Experimental Study on Performance of Asphalt Mixture Designed by Different Method

AbstractIn order to explore the Marshall, Superpave and GTM methods, the similarities and differences of the three design methods are detail studied. Experimental study on performance of asphalt mixture AC-13、AC-20 and AC-25 designed by different method were executed in this paper. Test results show that, GTM method gives lower void and lower bitumen aggregate ratio than other two methods, it have very better water stability and high-temperature stability. The DS value is 3256 / mm by GTM design method, is 1.91 times of the Marshall and 1.33 times of the Superpave. Superpave method gives lower bitumen aggregate ratio than Marshall method. The asphalt mixture designed by Superpave method has longer fatigue life than the mixture designed by other two methods. The volume parameters of asphalt mixture designed by Marshall can conform specification very well, but the performance of asphalt mixture seems to be worse than other two methods

Basins of attraction of chimera states on networks

Networks of identical coupled oscillators display a remarkable spatiotemporal pattern, the chimera state, where coherent oscillations coexist with incoherent ones. In this paper we show quantitatively in terms of basin stability that stable and breathing chimera states in the original two coupled networks typically have very small basins of attraction. In fact, the original system is dominated by periodic and quasi-periodic chimera states, in strong contrast to the model after reduction, which can not be uncovered by the Ott-Antonsen ansatz. Moreover, we demonstrate that the curve of the basin stability behaves bimodally after the system being subjected to even large perturbations. Finally, we investigate the emergence of chimera states in brain network, through inducing perturbations by stimulating brain regions. The emerged chimera states are quantified by Kuramoto order parameter and chimera index, and results show a weak and negative correlation between these two metrics

DSAM-GN:Graph Network based on Dynamic Similarity Adjacency Matrices for Vehicle Re-identification

In recent years, vehicle re-identification (Re-ID) has gained increasing importance in various applications such as assisted driving systems, traffic flow management, and vehicle tracking, due to the growth of intelligent transportation systems. However, the presence of extraneous background information and occlusions can interfere with the learning of discriminative features, leading to significant variations in the same vehicle image across different scenarios. This paper proposes a method, named graph network based on dynamic similarity adjacency matrices (DSAM-GN), which incorporates a novel approach for constructing adjacency matrices to capture spatial relationships of local features and reduce background noise. Specifically, the proposed method divides the extracted vehicle features into different patches as nodes within the graph network. A spatial attention-based similarity adjacency matrix generation (SASAMG) module is employed to compute similarity matrices of nodes, and a dynamic erasure operation is applied to disconnect nodes with low similarity, resulting in similarity adjacency matrices. Finally, the nodes and similarity adjacency matrices are fed into graph networks to extract more discriminative features for vehicle Re-ID. Experimental results on public datasets VeRi-776 and VehicleID demonstrate the effectiveness of the proposed method compared with recent works.Comment: This paper has been accepted by the 20th Pacific Rim International Conference on Artificial Intelligence in 202

The Phosphodiesterase-4 Inhibitor Rolipram Attenuates Heroin-Seeking Behavior Induced By Cues Or Heroin Priming In Rats

Inhibition of phosphodiesterase-4 (PDE4), an enzyme that specifically hydrolyzes cyclic adenosine monophosphate (cAMP) increases intracellular cAMP/cAMP-response element binding protein (CREB) signaling. Activation of this signaling is considered as an important compensatory response that decreases motivational properties of drugs of abuse. However, it is not known whether PDE4 is involved in heroin seeking. Self-administration of heroin (5

Altered intestinal microbiota enhances adenoid hypertrophy by disrupting the immune balance

IntroductionAdenoid hypertrophy (AH) is a common upper respiratory disorder in children. Disturbances of gut microbiota have been implicated in AH. However, the interplay of alteration of gut microbiome and enlarged adenoids remains elusive.Methods119 AH children and 100 healthy controls were recruited, and microbiome profiling of fecal samples in participants was performed using 16S rRNA gene sequencing. Fecal microbiome transplantation (FMT) was conducted to verify the effects of gut microbiota on immune response in mice.ResultsIn AH individuals, only a slight decrease of diversity in bacterial community was found, while significant changes of microbial composition were observed between these two groups. Compared with HCs, decreased abundances of Akkermansia, Oscillospiraceae and Eubacterium coprostanoligenes genera and increased abundances of Bacteroides, Faecalibacterium, Ruminococcus gnavus genera were revealed in AH patients. The abundance of Bacteroides remained stable with age in AH children. Notably, a microbial marker panel of 8 OTUs were identified, which discriminated AH from HC individuals with an area under the curve (AUC) of 0.9851 in the discovery set, and verified in the geographically different validation set, achieving an AUC of 0.9782. Furthermore, transfer of mice with fecal microbiota from AH patients dramatically reduced the proportion of Treg subsets within peripheral blood and nasal-associated lymphoid tissue (NALT) and promoted the expansion of Th2 cells in NALT.ConclusionThese findings highlight the effect of the altered gut microbiota in the AH pathogenesis

Frisson Waves: Exploring Automatic Detection, Triggering and Sharing of Aesthetic Chills in Music Performances

Frisson is the feeling and experience of physical reactions such as shivers, tingling skin, and goosebumps. Using entrainment through facilitating interpersonal transmissions of embodied sensations, we present "Frisson Waves" with the aim to enhance live music performance experiences. "Frisson Waves" is an exploratory real-time system to detect, trigger and share frisson in a wave-like pattern over audience members during music performances. The system consists of a physiological sensing wristband for detecting frisson and a thermo-haptic neckband for inducing frisson. In a controlled environment, we evaluate detection (n=19) and triggering of frisson (n=15). Based on our findings, we conducted an in-the-wild music concert with 48 audience members using our system to share frisson. This paper summarizes a framework for accessing, triggering and sharing frisson. We report our research insights, lessons learned, and limitations of "Frisson Waves". Yan He, George Chernyshov, Jiawen Han, Dingding Zheng, Ragnar Thomsen, Danny Hynds, Muyu Liu, Yuehui Yang, Yulan Ju, Yun Suen Pai, Kouta Minamizawa, Kai Kunze, and Jamie A War

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

An evolution model of online social networks based on “Sina micro-blog”

The impact of online social networks and the necessity to sustain their rapid growth emphasize the importance to unravel the laws governing their evolution. With online data crawled from “Sina micro-blog”, we divide the entire users into opinion leaders and ordinary microbloggers without verification. This allows us to illustrate a quantitative two-layer model to reproduce the evolution of the online social networks from the birth of it, which is a visual framework for micro-blog users ′ behaviors. The empirical study of the model shows that the different influence between ordinary users and opinion leaders and the viral spreading mechanism and mass media influence govern the evolution of online social networks. At the end we verify the accuracy of our model with real “Sina micro-blog”dataset. Furthermore, considering the complexity of microbloggers, we can develop the information dissemination to show the mutual impact of various social values

Design and Application of Intelligent Transportation Multi-Source Data Collaboration Framework Based on Digital Twins

The increasing urban traffic problems have made the transportation system require a large amount of data. Aiming at the current problems of data types redundancy and low coordination rate of intelligent transportation systems (ITS), this paper proposes an improved digital twin architecture applicable to ITS. Based on the improved digital twin architecture, a framework for dynamic and static data collaboration in ITS is constructed. For various collaboration methods, this paper specifically describes the collaboration methods and scopes, and designs the framework and interfaces for data mapping. Finally, the effectiveness of the framework is verified by case studies to mine the spatiotemporal distribution characteristics of data, capture human travel characteristics, and visualize intersections using digital twins. This paper provides a new data fusion idea for digital twin systems in ITS, and the framework covers all data types in digital twin systems for cross-integration analysis

Design and Application of Intelligent Transportation Multi-Source Data Collaboration Framework Based on Digital Twins

The increasing urban traffic problems have made the transportation system require a large amount of data. Aiming at the current problems of data types redundancy and low coordination rate of intelligent transportation systems (ITS), this paper proposes an improved digital twin architecture applicable to ITS. Based on the improved digital twin architecture, a framework for dynamic and static data collaboration in ITS is constructed. For various collaboration methods, this paper specifically describes the collaboration methods and scopes, and designs the framework and interfaces for data mapping. Finally, the effectiveness of the framework is verified by case studies to mine the spatiotemporal distribution characteristics of data, capture human travel characteristics, and visualize intersections using digital twins. This paper provides a new data fusion idea for digital twin systems in ITS, and the framework covers all data types in digital twin systems for cross-integration analysis