An Explicit Method for Fast Monocular Depth Recovery in Corridor Environments

Monocular cameras are extensively employed in indoor robotics, but their performance is limited in visual odometry, depth estimation, and related applications due to the absence of scale information.Depth estimation refers to the process of estimating a dense depth map from the corresponding input image, existing researchers mostly address this issue through deep learning-based approaches, yet their inference speed is slow, leading to poor real-time capabilities. To tackle this challenge, we propose an explicit method for rapid monocular depth recovery specifically designed for corridor environments, leveraging the principles of nonlinear optimization. We adopt the virtual camera assumption to make full use of the prior geometric features of the scene. The depth estimation problem is transformed into an optimization problem by minimizing the geometric residual. Furthermore, a novel depth plane construction technique is introduced to categorize spatial points based on their possible depths, facilitating swift depth estimation in enclosed structural scenarios, such as corridors. We also propose a new corridor dataset, named Corr\_EH\_z, which contains images as captured by the UGV camera of a variety of corridors. An exhaustive set of experiments in different corridors reveal the efficacy of the proposed algorithm.Comment: 10 pages, 8 figures. arXiv admin note: text overlap with arXiv:2111.08600 by other author

Gold Nanopyramid Arrays for Non-Invasive Surface-Enhanced Raman Spectroscopy-Based Gastric Cancer Detection via sEVs.

Gastric cancer (GC) is one of the most common and lethal types of cancer affecting over one million people, leading to 768,793 deaths globally in 2020 alone. The key for improving the survival rate lies in reliable screening and early diagnosis. Existing techniques including barium-meal gastric photofluorography and upper endoscopy can be costly and time-consuming and are thus impractical for population screening. We look instead for small extracellular vesicles (sEVs, currently also referred as exosomes) sized ⌀ 30-150 nm as a candidate. sEVs have attracted a significantly higher level of attention during the past decade or two because of their potentials in disease diagnoses and therapeutics. Here, we report that the composition information of the collective Raman-active bonds inside sEVs of human donors obtained by surface-enhanced Raman spectroscopy (SERS) holds the potential for non-invasive GC detection. SERS was triggered by the substrate of gold nanopyramid arrays we developed previously. A machine learning-based spectral feature analysis algorithm was developed for objectively distinguishing the cancer-derived sEVs from those of the non-cancer sub-population. sEVs from the tissue, blood, and saliva of GC patients and non-GC participants were collected (n = 15 each) and analyzed. The algorithm prediction accuracies were reportedly 90, 85, and 72%. Leave-a-pair-of-samples out validation was further performed to test the clinical potential. The area under the curve of each receiver operating characteristic curve was 0.96, 0.91, and 0.65 in tissue, blood, and saliva, respectively. In addition, by comparing the SERS fingerprints of individual vesicles, we provided a possible way of tracing the biogenesis pathways of patient-specific sEVs from tissue to blood to saliva. The methodology involved in this study is expected to be amenable for non-invasive detection of diseases other than GC

Mobile zinc increases rapidly in the retina after optic nerve injury and regulates ganglion cell survival and optic nerve regeneration

Retinal ganglion cells (RGCs), the projection neurons of the eye, cannot regenerate their axons once the optic nerve has been injured and soon begin to die. Whereas RGC death and regenerative failure are widely viewed as being cell-autonomous or influenced by various types of glia, we report here that the dysregulation of mobile zinc (Zn²⁺) in retinal interneurons is a primary factor. Within an hour after the optic nerve is injured, Zn²⁺ increases several-fold in retinal amacrine cell processes and continues to rise over the first day, then transfers slowly to RGCs via vesicular release. Zn²⁺ accumulation in amacrine cell processes involves the Zn²⁺ transporter protein ZnT-3, and deletion of slc30a3, the gene encoding ZnT-3, promotes RGC survival and axon regeneration. Intravitreal injection of Zn²⁺ chelators enables many RGCs to survive for months after nerve injury and regenerate axons, and enhances the prosurvival and regenerative effects of deleting the gene for phosphatase and tensin homolog (pten). Importantly, the therapeutic window for Zn²⁺ chelation extends for several days after nerve injury. These results show that retinal Zn²⁺ dysregulation is a major factor limiting the survival and regenerative capacity of injured RGCs, and point to Zn²⁺ chelation as a strategy to promote long-term RGC protection and enhance axon regeneration