Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research.

Modeling the Ventral and Dorsal Cortical Visual Pathways Using Artificial Neural Networks

Although in conventional models of cortical processing, object recognition and spatial properties are processed separately in ventral and dorsal cortical visual pathways respectively, some recent studies have shown that representations associated with both objects' identity (of shape) and space are present in both visual pathways. However, it is still unclear whether the presence of identity and spatial properties in both pathways have functional roles. In our study, we have tried to answer this question through computational modeling. Our simulation results show that both a model ventral and dorsal pathway, separately trained to do object and spatial recognition, respectively, each actively retained information about both identity and space. In addition, we show that these networks retained different amounts and kinds of identity and spatial information. As a result, our modeling suggests that two separate cortical visual pathways for identity and space (1) actively retain information about both identity and space (2) retain information about identity and space differently and (3) that this differently retained information about identity and space in the two pathways may be necessary to accurately and optimally recognize and localize objects. Further, modeling results suggests these findings are robust and do not strongly depend on the specific structures of the neural networks.

Spatial Recognition Memory: Differential Brain Strategic Activation According to Sex

Human spatial memory research has significantly progressed since the development of computerized tasks, with many studies examining sex-related performances. However, few studies explore the underlying electrophysiological correlates according to sex. In this study event-related potentials were compared between male and female participants during the performance of an allocentric spatial recognition task. Twenty-nine university students took part in the research. Results showed that while general performance was similar in both sexes, the brain of males and females displayed a differential activation. Males showed increased N200 modulation than females in the three phases of memory process (encoding, maintenance, and retrieval). Meanwhile females showed increased activation of P300 in the three phases of memory process compared to males. In addition, females exhibited more negative slow wave (NSW) activity during the encoding phase. These differences are discussed in terms of attentional control and the allocation of attentional resources during spatial processing. Our findings demonstrate that sex modulates the resources recruited to performed this spatial task.

Spatial Recognition of Regional Maximum Floods in Ungauged Watersheds and Investigations of the Influence of Rainfall

This study primarily aims to develop a method for estimating the range of flood sizes in small and medium ungauged watersheds in local river streams. In practice, several water control projects have insufficient streamflow information. To compensate for the lack of data, the streamflow propagation method (SPM) provides streamflow information for ungauged watersheds. The ranges of flood sizes for ungauged watersheds were generated using a specific flood distribution analysis based on the obtained streamflow data. Furthermore, the influence of rainfall information was analyzed to characterize the patterns of specific flood distributions. Rainfall location, intensity, and duration highly affected the shape of the specific flood distribution. Concentrated rainfall locations affected the patterns of the maximum specific flood distribution. The shape and size of the minimum specific flood distribution were dependent on the rainfall intensity and duration. The Creager envelope curve was used to generate equations for the maximum/minimum specific flood distribution for the study site. The ranges of the specific flood distributions were produced for each watershed size.

Applying a novel visual-to-touch sensory substitution for studying tactile reference frames

Perceiving the spatial location and physical dimensions of touched objects is crucial for goal-directed actions. To achieve this, our brain transforms skin-based coordinates into a reference frame by integrating visual and posture information. In the current study, we examine the role of posture in mapping tactile sensations to a visual image. We developed a new visual-to-touch sensory substitution device that transforms images into a sequence of vibrations on the arm. 52 blindfolded participants performed spatial recognition tasks in three different arm postures and had to switch postures between trial blocks. As participants were not told which side of the device is down and which is up, they could choose how to map its vertical axis in their responses. Contrary to previous findings, we show that new proprioceptive inputs can be overridden in mapping tactile sensations. We discuss the results within the context of the spatial task and the various sensory contributions to the process.

Postconditioning with Sevoflurane or Propofol Alleviate Lipopolysaccharide-Induced Neuroinflammation, but Exert Dissimilar Effects on NR2B Subunit and Cognition

Neuroinflammation can cause cognitive deficits, and pre-existing neuroinflammation is very common in the clinic after trauma, surgery, and infection. Patients with pre-existing neuroinflammation often need further medical treatment under general anesthesia. However, it is still unknown the effects of postconditioning with general anesthetics on the pre-existing neuroinflammation. In this study, adult rats were post-treated with sevoflurane or propofol after intracerebroventricular administration of lipopolysaccharide. The effects of sevoflurane or propofol postconditioning on neuroinflammation-induced recognition memory deficit were detected. Our results found that postconditioning with sevoflurane, but not propofol reversed the selective spatial recognition memory impairment induced by neuroinflammation, and these differential effects did not appear to be associated with the similar anti-neuroinflammatory response of general anesthetics. However, postconditioning with propofol induced a selective long-lasting upregulation of extrasynaptic NR2B-containing NMDARs in the dorsal hippocampus, which down-regulated the CREB signaling pathway, and impaired spatial recognition memory. Additionally, the NR2B antagonists, memantine and Ro2506981, reversed this neurotoxicity induced by propofol postconditioning. Altogether, these results indicate that under the pre-existing neuroinflammation, postconditioning with sevoflurane can provide reliable neuroprotection through attenuating LPS-induced neuroinflammation, apoptosis, neuronal loss, and eventually improving spatial recognition deficit. However, although posttreatment with propofol also have the same anti-neuroinflammatory effects, the neurotoxicity caused by propofol postconditioning following neuroinflammation deserves to be continuously concerned.