Abstract
A method for the separation and fractionation of the major whey proteins from a whey protein concentrate (WPC80) by anion-exchange chromatography coupled to a Fast Protein Liquid Chromatography (FPLC) system is proposed. The method is based on the use of an ionic column (Mono Q) and a salt gradient elution by increasing the ionic strength of the elution buffer (Tris-HCl 20 mM plus 0 to 1 M NaCl). The proposed method was found to be suitable to fractionate the major whey proteins from the WPC80 in different fractions, namely one fraction containing all the alpha-Lactalbumin and immunoglobulins; another fraction containing all the bovine serum albumin; and two distinct fractions each containing a different variant of p-Lactoglobulin. A 60.5% (w/w) recovery of the two main p-Lactoglobulin variants was obtained.

Abstract
Purpose - The purpose of this paper is to study the alignment measurement in collaborative networks, using the fit concept and predictive performance measurement as its main enablers. A performance prediction approach is used in order to control a collaborative business network based not only in present and past performance measurements of each partner, but also taking into account the future behaviour of the intra- and inter-organisational processes performance. Design/methodology/approach - An exploratory case study was applied to a Brazilian collaborative network and mathematical approaches normally used in control theory were adopted to support alignment measurement. Findings - The use of predictive measurements to manage the alignment between the results of inter-organisational processes and performance targets set by the collaborative network. Research limitations/implications - This approach was applied in a specific supply chain network, based on three industrial companies. For other network typologies it will be necessary to evaluate the alignment that can be achieved. Practical implications - This predictive approach makes it possible to manage performance pro-actively using feedforward and feedback control. Therefore, tools that consider performance estimation are used based on a data fusion approach, with a proper combination of leading and lagging measurements, which make it possible to use forecasting methods and tools to achieve good predictions. Originality/value - The paper introduces an approach to alignment measurement leveraged by the new paradigm of performance prediction and presents an alignment metric for collaborative networks. © Emerald Group Publishing Limited.

Abstract
The purpose of this paper is to present a methodology that allows higher education institutions (HEIs) to promote, to evaluate and to report on sustainability. The ultimate goal of the afore-mentioned methodology is to help HEIs achieve sustainability. First, a model entitled Sustainability in Higher Education Institutions (SusHEI) that generally describes and characterizes the functioning of an HEI was defined. SusHEI takes into account the core activities of any HEI (education and research), its impacts at economic, environmental and social levels, and the role of its community. SusHEI allowed for the establishment of internal dimensions interrelated to the functioning of an HEI. Then, a matricial representation of the model was developed. The matrix crosses internal dimensions (and eventually sub-dimensions) with sustainability dimensions (and eventually sub-dimensions) and it is quantified through indicators. There is a wide range of possible sustainability indicators that can be chosen, depending on the purpose and the public to whom the indicators/reports are addressed. The methodology is illustrated by a case-study - the Faculty of Engineering of the University of Porto (FEUP). This paper provides a methodology that enables the selection of sustainability indicators for sustainability reporting, assessment or even for benchmarking, and also eliminates some of the main weaknesses found in the models currently available. Higher Education Policy (2011) 24, 459-479. doi:10.1057/hep.2011.18

Abstract
We propose two exact algorithms for two-dimensional orthogonal packing problems whose main components are simple mixed-integer linear programming models. Based on the different forms of time representation in scheduling formulations, we extend the concept of multiple time grids into a second dimension and propose a hybrid discrete/continuous-space formulation. By relying on events to continuously locate the rectangles along the strip height, we aim to reduce the size of the resulting mathematical problem when compared to a pure discrete-space model, with hopes of achieving a better computational performance. Through the solution of a set of 29 test instances from the literature, we show that this was mostly accomplished, primarily because the associated search strategy can quickly find good feasible solutions prior to the optimum, which may be very important in real industrial environments. We also provide a comprehensive comparison to seven other conceptually different approaches that have solved the same strip packing problems.

Abstract

Abstract
Optimisation problems in Healthcare have received considerable attention for more than three decades. More recently, however, with decreasing birth rates in nearly all of the developed countries and increasing average longevity globally, optimisation issues in Healthcare have become noticeably important and attract keen interest from the Operations Research community. Over the years, attention has gradually expanded from resource allocation and strategic planning to include operational issues such as resource scheduling and treatment planning. This paper surveys several applications of Operations Research in the domain of Healthcare. In particular, the paper reviews key contributions addressing contemporary optimisation issues in this area. It highlights current research activities, focusing on a variety of optimisation problems as well as solution techniques used for solving the optimisation problems.