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Monocular depth estimation aims to infer a depth map from a single image. Although supervised learning-based methods have achieved remarkable performance, they generally rely on a large amount of labor-intensively annotated data. Self-supervised methods, on the other hand, do not require any annotation of ground-truth depth and have recently attracted increasing attention. In this work, we propose a self-supervised monocular depth estimation network via binocular geometric correlation learning. Specifically, considering the inter-view geometric correlation, a binocular cue prediction module is presented to generate the auxiliary vision cue for the self-supervised learning of monocular depth estimation. Then, to deal with the occlusion in depth estimation, an occlusion interference attenuated constraint is developed to guide the supervision of the network by inferring the occlusion region and producing paired occlusion masks. Experimental results on two popular benchmark datasets have demonstrated that the proposed network obtains competitive results compared to state-of-the-art self-supervised methods and achieves comparable results to some popular supervised methods. [ABSTRACT FROM AUTHOR]

Recently, deep learning‐based stereo matching has achieved great success. However, models trained on the source domain dataset encounter substantial performance degradation when directly tested on an unseen target domain dataset because of neglecting the generalization to out‐of‐distribution (OOD) stereo samples. This paper proposes a stereo sample generation‐based domain generalization network (SGDG‐Net) for stereo matching. Specifically, to expand the distribution span of training samples, OOD stereo samples are generated to assist training. To effectively generate OOD left samples, a style transfer‐based generation mechanism is proposed to transmit perturbations to the source left samples. In addition, to generate the OOD right samples, a disparity‐assisted generation strategy is proposed by using disparity map labels as auxiliary information. Experimental results demonstrate that the proposed SGDG‐Net produces remarkable results on four benchmark datasets. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) can provide multi-modality MR images by setting task-specific scan parameters, and has been widely used in various disease diagnosis and planned treatments. However, in practical clinical applications, it is often difficult to obtain multi-modality MR images simultaneously due to patient discomfort, and scanning costs, etc. Therefore, how to effectively utilize the existing modality images to synthesize missing modality image has become a hot research topic. In this paper, we propose a novel confidence-guided aggregation and cross-modality refinement network (CACR-Net) for multi-modality MR image synthesis, which effectively utilizes complementary and correlative information of multiple modalities to synthesize high-quality target-modality images. Specifically, to effectively utilize the complementary modality-specific characteristics, a confidence-guided aggregation module is proposed to adaptively aggregate the multiple target-modality images generated from multiple source-modality images by using the corresponding confidence maps. Based on the aggregated target-modality image, a cross-modality refinement module is presented to further refine the target-modality image by mining correlative information among the multiple source-modality images and aggregated target-modality image. By training the proposed CACR-Net in an end-to-end manner, high-quality and sharp target-modality MR images are effectively synthesized. Experimental results on the widely used benchmark demonstrate that the proposed method outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Sex-specific markers play an important role in revealing sex-determination mechanism. Sea urchin (Mesocentrotus nudus) is an economically important mariculture species in several Asian countries and its gonads are the sole edible parts for people. However, growth rate and immunocompetence differ by sex in this species, sex-specific markers have not been identified, and the sex-determination mechanism of sea urchin remains undetermined. In this study, type IIB endonuclease restriction-site associated DNA sequencing (2b-RAD-seq) and a genome survey of M. nudus were performed, and three female-specific markers and three female heterogametic single nucleotide polymorphism (SNP) loci were identified. We validated these sex-specific markers via PCR amplification in a large number of individuals, including wild and artificially bred populations. Several open reading frames (ORFs) were predicted, although there are no potential genes known for sex determination and sex differentiation within the scaffold in which the sex-specific markers are located. Importantly, the female-specific sequences and female heterozygous SNP loci indicate that a female heterogametic and male homogametic ZW/ZZ sex-determination system should exist in M. nudus. The results provide a solid basis for revealing the sex-determination mechanism of this species, and open up new possibilities for developing sex-control breeding in sea urchin. [ABSTRACT FROM AUTHOR]

Sea urchin (Mseocentrotus nudus) is an economically important mariculture species in several Asian countries. The growth rate and immunocompetence differ by sex in this species. However, the mechanisms of sex determination in M. nudus have remain unclear. In the present study, we focus on the dmrt1 gene of M. nudus (Mndmrt1) to investigate its dynamic expression pattern during different developmental stages. Real-time quantitative PCR (RT-qPCR) revealed that Mndmrt1 exhibits testis-specific expression and undetectable during the whole embryogenesis. With the development of ontogenetic, Mndmrt1 transcripts are first detected at 9 months post-fertilization (mpf). In addition, both the transcripts and protein of Mndmrt1 gene were specifically expressed in spermatogonia and spermatocytes, indicating that it might be a male germ cells marker in sea urchin. Significantly, the 1441 bp promoter sequence of Mndmrt1 gene was obtained by DNA walking, and one positive regulatory region at −1197/ −968 in the promoter, as well as one negative regulatory region at −1441/ −1198 have been identified by promoter activity analysis. Moreover, two regulatory regions contain multiple putative binding sites for transcription factors, including Sp1, Egr1, Sox5, CEBP, GATA and SRY. These findings suggest that Mndmrt1 may be related to testis differentiation and spermatogenesis in sea urchin and will provide an insight into understanding the regulatory mechanism of the dmrt1 gene. [Display omitted] • Mndmrt1 exhibits testis-specific expression. • Mndmrt1 is a male germ cells marker in sea urchin. • Two regulatory regions have been identified in the promoter of Mndmrt1. [ABSTRACT FROM AUTHOR]

To test whether electromyogram (EMG) is nonlinear deterministic signal or just random noise, we analyzed four EMGs data of an adult woman. EMG is assessed with the correlation dimension (D2), maximum Lyapunov exponent (λ1), approximate entropy(ApEn), recurrence plot analysis (RPA) and recurrence quantification analysis (RQA). From all the results of these assessments we can conclude that EMG obeys a certain nonlinear deterministic law and nonstationarity is significant within this signal.