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The rising use of 3D digital products has increased the demand for copyright protection. In this paper, we propose a novel and robust 3D watermarking method with high imperceptibility based on EMD (empirical mode decomposition) on surfaces. It first defines a normalized modulus signal on a 3D host model so as to involve EMD into 3D watermarking effectively. And then, it extracts different scale features of the defined signal by using EMD to locate the proper embedding positions. After this, the watermark signal is embedded repeatedly and cyclically into the 3D host model to enhance the robustness. The embedding strength is optimized according to a predefined fidelity parameter to control the imperceptibility of the watermark. Many experiment results show that the proposed method can obtain good results against various attacks while maintaining high invisibility, such as pseudo-random noise, Laplacian smoothing, simplification, subdivision, cropping, and similarity transformation. Furthermore, it is very competitive with the current state-of-the-art 3D watermarking techniques in terms of robustness and invisibility. [ABSTRACT FROM AUTHOR]

This paper presents a novel and fast EMD-based (empirical mode decomposition-based) image fusion approach via morphological filter. Firstly, we develop a multi-channel bidimensional EMD method based on morphological filter to conduct image fusion. It uses the morphological expansion and erosion filters to compute the upper and lower envelopes of a multi-channel image in the sifting processing, and can decompose the input source images into several intrinsic mode functions (IMFs) with different scales and a residue. It significantly improves the computation efficiency of EMD for multi-channel images while maintaining the decomposition quality. Secondly, we adopt a patch-based fusion strategy with overlapping partition to fuse the IMFs and residue instead of the pixel-based fusion way usually used in EMD-based image fusion, where an energy-based maximum selection rule is designed to fuse the IMFs, and the feature information extracted by IMFs is used as a guide to merge the residue. Such strategy can extract the salient information of the source images well and can also reduce the spatial artifacts introduced by the noisy characteristics of the pixel-wise maps. A large number of comparative experiments on the fusion of several commonly used image data sets with multi-focus and multi-modal images, show that our newly proposed fusion method can obtain much better results than the existing EMD-based image fusion approaches. Furthermore, it is very competitive with the state-of-the-art image fusion methods in visualization, objective metrics, and time performance. The code of the proposed method can be downloaded from: https://github.com/neepuhjp/MFMBEMD-ImageFusion. [ABSTRACT FROM AUTHOR]

Steganography is critical in traceability, authentication, and secret delivery for multimedia. In this paper, we propose a novel image steganography framework, named StegaEdge, via learning edge-guidance network to simultaneously address three challenges, capacity, multi-task, and invisibility. First, we use an upsampling strategy to expand the embedding space and thus increase the capacity of the embedded message. Second, our algorithm improves the embedding way of messages so that it can handle different messages embedded in the same image and achieve split-task recovery completely. Different information can be embedded in one cover image without affecting each other. Third, we innovatively propose an edge-guidance strategy to solve the problem of poor invisibility in smooth regions. The human eye is significantly less perceptive of intensity changes in edges than in smooth areas. Unlike traditional steganography methods, our edge-guidance steganography can appropriately embed part of the information into non-edge regions when the amount of embedded information is too large. Experimental results on three datasets show that the newly proposed StegaEdge algorithm achieves satisfactory results in terms of capacity, multi-task, imperceptibility, and security compared to the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

In this paper, we develop a robust image zero-watermarking algorithm based on multiple circular statistical features. First of all, we detect stable feature points from the host image, and construct circular region partitions from the identified feature points, which contain the critical information of the host image. Second, the statistics and differences of circular region partitions are calculated, which contain both the local differences and the global information of the host image. Third, we apply discrete cosine transform (DCT) and singular value decomposition (SVD) in statistics and differences in order to construct the feature image. The stability of DCT and SVD further warrants the robustness of the algorithm. Moreover, Arnold transform is used to scramble the watermark image to enhance the security of the algorithm. Finally, we obtain the zero watermark by performing the exclusive-or (XOR) operation between the feature image and the scrambled watermark image, and the zero watermark is stored in the copyright authentication database for copyright authentication. Moreover, to combat geometric attacks, we develop a blind image correction algorithm without using the original image to accurately correct the attacked image. Numerous experiments and comparisons with the state-of-the-art (SOTA) watermarking algorithms confirm that the proposed algorithm affords good robustness against various attacks, such as filtering attacks, noise attacks, geometric attacks, and even a random combination of the above-stated attacks. [ABSTRACT FROM AUTHOR]

In the past decades, bi-dimensional empirical mode decomposition (BEMD) algorithms have been developed for the image watermarking task with good robustness and imperceptibility; however, the non-negligible algorithm efficiency has received little attention at the same time. In this paper, we devise a robust and efficient image watermarking algorithm based on 1D empirical mode decomposition (EMD) and dimensional reduction via Hilbert curve. Converting the problem of two-dimensional image watermarking into the problem of one-dimensional signal watermarking promises to enhance the efficiency and the robustness of the proposed algorithm. Specifically, host image is first reduced into one-dimensional signal by the Hilbert curve. Our key insight is a dimensionality reduction strategy based on the Hilbert curve that preserves the spatial local relationship to the greatest extent possible. Second, the one-dimensional signal is segmented into several short signal intervals, and each of them is decomposed into several intrinsic mode functions (IMFs) and a residue by 1D EMD, which is much faster than BEMD. Third, the maximum or minimum points of the first IMF are chosen as the watermark embedding positions. For the watermark image, it is first encrypted by Arnold transform, which improves the security of the algorithm. And then, it is also transformed into one-dimensional signal correspondingly. A repeated embedding strategy is used in the embedding process to improve the algorithm's robustness. The final watermarked image can be reconstructed by the inverse Hilbert curve transform after integrating the modified first IMF, the remaining IMFs, and the residual. To improve the security and reduce the length of the key, Arnold transform and Huffman coding are adopted. The watermark extraction is the inverse of the embedding process without using the host image and watermark image. Comprehensive experimental results confirm that our new algorithm exhibits good robustness, efficiency, and high imperceptibility. Compared with the actual watermarking algorithms, the newly proposed watermarking algorithm not only reduces the computational expense, but also shows better performance in combating the cropping attacks, Gaussian noise, median filter, image enhancement attacks, etc. [ABSTRACT FROM AUTHOR]

To improve the resistance to geometric rotation attacks and to solve the problem of high computational complexity of existing watermarking algorithms, a novel efficient and robust zero watermarking algorithm in spatial domain is proposed. First, the central pixels of different channels of colorful host image are taken as the center of the circle, and the features of the image are constructed by the pixels covered by rings with different radius and width. The binary feature image is obtained by binary operation on the constructed image features. Then, the zero watermark image is constructed by XOR operation for the scrambled binary feature image and copyright watermark image encrypted Logistic chaotic algorithm. Finally, the zero watermark image is stored in the intellectual property database for copyright certification in possible copyright disputes. Experimental results show that the proposed algorithm is robust to geometric rotation attacks and common image processing attacks. Compared with similar zero watermarking schemes, the proposed algorithm has lower computational complexity and better robustness. [ABSTRACT FROM AUTHOR]

In the research of the wheelset's hunting oscillation, it is found that if the wheel–rail geometric contact is nonlinear, the wheelset oscillation will produce the high-order odd harmonic frequencies (HOHFs) besides the hunting fundamental frequency. In the existing literature, the HOHFs are rarely discussed. Based on the Klingel's linear model, the kinematics model of a wheel–rail nonlinear geometric contact system is established, and equation analysis proves that there are only odd harmonics in the hunting oscillation without even harmonics. The HOHFs energy is concentrated in the strongly nonlinear zone of wheel–rail geometric contact, which is an important manifestation of the wheel–rail hunting impact. The numerical simulations of an isolated wheelset model and a complete vehicle model are conducted to study the HOHFs performance on the vibration of the wheelset and bogie frame. The results show that the HOHFs can produce the lateral vibration responses of the bogie frame, such as the 3rd harmonic, and track irregularity and primary suspension can disturb or restrain the HOHFs vibration response, such as the 5th and 7th harmonics. The wheel–rail nonlinear kinematics model proposed in this paper is an extension to the classical Klingel's linear model. Like the hunting fundamental frequency, the HOHFs perform as the sources of the self-excited oscillation in rail vehicles, which is of great significance to the research of the train hunting instability and its condition monitoring methods. [ABSTRACT FROM AUTHOR]

A novel robust zero-watermarking algorithm for medical images is presented in this paper. The multi-scale decomposition of bi-dimensional empirical mode decomposition (BEMD) has exhibited many attractive properties that enable the proposed algorithm to robustly detect the tampering regions and protect the copyright of medical images simultaneously. Given a medical image, we first decompose a medical image adaptively into a finite number of intrinsic mode functions (IMFs) and a residue, by taking a full advantage of BEMD. The first IMF starts with the finest scale retaining fragile information and is best suitable for tampering detection, while the residue includes robust information at the coarser scale and is applied to the protection of intellectual property rights of medical images. Next, the feature matrices are extracted from the first IMF and the residue via singular value decomposition, which achieves robust performance subject to most attacks. For a given watermark image, it is encrypted by Arnold transform to enhance the security of the watermark. Then, the feature images are constructed by performing the exclusive-or operation between the encrypted watermark image and the extracted feature matrices. Finally, the feature images are securely stored in the copyright authentication database to be further used for copyright authentication and tampering detection. A large number of experimental results and comparisons with existing watermarking algorithms confirm that the newly proposed watermarking algorithm not only has strong ability on tampering detection, but also has better performance in combating various attacks, including cropping, Gaussian noise, median filtering, image enhancement attacks, etc. The newly developed algorithm also shows great promise in processing natural images. [ABSTRACT FROM AUTHOR]

This study explored the relationship between immunological status and clinical characteristics of aplastic anemia (AA) patients to plasma aluminum levels, which were increased after constant exposure to high levels of this metal. Sixty-two AA patients (33 cases with high and 29 cases with low or no exposure to aluminum) and 30 healthy controls were selected for this study. Aluminum in human albumin solution was measured by inductivity coupled plasma mass spectrometry. IL-10, IL-12, IL-17, and INF-γ levels were measured by enzyme-linked immunosorbent assay. The distribution of lymphocyte subsets were determined by flow cytometry. The expression levels of immunoglobulins and complement C3 and C4 were also measured. Exposure to high aluminum raised the levels of serum aluminum in AA patients (P < 0.01). The levels of hemoglobin and complement C4 were lower in AA patients with high aluminum exposure (P < 0.05 and < 0.01, respectively). The percentage of CD4+ T cells and the ratio of CD4+/ CD8+T cells in peripheral blood in AA patients with high aluminum exposure were higher compared with control AA patients (P < 0.05 in both cases), while the percentage of CD8+ T cells was significantly lower than that in non-aluminum–exposed AA patients (P < 0.05). Compared with non-aluminum–exposed AA patients, the level of IL-10 in the high aluminum–exposed AA group was significantly higher (P < 0.05 in both cases). The immunological and clinical characteristics of AA patients from regions of high aluminum exposure are different to those in from non-aluminum areas. These results suggest that high aluminum exposure alters the immune system in patients suffering from AA. [ABSTRACT FROM AUTHOR]

In this paper, a robust and blind image watermarking algorithm via circular embedding and bidimensional empirical mode decomposition (BEMD) is developed. First, the watermark image is scrambled by Arnold transform to increase the security of the algorithm. Second, the Hilbert curve is adopted to reduce the scrambled 2D watermark image to one-dimensional watermark signal. Third, the host image is decomposed by BEMD to obtain the multi-scale representation in the forms of intrinsic mode functions (IMFs) and a residue. Then, the extreme points of the IMFs are extracted as the embedding locations. Finally, the one-dimensional watermark signal is repeatedly and cyclically embedded in the extreme locations of the first IMF according to the texture masking characteristics of the human visual system, which greatly improves the ability of our algorithm against various attacks. The final watermarked image is reconstructed by combining the modified first IMF and the residual. The watermark can be successfully extracted without resorting to the original host image. Furthermore, image correction can be applied before image watermarking extraction if there are geometric attacks in watermarked image. A large number of experimental results and thorough evaluations confirm that our method can obtain higher imperceptibility and robustness under different types of attacks, and achieve better performance than the current state-of-the-art watermarking algorithms, especially in large-scale cropping attack, JPEG compression, Gaussian noise, sharpening, Gamma correction, scaling, histogram equalization, and rotation attacks. [ABSTRACT FROM AUTHOR]

By analyzing the gas occurrence, it is found that ground stress plays a leading role in coal and gas outburst in eastern coal mines of Nos. 8, 10 and 12 in Pingdingshan Mining Area where show the most serious outburst hazards. According to the isograms of coal seam depth in F Group, the relationship between the distributions of the fold tectonic stress and the coal and gas outburst was simulated using the ANSYS program. The result shows that the stress concentrates near to the fault and the outcrop of the fault enhances the possibility of gas outburst. The shear stress in the north of the anticline is greater than that in the south. The shear stress direction on the north wing of the anticline is dextral and the coal seam in this area exhibits highest possibility for gas outburst. However, on the surrounding rock, the shear stress direction on the north wing of the anticline is sinistral. The regions with fold tectonic stress ranging from 1.44 to 4.47 MPa correspond to the sites with high risk of gas outburst. Ground stress is the main factor controlling the coal and gas outburst in the three mines. Currently, the distribution of coal and gas outburst in the three mines is in agreement with that of coal shear stress. [ABSTRACT FROM AUTHOR]

Finally, we compare our algorithm with the SOTA embedding-based watermarking algorithms and zero-watermarking algorithms to further demonstrate the advantages of the proposed algorithm. The following text should not be included in the figure legend of figure 3 but below the heading "5 Experimental results": In this section, we first discuss the image and parameter selection as well as the metrics used to evaluate the performance of the watermarking algorithms. [Extracted from the article]

Empirical Mode Decomposition (EMD) has proved to be an effective and powerful analytical tool for non-stationary time series and starts to exhibit its modeling potential for 3D geometry analysis. Yet, existing EMD-based geometry processing algorithms only concentrate on multi-scale data decomposition by way of computing intrinsic mode functions. More in-depth analytical properties, such as Hilbert spectra, are hard to study for 3D surface signals due to the lack of theoretical and algorithmic tools. This has hindered much more broader penetration of EMD-centric algorithms into various new applications on 3D surface. To tackle this challenge, in this paper we propose a novel and efficient EMD and Hilbert spectra computational scheme for 3D geometry processing and analysis. At the core of our scheme is the strategy of dimensionality reduction via space-filling curve. This strategy transforms the problem of 3D geometry analysis to 1D time series processing, leading to two major advantages. First, the envelope computation is carried out for 1D signal by cubic spline interpolation, which is much faster than existing envelope computation directly over 3D surface. Second, it enables us to calculate Hilbert spectra directly on 3D surface. We could take advantages of Hilbert spectra that contain a wealth of unexploited properties and utilize them as a viable indicator to guide our EMD-based 3D surface processing. Furthermore, to preserve sharp features, we develop a divide-and-conquer scheme of EMD by explicitly separating the feature signals from non-feature signals. Extensive experiments have been carried out to demonstrate that our new EMD and Hilbert spectra based method is both fast and powerful for 3D surface processing and analysis. [ABSTRACT FROM AUTHOR]

The article High-Dose Aluminum Exposure Further Alerts Immune Phenotype in Aplastic Anemia Patients, written by Yao Zuo, Xiang Lu, Xiaochao Wang, Suren R. Sooranna, Liju Tao, Shiqiang Chen, Hongwen Li, Dan Huang, Guanye Nai, Hong Chen, Chunfeng Pan, Caihong Huang and Yanmin Pang. [ABSTRACT FROM AUTHOR]

The publication of this article unfortunately contained mistakes. The affiliation and the biography of Ling Du were not correct. The corrected affiliation and bibliography is given below. [ABSTRACT FROM AUTHOR]