34 research outputs found
Whole proteome analyses on Ruminiclostridium cellulolyticum show a modulation of the cellulolysis machinery in response to cellulosic materials with subtle differences in chemical and structural properties
Lignocellulosic materials from municipal solid waste emerge as attractive resources for anaerobic digestion biorefinery. To increase the knowledge required for establishing efficient bioprocesses, dynamics of batch fermentation by the cellulolytic bacterium Ruminiclostridium cellulolyticum were compared using three cellulosic materials, paper handkerchief, cotton discs and Whatman filter paper. Fermentation of paper handkerchief occurred the fastest and resulted in a specific metabolic profile: it resulted in the lowest acetate-to-lactate and acetate-to-ethanol ratios. By shotgun proteomic analyses of paper handkerchief and Whatman paper incubations, 151 proteins with significantly different levels were detected, including 20 of the 65 cellulosomal components, 8 non-cellulosomal CAZymes and 44 distinct extracytoplasmic proteins. Consistent with the specific metabolic profile observed, many enzymes from the central carbon catabolic pathways had higher levels in paper handkerchief incubations. Among the quantified CAZymes and cellulosomal components, 10 endoglucanases mainly from the GH9 families and 7 other cellulosomal subunits had lower levels in paper handkerchief incubations. An in-depth characterization of the materials used showed that the lower levels of endoglucanases in paper handkerchief incubations could hypothetically result from its lower crystallinity index (50%) and degree of polymerization (970). By contrast, the higher hemicellulose rate in paper handkerchief (13.87%) did not result in the enhanced expression of enzyme with xylanase as primary activity, including enzymes from the xyl-doc cluster. It suggests the absence, in this material, of molecular structures that specifically lead to xylanase induction. The integrated approach developed in this work shows that subtle differences among cellulosic materials regarding chemical and structural characteristics have significant effects on expressed bacterial functions, in particular the cellulolysis machinery, resulting in different metabolic patterns and degradation dynamics.This work was supported by a grant [R2DS 2010-08] from Conseil Regional d'Ile-de-France through DIM R2DS programs (http://www.r2ds-ile-de-france.com/). Irstea (www.irstea.fr/) contributed to the funding of a PhD grant for the first author. The funders provided support in the form of salaries for author [NB], funding for consumables and laboratory equipment, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. Omics Services provided support in the form of salaries for authors [VS, MD], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors [NB, VS, MD] are articulated in the 'author contributions' section.info:eu-repo/semantics/publishedVersio
Detection of collisions and self-collisions using image-space techniques
Image-space techniques have shown to be very efficient for collision detection in dynamic
simulation and animation environments. This paper proposes a new image-space technique for efficient
collision detection of arbitrarily shaped, water-tight objects. In contrast to existing approaches
that do not consider self-collisions, our approach combines the image-space object representation with
information on face orientation to overcome this limitation.
While image-space techniques are commonly implemented on graphics hardware, software solutions
have been neglected so far. In this paper, the performance of two GPU-based implementations and
one CPU-based implementation of the proposed collision detection algorithm are compared. Results
suggest, that graphics hardware accelerates collision detection in geometrically complex environments,
while the CPU-based implementation provides more flexibility and better performance in case of small
environments
Volumetric Collision Detection for Deformable Objects
We present a new algorithm for the efficient detection of collisions of geometrically complex objects. Our approach requires neither expensive setup nor sophisticated spatial data structures and is hence specifically suitable for handling deformable objects with arbitrarily shaped, closed surfaces. The algorithm is based on a Layered Depth Image (LDI) decomposition of the intersection volume. Currently, we have implemented two types of collision queries. The first one comprises an explicit representation of the intersection volume. The second one computes vertex-in-volume tests. All queries are processed on the LDI based volume representation. Our algorithm is very easy to implement and can be accelerated in graphics hardware by using OpenGL
Abstract Real–Time Volumetric Intersections of Deforming Objects
We present a new algorithm for the computation of volumetric intersections of geometrically complex objects, which can be used for the efficient detection of collisions. Our approach requires neither expensive setup nor sophisticated spatial data structures and is specifically suitable for handling deformable objects with arbitrarily shaped, closed surfaces. The algorithm employs a Layered Depth Image (LDI) decomposition of the intersection volume. Currently, we have implemented two types of collision queries. The first one comprises an explicit representation of the intersection volume. The second one computes vertex-in-volume tests. All queries are processed on the LDI-based representation of the intersection volume. Our algorithm is very easy to implement and can be accelerated in graphics hardware by using OpenGL.
Meshless deformations based on shape matching
We present a new approach for simulating deformable objects. The underlying model is geometrically motivated. It handles pointbased objects and does not need connectivity information. The approach does not require any pre-processing, is simple to compute, and provides unconditionally stable dynamic simulations. The main idea of our deformable model is to replace energies by geometric constraints and forces by distances of current positions to goal positions. These goal positions are determined via a generalized shape matching of an undeformed rest state with the current deformed state of the point cloud. Since points are always drawn towards well-defined locations, the overshooting problem of explicit integration schemes is eliminated. The versatility of the approach in terms of object representations that can be handled, the efficiency in terms of memory and computational complexity, and the unconditional stability of the dynamic simulation make the approach particularly interesting for games
A Versatile and Robust Model for Geometrically Complex Deformable Solids
In this paper, we present a versatile and robust model for geometrically complex deformable solids. Our approach can be applied to deformable tetrahedral meshes and to deformable triangle meshes. The model considers elastic and plastic deformation. It handles a large variety of material properties ranging from stiff to fluid-like behavior. Due to the computational efficiency of our approach, complex environments consisting of up to several thousand primitives can be simulated at interactive speed