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

某三甲医院造口伤口失禁门诊诊疗现状调查

Objective: To investigate the present situation of wound ostomy continence(WOC) clinic as well as to provide objective basis and expand working thoughts for carrying out WOC clinic.Method:3251 patients who visited our WOC clinic between December 2010 and March 2015 were retrospectively analyzed.Results: The patients know WOC clinic mostly (94.72%) by medical staff in our hospital. Chronic wound patients have the highest demand (63.82%). 6.51% patients with poor health and economic condition can’t stick to outpatient dressing. Most ostomy patients receive well health guidance during their hospitalization.Conclusion: The patients show great demands for WOC clincic. Next we should strengthen the propaganda, develop continuous nursing and telemedicine network.目的  调查造口伤口失禁门诊的工作现状，为更好地开展造口伤口失禁门诊提供客观依据和方向，拓展工作思路。方法  对我院自2010年12月—2015年3月造口伤口失禁门诊的3251名患者的诊疗状况进行回顾性分析。结果  造口伤口失禁门诊患者主要是通过本院医护人员知晓造口伤口失禁门诊（94.72%），患者中慢性伤口患者的需求量最大（63.82%），部分患者身体及家庭经济条件较差，未能坚持在门诊换药治疗（6.51%），造口患者在住院期间大部分已获得良好的健康指导。结论  患者对造口伤口失禁门诊有极大的需求，下一步须加强门诊宣传力度，开展延续性护理及远程治疗平台

MagicFusion: Boosting Text-to-Image Generation Performance by Fusing Diffusion Models

The advent of open-source AI communities has produced a cornucopia of powerful text-guided diffusion models that are trained on various datasets. While few explorations have been conducted on ensembling such models to combine their strengths. In this work, we propose a simple yet effective method called Saliency-aware Noise Blending (SNB) that can empower the fused text-guided diffusion models to achieve more controllable generation. Specifically, we experimentally find that the responses of classifier-free guidance are highly related to the saliency of generated images. Thus we propose to trust different models in their areas of expertise by blending the predicted noises of two diffusion models in a saliency-aware manner. SNB is training-free and can be completed within a DDIM sampling process. Additionally, it can automatically align the semantics of two noise spaces without requiring additional annotations such as masks. Extensive experiments show the impressive effectiveness of SNB in various applications. Project page is available at https://magicfusion.github.io/

Nonlinear quantum input-output analysis using Volterra series

Quantum input-output theory plays a very important role for analyzing the dynamics of quantum systems, especially large-scale quantum networks. As an extension of the input-output formalism of Gardiner and Collet, we develop a new approach based on the quantum version of the Volterra series which can be used to analyze nonlinear quantum input-output dynamics. By this approach, we can ignore the internal dynamics of the quantum input-output system and represent the system dynamics by a series of kernel functions. This approach has the great advantage of modelling weak-nonlinear quantum networks. In our approach, the number of parameters, represented by the kernel functions, used to describe the input-output response of a weak-nonlinear quantum network, increases linearly with the scale of the quantum network, not exponentially as usual. Additionally, our approach can be used to formulate the quantum network with both nonlinear and nonconservative components, e.g., quantum amplifiers, which cannot be modelled by the existing methods, such as the Hudson-Parthasarathy model and the quantum transfer function model. We apply our general method to several examples, including Kerr cavities, optomechanical transducers, and a particular coherent feedback system with a nonlinear component and a quantum amplifier in the feedback loop. This approach provides a powerful way to the modelling and control of nonlinear quantum networks.Comment: 12 pages, 7 figure