Stable schedule matching under revealed preference

Baiou and Balinski (Math. Oper. Res., 27 (2002) 485) studied schedule matching where one determines the partnerships that form and how much time they spend together, under the assumption that each agent has a ranking on all potential partners. Here we study schedule matching under more general preferences that extend the substitutable preferences in Roth (Econometrica 52 (1984) 47) by an extension of the revealed preference approach in Alkan (Econom. Theory 19 (2002) 737). We give a generalization of the GaleShapley algorithm and show that some familiar properties of ordinary stable matchings continue to hold. Our main result is that, when preferences satisfy an additional property called size monotonicity, stable matchings are a lattice under the joint preferences of all agents on each side and have other interesting structural properties

A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries

Energy intensive industries can be classified into those that process metal, glass, ceramics, paper, cement, and bulk chemicals. They are associated with significantly high proportions of carbon emissions, consume a lot of energy and raw materials, and cause energy wastage as a result of heat escaping from furnaces, reheating of products, and rejection of parts. In alignment with UN sustainable development goals of industry, innovation, infrastructure and responsible consumption and production, it is important to ensure that the energy consumption of EIIs are monitored and reduced such that their energy efficiency can be improved. Towards this aim, it is possible to employ the concepts of digitalization and smart manufacturing to identify the critical areas of improvement and establish enablers that can help improve the energy efficiency. The aim of this research is to review the current state of digitalisation in energy-intensive industries and propose a framework to support the realisation of sustainable smart manufacturing in Energy Intensive Industries (EIIs). The key objectives of the work are (i) the investigation of process mining and simulation modelling to support sustainability, (ii) embedding intelligence in EIIs to improve energy and material efficiency and (iii) proposing a framework to enable the digital transformation of EIIs. The proposed five-layer framework employs data acquisition, process management, simulation & modelling, artificial intelligence, and data visualisation to identify and forecast energy consumption. A detailed description of the various phases of the framework and how they can be used to support sustainability and smart manufacturing is demonstrated using business process data obtained from a machining industry. In the demonstrated case study, the process management layer utilises Disco for process mining, the simulation layer utilises Matlab SimEvent for discrete-event simulation, the artificial intelligence layer utilises Matlab for energy prediction and the visualisation layer utilises grafana to dashboard the e-KPIs. The findings of the research indicate that the proposed digital life-cycle framework helps EIIs realise sustainable smart manufacturing through better understanding of the energy-intensive processes. The study also provided a better understanding of the integration of process mining and simulation & modelling within the context of EIIs

Environmental urbanization assessment using gis and multicriteria decision analysis: a case study for Denizli (Turkey) municipal area

In recent years, life quality of the urban areas is a growing interest of civil engineering. Environmental quality is essential to display the position of sustainable development and asserts the corresponding countermeasures to the protection of environment. Urban environmental quality involves multidisciplinary parameters and difficulties to be analyzed. The problem is not only complex but also involves many uncertainties, and decision-making on these issues is a challenging problem which contains many parameters and alternatives inherently. Multicriteria decision analysis (MCDA) is a very prepotent technique to solve that sort of problems, and it guides the users confidence by synthesizing that information. Environmental concerns frequently contain spatial information. Spatial multicriteria decision analysis (SMCDA) that includes Geographic Information System (GIS) is efficient to tackle that type of problems. This study has employed some geographic and urbanization parameters to assess the environmental urbanization quality used by those methods. The study area has been described in five categories: very favorable, favorable, moderate, unfavorable, and very unfavorable. The results are momentous to see the current situation, and they could help to mitigate the related concerns. The study proves that the SMCDA descriptions match the environmental quality perception in the city. © 2018 Erdal Akyol et al

Fuel-cell performance of multiply-crosslinked polymer electrolyte membranes prepared by two-step radiation technique

A multiply-crosslinked polymer electrolyte membrane was prepared by the radiation-induced co-grafting of styrene and a bis(vinyl phenyl)ethane (BVPE) crosslinker into a radiation-crosslinked polytetrafluoroethylene (cPTFE) film. We then investigated its H2/O2 fuel-cell performance at 60 and 80ºC in terms of the effect of radiation and chemical crosslinking. At 60ºC, all the membranes initially exhibited similar performance, but only the cPTFE-based membranes were durable at 80ºC, indicating the necessity of radiation crosslinking in the PTFE main chains. Importantly, cell performance of the multiply-crosslinked membrane was found high enough to reach that of a Nafion112 membrane. This is probably because the BVPE crosslinks in the graft component improved the membrane-electrode interface in addition to membrane durability. After severe OCV hold tests at 80 and 95ºC, the performance deteriorated, while no significant change was observed in ohmic resistivity. Accordingly, our membranes seemed so chemically stable that an influence on overall performance loss could be negligible

Denaturation of Circular DNA: Supercoil Mechanism

The denaturation transition which takes place in circular DNA is analyzed by extending the Poland-Scheraga model to include the winding degrees of freedom. We consider the case of a homopolymer whereby the winding number of the double stranded helix, released by a loop denaturation, is absorbed by \emph{supercoils}. We find that as in the case of linear DNA, the order of the transition is determined by the loop exponent $c$. However the first order transition displayed by the PS model for $c>2$ in linear DNA is replaced by a continuous transition with arbitrarily high order as $c$ approaches 2, while the second-order transition found in the linear case in the regime $1<c\le2$ disappears. In addition, our analysis reveals that melting under fixed linking number is a \emph{condensation transition}, where the condensate is a macroscopic loop which appears above the critical temperature.Comment: 9 pages, 4 figure

An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles

Within the concept of factories of the future, big data analytics systems play a critical role in supporting decision-making at various stages across enterprise processes. However, the design and deployment of industry-ready, lightweight, modular, flexible, and low-cost big data analytics solutions remains one of the main challenges towards the Industry 4.0 enabled digital transformation. This paper presents an end-to-end IoT-based big data analytics platform that consists of five interconnected layers and several components for data acquisition, integration, storage, analytics and visualisation purposes. The platform architecture benefits from state-of-the-art technologies and integrates them in a systematic and interoperable way with clear information flows. The developed platform has been deployed in an Electric Vehicle (EV) battery module smart assembly automation system designed by the Automation Systems Group (ASG) at the University of Warwick, UK. The developed proof-of-concept solution demonstrates how a wide variety of tools and methods can be orchestrated to work together aiming to support decision-making and to improve both process and product qualities in smart manufacturing environments

Synthesis, Characterization and Antibacterial Activity of Imidazole Derivatives of 1,10-Phenanthroline and their Cu(II), Co(II) and Ni(II) Complexes

Six new CuL1 (L1 = 4-bromo-2-(1H-imidazo[4,5-f][1,10]phenanthroline-2-yl)phenol), CoL1, NiL1, CuL2 (L2 = 2-(1H-imidazo[4,5-f] [1,10]phenanthroline-2-yl)-5-methoxyphenol), CoL2 and NiL2 complexes were synthesized. L1 and L2 ligands were prepared by the condensation of 1,10-phenanthroline-5,6-dione with 5-bromosalicylaldehyde and 2-hydroxy-4-methoxybenzaldehyde, respectively. The structures of the compounds were determined by elemental analyses, IR,UV-visible, 1H-NMR, TGA, magnetic susceptibilities and molar conductance measurements. It is observed that the synthesized complexes have tetragonal and distorted square pyramidal geometrical structures. Antibacterial activity of the ligands and their metal complexes were tested against selected bacteria by disc diffusion method.KEY WORDS 1,10-Phenanthroline, imidazole, complex, antibacterial activity