Development of miniaturized wireless sensor nodes suitable for building energy management and modelling

Buildings consume 40% of Ireland's total annual energy translating to 3.5 billion (2004). The EPBD directive (effective January 2003) places an onus on all member states to rate the energy performance of all buildings in excess of 50m2. Energy and environmental performance management systems for residential buildings do not exist and consist of an ad-hoc integration of wired building management systems and Monitoring & Targeting systems for non-residential buildings. These systems are unsophisticated and do not easily lend themselves to cost effective retrofit or integration with other enterprise management systems. It is commonly agreed that a 15-40% reduction of building energy consumption is achievable by efficiently operating buildings when compared with typical practice. Existing research has identified that the level of information available to Building Managers with existing Building Management Systems and Environmental Monitoring Systems (BMS/EMS) is insufficient to perform the required performance based building assessment. The cost of installing additional sensors and meters is extremely high, primarily due to the estimated cost of wiring and the needed labour. From this perspective wireless sensor technology provides the capability to provide reliable sensor data at the required temporal and spatial granularity associated with building energy management. In this paper, a wireless sensor network mote hardware design and implementation is presented for a building energy management application. Appropriate sensors were selected and interfaced with the developed system based on user requirements to meet both the building monitoring and metering requirements. Beside the sensing capability, actuation and interfacing to external meters/sensors are provided to perform different management control and data recording tasks associated with minimisation of energy consumption in the built environment and the development of appropriate Building information models(BIM)to enable the design and development of energy efficient spaces.

Targeting aberrant kinase activity in myeloid leukaemias

Acute myeloid leukaemia (AML) is the most common form of acute leukaemia in adults. Its treatment has remained largely unchanged for the past 30 years. Chronic myeloid leukaemia (CML) represents a tremendous success story in the era of targeted therapy but significant challenges remain including the development of drug resistance and disease persistence due to presence of CML stem cells. The Aurora family of kinases is essential for cell cycle regulation and their aberrant expression in cancer prompted the development of small molecules that selectively inhibit their activity. Chapter 2 of this thesis outlines the efficacy and mechanism of action of alisertib, a novel inhibitor of Aurora A kinase, in preclinical models of CML. Alisertib possessed equipotent activity against CML cells expressing unmutated and mutated forms of BCR-ABL. Notably, this agent retained high activity against the T315I and E255K BCR-ABL mutations, which confer the greatest degree of resistance to standard CML therapy. Chapter 3 explores the activity of alisertib in preclinical models of AML. Alisertib disrupted cell viability, diminished clonogenic survival, induced expression of the forkhead box O3 (FOXO3a) targets p27 and BCL-2 interacting mediator (BIM), and triggered apoptosis. A link between Aurora A expression and sensitivity to ara-C was established. Chapter 4 outlines the role of the proto-oncogene serine/threonine-protein (PIM) kinases in resistance to ara-C in AML. We report that the novel small molecule PIM kinase inhibitor SGI-1776 disrupted cell viability and induced apoptosis in AML. We establish a link between ara-C resistance and PIM over-expression. Finally, chapter 5 explores how the preclinical work outlined in this thesis may be translated into clinical studies that may lead to novel therapeutic approaches for patients with refractory myeloid leukaemia.

Synthesis and evaluation of novel azaindolocarbazole derivatives as cancer chemotherapeutics

This thesis details the design and implementation of novel chemical routes towards a series of highly propitious 7-azaindolyl derivatives of the indolocarbazole (ICZ) and bisindolylmaleimide (BIM) families, with subsequent evaluation for use as cancer chemotherapeutic agents. A robust synthetic strategy was devised to allow the introduction of a 7-azaindolyl moiety into our molecular template. This approach allowed access to a wide range of β-keto ester and β-keto nitrile intermediates. Critical analysis identified F-ring modulation as a major theme towards the advancement of ICZ and BIM derivatives in drug therapy. Thus, the employment of cyclocondensation methodology furnished a number of novel aminopyrazole, isoxazolone, pyrazolone and pyrimidinone analogues, considerably widening the scope of the prevalent maleimide functionality. Photochemical cyclisation provided for the first reported aza ICZ containing a six-membered F-ring. Another method towards achieving the aza ICZ core involved use of a Perkin-type condensation approach, with chemical elaboration of the headgroup instigated post-aromatisation. Subsequent use of a modified Lossen rearrangement allowed access to further analogues containing a six-membered F-ring. Extensive screening of the novel aza ICZ and BIM derivatives was carried out against the NCI-60 cancer cell array, with nine prospective candidates selected for continued biological evaluation. From these assays, a number of compounds were shown to inhibit cancer cell growth at concentrations of below 10 nM. Indeed, the most active aza ICZ tested is currently under assessment by the Biological Evaluation Committee of the NCI due to excellent antiproliferative activity demonstrated across the panel of cell lines, with a mean GI50 of 34 nM, a mean total growth inhibition (TGI) of 4.6 μM and a mean cytotoxicity (LC50) of 63.1 μM. Correlation to known topoisomerase I (topo I) inhibitors was revealed by COMPARE analysis, and subsequent topo I-mediated DNA cleavage assays showed inhibitory activity below 1 μM for several derivatives.

A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.