Automated metaphase finding: an assessment of the efficiency of the METAFER2 system in a routine mutagenicity assay

The efficiency of the automated metaphase finding system METAFER2 is assessed in a routine mutagenicity assay using an aneuploid rat liver cell line treated with various promutagens. Data sets generated by automated and manual selection of metaphases are compared. It is demonstrated that METAFER2 routinely allows an efficient automatic identification of metaphases not only in lymphocyte preparations, but also in preparation from mammalian cell lines with varying chromosome numbers. Although larger slide areas are required for automated compared to manual metaphase scanning, the automatic system is faster by a factor of about 5. The interactive visual elimination of metaphases of insufficient quality is an easy and fast procedure.METAFER2 allows an unbiased selection of metaphases irrespective of their appearance as homogeneously stained first or harlequin-staines second division cells. Random selection of metaphases is neither influenced by various structural chromosome changes nor by increased frequencies of sister-chromatid exchanges.     

High-throughput fluorescence-based isolation of live C. elegans larvae

For the nematode Caenorhabditis elegans, automated selection of animals of specific genotypes from a mixed pool has become essential for genetic interaction or chemical screens. To date, such selection has been accomplished using specialized instruments. However, access to such dedicated equipment is not common. Here we describe live animal fluorescence-activated cell sorting (laFACS), a protocol for automatic selection of live first larval stage (L1) animals using a standard FACS system. We show that FACS can be used for the precise identification of GFP-expressing and non-GFP-expressing subpopulations and can accomplish high-speed sorting of live animals. We have routinely collected 100,000 or more homozygotes from a mixed starting population within 2 h, and with greater than 99% purity. The sorted animals continue to develop normally, making this protocol ideally suited for the isolation of terminal mutants for use in genetic interaction or chemical genetic screens.     

Estimation of Part Waiting Time and Fleet Sizing in AGV Systems

As manufacturing systems have grown in size and complexity, material flow control has become one of the key issues for system efficiency, and determination of the number of vehicles required is an important issue in the design of the AGV (automatic guided vehicle) systems for automated material flow control. In an AGV system, a part issues a delivery request for its transportation, and then an empty vehicle is assigned based on a pre-determined vehicle selection rule and provides delivery service.This research presents a fleet sizing procedure for an AGV system with multiple pickup and delivery stations. A queueing model is used to estimate part waiting times. The fleet sizing procedure estimates the minimum number of vehicles needed to ensure a predefined part waiting time limit. While most stochastic models assume first-come-first-served or random vehicle selection rules for the selection of an empty vehicle, this model considers such additional rules as the nearest vehicle selection rule, which is the most popular among all vehicle selection rules. The performance of the proposed model is examined through computational experiments.     

The simultaneous determination of caffeine,aspirin and paracetamol by principal components regression using automatic dilution and calibration

The development of continuous and stepwise automatic dilution and calibration systems that enable analyte dilution and enhancement in multicomponent analyses are described. The continuous system has been used with a robot and the stepwise configuration integrated into a flow-injection analysis system. All analyses are performed using a UV/Visible diode-array detector and data analysis performed using principal components regression. Results of both systems are presented for the simultaneous determination of caffeine, aspirin and paracetamol in pharmaceutical formulations.     

Swarm cognition on off-road autonomous robots

This paper contributes with the first validation of swarm cognition as a useful framework for the design of autonomous robots controllers. The proposed model is built upon the authors’ previous work validated on a simulated robot performing local navigation on a 2-D deterministic world. Based on the ant foraging metaphor and motivated by the multiple covert attention hypothesis, the model consists of a set of simple virtual agents inhabiting the robot’s visual input, searching in a collectively coordinated way for obstacles. Parsimonious and accurate visual attention, operating on a by-need basis, is attained by making the activity of these agents modulated by the robot’s action selection process. A by-product of the system is the maintenance of active, parallel and sparse spatial working memories. In short, the model exhibits the self-organisation of a relevant set of features composing a cognitive system. To show its robustness, the model is extended in this paper to handle the challenges of physical off-road robots equipped with noisy stereoscopic vision sensors. Furthermore, an extensive aggregate of biological arguments sustaining the model is provided. Experimental results show the ability of the model to robustly control the robot on a local navigation task, with less than 1% of the robot’s visual input being analysed. Hence, with this system the computational cost of perception is considerably reduced, thus fostering robot miniaturisation and energetic efficiency. This confirms the advantages of using a swarm-based system, operating in an intricate way with action selection, to judiciously control visual attention and maintain sparse spatial memories, constituting a basic form of swarm cognition.     

Optimised generalized polarisation analysis of C-laurdan reveals clear order differences between T cell membrane compartments

Heterogenous packing of plasma membrane lipids is important for cellular processes like signalling, adhesion and sorting of membrane components. Solvatochromic membrane fluorophores that respond to changes from liquid-ordered (l_o) phase to liquid-disordered (l_d) by red shifts in their emission spectra are often used to assess lipid packing. Their response can be quantified using generalized polarisation (GP) using fluorescence microscopy images from two emission ranges, preferably from a region of interest (ROI) limited to a specific membrane compartment. However, image quality is limited by Poisson noise and convolution by the point spread function of the imaging system. Examining GP-analysis of C-laurdan labelled T cells using the image restoration procedure deconvolution, we demonstrate that deconvolution substantially improves the image resolution by making the plasma membrane clearly discernible and facilitating plasma membrane ROI selection. We conclude that automatic ROI selection has advantages over manual ROI selection when it comes to reproducibility and speed, but reliable GP-measurements can also be obtained by manually demarcated ROIs. We find that deconvolution enhances the difference in GP-values between the plasma and intracellular membranes and demonstrate that moving an intensity defined plasma membrane ROI outwards from the cell further improves this differentiation. By systematically changing the key deconvolution regularization parameter signal to noise, we establish a protocol for deconvolution optimisation applicable to any solvatochromic dye and imaging system. The image processing and ROI selection protocol presented improves both the resolution and precision of GP-measurement and will enable detection of smaller changes in membrane order than is currently achievable.     

Objective threshold selection procedure (OTS) for segmentation of scanning laser confocal microscope images

The determination of volumes and interface areas from confocal laser scanning microscopy (CLSM) images requires the identification of component objects by segmentation. An automated method for the determination of segmentation thresholds for CLSM imaging of biofilms was developed. The procedure, named objective threshold selection (OTS), is a three-dimensional development of the approach introduced by the popular robust automatic threshold selection (RATS) method. OTS is based on the statistical properties of local gray-values and gradients in the image. By characterizing the dependence between a volumetric feature and the intensity threshold used for image segmentation, the former can be determined with an arbitrary confidence level, with no need for user intervention. The identification of an objective segmentation procedure renders the possibility for the full automation of volume and interfacial area measurement. Images from two distinct biofilm systems, acquired using different experimental techniques and instrumental setups were segmented by OTS to determine biofilm volume and interfacial area. The reliability of measurements for each case was analyzed to identify optimal procedure for image acquisition. The automated OTS method was shown to reproduce values obtained manually by an experienced operator.     

Improvement of the lectin-antibody enzyme immunoassay of the alphafetoprotein carbohydrate chain for automation with the enzyme immunoassay robot

The lectin-antibody enzyme immunoassay of the alphafetoprotein-L3 carbohydrate chain, a tumor marker of liver cancer, has not been automated. We improved the technique of the assay for automation. Consequently, alphafetoprotein-L3 and total alphafetoprotein were detected with two lectins using an automatic paramagnetic bead handling robot. This indicates that the improved method is potentially applicable to the automated enzyme immunoassay robot.     

Improvement of the Lectin-Antibody Enzyme Immunoassay of the Alphafetoprotein Carbohydrate Chain for Automation with the Enzyme Immunoassay Robot

The lectin-antibody enzyme immunoassay of the alphafetoprotein-L3 carbohydrate chain, a tumor marker of liver cancer, has not been automated. We improved the technique of the assay for automation. Consequently, alphafetoprotein-L3 and total alphafetoprotein were detected with two lectins using an automatic paramagnetic bead handling robot. This indicates that the improved method is potentially applicable to the automated enzyme immunoassay robot.     

Automated screening of 2D crystallization trials using transmission electron microscopy: A high-throughput tool-chain for sample preparation and microscopic analysis

We have built and extensively tested a tool-chain to prepare and screen two-dimensional crystals of membrane proteins by transmission electron microscopy (TEM) at room temperature. This automated process is an extension of a new procedure described recently that allows membrane protein 2D crystallization in parallel (Iacovache et al., 2010). The system includes a gantry robot that transfers and prepares the crystalline solutions on grids suitable for TEM analysis and an entirely automated microscope that can analyze 96 grids at once without human interference. The operation of the system at the user level is solely controlled within the MATLAB environment: the commands to perform sample handling (loading/unloading in the microscope), microscope steering (magnification, focus, image acquisition, etc.) as well as automatic crystal detection have been implemented. Different types of thin samples can efficiently be screened provided that the particular detection algorithm is adapted to the specific task. Hence, operating time can be shared between multiple users. This is a major step towards the integration of transmission electron microscopy into a high throughput work-flow.     

A memory-based approach to navigation

A memory-based system for autonomous indoor navigation is presented. The system was implemented as a follow-midline reflex on a robot that moves along the corridors of our institute. The robot estimates its position in the environment by comparing the visual input with images contained in its memory. Spatial positions are represented by classes. Memories are formed during a learning phase by encoding labeled images. The output of the system is the a posteriori probability distribution of the classes, given an input image. During performance, an image is assigned to the class that maximizes the probability. This work shows that extensive use of memory can reduce information processing to a simple and flexible procedure, without the need of complicated and specific preprocessing. The system is shown to be reliable, with good generalization capability. With learning limited to a small part of a corridor, the robot navigates along the entire corridor. Furthermore, it is able to move in other corridors of different shape, with different illumination conditions.     

Recombinant fragment assay for gene targetting based on the polymerase chain reaction.

The modification of chromosomal genes by homologous recombination between exogenous DNA and a target locus provides a powerful approach to the study of gene function. One of the current limitations of this gene targetting is the difficulty of identifying cells containing the correctly modified target locus when the modified gene is not amenable to either direct or indirect selection. We here describe a procedure for identifying correctly modified cells that depends on amplifying by the polymerase chain reaction (PCR) predictable fragments of DNA present only in the desired recombinants. This recombinant fragment assay can detect targetted modification using only a few cells, either alone or mixed with tens of thousands of unmodified cells; it does not depend on the phenotype of the modified gene, or on its expression in the target cells. The PCR amplification needed for the procedure is carried out with a heat stable polymerase and a simple automatic temperature-shift apparatus which is described.     

RALPH application for surface mount assembly

Automated assembly in the electronics industry offers many advantages over traditional assembly methods. As product lives become shorter and batch numbers become smaller, new programming methods will be needed to shorten the lead time for these automated lines. Providing a method for humans to interact with the robot in a natural language mode will lead to some of these advantages. Task-level programming deals with the interactions of objects rather than robot motions and therefore requires little robotic expertise but allows for easy and fast programming. One of the long-term projects aimed at alleviating the above problem is the development of a Robotic Assembly Language Planning Hierarchy (RALPH), a task-level automatic robot programming language with natural language commands. In surface mount assembly, the PC board must be populated with chips with high tolerances—a few thousandths of an inch. The part features are so small that human assemblers constantly make mistakes. The redeeming aspect of the components with regard to assembly lies in the geometry of the features. In this article we capitalize on the above geometric attributes of chips and chip pads on PCBs in order to apply the principles of RALPH in the development of a system for automatic assembly.     

Designing pheromone communication in swarm robotics: Group foraging behavior mediated by chemical substance

In swarm robotics, communication among the robots is essential. Inspired by biological swarms using pheromones, we propose the use of chemical compounds to realize group foraging behavior in robot swarms. We designed a fully autonomous robot, and then created a swarm using ethanol as the trail pheromone allowing the robots to communicate with one another indirectly via pheromone trails. Our group recruitment and cooperative transport algorithms provide the robots with the required swarm behavior. We conducted both simulations and experiments with real robot swarms, and analyzed the data statistically to investigate any changes caused by pheromone communication in the performance of the swarm in solving foraging recruitment and cooperative transport tasks. The results show that the robots can communicate using pheromone trails, and that the improvement due to pheromone communication may be non-linear, depending on the size of the robot swarm.     

Multipurpose robot for automated cycle sequencing

Paramagnetic beads have the superior advantages of easy separation and resuspension by controlling the magnetic filed. Previously, we have developed Magtration technology to automate paramagnetic bead handling and have built several automated instruments that handle 1-12 samples simultaneously. To achieve more high-throughput sample processing, two types of a 96-arrayed Integrated Magtration Unit (IMU) were developed, one installed with electromagnets and the other with thin rod-shaped magnets made of neodymium. A multipurpose robot (SX-96GC) equipped with the IMU was also developed for fully automatic processing of 96 samples in parallel. The cleanup of dye-terminator sequencing products was performed using the robot installed with the permanent magnet version of IMU. The results had quality comparable to those by the same protocol in manual handling or to those by the conventional protocols. The robot processed 96 samples in a microplate within 30 min. The protocol that can purify 384 samples within 1 h by processing two microplates concurrently was successfully designed.     

A knowledge-based system for the strategic control level of robots in flexible manufacturing cells

The strategic control level synthesis for robots is related to a hierarchical robot control problem. The main control problem at the strategic control level is to select the model and algorithm to be used by the lower control level to execute the given robot task. Usually there are several lower control level models and algorithms that can be used by the robot control system for every robot task. Strategic control level synthesis depends on the particular robot system application. In a typical application, when the robot system is used in a flexible manufacturing system for manipulating various part types, the robot tasks executed by the robot system depend on the manufacturing processes in the system. If the robot system is applied in another flexible manufacturing system, dedicated to other manufacturing processes, another set of robot tasks might be needed to perform the necessary operations. Therefore, the quantity and the kind of knowledge required in the system for the strategic control level differ from one application to another. Such a fact creates the appropriate conditions for employing some artificial intelligence techniques. This article describes a knowledge-based system approach to the strategic control level synthesis problem.     

Computer analysis of protein-protein interaction

An automatic procedure which generates possible modes of protein-protein association is developed and applied to the bovine pancreatic trypsin inhibitor-trypsin complex as a test case. Using a simplified model in which each residue is replaced by one interaction center, all possible modes of interaction between the inhibitor and the active center of the enzyme are generated systematically. The non-bonded interactions between the molecules and the protein surface area buried in the generated interfaces are evaluated and used as criteria for selecting stable complexes. We show that satisfactory estimates of accessible and buried surface areas can be made using the simplified model.The procedure leads to about nine structures having non-bonded interactions and buried surface areas similar to those of the native complex. This suggests that the major contributions to the free energy of dissociation are taken into account by our selection procedure, though complementarity and specificity are not properly represented in the simplified model. However, it makes it possible to scan a much larger number of configurations than would otherwise be feasible, chiefly through elimination of side-chain detail.     

A Novel Vision Localization Method of Automated Micro-Polishing Robot

Based on photogrammetry technology,a novel localization method of micro-polishing robot,which is restricted withincertain working space,is presented in this paper.On the basis of pinhole camera model,a new mathematical model of visionlocalization of automated polishing robot is established.The vision localization is based on the distance-constraints of featurepoints.The method to solve the mathematical model is discussed.According to the characteristics of gray image,an adaptivemethod of automatic threshold selection based on connected components is presented.The center coordinate of the featureimage point is resolved by bilinear interpolation gray square weighted algorithm.Finally,the mathematical model of testingsystem is verified by global localization test.The experimental results show that the vision localization system in working spacehas high precision.     

Simple chemical reaction systems with limit cycle behaviour

It is shown that for exhibiting limit cycle behaviour a two-component chemical reaction system has to involve at least three reactions among which one must be autocatalytic of the type 2X + … ? 3X + … Under this condition, possible candidates for chemical limit cycle systems are selected by postulating their steady state to be an instable focus. This procedure can be reduced to the selection of appropriate stoichiometric coefficients and is readily performed by a medium size computer. The result is quite a lot of limit cycle systems which are altogether simpler than, for example, the “Brusselator” with its number of four reactions. One of the results is briefly discussed.     

A COMPUTERIZED SYSTEM FOR CONTROLLING AND MEASURING GUSTATORY REACTION TIMES

Reaction Time (RT) procedures are widely used in cognitive and behavioral experiments. In the sensory realm RT has been traditionally applied to measure visual, auditory or motor responses. The application of the RT method to gustatory stimuli has proved to be difficult. Attempts to develop automatic control techniques have been restrained by difficulties related to the control of variables, e.g. physiochemical characteristics of chemical solutions and the procedure for stimulus presentation. In this report we describe a computer based system that was designed to measure the reaction time to taste solutions dropped on the tongue. The equipment consists of a pumping system, an interface between the computer and the pumping system, the software required to control the interface and to measure reaction time, and a push button to detect the subject's response. The system can be used as a tool for both research and evaluation tests.