Culture supernatant of Shiga toxin-producing Escherichia coli strains provoke fluid accumulation in rabbit ileal loops

In the present study, in order to get a better insight into the mechanism of action of cyclophosphamide (CY) in rheumatoid arthritis (RA), we monitored the changes in lymphocytes' expression of leukocyte function associated antigen 1 (LFA-1). A group of 28 patients with refractory severe RA were treated with CY and methylprednisolone (MO) intravenously. Using flow cytometry we evaluated the changes in LFA-1 molecule expression on peripheral lymphocytes. In the analyzed group of patients the proportion of LFA-1 "dim" cells was reduced. After the treatment the ratio was partly normalized. Twelve months after cessation of the therapy high proportion of LFA-1 "dim" was observed only among CY/MP treated patients. The changes were related to clinical improvement. Based on the obtained data, it seems, that the treatment affecting the expression of LFA-1 may slow down lymphocyte migration and by that limit chronic inflammation within the synovium.     

Optimal Designs of the Variable Sample Size Chart Based on Median Run Length and Expected Median Run Length

The variable sample size (VSS) chart, devoted to the detection of moderate mean shifts, has been widely investigated under the context of the average run‐length criterion. Because the shape of the run‐length distribution alters with the magnitude of the mean shifts, the average run length is a confusing measure, and the use of percentiles of the run‐length distribution is considered as more intuitive. This paper develops two optimal designs of the VSS chart, by minimizing (i) the median run length and (ii) the expected median run length for both deterministic and unknown shift sizes, respectively. The 5th and 95th percentiles are also provided in order to measure the variation in the run‐length distribution. Two VSS schemes are considered in this paper, that is, when the (i) small sample size (n_S) or (ii) large sample size (n_L) is predefined for the first subgroup (n₁). The Markov chain approach is adopted to evaluate the performance of these two VSS schemes. The comparative study reveals that improvements in the detection speed are found for these two VSS schemes without increasing the in‐control average sample size. For moderate to large mean shifts, the optimal VSS chart with n₁ = n_L significantly outperforms the optimal EWMA chart, while the former is comparable to the latter when n₁ = n_S. Copyright © 2016 John Wiley & Sons, Ltd.     

Adaptive CUSUM and EWMA charts with auxiliary information and variable sampling intervals for monitoring the process mean

The variable sampling interval (VSI) feature enhances the sensitivity of a control chart that is based on fixed sampling interval (FSI). In this paper, we enhance the sensitivities of the auxiliary information-based (AIB) adaptive Crosier cumulative sum (CUSUM) (AIB-ACC) and adaptive exponentially weighted moving average (EWMA) (AIB-AE) charts using the VSI feature when monitoring a mean shift which is expected to lie within a given interval. The Monte Carlo simulations are used to compute zero-state and steady-state run length properties of these control charts. It is found that the AIB-ACC and AIB-AE charts with VSI feature are uniformly more sensitive than those based on FSI feature. Real datasets are also considered to demonstrate the implementation of these control charts.     

Hotelling's T2 control charts with fixed and variable sample sizes for monitoring short production runs

Short production runs are common in enterprises that require a high degree of flexibility and variety in manufacturing processes. To date, past research on short production runs has little focus on the multivariate control charts. In view of this, fixed sample size (FSS) and variable sample size (VSS) Hotelling's T² charts are designed to monitor the process mean when the production horizon is finite. Optimal parameters to minimize the out‐of‐control (1) truncated average run length (TARL) and (2) expected TARL (ETARL) are provided such that the in‐control TARL is equal to the number of inspections (say I). The numerical study considers the run length performances of the FSS and VSS T² short‐run charts for both known and unknown shift sizes. The VSS T² short‐run chart performs well in swiftly detecting various mean shifts in comparison with the FSS T² short‐run chart. Additionally, the VSS T² short‐run chart is superior to the FSS T² short‐run chart, in terms of the truncated standard deviation of the run length, expected truncated standard deviation of the run length, probability that the chart signals an alarm within the I inspections, ie, P(I) and expected P(I). A case study on the impurity profile of a crystalline drug substance illustrates the implementation of the VSS T² short‐run chart.     

An EWMA control chart for the multivariate coefficient of variation

Monitoring the multivariate coefficient of variation over time is a natural choice when the focus is on stabilising the relative variability of a multivariate process, as is the case in a significant number of real situations in engineering, health sciences, and finance, to name but a few areas. However, not many tools are available to practitioners with this aim. This paper introduces a new control chart to monitor the multivariate coefficient of variation through an exponentially weighted moving average (EWMA) scheme. Concrete methodologies to calculate the limits and evaluate the performance of the chart proposed and determine the optimal values of the chart's parameters are derived based on a theoretical study of the statistic being monitored. Computational experiments reveal that our proposal clearly outperforms existing alternatives, in terms of the average run length to detect an out‐of‐control state. A numerical example is included to show the efficiency of our chart when operating in practice.     

Negative differential resistance in carbon atomic wire-carbon nanotube junctions

Negative differential resistance (NDR) was recently observed in carbon nanotube junctions just before breaking and hypothesized to arise from the formation of monatomic carbon wires in the junction. Motivated by these results, a first-principles scattering-state approach, based on density functional theory, is used to study the transport properties of carbon chains covalently connecting metallic carbon nanotube leads at finite bias. The I- V characteristics of short carbon chains are predicted to exhibit even-odd behavior, and NDR is found for both even and odd chain junctions in our calculations.     

A Rough-Set-Based Approach for Classification and Rule Induction

The inconsistency of information about objects may be the greatest obstacle to performing inductive learning from examples. Rough sets theory provides a new mathematical tool to deal with uncertainty and vagueness. Based on rough sets theory, this paper proposes a novel approach for the classification and rule induction of inconsistent information systems. It is achieved by integrating rough sets theory with a statistics-based inductive learning algorithm. The framework of a proto-type rough-set-based classification system (RClass) is presented. Two examples are used to verify the prototype system. The results of the validation are discussed.     

Variable feed rates and variable machine forces for a constant material removal rate and constant cutting force along Pythagorean-hodograph curves

This paper proposes a new machining strategy to realize better dimensional accuracy as well as surface finish. The strategy attempts to keep cutting force and the material removal rate approximately constant and force the tool to move along a so-called Pythagorean-hodograph curve, which is a group of analytic curves with special properties, in a milling operation. In conventional milling operations, a constant feed rate is frequently used. This would invariably lead to higher material removal rates in concave regions and lower material removal rates in convex regions, and affects dimensional accuracy. This work aims to establish the theoretical basis to show how the above-mentioned phenomenon can be predicted. Additionally, chattering is a well-known problem in machining. In this work, it is postulated that keeping certain machining conditions approximately constant would help in reducing chattering during machining. A numerical example is given to illustrate the proposed machining strategy.     

Economically Optimum Design of a Synthetic Chart

This paper proposes an economic model for the synthetic chart. The synthetic chart is an integration of the chart and the CRL chart. A simplified algorithm to obtain the optimal parameters of the synthetic chart which minimizes the expected cost function is introduced. Numerical examples based on different values of input parameters are given, and sensitivity analyses of the parameters are performed. The input parameters which have a significant impact on the cost and choice of optimal parameters of the synthetic chart are identified. The effect of incorrect estimation of the input parameters is also investigated, and it is found that the optimal design parameters are quite robust to changes in the input parameters, except the shift parameter. It is also shown that if the chart cannot be operated at the economically optimal level, there is still a large choice of parameters to choose from which does not result in a large increase in cost. All the above analyses and results are based on numerical examples and verified through simulation over a wide range of parameter values. Comparisons are also performed among the synthetic Shewhart and EWMA charts. Based on the numerical examples and simulation over a wide range of parameter values, it is shown that the synthetic chart has better economic performance than the other two control charts under most conditions. Copyright © 2011 John Wiley & Sons, Ltd.     

The variable sampling interval X̄ chart with estimated parameters

The VSI chart has been investigated by many researchers under the assumption of known process parameters. However, in practice, these parameters are usually unknown and it is necessary to estimate them from the past data. In this paper, we evaluate and compare the performance of the VSI chart in terms of its average time to signal in the case where the process parameters are known and in the case where these parameters are estimated. We also provide new chart constants taking into account the number of phase I samples. Copyright © 2011 John Wiley & Sons, Ltd.