A Novel Image-Encryption Scheme Based on a Non-Linear Cross-Coupled Hyperchaotic System with the Dynamic Correlation of Plaintext Pixels.

Based on a logistic map and Feigenbaum map, we proposed a logistic Feigenbaum non-linear cross-coupled hyperchaotic map (LF-NCHM) model. Experimental verification showed that the system is a hyperchaotic system. Compared with the existing cross-coupled mapping, LF-NCHM demonstrated a wider hyperchaotic range, better ergodicity and richer dynamic behavior. A hyperchaotic sequence with the same number of image pixels was generated by LF-NCHM, and a novel image-encryption algorithm with permutation that is dynamically related to plaintext pixels was proposed. In the scrambling stage, the position of the first scrambled pixel was related to the sum of the plaintext pixel values, and the positions of the remaining scrambled pixels were related to the pixel values after the previous scrambling. The scrambling operation also had a certain diffusion effect. In the diffusion phase, using the same chaotic sequence as in the scrambling stage increased the usage rate of the hyperchaotic sequence and improved the calculation efficiency of the algorithm. A large number of experimental simulations and cryptanalyses were performed, and the results proved that the algorithm had outstanding security and extremely high encryption efficiency. In addition, LF-NCHM could effectively resist statistical analysis attacks, differential attacks and chosen-plaintext attacks.

TransZero++: Cross Attribute-Guided Transformer for Zero-Shot Learning.

Zero-shot learning (ZSL) tackles the novel class recognition problem by transferring semantic knowledge from seen classes to unseen ones. Semantic knowledge is typically represented by attribute descriptions shared between different classes, which act as strong priors for localizing object attributes that represent discriminative region features, enabling significant and sufficient visual-semantic interaction for advancing ZSL. Existing attention-based models have struggled to learn inferior region features in a single image by solely using unidirectional attention, which ignore the transferable and discriminative attribute localization of visual features for representing the key semantic knowledge for effective knowledge transfer in ZSL. In this paper, we propose a cross attribute-guided Transformer network, termed TransZero++, to refine visual features and learn accurate attribute localization for key semantic knowledge representations in ZSL. Specifically, TransZero++ employs an attribute → visual Transformer sub-net (AVT) and a visual → attribute Transformer sub-net (VAT) to learn attribute-based visual features and visual-based attribute features, respectively. By further introducing feature-level and prediction-level semantical collaborative losses, the two attribute-guided transformers teach each other to learn semantic-augmented visual embeddings for key semantic knowledge representations via semantical collaborative learning. Finally, the semantic-augmented visual embeddings learned by AVT and VAT are fused to conduct desirable visual-semantic interaction cooperated with class semantic vectors for ZSL classification. Extensive experiments show that TransZero++ achieves the new state-of-the-art results on three golden ZSL benchmarks and on the large-scale ImageNet dataset. The project website is available at: https://shiming-chen.github.io/TransZero-pp/TransZero-pp.html.

[Effect of RNA interference of CD59 gene on proliferation of non-small cell lung cancer cell line GLC-P in vitro].

OBJECTIVE: To investigate the effect of CD59 gene inhibition mediated by RNA interference on the proliferation and apoptosis of non-small cell lung cancer (NSCLC) GLC-P cells in vitro. METHODS: Recombinant plasmids for RNA interference of CD59 gene were constructed and transfected into GLC-P cells via lipofectamine 2000. The stably transfected cells were examined with real-time RT-PCR, MTT assay and enzyme-linked immunosorbent assay to investigate the changes in cell proliferation and apoptosis. RESULTS: Compared with the control cells, the cells transfected with CD59-siRNA showed significantly decreased expression levels of CD59 mRNA (P<0.05) and significantly inhibited cell proliferation. CONCLUSION: CD59 gene is highly expressed in NSCLC and RNA interference-mediated CD59 silencing can strongly inhibit the proliferation and induce apoptosis in GLC-P cells, which shed light on a potentially new target for targeted gene therapy of NSCLC.

[miRNA-144 in the saliva is a genetic marker for early diagnosis of esophageal cancer].

OBJECTIVE: To investigate the presence of miRNA-144 in the saliva of patients with esophageal cancer and its value for early diagnosis of esophageal cancer. METHODS: Saliva samples were collected form patients with esophageal cancer admitted in the Fourth Affiliated Hospital of Jinan University and the First Affiliated Hospital of Guangzhou Medical College between January, 2011 and May, 2013, with saliva samples from 50 middle-aged healthy volunteers matched for age and gender ratio as the control group. The contents of miRNA-144 in the samples were detected with RT-PCR. RESULTS: The levels of miRNA-144 in both the whole saliva and saliva supernatant were significantly higher in esophageal cancer group than in the control group (P<0.05). In the whole saliva, the cut-off point of miRNA-144 was ≥100, with a sensitivity of 74.6% and a specificity of 92.0% for esophageal cancer diagnosis (Az=0.865); in saliva supernatant, the cut-off point was ≥20 with a sensitivity of 53.7% and a specificity of 94.0% (Az=0.754), suggesting a moderate diagnostic value of miRNA-144 in whole saliva and saliva supernatant. CONCLUSION: miRNA-144 is highly expressed in the saliva of patients with esophageal cancer and can be used as a genetic marker for early diagnosis of esophageal cancer.