A neuron membrane mesh representation for visualization of electrophysiological simulations

We present a process to automatically generate three-dimensional mesh representations of the complex, arborized cell membrane surface of cortical neurons (the principal information processing cells of the brain) from nonuniform morphological measurements. Starting from manually sampled morphological points (3D points and diameters) from neurons in a brain slice preparation, we construct a polygonal mesh representation that realistically represents the continuous membrane surface, closely matching the original experimental data. A mapping between the original morphological points and the newly generated mesh enables simulations of electrophysiolgical activity to be visualized on this new membrane representation. We compare the new mesh representation with the state of the art and present a series of use cases and applications of this technique to visualize simulations of single neurons and networks of multiple neurons.     

The BIOPHILE Sample Process Management System - Automated Sample Access at Ultra Low Temperatures

The genomics, proteomics, clinical, and drug discovery laboratories have a growing need to maintain valuable samples at ultra-low (−80°C) temperatures in a validated, secure environment. Automated sample processing systems have until now required manual (off-line) storage of samples at −80°C, reducing system reliability and speed. Both of these important needs are addressed by the Sample Process Management System being introduced by BIOPHILE Inc. Conventional sample management processes, such as storage, retrieval, and cataloging, are increasingly strained by the growing sample populations. There are variable sample types, access requirements and storage requirements. Security and inventory procedures are implemented manually. The evolving technologies present in the laboratory cannot interface with conventional manual storage techniques. Addressing these limitations, the primary benefits of BIOPHILE's solutions are:

• Fully validated sample management process that coordinates the life-cycles of samples and their related data.

• Robotic technology to securely store and retrieve samples, improving their accessibility and stability. Thermal shock is reduced, improving sample longevity and quality. The robotic technology allows integration with larger automation systems.

• A process program to develop a Sample Management Strategy. This strategy is developed by analyzing long-term research goals, current baseline processes, and identification of current sample life cycles. A full validation documentation package can be generated, providing a high level of quality assurance.

• Improved sample visibility and quality assurance - automated sample population cataloging; controlled sample management access and security.

     

ICCD: Interactive Continuous Collision Detection between Deformable Models Using Connectivity-Based Culling

We present an interactive algorithm for continuous collision detection between deformable models. We introduce multiple techniques to improve the culling efficiency and the overall performance of continuous collision detection. First, we present a novel formulation for continuous normal cones and use these normal cones to efficiently cull large regions of the mesh as part of self-collision tests. Second, we introduce the concept of “procedural representative triangles” to remove all redundant elementary tests between nonadjacent triangles. Finally, we exploit the mesh connectivity and introduce the concept of “orphan sets” to eliminate redundant elementary tests between adjacent triangle primitives. In practice, we can reduce the number of elementary tests by two orders of magnitude. These culling techniques have been combined with bounding volume hierarchies and can result in one order of magnitude performance improvement as compared to prior collision detection algorithms for deformable models. We highlight the performance of our algorithm on several benchmarks, including cloth simulations, N-body simulations, and breaking objects.     

Tool Building Requirements for an API to First-Order Solvers

Effective formal verification tools require that robust implementations of automatic procedures for first-order logic and satisfiability modulo theories be integrated into expressive interactive frameworks for logical deduction, such as higher-order logic theorem provers. This paper states some pragmatic requirements for implementations of decision procedures that make them well-suited to integration into such frameworks. The aim is to open a dialogue with the designers of decision procedure software that will lead to greater and easier uptake of their implementations by verification users.     

Connection and coordination: the interplay between architecture and dynamics in evolved model pattern generators

We undertake a systematic study of the role of neural architecture in shaping the dynamics of evolved model pattern generators for a walking task. First, we consider the minimum number of connections necessary to achieve high performance on this task. Next, we identify architectural motifs associated with high fitness. We then examine how high-fitness architectures differ in their ability to evolve. Finally, we demonstrate the existence of distinct parameter subgroups in some architectures and show that these subgroups are characterized by differences in neuron excitabilities and connection signs.     

A dynamic workflow framework for mass customization using web service and autonomous agent techniques

Custom software development and maintenance is one of the key expenses associated with developing automated systems for mass customization. This paper presents a method for reducing the risk associated with this expense by developing a flexible environment for determining and executing dynamic workflow paths. Strategies for developing an autonomous agent-based framework and for identifying and creating web services for specific process tasks are presented. The proposed methods are outlined in two different case studies to illustrate the approach for both a generic process with complex workflow paths and a more specific sequential engineering process.     

Contextual web searches in Facebook using learning materials and discussion messages

The web is nowadays one of the main information sources, and information search is an important area in which many advances have been registered. One approach to improve web search results is to consider contextual information. Usually, information about context has been provided through user logs on previous searches or the monitoring of clicks on first results, but different approaches can be used in specific environments. In a web based learning environment, existing documents and exchanged messages could provide contextual information. So, the main goal of this work is to provide a contextual web search engine based on shared documents and messages posted in a social network used for collaborative learning. Contextual search is provided through query expansion using learning documents (material provided by the teacher) and discussion messages (posts, links and comments that result from the participants’ interactions). A prototype was implemented and used in a learning scenario to acquire the context in a learning community. The proposed approach makes the context acquisition faster and more dynamic as it considers an automatic approach over text processing of documents and discussions. In addition, the results of the query engine with and without the contextual information were compared and the proposed approach using contextual information showed improvements in the precision of the results.