959 resultados para Cellular automata models


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Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management.

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Protein N-terminal acetylation (Nt-acetylation) is an important mediator of protein function, stability, sorting, and localization. Although the responsible enzymes are thought to be fairly well characterized, the lack of identified in vivo substrates, the occurrence of Nt-acetylation substrates displaying yet uncharacterized N-terminal acetyltransferase (NAT) specificities, and emerging evidence of posttranslational Nt-acetylation, necessitate the use of genetic models and quantitative proteomics. NatB, which targets Met-Glu-, Met-Asp-, and Met-Asn-starting protein N termini, is presumed to Nt-acetylate 15% of all yeast and 18% of all human proteins. We here report on the evolutionary traits of NatB from yeast to human and demonstrate that ectopically expressed hNatB in a yNatB-Δ yeast strain partially complements the natB-Δ phenotypes and partially restores the yNatB Nt-acetylome. Overall, combining quantitative N-terminomics with yeast studies and knockdown of hNatB in human cell lines, led to the unambiguous identification of 180 human and 110 yeast NatB substrates. Interestingly, these substrates included Met-Gln- N-termini, which are thus now classified as in vivo NatB substrates. We also demonstrate the requirement of hNatB activity for maintaining the structure and function of actomyosin fibers and for proper cellular migration. In addition, expression of tropomyosin-1 restored the altered focal adhesions and cellular migration defects observed in hNatB-depleted HeLa cells, indicative for the conserved link between NatB, tropomyosin, and actin cable function from yeast to human.

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Tissue Engineering is a promising emerging field that studies the intrinsic regenerative potential of the human body and uses it to restore functionality of damaged organs or tissues unable of self-healing due to illness or ageing. In order to achieve regeneration using Tissue Engineering strategies, it is first necessary to study the properties of the native tissue and determine the cause of tissue failure; second, to identify an optimum population of cells capable of restoring its functionality; and third, to design and manufacture a cellular microenvironment in which those specific cells are directed towards the desired cellular functions. The design of the artificial cellular niche has a tremendous importance, because cells will feel and respond to both its biochemical and biophysical properties very differently. In particular, the artificial niche will act as a physical scaffold for the cells, allowing their three-dimensional spatial organization; also, it will provide mechanical stability to the artificial construct; and finally, it will supply biochemical and mechanical cues to control cellular growth, migration, differentiation and synthesis of natural extracellular matrix. During the last decades, many scientists have made great contributions to the field of Tissue Engineering. Even though this research has frequently been accompanied by vast investments during extended periods of time, yet too often these efforts have not been enough to translate the advances into new clinical therapies. More and more scientists in this field are aware of the need of rational experimental designs before carrying out complex, expensive and time-consuming in vitro and in vivo trials. This review highlights the importance of computer modeling and novel biofabrication techniques as critical key players for a rational design of artificial cellular niches in Tissue Engineering.

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The dynamics describing the motion response of a marine structure in waves can be represented within a linear framework by the Cummins Equation. This equation contains a convolution term that represents the component of the radiation forces associated with fluid memory effects. Several methods have been proposed in the literature for the identification of parametric models to approximate and replace this convolution term. This replacement can facilitate the model implementation in simulators and the analysis of motion control designs. Some of the reported identification methods consider the problem in the time domain while other methods consider the problem in the frequency domain. This paper compares the application of these identification methods. The comparison is based not only on the quality of the estimated models, but also on the ease of implementation, ease of use, and the flexibility of the identification method to incorporate prior information related to the model being identified. To illustrate the main points arising from the comparison, a particular example based on the coupled vertical motion of a modern containership vessel is presented.

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Time-domain models of marine structures based on frequency domain data are usually built upon the Cummins equation. This type of model is a vector integro-differential equation which involves convolution terms. These convolution terms are not convenient for analysis and design of motion control systems. In addition, these models are not efficient with respect to simulation time, and ease of implementation in standard simulation packages. For these reasons, different methods have been proposed in the literature as approximate alternative representations of the convolutions. Because the convolution is a linear operation, different approaches can be followed to obtain an approximately equivalent linear system in the form of either transfer function or state-space models. This process involves the use of system identification, and several options are available depending on how the identification problem is posed. This raises the question whether one method is better than the others. This paper therefore has three objectives. The first objective is to revisit some of the methods for replacing the convolutions, which have been reported in different areas of analysis of marine systems: hydrodynamics, wave energy conversion, and motion control systems. The second objective is to compare the different methods in terms of complexity and performance. For this purpose, a model for the response in the vertical plane of a modern containership is considered. The third objective is to describe the implementation of the resulting model in the standard simulation environment Matlab/Simulink.

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The motion of marine vessels has traditionally been studied using two different approaches: manoeuvring and seakeeping. These two approaches use different reference frames and coordinate systems to describe the motion. This paper derives the kinematic models that characterize the transformation of motion variables (position, velocity, accelerations) and forces between the different coordinate systems used in these theories. The derivations hereby presented are done in terms of the formalism adopted in robotics. The advantage of this formulation is the use of matrix notation and operations. As an application, the transformation of linear equations of motion used in seakeeping into body-fixed coordinates is considered for both zero and forward speed.

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Introduction Epithelial-to-mesenchymal transition (EMT) promotes cell migration and is important in metastasis. Cellular proliferation is often downregulated during EMT, and the reverse transition (MET) in metastases appears to be required for restoration of proliferation in secondary tumors. We studied the interplay between EMT and proliferation control by MYB in breast cancer cells. Methods MYB, ZEB1, and CDH1 expression levels were manipulated by lentiviral small-hairpin RNA (shRNA)-mediated knockdown/overexpression, and verified with Western blotting, immunocytochemistry, and qRT-PCR. Proliferation was assessed with bromodeoxyuridine pulse labeling and flow cytometry, and sulforhodamine B assays. EMT was induced with epidermal growth factor for 9 days or by exposure to hypoxia (1% oxygen) for up to 5 days, and assessed with qRT-PCR, cell morphology, and colony morphology. Protein expression in human breast cancers was assessed with immunohistochemistry. ZEB1-MYB promoter binding and repression were determined with Chromatin Immunoprecipitation Assay and a luciferase reporter assay, respectively. Student paired t tests, Mann–Whitney, and repeated measures two-way ANOVA tests determined statistical significance (P < 0.05). Results Parental PMC42-ET cells displayed higher expression of ZEB1 and lower expression of MYB than did the PMC42-LA epithelial variant. Knockdown of ZEB1 in PMC42-ET and MDA-MB-231 cells caused increased expression of MYB and a transition to a more epithelial phenotype, which in PMC42-ET cells was coupled with increased proliferation. Indeed, we observed an inverse relation between MYB and ZEB1 expression in two in vitro EMT cell models, in matched human breast tumors and lymph node metastases, and in human breast cancer cell lines. Knockdown of MYB in PMC42-LA cells (MYBsh-LA) led to morphologic changes and protein expression consistent with an EMT. ZEB1 expression was raised in MYBsh-LA cells and significantly repressed in MYB-overexpressing MDA-MB-231 cells, which also showed reduced random migration and a shift from mesenchymal to epithelial colony morphology in two dimensional monolayer cultures. Finally, we detected binding of ZEB1 to MYB promoter in PMC42-ET cells, and ZEB1 overexpression repressed MYB promoter activity. Conclusions This work identifies ZEB1 as a transcriptional repressor of MYB and suggests a reciprocal MYB-ZEB1 repressive relation, providing a mechanism through which proliferation and the epithelial phenotype may be coordinately modulated in breast cancer cells.

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The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

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This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

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This paper presents the application of a statistical method for model structure selection of lift-drag and viscous damping components in ship manoeuvring models. The damping model is posed as a family of linear stochastic models, which is postulated based on previous work in the literature. Then a nested test of hypothesis problem is considered. The testing reduces to a recursive comparison of two competing models, for which optimal tests in the Neyman sense exist. The method yields a preferred model structure and its initial parameter estimates. Alternatively, the method can give a reduced set of likely models. Using simulated data we study how the selection method performs when there is both uncorrelated and correlated noise in the measurements. The first case is related to instrumentation noise, whereas the second case is related to spurious wave-induced motion often present during sea trials. We then consider the model structure selection of a modern high-speed trimaran ferry from full scale trial data.

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Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N equals 137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.

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Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

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Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.

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In vitro analyses of basement membrane invasiveness employing Matrigel (a murine tumor extract rich in basement membrane components) have been performed on human breast cancer model systems. Constitutive invasiveness of different human breast cancer (HBC) cell lines has been examined as well as regulation by steroid hormones, growth factors, and oncogenes. Carcinoma cells exhibiting a mesenchymal-like phenotype (vimentin expression, lack of cell border associated uvomorulin) show dramatically increased motility, invasiveness, and metastatic potential in nude mice. These findings support the hypothesis that epithelial to mesenchymal transition (EMT)-like events may be instrumental in the metastatic progression of human breast cancer. The MCF-7 subline MCF-7ADR appears to have undergone such a transition. The importance of such a transition may be reflected in the emergence of vimentin expression as an indicator of poor prognosis in HBC. Matrix degradation and laminin recognition are highlighted as potential targets for antimetastatic therapy, and analyses of laminin attachment and the matrix metalloproteinase (MMP) family in HBC cell lines are summarized. Matrigel-based assays have proved useful in the study of the molecular mechanisms of basement membrane invasiveness, their regulation in HBC cells, and their potential as targets for antimetastatic therapy.

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We have established and characterized a series of variant cell lines in which to identify the critical factors associated with E2-induced malignant progression, and the acquisition to tamoxifen resistance in human breast cancer. Sublines of the hormone-dependent MCF-7 cell line (MCF7/MIII and MCF7/LCC1) form stable, invasive, estrogen independent tumors in the mammary fat pads of ovariectomized athymic nude mice. These cells retain expression of both estrogen (ER) and progesterone receptors (PGR), but retain sensitivity to each of the major structural classes of antiestrogens. The tamoxifen-resistant MCF7/LCC2 cells retain sensitivity to the inhibitory effects of the steroidal antiestrogen ICI 182780. By comparing the parental hormone-dependent and variant hormone-independent cells, we have demonstrated an altered expression of some estrogen regulated genes (PGR, pS2, cathepsin D) in the hormone-independent variants. Other genes remain normally estrogen regulated (ER, laminin receptor, EGF-receptor). These data strongly implicate the altered regulation of a specific subset or network of estrogen regulated genes in the malignant progression of human breast cancer. Some of the primary response genes in this network may exhibit dose-response and induction kinetics similar to pS2, which is constitutively upregulated in the MCF7/MIII, MCF7/LCC1 and MCF7/LCC2 cells.