Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Direct analysis of dried blood spots coupled with mass spectrometry: concepts and biomedical applications.

Because of the emergence of dried blood spots (DBS) as an attractive alternative to conventional venous plasma sampling in many pharmaceutical companies and clinical laboratories, different analytical approaches have been developed to enable automated handling of DBS samples without any pretreatment. Associated with selective and sensitive MS-MS detection, these procedures give good results in the rapid identification and quantification of drugs (generally less than 3 min total run time), which is desirable because of the high throughput requirements of analytical laboratories. The objective of this review is to describe the analytical concepts of current direct DBS techniques and to present their advantages and disadvantages, with particular focus on automation capacity and commercial availability. Finally, an overview of the different biomedical applications in which these concepts could be of major interest will be presented.

Application of Molecular Diagnostic Techniques for Viral Testing.

Nucleic acid amplification techniques are commonly used currently to diagnose viral diseases and manage patients with this kind of illnesses. These techniques have had a rapid but unconventional route of development during the last 30 years, with the discovery and introduction of several assays in clinical diagnosis. The increase in the number of commercially available methods has facilitated the use of this technology in the majority of laboratories worldwide. This technology has reduced the use of some other techniques such as viral culture based methods and serological assays in the clinical virology laboratory. Moreover, nucleic acid amplification techniques are now the methods of reference and also the most useful assays for the diagnosis in several diseases. The introduction of these techniques and their automation provides new opportunities for the clinical laboratory to affect patient care. The main objectives in performing nucleic acid tests in this field are to provide timely results useful for high-quality patient care at a reasonable cost, because rapid results are associated with improvements in patients care. The use of amplification techniques such as polymerase chain reaction, real-time polymerase chain reaction or nucleic acid sequence-based amplification for virus detection, genotyping and quantification have some advantages like high sensitivity and reproducibility, as well as a broad dynamic range. This review is an up-to-date of the main nucleic acid techniques and their clinical applications, and special challenges and opportunities that these techniques currently provide for the clinical virology laboratory.

Evaluation of three automated systems for susceptibility testing of enterobacteria containing qnrB, qnrS, and/or aac(6')-Ib-cr.

The accuracy of the MicroScan WalkAway, BD Phoenix, and Vitek-2 systems for susceptibility testing of quinolones and aminoglycosides against 68 enterobacteria containing qnrB, qnrS, and/or aac(6 ')-Ib-cr was evaluated using reference microdilution. Overall, one very major error (0.09%), 6 major errors (0.52%), and 45 minor errors (3.89%) were noted.

A distributed environment for virtual and/or real experiments for underwater robots

This paper presents the distributed environment for virtual and/or real experiments for underwater robots (DEVRE). This environment is composed of a set of processes running on a local area network composed of three sites: 1) the onboard AUV computer; 2) a surface computer used as human-machine interface (HMI); and 3) a computer used for simulating the vehicle dynamics and representing the virtual world. The HMI can be transparently linked to the real sensors and actuators dealing with a real mission. It can also be linked with virtual sensors and virtual actuators, dealing with a virtual mission. The aim of DEVRE is to assist engineers during the software development and testing in the lab prior to real experiments

Dynamic modelling of an underwater vehicle

Nessie is an Autonomous Underwater Vehicle (AUV) created by a team of students in the Heriot Watt University to compete in the Student Autonomous Underwater Competition, Europe (SAUC-E) in August 2006. The main objective of the project is to find the dynamic equation of the robot, dynamic model. With it, the behaviour of the robot will be easier to understand and movement tests will be available by computer without the need of the robot, what is a way to save time, batteries, money and the robot from water inside itself. The object of the second part in this project is setting a control system for Nessie by using the model

Optimization of floor cleaning coverage performance of a random path-planning mobile robot

Floor cleaning is a typical robot application. There are several mobile robots aviable in the market for domestic applications most of them with random path-planning algorithms. In this paper we study the cleaning coverage performances of a random path-planning mobile robot and propose an optimized control algorithm, some methods to estimate the are of the room, the evolution of the cleaning and the time needed for complete coverage.

Automatic recognition of postural allocations.

A significant part of daily energy expenditure may be attributed to non-exercise activity thermogenesis and exercise activity thermogenesis. Automatic recognition of postural allocations such as standing or sitting can be used in behavioral modification programs aimed at minimizing static postures. In this paper we propose a shoe-based device and related pattern recognition methodology for recognition of postural allocations. Inexpensive technology allows implementation of this methodology as a part of footwear. The experimental results suggest high efficiency and reliability of the proposed approach.

PANACEA (Platform for Automatic, Normalised Annotation and Cost-Effective Acquisition of Language Resources for Human Language Technologies)

The objective of PANACEA is to build a factory of LRs that automates the stages involved in the acquisition, production, updating and maintenance of LRs required by MT systems and by other applications based on language technologies, and simplifies eventual issues regarding intellectual property rights. This automation will cut down the cost, time and human effort significantly. These reductions of costs and time are the only way to guarantee the continuous supply of LRs that MT and other language technologies will be demanding in the multilingual Europe.

Relatedness influences signal reliability in evolving robots.

Communication is an indispensable component of animal societies, yet many open questions remain regarding the factors affecting the evolution and reliability of signalling systems. A potentially important factor is the level of genetic relatedness between signallers and receivers. To quantitatively explore the role of relatedness in the evolution of reliable signals, we conducted artificial evolution over 500 generations in a system of foraging robots that can emit and perceive light signals. By devising a quantitative measure of signal reliability, and comparing independently evolving populations differing in within-group relatedness, we show a strong positive correlation between relatedness and reliability. Unrelated robots produced unreliable signals, whereas highly related robots produced signals that reliably indicated the location of the food source and thereby increased performance. Comparisons across populations also revealed that the frequency for signal production-which is often used as a proxy of signal reliability in empirical studies on animal communication-is a poor predictor of signal reliability and, accordingly, is not consistently correlated with group performance. This has important implications for our understanding of signal evolution and the empirical tools that are used to investigate communication.

Using robots to understand social behaviour.

A major challenge in studying social behaviour stems from the need to disentangle the behaviour of each individual from the resulting collective. One way to overcome this problem is to construct a model of the behaviour of an individual, and observe whether combining many such individuals leads to the predicted outcome. This can be achieved by using robots. In this review we discuss the strengths and weaknesses of such an approach for studies of social behaviour. We find that robots-whether studied in groups of simulated or physical robots, or used to infiltrate and manipulate groups of living organisms-have important advantages over conventional individual-based models and have contributed greatly to the study of social behaviour. In particular, robots have increased our understanding of self-organization and the evolution of cooperative behaviour and communication. However, the resulting findings have not had the desired impact on the biological community. We suggest reasons for why this may be the case, and how the benefits of using robots can be maximized in future research on social behaviour.

Revision of the neotropical species of empididae (Diptera) described by Mario Bezzi: IX. The species described in Atrichopleura Bezzi and the description of a new species

Revision of the Neotropical species of Empididae (Diptera) described by Mario Bezzi. IX. The species described in Atrichopleura Bezzi and the description of a new species. Four Neotropical species of Empididae described by Bezzi in Atrichopleura Bezzi, 1909 are redescribed: A. crassa (lectotype, pres. desig.), A. hirtipes (lectotype, pres. desig.), A. nitida (lectotype, pres. desig.), A. schnusei (lectotype, pres. desig.). Atrichopleura bezzii sp. nov. is described from among syntypes of A. schnusei.

Automation in clinical bacteriology: what system to choose?

With increased activity and reduced financial and human resources, there is a need for automation in clinical bacteriology. Initial processing of clinical samples includes repetitive and fastidious steps. These tasks are suitable for automation, and several instruments are now available on the market, including the WASP (Copan), Previ-Isola (BioMerieux), Innova (Becton-Dickinson) and Inoqula (KIESTRA) systems. These new instruments allow efficient and accurate inoculation of samples, including four main steps: (i) selecting the appropriate Petri dish; (ii) inoculating the sample; (iii) spreading the inoculum on agar plates to obtain, upon incubation, well-separated bacterial colonies; and (iv) accurate labelling and sorting of each inoculated media. The challenge for clinical bacteriologists is to determine what is the ideal automated system for their own laboratory. Indeed, different solutions will be preferred, according to the number and variety of samples, and to the types of sample that will be processed with the automated system. The final choice is troublesome, because audits proposed by industrials risk being biased towards the solution proposed by their company, and because these automated systems may not be easily tested on site prior to the final decision, owing to the complexity of computer connections between the laboratory information system and the instrument. This article thus summarizes the main parameters that need to be taken into account for choosing the optimal system, and provides some clues to help clinical bacteriologists to make their choice.

Identification of geometrically consistent interest points for 3D scene reconstruction

We propose an algorithm that extracts image features that are consistent with the 3D structure of the scene. The features can be robustly tracked over multiple views and serve as vertices of planar patches that suitably represent scene surfaces, while reducing the redundancy in the description of 3D shapes. In other words, the extracted features will off er good tracking properties while providing the basis for 3D reconstruction with minimum model complexity

Automated DNA extraction using the QIAsymphony platform: Estimation of DNA recovery from simulated forensic stains

The aim of this study was to evaluate the forensic protocol recently developed by Qiagen for the QIAsymphony automated DNA extraction platform. Samples containing low amounts of DNA were specifically considered, since they represent the majority of samples processed in our laboratory. The analysis of simulated blood and saliva traces showed that the highest DNA yields were obtained with the maximal elution volume available for the forensic protocol, that is 200 ml. Resulting DNA extracts were too diluted for successful DNA profiling and required a concentration. This additional step is time consuming and potentially increases inversion and contamination risks. The 200 ml DNA extracts were concentrated to 25 ml, and the DNA recovery estimated with real-time PCR as well as with the percentage of SGM Plus alleles detected. Results using our manual protocol, based on the QIAamp DNA mini kit, and the automated protocol were comparable. Further tests will be conducted to determine more precisely DNA recovery, contamination risk and PCR inhibitors removal, once a definitive procedure, allowing the concentration of DNA extracts from low yield samples, will be available for the QIAsymphony.