596 research outputs found
Control strategy for a flexible analytical chemistry robotics system
This thesis is the result of work carried out during more than two years on a Teaching Company Scheme. Liaison took place between Rhone-Poulenc Agriculture Limited (the industrial partner), hereafter referred to as RPAL or the company, and Middlesex University (the academic partner). The aim of the Scheme was to realise the design, development, commissioning, testing and validation of an intelligent robotic system for sample analysis of trace
pesticides and metabolites in order to enable quicker product development. Due to the complexity of the project and the range of technical expertise and skills needed for its implementation, three associates participated in the
Programme. I joined as the second associate. With my degree in Industrial Engineering, I have been in overall charge of developing the computational aspects of the system, from control overview to implementation and validation.
Two distinct types of studies will be carried out with the robot based system:
• Routine extraction of pesticide from soil or plant material, which is compound as well as analyst dependant.
• Method development studies, to optimise those routine extraction processes.
Traditional strategies of control were not applicable for such system because we were dealing with the automation of a non repetitive process involving non-deterministic operations (evaporation, filtration, etc.). The resulting control system should provide a high degree of flexibility to allow workcell
reconfiguration without involving any reprogramming. Modularity is also a must if expansion and upgrading to new technologies and equipment is to involve relatively little cost and effort. In addition, all generated data has to be stored and reported following Good Laboratory Practice (GLP) standards.
As the system is both large and flexible in operation, it has proven a real challenge to develop. Software had to be written that can - among its many tasks - allow unrestricted analyst choice, optimise system performance, detect, prioritise and act upon error signals, dynamically schedule robot and
instrument operation in real time, trace samples as they pass through the system and generate results as reports stored in databases.
The system is now virtually complete, and is presently undergoing the last stages of the validation. Due to the success of this scheme, further cooperative ventures are being planned between Rhone-Poulenc and Middlesex University in both the UK and France
Hierarchical workflow management system for life science applications
In modern laboratories, an increasing number of automated stations and instruments are applied as standalone automated systems such as biological high throughput screening systems, chemical parallel reactors etc. At the same time, the mobile robot transportation solution becomes popular with the development of robotic technologies. In this dissertation, a new superordinate control system, called hierarchical workflow management system (HWMS) is presented to manage and to handle both, automated laboratory systems and logistics systems.In modernen Labors werden immer mehr automatisierte Stationen und Instrumente als eigenständige automatisierte Systeme eingesetzt, wie beispielsweise biologische High-Throughput-Screening-Systeme und chemische Parallelreaktoren. Mit der Entwicklung der Robotertechnologien wird gleichzeitig die mobile Robotertransportlösung populär. In der vorliegenden Arbeit wurde ein hierarchisches Verwaltungssystem für Abeitsablauf, welches auch als HWMS bekannt ist, entwickelt. Das neue übergeordnete Kontrollsystem kann sowohl automatisierte Laborsysteme als auch Logistiksysteme verwalten und behandeln
RACS: Rapid Analysis of ChIP-Seq data for contig based genomes
Background: Chromatin immunoprecipitation coupled to next generation
sequencing (ChIP-Seq) is a widely used technique to investigate the function of
chromatin-related proteins in a genome-wide manner. ChIP-Seq generates large
quantities of data which can be difficult to process and analyse, particularly
for organisms with contig based genomes. Contig-based genomes often have poor
annotations for cis-elements, for example enhancers, that are important for
gene expression. Poorly annotated genomes make a comprehensive analysis of
ChIP-Seq data difficult and as such standardized analysis pipelines are
lacking. Methods: We report a computational pipeline that utilizes traditional
High-Performance Computing techniques and open source tools for processing and
analysing data obtained from ChIP-Seq. We applied our computational pipeline
"Rapid Analysis of ChIP-Seq data" (RACS) to ChIP-Seq data that was generated in
the model organism Tetrahymena thermophila, an example of an organism with a
genome that is available in contigs. Results: To test the performance and
efficiency of RACs, we performed control ChIP-Seq experiments allowing us to
rapidly eliminate false positives when analyzing our previously published data
set. Our pipeline segregates the found read accumulations between genic and
intergenic regions and is highly efficient for rapid downstream analyses.
Conclusions: Altogether, the computational pipeline presented in this report is
an efficient and highly reliable tool to analyze genome-wide ChIP-Seq data
generated in model organisms with contig-based genomes.
RACS is an open source computational pipeline available to download from:
https://bitbucket.org/mjponce/racs --or--
https://gitrepos.scinet.utoronto.ca/public/?a=summary&p=RACSComment: Submitted to BMC Bioinformatics. Computational pipeline available at
https://bitbucket.org/mjponce/rac
Integration and operational strategy of a flexible automated system for sample analysis
This project describes the integration of a twenty-two workstation laboratory automation system based around a track-mounted robot. The required level of operational flexibility
of the overall system puts the emphasis on interfacing and controlling effectively a large number of instruments. The integration of such a large system can sometimes be tricky
as off-the-shelf instruments are put near side modified commercial equipment and purpose built workstations.
The automated system being developed at Rhone-Poulenc Agriculture Ltd (RPAL) automates several highly manual analytical processes following one another in a constantly varying order. The integration of such a system was carried out in collaboration with a software and a mechanical engineer. The choice of the controlsystem was made so that the variety of workstations included could be controlled by a
limited number of different means. After having drawn the specifications and estimated the number of inputs/outputs needed for every station, a PLC was acquired together with
four computers. Various electronics interfaces had to be built or purchased in order to fully operate the system from the controlling computers. Printed circuit boards have been designed and manufactured at Middlesex University together with many mechanical parts for different stations. This integration had to make sure that the system will operate as intended and governed by the parameters entered by the user. System's behaviour and safety in case of an error or an emergency was studied and an emergency stop circuit together with interlocks was implemented. The PLC program was designed so that the machines will fail safe in case of a problem. Being a tool for method development and optimisation, the system evolves gradually towards becoming an expert system. From the information gathered during runs, a decision tree is implemented and responsibilities are gradually withdrawn from the user. Cross-contamination, radio-labelled samples, and solvent compatibility are determining
factors in the safety evaluation and validation processes. This system was developed as part of a three year Teaching Company Scheme collaboration project between Middlesex University and RPAL. The diversity of the task required the participation of three engineers with varying skills: mechanical, software, and electronics
High performance techniques for space mission scheduling
In this paper, we summarize current research at Carnegie Mellon University aimed at development of high performance techniques and tools for space mission scheduling. Similar to prior research in opportunistic scheduling, our approach assumes the use of dynamic analysis of problem constraints as a basis for heuristic focusing of problem solving search. This methodology, however, is grounded in representational assumptions more akin to those adopted in recent temporal planning research, and in a problem solving framework which similarly emphasizes constraint posting in an explicitly maintained solution constraint network. These more general representational assumptions are necessitated by the predominance of state-dependent constraints in space mission planning domains, and the consequent need to integrate resource allocation and plan synthesis processes. First, we review the space mission problems we have considered to date and indicate the results obtained in these application domains. Next, we summarize recent work in constraint posting scheduling procedures, which offer the promise of better future solutions to this class of problems
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