University of Rennes

About: University of Rennes is a education organization based out in Rennes, France. It is known for research contribution in the topics: Population & Crystal structure. The organization has 18404 authors who have published 40374 publications receiving 995327 citations.

Surgical process modelling: a review

Abstract: Surgery is continuously subject to technological and medical innovations that are transforming daily surgical routines. In order to gain a better understanding and description of surgeries, the field of surgical process modelling (SPM) has recently emerged. The challenge is to support surgery through the quantitative analysis and understanding of operating room activities. Related surgical process models can then be introduced into a new generation of computer-assisted surgery systems. In this paper, we present a review of the literature dealing with SPM. This methodological review was obtained from a search using Google Scholar on the specific keywords: “surgical process analysis”, “surgical process model” and “surgical workflow analysis”. This paper gives an overview of current approaches in the field that study the procedural aspects of surgery. We propose a classification of the domain that helps to summarise and describe the most important components of each paper we have reviewed, i.e., acquisition, modelling, analysis, application and validation/evaluation. These five aspects are presented independently along with an exhaustive list of their possible instantiations taken from the studied publications. This review allows a greater understanding of the SPM field to be gained and introduces future related prospects.

Experiment-based modeling, simulation and validation of interactions between virtual walkers

Abstract: An interaction occurs between two humans when they walk with converging trajectories. They need to adapt their motion in order to avoid and cross one another at respectful distance. This paper presents a model for solving interactions between virtual humans. The proposed model is elaborated from experimental interactions data. We first focus our study on the pair-interaction case. In a second stage, we extend our approach to the multiple interactions case. Our experimental data allow us to state the conditions for interactions to occur between walkers, as well as each one's role during interaction and the strategies walkers set to adapt their motion. The low number of parameters of the proposed model enables its automatic calibration from available experimental data. We validate our approach by comparing simulated trajectories with real ones. We also provide comparison with previous solutions. We finally discuss the ability of our model to be extended to complex situations.

Europe-wide dampening of population cycles in keystone herbivores

Abstract: Suggestions of collapse in small herbivore cycles since the 1980s have raised concerns about the loss of essential ecosystem functions. Whether such phenomena are general and result from extrinsic environmental changes or from intrinsic process stochasticity is currently unknown. Using a large compilation of time series of vole abundances, we demonstrate consistent cycle amplitude dampening associated with a reduction in winter population growth, although regulatory processes responsible for cyclicity have not been lost. The underlying syndrome of change throughout Europe and grass-eating vole species suggests a common climatic driver. Increasing intervals of low-amplitude small herbivore population fluctuations are expected in the future, and these may have cascading impacts on trophic webs across ecosystems.

Discrete Cationic Complexes for Ring-Opening Polymerization Catalysis of Cyclic Esters and Epoxides

Abstract: A review. Many discrete cationic complexes have been designed and exhibited increasingly impressive catalytic performances for the ROP of epoxides and cyclic esters. The current state-of-the-art suggests that major breakthroughs cannot be foreseen in the homopolymn. of epoxides, due to the nature of the assocd. mechanisms, and as a consequence, interest in the use of metal cations to polymerize epoxides has dwindled. It seems to the authors that in view of the activated monomer mechanism that is often assocd. with discrete metal cations, this is clearly an area where the use of rationally devised cationic complexes could bring original breakthroughs.

Depth-Aware Salient Object Detection and Segmentation via Multiscale Discriminative Saliency Fusion and Bootstrap Learning

Abstract: This paper proposes a novel depth-aware salient object detection and segmentation framework via multiscale discriminative saliency fusion (MDSF) and bootstrap learning for RGBD images (RGB color images with corresponding Depth maps) and stereoscopic images By exploiting low-level feature contrasts, mid-level feature weighted factors and high-level location priors, various saliency measures on four classes of features are calculated based on multiscale region segmentation A random forest regressor is learned to perform the discriminative saliency fusion (DSF) and generate the DSF saliency map at each scale, and DSF saliency maps across multiple scales are combined to produce the MDSF saliency map Furthermore, we propose an effective bootstrap learning-based salient object segmentation method, which is bootstrapped with samples based on the MDSF saliency map and learns multiple kernel support vector machines Experimental results on two large datasets show how various categories of features contribute to the saliency detection performance and demonstrate that the proposed framework achieves the better performance on both saliency detection and salient object segmentation