Dynamic Objects Segmentation for Visual Localization in Urban Environments

Visual localization and mapping is a crucial capability to address many challenges in mobile robotics. It constitutes a robust, accurate and cost-effective approach for local and global pose estimation within prior maps. Yet, in highly dynamic environments, like crowded city streets, problems arise as major parts of the image can be covered by dynamic objects. Consequently, visual odometry pipelines often diverge and the localization systems malfunction as detected features are not consistent with the precomputed 3D model. In this work, we present an approach to automatically detect dynamic object instances to improve the robustness of vision-based localization and mapping in crowded environments. By training a convolutional neural network model with a combination of synthetic and real-world data, dynamic object instance masks are learned in a semi-supervised way. The real-world data can be collected with a standard camera and requires minimal further post-processing. Our experiments show that a wide range of dynamic objects can be reliably detected using the presented method. Promising performance is demonstrated on our own and also publicly available datasets, which also shows the generalization capabilities of this approach.Comment: 4 pages, submitted to the IROS 2018 Workshop "From Freezing to Jostling Robots: Current Challenges and New Paradigms for Safe Robot Navigation in Dense Crowds

Quantum Multicritical Behavior for Coupled Optical Cavities with Driven Laser Fields

Quantum phase transitions with multicritical points are fascinating phenomena occurring in interacting quantum many-body systems. However, multicritical points predicted by theory have been rarely verified experimentally; finding multicritical points with specific behaviors and realizing their control remains a challenging topic. Here, we propose a system that a quantized light field interacts with a two-level atomic ensemble coupled by microwave fields in optical cavities, which is described by a generalized Dicke model. Multicritical points for the superradiant quantum phase transition are shown to occur. We determine the number and position of these critical points and demonstrate that they can be effectively manipulated through the tuning of system parameters. Particularly, we find that the quantum critical points can evolve into a Lifshitz point if the Rabi frequency of the light field is modulated periodically in time. Remarkably, the texture of atomic pseudo-spins can be used to characterize the quantum critical behaviors of the system. The magnetic orders of the three phases around the Lifshitz point, represented by the atomic pseudo-spins, are similar to those of an axial next-nearest-neighboring Ising model. The results reported here are beneficial for unveiling intriguing physics of quantum phase transitions and pave the way towards to find novel quantum multicritical phenomena based on the generalized Dicke model

Genome-wide analyses of abiotic stress-related microRNAs and their targets in Arabidopsis thaliana

Abstract MicroRNAs (miRNAs) are known to regulate plant growth and development via regulating gene expression at both transcriptional and post-transcriptional levels. Although several miRNAs have been reported to be associated with abiotic stress responses in plant, systematic investigation of stress-related miRNAs and their targets in plants is limited. In this study, we systematically investigated stress-related miRNAs and their targets in Arabidopsis thaliana. We identified 94 putative stress-related miRNA genes, in which 8 miRNAs were new identified with stress-related response function based on targets prediction. Sequence analysis of these miRNA genes showed that most stress-related miRNAs possess TATA boxes in their promoters, and more than half contain at least two promoters. We also demonstrated that most stress-related miRNA genes contain stress-related elements in their promoters. Furthermore, conservation analysis showed that many stress-related miRNAs are species/family-specific and a subset of stress-related miRNAs may be derived from repeat sequences. Finally, we found that the stress-related miRNAs target 374 genes with 1,153 predicted target sites, of which 87.2% are targeted for gene cleavage and 12.8% affect protein translation. In conclusion, our findings provide an insight into both the function and evolution of stress-related miRNAs

Pedestrian-Aware Supervisory Control System Interactive Optimization of Connected Hybrid Electric Vehicles via Fuzzy Adaptive Cost Map and Bees Algorithm

Electrified vehicles are increasingly being seen as a means of mitigating the pressing concerns of traffic-related pollution. Due to the nature of engine-assisted vehicle exhaust systems, pedestrians in close proximity to these vehicles may experience events where specific emission concentrations are high enough to cause health effects. To minimize pedestrians’ exposure to vehicle emissions and pollutants nearby, we present a pedestrian-aware supervisory control system for connected hybrid electric vehicles by proposing an interactive optimization methodology. This optimization methodology combines a novel fuzzy adaptive cost map and the Bees Algorithm to optimize power-split control parameters. It enables the self-regulation of inter-objective weights of fuel and exhaust emissions based on the real-time pedestrian density information during the optimization process. The evaluation of the vehicle performance by using the proposed methodology is conducted on the realistic trip map involving pedestrian density information collected from the University College Dublin campus. Moreover, two bootstrap sampling techniques and effect of communication quality are both investigated in order to examine the robustness of the improved vehicle system. The results demonstrate that 14.42% mass of exhaust emissions can be reduced for the involved pedestrians, by using the developed fuzzy adaptive cost map

Convergence analysis of environmental efficiency from the perspective of environmental regulation: evidence from China

The aim of this paper is to analyze the impact of environmental regulation on regional environmental efficiency convergence using the fixed effects model and threshold regression model. The results show that the differences in environmental efficiency have a convergence trend in China, as well as in the eastern, central and western regions. The effect of environmental regulation on regional environmental efficiency is inhibition first and then promotion, research and development investment and outward foreign direct investment have a positive transmission effect; when environmental regulation intensity exceeds a certain threshold, the growth rate of environmental efficiency in the central and western regions will be significantly higher than that in the eastern regions

Inhibition of Stimulator of Interferon Genes Protects Against Myocardial Ischemia-Reperfusion Injury in Diabetic Mice

Background: Although the past decade has witnessed substantial scientific progress with the advent of cardioprotective pharmacological agents, most have failed to protect against myocardial ischemia/reperfusion (I/R) injury in diabetic hearts. This study was aimed at investigating the role of stimulator of interferon genes (STING) in I/R injury in diabetic mice and further exploring the underlying mechanisms. Methods: Type 2 diabetic mice were subjected to I/R or sham operation to investigate the role of STING. STING knockout mice were subjected to 30 minutes of ischemia followed by reperfusion for 24 hours. Finally, myocardial injury, cardiac function, and inflammation levels were assessed. Results: STING pathway activation was observed in diabetic I/R hearts, as evidenced by increased p-TBK and p-IRF3 expression. STING knockout significantly decreased the ischemic area and improved cardiac function after I/R in diabetic mice. STING knockout also elicited cardio-protective effects by decreasing serum cardiac troponin T and lactate dehydrogenase levels, thus diminishing the inflammatory response in the heart after I/R in diabetic mice. In vitro , STING inhibition decreased the expression of hypoxia-re-oxygenation-induced inflammatory cytokines. Conclusions: Targeting STING inhibits inflammation and prevents I/R injury in diabetic mice. Thus, STING may be a potential novel therapeutic target against myocardial I/R injury in diabetes