Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

sizing problem with setup carryover and backordering

The classical capacitated lot sizing problem is shown to be NP -hard for even a single item problem. This study deals with an extended version of this problem with setup carryover and backordering. To solve this computationally difficult lot sizing problem, we propose a number of hybrid meta -heuristic approaches consisting of genetic algorithms and a mixed integer programming -based heuristic. This MIP-based heuristic is combined with two types of decomposition schemes (i.e., product and time decomposition) to generate subproblems. Computational experiments are carried out on various problem sizes. We found that hybrid approaches employing only time decomposition scheme or combination of both time and product decomposition schemes in different forms outperform the other hybrid approaches. Moreover, we investigated the sensitivity of the two best performing approaches to changes in problem-specific parameters including backorder costs, setup times, setup costs, capacity utilisation and demand variability

systems considering risk factors

Effective and good quality imaging is important for medical decision-making and can reduce unnecessary costs and procedures. Therefore, decision making regarding any technology can present serious problems for healthcare centers with multi criteria decision making problems (MCDM). This paper is the first to develop the fuzzy axiomatic design with risk factors (RFAD) approach and to use it in multi attribute comparisons of medical imaging systems in a university hospital. Although most MCDM approaches in the literature treat risk factors as separate criteria, in real life every alternative has its own risks related to each criterion. The proposed approach integrates the risk factors in each criterion and calculates the information content to compare alternatives. This paper applies three different approaches to MCDM problems related to the selection of medical imaging systems for a university hospital. (C) 2015 Elsevier B.V. All rights reserved

settlement siting

The refugee crisis resulted in a large influx of refugees in the Mediterranean since 2014. However, crises are inherently complex phenomena, whereas the ultimate goal of all involved actors is to provide humanitarian aid to the affected populations. The required supply chain management and logistics operations are characterized by complex decision making whereas coordination between involved actors is necessary for effective aid delivery. Therefore, distributed problem solving based on autonomous and interacting agent can be used as a decision support tool in this field. The purpose of this paper is to address the solution of the refugee settlement site planning problem with an intelligent multi-agent system (MAS) modeling method. In particular, intelligent agents use two well-known multi-criteria decision-making methods (MCDM), Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy axiomatic design approach with risk factors (RFAD), to rank alternative sites for refugee settlement siting. Up to authors' knowledge, this study is the first that utilizes MAS and MCDM approaches in a decision support system for refugee settlement planning in literature. The proposed method has been applied to evaluate four currently operating refugee accommodation sites in Greece. Obtained results have confirmed and reflected the current situation in these camp locations

A SUPPLIER SELECTION, EVALUATION AND RE-EVALUATION MODEL FOR TEXTILE

In general, supplier selection is a multi-criteria decision problem that contains tangible and intangible factors. This paper identities and organizes these factors into a three-phase supplier selection model for a textile retail organization. The first phase of the model is designed to identify the relative importance of the factors associated with the identification of a portfolio of suppliers from rather a large set of candidate suppliers. In the second phase of the model, factors required for the evaluation of the suppliers, selected in the first phase, depending on their ability to meet the product requirements are identified and their weights are suggested. In the last phase, the factors related to system performance of the certified suppliers determined in the second phase of the model are identified and their relative importance values are suggested. The model utilizes Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) as decision-making tools. Both model and the weights of the factors determined present a valuable insight on supply processes of a wide range of textile products supplying departments of all retail chain companies

A SUPPLIER SELECTION, EVALUATION AND RE-EVALUATION MODEL FOR TEXTILE

In general, supplier selection is a multi-criteria decision problem that contains tangible and intangible factors. This paper identities and organizes these factors into a three-phase supplier selection model for a textile retail organization. The first phase of the model is designed to identify the relative importance of the factors associated with the identification of a portfolio of suppliers from rather a large set of candidate suppliers. In the second phase of the model, factors required for the evaluation of the suppliers, selected in the first phase, depending on their ability to meet the product requirements are identified and their weights are suggested. In the last phase, the factors related to system performance of the certified suppliers determined in the second phase of the model are identified and their relative importance values are suggested. The model utilizes Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) as decision-making tools. Both model and the weights of the factors determined present a valuable insight on supply processes of a wide range of textile products supplying departments of all retail chain companies