Simultaneous determination of pyruvate and acetate levels in xanthan biopolymer by infrared spectroscopy: effect of spectral pre-processing for solid-state analysis

A rapid, direct, and reagent-free procedure based on solid-state Fourier transform infrared spectroscopy (FT-IR) coupled with partial least squares (PLS) data analysis has been developed for simultaneous determination of pyruvate and acetate levels in a microbial xanthan biopolymer. The influences of various spectral pre-processing procedures were studied in order to eliminate effects caused by sample preparation. It was determined that the combination of first derivative and orthogonal signal correction pre-processing contributes to a significant increase in the predictive performance of PLS-1 regression models. By employing the wavenumber region 1320–1350 cm⁻¹ for pyruvate determination and 1500–1600 cm⁻¹ for acetate determination, the root mean square error of cross-validation (RMSECV) for pyruvate and acetate contents were obtained 0.13% and 0.29% w/w, respectively. Results of the proposed procedure for different real samples and those obtained by their reference methods were compared.     

Analysis of DLL Jitter due to Voltage-Controlled Delay Line

In this paper we analyze jitter in a delay-locked loop (DLL) due to uncertainties in the voltage-controlled delay line (VCDL). To obtain a closed-form equation for jitter in the DLL, time-domain equations of the DLL are used. The jitter at the intermediate stages of the VCDL and the jitter of a conventional delay cell are analyzed. The simulation results show that the jitter of the DLL due to mismatch of the delay cells is zero at the beginning and end of the VCDL and is highest at the middle of the VCDL. Also, a DLL is designed in TSMC 0.18 μm CMOS technology to show the accuracy of the proposed analytical method.     

An immune algorithm for scheduling a hybrid flow shop with sequence-dependent setup times and machines with random breakdowns

Much of the research on operations scheduling problems has either ignored setup times or assumed that setup times on each machine are independent of the job sequence. Furthermore, most scheduling problems that have been discussed in the literature are under the assumption that machines are continuously available. Nevertheless, in most real-life industries a machine can be unavailable for many reasons, such as unanticipated breakdowns (stochastic unavailability), or due to scheduled preventive maintenance where the periods of unavailability are known in advance (deterministic unavailability). This paper deals with hybrid flow shop scheduling problems in which there are sequence-dependent setup times (SDSTs), and machines suffer stochastic breakdowns, to optimise objectives based on the expected makespan. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. An immune algorithm (IA) can be used to tackle complex problems and produce a reasonable manufacturing schedule within an acceptable time. In this research, a computational method based on a clonal selection principle and an affinity maturation mechanism of the immune response is used. This paper describes how we can incorporate simulation into an immune algorithm for the scheduling of a SDST hybrid flow shop with machines that suffer stochastic breakdowns. The results obtained are analysed using a Taguchi experimental design.     

Wall Decay Coefficient Estimation in a Real-Life Drinking Water Distribution Network

Water Resources Management - Injection of chlorine as a disinfectant and the correct prediction of the residual amount in water distribution networks are key points and important principles in the...     

PDE-constrained optimization in medical image analysis

PDE-constrained optimization problems find many applications in medical image analysis, for example, neuroimaging, cardiovascular imaging, and oncologic imaging. We review the related literature and give examples of the formulation, discretization, and numerical solution of PDE-constrained optimization problems for medical imaging. We discuss three examples. The first is image registration, the second is data assimilation for brain tumor patients, and the third is data assimilation in cardiovascular imaging. The image registration problem is a classical task in medical image analysis and seeks to find pointwise correspondences between two or more images. Data assimilation problems use a PDE-constrained formulation to link a biophysical model to patient-specific data obtained from medical images. The associated optimality systems turn out to be sets of nonlinear, multicomponent PDEs that are challenging to solve in an efficient way. The ultimate goal of our work is the design of inversion methods that integrate complementary data, and rigorously follow mathematical and physical principles, in an attempt to support clinical decision making. This requires reliable, high-fidelity algorithms with a short time-to-solution. This task is complicated by model and data uncertainties, and by the fact that PDE-constrained optimization problems are ill-posed in nature, and in general yield high-dimensional, severely ill-conditioned systems after discretization. These features make regularization, effective preconditioners, and iterative solvers that, in many cases, have to be implemented on distributed-memory architectures to be practical, a prerequisite. We showcase state-of-the-art techniques in scientific computing to tackle these challenges.     

Shrinkage behaviour of superplasticised RCCP and its relationship with internal temperature

Shrinkage properties of roller-compacted concrete pavement (RCCP) and its relationship with internal temperature variations in superplasticised RCCP were studied. The control and superplasticised RCCPs containing different amounts of sodium naphthalene sulphonate superplasticiser between 1 and 4% by weight of cement were compacted at their optimum water content. The short- and long-term shrinkage and internal temperature variations were monitored in isolated and non-isolated conditions. Micro-structural analysis was implemented using the electron scanning microscope and X-ray diffraction methods. The initial internal temperature of superplasticised RCCP during the first hours of setting was higher than the control mix. A dormant period of low internal temperature was found for superplasticised mixes which started after about 7–13 and 6–10 h in non-isolated and isolated conditions, respectively. For non-isolated condition, the dormant period lasted about 3 days. Under isolated condition, similar trend was found after 4–8 days. During the first day of curing, the total and drying shrinkages of the control RCCP were considerably higher than the superplasticised mixes. On the contrary, the long-term monitoring indicated higher total and drying shrinkages in superplasticised mixes. Based on statistical analysis, the relationship between the autogenous shrinkage and area under the internal temperature diagram was significant.     

Scalable Production of Nanographene and Doping via Nondestructive Covalent Functionalization

A new method for top‐down, one‐pot, gram‐scale production of high quality nanographene by incubating graphite in a dilute sodium hypochlorite solution at only 40 °C is reported here. The produced sheets have only 4 at% oxygen content, comparable with nanographene grown by chemical vapor deposition. The nanographene sheets are covalently functionalized using a nondestructive nitrene [2+1] cycloaddition reaction that preserves their π‐conjugated system. Statistical analyses of Raman spectroscopy and X‐ray photoelectron spectroscopy indicate a low number of sp³ carbon atoms on the order of 2% before and 4% after covalent functionalization. The nanographene sheets are significantly more conductive than conventionally prepared nanographene oxide, and conductivity further increases after covalent functionalization. The observed doping effects and theoretical studies suggest sp² hybridization for the carbon atoms involved in the [2+1] cycloaddition reaction leading to preservation of the π‐conjugated system and enhancing conductivity via n‐type doping through the bridging N‐atom. These methods are easily scalable, which opens the door to a mild and efficient process to produce high quality nanographenes and covalently functionalize them while retaining or improving their physicochemical properties.     

Shale gas: A solution for energy crisis and lower CO2 emission in Pakistan

Energy supply is an essential element for development in any country. However, the huge energy demand in future, which depends mainly on fossil fuels, may create an environmental crisis. In this paper, an attempt was made to highlight the shale gas prospect of Pakistan as a solution for its future energy demands. It seems that Pakistan is currently consuming a huge amount of domestic natural gas and crude oil, which may soon result in climate change. As such, it is crucial to consider shale gas reserves as an ultimate solution for energy and achieving a low carbon economy.     

Green information systems use in social enterprise: the case of a community-led eco-localization website in the West Midlands region of the UK

This study examines the intention of environmentally-oriented social enterprises to continue using Green IS (an eco-localization website here) in Herefordshire located in the West Midlands region of the United Kingdom. The Herefordshire Greenlinks (HGL) Association is a local business community that operates primarily through the HGL Website in order to help local social enterprises find and trade local eco-friendly goods and services. It is an example of a “market-based” approach to solving social and environmental issues that is inspired by a bottom-up view of community development and eco-localization. Based on the theory of uses and gratification of media use and the new environmental paradigm, we propose a research model that outlines the various factors contributing to intention to continue using an eco-localization website. The research model and its associated hypotheses were empirically tested using a dataset generated from a survey of 83 small social enterprises. The results demonstrate the importance of three different types of gratification – content, social and performance gratification as well as users’ environmental concerns in determining the intention to continue using an eco-localization website. This study contributes to the Green IS literature by extending research to the social sector environment, and it also provides practical insight for designers of such community-led eco-localization websites.