Framing fracking: which frames are heard in English planning and environmental policy and practice?

Fracking in England has been the subject of significant controversy and has sparked not only public protest but also an associated framing war with differing social constructions of the technology adopted by different sides. This article explores the frames and counter-frames which have been employed by both the anti-fracking movement and by government and the oil and gas industry. It then considers the way in which the English planning and regulatory permitting systems have provided space for these frames within the relevant machinery for public participation. The article thus enables one to see which frames have been allowed a voice and which have been excluded.

Multi-population genetic algorithm to solve the synchronized and integrated two-level lot sizing and scheduling problem

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Heuristics and meta-heuristics for lot sizing and scheduling in the soft drinks industry: A comparison study

This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

Asynchronous teams for joint lot-sizing and scheduling problem in flow shops

The integrated production scheduling and lot-sizing problem in a flow shop environment consists of establishing production lot sizes and allocating machines to process them within a planning horizon in a production line with machines arranged in series. The problem considers that demands must be met without backlogging, the capacity of the machines must be respected, and machine setups are sequence-dependent and preserved between periods of the planning horizon. The objective is to determine a production schedule to minimise the setup, production and inventory costs. A mathematical model from the literature is presented, as well as procedures for obtaining feasible solutions. However, some of the procedures have difficulty in obtaining feasible solutions for large-sized problem instances. In addition, we address the problem using different versions of the Asynchronous Team (A-Team) approach. The procedures were compared with literature heuristics based on Mixed Integer Programming. The proposed A-Team procedures outperformed the literature heuristics, especially for large instances. The developed methodologies and the results obtained are presented.

Combinatorial and Robust Optimisation Models and Algorithms for Railway Applications

This thesis deals with an investigation of combinatorial and robust optimisation models to solve railway problems. Railway applications represent a challenging area for operations research. In fact, most problems in this context can be modelled as combinatorial optimisation problems, in which the number of feasible solutions is finite. Yet, despite the astonishing success in the field of combinatorial optimisation, the current state of algorithmic research faces severe difficulties with highly-complex and data-intensive applications such as those dealing with optimisation issues in large-scale transportation networks. One of the main issues concerns imperfect information. The idea of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, dates back to 1970s. Unfortunately, none of those techniques proved to be successfully applicable in one of the most complex and largest in scale (transportation) settings: that of railway systems. Railway optimisation deals with planning and scheduling problems over several time horizons. Disturbances are inevitable and severely affect the planning process. Here we focus on two compelling aspects of planning: robust planning and online (real-time) planning.

Synchronization and Detection Techniques for Navigation and Communication Systems

Synchronization is a key issue in any communication system, but it becomes fundamental in the navigation systems, which are entirely based on the estimation of the time delay of the signals coming from the satellites. Thus, even if synchronization has been a well known topic for many years, the introduction of new modulations and new physical layer techniques in the modern standards makes the traditional synchronization strategies completely ineffective. For this reason, the design of advanced and innovative techniques for synchronization in modern communication systems, like DVB-SH, DVB-T2, DVB-RCS, WiMAX, LTE, and in the modern navigation system, like Galileo, has been the topic of the activity. Recent years have seen the consolidation of two different trends: the introduction of Orthogonal Frequency Division Multiplexing (OFDM) in the communication systems, and of the Binary Offset Carrier (BOC) modulation in the modern Global Navigation Satellite Systems (GNSS). Thus, a particular attention has been given to the investigation of the synchronization algorithms in these areas.

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Advanced lithium and lithium-ion rechargeable batteries for automotive applications

The worldwide demand for a clean and low-fuel-consuming transport promotes the development of safe, high energy and power electrochemical storage and conversion systems. Lithium-ion batteries (LIBs) are considered today the best technology for this application as demonstrated by the recent interest of automotive industry in hybrid (HEV) and electric vehicles (EV) based on LIBs. This thesis work, starting from the synthesis and characterization of electrode materials and the use of non-conventional electrolytes, demonstrates that LIBs with novel and safe electrolytes and electrode materials meet the targets of specific energy and power established by U.S.A. Department of Energy (DOE) for automotive application in HEV and EV. In chapter 2 is reported the origin of all chemicals used, the description of the instruments used for synthesis and chemical-physical characterizations, the electrodes preparation, the batteries configuration and the electrochemical characterization procedure of electrodes and batteries. Since the electrolyte is the main critical point of a battery, in particular in large- format modules, in chapter 3 we focused on the characterization of innovative and safe electrolytes based on ionic liquids (characterized by high boiling/decomposition points, thermal and electrochemical stability and appreciable conductivity) and mixtures of ionic liquid with conventional electrolyte. In chapter 4 is discussed the microwave accelerated sol–gel synthesis of the carbon- coated lithium iron phosphate (LiFePO 4 -C), an excellent cathode material for LIBs thanks to its intrinsic safety and tolerance to abusive conditions, which showed excellent electrochemical performance in terms of specific capacity and stability. In chapter 5 are presented the chemical-physical and electrochemical characterizations of graphite and titanium-based anode materials in different electrolytes. We also characterized a new anodic material, amorphous SnCo alloy, synthetized with a nanowire morphology that showed to strongly enhance the electrochemical stability of the material during galvanostatic full charge/discharge cycling. Finally, in chapter 6, are reported different types of batteries, assembled using the LiFePO 4 -C cathode material, different anode materials and electrolytes, characterized by deep galvanostatic charge/discharge cycles at different C-rates and by test procedures of the DOE protocol for evaluating pulse power capability and available energy. First, we tested a battery with the innovative cathode material LiFePO 4 -C and conventional graphite anode and carbonate-based electrolyte (EC DMC LiPF 6 1M) that demonstrated to surpass easily the target for power-assist HEV application. Given that the big concern of conventional lithium-ion batteries is the flammability of highly volatile organic carbonate- based electrolytes, we made safe batteries with electrolytes based on ionic liquid (IL). In order to use graphite anode in IL electrolyte we added to the IL 10% w/w of vinylene carbonate (VC) that produces a stable SEI (solid electrolyte interphase) and prevents the graphite exfoliation phenomenon. Then we assembled batteries with LiFePO 4 -C cathode, graphite anode and PYR 14 TFSI 0.4m LiTFSI with 10% w/w of VC that overcame the DOE targets for HEV application and were stable for over 275 cycles. We also assembled and characterized ―high safety‖ batteries with electrolytes based on pure IL, PYR 14 TFSI with 0.4m LiTFSI as lithium salt, and on mixture of this IL and standard electrolyte (PYR 14 TFSI 50% w/w and EC DMC LiPF 6 50% w/w), using titanium-based anodes (TiO 2 and Li 4 Ti 5 O 12 ) that are commonly considered safer than graphite in abusive conditions. The batteries bearing the pure ionic liquid did not satisfy the targets for HEV application, but the batteries with Li 4 Ti 5 O 12 anode and 50-50 mixture electrolyte were able to surpass the targets. We also assembled and characterized a lithium battery (with lithium metal anode) with a polymeric electrolyte based on poly-ethilenoxide (PEO 20 – LiCF 3 SO 3 +10%ZrO 2 ), which satisfied the targets for EV application and showed a very impressive cycling stability. In conclusion, we developed three lithium-ion batteries of different chemistries that demonstrated to be suitable for application in power-assist hybrid vehicles: graphite/EC DMC LiPF 6 /LiFePO 4 -C, graphite/PYR 14 TFSI 0.4m LiTFSI with 10% VC/LiFePO 4 -C and Li 4 T i5 O 12 /PYR 14 TFSI 50%-EC DMC LiPF 6 50%/LiFePO 4 -C. We also demonstrated that an all solid-state polymer lithium battery as Li/PEO 20 –LiCF 3 SO 3 +10%ZrO 2 /LiFePO 4 -C is suitable for application on electric vehicles. Furthermore we developed a promising anodic material alternative to the graphite, based on SnCo amorphous alloy.

Impact of metal and metal oxide engineered nanoparticles in soil and plant systems

Nanotechnology promises huge benefits for society and capital invested in this new technology is steadily increasing, therefore there is a growing number of nanotechnology products on the market and inevitably engineered nanomaterials will be released in the atmosphere with potential risks to humans and environment. This study set out to extend the comprehension of the impact of metal (Ag, Co, Ni) and metal oxide (CeO2, Fe3O4, SnO2, TiO2) nanoparticles (NPs) on one of the most important environmental compartments potentially contaminated by NPs, the soil system, through the use of chemical and biological tools. For this purpose experiments were carried out to simulate realistic environmental conditions of wet and dry deposition of NPs, considering ecologically relevant endpoints. In detail, this thesis involved the study of three model systems and the evaluation of related issues: (i) NPs and bare soil, to assess the influence of NPs on the functions of soil microbial communities; (ii) NPs and plants, to evaluate the chronic toxicity and accumulation of NPs in edible tissues; (iii) NPs and invertebrates, to verify the effects of NPs on earthworms and the damaging of their functionality. The study highlighted that NP toxicity is generally influenced by NP core elements and the impact of NPs on organisms is specie-specific; moreover experiments conducted in media closer to real conditions showed a decrease in toxicity with respect to in vitro test or hydroponic tests. However, only a multidisciplinary approach, involving physical, chemical and biological skills, together with the use of advanced techniques, such as X-ray absorption fine structure spectroscopy, could pave the way to draw the right conclusions and accomplish a deeper comprehension of the effects of NPs on soil and soil inhabitants.

Sustainable improvement of water networks : to achieve best decisions for rehabilitation plans using advanced GIS and statistical techniques

Many of developing countries are facing crisis in water management due to increasing of population, water scarcity, water contaminations and effects of world economic crisis. Water distribution systems in developing countries are facing many challenges of efficient repair and rehabilitation since the information of water network is very limited, which makes the rehabilitation assessment plans very difficult. Sufficient information with high technology in developed countries makes the assessment for rehabilitation easy. Developing countries have many difficulties to assess the water network causing system failure, deterioration of mains and bad water quality in the network due to pipe corrosion and deterioration. The limited information brought into focus the urgent need to develop economical assessment for rehabilitation of water distribution systems adapted to water utilities. Gaza Strip is subject to a first case study, suffering from severe shortage in the water supply and environmental problems and contamination of underground water resources. This research focuses on improvement of water supply network to reduce the water losses in water network based on limited database using techniques of ArcGIS and commercial water network software (WaterCAD). A new approach for rehabilitation water pipes has been presented in Gaza city case study. Integrated rehabilitation assessment model has been developed for rehabilitation water pipes including three components; hydraulic assessment model, Physical assessment model and Structural assessment model. WaterCAD model has been developed with integrated in ArcGIS to produce the hydraulic assessment model for water network. The model have been designed based on pipe condition assessment with 100 score points as a maximum points for pipe condition. As results from this model, we can indicate that 40% of water pipeline have score points less than 50 points and about 10% of total pipes length have less than 30 score points. By using this model, the rehabilitation plans for each region in Gaza city can be achieved based on available budget and condition of pipes. The second case study is Kuala Lumpur Case from semi-developed countries, which has been used to develop an approach to improve the water network under crucial conditions using, advanced statistical and GIS techniques. Kuala Lumpur (KL) has water losses about 40% and high failure rate, which make severe problem. This case can represent cases in South Asia countries. Kuala Lumpur faced big challenges to reduce the water losses in water network during last 5 years. One of these challenges is high deterioration of asbestos cement (AC) pipes. They need to replace more than 6500 km of AC pipes, which need a huge budget to be achieved. Asbestos cement is subject to deterioration due to various chemical processes that either leach out the cement material or penetrate the concrete to form products that weaken the cement matrix. This case presents an approach for geo-statistical model for modelling pipe failures in a water distribution network. Database of Syabas Company (Kuala Lumpur water company) has been used in developing the model. The statistical models have been calibrated, verified and used to predict failures for both networks and individual pipes. The mathematical formulation developed for failure frequency in Kuala Lumpur was based on different pipeline characteristics, reflecting several factors such as pipe diameter, length, pressure and failure history. Generalized linear model have been applied to predict pipe failures based on District Meter Zone (DMZ) and individual pipe levels. Based on Kuala Lumpur case study, several outputs and implications have been achieved. Correlations between spatial and temporal intervals of pipe failures also have been done using ArcGIS software. Water Pipe Assessment Model (WPAM) has been developed using the analysis of historical pipe failure in Kuala Lumpur which prioritizing the pipe rehabilitation candidates based on ranking system. Frankfurt Water Network in Germany is the third main case study. This case makes an overview for Survival analysis and neural network methods used in water network. Rehabilitation strategies of water pipes have been developed for Frankfurt water network in cooperation with Mainova (Frankfurt Water Company). This thesis also presents a methodology of technical condition assessment of plastic pipes based on simple analysis. This thesis aims to make contribution to improve the prediction of pipe failures in water networks using Geographic Information System (GIS) and Decision Support System (DSS). The output from the technical condition assessment model can be used to estimate future budget needs for rehabilitation and to define pipes with high priority for replacement based on poor condition. rn

Advanced morphological and biochemical magnetic resonance imaging of cartilage repair procedures in the knee joint at 3 Tesla

Morphological and biochemical magnetic resonance imaging (MRI) is due to high field MR systems, advanced coil technology, and sophisticated sequence protocols capable of visualizing articular cartilage in vivo with high resolution in clinical applicable scan time. Several conventional two-dimensional (2D) and three-dimensional (3D) approaches show changes in cartilage structure. Furthermore newer isotropic 3D sequences show great promise in improving cartilage imaging and additionally in diagnosing surrounding pathologies within the knee joint. Functional MR approaches are additionally able to provide a specific measure of the composition of cartilage. Cartilage physiology and ultra-structure can be determined, changes in cartilage macromolecules can be detected, and cartilage repair tissue can thus be assessed and potentially differentiated. In cartilage defects and following nonsurgical and surgical cartilage repair, morphological MRI provides the basis for diagnosis and follow-up evaluation, whereas biochemical MRI provides a deeper insight into the composition of cartilage and cartilage repair tissue. A combination of both, together with clinical evaluation, may represent a desirable multimodal approach in the future, also available in routine clinical use.

Assessing and mapping LD and SLM to directly support the planning and scaling up of SLM interventions to combat desertification

Global investment in Sustainable Land Management (SLM) has been substantial, but knowledge gaps remain. Overviews of where land degradation (LD) is taking place and how land users are addressing the problem using SLM are still lacking for most individual countries and regions. Relevant maps focus more on LD than SLM, and they have been compiled using different methods. This makes it impossible to compare the benefits of SLM interventions and prevents informed decision-making on how best to invest in land. To fill this knowledge gap, a standardised mapping method has been collaboratively developed by the World Overview of Conservation Approaches and Technologies (WOCAT), FAO’s Land Degradation Assessment in Drylands (LADA) project, and the EU’s Mitigating Desertification and Remediating Degraded Land (DESIRE) project. The method generates information on the distribution and characteristics of LD and SLM activities and can be applied at the village, national, or regional level. It is based on participatory expert assessment, documents, and surveys. These data sources are spatially displayed across a land-use systems base map. By enabling mapping of the DPSIR framework (Driving Forces-Pressures-State-Impacts-Responses) for degradation and conservation, the method provides key information for decision-making. It may also be used to monitor LD and conservation following project implementation. This contribution explains the mapping method, highlighting findings made at different levels (national and local) in South Africa and the Mediterranean region. Keywords: Mapping, Decision Support, Land Degradation, Sustainable Land Management, Ecosystem Services, Participatory Expert Assessment