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Due to the wide application of image information transmission technology, people have higher requirement for the security of image transmission. Aiming at the problem that the previous encryption scheme uses a single key to encrypt the image information, and the key leakage will directly lead to the theft of the image information, an image encryption scheme combining optical chaos and elliptic curve encryption algorithm is proposed. The external key input by the user and the hash function of the plaintext image jointly generate the control parameters required for image encryption and encrypt the plaintext image together with the optical chaotic sequence. The control parameters are encrypted by the public key of the elliptic curve encryption algorithm and transmitted to the receiver. Only by combining the decrypted control parameters with the optical chaotic sequence synchronized at the receiver to generate the decryption sequence of each stage, the image can be restored. When the optical chaotic sequence is generated, the binary sequence generated by the control parameters will be used to encrypt the optical chaotic sequence, so that the optical chaotic sequence can be double encrypted at the physical layer and the application layer, and it is difficult to decipher the physical parameters of the laser and improve the security of encryption. The experimental simulation results show that the key space of the encryption scheme is greater than 2100, the information entropy is close to the theoretical maximum value of 8, the Number of Pixels Change Rate, and the Unified Average Changing Intensity are close to the theoretical value of 99.6094% and 33.4635%, respectively. And it has good robustness to various typical attacks. [ABSTRACT FROM AUTHOR]

The results of a study of nitrogen-containing active regions based on superlattices grown on GaAs substrates are presented. Active regions based on alternating InAs and GaAsN layers were fabricated by molecular-beam epitaxy using a nitrogen plasma source. Based on the XRD analysis, the thicknesses and average composition of superlattice layers are estimated. The study of dark-field images obtained by transmission electron microscopy showed the presence of interdiffusion of InAs into GaAsN. The results of a study of the photoluminescence and electroluminescence spectra at different pump levels are presented. Efficient electroluminescence is demonstrated near 1150 nm with a full width at half-maximum of about ~90 meV. [ABSTRACT FROM AUTHOR]

To improve the work efficiency of on-site inspection personnel in diagnosing faults of power transmission lines, in this paper we propose an infrared image segmentation method based on DeepLabV3+ for identifying key components of transmission line. We collected 556 infrared images of transmission lines in our own power supply system, and expanded the original data by data augmentation method. Based on the comparison of the DeepLabV3+ model with three different backbone networks, MobileNetV2 with the best performance is selected as the main backbone network. Compared with FCN, U-Net, and SegNet, the test results show that DeepLabV3+ using MobileNetV2 (compared with ResNet50 and Xception) can segment the five types of key components in power transmission lines from infrared images more accurately and faster. The MIoU on the test set is 0.8624, which is better than the performance of FCN, U-Net, and SegNet. This lays a foundation for improving the work efficiency of on-site inspection personnel and improving the continuous power supply capacity, stability, and safe operation level of the power grid. [ABSTRACT FROM AUTHOR]

The rapid development of IOT and the ease of capturing and transmitting digital images have increased the demand for image encryption. Despite the availability of various encryption methods, chaos-based image encryption is the most suitable method for image applications due to its sensitivity to initial conditions and control parameters. Many image encryption schemes have been developed to enhance the security of images by using chaotic maps, but they cannot combat all possible threats from the cryptanalysis community. This study presents a new chaosbased substitution box (S-box) and its application for securing images. The construction of the presented S-box approach is based on a new five-dimensional hyper-chaotic system, and the experimental results prove that the suggested S-box approach has high nonlinearity and good cryptographic characteristics. In addition, we utilize the effectiveness of the presented S-box approach in designing a novel lightweight image encryption/decryption scheme. Results demonstrate that this scheme has a sufficient peak signal-to-noise ratio, a low correlation, and a large key space. These factors make it more efficient than its classical counterpart and allow it to resist statistical and differential attacks. The number of changing pixel rate (NPCR) and the unified averaged changed intensity (UACI) values were 99.623 and 33.532, respectively. The entropy oscillates from 7.9965 to 7.9971 for the tested encrypted images. These criteria indicate an efficient, fast, and robust scheme that can be used for secure image transmission via public channels. [ABSTRACT FROM AUTHOR]

Digital image processing has a wide range of uses, including robotics and automated inspection of industrial parts. Other uses include remote sensing using satellites and other spacecraft, image transmission and storage for business applications, medical processing, and Acoustic image processing. The process of highlighting particular intriguing features in a hidden image is known as image enhancement. We can accomplish this by altering the brightness, contrast, etc. The generated output is more suitable than the original image for some particular purposes. The proposed algorithm which is based on the convolution of coefficient bounds of a subclass p - Υ S ∗ (t , δ , μ) obtained using Mittag-Leffler type Poisson Distribution is tested on three image data sets with different dimensions and image formats (PNG, JPEG, TIFF, etc.) and its PSNR, SSIM, MSE, RMSE, PCC and MAE values are observed to check the quality of the enhanced images. [ABSTRACT FROM AUTHOR]

Background: Heavy ion irradiation (IR) with high-linear energy transfer (LET) is characterized by a unique depth dose distribution and increased biological effectiveness. Following high-LET IR, localized energy deposition along the particle trajectories induces clustered DNA lesions, leading to low electron density domains (LEDDs). To investigate the spatiotemporal dynamics of DNA repair and chromatin remodeling, we established the automated image analysis of transmission electron micrographs. Methods: Human fibroblasts were irradiated with high-LET carbon ions or low-LET photons. At 0.1 h, 0.5 h, 5 h, and 24 h post-IR, nanoparticle-labeled repair factors (53BP1, pKu70, pKu80, DNA-PKcs) were visualized using transmission electron microscopy in interphase nuclei to monitor the formation and repair of DNA damage in the chromatin ultrastructure. Using AI-based software tools, advanced image analysis techniques were established to assess the DNA damage pattern following low-LET versus high-LET IR. Results: Low-LET IR induced single DNA lesions throughout the nucleus, and most DNA double-strand breaks (DSBs) were efficiently rejoined with no visible chromatin decondensation. High-LET IR induced clustered DNA damage concentrated along the particle trajectories, resulting in circumscribed LEDDs. Automated image analysis was used to determine the exact number of differently sized nanoparticles, their distance from one another, and their precise location within the micrographs (based on size, shape, and density). Chromatin densities were determined from grayscale features, and nanoparticles were automatically assigned to euchromatin or heterochromatin. High-LET IR-induced LEDDs were delineated using automated segmentation, and the spatial distribution of nanoparticles in relation to segmented LEDDs was determined. Conclusions: The results of our image analysis suggest that high-LET IR induces chromatin relaxation along particle trajectories, enabling the critical repair of successive DNA damage. Following exposure to different radiation qualities, automated image analysis of nanoparticle-labeled DNA repair proteins in the chromatin ultrastructure enables precise characterization of specific DNA damage patterns. [ABSTRACT FROM AUTHOR]

The design of the heterostructure of a 2.5 THz range quantum-cascade detector is proposed and heterostructure is grown by molecular-beam epitaxy technique. To optimize the thicknesses of the layers of the heterostructure cascades, a numerical method for iterative solution of the Schrödinger–Poisson equation in the kp formalism was used. The grown heterostructure of the quantum-cascade detector showed a high structural perfection, confirmed by the small values of the average FWHM of the high-order satellite peaks on the X-ray diffraction rocking curves, which were (8.3 ± 0. 5)n. Analysis of dark-field images obtained by transmission electron microscopy showed that the total thickness of the layers in the cascade is 137.3 ± 6.9 nm, which corresponds to the calculated thickness of the layers in the cascade of the heterostructure of the quantum-cascade detector. [ABSTRACT FROM AUTHOR]

This review paper delves into the challenges and opportunities associated with multimedia transmission in vehicular ad hoc networks (VANETs), with a particular focus on audio-visual transmission using IEEE 802.11p. The currently deployed message dictionaries for VANETs only allow for textual exchange. By examining current research in the field of multimedia transmission within transportation systems, we explore the technical issues, challenges, and opportunities involved in transmitting audio-visual-enhanced emergency notifications to transportation users. Additionally, we shed light on the challenges related to video transmission in VANETs and propose focused research areas where Artificial Intelligence can be applied to address the bandwidth constraints imposed by devices. This work makes three significant contributions. Firstly, it presents a detailed comparison between video and image transmission, highlighting their respective strengths and limitations. Secondly, it identifies and discusses the challenges associated with multimedia transmission, emphasizing the need for quality of service and resource availability. Lastly, it examines the opportunities for using intelligence at the edge for transmitting short clips of audio-visual emergency notifications within VANETs to support new services that can coexist with the currently deployed message dictionaries. [ABSTRACT FROM AUTHOR]

In order to obtain high precision image identification results of transmission line ice thickness, an image identification method of transmission line ice thickness based on visual sensing was proposed. The ice-covered images of transmission lines are collected by visual sensors, and we take the non-local self-similarity information of the images as a regularized prior constraint term, which is combined with K-SVD algorithm to establish an image denoising model to remove the noise in the images. The ice-covered regions of transmission lines are segmented in the image and the edge features of ice-covered regions are extracted; we can calculate Ice thickness based on regional pixels, and finally realized the image identification of transmission line ice thickness. After experimental testing, it has been proven that the signal-to-noise ratio of the denoised image using the proposed method is higher than 3.76 dB, which can effectively extract the grayscale features of the icing on the transmission line and obtain accurate identification results of the icing thickness. The deviation between the calculated icing thickness and the actual value is less than 0.05 mm, and the accuracy of icing thickness identification is high, which has strong engineering application value. [ABSTRACT FROM AUTHOR]

Bragg edge imaging using pulsed neutrons is a non-destructive technique for studying microstructure and texture of materials. It provides two-dimensional visualization of crystallographic information using a pixelated gas electron multiplier detector and a time-of-flight method. In this work, the properties of type 304 austenitic stainless steel samples were studied via Bragg edge imaging. The samples included hot-rolled, cold-rolled and heat-treated specimens, which were characterized to investigate texture, phase fraction and grain growth. The results showed that the crystallite size increased with increasing annealing temperature. The cold-rolled and annealed samples exhibited strong textures, while the hot-rolled sample showed no preferred orientation. The phase volume fraction of induced martensite in the cold-rolled sample was also obtained. Twodimensional maps of microstructures and textures were obtained without destructive processes. The results were validated by electron backscatter diffraction and found to be consistent. This work provides valuable information for non-destructive characterization of bulk materials by performing Bragg edge imaging using the Hokkaido University compact accelerator neutron source. [ABSTRACT FROM AUTHOR]

In this work, near‐field and far‐field link measurement in metal enclosure environment is performed. The performance of near‐field and far‐field links are assessed using key performance indicators such as error vector magnitude, bit error rate, and signal‐to‐noise ratio. The metal enclosure is placed in an anechoic chamber, ensuring a stationary measurement environment. There are no external interference sources and the results are a function of near‐field and far‐field scenarios and hardware impairments. In measurements, software‐defined radios used for the transmission and reception of image data using the long‐term evolution‐advanced physical layer. Based on the results of the study, an optimum gain region can be determined where better key performance indicators are achieved. Furthermore, the frequency selectivity of the channel is reduced within the determined optimum gain region, leading to an improvement in the system's performance. [ABSTRACT FROM AUTHOR]

Black phosphorene quantum dots (BPQDs) are most commonly derived from high‐cost black phosphorus, while previous syntheses from the low‐cost red phosphorus (Pred) allotrope are highly oxidised. Herein, we present an intrinsically scalable method to produce high quality BPQDs, by first ball‐milling Pred to create nanocrystalline Pblack and subsequent reductive etching using lithium electride solvated in liquid ammonia. The resultant ~25 nm BPQDs are crystalline with low oxygen content, and spontaneously soluble as individualized monolayers in tertiary amide solvents, as directly imaged by liquid‐phase transmission electron microscopy. This new method presents a scalable route to producing quantities of high quality BPQDs for academic and industrial applications. [ABSTRACT FROM AUTHOR]

Image encryption is the core technology of secure storage and transmission of image information. Based on a perceptron-like network of integer domain, a new unified image encryption algorithm is proposed. Its encryption algorithm and decryption algorithm are the same, both including an exclusive-or module, two types of perceptron-like networks and a sequence-flip module. The image data are diffused and encrypted by the forward propagation algorithm of neural network, and the historical data of the image are memorized and updated by the backward propagation algorithm of the network. The unified image cryptosystem uses a 512-bit key with the encryption speed up to 13.794Mbps on the computer equipped with an i7-9750H CPU. The maximum relative error of each system sensitivity index is less than 0.1%. The system requires the pseudorandom numbers by only half the size of the image. Simulated tests and comparative analyses show that the unified image cryptosystem possesses excellent characteristics of high speed and strong security strength. The proposed system can be used as a candidate safety method for network image information security. [ABSTRACT FROM AUTHOR]

Ultrastructural analysis of muscular biopsy is based on images of longitudinal sections of the fibers. Sometimes, due to experimental limitations, the resulting sections are instead oblique, and no accurate morphological information can be extracted with standard analysis methods. Thus, the biopsy is performed again, but this is too invasive and time‐consuming. In this study, we focused our attention on the sarcomere's shape and we investigated which is the structural information that can be obtained from oblique sections. A routine was written in MATLAB to allow the visualization of how a sarcomere's section appears in ultrastructural images obtained by Transmission Electron Microscopy (TEM) at different secant angles. The routine was used also to analyze the intersection between a cylinder and a plane to show how the Z‐bands and M‐line lengths vary at different secant angles. Moreover, we explored how to calculate sarcomere's radius and length as well as the secant angle from ultrastructural images, based only on geometrical considerations (Pythagorean theorem and trigonometric functions). The equations to calculate these parameters starting from ultrastructural image measurements were found. Noteworthy, to obtain the real sarcomere length in quasi‐longitudinal sections, a small correction in the standard procedure is needed and highlighted in the text. In conclusion, even non‐longitudinal sections of skeletal muscles can be used to extrapolate morphological information of sarcomeres, which are important parameters for diagnostic purposes. [ABSTRACT FROM AUTHOR]

Multimedia means text, image, audio or video file and transferring multimedia files through the internet are noticeable one. Multimedia securing techniques are additionally used to protect the file. Securing multimedia image file is difficult by using formal encryption techniques such as AES, RSA because of high correlation between pixels. For encryption, chaotic map with XOR function is used and to provide double protection, steganography technique is used. After the encryption, encrypted image is hidden into the cover image file using LSB-steganography. For that, from the cover image, the rectangular positioned pixel values are selected and the encrypted image values are hidden into the selected rectangular positioned pixel locations of the cover file. Embedded image i.e., stego image is transmitted to the recipient through the internet and the reversal process is carried over at the retriever side. The performance of this proposed algorithm is evaluated by using many numerical calculations such as NPCR, UACI and PSNR. Correlation analysis is also performed and the values of the secret image is compared with the chaotic map encrypted image. The obtained average NPCR, UACI and PSNR values are 99.8004%, 37.6773% and 46.41 respectively. These values are compared with existing methods. After retrieving the secret image, the PSNR value is calculated and is high as 46.41dB. From the analysis, it is clear that the chaotic map based image cryptography and steganography method provides more security and robustness in the wireless secret image transmission [ABSTRACT FROM AUTHOR]

Bottle beams have drawn considerable research interest due to their attractive features and applications in beam trapping. Herein, the flexible generation and modulation of bottle beams utilizing a reconfigurable metamirror over a non‐negligible frequency band ranging from 8.5 to 9.5 GHz is investigated. A varactor diode is embedded into each meta‐atom on the metamirror enabling the achievement of a nearly 2π phase coverage by varying the external bias voltage. Based on the caustic theory, several configurations of bottle beam with distinct radius a are realized as proof‐of‐concept validation. Besides, the flexible modulation of the operating frequency is analyzed by judiciously controlling the bias voltages applied to the metasurface. The experimental results are in good agreement with those obtained from numerical simulations. Such a flexible bottle beam generator shows good potential in the microwave regime for near‐field applications, such as imaging and power transmission. [ABSTRACT FROM AUTHOR]

Digital imaging fiber-optic transillumination (DIFOTI) devices have been used to detect caries, a technique without using X-rays. However, the effects of resin composites (RCs) shades on the images acquired with DIFOTI devices have not been investigated. Thus, this study aimed to elucidate the influence of RC shade on the images obtained with DIFOTI technique. Three shades (A1, A3, and Opaque) for each of four flowable RCs were filled on a cavity prepared in a left mandibular first premolar obtained from a donated body. Then, transmission images with a DIFOTI device (DIAGNOcam; KaVo, Biberach, Germany) were acquired, and the average lightness values of the images in the RC and enamel were used to calculate differences between those areas. To clarify the influence of the optical translucency and color on DIFOTI images, the color parameters (L*, a* and b*) of each RC were obtained with black and white backgrounds. The color differences between the backgrounds were calculated as transparency parameter (TP) values. The number of repetitions was set to 10. Differences in the lightness value of the shades varied in each RC. The difference in lightness was significantly associated with the TP value and color parameters of L* (p < 0.01), with negative (R = − 0.81) and positive (R = 0.84) correlations, respectively. In conclusion, DIFOTI images of RCs with high optical translucency resembled those of the natural tooth structure. [ABSTRACT FROM AUTHOR]

This paper proposes a Field Programmable Gate Array (FPGA)-based control system to implement micro-light-emitting diode (micro-LED) real-time display. The control system includes the interface control, video processing, memory management, image data transmission, control signal generation and correction. Then, we implement the micro-LED real-time display via memory management. We propose the brightness correction to achieve high grey-scale and high uniformity display. The LEDs are mounted on the glass substrate prepared using low-temperature polysilicon (LTPS) technology, and then we find the 24 × 46 pixels micro-LED panel. And the control system has been successfully applied to the panel of glass-based micro-LED displays. A new grey control method is proposed in this work, which can effectively improve the refresh rate of the micro-LED displays. The high grey-scale refresh rate is 2100 Hz, and the low grey-scale refresh rate is 300 Hz. The uniformity of the panel is increased to 85% after brightness correction. [ABSTRACT FROM AUTHOR]

The article titled "Quantum-inspired adaptive loss detection and real-time image restoration for live optical quantum image transmission" published in Optical & Quantum Electronics has been retracted by the Publisher due to concerns about compromised peer-review processes, inappropriate references, and being out of scope for the journal. The authors of the article have not responded to correspondence regarding the retraction. Springer Nature, the Publisher, remains neutral in this matter. [Extracted from the article]

Near-field optical microscopy visualizes spatial characteristics of elementary excitations induced in metal nanostructures. However, the microscopy is not able to reveal the absorption and scattering characteristics of the object simultaneously. In this study, we demonstrate a method for revealing the absorption and scattering characteristics of silver nanoplate by using near-field transmission and reflection spectroscopy. Near-field transmission and reflection images show characteristic spatial features attributable to the excited plasmon modes. The near-field refection image near the resonance shows a reversed contrast depending on the observed wavelength. Near-field reflection spectra show unique positive and negative resonant features. We reveal that the optical characteristics and the wavelength dependency of the optical contrast originate from the scattering and absorption properties of the plasmons, with the aid of the electromagnetic simulations. [ABSTRACT FROM AUTHOR]

We visualize plasmon mode patterns induced in a single gold nanorod by three-dimensional scanning near-field optical microscopy. From the near-field transmission imaging, we find that 3rd and 4th order plasmon modes are resonantly excited in the nanorod. We perform electromagnetic simulations based on the discrete dipole approximation method under focused Gaussian beam illumination and demonstrate that the observed near-field spectral and spatial features are well reproduced by the simulation. We also reveal from the three-dimensional near-field microscopy that the 4th order plasmon mode confines optical fields more tightly compared with the 3rd order mode. This result indicates that the even-order plasmon modes are promising for enhancing the light−matter interactions. [ABSTRACT FROM AUTHOR]

In this Letter, the phase profile of the self-rotating beam is modified by introducing the radial shift factor c and the azimuthal shift factor θ0. The effect of the radial shift factor c on the corresponding intensity distribution is discussed. The results demonstrate that the focal-field intensity patterns of the modified self-rotating beams with different radial shift factors moved away from the center of the light field with the radial shift factor increased. The self-rotating beam array can be arranged arbitrarily along the azimuthal direction with a synthetic phase produced by superimposing multiple modified subphases (i.e., modified self-rotating beam phase). Furthermore, the position of each self-rotating beam in the beam array can be also adjusted arbitrarily in the transverse plane by adding the gratings into each subphase layer of the synthetic phase. The proposed beam array has potential applications in image transmission, data coding and decoding, and optical trapping. [ABSTRACT FROM AUTHOR]

A complementary solid-state nuclear magnetic resonance and transmission electron microscopy (TEM) analysis was performed for LiBH4–ZrO2 nanocomposites. As a result, amorphous LiBH4 films with thicknesses of less than 30 nm were observed covering the ZrO2 particles. Li imaging by energy-filtered TEM is useful for the real-space characterization of nanoscale LiBH4. [ABSTRACT FROM AUTHOR]

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which the encryption process is applied in the frequency domain. The proposed DCBS secret key generator generates a very large key space of 2 2200 . The proposed DCBS secret keys generator can achieve the confidentiality and authentication properties. Statistical analysis, differential analysis and a key sensitivity test are performed to estimate the security strengths of the proposed DCBS-MP-FrFT-OFDM cryptosystem over the IoT network. The experimental results show that the proposed DCBS-MP-FrFT-OFDM cryptosystem is robust against common signal processing attacks and provides a high security level for image encryption application. [ABSTRACT FROM AUTHOR]

Transmission line fault detection using drones provides real-time assessment of the operational status of transmission equipment, and therefore it has immense importance in ensuring stable functioning of the transmission lines. Currently, identification of transmission line equipment relies predominantly on manual inspections that are susceptible to the influence of natural surroundings, resulting in sluggishness and a high rate of false detections. In view of this, in this study, we propose an insulator defect recognition algorithm based on a YOLOv5 model with a new lightweight network as the backbone network, combining noise reduction and target detection. First, we propose a new noise reduction algorithm, i.e., the adaptive neighborhood-weighted median filtering (NW-AMF) algorithm. This algorithm employs a weighted summation technique to determine the median value of the pixel point's neighborhood, effectively filtering out noise from the captured aerial images. Consequently, this approach significantly mitigates the adverse effects of varying noise levels on target detection. Subsequently, the RepVGG lightweight network structure is improved to the newly proposed lightweight structure called RcpVGG-YOLOv5. This structure facilitates single-branch inference, multi-branch training, and branch normalization, thereby improving the quantization performance while simultaneously striking a balance between target detection accuracy and speed. Furthermore, we propose a new loss function, i.e., Focal EIOU, to replace the original CIOU loss function. This optimization incorporates a penalty on the edge length of the target frame, which improves the contribution of the high-quality target gradient. This modification effectively addresses the issue of imbalanced positive and negative samples for small targets, suppresses background positive samples, and ultimately enhances the accuracy of detection. Finally, to align more closely with real-world engineering applications, the dataset utilized in this study consists of machine patrol images captured by the Unmanned Aerial Systems (UAS) of the Yunnan Power Supply Bureau Company. The experimental findings demonstrate that the proposed algorithm yields notable improvements in accuracy and inference speed compared to YOLOv5s, YOLOv7, and YOLOv8. Specifically, the improved algorithm achieves a 3.7% increase in accuracy and a 48.2% enhancement in inference speed compared to those of YOLOv5s. Similarly, it achieves a 2.7% accuracy improvement and a 33.5% increase in inference speed compared to those of YOLOv7, as well as a 1.5% accuracy enhancement and a 13.1% improvement in inference speed compared to those of YOLOv8. These results validate the effectiveness of the proposed algorithm through ablation experiments. Consequently, the method presented in this paper exhibits practical applicability in the detection of aerial images of transmission lines within complex environments. In future research endeavors, it is recommended to continue collecting aerial images for continuous iterative training, to optimize the model further, and to conduct in-depth investigations into the challenges associated with detecting small targets. Such endeavors hold significant importance for the advancement of transmission line detection. [ABSTRACT FROM AUTHOR]

Prohibited item detection plays a significant role in ensuring public safety, as the timely and accurate identification of prohibited items ensures the safety of lives and property. X-ray transmission imaging technology is commonly employed for prohibited item detection in public spaces, producing X-ray images of luggage to visualize their internal contents. However, challenges such as multiple object overlapping, varying angles, loss of details, and small targets in X-ray transmission imaging pose significant obstacles to prohibited item detection. Therefore, a dual attention mechanism network (DAMN) for X-ray prohibited item detection is proposed. The DAMN consists of three modules, i.e., spatial attention, channel attention, and dependency relationship optimization. A long-range dependency model is achieved by employing a dual attention mechanism with spatial and channel attention, effectively extracting feature information. Meanwhile, the dependency relationship module is integrated to address the shortcomings of traditional convolutional networks in terms of short-range correlations. We conducted experiments comparing the DAMN with several existing algorithms on datasets containing 12 categories of prohibited items, including firearms and knives. The results show that the DAMN has a good performance, particularly in scenarios involving small object detection, detail loss, and target overlap under complex conditions. Specifically, the detection average precision of the DAMN reaches 63.8%, with a segmentation average precision of 54.7%. [ABSTRACT FROM AUTHOR]

The image transmission over wireless media experiences not only unavailable performance loss caused by the environment and hardware issues, but also information leakage to eavesdroppers who can overhear and attempt to recover the images. This paper proposes a secure cooperative relaying (SCR) protocol for the image communications in wireless relay networks (WRNs) where Alice sends high-resolution (HR) images to Bob with the assistance of a relaying user named Relay, and in the presence of an eavesdropper named Eve. In order to enhance the security of the image communications, random linear network coding (RLNC) is employed at both Alice and Relay to conceal the original images from Eve with RLNC coefficient matrices and reference images in the shared image datastore. Furthermore, the original HR images are downscaled at Alice to save transmission bandwidth and image super-resolution (ISR) is adopted at Bob due to its capability to recover the HR images from their low-resolution (LR) version, while still maintaining the image quality. In the proposed SCR protocol, Bob can decode both the original images transmitted from Alice over the direct link and the images forwarded by Relay over the relaying links. Simulation results show that the SCR protocol achieves a considerably higher performance at Bob than at Eve since Eve does not know the coefficient matrices and reference images used at Alice and Relay for the RLNC. The SCR protocol is also shown to outperform the counterpart secure direct transmission protocol without the relaying links and secure relaying transmission without the direct link. Additionally, an increased scaling factor can save the transmission bandwidth for a slight change in the image quality. Moreover, the impacts of direct, relaying and wiretap links are evaluated, verifying the effectiveness of the SCR protocol with the employment of Relay to assist the image communications between Alice and Bob in the WRNs. [ABSTRACT FROM AUTHOR]

The development of optical sensors, especially with regard to the improved resolution of cameras, has made optical techniques more applicable in medicine and live animal research. Research efforts focus on image signal acquisition, scattering de-blur for acquired images, and the development of image reconstruction algorithms. Rapidly evolving artificial intelligence has enabled the development of techniques for de-blurring and estimating the depth of light-absorbing structures in biological tissues. Although the feasibility of applying deep learning to overcome these problems has been demonstrated in previous studies, limitations still exist in terms of de-blurring capabilities on complex structures and the heterogeneity of turbid medium, as well as the limit of accurate estimation of the depth of absorptive structures in biological tissues (shallower than 15.0 mm). These problems are related to the absorption structure's complexity, the biological tissue's heterogeneity, the training data, and the neural network model itself. This study thoroughly explores how to generate training and testing datasets on different deep learning models to find the model with the best performance. The results of the de-blurred image show that the Attention Res-UNet model has the best de-blurring ability, with a correlation of more than 89% between the de-blurred image and the original structure image. This result comes from adding the Attention gate and the Residual block to the common U-net model structure. The results of the depth estimation show that the DenseNet169 model shows the ability to estimate depth with high accuracy beyond the limit of 20.0 mm. The results of this study once again confirm the feasibility of applying deep learning in transmission image processing to reconstruct clear images and obtain information on the absorbing structure inside biological tissue. This allows the development of subsequent transillumination imaging studies in biological tissues with greater heterogeneity and structural complexity. [ABSTRACT FROM AUTHOR]

Despite being thirteen years since the installation of the first PET-MR system, the scanners constitute a very small proportion of the total hybrid PET systems installed. This is in stark contrast to the rapid expansion of the PET-CT scanner, which quickly established its importance in patient diagnosis within a similar timeframe. One of the main hurdles is the development of an accurate, reproducible and easy-to-use method for attenuation correction. Quantitative discrepancies in PET images between the manufacturer-provided MR methods and the more established CT- or transmission-based attenuation correction methods have led the scientific community in a continuous effort to develop a robust and accurate alternative. These can be divided into four broad categories: (i) MR-based, (ii) emission-based, (iii) atlas-based and the (iv) machine learning-based attenuation correction, which is rapidly gaining momentum. The first is based on segmenting the MR images in various tissues and allocating a predefined attenuation coefficient for each tissue. Emission-based attenuation correction methods aim in utilising the PET emission data by simultaneously reconstructing the radioactivity distribution and the attenuation image. Atlas-based attenuation correction methods aim to predict a CT or transmission image given an MR image of a new patient, by using databases containing CT or transmission images from the general population. Finally, in machine learning methods, a model that could predict the required image given the acquired MR or non-attenuation-corrected PET image is developed by exploiting the underlying features of the images. Deep learning methods are the dominant approach in this category. Compared to the more traditional machine learning, which uses structured data for building a model, deep learning makes direct use of the acquired images to identify underlying features. This up-to-date review goes through the literature of attenuation correction approaches in PET-MR after categorising them. The various approaches in each category are described and discussed. After exploring each category separately, a general overview is given of the current status and potential future approaches along with a comparison of the four outlined categories. [ABSTRACT FROM AUTHOR]

Human body pose transfer is to transform the character image from the source image pose to the target pose. In recent years, the research has achieved great success in transforming the human body pose from the source image to the target image, but it is still insufficient in the detailed texture of the generated image. To solve the above problems, a new two-stage TPIT network model is proposed to process the detailed texture of the pose-generated image. The first stage is the source image self-learning module, which extracts the source image features by learning the source image itself and further improves the appearance details of pose-generated image. The other stage is to change the pose of the figure gradually from the source image pose to the target pose. Then, by learning the feature correlation between source and target images through cross-modal attention, texture transmission between images is promoted to generate finer-grained details of the generated image. A large number of experiments show that the model has superior performance on the Market-1501 and DeepFashion datasets, especially in the quantitative and qualitative evaluation of Market-1501, which is superior to other advanced methods. [ABSTRACT FROM AUTHOR]

Due to the increasing capabilities of cybercriminals and the vast quantity of sensitive data, it is necessary to protect remote sensing images during data transmission with "Belt and Road" countries. Joint image compression and encryption techniques exhibit reliability and cost-effectiveness for data transmission. However, the existing methods for multiband remote sensing images have limitations, such as extensive preprocessing times, incompatibility with multiple bands, and insufficient security. To address the aforementioned issues, we propose a joint encryption and compression algorithm (JECA) for multiband remote sensing images, including a preprocessing encryption stage, crypto-compression stage, and decoding stage. In the first stage, multiple bands from an input image can be spliced together in order from left to right to generate a grayscale image, which is then scrambled at the block level by a chaotic system. In the second stage, we encrypt the DC coefficient and AC coefficient. In the final stage, we first decrypt the DC coefficient and AC coefficient, and then restore the out-of-order block through the chaotic system to get the correct grayscale image. Finally, we postprocess the grayscale image and reconstruct it into a remote sensing image. The experimental results show that JECA can reduce the preprocessing time of the sender by 50% compared to existing joint encryption and compression methods. It is also compatible with multiband remote sensing images. Furthermore, JECA improves security while maintaining the same compression ratio as existing methods, especially in terms of visual security and key sensitivity. [ABSTRACT FROM AUTHOR]

The blurring of texture edges often occurs during image data transmission and acquisition. To ensure the detailed clarity of the drag-time images, we propose a time image de-noising method based on sparse regularization. First, the image pixel sparsity index is set, and then an image de-noising model is established based on sparse regularization processing to obtain the neighborhood weights of similar image blocks. Second, a time image de-noising algorithm is designed to determine whether the coding coefficient reaches the standard value, and a new image de-noising method is obtained. Finally, the images of electronic clocks and mechanical clocks are used as two kinds of time images to compare different image de-noising methods, respectively. The results show that the sparsity regularization method has the highest peak signal-to-noise ratio among the six compared methods for different noise standard deviations and two time images. The image structure similarity is always above which shows that the proposed method is better than the other five image de-noising methods. [ABSTRACT FROM AUTHOR]

Wireless Body Area Network (WBAN) is a wireless network of short-range communication protocols for remote healthcare monitoring with the possibility of giving freedom of human body movements. Sensor nodes (motes) are usually located under the skin, implanted deep in the body, or ingested, as in the rare case of smart pills for medical and non-medical usage. Since the necessary connections of wearable and implantable devices are wireless, and the components use low batteries, processing and transferring the critical data can deplete the nodes' power. In most cases, it is impossible to exchange or re-power batteries. Holter monitoring, loop recorders, and wireless capsule endoscopy are some of the WBAN's applications for saving and transferring medical data. Wireless capsule endoscopy is the application for image transmission in WBANs, and the image compression in common is a specific segment of capsule endoscopy. Since the better compression of images increases the frame rate and typically improves the diagnosis process, selecting the compression algorithm should be relevant. The considerable scope of this comprehensive study pays attention to the various biomedical data compression approaches in WBANs. This paper focuses on power-efficient schemes of remote healthcare networks. In this survey article, the energy-based biomedical data compression approaches of WBANs and remote healthcare networks are accurately classified based on lossy, lossless, and hybrid techniques; later, a comprehensive comparison of each specific method's power consumption is presented. [ABSTRACT FROM AUTHOR]

In today's world, digital image storage and transmission play an essential role,where images are mainly involved in data transfer. Digital images usually take large storage space and bandwidth for transmission, so image compression is important in data communication. This paper discusses a unique and novel lossy image compression approach. Exactly 50% of image pixels are encoded, and other 50% pixels are excluded. The method uses a block approach. Pixels of the block are transformed with a novel transform. Pixel nibbles are mapped as a single bit in a transform table generating more zeros, which helps achieve compression. Later, inverse transform is applied in reconstruction, and a single bit value from the table is remapped into pixel nibbles. With these nibbles, pixel values of the block are reconstructed without any loss. The average method is used in reconstruction of excluded pixels. This approach achieves better quality in reconstructed test images at lower PSNR values ranging from 33dB to 44dB. Compression ratio achieved is more than 2. Correctness ratio achieved by proposed method is more than 0.5. [ABSTRACT FROM AUTHOR]

A recent study and research have shown that the relay selection schemes for cooperative communication can achieve full cooperative diversity gains and still maintains energy efficiency. Multi-source and multi-relay networks frequently cooperate to transfer their own data to the destination, mainly the access point, in cooperative wireless networks. In this paper, we use a jellyfish optimizer to select the number of relays to transmit packets of the image depending on the order of the data in the image according to its importance and at a constant rate. First, the relationships between the number of relays, peak signal-to-noise ratio (PSNR), and signal-to-noise ratio (SNR) are analysed. Second, the comparison between the performances of Equal Diversity (ED) and Unequal Diversity (UED) with Equal Error Protection (EEP) and Unequal Error Protection (UEP) is introduced using the set partitioning in hierarchical trees (SPIHT) image coder as a source coding. The jellyfish (JS) algorithm, as an efficient optimization technique, is applied for solving the problem of optimal relay selection method to reduce the bit error rate and to improve the transmitted image quality. Many useful and important results in the proposed work can be used in the enhancement of image transmission over cooperative networks. Relative to the traditional methods, the proposed method achieves better results for the transmission of images with high quality through cooperative communication networks. [ABSTRACT FROM AUTHOR]

It is difficult to overstate the degree of uncertainty during the early days of the coronavirus disease of 2019 (COVID-19) pandemic, as government advice largely emphasized self-quarantine and isolation, stringent hygienic and sanitation practices, implementation of regulations around face masks and shields, and closure of congregate public spaces. This uncertainty was especially true for homelessness service providers, as homelessness is a phenomenon which has historically taken place primarily in public and communal spaces. It is important to consider that data collection among people experiencing homelessness (PEH) has always been a complex endeavor, as these populations can be transient, hard-to-reach, and reluctant to engage with researchers. COVID-19 testing was also severely limited throughout 2020, prior to the development of readily available selfadministered tests. Understanding the complete picture of COVID-19 transmission within homeless populations during the early days of the outbreak, is therefore immensely challenging. For these reasons, this study, undertaken in August 2020, seeks to record the impact of the early pandemic period on homelessness service systems from a policy perspective. The value of this perspective is twofold: first, it documents how systems in a wide array of contexts responded to a critical public health crisis and can stand as a record of how systems operated prior to and immediately after the outbreak occurred, providing important historical context for future research; and second, it helps contextualize new and emerging data around the experience of PEH during COVID-19 and its lingering impacts. [ABSTRACT FROM AUTHOR]

In this work, we build upon an implementation of a peer-to-peer image encryption algorithm: "Rubik's cube algorithm". The algorithm utilizes pixel-level scrambling and XOR-based diffusion, facilitated through the symmetric key. Empirical analysis has proven this algorithm to have the advantage of large key space, high-level security, high obscurity level, and high speed, aiding in secure image transmission over insecure channels. However, the base approach has drawbacks of key generation being handled client-side (at nodes) and the process is time-consuming due to dynamically generating keys. Our work solves these issues by introducing a Key Distribution Center (KDC) to distribute symmetric keys for transmission, increasing confidentiality, and reducing key-generation overhead on nodes. Three approaches utilizing the KDC are presented, communicating the dimensions with KDC to generate keys, standardizing any image to fixed dimensions to standardize key-generation, and lastly, using a single session key which is cyclically iterated over, emulating different dimensions. [ABSTRACT FROM AUTHOR]

Due to the inherent insecure nature of the Internet, it is crucial to ensure the secure transmission of image data over this network. Additionally, given the limitations of computers, it becomes even more important to employ efficient and fast image encryption techniques. While 1D chaotic maps offer a practical approach to real-time image encryption, their limited flexibility and increased vulnerability restrict their practical application. In this research, we have utilized a 3D Hindmarsh-Rose model to construct a secure cryptosystem. The randomness of the chaotic map is assessed through standard analysis. The proposed system enhances security by incorporating an increased number of system parameters and a wide range of chaotic parameters, as well as ensuring a uniform distribution of chaotic signals across the entire value space. Additionally, a fast image encryption technique utilizing the new chaotic system is proposed. The novelty of the approach is confirmed through time complexity analysis. To further strengthen the resistance against cryptanalysis attacks and differential attacks, the SHA-256 algorithm is employed for secure key generation. Experimental results through a number of parameters demonstrate the strong cryptographic performance of the proposed image encryption approach, highlighting its exceptional suitability for secure communication. Moreover, the security of the proposed scheme has been compared with stateof-the-art image encryption schemes, and all comparison metrics indicate the superior performance of the proposed scheme. [ABSTRACT FROM AUTHOR]

The world has taken a drastic look towards scalar mobile wireless multi media sensor networks (MWMSN) and almost all the nodes (IOT devices) are connected via the internet. The amount of image, video and data transmission has increased significantly. For battery-powered smart gadgets like smartphones and tablets, energy efficiency is a constant issue. To fully utilise the advantages of the multiple-input-multiple-output technology, MWMSN heavily relies on cooperative communication. Since each node in a cooperative mobile multimedia sensor network is mobile, energy consumption and routing present significant issues. Since each node in the network is mobile, energy consumption and routing pose significant problems for cooperative mobile multimedia sensor networks. To address these challenges optimal cooperative relay selection (OCRS) technique was proposed by utilizing velocity, distance, and connection quality factors. The suggested method bases its determination of the link quality for each pair of nodes on the signal strength and distance values. The highest quality of service (QoS) rating, which is determined to ensure route stability, reliability, and durability, is chosen as the relay nodes. Further, we have proposed an energy efficient cooperative multi media transmission (EECMT) to achieve a better compression rate with lower energy consumption. This approach utilizes the auto-correction code feature present in the QR code to further improve the performance of MWMSN. The simulation result shows that the proposed approach gives better performance and saves the energy up to 39% (approximately) compared to the efficient cooperative image transmission (ECIT), energy efficient relay node placement (EERP) and energy aware cooperative image transmission (EACIT) approaches. [ABSTRACT FROM AUTHOR]

Achieving high-efficient and low-power communication is pivotal yet very challenging in the emerging technologies. Unlike conventional backscatter communication system, we propose and demonstrate an amplitude-reconfigurable metasurface loaded with PIN diodes to build a front-back scattering communication transmitter, which features the exclusive advantages of full-space secondary modulation of the ambient signals with high energy utilization efficiency. Meanwhile, this device can eliminate the interference originated from the ambient source by polarization conversion in the transmission channel. At a modulation rate of 800 kbps and a distance of 80 m, our system can achieve distortion-free transmission of a picture with size of 200 × 200 pixels. In addition, multiple amplitude-shift-keying modulation is also realized by segmenting the metasurface to further increase the communication rate. Due to the advantages of high spectral efficiency and low energy consumption, this system can be widely used in future engineering applications for the internet of things, especially for smart home, agriculture environmental monitoring, wearable sensing and others. [ABSTRACT FROM AUTHOR]

In this paper, we developed a hyperspectral transmission microscopic imaging (HTMI) system for rapid detection of pathogenic bacteria, which can realize precise identification and classification of mixed pathogenic bacteria to a single-bacterium level. The system works in trans-illumination patterns and a self-developed dispersive hyperspectral imaging module is used as the detection setup, providing spectral images with high SNR, and showing excellent performances with spatial resolution of 2.19 µm and spectral resolutions less than 1 nm. Hyperspectral microscopic imaging of five types of bacteria in low concentration were performed. The merging spatial-spectral profiles of individual bacteria for each species were extracted and utilized for species identification, achieving high classification accuracy of 93.6% using a simple PCA-SVM method. Species identification experiments of the mixed bacterial samples were further carried out, and the results demonstrate the validity and capability of the system assisted with simple machine learning methods to be used as an effective and rapid diagnostic tool for elaborate identification of mixed bacterial pathogen samples, providing guidance for the use of correct antibiotics. [ABSTRACT FROM AUTHOR]

Dermal substitutes are well established in the reconstructive ladder. MatriDerm® (Dr. Otto Suwelack Skin & Health Care AG, Billerbeck, Germany) is a single-layer dermal substitute composed of a bovine collagen (type I, III, and V) and elastin hydrolysate, that allows for immediate split-thickness skin grafting (SSG). The aim of this study was to histologically characterize the integration of MatriDerm® when used during burns surgery reconstruction. Eight subjects with nine burn scars and one acute burn wound underwent reconstruction with MatriDerm® and an immediate SSG. MatriDerm® integration and skin graft take were assessed with serial biopsies performed at weeks 1, 2, 3, and 4 and months 2, 3, 6, 9, and 12. Biopsies were assessed with standard special stains and immunohistochemistry, and representative slides were imaged with a transmission electron microscope. Patient satisfaction and clinical scar outcome were assessed with the Vancouver Scar Scale and a patient questionnaire. Histological analysis showed similar stages of wound healing as shown in other dermal templates but on a different timescale. There is early evidence of vascularization and an inflammatory infiltrate in the first 2 weeks. MatriDerm® is resorbed earlier than other dermal substitutes, with evidence of resorption at week 3, to be completely replaced by a neodermis at 2 months. The use of MatriDerm® in reconstruction with immediate skin grafting is supported histologically with early evidence of vascularization to support an epidermal autograft. Future histological studies may help further characterize the ideal dermal substitute. [ABSTRACT FROM AUTHOR]

The traditional inclination measurement method usually measures one-dimensional or two-dimensional inclinations of power transmission towers. This research proposed a method, which is feasible to measure three-dimensional (3D) inclinations using the stereo images of power transmission towers. The main work of this method is the 3D reconstruction of power transmission tower model using stereo images and the calculation of 3D inclinations. As for the 3D reconstruction, a method of calculating the matching cost using a combination of multichannel red–green–blue stereo pairs and Sobel edge detection stereo pairs is proposed to obtain accurate matching cost, and a method of invalid disparity judgment is proposed to detect the invalid disparities in small closed areas; as for the calculation of 3D inclinations, a 3D inclination calculation method is put forward to measure 3D inclinations by rotation and translation of different 3D reconstruction models. The experiment shows that the 3D reconstruction quality is good and the results of the 3D inclinations are accurate, which is of great value in the static or dynamic measurement of 3D inclinations of power transmission towers. [ABSTRACT FROM AUTHOR]

Unmanned Aerial Vehicle (UAV) inspection of transmission channels in mountainous areas is susceptible to non-homogeneous fog, such as up-slope fog and advection fog, which causes crucial portions of transmission lines or towers to become fuzzy or even wholly concealed. This paper presents a Dual Attention Level Feature Fusion Multi-Patch Hierarchical Network (DAMPHN) for single image defogging to address the bad quality of cross-level feature fusion in Fast Deep Multi-Patch Hierarchical Networks (FDMPHN). Compared with FDMPHN before improvement, the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) of DAMPHN are increased by 0.3 dB and 0.011 on average, and the Average Processing Time (APT) of a single picture is shortened by 11%. Additionally, compared with the other three excellent defogging methods, the PSNR and SSIM values DAMPHN are increased by 1.75 dB and 0.022 on average. Then, to mimic non-homogeneous fog, we combine the single picture depth information with 3D Berlin noise to create the UAV-HAZE dataset, which is used in the field of UAV power assessment. The experiment demonstrates that DAMPHN offers excellent defogging results and is competitive in no-reference and full-reference assessment indices. [ABSTRACT FROM AUTHOR]

The Internet is a conduit for vast quantities of digital data, with the transmission of images being especially prevalent due to the widespread use of social media. However, this popularity has led to an increase in security concerns such as image tampering and forgery. As a result, image authentication has become a critical technology that cannot be overlooked. Recently, numerous researchers have focused on developing image authentication techniques using deep learning to combat various image tampering attacks. Nevertheless, image authentication techniques based on deep learning typically classify only specific types of tampering attacks and are unable to accurately detect tampered images or indicate the precise location of tampered areas. The paper introduces a novel image authentication framework that utilizes block-wise encoding through Variational Autoencoder and Generative Adversarial Network models. Additionally, the framework includes a classification mechanism to develop separate authentication models for different images. In the training phase, the image is first divided into blocks of the same size as training data. The goal is to enable the model to judge the authenticity of the image by blocks and to generate blocks similar to the original image blocks. In the verification phase, the input image can detect the authenticity of the image through the trained model, locate the exact position of the image tampering, and reconstruct the image to ensure the ownership. [ABSTRACT FROM AUTHOR]

This article presents a technique to integrate two dynamical models, a four-wing spherical chaotic oscillator and the elliptical path described by the planet Earth during its translation movement around the sun. Four application cases are derived from the system by varying the dynamics of the chaotic oscillator and these can be applied in information encryption to transmit RGB and grayscale images modulated by CSK. Consequently, the three main contributions of this work are (1) the emulation of the trajectories of the planet Earth with chaotic interference, (2) the CSK modulation and image encryption in a master-slave synchronization topology, and (3) the CSK demodulation for decryption without loss of information with respect to the original information. The three contributions are based on VHDL code implementation. The results of the synchronization, encryption and decryption technique were verified by means of time series and the encrypted images showed a correlation less than − 0.000142 and − 0.0003439 for RGB and grayscale format, respectively, while the retrieved image shows a complete correlation with the image original. In this work, the co-simulations were performed between MATLAB/Simulink and Vivado, using the VHDL language on two FPGA boards from different manufacturers, namely, Xilinx Artix-7 AC701 and Intel Cyclone IV. [ABSTRACT FROM AUTHOR]

The detection performance of power transmission towers in mountainous areas using SAR amplitude images is obviously influenced by the strong layover background (mainly including vegetation and soil) clutter interference around the towers. In this paper, power transmission tower detection in a mountainous layover area, using single-baseline SAR interferometry coherence images, which show better feature enhancement effectiveness compared to SAR amplitude images, is presented. Moreover, a novel feature enhancement method, that of generating multi-baseline SAR interferometry-correlated synthesis images for power transmission tower detection in a mountain layover area, is proposed. It demonstrates better feature enhancement (layover background cluster suppression) than that using single-baseline SAR interferometry coherence images. Theoretical analysis illustrates that the mountainous layover background clutter interference can be suppressed in the proposed single-baseline/multi-baseline SAR interferometry-correlated synthesis image. Experiments including over 12 repeat-pass TerraSAR-X staring spotlight mode acquisitions were conducted, and the results demonstrate that the detection performance with the use of multi-baseline SAR interferometry-correlated synthesis images showed an improvement of more than 43.6%, compared with the traditional method of using SAR amplitude images when benchmark deep learning-based detectors are used, i.e., Faster RCNN and YOLOv7. [ABSTRACT FROM AUTHOR]

The High Resolution Picture Transmission (HRPT) data of the National Oceanic and Atmospheric Administration (NOAA) series meteorological satellites had been received by the SeaSpace ground station located at the Ocean University of China (OUC). Based on the atmospheric radiative transfer model, we obtained the NOAA-15/16/17/18/19 Advanced Very High Resolution Radiometer (AVHRR) sea surface skin temperature (SSTskin) data using the Bayesian cloud detection method and the optimal estimation (OE) sea surface temperature (SST) retrieval algorithm. Compared with the NOAA/AVHRR multi-channel SST data, the AVHRR SSTskin data have higher data accuracy. We also compared the AVHRR SSTskin with the buoy SST with spatial and temporal windows of 0.01° and 30 min. The daytime biases ranged from −0.32 °C (NOAA-16) to 0.08 °C (NOAA-17) with standard deviations (SDs) ranging from 0.36 °C (NOAA-18/ NOAA-19) to 0.60 °C (NOAA-16), and the nighttime biases ranged from −0.26 °C (NOAA-16) to −0.02 °C (NOAA-17) with SDs ranging from 0.33 °C (NOAA-19) to 0.60 °C (NOAA-16). The accuracy of all five satellite data during daytime and nighttime was significantly improved. These results show that the AVHRR SSTskin of NOAA series satellites is good and consistent in different periods, and the SSTskin data products with high spatial resolution and accuracy can be used for mesoscale and submesoscale marine applications. [ABSTRACT FROM AUTHOR]

This study developed a high-temperature and high-pressure (HTHP) cell for in situ neutron imaging of hydrothermal reactions. The cell's maximum temperature and pressure were 500 °C and 50 MPa, respectively, and its vessel for observing reactions comprised SUS316 stainless steel. Neutron transmission images were obtained to observe the behavior of sub- and supercritical water and the decomposition of two plastics (polypropylene and polyethylene) at HTHP. The images showed that water's density and phase changed with temperature and pressure, affecting neutron transmission (and thus image brightness). The plastics began to melt and change shape at 150–200 °C, and they decomposed at 500 °C and 20 MPa. This study provides a basis for future research using the HTHP cell to examine various reactions such as the decomposition of biomass samples, the reforming of heavy oil, and the synthesis of nano-materials using sub- and supercritical water. [ABSTRACT FROM AUTHOR]