A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model. Journal web page & a lot of robotic related papers www.ars-journal.co

Antibiotic resistance in urban green spaces mirrors the pattern of industrial distribution

Urban green spaces are closely related to the activities and health of urban residents. Turf grass and soil are two major interfaces between the environmental and human microbiome, which represent potential pathways for the spread of antibiotic resistance genes (ARGs) from environmental to human microbiome through skin-surface contact. However, the information regarding the prevalence of ARGs in urban green spaces and drivers in shaping their distribution patterns remain unclear. Here, we profiled a wide spectrum of ARGs in grass phyllosphere and soils from 40 urban parks across Greater Melbourne, Australia, using high throughput quantitative PCR. A total of 217 and 218 unique ARGs and MGEs were detected in grass phyllosphere and soils, respectively, conferring resistance to almost all major classes of antibiotics commonly used in human and animals. The plant microbiome contained a core resistome, which occupied > 84% of the total abundance of ARGs. In contrast, no core resistome was identified in the soil microbiome. The difference between plant and soil resistome composition was attributed to the difference in bacterial community structure and intensity of environmental and anthropogenic influence. Most importantly, the abundance of ARGs in urban green spaces was significantly positively related to industrial factors including total number of business, number of manufacturing, and number of electricity, gas, water and waste services in the region. Structural equation models further revealed that industrial distribution was a major factor shaping the ARG profiles in urban green spaces after accounting for multiple drivers. These findings have important implications for mitigation of the potential risks posed by ARGs to urban residents

Molecular Authentication of the Medicinal Species of Ligusticum (Ligustici Rhizoma et Radix, “Gao-ben”) by Integrating Non-coding Internal Transcribed Spacer 2 (ITS2) and Its Secondary Structure

Ligustici Rhizoma et Radix (LReR), an important Chinese medicine known as “Gao-ben,” refers to Ligusticum sinense Oliv. or Ligusticum jeholense Nakai et Kitag. However, a number of other species are commonly sold as “Gao-ben” in the herbal medicine market, which may result in a series of quality control problems and inconsistent therapeutic effects. The “Gao-ben” is commonly sold sliced and dried, making traditional identification methods difficult. Here, the mini barcode ITS2 region was examined on 68 samples representing LReR and 7 potential adulterant or substitute species. The results showed 100% success rates of PCR and sequencing and the existence of a barcoding gap. The neighbor-joining (NJ) tree indicated that all the tested samples could be exactly identified. The ITS2 secondary structure revealed a clear difference between true “Gao-ben” and three adulterant species. We therefore recommend the use of ITS2 as a mini barcode for distinguishing between closely or distantly related plant species that may be used in Chinese medicine