Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

Religiosity and emotional disturbance: A test of Ellis's thesis in his own counseling center.

Assessed the validity of A. Ellis's (1971, 1973, 1981) contention that being religious was negatively correlated with mental health. 28 very religious, 34 atheist, and 33 religiously-neutral individuals seeking consultation were compared on the frequency and number of 8 reported problems. Contrary to Ellis's prediction, there were no significant differences among the groups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

建立基于模型设计文化的最佳策略

本文引入了基于模型设计的概念,突出了其中的一些优点,详细讨论了组织中采用基于模型设计文化的10个最佳策略。这些最佳策略从不同工业领域的公司中收集,包括向基于模型设计的成功或者不成功的过渡。     

Engineering extruded collagen fibers for biomedical applications

Extruded collagen fibers constitute a promising biomimetic scaffold for tissue engineering applications. In this study, we compared the structural, thermal, and mechanical properties of fibers produced from either NaCl or poly(ethylene glycol) with a number-average molecular weight of 8000 (PEG 8K), the only two coagents that have been used in the fabrication process. As novel, we report the fabrication of fibers with properties similar to native or synthetic fibers using other coagents. NaCl derived fibers were characterized by higher thermal stability (p < 0.026), stress (p < 0.001), and modulus (p < 0.0025) values than PEG 8K, whereas the latter yielded more extendable fibers (p < 0.012). Poly(ethylene glycol)s with number-average molecular weights of 200 and 1000 produced fibers with similar mechanical properties (p > 0.05) that were thinner (p < 0.033), stiffer (p < 0.022), and less extendable (p < 0.0002) than those of PEG 8K. Poly(vinyl alcohol) (PVA) with a number-average average molecular weight of 9–10,000 and PEG 8K yielded fibers with similar diameters and stress-at-break values (p > 0.05); however, the poly(ethylene glycol) derived fibers were more extendable (p < 0.0003), whereas the PVA fibers were stiffer (p < 0.029). Gum-arabic- and soluble-starch-derived fibers were of similar tensile strength, extendibility, and stiffness (p > 0.05). In this in vitro study, the thickest (p < 0.011) and the weakest (p < 0.0066) fibers were produced in the presence of sodium sulfate. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

On the effectiveness of early life cycle defect prediction with Bayesian Nets

Standard practice in building models in software engineering normally involves three steps: collecting domain knowledge (previous results, expert knowledge); building a skeleton of the model based on step 1 including as yet unknown parameters; estimating the model parameters using historical data. Our experience shows that it is extremely difficult to obtain reliable data of the required granularity, or of the required volume with which we could later generalize our conclusions. Therefore, in searching for a method for building a model we cannot consider methods requiring large volumes of data. This paper discusses an experiment to develop a causal model (Bayesian net) for predicting the number of residual defects that are likely to be found during independent testing or operational usage. The approach supports (1) and (2), does not require (3), yet still makes accurate defect predictions (an R ² of 0.93 between predicted and actual defects). Since our method does not require detailed domain knowledge it can be applied very early in the process life cycle. The model incorporates a set of quantitative and qualitative factors describing a project and its development process, which are inputs to the model. The model variables, as well as the relationships between them, were identified as part of a major collaborative project. A dataset, elicited from 31 completed software projects in the consumer electronics industry, was gathered using a questionnaire distributed to managers of recent projects. We used this dataset to validate the model by analyzing several popular evaluation measures (R ², measures based on the relative error and Pred). The validation results also confirm the need for using the qualitative factors in the model. The dataset may be of interest to other researchers evaluating models with similar aims. Based on some typical scenarios we demonstrate how the model can be used for better decision support in operational environments. We also performed sensitivity analysis in which we identified the most influential variables on the number of residual defects. This showed that the project size, scale of distributed communication and the project complexity cause the most of variation in number of defects in our model. We make both the dataset and causal model available for research use.     

Anion Sensing Porphyrin Functionalized Nanoparticles

Disulfide and dithiocarbamate functionalized porphyrins have been synthesized and used as protecting ligands for gold nanoparticle formation either via ligand substitution reactions or by direct synthesis. These nanoparticles have been shown to recognize anions via changes in the absorbance spectrum of the surface adsorbed porphyrin moieties. Association constants, derived from quantitative titrations, indicate a remarkable surface enhancement effect where the surface bound porphyrins bind anions much more strongly than the free receptor in solution.     

Yodel: A Yield Stress Model for Suspensions

A model for the yield stress of particulate suspensions is presented that incorporates microstructural parameters taking into account volume fraction of solids, particle size, particle size distribution, maximum packing, percolation threshold, and interparticle forces. The model relates the interparticle forces between particles of dissimilar size and the statistical distribution of particle pairs expected for measured or log-normal size distributions. The model is tested on published data of sub-micron ceramic suspensions and represents the measured data very well, over a wide range of volume fractions of solids. The model shows the variation of the yield stress of particulate suspensions to be inversely proportional to the particle diameter. Not all the parameters in the model could be directly evaluated; thus, two were used as adjustable variables: the maximum packing fraction and the minimum interparticle separation distance. The values for these two adjustable variables provided by the model are in good agreement with separate determinations of these parameters. This indicates that the model and the approximations used in its derivation capture the main parameters that influence the yield stress of particulate suspensions and should help us to better predict changes in the rheological properties of complex suspensions. The model predicts the variation of the yield stress of particulate suspensions to be inversely proportional to the particle diameter, but the experimental results do not show a clear dependence on diameter. This result is consistent with previous evaluations, which have shown significant variations in this dependence, and the reasons behind the yield stress dependence on particle size are discussed in the context of the radius of curvature of particles at contact.     

Shear mode coupling and tilted grain growth of A1N thin films in BAW resonators.

Polycrystalline A1N thin films were deposited by RF reactive magnetron sputtering on Pt(111)/Ti electrode films. The substrates were tilted by an angle ranging from 40 degrees to 70 degrees with respect to the target normal. A low deposition temperature and a high sputter gas pressure were found ideal for tilted growth. The resulting grain tilt angle amounts to about half the substrate tilt angle. For coupling evaluation, 5 GHz solidly mounted resonator structures have been realized. The tilted grain A1N films exhibited a permittivity in the 9.5-10.5 range and loss tangent of 0.3%. Two shear modes as well as the longitudinal mode could be clearly identified. The coupling coefficient k2(eff) of the fundamental thickness shear mode (TS0) was found to be about 0.5%, which is compatible with a c-axis tilt of about 6 degrees.