GIS and optimisation:potential benefits for emergency facility location in humanitarian logistics

Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

Logistical framework for last mile relief distribution in humanitarian supply chains:considerations from the field

Recent years large scale natural disasters: (e.g. 2004 Tsunami, 2005 Earthquake in South Asia, 2010 Earthquake in Haiti, 2010 flood in Pakistan, 2011 Earthquake in Japan etc.) have captured international attention and led to the advance of research of disaster management. To cope with these huge impact disasters, the involved stakeholders have to learn how quickly and efficiently the relief organisations are able to respond. After a disaster strikes, it is necessary to get the relief aid to the affected people by the prompt action of relief organisations. This supply chain process has to be very fast and efficient. The purpose of this paper is to define the last mile relief distribution in humanitarian supply chain and develop a logistical framework by identifying the factors that affect this process. Seventeen interviews were conducted with field officers and the data analysed to identify which are the critical factors for last mile relief distribution of disaster relief operation. A framework is presented classifying these factors according to the ability to implement them in an optimisation model of humanitarian logistics.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

Developing a scalable model of recombinant protein yield from Pichia pastoris:the influence of culture conditions, biomass and induction regime

Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

Traffic based energy consumption optimisation to improve the lifetime and performance of ad hoc wireless sensor networks

Ad hoc wireless sensor networks (WSNs) are formed from self-organising configurations of distributed, energy constrained, autonomous sensor nodes. The service lifetime of such sensor nodes depends on the power supply and the energy consumption, which is typically dominated by the communication subsystem. One of the key challenges in unlocking the potential of such data gathering sensor networks is conserving energy so as to maximize their post deployment active lifetime. This thesis described the research carried on the continual development of the novel energy efficient Optimised grids algorithm that increases the WSNs lifetime and improves on the QoS parameters yielding higher throughput, lower latency and jitter for next generation of WSNs. Based on the range and traffic relationship the novel Optimised grids algorithm provides a robust traffic dependent energy efficient grid size that minimises the cluster head energy consumption in each grid and balances the energy use throughout the network. Efficient spatial reusability allows the novel Optimised grids algorithm improves on network QoS parameters. The most important advantage of this model is that it can be applied to all one and two dimensional traffic scenarios where the traffic load may fluctuate due to sensor activities. During traffic fluctuations the novel Optimised grids algorithm can be used to re-optimise the wireless sensor network to bring further benefits in energy reduction and improvement in QoS parameters. As the idle energy becomes dominant at lower traffic loads, the new Sleep Optimised grids model incorporates the sleep energy and idle energy duty cycles that can be implemented to achieve further network lifetime gains in all wireless sensor network models. Another key advantage of the novel Optimised grids algorithm is that it can be implemented with existing energy saving protocols like GAF, LEACH, SMAC and TMAC to further enhance the network lifetimes and improve on QoS parameters. The novel Optimised grids algorithm does not interfere with these protocols, but creates an overlay to optimise the grids sizes and hence transmission range of wireless sensor nodes.

Lipoplexes formulation and optimisation:in vitro transfection studies reveal no correlation with in vivo vaccination studies

The aim of these studies was to compare the effect of liposome composition on physico-chemical characteristics and transfection efficacy of cationic liposomes both in vitro and in vivo. Comparison between 4 popularly used cationic lipids, showed 3b-N-(dimethylaminoethyl)carbamate (DC-Chol) to promote the highest transfect levels in cells in vitro with levels being at least 6 times higher than those of 1,2-di-O-octadecenyl-3-trimethylammonium propane (DOTMA). 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP), and dimethyldioctadecylammonium (DDA) and approximately twice as efficient as dipalmitoyl-trimethylammonium-propane (DPTAP). To establish the role of the helper lipid, DC-Chol liposomes were formulated in combination with either 1,2-dioleoyl-sn-glycero-3-phosphatidylethanolamine (DOPE) or cholesterol (Chol) (1:1 molar ratio) with and without the addition of phosphatidyl choline. The choice of helper lipid incorporated within the bilayer was found to influence the formation of complexes, their resultant structure and their transfection efficiency in vitro, with SUV-DNA complexes containing optimum levels of DOPE giving higher transfection than those containing cholesterol. The inclusion of PC within the formulation also reduced transfection efficiency in vitro. However, when administered in vivo, SUV-DNA complexes composed of PC:Chol:DC-Chol at a molar ratio of 16:8:4 micromole/ml were the most effective at inducing splenocyte proliferation upon exposure to antigen in comparison to control spleens. These results demonstrate that there is no in vitro/in vivo correlation between the transfection efficacy of these liposome formulations and in vitro transfection in the above cell model cannot be taken as a reliable indicator for in vivo efficacy of DNA vaccines.

Global optimisation of cold-formed steel sections

In this thesis, standard algorithms are used to carry out the optimisation of cold-formed steel purlins such as zed, channel and sigma sections, which are assumed to be simply supported and subjected to a gravity load. For zed, channel and sigma section, the local buckling, distortional buckling and lateral-torsional buckling are considered respectively herein. Currently, the local buckling is based on the BS 5950-5:1998 and EN 1993-1-3:2006. The distortional buckling is calculated by the direct strength method employing the elastic distortional buckling which is calculated by three available approaches such as Hancock (1995), Schafer and Pekoz (1998), Yu (2005). In the optimisation program, the lateral-torsional buckling based on BS 5950-5:1998, AISI and analytical model of Li (2004) are investigated. For the optimisation program, the programming codes are written for optimisation of channel, zed and sigma beam. The full study has been coded into a computer-based analysis program (MATLAB).

Aircraft rotable inventory optimisation: development of a new solution

Analysis of the use of ICT in the aerospace industry has prompted the detailed investigation of an inventory-planning problem. There is a special class of inventory, consisting of expensive repairable spares for use in support of aircraft operations. These items, called rotables, are not well served by conventional theory and systems for inventory management. The context of the problem, the aircraft maintenance industry sector, is described in order to convey some of its special characteristics in the context of operations management. A literature review is carried out to seek existing theory that can be applied to rotable inventory and to identify a potential gap into which newly developed theory could contribute. Current techniques for rotable planning are identified in industry and the literature: these methods are modelled and tested using inventory and operational data obtained in the field. In the expectation that current practice leaves much scope for improvement, several new models are proposed. These are developed and tested on the field data for comparison with current practice. The new models are revised following testing to give improved versions. The best model developed and tested here comprises a linear programming optimisation, which finds an optimal level of inventory for multiple test cases, reflecting changing operating conditions. The new model offers an inventory plan that is up to 40% less expensive than that determined by current practice, while maintaining required performance.

Liposome formulation of poorly water soluble drugs:optimisation of drug loading and ESEM analysis of stability

Liposomes due to their biphasic characteristic and diversity in design, composition and construction, offer a dynamic and adaptable technology for enhancing drug solubility. Starting with equimolar egg-phosphatidylcholine (PC)/cholesterol liposomes, the influence of the liposomal composition and surface charge on the incorporation and retention of a model poorly water soluble drug, ibuprofen was investigated. Both the incorporation and the release of ibuprofen were influenced by the lipid composition of the multi-lamellar vesicles (MLV) with inclusion of the long alkyl chain lipid (dilignoceroyl phosphatidylcholine (C 24PC)) resulting in enhanced ibuprofen incorporation efficiency and retention. The cholesterol content of the liposome bilayer was also shown to influence ibuprofen incorporation with maximum ibuprofen incorporation efficiency achieved when 4 μmol of cholesterol was present in the MLV formulation. Addition of anionic lipid dicetylphosphate (DCP) reduced ibuprofen drug loading presumably due to electrostatic repulsive forces between the carboxyl group of ibuprofen and the anionic head-group of DCP. In contrast, the addition of 2 μmol of the cationic lipid stearylamine (SA) to the liposome formulation (PC:Chol - 16 μmol:4 μmol) increased ibuprofen incorporation efficiency by approximately 8%. However further increases of the SA content to 4 μmol and above reduced incorporation by almost 50% compared to liposome formulations excluding the cationic lipid. Environmental scanning electron microscopy (ESEM) was used to dynamically follow the changes in liposome morphology during dehydration to provide an alternative assay of liposome stability. ESEM analysis clearly demonstrated that ibuprofen incorporation improved the stability of PC:Chol liposomes as evidenced by an increased resistance to coalescence during dehydration. These finding suggest a positive interaction between amphiphilic ibuprofen molecules and the bilayer structure of the liposome. © 2004 Elsevier B.V. All rights reserved.

Supply chain optimisation of pyrolysis plant deployment using goal programming

This paper presents a goal programming model to optimise the deployment of pyrolysis plants in Punjab, India. Punjab has an abundance of waste straw and pyrolysis can convert this waste into alternative bio-fuels, which will facilitate the provision of valuable energy services and reduce open field burning. A goal programming model is outlined and demonstrated in two case study applications: small scale operations in villages and large scale deployment across Punjab's districts. To design the supply chain, optimal decisions for location, size and number of plants, downstream energy applications and feedstocks processed are simultaneously made based on stakeholder requirements for capital cost, payback period and production cost of bio-oil and electricity. The model comprises quantitative data obtained from primary research and qualitative data gathered from farmers and potential investors. The Punjab district of Fatehgarh Sahib is found to be the ideal location to initially utilise pyrolysis technology. We conclude that goal programming is an improved method over more conventional methods used in the literature for project planning in the field of bio-energy. The model and findings developed from this study will be particularly valuable to investors, plant developers and municipalities interested in waste to energy in India and elsewhere. © 2014 Elsevier Ltd. All rights reserved.

Pharmaceutical process optimisation of bulk lyophilisates:implications of powder handling

Lyophilisation or freeze drying is the preferred dehydrating method for pharmaceuticals liable to thermal degradation. Most biologics are unstable in aqueous solution and may use freeze drying to prolong their shelf life. Lyophilisation is however expensive and has seen lots of work aimed at reducing cost. This thesis is motivated by the potential cost savings foreseen with the adoption of a cost efficient bulk drying approach for large and small molecules. Initial studies identified ideal formulations that adapted well to bulk drying and further powder handling requirements downstream in production. Low cost techniques were used to disrupt large dried cakes into powder while the effects of carrier agent concentration were investigated for powder flowability using standard pharmacopoeia methods. This revealed superiority of crystalline mannitol over amorphous sucrose matrices and established that the cohesive and very poor flow nature of freeze dried powders were potential barriers to success. Studies from powder characterisation showed increased powder densification was mainly responsible for significant improvements in flow behaviour and an initial bulking agent concentration of 10-15 %w/v was recommended. Further optimisation studies evaluated the effects of freezing rates and thermal treatment on powder flow behaviour. Slow cooling (0.2 °C/min) with a -25°C annealing hold (2hrs) provided adequate mechanical strength and densification at 0.5-1 M mannitol concentrations. Stable bulk powders require powder transfer into either final vials or intermediate storage closures. The targeted dosing of powder formulations using volumetric and gravimetric powder dispensing systems where evaluated using Immunoglobulin G (IgG), Lactate Dehydrogenase (LDH) and Beta Galactosidase models. Final protein content uniformity in dosed vials was assessed using activity and protein recovery assays to draw conclusions from deviations and pharmacopeia acceptance values. A correlation between very poor flowability (p<0.05), solute concentration, dosing time and accuracy was revealed. LDH and IgG lyophilised in 0.5 M and 1 M mannitol passed Pharmacopeia acceptance values criteria with 0.1-4 while formulations with micro collapse showed the best dose accuracy (0.32-0.4% deviation). Bulk mannitol content above 0.5 M provided no additional benefits to dosing accuracy or content uniformity of dosed units. This study identified considerations which included the type of protein, annealing, cake disruption process, physical form of the phases present, humidity control and recommended gravimetric transfer as optimal for dispensing powder. Dosing lyophilised powders from bulk was demonstrated as practical, time efficient, economical and met regulatory requirements in cases. Finally the use of a new non-destructive technique, X-ray microcomputer tomography (MCT), was explored for cake and particle characterisation. Studies demonstrated good correlation with traditional gas porosimetry (R2 = 0.93) and morphology studies using microscopy. Flow characterisation from sample sizes of less than 1 mL was demonstrated using three dimensional X-ray quantitative image analyses. A platinum-mannitol dispersion model used revealed a relationship between freezing rate, ice nucleation sites and variations in homogeneity within the top to bottom segments of a formulation.

Optimisation of polymer optical fibre based interferometric sensors

A numerical model for studying the performance of polymer optical fibre-based interferometric sensors is presented. The strain sensitivity of Fabry-Perot and two-beam interferometric sensors is investigated by varying the physical and optical properties corresponding to frequently used wavelengths. The developed model was used to identify the regimes in which these devices offer enhanced performance over their silica counterparts when used for stress sensing. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Powertrain optimisation in a hybrid electric bus

This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

Performance optimisation of the MAC protocol with multiple contention slots in MIMO ad hoc networks

The multiple-input multiple-output (MIMO) technique can be used to improve the performance of ad hoc networks. Various medium access control (MAC) protocols with multiple contention slots have been proposed to exploit spatial multiplexing for increasing the transport throughput of MIMO ad hoc networks. However, the existence of multiple request-to-send/clear-to-send (RTS/CTS) contention slots represents a severe overhead that limits the improvement on transport throughput achieved by spatial multiplexing. In addition, when the number of contention slots is fixed, the efficiency of RTS/CTS contention is affected by the transmitting power of network nodes. In this study, a joint optimisation scheme on both transmitting power and contention slots number for maximising the transport throughput is presented. This includes the establishment of an analytical model of a simplified MAC protocol with multiple contention slots, the derivation of transport throughput as a function of both transmitting power and the number of contention slots, and the optimisation process based on the transport throughput formula derived. The analytical results obtained, verified by simulation, show that much higher transport throughput can be achieved using the joint optimisation scheme proposed, compared with the non-optimised cases and the results previously reported.