Electrochemical performance and modeling of lithium‐sulfur batteries with varying carbon to sulfur ratios

Lithium‐sulfur batteries have attracted much research interest because of their high theoretical energy density and low‐cost raw materials. While the electrodes are composed of readily available materials, the processes that occur within the cell are complex, and the electrochemical performance of these batteries is very sensitive to a number of cell processing parameters. Herein, a simple electrochemical model will be used to predict, with quantitative agreement, the electrochemical properties of lithium‐sulfur cathodes with varying carbon to sulfur ratios. The discharge capacity and the polarization were very similar for the lowest sulfur loadings, while above 23.2 wt% sulfur the gravimetric capacity dropped significantly, and there was an increase in the cell polarization. In addition, a transition in the electrode morphology, from well dispersed to aggregated sulfur at the surface, will be reflected in the change in a critical model parameter demonstrating the sensitivity and functionality of even this simple model in predicting complex behavior in the lithium‐sulfur cells.     

Monitoring manufacturing system availability

The monitoring of production line availability on a day-to-day basis and for continuous improvement is approached from a control charting point of view. Control limits are developed along with the length of time between monitoring periods to control accuracy. This provides a convenient way to monitor the availability measure at any desired level of accuracy.     

Novel macro-microporous gelatin scaffold fabricated by particulate leaching for soft tissue reconstruction with adipose-derived stem cells

The restoration of body contours as shaped by adipose tissue remains a clinical challenge specifically in patients who have experienced loss of contour due to trauma, surgical removal of tumours or congenital abnormalities. We have developed a novel macro-microporous biomaterial for use in soft tissue re-bulking and augmentation. Alginate beads provided the pore template for the construct. Incorporation, and subsequent dissolution, of the beads within a 7 % (w/v) gelatin matrix, produced a highly porous scaffold with an average pore size of 2.01 ± 0.08 mm. The ability of this scaffold to support the in vitro growth and differentiation of human adipose-derived stem cells (ADSCs) was then investigated. Histological analysis confirmed that the scaffold itself provided a suitable environment to support the growth of ADSCs on the scaffold walls. When delivered into the macropores in a fibrin hydrogel, ADSCs proliferated and filled the pores. In addition, ADSCs could readily be differentiated along the adipogenic lineage. These results therefore describe a novel scaffold that can support the proliferation and delivery of ADSCs. The scaffold is the first stage in developing a clinical alternative to current treatment methods for soft tissue reconstruction.     

Real-time tool control and job dispatching in flexible manufacturing systems

A method of loading a set of tools to the different machining centres of a shop is presented, where each part visits only one of the machining centres for its entire processing. Any tools which are required but unavailable for the processing of a part are borrowed from other machining centres. As a real-time control, the tool-returning policies for those borrowed tools and the job-dispatching rules at the machining centres are evaluated to maximize the throughput performance of the shop. Some experimental results are provided.     

Determination of moisture content of polyamide 66 directly from combination region near‐infrared spectra

The hygroscopic nature of polyamide (PA) polymers motivates the development of analysis tools for use in assessing their moisture content. Among possible analysis techniques, near‐infrared (near‐IR) spectroscopy is non‐destructive, requires little or no sample preparation, and is compatible with sample thicknesses on the order of mm. The work reported here makes use of transmission near‐IR spectroscopy in the combination region (5000–4000 cm^?1) to develop a protocol for assessing the moisture content of PA 66 samples directly from their spectral intensities after preprocessing with the standard normal variate transform and partial least‐squares. The method is compatible with online or continuous monitoring applications and can be calibrated without the use of destructive reference measurements such as thermogravimetric analysis. The long‐term calibration performance of the technique is evaluated, and on a scale of 0–100% moisture uptake, the standard error of prediction is found to average 1.4% over 6 months. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40645.     

An exploratory study for investigating the critical success factors for cloud migration in the Saudi Arabian higher education context

Saudi universities have at their disposal a huge number of low cost IT resources to aid in teaching, research and learning. By migrating to cloud services, Saudi universities will be moving data and programs from local servers to the internet, thereby providing users with the ability to access and share information at any time from multiple devices. The migration to cloud-based IT resources is not yet widespread in Saudi universities due to several challenges including security, legal policies and implementation. At present, there is lack of research and guidance for Saudi universities on how to overcome these challenges and how contextual factors can influence the successful migration to the educational clouds.This research presents a framework for the successful migration to cloud technology in the Saudi Arabian universities. In this research, a set of key critical success factors (CSFs) were identified by synthesizing components from studies concerned with the migration of cloud for higher education and factors identified from the successful implementation of WBL (Web Based Learning) and ERP (Enterprise Resource Planning) on higher education in Saudi Arabia. Based on this knowledge, the proposed framework was evaluated via expert review and a survey by IT specialists from the Saudi universities. The initial CSFs were updated based on the expert reviews and the results were analysed. Based on the findings at this stage, additional CSFs were added to the framework as suggested by the experts. Subsequently, in order to confirm the reviewed CSFs, additional investigation via a structured online questionnaire was conducted and the outcome was analysed via one-sample t-test with the data integrity analysed via Cronbach’s alpha. The outcome indicated the majority of CSFs to be statistically significant except the Physical Location CSF. Potential future study and contributions are discussed.     

Enterprise Performance Management: Making it Work

Abstract

Enterprise performance management (EPM) is the integration of control and improvement methods imbedded with analytics. Its methods include the strategy map, balanced scorecards, costing (including activity based cost management), budgeting, forecasting and resource capacity requirements planning. These methods fuel other core solutions such as customer relationship management (CRM), supply chain management (SCM), risk management, and human capital management systems, as well as lean management and Six Sigma initiatives.     

Instabilities of Regression Estimates Relating Air Pollution to Mortality

The instability of ordinary least squares estimates of linear regression coefficients is demonstrated for mortality rates regressed around various socioeconomic, weather and pollution variables. A ridge regression technique presented by Hoer1 and Kennard (Technometrics 12 (1970) 69–82) is employed to arrive at “stable” regression coefficients which, in some instances, differ considerably from the ordinary least squares estimates. In addition, two methods of variable elimination are compared—one based on total squared error and the other on a ridge trace analysis.     

A Procedure to Estimate the Population Mean In Random Effects Models

A general procedure for estimating the population mean in random effects models of the nested and/of classification type is considered. The suggested estimator is unbiased and consistent (with respect to the structure of the experimental design). It is also optimal with respect to a particular quadratic, location-sensitive criterion. Finally, for experimental designs which contain a certain degree of structural balance, the suggested estimator coincides with the sample mean.