Delivering enhanced efficiency in the synthesis of α-diazosulfoxides by exploiting the process control enabled in flow

Continuous-flow generation of α-diazosulfoxides results in a two- to three-fold increase in yields and decreased reaction times compared to standard batch synthesis methods. These high yielding reactions are enabled by flowing through a bed of polystyrene-supported base (PS-DBU or PS-NMe2) with highly controlled residence times. This engineered solution allows the α-diazosulfoxides to be rapidly synthesized while limiting exposure of the products to basic reaction conditions, which have been found to cause rapid decomposition. In addition to improved yields, this work has the added advantage of ease of processing, increased safety profile, and scale-up potential.

Dynamic control of laser driven proton beams by exploiting self-generated, ultrashort electromagnetic pulses

As part of the ultrafast charge dynamics initiated by high intensity laser irradiations of solid targets,high amplitude EM pulses propagate away from the interaction point and are transported along anystalks and wires attached to the target. The propagation of these high amplitude pulses along a thinwire connected to a laser irradiated target was diagnosed via the proton radiography technique,measuring a pulse duration of 20 ps and a pulse velocity close to the speed of light. The strongelectric field associated with the EM pulse can be exploited for controlling dynamically the protonbeams produced from a laser-driven source. Chromatic divergence control of broadband laser drivenprotons (upto 75% reduction in divergence of >5 MeV protons) was obtained by winding the supportingwire around the proton beam axis to create a helical coil structure. In addition to providingfocussing and energy selection, the technique has the potential to post-accelerate the transiting protonsby the longitudinal component of the curved electric field lines produced by the helical coil lens.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

Exploiting DNA damage repair defects for effective targeting of acute myeloid leukaemia by PARP inhibitors

Abstract for 24th Biennial Congress of the European Association for Cancer Research, 9–12 July 2016, Manchester, UK. Poster Session: Cancer Genomics, Epigenetics and Genome Instability II: Monday 11 July 2016

'Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem'

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

Exploiting Nested Parallelism on Heterogeneous Processors

Heterogeneous computing systems have become common in modern processor architectures. These systems, such as those released by AMD, Intel, and Nvidia, include both CPU and GPU cores on a single die available with reduced communication overhead compared to their discrete predecessors. Currently, discrete CPU/GPU systems are limited, requiring larger, regular, highly-parallel workloads to overcome the communication costs of the system. Without the traditional communication delay assumed between GPUs and CPUs, we believe non-traditional workloads could be targeted for GPU execution. Specifically, this thesis focuses on the execution model of nested parallel workloads on heterogeneous systems. We have designed a simulation flow which utilizes widely used CPU and GPU simulators to model heterogeneous computing architectures. We then applied this simulator to non-traditional GPU workloads using different execution models. We also have proposed a new execution model for nested parallelism allowing users to exploit these heterogeneous systems to reduce execution time.

Exploiting Collective Effects to Direct Light Absorption in Natural and Artificial Light-harvesters

Photosynthesis –the conversion of sunlight to chemical energy –is fundamental for supporting life on our planet. Despite its importance, the physical principles that underpin the primary steps of photosynthesis, from photon absorption to electronic charge separation, remain to be understood in full. Electronic coherence within tightly-packed light-harvesting (LH) units or within individual reaction centers (RCs) has been recognized as an important ingredient for a complete understanding of the excitation energy transfer (EET) dynamics. However, the electronic coherence across units –RC and LH or LH and LH –has been consistently neglected as it does not play a significant role during these relatively slow transfer processes. Here, we turn our attention to the absorption process, which, as we will show, has a much shorter built-in timescale. We demonstrate that the- often overlooked- spatially extended but short-lived excitonic delocalization plays a relevant role in general photosynthetic systems. Most strikingly, we find that absorption intensity is, quite generally, redistributed from LH units to the RC, increasing the number of excitations which can effect charge separation without further transfer steps. A biomemetic nano-system is proposed which is predicted to funnel excitation to the RC-analogue, and hence is the first step towards exploiting these new design principles for efficient artificial light-harvesting.

Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

Parallel Cyclostationarity-Exploiting Algorithm for Energy-Efficient Spectrum Sensing

The evolution of wireless communication systems leads to Dynamic Spectrum Allocation for Cognitive Radio, which requires reliable spectrum sensing techniques. Among the spectrum sensing methods proposed in the literature, those that exploit cyclostationary characteristics of radio signals are particularly suitable for communication environments with low signal-to-noise ratios, or with non-stationary noise. However, such methods have high computational complexity that directly raises the power consumption of devices which often have very stringent low-power requirements. We propose a strategy for cyclostationary spectrum sensing with reduced energy consumption. This strategy is based on the principle that p processors working at slower frequencies consume less power than a single processor for the same execution time. We devise a strict relation between the energy savings and common parallel system metrics. The results of simulations show that our strategy promises very significant savings in actual devices.

'Exploiting problem structure in a genetic algorithm approach to a nurse rostering problem'

There is considerable interest in the use of genetic algorithms to solve problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle the conflict between objectives and constraints that typically occurs in such problems. In order to overcome this, successful implementations frequently make use of problem specific knowledge. This paper is concerned with the development of a GA for a nurse rostering problem at a major UK hospital. The structure of the constraints is used as the basis for a co-evolutionary strategy using co-operating sub-populations. Problem specific knowledge is also used to define a system of incentives and disincentives, and a complementary mutation operator. Empirical results based on 52 weeks of live data show how these features are able to improve an unsuccessful canonical GA to the point where it is able to provide a practical solution to the problem.

Anisotropic Assembly of Colloidal Nanoparticles: Exploiting Substrate Crystallinity

We show that the crystal structure of a substrate can be exploited to drive the anisotropic assembly of colloidal nanoparticles. Pentanethiol-passivated Au particles of approximately 2 nm diameter deposited from toluene onto hydrogen-passivated Si(111) surfaces form linear assemblies (rods) with a narrow width distribution. The rod orientations mirror the substrate symmetry, with a high degree of alignment along principal crystallographic axes of the Si(111) surface. There is a strong preference for anisotropic growth with rod widths substantially more tightly distributed than lengths. Entropic trapping of nanoparticles provides a plausible explanation for the formation of the anisotropic assemblies we observe.

Small molecules exploiting emerging therapeutic opportunities for breast cancer treatment

Among the different types of breast cancer (BC), the estrogen receptor positive (ER+) subtype, which requires estrogens for its growth and proliferation, is the most common, while triple negative BC, characterized by the absence of ER, progesterone receptor and human epidermal growth factor receptor 2, often leads to poor prognosis. First-line therapies for the treatment of ER+ BC act either by suppressing estrogen production, through the inhibition of aromatase (AR) enzyme, or by blocking estrogen prooncogenic activity, via the modulation/degradation of ERs. The serious side effects and the intrinsic or acquired resistance phenomena that arise with prolonged use of these drugs limit their therapeutic application, stimulating the search for new strategies to face this disease. In this context, the development of dual acting aromatase inhibitors, able to target both the orthosteric and the recently identified allosteric pockets of AR could be an opportunity to fight ER+ BC. Another promising strategy could be the development of multitarget compounds, targeting both AR and ERs. In this scenario, here we designed and synthesized two series of new xanthones or more flexible benzophenones as potential dual acting aromatase inhibitors. Moreover, inspired from tamoxifen metabolites and a literature compound endowed with activity on both AR and ER, different structurally related series of potential multitarget compounds were developed. The biological results showed that some of the new molecules were promising candidates for further development. It was recently observed that the lately discovered histamine H4 receptor is expressed in human breast tissue, displaying a key role in biological processes mediated by histamine such as cell proliferation, senescence, and apoptosis in malignant cells, representing a potential target in triple negative BC. Thus, a broad series of methyl quinazoline sulfonamides, carrying different functional groups on the sulfonamide moiety, were designed and synthesized as potential H4 receptor ligands.

Precise Near-Field Focusing exploiting Bessel Beam Launchers for Wireless Power Transfer at millimeter waves

Wireless Power Transfer has become a promising technology to overcome the limits of wired solutions. Within this framework, the objective of this thesis is to study a WPT link at millimeter waves involving a particular type of antenna working in the radiative near-field, known as Bessel Beam (BB) Launcher. This antenna has been chosen for its peculiarity of generating a Bessel Beam which is by nature non-diffractive, showing good focusing and self-healing capabilities. In particular, a Bull-Eye Leaky Wave Antenna is designed and analysed, fed by a loop antenna and resonating at approximately 30 GHz. The structure excites a Hybrid-TE mode showing zeroth-order Bessel function over the z-component of the magnetic field. The same antenna is designed with two different dimensions, showing good wireless power transport properties. The link budgets obtained for different configurations are reported. With the aim of exploiting BB Launchers in wearable applications, a further analysis on the receiving part is conducted. For WPT wearable or implantable devices a reduced dimension of the receiver system must be considered. Therefore, an electrically large loop antenna in planar technology is modified, inserting phase shifters in order to increase the intensity of the magnetic field in its interrogation zone. This is fundamental when a BB Launcher is involved as transmitter. The loop antenna, in reception, shows a further miniaturization level since it is built such that its interrogation zone corresponds to the main beam dimension of transmitting BB Launcher. The link budget is evaluated with the new receiver showing comparable results with respect to previous configurations, showing an efficient WPT link for near-field focusing. Finally, a matching network and a full-wave rectifying circuit are attached to two of the different receiving systems considered. Further analysis will be carried out about the robustness of the square loop over biological tissues.