peripheral drusen and AMD. We collated clinical data, ultra-widefield (UWF) pseudocolor fundus images and Spectral-Domain Optical Coherence Tomography (SD-OCT) scans from consecutive retinal patients. SD-OCT scans were used to determine AMD stage. A masked retinal specialist recorded the types of peripheral drusen observed in UWF images. Eyes whose UWF images did not pass quality screening and those without AMD and peripheral drusen were excluded from the study. Statistical tests were utilized to determine the validity of our grading system and associations of peripheral drusen with AMD. A total of 481 eyes (283 subjects) were included in the study (mean age 73.1 ± 1.2years, 64.3% female). Interobserver and test–retest statistical analyses to evaluate the UWF image grading system resulted in Cohen's Kappa 0.649 (p < 0.001) and 0.922 (p < 0.001) respectively. A total of 284 (59.0%), 28 (5.8%), 15 (3.1%), 22 (4.6%), 4 (0.8%), 39 (8.1%), and 32 (6.7%) eyes had hard, soft, reticular, cuticular, atrophic, mixed drusen, and mixed drusen and atrophy respectively in at least one peripheral retinal quadrant. Hard peripheral drusen was significantly associated with the presence of AMD (p = 0.010). Peripheral drusen types were variably seen in retinal patients with and without AMD. We validated a peripheral drusen grading system and provided an image library to assist in the identification of peripheral drusen. Our study found an association between peripheral hard drusen and an AMD diagnosis but did not find a link between peripheral drusen and severity of AMD. [ABSTRACT FROM AUTHOR]

CRISPR‐based genomic‐imaging systems have been utilized for spatiotemporal imaging of the repetitive genomic loci in living cells, but they are still challenged by limited signal‐to‐noise ratio (SNR) at a non‐repetitive genomic locus. Here, an efficient genomic‐imaging system is proposed, termed CRISPR/Pepper‐tDeg, by engineering the CRISPR sgRNA scaffolds with the degron‐binding Pepper aptamers for binding fluorogenic proteins fused with Tat peptide derived degron domain (tDeg). The target‐dependent stability switches of both sgRNA and fluorogenic protein allow this system to image repetitive telomeres sensitively with a 5‐fold higher SNR than conventional CRISPR/MS2‐MCP system using "always‐on" fluorescent protein tag. Subsequently, CRISPR/Pepper‐tDeg is applied to simultaneously label and track two different genomic loci, telomeres and centromeres, in living cells by combining two systems. Given a further improved SNR by the split fluorescent protein design, CRISPR/Pepper‐tDeg system is extended to non‐repetitive sequence imaging using only one sgRNA with two aptamer insertions. Neither complex sgRNA design nor difficult plasmid construction is required, greatly reducing the technical barriers to define spatiotemporal organization and dynamics of both repetitive and non‐repetitive genomic loci in living cells, and thus demonstrating the large application potential of this genomic‐imaging system in biological research, clinical diagnosis and therapy. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the feasibility of a time-resolved reflectance imaging system employing a single photodetector to assess the activity of caries lesions that exploits the differential absorption of water at 1300 and 1950 nm. The time-resolved reflectivity of 10 active and 10 arrested lesions on the proximal surfaces and 5 active and 5 arrested lesions on the occlusal surfaces of extracted teeth were monitored simultaneously at 1300 and 1950 nm during forced air drying for 60 s. The presence of a highly mineralized surface zone measured with microcomputed tomography (microCT) was used to indicate lesion activity. Multiple kinetic parameters were extracted from the acquired short wavelength infrared (SWIR) intensity versus time dehydration curves and used to assess lesion activity. Differences in the reflectivity between curves acquired at 1300 and 1950 nm due to differential absorption of water provided improved discrimination between active and arrested lesions over the use of 1950 nm alone. This study demonstrates that it is feasible to use a device with a single photodetector operating at 1950 nm to collect dehydration curves for the assessment of lesion activity and that a system employing two SWIR wavelengths with differential water absorption can improve the performance of lesion activity assessment. [ABSTRACT FROM AUTHOR]

This paper introduces a novel Fast Visually Meaningful Image Encryption based on Compressive Sensing and Joint Diffusion and Scrambling (FVMIECJ). Our approach leverages several innovative aspects: First, we employ a novel seven-dimensional (7D) hyper-chaotic system to generate the measurement matrix for Compressive Sensing (CS) and the random sequences essential for subsequent encryption operations. Utilizing this 7D hyper-chaotic system enhances the randomness and security of the image encryption process. Second, we propose a novel joint diffusion and scrambling encryption scheme to improve the security performance of the algorithm further. This algorithm combines different cryptographic techniques to provide robust protection against attacks. Finally, we present an efficient visual image encryption framework for high-speed encryption applications. This framework ensures robust security and delivers exceptional encryption speed, making it suitable for scenarios where fast encryption is required. Through simulations and comparative analysis, FVMIECJ demonstrated outstanding performance in terms of security and speed, making it a promising solution for image encryption applications. [ABSTRACT FROM AUTHOR]

Metal halide perovskites have attracted significant attention for high‐performance and cost‐effective photodetector (PD) arrays in recent years. Traditional perovskite photodetector arrays typically rely on planar structure and photolithography, which limit resolution and involve complex, costly processes. To address these challenges, an innovative, lithography‐free fabrication strategy is proposed utilizing direct laser writing ablation and a surface energy‐assisted selective growth process. A 10 × 10 self‐powered perovskite photodetector array is demonstrated with a vertical cross‐bar structure fabricated on a laser‐ablated textured Indium‐Tin Oxide (ITO) substrate which improves the device performance. The device exhibits a fast photoresponse and effective imaging capability. Moreover, the intrinsic physical disorder and randomness of perovskite provide highly secure entropy sources, making the photodetector array suitable for physical unclonable function (PUF) devices. This method offers a promising opportunity for simplifying the fabrication process, enhancing manufacturability, and advancing the application of perovskite PD arrays in secure imaging systems. [ABSTRACT FROM AUTHOR]

To investigate the diagnostic value of CEUS combined with C-TIRADS for indeterminate FNA cytological thyroid nodules.The clinical data, ultrasonic images, C-TIRADS categories and CEUS images of 192 patients with indeterminate FNA cytological thyroid nodules confirmed by the surgical pathology were analyzed retrospectively. The diagnostic efficacy of CEUS, C-TIRADS and CEUS-TIRADS were calculated.The AUCs of CEUS, C-TIRADS and CEUS-TIRADS were 0.905 (95% CI: 0.862∼0.949), 0.881 (95% CI: 0.825∼0.938) and 0.954 (95% CI: 0.922∼0.986), respectively. The sensitivity, specificity, PPV, NPV, accuracy, LR– and LR+ were 84.7% (116/137), 85.5% (47/55), 93.5% (116/124), 69.1% (47/68), 84.9% (163/192), 0.179, 5.82 and 84.7% (116/137), 83.6% (46/55), 92.8% (116/125), 68.7% (46/67), 84.4% (162/192), 0.183, 5.17, 92.7% (127/137), 89.1% (49/55), 95.5% (127/133), 83.1% (49/59), 91.7% (176/192), 0.082, and 8.50, respectively. Compared with CEUS and C-TIRADS, CEUS-TIRADS had improved the AUC, sensitivity and accuracy (all P < 0.05).CEUS and C-TIRADS had high diagnostic values in indeterminate FNA cytological thyroid nodules. CEUS-TIRADS improved AUC, diagnostic sensitivity and accuracy, and helped to distinguish indeterminate FNA cytological nodules. [ABSTRACT FROM AUTHOR]

In view of the special engineering properties of red clay and the waste of phosphogypsum resources, the expansion and contraction deformation and fissure evolution of phosphogypsum stabilized red clay under different conditions were investigated by laboratory tests and image processing system. The research results show that: (1) the absolute expansion and absolute shrinkage of phosphogypsum stabilized red clay are positively correlated with the compaction degree, the number of dry and wet cycles and the cement dosage, and negatively correlated with the initial water content and the phosphogypsum dosage; (2) the fissure rate increases with the increase of the number of dry and wet cycles, and decreases with the increase of the initial water content, the compaction degree, the cement, and the phosphogypsum dosage; (3) The relationship among absolute expansion rate (absolute shrinkage), degree of compaction and fracture rate can be fitted by the equation f(x,y) = ax+by+cx2+dy2+e; (4) Phosphogypsum has an obvious inhibiting effect on the expansion, shrinkage and cracking of the mix. It is recommended that the cement mixing amount of 6% and phosphogypsum: red clay = 1:1~1:2 as roadbed filler. [ABSTRACT FROM AUTHOR]

We report here on the characterisation in mice of a noninvasive bacille Calmette-Guérin (BCG) skin challenge model for assessing tuberculosis (TB) vaccine efficacy. Controlled human infection models (CHIMs) are valuable tools for assessing the relevant biological activity of vaccine candidates, with the potential to accelerate TB vaccine development into the clinic. TB infection poses significant constraints on the design of a CHIM using the causative agent Mycobacterium tuberculosis (Mtb). A safer alternative is a challenge model using the attenuated vaccine agent Mycobacterium bovis BCG as a surrogate for Mtb, and intradermal (skin) challenge as an alternative to pulmonary infection. We have developed a unique noninvasive imaging system based on fluorescent reporters (FluorBCG) to quantitatively measure bacterial load over time, thereby determining a relevant biological vaccine effect. We assessed the utility of this model to measure the effectiveness of 2 TB vaccines: the currently licenced BCG and a novel subunit vaccine candidate. To assess the efficacy of the skin challenge model, a nonlinear mixed effect model was built describing the decline of fluorescence over time. The model-based analysis identified that BCG vaccination reduced the fluorescence readout of both fluorophores compared to unvaccinated mice (p < 0.001). However, vaccination with the novel subunit candidate did not alter the fluorescence decline compared to unvaccinated mice (p > 0.05). BCG-vaccinated mice that showed the reduced fluorescent readout also had a reduced bacterial burden in the lungs when challenged with Mtb. This supports the fluorescence activity in the skin as a reflection of vaccine induced functional pulmonary immune responses. This novel noninvasive approach allows for repeated measurements from the challenge site, providing a dynamic readout of vaccine induced responses over time. This BCG skin challenge model represents an important contribution to the ongoing development of controlled challenge models for TB. We need better models to assess the efficacy of early tuberculosis vaccine candidates and prioritise some for larger scale trials. This study introduces a novel non-invasive skin challenge model using a fluorescent BCG reporter strain that enables measuring of vaccine-induced immune responses. [ABSTRACT FROM AUTHOR]

The effective restoration of degraded remote sensing images is one of the major concerns as it directly affects imaging system performance. In recent years, investigators have developed innumerable systems and methods for remotely sensed hazy or blurred image restoration to enhance the system's performance. However, the existing remotely sensed image restoration system and methods still have untold limitations such as texture degradation, high computational complexity, preparative parametric tunning, more time consumption in restoration procedure, lesser accuracy, and many more. Hence, effective and fast restoration of the degraded remote sensing images with more accuracy is still a challenging problem, which requires enormous attention toward a novel image restoration approach. In this work, the researchers implement a remote sensing image restoration framework namely IMU-CNN, which is based on mask-upgraded cascade R-CNN and deep autoencoder. Our proposed IMU-CNN model performs hazy or blurred remotely sensed image restoration in a faster manner with improved accuracy, as well as saves time in the image restoration process, significantly. The outcome of the proposed image restoration framework is found improved and optimal and measured accuracy, precision, F1 score, and Recall is 99.59%, 97.24%, 97.69%, and 96.49%, respectively. Recently, researchers have conducted much investigation on remotely sensed image restoration systems by using various hybrid approaches. However, still, there is a need for further investigation in the future for building sophisticated and less computationally complex systems for effective remotely sensed image restoration in less time. [ABSTRACT FROM AUTHOR]

(1) Background: Yield-monitoring systems are widely used in grain crops but are less advanced for hay and forage. Current commercial systems are generally limited to weighing individual bales, limiting the spatial resolution of maps of hay yield. This study evaluated an Uncrewed Aerial Vehicle (UAV)-based imaging system to estimate hay yield. (2) Methods: Data were collected from three 0.4 ha plots and a 35 ha hay field of red clover and timothy grass in September 2020. A multispectral camera on the UAV captured images at 30 m (20 mm pixel−1) and 50 m (35 mm pixel−1) heights. Eleven Vegetation Indices (VIs) and five texture features were calculated from the images to estimate biomass yield. Multivariate regression models (VIs and texture features vs. biomass) were evaluated. (3) Results: Model R2 values ranged from 0.31 to 0.68. (4) Conclusions: Despite strong correlations between standard VIs and biomass, challenges such as variable image resolution and clarity affected accuracy. Further research is needed before UAV-based yield estimation can provide accurate, high-resolution hay yield maps. [ABSTRACT FROM AUTHOR]

The objective of the proposed research is to develop plasma soft X-ray (SXR) radiation imaging that includes spectral information in addition to standard SXR tomography for the purpose of studying, for example, tungsten transport and its interplay with magnetohydrodynamics (MHD) in tokamak plasmas in an ITER-relevant approach. The SXR radiation provides valuable information about both aspects, particularly when measured with high spatial and temporal resolution and when tomographic reconstructions are performed. The spectral data will facilitate the tracking of both light and high-Z impurities. This approach is pertinent to both the advancement of a detailed understanding of physics and the real-time control of plasma, thereby preventing radiative collapses. The significance of this development lies in its ability to provide three-dimensional plasma tomography, a capability that extends beyond the scope of conventional tomography. The utilization of two-dimensional imaging capabilities inherent to Gas Electron Multiplier (GEM) detectors in a toroidal view, in conjunction with the conventional poloidal tomography, allows for the acquisition of three-dimensional information, which should facilitate the study of, for instance, the interplay between impurities and MHD activities. Furthermore, this provides a valuable opportunity to investigate the azimuthal asymmetry of tokamak plasmas, a topic that has rarely been researched. The insights gained from this research could prove invaluable in understanding other toroidal magnetically confined plasmas, such as stellarators, where comprehensive three-dimensional measurements are essential. To illustrate, by attempting to gain access to anisotropic radiation triggered by magnetic reconnection or massive gas injections, such diagnostics will provide the community with enhanced experimental tools to understand runaway electrons (energy distribution and spatial localization) and magnetic reconnection (spatial localization, speed...). This work forms part of the optimization studies of a detecting unit proposed for use in such a diagnostic system, based on GEM technology. The detector is currently under development with the objective of achieving the best spatial resolution feasible with this technology (down to approximately 100 µm). The diagnostic design focuses on the monitoring of photons within the 2–15 keV range. The findings of the optimization studies conducted on the amplification stage of the detector, particularly with regard to the geometrical configuration of the GEM foils, are presented herein. The impact of hole shape and spacing in the amplifying foils on the detector parameters, including the spatial size of the avalanches and the electron gain/multiplication, has been subjected to comprehensive numerical analysis through the utilization of Degrad (v. 3.13) and Garfield++ (v. bd8abc76) software. The results obtained led to the identification of two configurations as the most optimal geometrical configurations of the amplifying foil for the three-foil GEM system for the designed detector. The first configuration comprises cylindrical holes with a diameter of 70 μm, while the second configuration comprises biconical holes with diameters of 70/50/70 μm. Both configurations had a hole spacing of 120 μm. [ABSTRACT FROM AUTHOR]

Background/Objectives: Radiography is an essential and low-cost diagnostic method in pulmonary medicine that is used for the early detection and monitoring of lung diseases. An adequate and consistent image quality (IQ) is crucial to ensure accurate diagnosis and effective patient management. This pilot study evaluates the feasibility and effectiveness of the International Atomic Energy Agency (IAEA)'s remote and automated quality control (QC) methodology, which has been tested in multiple imaging centers. Methods: The data, collected between April and December 2022, included 47 longitudinal data sets from 22 digital radiographic units. Participants submitted metadata on the radiography setup, exposure parameters, and imaging modes. The database comprised 968 exposures, each representing multiple image quality parameters and metadata of image acquisition parameters. Python scripts were developed to collate, analyze, and visualize image quality data. Results: The pilot survey identified several critical issues affecting the future implementation of the IAEA method, as follows: (1) difficulty in accessing raw images due to manufacturer restrictions, (2) variability in IQ parameters even among identical X-ray systems and image acquisitions, (3) inconsistencies in phantom construction affecting IQ values, (4) vendor-dependent DICOM tag reporting, and (5) large variability in SNR values compared to other IQ metrics, making SNR less reliable for image quality assessment. Conclusions: Cross-comparisons among radiography systems must be taken with cautious because of the dependence on phantom construction and acquisition mode variations. Awareness of these factors will generate reliable and standardized quality control programs, which are crucial for accurate and fair evaluations, especially in high-frequency chest imaging. [ABSTRACT FROM AUTHOR]

Medication-Related Osteonecrosis of the Jaw (MRONJ) is characterized by bone exposure in the oral and maxillofacial region for more than eight weeks in patients treated with anti-resorptive agents, immunosuppressants, or anti-angiogenic agents, without prior radiation therapy or metastatic disease to the jaws. Conservative treatments can control infection in mild cases, but surgical intervention is necessary for patients with severe symptoms. A 78-year-old female with a history of bisphosphonate treatment for osteoporosis presented with persistent pain, swelling, and malodor following implant placement in the upper right maxilla. SPECT/CT imaging revealed a high-risk hot spot in the right maxillary region. BIS-guided surgery using the Qray pen-C was performed, selectively removing red fluorescent bone tissue. The defect was grafted with HuBT incorporated with rhBMP-2. Postoperative follow-ups at 4, 7, and 14 months showed successful bone healing, transforming into a corticocancellous complex, and implant placement without MRONJ recurrence. Allogeneic demineralized dentin matrix (DDM) incorporated with rhBMP-2 demonstrates effective bone healing and implant placement following BIS-guided MRONJ surgery. This case supports the use of DDM/rhBMP-2 for tissue regeneration in MRONJ treatment, enabling successful prosthetic restoration without recurrence. [ABSTRACT FROM AUTHOR]

Most image quality assessment (IQA) algorithms based on sparse representation primarily focus on amplitude information, often overlooking the structural composition of images. However, structural composition is closely linked to perceived image quality, a connection that existing methods do not adequately address. To fill this gap, this paper proposes a novel distorted-image quality assessment algorithm based on a sparse structure and subjective perception (IQA-SSSP). This algorithm evaluates the quality of distorted images by measuring the sparse structure similarity between a reference and distorted images. The proposed method has several advantages. First, the sparse structure algorithm operates with reduced computational complexity, leading to faster processing speeds, which makes it suitable for practical applications. Additionally, it efficiently handles large-scale data, further enhancing the assessment process. Experimental results validate the effectiveness of the algorithm, showing that it achieves a high correlation with human visual perception, as reflected in both objective and subjective evaluations. Specifically, the algorithm yielded a Pearson correlation coefficient of 0.929 and a mean squared error of 8.003, demonstrating its robustness and efficiency. By addressing the limitations of existing IQA methods and introducing a more holistic approach, this paper offers new perspectives on IQA. The proposed algorithm not only provides reliable quality assessment results but also closely aligns with human visual experience, thereby enhancing both the objectivity and accuracy of image quality evaluations. This research offers significant theoretical support for the advancement of sparse representation in IQA. [ABSTRACT FROM AUTHOR]

Infrared upconversion devices (UCDs) enable NIR imaging without array and readout circuits, making them desirable for portable sensor, imaging and monitoring. However, the exorbitant cost and difficulties in fabrication associated with vacuum‐deposited materials, which are usually employed in high‐performance UCDs, restrict their application in flexible‐stretchable systems. Here, a solution‐processed upconversion device (s‐UCD), which is composed of detector and emitter, with high conversion efficiency and low turn‐on voltage achieved by device structure design and interlayer engineering is reported. The role of the electron blocking layer is investigated in s‐UCDs, and a peak luminance of 5,500 cd m−2 @7 V and a luminance on‐off ratio of 110000 @5.25 V are achieved. The s‐UCDs exhibit high resolution, microsecond response time and are compatible with flexible substrates. With the high‐performance large‐area s‐UCDs, direct non‐invasive transmission‐based bioimaging applications with high quality of bioimaging are further performed. It is believed that the s‐UCD imaging system offers potential applications for portable low‐cost non‐invasive tissue analysis, disease diagnosis, and virtual reality. [ABSTRACT FROM AUTHOR]

(1) Background: Mild cognitive impairment (MCI) due to Alzheimer's disease (AD) progresses to dementia at a higher annual rate, while other MCIs may remain stable or even improve over time. Discriminating progressive from non-progressive cases of MCI is crucial and challenging. (2) Methods: A retrospective study of individuals with MCI was conducted at a university hospital located in southern Taiwan. The researchers collected demographic data, comorbidities, the scores of cognitive tests, three easy Z-score imaging system (eZIS) indicators (severity, extent, and ratio), Fazekas scale scores, mesial temporal atrophy (MTA) scores, clinical outcomes including deterioration of Cognitive Abilities Screening Instrument, Mini-mental State Examination, Clinical Dementia Rating Sum of Box scores, and the conversion from MCI to dementia. Those who converted to dementia in three years and non-converters were compared by the three eZIS indicators to test the predictive utility, and the clinical outcomes were evaluated by regression and ROC curve analysis. (3) Results: The three eZIS indicators were significantly higher in the group of progressive MCI than in stable MCI. eZIS severity is positively correlated with a deterioration in the scores of the Cognitive Abilities Screening Instrument and Clinical Dementia Rating Sum of Box. eZIS severity is also positively correlated with conversion from MCI to dementia. The AUC for severity is 0.719, and the optimal cutoff value of severity for predicting conversion is 1.22. (4) Conclusions: During three years of follow-up, MCI individuals with greater eZIS severity were significantly associated with worse cognitive assessment scores and a higher conversion rate to dementia. [ABSTRACT FROM AUTHOR]

Nonlinear optical methods based on second harmonic generation have been widely used to observe ferroelectric domain structures. However, most previous methods have some flaws, such as limitations in structure patterns and time-consuming scanning processes. We have developed a technique called nonlinear spiral interferometry to observe domain walls, which avoids these problems. By placing a spiral phase plate on the rear focal plane of the imaging system, the intensity of the second harmonic wave can be concentrated at 180° domain walls, while regions with homogeneous polarization appear as a dark field. This phenomenon originates from the interference of point spread functions with spiral phase, and the principle is applicable to samples with any polarized pattern. Using this method, disturbing miscellaneous peaks can be suppressed, and imaging contrast is improved due to the redistribution of energy. This technique is verified through theoretical calculations and experiments, providing an effective and convenient way to observe domain structures. [ABSTRACT FROM AUTHOR]