49 research outputs found
Multi-Robot Trajectory Planning with Feasibility Guarantee and Deadlock Resolution: An Obstacle-Dense Environment
This article presents a multi-robot trajectory planning method which
guarantees optimization feasibility and resolves deadlocks in an obstacle-dense
environment. The method is proposed via formulating an optimization problem,
where the modified buffered Voronoi cell with warning band is utilized to avoid
the inter-robot collision and the deadlock is resolved by an adaptive
right-hand rule. Meanwhile, a novel safe corridor derived from historical
planned trajectory is proposed to provide a proper space for obstacle avoidance
in trajectory planning. Comparisons with state-of-the-art works are conducted
to illustrate the safety and deadlock resolution in cluttered scenarios.
Additionally, hardware experiments are carried out to verify the performance of
the proposed method where eight nano-quadrotors fly through a 0.6m cubic
framework
Graph-Level Embedding for Time-Evolving Graphs
Graph representation learning (also known as network embedding) has been
extensively researched with varying levels of granularity, ranging from nodes
to graphs. While most prior work in this area focuses on node-level
representation, limited research has been conducted on graph-level embedding,
particularly for dynamic or temporal networks. However, learning
low-dimensional graph-level representations for dynamic networks is critical
for various downstream graph retrieval tasks such as temporal graph similarity
ranking, temporal graph isomorphism, and anomaly detection. In this paper, we
present a novel method for temporal graph-level embedding that addresses this
gap. Our approach involves constructing a multilayer graph and using a modified
random walk with temporal backtracking to generate temporal contexts for the
graph's nodes. We then train a "document-level" language model on these
contexts to generate graph-level embeddings. We evaluate our proposed model on
five publicly available datasets for the task of temporal graph similarity
ranking, and our model outperforms baseline methods. Our experimental results
demonstrate the effectiveness of our method in generating graph-level
embeddings for dynamic networks.Comment: In Companion Proceedings of the ACM Web Conference 202
Embedding Heterogeneous Networks into Hyperbolic Space Without Meta-path
Networks found in the real-world are numerous and varied. A common type of
network is the heterogeneous network, where the nodes (and edges) can be of
different types. Accordingly, there have been efforts at learning
representations of these heterogeneous networks in low-dimensional space.
However, most of the existing heterogeneous network embedding methods suffer
from the following two drawbacks: (1) The target space is usually Euclidean.
Conversely, many recent works have shown that complex networks may have
hyperbolic latent anatomy, which is non-Euclidean. (2) These methods usually
rely on meta-paths, which require domain-specific prior knowledge for meta-path
selection. Additionally, different down-streaming tasks on the same network
might require different meta-paths in order to generate task-specific
embeddings. In this paper, we propose a novel self-guided random walk method
that does not require meta-path for embedding heterogeneous networks into
hyperbolic space. We conduct thorough experiments for the tasks of network
reconstruction and link prediction on two public datasets, showing that our
model outperforms a variety of well-known baselines across all tasks.Comment: In proceedings of the 35th AAAI Conference on Artificial Intelligenc
Microglia-mediated inflammatory destruction of neuro-cardiovascular dysfunction after stroke
Stroke, a serious systemic inflammatory disease, features neurological deficits and cardiovascular dysfunction. Neuroinflammation is characterized by the activation of microglia after stroke, which disrupts the cardiovascular-related neural network and the blood–brain barrier. Neural networks activate the autonomic nervous system to regulate the cardiac and blood vessels. Increased permeability of the blood–brain barrier and the lymphatic pathways promote the transfer of the central immune components to the peripheral immune organs and the recruitment of specific immune cells or cytokines, produced by the peripheral immune system, and thus modulate microglia in the brain. In addition, the spleen will also be stimulated by central inflammation to further mobilize the peripheral immune system. Both NK cells and Treg cells will be generated to enter the central nervous system to suppress further inflammation, while activated monocytes infiltrate the myocardium and cause cardiovascular dysfunction. In this review, we will focus on microglia-mediated inflammation in neural networks that result in cardiovascular dysfunction. Furthermore, we will discuss neuroimmune regulation in the central–peripheral crosstalk, in which the spleen is a vital part. Hopefully, this will benefit in anchoring another therapeutic target for neuro-cardiovascular dysfunction
Geology, U-Pb geochronology and stable isotope geochemistry of the Heihaibei gold deposit in the southern part of the Eastern Kunlun Orogenic Belt, China : A granitic intrusion-related gold deposit?
The Heihaibei gold deposit is a newly discovered gold deposit in the southern part of the Eastern Kunlun Orogenic Belt. Its most distinctive features are that the gold mineralization is hosted in monzogranite, and that the presence of pre-ore (possibly syn-ore) monzogranite and post-ore gabbro allows to constrain the minerali-zation's formation age. Zircons from the monzogranites yield U-Pb ages of 454 +/- 3 Ma, while zircons separated from the gabbro dikes cutting the monzogranites and gold mineralized body yield U-Pb ages of 439 +/- 3 Ma, which is interpreted to be the minimum age of the Au mineralizing event. Combined with the regional geological background, we proposed that the Heihaibei Au mineralization occurred during the subduction stage of the Early Paleozoic Proto-Tethys ocean. The ore assemblage is dominated by pyrite, arsenopyrite and native gold. The hydrothermal alteration that has led to the peculiar enrichment of Au is not systematically distributed and displays no clear concentric zoning pattern. The main mineralization formed during three stages: the K-feldspar-quartz-pyrite (Py1)-arsenopyrite-sericite-epidote stage (I), the quartz-pyrite (Py2)-native gold-chlorite stage (II), and the quartz-carbonate stage (III). The main gold mineralization occurred during stage II. Fluid inclusion homogenization temperature and salinities decrease from stage I (Th., 268-412 C; W., 6.87-16.63 wt% NaCl equiv.) to stage II (Th., 183-288 C; W., 3.69-14.84 wt% NaCl equiv.). The 818O and 8D values (818OH2O = 4.9 to 9.7%o; 8DV-SMOW =-84.1%o to -81.1%o) of quartz samples from stage I and stage II are comparable to a magmatic-hydrothermal ore-forming fluid that possibly underwent fluid-rock interaction with the Nachitai Group metamorphic rocks during the early ore-forming stage. The relatively uniform 834S values (834SV-CDT = 7.7 to 8.5%o) are slightly elevated compared to magmatic 834S values, but could be derived from a magma if a significant crustal melt component is present. Moreover, the 834S values are within the S isotopic composition range of a granitic reservoir, suggesting that they are probably inherited from the Heihaibei monzogranites. The Pb and Hf isotope compositions imply a close genetic association between the gold mineralization and granitic magmatism, which are both the products of the mixing of crustal and mantle sources. The trace element compositions of pyrite provide additional evidence that the gold mineralization in the Heihaibei deposit was related to the magmatism. Compared with the typical characteristics of orogenic gold and intrusion-related gold systems (IRGS) deposits, the Heihaibei gold deposit may instead be classified as a granitic intrusion-related gold deposit.Peer reviewe
Non-syndromic enlarged vestibular aqueduct caused by novel compound mutations of the SLC26A4 gene: a case report and literature review
Enlarged vestibular aqueduct is an autosomal genetic disease mainly caused by mutations in the SLC26A4 gene and includes non-syndromic and syndromic types. This study aimed to identify genetic defects in a Chinese patient with non-syndromic enlarged vestibular aqueduct (NSEVA) and to investigate the impact of variants on the severity of non-syndromic enlarged vestibular aqueduct. A male patient with NSEVA, aged approximately 6 years, was recruited for this study. The clinical characteristics and results of auxiliary examinations, including laboratory and imaging examinations, were collected, and 127 common hereditary deafness genes were detected by chip capture high-throughput sequencing. Protein structure predictions, the potential impact of mutations, and multiple sequence alignments were analyzed in silico. Compound heterozygote mutations c.1523_1528delinsAC (p.Thr508Asnfs*3) and c.422T>C (p.Phe141Ser) in the SLC26A4 gene were identified. The novel frameshift mutation c.1523_1528delinsAC produces a severely truncated pendrin protein, and c.422T>C has been suggested to be a disease-causing mutation. Therefore, this study demonstrates that the novel mutation c.1523_1528delinsAC in compound heterozygosity with c.422T>C in the SLC26A4 gene is likely to be the cause of NSEVA. Cochlear implants are the preferred treatment modality for patients with NSEVA and severe-to-profound sensorineural hearing loss Genetic counseling and prenatal diagnosis are essential for early diagnosis. These findings expand the mutational spectrum of SLC26A4 and improve our understanding of the molecular mechanisms underlying NSEVA
The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study
BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID‐19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial.MethodsWe conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran’s Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results.ResultsWe found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92–0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy.ConclusionsOur study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels
Improvement of Bayesian Dynamic Linear Model for Predicting Missing Data of Bridges
The missing data in bridge operation will lead to the decline of the reliability of data analysis results. In this paper, the Bayesian dynamic linear model is improved by changing the parameter matrix of hidden state variables, and the model is optimized under the condition that the predefined variables are unchanged. The frequency of a strain measuring point of the bridge is taken as the observed value, and the collected frequency value of one month is used as the training set (the collection time interval is 30 minutes) to predict the data of the next week. By comparing the predicted result with the observed value, it is found that the absolute error is less than 14.05Hz and the relative error is less than 1.82% when the training frequency value varies from 756 Hz to 773.4 Hz
Treatment and Effect of Loess Metro Tunnel under Surrounding Pressure and Water Immersion Environment
It is possible to pass through a collapsible loess stratum during metro tunneling. When the surrounding potential water sources with pressure are induced by external influences, the tunnel structure will be influenced in the affected area of loess collapsibility. To deal with the water inrush disaster of the tunnel in a collapsible loess stratum, the mechanism of grouting diffusion in the loess stratum is analyzed. It is found that the main influencing factors of the grouting effect are the radius of the grouting ring and the permeability coefficient of the grouting ring. Then, based on the water inrush section of a metro tunnel in Xi’an city, China, the treatment effect of the project is compared and analyzed through field tests, field monitoring, and finite element simulation. The results show that the water pressure at the measuring point of the tunnel vault is reduced by 4 MPa; the maximum and the minimum principal stresses at the top of the segment lining increased by 34.9 kPa and 8.8 kPa, respectively, which is less than the increase without grouting; and the maximum displacement of the surrounding rock is reduced by 19 mm. The plastic area produced by local water source infiltration is about 62% of that before grouting. The treatment measures of grouting in the tunnel are safe and effective. This study is of valuable meaning for the treatment of water inrush disaster of a loess tunnel under the water environment