Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.

Optimised extraction of heterocyclic aromatic amines from blood using hollow fibre membrane liquid-phase microextraction and triple quadrupole mass spectrometry

Heterocyclic aromatic amines (HCA) are carcinogenic mutagens formed during cooking of proteinaceous foods, particularly meat. To assist in the ongoing search for biomarkers of HCA exposure in blood, a method is described for the extraction from human plasma of the most abundant HCAs: 2-Amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP), 2-amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) and 2-amino-3,4,8-trimethylimidazo[4,5-f]quinoxaline (4,8-DiMeIQx) (and its isomer 7,8-DiMeIQx), using Hollow Fibre Membrane Liquid-Phase Microextraction. This technique employs 2.5 cm lengths of porous polypropylene fibres impregnated with organic solvent to facilitate simultaneous extraction from an alkaline aqueous sample into a low volume acidic acceptor phase. This low cost protocol is extensively optimised for fibre length, extraction time, sample pH and volume. Detection is by UPLC-MS/MS using positive mode electrospray ionisation with a 3.4 min runtime, with optimum peak shape, sensitivity and baseline separation being achieved at pH 9.5. To our knowledge this is the first description of HCA chromatography under alkaline conditions. Application of fixed ion ratio tolerances for confirmation of analyte identity is discussed. Assay precision is between 4.5 and 8.8% while lower limits of detection between 2 and 5 pg/mL are below the concentrations postulated for acid-labile HCA-protein adducts in blood.

Adsorption Study using Optimised 3D Organised Mesoporous Silica Coated with Fe and Al Oxides for Specific As(III) and As(V) Removal from Contaminated Synthetic Groundwater

This work presents the possibility of optimising 3D Organised Mesoporous Silica (OMS) coated with both iron and aluminium oxides for the optimal removal of As(III) and As(V) from synthetic contaminated water. The materials developed were fully characterised and were tested for removing arsenic in batch experiments. The effect of total Al to Fe oxides coating on the selective removal of As(III) and As(V) was studied. It was shown that 8% metal coating was the optimal configuration for the coated OMS materials in removing arsenic. The effect of arsenic initial concentration and pH, kinetics and diffusion mechanisms was studied, modelled and discussed. It was shown that the advantage of an organised material over an un-structured sorbent was very limited in terms of kinetic and diffusion under the experimental conditions. It was shown that physisorption was the main adsorption process involved in As removal by the coated OMS. Maximum adsorption capacity of 55 mg As(V).g-1 was noticed at pH 5 for material coated with 8% Al oxides while 35 mg As(V).g-1 was removed at pH 4 for equivalent material coated with Fe oxides.

Biocompatibility of Calcium Phosphate Bone Cement with Optimised Mechanical Properties

The broad aim of this work was to investigate and optimise the properties of calcium phosphate bone cements (CPCs) for use in vertebroplasty to achieve effective primary fixation of spinal fractures. The incorporation of collagen, both bovine and from a marine sponge (Chondrosia reniformis), into a CPC was investigated. The biological properties of the CPC and collagen-CPC composites were assessed in vitro through the use of human bone marrow stromal cells. Cytotoxicity, proliferation and osteoblastic differentiation were evaluated using lactate dehydrogenase, PicoGreen and alkaline phosphatase activity assays respectively. The addition of both types of collagen resulted in an increase in cytotoxicity, albeit not to a clinically relevant level. Cellular proliferation after 1, 7 and 14 days was unchanged. The osteogenic potential of the CPC was reduced through the addition of bovine collagen but remained unchanged in the case of the marine collagen. These findings, coupled with previous work showing that incorporation of marine collagen in this way can improve the physical properties of CPCs, suggest that such a composite may offer an alternative to CPCs in applications where low setting times and higher mechanical stability are important.

An optimised milk testing protocol to ensure accurate enumeration of viable Mycobacterium avium subsp. paratuberculosis by the PMS-phage assay

There is interest in determining levels of Mycobacterium avium subsp. paratuberculosis (MAP) contamination in milk. The optimal sample preparation for raw cows' milk to ensure accurate enumeration of viable MAP by the peptide-mediated magnetic separation (PMS)-phage assay was determined. Results indicated that milk samples should be refrigerated at 4 C after collection and MAP testing should commence within 24 h, or samples can be frozen at 70 C for up to one month without loss of MAP viability. Use of Bronopol is not advised as MAP viability is affected. The vast majority (>95%) of MAP in raw milk sedimented to the pellet upon centrifugation at 2500 g for 15 min, so this milk fraction should be tested. De-clumping of MAP cells was most effectively achieved by ultrasonication of the resuspended milk pellet on ice in a sonicator bath at 37 kHz for 4 min in ‘Pulse’ mode.

Optimised Multiplication Architectures for Accelerating Fully Homomorphic Encryption

Large integer multiplication is a major performance bottleneck in fully homomorphic encryption (FHE) schemes over the integers. In this paper two optimised multiplier architectures for large integer multiplication are proposed. The first of these is a low-latency hardware architecture of an integer-FFT multiplier. Secondly, the use of low Hamming weight (LHW) parameters is applied to create a novel hardware architecture for large integer multiplication in integer-based FHE schemes. The proposed architectures are implemented, verified and compared on the Xilinx Virtex-7 FPGA platform. Finally, the proposed implementations are employed to evaluate the large multiplication in the encryption step of FHE over the integers. The analysis shows a speed improvement factor of up to 26.2 for the low-latency design compared to the corresponding original integer-based FHE software implementation. When the proposed LHW architecture is combined with the low-latency integer-FFT accelerator to evaluate a single FHE encryption operation, the performance results show that a speed improvement by a factor of approximately 130 is possible.

Detecting obfuscated malware using reduced opcode set and optimised runtime trace

The research presented, investigates the optimal set of operational codes (opcodes) that create a robust indicator of malicious software (malware) and also determines a program’s execution duration for accurate classification of benign and malicious software. The features extracted from the dataset are opcode density histograms, extracted during the program execution. The classifier used is a support vector machine and is configured to select those features to produce the optimal classification of malware over different program run lengths. The findings demonstrate that malware can be detected using dynamic analysis with relatively few opcodes.