On model-driven design of robot software using co-simulation

Abstract. In this paper we show that using co-simulation for robot software design will be more efficient than without co-simulation. We will show an example of the plotter how the co-simulation is helping with the design process. We believe that a collaborative methodology based on model-driven design will improve the chances of closing the design loop early, improving cross-discipline design dialog, and reduce errors, saving cost and time

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

System design support of cyber-physical systems: a co-simulation and co-modelling approach

The goal of this research is to support system-level design for CPS devices from methods perspective with corresponding tooling support to bridge the existing design gap. In this work, a set of methods are provided that support different exper- tise to understand CPS design from a system level, instead of only considering one single specific discipline. In order to avoid confusions across the different domains, a list of explained terms is provided. Co-design support guidelines (co-design flows) that consider different backgrounds of the possible designers and different system properties are discussed in detail. Following the step-wise refinement design steps, a CPS is firstly modelled in a top-level model, then detailed out with different focuses of the interest: such as dynamic-behaviour oriented, control-logic oriented and contract oriented. A way of working, to reduce unnecessary design iterations and help engineers to structure the cyber part software in a way that the whole system can act more robust, is also discussed. This includes a general method of modelling the possible faults using a layered controller structure. From these two aspects, the resulting system design is made more robust (fault-tolerant). From a tooling support aspect, a design-support software framework is in- troduced. A co-simulation framework is presented that supports expertise from different domains to work together, which can enable early stage testing to avoid high expenses (both money and time wise) in the development cycle. This framework combines two domain-specific tools with an appropriate synchro- nization scheme for the co-simulation engine. Additionally, a domain-specific scripting language (DCL) is introduced to ease the change of a co-model sce- nario during the co-simulation, such as fault injections. With the assistance of the co-simulation framework, engineers have a practical tool that can facilitate the system-level design of CPS devices. With the aid of design space explo- ration (DSE) tool support, system designers can make better early-stage design choices. The methods and the tooling support introduced in this work are demon- strated in two different case studies with different focuses: the mobile robot case study aims to demonstrate the design space exploration facility; the slider setup is focussed on demonstrating fault-tolerant mechanisms

Analysis of Chromatin Modification and Remodeling in the Transcriptional Regulation of the Wnt/Wg Pathway.

The Wnt/Wingless pathway regulates many developmental events and is conserved throughout the animal kingdom. Disruption of the Wnt/Wingless pathway has been linked with many diseases. Due to its importance, how Wnt/Wingless signals to influence animal development has been intensively studied. Although many nuclear proteins have been implicated to regulate Wnt/Wingless transcription, some of which are chromatin remodelers, direct evidence for chromatin alteration of Wnt/Wingless target genes is largely lacking. In this thesis, I will discuss the roles of both ATP-dependant chromatin remodeling and histone covalent modification in transcriptional regulation by Wingless (Wg, the fly Wnt). Chapter I is a general introduction to our current knowledge of the Wnt/Wg signaling pathway and chromatin remodeling. In chapter II, evidence for the Wg induction of widespread histone acetylation is presented. In contrast to many other studies which found histone acetylation at distinct loci, we found widespread histone acetylation induced by Wg signaling at two Wg target regions that was independent of transcription. Possible histone acetyltransferases required for histone acetylation is be discussed. In chapter III, I present my work on how Polycomb group proteins and H3K27 methylation negatively regulate transcription of Wg target genes. High levels of H3K27me3 at Wg targets are regulated by the histone methyltransferase Enhancer of Zeste (E(z)), a Polycomb group protein; E(z) is required for repression of Wg targets. However, Wg activation does not necessarily remove H3K27me3, and the implication of this phenomenon is discussed. In chapter IV, I discuss dual roles for the ATP-dependent chromatin remodeler Brm complexes in Wg transcriptional regulation. Brm complexes are required to repress some Wg targets in the absence of Wg signaling; whereas, other targets require Brm complexes to be fully activated by Wg. The directness of the regulation is discussed.Ph.D.Molecular, Cellular, and Developmental BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/77770/1/niyunyun_1.pd

A co-modelling method for solving incompatibilities during co-design of mechatronic devices

The design process of mechatronic devices, which involves experts from different disciplines working together, has limited time and resource constraints. These experts normally have their own domain-specific designing methods and tools, which can lead to incompatibilities when one needs to work together using these those methods and tools. Having a proper framework which integrates different design tools is of interest, as such a framework can prevent incompatibilities between parts during the design process. In this paper, we propose our co-modelling methodology and co-simulation tools integration framework, which helps to maintain the domain specific properties of the model components during the co-design process of various mechatronic devices. To avoid expensive rework later in the design phase and even possible system failure, fault modelling and a layered structure with fault-tolerance mechanisms for the controller software are introduced. In the end, a practical mechatronic device is discussed to illustrate the methods and tools which are presented in this paper in details

Model-Driven Robot-Software Design using integrated Models and Co-Simulation

The work presented here is on a methodology for design of hard real-time embedded control software for robots, i.e. mechatronic products. The behavior of the total robot system (machine, control, software and I/O) is relevant, because the dynamics of the machine influences the robot software. Therefore, we use two appropriate Models of Computation, which represent continuous-time equations for the machine / robot part, and discrete event / discrete time equations for the control software part. To compute (simulate) such combined models, co-simulation of these models is used. The design work can be done as a stepwise refinement process, whereby each step is verified via co-simulation. This in general yields a shorter design time, and a better quality product. The tools pass model-specific information between each other via parametrized tokens in the generated, high-level code to get a better separation of design steps. This allows for better quality of the models and more reuse, thus enhancing the efficiency of model-driven design for the (industrial) end user. The method is illustrated with a case study using the tools, some of which are at the prototype level. Especially the structuring of the models and regularly doing simulations (of which some can be ’repeated’ as real experiments), is beneficial, shortening the development time and producing better models. Future work is to test the method on more complex cases, and to extend the method by detailing out the electronics and mechanics sub design flows

Disrupted Module Efficiency of Structural and Functional Brain Connectomes in Clinically Isolated Syndrome and Multiple Sclerosis

Recent studies have demonstrated disrupted topological organization of brain connectome in multiple sclerosis (MS). However, whether the communication efficiency between different functional systems is affected in the early stage of MS remained largely unknown. In this study, we constructed the structural connectivity (SC) and functional connectivity (FC) networks in 41 patients with clinically isolated syndrome (CIS), 32 MS patients and 35 healthy controls (HC) based on diffusion and resting-state functional MRI. To quantify the communication efficiency within and between different functional systems, we proposed two measures called intra- and inter-module efficiency. Based on the module parcellation of functional backbone network, the intra- and inter-module efficiency of SC and FC networks was calculated for each participant. For the SC network, CIS showed decreased inter-module efficiency between the sensory-motor network (SMN), the visual network (VN), the default-mode network (DMN) and the fronto-parietal network (FPN) compared with HC, while MS showed more widespread decreased module efficiency both within and between modules relative to HC and CIS. For the FC network, no differences were found between CIS and HC, and a decreased inter-module efficiency between SMN and FPN and between VN and FPN was identified in MS, compared with HC and CIS. Moreover, both intra- and inter-module efficiency of SC network were correlated with the disability and cognitive scores in MS. Therefore, our results demonstrated early SC changes between modules in CIS, and more widespread SC alterations and inter-module FC changes were observed in MS, which were further associated with cognitive impairment and physical disability

Collaborative Modelling and Co-Simulation with DESTECS: A Pilot Study

This paper describes a collaborative modelling ex- ercise using the DESTECS framework. The DESTECS approach allows engineers and software designers to collaborate to produce system models that contain a discrete-event (DE) model of a controller and continuous-time (CT) model of a plant. We call these models co-models and call their execution co-simulation. The DESTECS tool couples existing DE and CT tools (Overture and 20-sim, respectively) allowing engineers to use paradigms and tools with which they are familiar, while collaborating to construct these shared system models. The work involved collaborative modelling of a line-following robot. We report on both the details of the models and experience in producing them

Model-Driven Robot-Software Design using integrated Models and Co-Simulation

The work presented here is on a methodology for design of hard real-time embedded control software for robots, i.e. mechatronic products. The behavior of the total robot system (machine, control, software and I/O) is relevant, because the dynamics of the machine influences the robot software. Therefore, we use two appropriate Models of Computation, which represent continuous-time equations for the machine / robot part, and discrete event / discrete time equations for the control software part. To compute (simulate) such combined models, co-simulation of these models is used. The design work can be done as a stepwise refinement process, whereby each step is verified via co-simulation. This in general yields a shorter design time, and a better quality product. The tools pass model-specific information between each other via parametrized tokens in the generated, high-level code to get a better separation of design steps. This allows for better quality of the models and more reuse, thus enhancing the efficiency of model-driven design for the (industrial) end user. The method is illustrated with a case study using the tools, some of which are at the prototype level. Especially the structuring of the models and regularly doing simulations (of which some can be ’repeated’ as real experiments), is beneficial, shortening the development time and producing better models. Future work is to test the method on more complex cases, and to extend the method by detailing out the electronics and mechanics sub design flows

Simultaneous SNP identification and assessment of allele-specific bias from ChIP-seq data

Yunyun Ni, Amelia Weber Hall, Anna Battenhouse and Vishwanath R Iyer are with the Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, Section of Molecular Genetics and Microbiology, University of Texas at Austin, Austin, TX 78712, USABackground: Single nucleotide polymorphisms (SNPs) have been associated with many aspects of human development and disease, and many non-coding SNPs associated with disease risk are presumed to affect gene regulation. We have previously shown that SNPs within transcription factor binding sites can affect transcription factor binding in an allele-specific and heritable manner. However, such analysis has relied on prior whole-genome genotypes provided by large external projects such as HapMap and the 1000 Genomes Project. This requirement limits the study of allele-specific effects of SNPs in primary patient samples from diseases of interest, where complete genotypes are not readily available. Results: In this study, we show that we are able to identify SNPs de novo and accurately from ChIP-seq data generated in the ENCODE Project. Our de novo identified SNPs from ChIP-seq data are highly concordant with published genotypes. Independent experimental verification of more than 100 sites estimates our false discovery rate at less than 5%. Analysis of transcription factor binding at de novo identified SNPs revealed widespread heritable allele-specific binding, confirming previous observations. SNPs identified from ChIP-seq datasets were significantly enriched for disease-associated variants, and we identified dozens of allele-specific binding events in non-coding regions that could distinguish between disease and normal haplotypes. Conclusions: Our approach combines SNP discovery, genotyping and allele-specific analysis, but is selectively focused on functional regulatory elements occupied by transcription factors or epigenetic marks, and will therefore be valuable for identifying the functional regulatory consequences of non-coding SNPs in primary disease samples.Center for Systems and Synthetic BiologyInstitute for Cellular and Molecular BiologyMolecular [email protected]