S&Reg: End-to-End Learning-Based Model for Multi-Goal Path Planning Problem

In this paper, we propose a novel end-to-end approach for solving the multi-goal path planning problem in obstacle environments. Our proposed model, called S&Reg, integrates multi-task learning networks with a TSP solver and a path planner to quickly compute a closed and feasible path visiting all goals. Specifically, the model first predicts promising regions that potentially contain the optimal paths connecting two goals as a segmentation task. Simultaneously, estimations for pairwise distances between goals are conducted as a regression task by the neural networks, while the results construct a symmetric weight matrix for the TSP solver. Leveraging the TSP result, the path planner efficiently explores feasible paths guided by promising regions. We extensively evaluate the S&Reg model through simulations and compare it with the other sampling-based algorithms. The results demonstrate that our proposed model achieves superior performance in respect of computation time and solution cost, making it an effective solution for multi-goal path planning in obstacle environments. The proposed approach has the potential to be extended to other sampling-based algorithms for multi-goal path planning.Comment: 7 paegs, 12 figures. Accepted at IEEE International Conference on Robot and Human Interactive Communication (ROMAN), 202

PKE-RRT: Efficient Multi-Goal Path Finding Algorithm Driven by Multi-Task Learning Model

Multi-goal path finding (MGPF) aims to find a closed and collision-free path to visit a sequence of goals orderly. As a physical travelling salesman problem, an undirected complete graph with accurate weights is crucial for determining the visiting order. Lack of prior knowledge of local paths between vertices poses challenges in meeting the optimality and efficiency requirements of algorithms. In this study, a multi-task learning model designated Prior Knowledge Extraction (PKE), is designed to estimate the local path length between pairwise vertices as the weights of the graph. Simultaneously, a promising region and a guideline are predicted as heuristics for the path-finding process. Utilizing the outputs of the PKE model, a variant of Rapidly-exploring Random Tree (RRT) is proposed known as PKE-RRT. It effectively tackles the MGPF problem by a local planner incorporating a prioritized visiting order, which is obtained from the complete graph. Furthermore, the predicted region and guideline facilitate efficient exploration of the tree structure, enabling the algorithm to rapidly provide a sub-optimal solution. Extensive numerical experiments demonstrate the outstanding performance of the PKE-RRT for the MGPF problem with a different number of goals, in terms of calculation time, path cost, sample number, and success rate.Comment: 9 pages, 12 figure

The ancient phosphatidylinositol 3-kinase signaling system is a master regulator of energy and carbon metabolism in algae

Algae undergo a complete metabolic transformation under stress by arresting cell growth, inducing autophagy and hyperaccumulating biofuel precursors such as triacylglycerols and starch. However, the regulatory mechanisms behind this stress-induced transformation are still unclear. Here, we use biochemical, mutational, and “omics” approaches to demonstrate that PI3K signaling mediates the homeostasis of energy molecules and influences carbon metabolism in algae. In Chlamydomonas reinhardtii, the inhibition and knockdown (KD) of algal class III PI3K led to significantly decreased cell growth, altered cell morphology, and higher lipid and starch contents. Lipid profiling of wild-type and PI3K KD lines showed significantly reduced membrane lipid breakdown under nitrogen starvation (-N) in the KD. RNA-seq and network analyses showed that under -N conditions, the KD line carried out lipogenesis rather than lipid hydrolysis by initiating de novo fatty acid biosynthesis, which was supported by tricarboxylic acid cycle down-regulation and via acetyl-CoA synthesis from glycolysis. Remarkably, autophagic responses did not have primacy over inositide signaling in algae, unlike in mammals and vascular plants. The mutant displayed a fundamental shift in intracellular energy flux, analogous to that in tumor cells. The high free fatty acid levels and reduced mitochondrial ATP generation led to decreased cell viability. These results indicate that the PI3K signal transduction pathway is the metabolic gatekeeper restraining biofuel yields, thus maintaining fitness and viability under stress in algae. This study demonstrates the existence of homeostasis between starch and lipid synthesis controlled by lipid signaling in algae and expands our understanding of such processes, with biotechnological and evolutionary implications.Ministry of Science, ICT and Future Planning 2015M3A6A2065697Ministry of Oceans and Fisheries 2015018

Improvement in the hygroscopicity of inorganic binder through a dual coating process

The use of an anti-absorbent is proposed in this work to reduce the hygroscopicity of the inorganic binder in the casting mold, in which the anti-absorbent is coated on the mold prepared with an inorganic binder. Three types of polymers were used to select material with optimal water resistance. Polystyrene (PS) and polyvinyl alcohol (PVA) were used as a water-insoluble polymer and water-soluble polymer, respectively. In addition, polyurethane (PU) prepolymer has intermediate properties between PS and PVA. PVA and PU prepolymer were used for comparative testing with PS. For this testing process, the prepared green body was dipped into a solution of inorganic binder precursor mixed with tetraethyl orthosilicate (TEOS, SiO2 precursor) and sodium methoxide (NaOMe, Na2O precursor), and then dipped into a solution of coating reagent after a drying process. Thus, these series of coating processes in a green body is called a dual coating process. Finally the sample was heat-treated at 1000 °C to generate a glass phase by an organic–inorganic conversion process. In the sample prepared with PS, the highest contact angle and a high firing strength were exhibited, independent of polymer concentration, while the sample coated with PVA showed lower green and firing strengths. When prepolymer, PU, was applied, the green strength was remarkably improved, showing lower firing strength compared with that of PS. The green and firing strengths were optimized through the dual coating process with PS. Moreover, the moisture-proof effect of the dual coating process was verified through the moisture steam test

Traffic Convexity Aware Cellular Networks: A Vehicular Heavy User Perspective

Rampant mobile traffic increase in modern cellular networks is mostly caused by large-sized multimedia contents. Recent advancements in smart devices as well as radio access technologies promote the consumption of bulky content, even for people in moving vehicles, referred to as vehicular heavy users. In this article the emergence of vehicular heavy user traffic is observed by field experiments conducted in 2012 and 2015 in Seoul, Korea. The experiments reveal that such traffic is becoming dominant, captured by the 8.62 times increase in vehicular heavy user traffic while the total traffic increased 3.04 times. To resolve this so-called vehicular heavy user problem (VHP), we propose a cell association algorithm that exploits user demand diversity for different velocities. This user traffic pattern is discovered first by our field trials, which is convex-shaped over velocity, i.e. walking user traffic is less than stationary or vehicular user traffic. As the VHP becomes severe, numerical evaluation verifies the proposed user convexity aware association outperforms a well-known load balancing association in practice, cell range expansion (CRE). In addition to the cell association, several complementary techniques are suggested in line with the technical trend toward 5G.Comment: 15 pages, 5 figures, 1 table, to appear in IEEE Wireless Communications Magazin

Time-resolved pathogenic gene expression analysis of the plant pathogen Xanthomonas oryzae pv. oryzae

Virulence of wild-type and mutant Xoo strains on rice. (DOCX 16 kb