An analytical approach to predict web-warping and longitudinal strain in flexible roll formed sections of variable width

To reduce weight and improve passenger safety there is an increased need in the automotive industry to use Ultra High Strength Steel (UHSS) for structural and crash components. However, the application of UHSS is restricted by their limited formability and the difficulty of forming them in conventional stamping. An alternative method of manufacturing structural auto body parts from UHSS is the flexible roll forming process, which allows the manufacture of metal sheet with high strength and limited ductility into complex and weight-optimized components. One major problem in the flexible roll forming of UHSS is the web-warping defect, which is the deviation in height of the web area over the length of the profile. It has been shown that web-warping is strongly dependant to the permanent longitudinal strain formed in the flange of the part. Flexible roll forming is a continuous process with many roll stands, which makes numerical analysis extremely time intensive and computationally expensive. An analytical model of web-warping is therefore critical to improve design efficiency during the early process design stage before FEA is applied. This paper establishes for the first time an analytical model for the prediction of web-warping for the flexible roll forming of a section with variable width. The model is based on evaluating longitudinal edge strain in the flange of the part. This information is then used in combination with a simple geometrical model to investigate the relationship between web-warping and longitudinal strain with respect to process parameters.

Variable parameter and double sampling (X)over-bar charts in the presence of correlation: The Markov chain approach

The general assumption under which the (X) over bar chart is designed is that the process mean has a constant in-control value. However, there are situations in which the process mean wanders. When it wanders according to a first-order autoregressive (AR (1)) model, a complex approach involving Markov chains and integral equation methods is used to evaluate the properties of the (X) over bar chart. In this paper, we propose the use of a pure Markov chain approach to study the performance of the (X) over bar chart. The performance of the chat (X) over bar with variable parameters and the (X) over bar with double sampling are compared. (C) 2011 Elsevier B.V. All rights reserved.

Analytical approach to the metallomic of Nile tilapia (Oreochromis niloticus) liver tissue by SRXRF and FAAS after 2D-PAGE separation: Preliminary results

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Economic design of (X)over-bar charts with variable parameters: the Markov chain approach

This paper presents an economic design of (X) over bar control charts with variable sample sizes, variable sampling intervals, and variable control limits. The sample size n, the sampling interval h, and the control limit coefficient k vary between minimum and maximum values, tightening or relaxing the control. The control is relaxed when an (X) over bar value falls close to the target and is tightened when an (X) over bar value falls far from the target. A cost model is constructed that involves the cost of false alarms, the cost of finding and eliminating the assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. The assumption of an exponential distribution to describe the length of time the process remains in control allows the application of the Markov chain approach for developing the cost function. A comprehensive study is performed to examine the economic advantages of varying the (X) over bar chart parameters.

Green chromatographic fingerprinting: An environmentally friendly approach for the development of separation methods for fingerprinting complex matrices

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

From Sample Processing to Quantification: A Full Electrochemical Approach for Neutral Analyte Derivatization, Capillary Electrophoresis Separation, and Contactless Conductivity Detection

A thin-layer electrochemical flow cell coupled to capillary electrophoresis with contactless conductivity detection (EC-CE-(CD)-D-4) was applied for the first time to the derivatization and quantification of neutral species using aliphatic alcohols as model compounds. The simultaneous electrooxidation of four alcohols (ethanol, 1-propanol, 1-butanol, and 1-pentanol) to the corresponding carboxylates was carried out on a platinum working electrode in acid medium. The derivatization step required 1 min at 1.6 V vs. Ag/AgCl under stopped flow conditions, which was preceded by a 10 s activation at 0 V. The solution close to the electrode surface was then hydrodynamically injected into the capillary, and a 2.5 min electrophoretic separation was carried out. The fully automated flow system operated at a frequency of 12 analyses per hour. Simultaneous determination of the four alcohols presented detection limits of about 5 x 10(-5) mol As a practical application with a complex matrix, ethanol concentrations were determined in diluted pale lager beer and in nonalcoholic beer. No statistically significant difference was observed between the EC-CE-(CD)-D-4 and gas chromatography with flame ionization detection (GC-FID) results for these samples. The derivatization efficiency remained constant over several hours of continuous operation with lager beer samples (n = 40).

Modeling and classifying variable width riparian zones utilizing digital elevation models, flood height data, digital soil data and national wetlands inventory : a new approach for riparian zone delineation

Riparian zones are dynamic, transitional ecosystems between aquatic and terrestrial ecosystems with well defined vegetation and soil characteristics. Development of an all-encompassing definition for riparian ecotones, because of their high variability, is challenging. However, there are two primary factors that all riparian ecotones are dependent on: the watercourse and its associated floodplain. Previous approaches to riparian boundary delineation have utilized fixed width buffers, but this methodology has proven to be inadequate as it only takes the watercourse into consideration and ignores critical geomorphology, associated vegetation and soil characteristics. Our approach offers advantages over other previously used methods by utilizing: the geospatial modeling capabilities of ArcMap GIS; a better sampling technique along the water course that can distinguish the 50-year flood plain, which is the optimal hydrologic descriptor of riparian ecotones; the Soil Survey Database (SSURGO) and National Wetland Inventory (NWI) databases to distinguish contiguous areas beyond the 50-year plain; and land use/cover characteristics associated with the delineated riparian zones. The model utilizes spatial data readily available from Federal and State agencies and geospatial clearinghouses. An accuracy assessment was performed to assess the impact of varying the 50-year flood height, changing the DEM spatial resolution (1, 3, 5 and 10m), and positional inaccuracies with the National Hydrography Dataset (NHD) streams layer on the boundary placement of the delineated variable width riparian ecotones area. The result of this study is a robust and automated GIS based model attached to ESRI ArcMap software to delineate and classify variable-width riparian ecotones.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

The relation between cognitive and motor performance and their relevance for children’s transition to school: A latent variable approach

Both theoretically and empirically there is a continuous interest in understanding the specific relation between cognitive and motor development in childhood. In the present longitudinal study including three measurement points, this relation was targeted. At the beginning of the study, the participating children were 5-6-year-olds. By assessing participants' fine motor skills, their executive functioning, and their non-verbal intelligence, their cross-sectional and cross-lagged interrelations were examined. Additionally, performance in these three areas was used to predict early school achievement (in terms of mathematics, reading, and spelling) at the end of participants' first grade. Correlational analyses and structural equation modeling revealed that fine motor skills, non-verbal intelligence and executive functioning were significantly interrelated. Both fine motor skills and intelligence had significant links to later school achievement. However, when executive functioning was additionally included into the prediction of early academic achievement, fine motor skills and non-verbal intelligence were no longer significantly associated with later school performance suggesting that executive functioning plays an important role for the motor-cognitive performance link.

Relations among fluid intelligence, sensory discrimination and working memory in middle to late childhood – A latent variable approach

Two factors that have been suggested as key in explaining individual differences in fluid intelligence are working memory and sensory discrimination ability. A latent variable approach was used to explore the relative contributions of these two variables to individual differences in fluid intelligence in middle to late childhood. A sample of 263 children aged 7–12 years was examined. Correlational analyses showed that general discrimination ability (GDA)and working memory (WM) were related to each other and to fluid intelligence. Structural equation modeling showed that within both younger and older age groups and the sample as a whole, the relation between GDA and fluid intelligence could be accounted for by WM. While WM was able to predict variance in fluid intelligence above and beyond GDA, GDA was not able to explain significant amounts of variance in fluid intelligence, either in the whole sample or within the younger or older age group. We concluded that compared to GDA, WM should be considered the better predictor of individual differences in fluid intelligence in childhood. WM and fluid intelligence, while not being separable in middle childhood, develop at different rates, becoming more separable with age.

Generation of targeted retroviral vectors by using single-chain variable fragment: an approach to in vivo gene delivery.

We report the generation of a retroviral vector that infects human cells specifically through recognition of the low density lipoprotein receptor. The rationale for this targeted infection is to add onto the ecotropic envelope protein of Moloney murine leukemia virus, normally trophic for murine cells, a single-chain variable fragment derived from a monoclonal antibody recognizing the human low density lipoprotein receptor. This chimeric envelope protein was used to construct a packaging cell line producing a retroviral vector capable of high-efficiency transfer of the Escherichia coli beta-galactosidase gene to human cells expressing low density lipoprotein receptor. This approach offers a generalized plan to generate cell and tissue-specific retroviral vectors, an essential step toward in vivo gene therapy strategies.

Random error in willingness to pay measurement: A multiple indicators, latent variable approach to the reliability of contingent values

The reliability of measurement refers to unsystematic error in observed responses. Investigations of the prevalence of random error in stated estimates of willingness to pay (WTP) are important to an understanding of why tests of validity in CV can fail. However, published reliability studies have tended to adopt empirical methods that have practical and conceptual limitations when applied to WTP responses. This contention is supported in a review of contingent valuation reliability studies that demonstrate important limitations of existing approaches to WTP reliability. It is argued that empirical assessments of the reliability of contingent values may be better dealt with by using multiple indicators to measure the latent WTP distribution. This latent variable approach is demonstrated with data obtained from a WTP study for stormwater pollution abatement. Attitude variables were employed as a way of assessing the reliability of open-ended WTP (with benchmarked payment cards) for stormwater pollution abatement. The results indicated that participants' decisions to pay were reliably measured, but not the magnitude of the WTP bids. This finding highlights the need to better discern what is actually being measured in VVTP studies, (C) 2003 Elsevier B.V. All rights reserved.