An Efficient Feature Extraction Scheme for Mobile Anti-Shake in Augmented Reality

In recent years, augmented reality on mobile devices has become popular. Mobile shakes are the most typical type of interference in mobile augmented reality. To negate such interference, anti-shake is an urgent requirement. To enhance anti-shake efficiency, we propose an efficient feature extraction scheme for mobile anti-shake in augmented reality. The scheme directly detects corners to avoid the non-extreme constraint such that the efficiency of feature extraction is improved. Meanwhile, the scheme only updates the added corners during mobile shakes, which improves the accuracy of feature extraction. In the experiments, the memory consumption of existing methods is almost double compared to that in our scheme. Further, the runtime of our scheme is only half of the runtime of the existing methods. The experimental results demonstrate that our scheme performs better than the existing classic methods on mobile anti-shake in terms of memory consumption, efficiency, and accuracy

Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine

Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE) technique. Firstly, the extreme learning machine (ELM) with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED) predictor and gradient-adjusted predictor (GAP), the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches

An Efficient Top-k Query Scheme Based on Multilayer Grouping

The top-k query is to find the k data that has the highest scores from a candidate dataset. Sorting is a common method to find out top-k results. However, most of existing methods are not efficient enough. To remove this issue, we propose an efficient top-k query scheme based on multilayer grouping. First, we find the reference item by computing the average score of the candidate dataset. Second, we group the candidate dataset into three datasets: winner set, middle set and loser set based on the reference item. Third, we further group the winner set to the second-layer three datasets according to k value. And so on, until the data number of winner set is close to k value. Meanwhile, if k value is larger than the data number of winner set, we directly return the winner set to the user as a part of top-k results almost without sorting. In this case, we also return the top results with the highest scores from the middle set almost without sorting. Based on above innovations, we almost minimize the sorting. Experimental results show that our scheme significantly outperforms the current classical method on the performance of memory consumption and top-k query

The Insertion/Deletion Polymorphism of the Angiotensin Converting Enzyme (ACE) in Parkinson’s Disease

Parkinson’s disease (PDI is a neurodegenerative disorder of unknown etiology. Both genetic and environmental factors are thought to be implicated to some extent. The ACE gene insertion/deletion (I/D) polymorphism has been associated with common neurodegenerative disorders that share similar clinical and neuropathological features with PD (Alzheimer’s disease). In this study we set out to examine the role of the ACE gene insertion/deletion (I/D) polymorphism in Parkinson’s disease (PD)

Guanylyl cyclase activation reverses resistive breathing–induced lung injury and inflammation

Inspiratory resistive breathing (RB), encountered in obstructive lung diseases, induces lung injury. The soluble guanylyl cyclase (sGC)/cyclic guanosine monophosphate (cGMP) pathway is down-regulated in chronic and acute animal models of RB, such as asthma, chronic obstructive pulmonary disease, and in endotoxin-induced acute lung injury. Our objectives were to: (1) characterize the effects of increased concurrent inspiratory and expiratory resistance in mice via tracheal banding; and (2) investigate the contribution of the sGC/cGMP pathway in RB-induced lung injury. Anesthetized C57BL/6 mice underwent RB achieved by restricting tracheal surface area to 50% (tracheal banding). RB for 24 hours resulted in increased bronchoalveolar lavage fluid cellularity and protein content, marked leukocyte infiltration in the lungs, and perturbed respiratory mechanics (increased tissue resistance and elasticity, shifted static pressure–volume curve right and downwards, decreased static compliance), consistent with the presence of acute lung injury. RB down-regulated sGC expression in the lung. All manifestations of lung injury caused by RB were exacerbated by the administration of the sGC inhibitor, 1H-[1,2,4]oxodiazolo[4,3-]quinoxalin-l-one, or when RB was performed using sGCα1 knockout mice. Conversely, restoration of sGC signaling by prior administration of the sGC activator BAY 58-2667 (Bayer, Leverkusen, Germany) prevented RB-induced lung injury. Strikingly, direct pharmacological activation of sGC with BAY 58-2667 24 hours after RB reversed, within 6 hours, the established lung injury. These findings raise the possibility that pharmacological targeting of the sGC–cGMP axis could be used to ameliorate lung dysfunction in obstructive lung diseases

Characterization of Zur-dependent genes and direct Zur targets in Yersinia pestis

<p>Abstract</p> <p>Background</p> <p>The zinc uptake regulator Zur is a Zn²⁺-sensing metalloregulatory protein involved in the maintenance of bacterial zinc homeostasis. Up to now, regulation of zinc homeostasis by Zur is poorly understood in <it>Y. pestis</it>.</p> <p>Results</p> <p>We constructed a <it>zur </it>null mutant of <it>Y. pestis </it>biovar <it>microtus </it>strain 201. Microarray expression analysis disclosed a set of 154 Zur-dependent genes of <it>Y. pestis </it>upon exposure to zinc rich condition. Real-time reverse transcription (RT)-PCR was subsequently used to validate the microarray data. Based on the 154 Zur-dependent genes, predicted regulatory Zur motifs were used to screen for potential direct Zur targets including three putative operons <it>znuA, znuCB </it>and <it>ykgM</it>-<it>RpmJ2</it>. The LacZ reporter fusion analysis verified that Zur greatly repressed the promoter activity of the above three operons. The subsequent electrophoretic mobility shift assay (EMSA) demonstrated that a purified Zur protein was able to bind to the promoter regions of the above three operons. The DNase I footprinting was used to identify the Zur binding sites for the above three operons, verifying the Zur box sequence as predicted previously in γ-Proteobacteria. The primer extension assay was further used to determine the transcription start sites for the above three operons and to localize the -10 and -35 elements. Zur binding sites overlapped the -10 sequence of its target promoters, which was consistent with the previous observation that Zur binding would block the entry of the RNA polymerase to repress the transcription of its target genes.</p> <p>Conclusion</p> <p>Zur as a repressor directly controls the transcription of <it>znuA, znuCB </it>and <it>ykgM</it>-<it>RpmJ2 </it>in <it>Y. pestis </it>by employing a conserved mechanism of Zur-promoter DNA association as observed in γ-Proteobacteria. Zur contributes to zinc homeostasis in <it>Y. pestis </it>likely through transcriptional repression of the high-affinity zinc uptake system ZnuACB and two alternative ribosomal proteins YkgM and RpmJ2.</p

Genome Characterization and Potential Risk Assessment of the Novel SARS-CoV-2 Variant Omicron (B.1.1.529)

As the novel coronavirus SARS-CoV-2 spread around the world, multiple waves of variants emerged, thus leading to local or global population shifts during the pandemic. A new variant named Omicron (PANGO lineage B.1.1.529), which was first discovered in southern Africa, has recently been proposed by the World Health Organization to be a Variant of Concern. This variant carries an unusually large number of mutations, particularly on the spike protein and receptor binding domain, in contrast to other known major variants. Some mutation sites are associated with enhanced viral transmission, infectivity, and pathogenicity, thus enabling the virus to evade the immune protective barrier. Given that the emergence of the Omicron variant was accompanied by a sharp increase in infection cases in South Africa, the variant has the potential to trigger a new global epidemic peak. Therefore, continual attention and a rapid response are required to decrease the possible risks to public health