Using Bayesian Programming for Multisensor Multi-Target Tracking in Automative Applications

A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. Carsense is a European project whose purpose is to develop such a new sensing system. It will combine different sensors (laser, radar and video) and will rely on the fusion of the information coming from these sensors in order to achieve better accuracy, robustness and an increase of the information content. This paper demonstrates the interest of using probabilistic reasoning techniques to address this challenging multi-sensor data fusion problem. The approach used is called Bayesian Programming. It is a general approach based on an implementation of the Bayesian theory. It was introduced rst to design robot control programs but its scope of application is much broader and it can be used whenever one has to deal with problems involving uncertain or incomplete knowledge

A Potential Role for Drosophila Mucins in Development and Physiology

Vital vertebrate organs are protected from the external environment by a barrier that to a large extent consists of mucins. These proteins are characterized by poorly conserved repeated sequences that are rich in prolines and potentially glycosylated threonines and serines (PTS). We have now used the characteristics of the PTS repeat domain to identify Drosophila mucins in a simple bioinformatics approach. Searching the predicted protein database for proteins with at least 4 repeats and a high ST content, more than 30 mucin-like proteins were identified, ranging from 300–23000 amino acids in length. We find that Drosophila mucins are present at all stages of the fly life cycle, and that their transcripts localize to selective organs analogous to sites of vertebrate mucin expression. The results could allow for addressing basic questions about human mucin-related diseases in this model system. Additionally, many of the mucins are expressed in selective tissues during embryogenesis, thus revealing new potential functions for mucins as apical matrix components during organ morphogenesis

Systematic Analysis of Cis-Elements in Unstable mRNAs Demonstrates that CUGBP1 Is a Key Regulator of mRNA Decay in Muscle Cells

BACKGROUND: Dramatic changes in gene expression occur in response to extracellular stimuli and during differentiation. Although transcriptional effects are important, alterations in mRNA decay also play a major role in achieving rapid and massive changes in mRNA abundance. Moreover, just as transcription factor activity varies between different cell types, the factors influencing mRNA decay are also cell-type specific. PRINCIPAL FINDINGS: We have established the rates of decay for over 7000 transcripts expressed in mouse C2C12 myoblasts. We found that GU-rich (GRE) and AU-rich (ARE) elements are over-represented in the 3'UTRs of short-lived mRNAs and that these mRNAs tend to encode factors involved in cell cycle and transcription regulation. Stabilizing elements were also identified. By comparing mRNA decay rates in C2C12 cells with those previously measured for pluripotent and differentiating embryonic stem (ES) cells, we identified several groups of transcripts that exhibit cell-type specific decay rates. Further, whereas in C2C12 cells the impact of GREs on mRNA decay appears to be greater than that of AREs, AREs are more significant in ES cells, supporting the idea that cis elements make a cell-specific contribution to mRNA stability. GREs are recognized by CUGBP1, an RNA-binding protein and instability factor whose function is affected in several neuromuscular diseases. We therefore utilized RNA immunoprecipitation followed by microarray (RIP-Chip) to identify CUGBP1-associated transcripts. These mRNAs also showed dramatic enrichment of GREs in their 3'UTRs and encode proteins linked with cell cycle, and intracellular transport. Interestingly several CUGBP1 substrate mRNAs, including those encoding the myogenic transcription factors Myod1 and Myog, are also bound by the stabilizing factor HuR in C2C12 cells. Finally, we show that several CUGBP1-associated mRNAs containing 3'UTR GREs, including Myod1, are stabilized in cells depleted of CUGBP1, consistent with the role of CUGBP1 as a destabilizing factor. CONCLUSIONS: Taken together, our results systematically establish cis-acting determinants of mRNA decay rates in C2C12 myoblast cells and demonstrate that CUGBP1 associates with GREs to regulate decay of a wide range of mRNAs including several that are critical for muscle development

Present state and future perspectives of using pluripotent stem cells in toxicology research

The use of novel drugs and chemicals requires reliable data on their potential toxic effects on humans. Current test systems are mainly based on animals or in vitro–cultured animal-derived cells and do not or not sufficiently mirror the situation in humans. Therefore, in vitro models based on human pluripotent stem cells (hPSCs) have become an attractive alternative. The article summarizes the characteristics of pluripotent stem cells, including embryonic carcinoma and embryonic germ cells, and discusses the potential of pluripotent stem cells for safety pharmacology and toxicology. Special attention is directed to the potential application of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) for the assessment of developmental toxicology as well as cardio- and hepatotoxicology. With respect to embryotoxicology, recent achievements of the embryonic stem cell test (EST) are described and current limitations as well as prospects of embryotoxicity studies using pluripotent stem cells are discussed. Furthermore, recent efforts to establish hPSC-based cell models for testing cardio- and hepatotoxicity are presented. In this context, methods for differentiation and selection of cardiac and hepatic cells from hPSCs are summarized, requirements and implications with respect to the use of these cells in safety pharmacology and toxicology are presented, and future challenges and perspectives of using hPSCs are discussed

RiskStructures : A Design Algebra for Risk-Aware Machines

Machines, such as mobile robots and delivery drones, incorporate controllers responsible for a task while handling risk (e.g. anticipating and mitigating hazards; and preventing and alleviating accidents). We refer to machines with this capability as risk-aware machines. Risk awareness includes robustness and resilience, and complicates monitoring (i.e., introspection, sensing, prediction), decision making, and control. From an engineering perspective, risk awareness adds a range of dependability requirements to system assurance. Such assurance mandates a correct-by-construction approach to controller design, based on mathematical theory. We introduce RiskStructures, an algebraic framework for risk modelling intended to support the design of safety controllers for risk-aware machines. Using the concept of a risk factor as a modelling primitive, this framework provides facilities to construct, examine, and assure these controllers. We prove desirable algebraic properties of these facilities, and demonstrate their applicability by using them to specify key aspects of safety controllers for risk-aware automated driving and collaborative robots

From path to trajectory deformation

10.1109/IROS.2007.4399235IEEE International Conference on Intelligent Robots and Systems159-16485RB