Impaired lipoprotein metabolism in obese offspring of streptozotocin-induced diabetic rats

The time course of changes in lipoprotein metabolism of obese offspring of mildly diabetic rats was studied with respect to serum lipoprotein composition as well as LCAT and tissue lipoprotein lipase (LPL) activities. Mild hyperglycemia in pregnant rats was induced by intraperitoneal injection of streptozotocin on day 5 of gestation. Control pregnant rats were injected with citrate buffer. At birth, obese pups had higher serum glucose, insulin, and lipoprotein (VLDL, LDL-HDL₁, HDL_2–3) levels than control pups. After 1 mon of life, all of these parameters in obese rats became similar to those of controls. However, LCAT, adipose tissue LPL, and hepatic triacylglycerol lipase activities were high. At 2 mon of age, VLDL-TAG levels were higher in obese females than in controls. By the age of 3 mon, obese offspring had developed insulin resistance with hyperglycemia, hyperinsulinemia, and higher serum lipoprotein concentrations. Indeed, qualitative abnormalities of lipoproteins were seen and were typical of obese and diabetic human beings. Fetal hyperinsulinemia should be considered as a risk factor for later metabolic diseases, including dyslipoproteinemia.     

Numerical solution of the bivariate population balance equation for the interacting hydrodynamics and mass transfer in liquid-liquid extraction columns

A comprehensive model for predicting the interacting hydrodynamics and mass transfer is formulated on the basis of a spatially distributed population balance equation in terms of the bivariate number density function with respect to droplet diameter and solute concentration. The two macro- (droplet breakage and coalescence) and micro- (interphase mass transfer) droplet phenomena are allowed to interact through the dispersion interfacial tension. The resulting model equations are composed of a system of partial and algebraic equations that are dominated by convection, and hence it calls for a specialized discretization approach. The model equations are applied to a laboratory segment of an RDC column using an experimentally validated droplet transport and interaction functions. Aside from the model spatial discretization, two methods for the discretization of the droplet diameter are extended to include the droplet solute concentration. These methods are the generalized fixed-pivot technique (GFP) and the quadrature method of moments (QMOM). The numerical results obtained from the two extended methods are almost identical, and the CPU time of both methods is found acceptable so that the two methods are being extended to simulate a full-scale liquid-liquid extraction column.     

A type 2-hesitation fuzzy logic based multi-criteria group decision making system for intelligent shared environments

Intelligent environments aim to maximize the user comfort and safety while achieving other objectives such as energy minimization. Intelligent shared spaces (such as homes, classrooms, offices, libraries, etc.) need to consider the preferences of users from diverse backgrounds. However, there are high levels of uncertainties faced in intelligent shared spaces. Hence, there is a need to employ intelligent decision making systems which can consider the various users preferences and criteria in order to achieve the convenience of the various users while handling the faced uncertainties. Therefore, we propose a Fuzzy Logic-Multi-Criteria Group Decision Making (FL-MCGDM) system which provides a comprehensive valuation from a group of users/decision makers based on the aggregation of users’ opinions and preferences. The proposed FL-MCGDM system employs an interval type-2 fuzzy logic and hesitation index [from Intuitionistic Fuzzy Sets (IFSs)]. We have carried out experiments in the intelligent apartment (iSpace) located in the University of Essex to evaluate various approaches employing group decision making techniques for illumination selection in an intelligent shared environment. It was found that the Footprint of Uncertainty (of interval type-2 fuzzy sets) and hesitation index (of intuitionistic fuzzy sets (IFSs)) are able to provide a measure of the uncertainties present among the various decision makers. The proposed Type 2-Hesitation FL-MCGDM system better agrees with the users’ decision compared to existing fuzzy MCDM including the Fuzzy Logic based TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), type-1 FL-MCGDM and interval type-2 in FL-MCGDM.     

The boomerang returns? Accounting for the impact of uncertainties on the dynamics of remanufacturing systems

Recent years have witnessed companies abandon traditional open-loop supply chain structures in favour of closed-loop variants, in a bid to mitigate environmental impacts and exploit economic opportunities. Central to the closed-loop paradigm is remanufacturing: the restoration of used products to useful life. While this operational model has huge potential to extend product life-cycles, the collection and recovery processes diminish the effectiveness of existing control mechanisms for open-loop systems. We systematically review the literature in the field of closed-loop supply chain dynamics, which explores the time-varying interactions of material and information flows in the different elements of remanufacturing supply chains. We supplement this with further reviews of what we call the three ‘pillars’ of such systems, i.e. forecasting, collection, and inventory and production control. This provides us with an interdisciplinary lens to investigate how a ‘boomerang’ effect (i.e. sale, consumption, and return processes) impacts on the behaviour of the closed-loop system and to understand how it can be controlled. To facilitate this, we contrast closed-loop supply chain dynamics research to the well-developed research in each pillar; explore how different disciplines have accommodated the supply, process, demand, and control uncertainties; and provide insights for future research on the dynamics of remanufacturing systems.     

Analytic solutions to optimal control problems in crystal growth processes

A unified approach to optimal control of univariate and multivariate crystallization particulate processes with size-independent or/and size-dependent growth rate kinetics is developed by utilizing the minimum principle and the method of characteristics in conjunction with novel approximate integro-differential and ordinary differential equation computational schemes. The proposed theoretical approach leads to simple analytic solutions involving numerical boundary value problems with few unknown parameters.     

A study on wear evaluation of railway wheels based on multibody dynamics and wear computation

The wear evolution of railway wheels is a very important issue in railway engineering. In the past, the reprofiling intervals of railway vehicle steel wheels have been scheduled according to designers’ experience. Today, more reliable and accurate tools in predicting wheel wear evolution and wheelset lifetime can be used in order to achieve economical and safety benefits. In this work, a computational tool that is able to predict the evolution of the wheel profiles for a given railway system, as a function of the distance run, is presented. The strategy adopted consists of using a commercial multibody software to study the railway dynamic problem and a purpose-built code for managing its pre- and post-processing data in order to compute the wear. The tool is applied here to realistic operation scenarios in order to assess the effect of some service conditions on the wheel wear progression.     

Adsorptive capacity of spray-dried pH-treated bentonite and kaolin powders for ammonium removal

The effectiveness of ammonium (NH₄⁺) adsorption was investigated, using spray-dried, pH-treated bentonite, and kaolin as adsorbents. Each powder's adsorption capacity towards NH₄⁺ was examined after up to 120 min of sample exposure, and results were compared. The zeta potential values for bentonite samples were between ?1.1 and ?19.4 mV, while for kaolin samples, they were between ?35.7 and ?40.9 mV (pH range examined was 2–10). The adsorption isotherm for bentonite showed a fit with the Langmuir model. The pH 10-treated bentonite and as-received bentonite (dispersed as pH 10 in distilled water) showed the highest adsorption capacity towards NH₄⁺. Meanwhile, for kaolin, the adsorption capacity was low and observed only at low NH₄⁺ concentration (100 mg/L and 200 mg/L), with pH 10-treated kaolin showed the highest adsorption capacity.