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Adverse early life experiences, such as maternal separation, are associated with an increased risk for several mental health problems. Symptoms induced by maternal separation that mirror clinically relevant aspects of mental problems, such as cognitive inflexibility, open the possibility of testing putative therapeutics prior to clinical development. Although several animal (e.g., rodent) studies have evaluated the effects of early maternal separation on cognitive flexibility, no consistent conclusions have been drawn. To clarify this issue, in this study, a meta-analysis method was used to systematically explore the relationship between early maternal separation and cognitive flexibility in rodent offspring. Results indicate that early maternal separation could significantly impair cognitive flexibility in rodent offspring. Moderator analyses further showed that the relationship between early maternal separation and cognitive flexibility was not consistent in any case, but was moderated by variations in the experimental procedures, such as the deprivation levels, task characteristics, and rodent strains. These clarify the inconsistent effects of maternal separation on cognitive flexibility in rodents and help us better understand the association between early life adversity and cognitive development.

In Malik et al.'s method, each pixel can be embedded with log23 bits by being modified at most 1. Thus, their method achieves significant hiding capacity while maintaining good visual quality. However, in their method, the first lower and the first upper quantization levels must be excluded from data embedding in order to ensure reversibility. To this end, we propose a two-layer reversible data hiding (RDH) scheme in combination with (7,4) Hamming code. In the 1st-layer embedding, each block can be embedded with 16 bits. In the 2nd-layer embedding, each already-modified block can carry 6 bits or 12 bits by taking advantage of (7,4) Hamming code that hides three bits by modifying only one bit. At most 2-bit additional information is needed to help decoders to correctly extract the original lower and upper quantization levels. By means of two-layer embedding, our method achieves higher embedding capacity while maintaining almost the same visual quality, compared with Malik et al.'s method. Experimental results also demonstrate our effectivity.

The main purpose of data hiding is to hide secret data imperceptibly into multimedia, ensuring secure data transmission. Existing magic matrix-based data hiding schemes cannot achieve satisfactory visual quality for a given low payload because they adopt a single-layer embedding (i.e., the fixed-sized reference matrix (RM) embedding), rather than adaptive multi-layer embedding (i.e., variable-sized RM embedding). To this end, we propose an adaptive data hiding scheme by constructing multi-layer RM using mini-Sudoku. Our scheme can adjust the number of layers (e.g., one, two, or more) of the RM to obtain the desired payload (i.e., low, moderate, or large payloads). In addition, our method also has the capability of obtaining the optimal number of layers of RM achieving the highest visual quality for a given payload. For each pixel pair, our scheme selects the optimal pair having the smallest Euclidean distance with this pair as its stego pair, resulting in a large decrease in distortion. Experimental results show that our proposed scheme can obtain various payloads, and more importantly, it can achieve better or comparable rate-distortion performance than several existing magic matrix-based data hiding schemes.

The purpose of the image quality assessment is to evaluate image quality consistently with human's subjective evaluation. In image quality assessment, many structural features have been used to measure the quality degradation of an image. However, most of the existing image quality assessment methods are block-based, which ignores the features among neighboring blocks. In this paper, we argue that the human visual system perceives distortions not only depends on local structural (intra-block structure) distortions, but also relates to the structural distortions of their neighborhoods (inter-block texture). Based on this insight, we propose a novel image quality assessment method, called the diffusion speed structure similarity (DSSIM), by considering both intra-block structure and inter-block texture. Specifically, to characterize the inter-block texture, we devise a novel visual feature based on the image diffusion speed. To measure the changes of the intra-block structure, we adopt the image gradient magnitude. Furthermore, to differentiate the importance of a local region, we devise a weighting function based on the image diffusion speed. Extensive experimental results on six benchmark databases demonstrate that our proposed method yields a better performance than the state-of-the-art methods.

K-pass pixel value ordering (PVO) is an effective reversible data hiding (RDH) technique. In k-pass PVO, the complexity measurement may lead to a weak estimation result because the unaltered pixels in a block are excluded to estimate block complexity. In addition, the prediction-error is computed without considering the location relationship of the second largest and largest pixels or the second smallest and smallest pixels. To this end, an improved RDH technique is proposed in this paper to enhance the embedding performance. The improvement mainly lies in the following two aspects. First, some pixels in a block, which are excluded from data hiding in some existing RDH methods, are exploited together with the neighborhood surrounding this block to increase the estimation accuracy of local complexity. Second, the remaining pixels in a block, i.e., three largest and three smallest pixels are involved in data embedding. Taking three largest pixels for example, when the difference between the largest and third largest pixels is relatively large (e.g., > 1), we improve k-pass PVO by considering the location relationship of the second largest and largest pixels. The advantage of doing this is that the difference valued 3 between the maximum and the second largest pixel which is shifted in k-pass PVO, is able to carry 1 bit data in our method. In other words, a larger amount of pixels are able to carry data bits in our scheme compared with k-pass PVO. Abundant experimental results reveal that the proposed method achieves preferable embedding performance compared with the previous work, especially when a larger payload is required.

BIT technology is an important means of system and equipment fault detection, location and isolation. This paper takes the digital NBC protection system as the research object, and carries out research on the optimization design based on BIT technology. Based on the structural division of the digital NBC protection systems and the analysis of typical failure modes, combined with the weighted cost index function and the selection method of the improved special hierarchically optimized optimal test set, the calculation and comparison of the indices of the actual digitalized NBC protection systems was conducted. Determine the optimal test set, and finally design the BIT circuit for the selected optimal test set.