132 resultados para predictive equation


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Organotypic models may provide mechanistic insight into colorectal cancer (CRC) morphology. Three-dimensional (3D) colorectal gland formation is regulated by phosphatase and tensin homologue deleted on chromosome 10 (PTEN) coupling of cell division cycle 42 (cdc42) to atypical protein kinase C (aPKC). This study investigated PTEN phosphatase-dependent and phosphatase-independent morphogenic functions in 3D models and assessed translational relevance in human studies. Isogenic PTEN-expressing or PTEN-deficient 3D colorectal cultures were used. In translational studies, apical aPKC activity readout was assessed against apical membrane (AM) orientation and gland morphology in 3D models and human CRC. We found that catalytically active or inactive PTEN constructs containing an intact C2 domain enhanced cdc42 activity, whereas mutants of the C2 domain calcium binding region 3 membrane-binding loop (M-CBR3) were ineffective. The isolated PTEN C2 domain (C2) accumulated in membrane fractions, but C2 M-CBR3 remained in cytosol. Transfection of C2 but not C2 M-CBR3 rescued defective AM orientation and 3D morphogenesis of PTEN-deficient Caco-2 cultures. The signal intensity of apical phospho-aPKC correlated with that of Na/H exchanger regulatory factor-1 (NHERF-1) in the 3D model. Apical NHERF-1 intensity thus provided readout of apical aPKC activity and associated with glandular morphology in the model system and human colon. Low apical NHERF-1 intensity in CRC associated with disruption of glandular architecture, high cancer grade, and metastatic dissemination. We conclude that the membrane-binding function of the catalytically inert PTEN C2 domain influences cdc42/aPKC-dependent AM dynamics and gland formation in a highly relevant 3D CRC morphogenesis model system.

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The generalized Langevin equation (GLE) has been recently suggested to simulate the time evolution of classical solid and molecular systems when considering general nonequilibrium processes. In this approach, a part of the whole system (an open system), which interacts and exchanges energy with its dissipative environment, is studied. Because the GLE is derived by projecting out exactly the harmonic environment, the coupling to it is realistic, while the equations of motion are non-Markovian. Although the GLE formalism has already found promising applications, e. g., in nanotribology and as a powerful thermostat for equilibration in classical molecular dynamics simulations, efficient algorithms to solve the GLE for realistic memory kernels are highly nontrivial, especially if the memory kernels decay nonexponentially. This is due to the fact that one has to generate a colored noise and take account of the memory effects in a consistent manner. In this paper, we present a simple, yet efficient, algorithm for solving the GLE for practical memory kernels and we demonstrate its capability for the exactly solvable case of a harmonic oscillator coupled to a Debye bath.

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To test the applicability of the sex-specific 2008 Framingham general cardiovascular risk equation for coronary heart disease (CHD) and stroke in European middle-aged men from Ireland and France.

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Aim: The aim of this paper is to identify best practice relating to the effective management of materials in an urban, confined construction site, using structural equation modelling.

Methodology: A literature review, case study analysis and questionnaire survey are employed, with the results scrutinised using confirmatory factor analysis in the form of structural equation modelling.

Results: The following are the leading strategies in the management of materials in a confined urban site environment; (1) Consult and review the project programme, (2) Effective communication and delivery, (3) Implement site safety management plans, and (4) Proactive spatial monitoring and control.

Implication for Practice: With the relentless expansion of urban centres and the increasing high cost of materials, any potential savings made on-site would translate into significant monetary concessions on completion of a development.

Originality/Value: As on-site project management professionals successfully identify and implement the various strategies in the management of plant and materials on a confined urban site, successful resource management in this restrictive environment is attainable.

Innovative Aspect of Paper: An empirical study of three different construction sites in three different countries (Ireland, England and USA) together with a questionnaire survey from the industry, investigating the managerial strategies in the management of plant and material in confined urban site environments

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In this paper we describe the design of a parallel solution of the inhomogeneous Schrodinger equation, which arises in the construction of continuum orbitals in the R-matrix theory of atomic continuum processes. A prototype system is described which has been programmed in occam2 and implemented on a bi-directional pipeline of transputers. Some timing results for the prototype system are presented, and the development of a full production system is discussed.

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Predictive Demand Response (DR) algorithms allow schedulable loads in power systems to be shifted to off-peak times. However, the size of the optimisation problems associated with predictive DR can grow very large and so efficient implementations of algorithms are desirable. In this paper Laguerre functions are used to significantly reduce the size of the optimisation needed to implement predictive DR, thus significantly increasing the efficiency of the implementation. © 2013 IEEE.

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In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

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In this paper a multiple classifier machine learning methodology for Predictive Maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance issues given the increasing need to minimize downtime and associated costs. One of the challenges with PdM is generating so called ’health factors’ or quantitative indicators of the status of a system associated with a given maintenance issue, and determining their relationship to operating costs and failure risk. The proposed PdM methodology allows dynamical decision rules to be adopted for maintenance management and can be used with high-dimensional and censored data problems. This is achieved by training multiple classification modules with different prediction horizons to provide different performance trade-offs in terms of frequency of unexpected breaks and unexploited lifetime and then employing this information in an operating cost based maintenance decision system to minimise expected costs. The effectiveness of the methodology is demonstrated using a simulated example and a benchmark semiconductor manufacturing maintenance problem.

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Thermocouples are one of the most popular devices for temperature measurement due to their robustness, ease of manufacture and installation, and low cost. However, when used in certain harsh environments, for example, in combustion systems and engine exhausts, large wire diameters are required, and consequently the measurement bandwidth is reduced. This article discusses a software compensation technique to address the loss of high frequency fluctuations based on measurements from two thermocouples. In particular, a difference equation (DE) approach is proposed and compared with existing methods both in simulation and on experimental test rig data with constant flow velocity. It is found that the DE algorithm, combined with the use of generalized total least squares for parameter identification, provides better performance in terms of time constant estimation without any a priori assumption on the time constant ratios of the thermocouples.

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This paper reports an approach by which laboratory based testing and numerical modelling can be combined to predict the long term performance of a range of concretes exposed to marine environments. Firstly, a critical review of the test methods for assessing the chloride penetration resistance of concrete is given. The repeatability of the different test results is also included. In addition to the test methods, a numerical simulation model is used to explore the test data further to obtain long-term chloride ingress trends. The combined use of testing and modelling is validated with the help of long-term chloride ingress data from a North Sea exposure site. In summary, the paper outlines a methodology for determining the long term performance of concrete in marine environments.

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In modern semiconductor manufacturing facilities maintenance strategies are increasingly shifting from traditional preventive maintenance (PM) based approaches to more efficient and sustainable predictive maintenance (PdM) approaches. This paper describes the development of such an online PdM module for the endpoint detection system of an ion beam etch tool in semiconductor manufacturing. The developed system uses optical emission spectroscopy (OES) data from the endpoint detection system to estimate the RUL of lenses, a key detector component that degrades over time. Simulation studies for historical data for the use case demonstrate the effectiveness of the proposed PdM solution and the potential for improved sustainability that it affords.