Importance of Leptosphaeria biglobosa as a cause of phoma stem canker on winter oilseed rape in the UK

Phoma stem canker is a major disease of oilseed rape in the UK, leading to annual yield losses worth more than £100M. The disease is caused by two closely related species, Leptosphaeria maculans and L. biglobosa. L. maculans is generally considered more damaging, causing stem base canker; L. biglobosa is generally less damaging, causing upper stem lesions. Therefore, previous work has mainly focused on L. maculans and there has been little work on L. biglobosa. This work investigated the contribution of L. biglobosa to stem canker epidemics by assessing the amounts of DNA of L. maculans and L. biglobosa in upper stem lesions or stem base cankers on winter oilseed rape cultivars with different types of resistance against L. mac ulans. Diseased upper stem and stem base samples were collected from nine oilseed rape cultivars in a 2011/2012 field experiment at Rothamsted. The presence of L. maculans or L. biglobosa in each stem sample was detected by speciesspecific PCR. The abundance of L. maculans or L. biglobosa in each stem sample was measured by quantification of L. maculans DNA and L. biglobosa DNA using quantitative PCR (qPCR). The amounts of L. biglobosa DNA were greater than those of L. maculans DNA in both upper stem and stem base samples. These results suggest that the severe upper stem lesions and stem base cankers in the 2011/2012 cropping season were mainly caused by L. biglobosa, suggesting that L. biglobosa can sometimes cause considerable yield loss in the UK. There were differences between cultivars in the amounts of L. maculans DNA and L. biglobosa DNA, with the susceptible cultivar Drakkar having more L. maculans DNA than L. biglobosa DNA while resistant cultivars had less L. maculans DNA than L. biglobosa DNA. These results suggest that L. biglobosa can be an important cause of phoma stem canker on oilseed rape in the UK.Peer reviewedFinal Published versio

Commutative C*-Algebras Generated by Toeplitz Operators on the Fock Space

The Fock space $\mathcal{F}(\mathbb{C}^n)$ is the space of holomorphic functions on $\mathbb{C}^n$ that are square-integrable with respect to the Gaussian measure on $\mathbb{C}^n$. This space plays an essential role in several subfields of analysis and representation theory. In particular, it has for a long time been a model to study Toeplitz operators. Grudsky and Vasilevski showed in 2002 that radial Toeplitz operators on $\mathcal{F}(\mathbb{C})$ generate a commutative $C^*$-algebra $\mathcal{T}^G$, while Esmeral and Maximenko showed that $C^*$-algebra $\mathcal{T}^G$ is isometrically isomorphic to the $C^*$-algebra $C_{b,u}(\mathbb{N}_0,\rho_1)$. In this thesis, we extend the result to $k$-quasi-radial symbols acting on the Fock space $\mathcal{F}(\mathbb{C}^n)$. We calculate the spectra of the said Toeplitz operators and show that the set of all eigenvalue functions is dense in the $C^*$-algebra $C_{b,u}(\mathbb{N}_0^k,\rho_k)$ of bounded functions on $\mathbb{N}_0^k$ which are uniformly continuous with respect to the square-root metric. In fact, the $C^*$-algebra generated by Toeplitz operators with quasi-radial symbols is $C_{b,u}(\mathbb{N}_0^k,\rho_k)$

Classical And Ab Initio Qm/mm Simulations Of Bacterial Enzymes

This thesis describes analyses performed on three enzyme systems. Chapter 2, 3, and 4 involve studies carried out on the GatCAB enzyme of H. pylori and S. aureus. Since information at the electronic level was not required for these studies, sampling of the configuration space carried out at the molecular mechanics level was adequate. In Chapter 2, the snapshots sampled using MD were used as input for average correlation difference calculations and average RMSD difference calculations to ascertain the existence of a communication pathway between two subunits of GatCAB. Experimental and computational results obtained, suggest the existence of a communication pathway between the GatA and GatB subunits of H. pylori GatCAB. In Chapter 3, the snapshots sampled using MD were used as input for average correlation difference calculations and pKa calculations to analyze the possibility of an amino acid residue acting as a possible catalytic acid/base at the entrance of an intramolecular tunnel that transfers ammonia from one active site to another. Experimental results that compare glutaminase, kinase, and transamidase activity for wild-type H. pylori GatCAB with the mutants D185(A)E, D185(A)A, and D185(A)N as well as our computational results support the possibility of D185(A) in H. pylori GatCAB acting as a catalytic acid/base in protonation/deprotonation of ammonia. In Chapter 4, MD snapshots were used to calculate intramolecular tunnels inside S. aureus GatCAB along which the free energy for the transfer of ammonia was calculated using the WHAM method to identify the tunnel that was thermodynamically more favorable. EDA and APBS analyses were utilized for further characterization of the tunnels in terms of non-bonded interactions between the ammonia molecule and the surrounding amino acids lining the tunnel. The results of the free energy calculations using WHAM as well as the energy differences calculated using EDA showed that tunnel1 (proposed in 2006 by Nakamura et al.) is thermodynamically more favorable for transfer of ammonia compared to tunnel2 (proposed in 2012 by Kang et al.) Chapter 5 discusses the inorganic pyrophosphatase (PPase) mechanism in M. tuberculosis which requires information at the electronic level. The QM/MM hybrid method was used in which the reactive moieties were included in the QM subsystem to achieve accuracy at the electronic level while the rest of the system was treated at the molecular mechanics level. Based on a set of newly isolated crystal structures and the results of the QM/MM calculations, a new mechanism for the PPase catalyzed PPi hydrolysis was proposed and an energy barrier of 6.6 kcal/mol was calculated at the B3LYP/6-31G(d,p) level of theory. In Chapter 6, molecular docking was used to dock a set of novel substrates that are being experimentally tested as potential radiotracers, onto HDAC4 and HDAC8 enzymes to calculate/compare their relative binding affinities. The trends in the increase in affinity, of the novel substrates for HDAC4 and HDAC8 active sites calculated by molecular docking, agreed with the experimentally shown trends

Investigation of hydrogen based redox flow batteries

Large scale energy storage is crucial for effective integration of intermittent renewable energy sources such as solar and wind. Redox flow batteries are a promising grid scale energy storage technology and understanding their losses is key to further optimisation. This thesis investigates a novel class of RFBs which utilises a conventional liquid based cathode in combination with a hydrogen anode, similar to that used in a Proton Exchange Membrane Fuel Cell (PEMFC). Firstly, a new Reference Electrode (RE) positioning method was developed in order to decouple anode and cathode processes in RFBs. Unlike other methods presented in literature, the approach described here can generate reliable measurements, without noticeably affecting the performance of the cell. This set-up was used to further understand the Regenerative Hydrogen-Vanadium Fuel Cell (RHVFC), which revealed that cathode diffusion and ohmic losses were the limiting processes of this cell. Catholyte crossover was also observed, which resulted in vanadium adsorption onto the catalyst of the hydrogen electrode. Secondly, the feasibility of a novel Regenerative Hydrogen-Cerium Fuel Cell (RHCFC) was validated. Using the same RE set-up, further investigation was carried out on an optimised cell, which yielded energy efficiencies in the range of 70 to 85 \% when charging/discharging at current densities up to 20 mA/cm2. A combination of electrochemical impedance spectroscopy and polarisation tests allowed the decoupling of many of the processes occurring at each electrode. In addition, imaging and surface characterisation techniques revealed the presence of carbon deposits on the fresh electrode surface, which increased with use; the nature of these deposits and their implication on cell operation will be the subject of further investigation. Finally, it was established that the performance of the cell is currently limited by the cerium cathode, which suffers from poor kinetics and large diffusion losses.Open Acces

Unitary and Symmetric Structure in Deep Neural Networks

Recurrent neural networks (RNNs) have been successfully used on a wide range of sequential data problems. A well-known difficulty in using RNNs is the vanishing or exploding gradient problem. Recently, there have been several different RNN architectures that try to mitigate this issue by maintaining an orthogonal or unitary recurrent weight matrix. One such architecture is the scaled Cayley orthogonal recurrent neural network (scoRNN), which parameterizes the orthogonal recurrent weight matrix through a scaled Cayley transform. This parametrization contains a diagonal scaling matrix consisting of positive or negative one entries that can not be optimized by gradient descent. Thus the scaling matrix is fixed before training, and a hyperparameter is introduced to tune the matrix for each particular task. In the first part of this thesis, we develop a unitary RNN architecture based on a complex scaled Cayley transform. Unlike the real orthogonal case, the transformation uses a diagonal scaling matrix consisting of entries on the complex unit circle, which can be optimized using gradient descent and no longer requires the tuning of a hyperparameter. We compare the performance of The scaled Cayley unitary recurrent neural network (scuRNN) with scoRNN and other unitary RNN architectures. Convolutional Neural Networks (CNNs) is a class of deep neural networks, most commonly applied to analyzing visual imagery. Nowadays, deep neural networks also play an important role in understanding biological problems such as modeling RNA sequences and protein sequences. The second part of the thesis explores deep learning approaches involving recurrent and convolutional networks to directly infer RNA secondary structure or Protein contact map, which has a symmetric feature matrix as output. We develop a CNN architecture with a suitable symmetric parameterization of the convolutional Kernel that naturally produces symmetric feature matrices. We apply this architecture to the inference tasks for the RNA secondary structure or protein contact maps. We compare our symmetrized CNN architecture with the usual convolution network architecture and show that these approaches can improve prediction results while using equal or fewer numbers of machine parameters

Determinants of Farmers’ Perceptions towards the Adoption of New Farming Techniques in Paddy Production in Sri Lanka

The aim of this study is to identify and analyze the demographic, farming and other characteristics that influencing the perceptions of farmers to adopt new agricultural technologies in paddy sector evidence from Divulapitiya region in Sri Lanka. For this purpose, simple random sampling technique was used to select hundred farmers from three main paddy producing areas in the above region for the period of 2015. Primary data related to farmers’ perceptions and the characteristics of demographic, farming and others such as attitudes of the farmers towards risk and availability of market information were collected through a structured questionnaire. Dependent variable is the adoption of farmers’ perceptions which has the ranges between zero to one and farmers’ age and education, size of cultivated land, ownership of land, farming experience, attitudes of the farmers towards the risk and availability of market information were treated as explanatory variables. The collected data were analyzed using different econometrics techniques such as frequency analysis, chi – square test, Tobit model and marginal effects. Frequency results of farmers’ perceptions to adopt new types of technologies indicates that, nearly 6% of the farmers not adopting any type of technologies while, 35% of them adopting any three types of technologies. Only17% of them was adopting all four types of technologies in paddy cultivation in Divulapitiya area. Empirical results of Tobit model reveal that the farmers’ adoption decisions were significantly influenced by all the above characteristics and the marginal effects shows that the farmers who have more educational knowledge interested nearly 15% of more probability to adopt new techniques while the farmers who are prefers to avoid the risk interested almost 7% of less likely to adopt them in their cultivation. Findings of this study highlight the relevance of networks that promote farmer-to-farmer interactions in the circulation of new technologies and also it is important to policy makers to endorse paddy cultivation with expertise knowledge in the applications of new farming techniques in paddy cultivation in the Divulapitiya, Sri Lanka. Keywords: Demographic and farming characteristics, perceptions of farmers, Tobit model, Marginal effects

Supervisory control of fuzzy discrete event systems with applications to mobile robotics

Fuzzy Discrete Event Systems (FDES) were proposed in the literature for modeling and control of a class of event driven and asynchronous dynamical systems that are affected by deterministic uncertainties and vagueness on their representations. In contrast to classical crisp Discrete Event Systems (DES), which have been explored to a sufficient extent in the past, an in-depth study of FDES is yet to be performed, and their feasible real-time application areas need to be further identified. This research work intends to address the supervisory control problem of FDES broadly, while formulating new knowledge in the area. Moreover, it examines the possible applications of these developments in the behavior-based mobile robotics domain. An FDES-based supervisory control framework to facilitate the behavior-based control of a mobile robot is developed at first. The proposed approach is modular in nature and supports behavior integration without making state explosion. Then, this architecture is implemented in simulation as well as in real-time on a mobile robot moving in unstructured environments, and the feasibility of the approach is validated. A general decentralized supervisory control theory of FDES is then established for better information association and ambiguity management in large-scale and distributed systems, while providing less complexity of control computation. Furthermore, using the proposed architecture, simulation and real-time experiments of a tightly-coupled multi-robot object manipulation task are performed. The results are compared with centralized FDES-based and decentralized DES-based approaches. -- A decentralized modular supervisory control theory of FDES is then established for complex systems having a number of modules that are concurrently operating and also containing multiple interactions. -- Finally, a hierarchical supervisory control theory of FDES is established to resolve the control complexity of a large-scale compound system by modularizing the system vertically and assigning multi-level supervisor hierarchies. As a proof-of-concept example to the established theory, a mobile robot navigation problem is discussed. This research work will contribute to the literature by developing novel knowledge and related theories in the areas of decentralized, modular and hierarchical supervisory control of FDES. It also investigates the applicability of these contributions in the mobile robotics arena

Disease management in oilseed rape: insights into the Brassica napus-Pyrenopeziza brassicae pathosystem

Final Published versio

Nutritional and toxicological composition analysis of selected cassava processed products

Cassava (Manihot esculanta Crantz) is an important food source in tropical countries where it can withstand environmentally stressed conditions. Cassava and its processed products have a high demand in both local and export market of Sri Lanka. MU51 cassava variety is one of the more common varieties and boiling is the main consumption pattern of cassava among Sri Lankans. The less utilization of cassava is due to the presence of cyanide which is a toxic substance. This research was designed to analyse the nutritional composition and toxicological (cyanide) content of Cassava MU51 variety and selected processed products of cassava MU51 (boiled, starch, flour, chips, two chips varieties purchased from market) to identify the effect of processing on cassava MU51 variety. Nutritional composition was analysed by AOAC (2012) methods with modifications and cyanide content was determined following picric acid method of spectrophotometric determination. The Flesh of MU51 variety and different processed products of cassava had an average range of moisture content (3.18 - 61.94%), total fat (0.31 - 23.30%), crude fiber (0.94 - 2.15%), protein (1.67 - 3.71%) and carbohydrates (32.68 - 84.20%) and where they varied significantly in between products and the variety MU51, where no significance difference (p >0.05) observed in between MU51 flesh and processed products' ash content where it ranged (1.02 - 1.91%). However, boiled product and MU51 flesh had more similar results in their nutritional composition where they showed no significant difference at any of the nutrient that was analysed. Thus, there could be no significant effect on the nutrient composition of raw cassava once it boiled. Cyanide content of the MU51 flesh and selected products (boiled, starch, flour and chips prepared using MU51 variety), showed wide variation ranging from 4.68 mg.kg-1 to 33.92 mg.kg-1 in dry basis. But except boiled cassava all processed products had cyanide content <10 mg.kg-1, which is the safe level recommended by the Codex Alimentarius Committee of the FAO/WHO. Thus, preparing products such as flour, starch and chips using MU51 variety could be safe for human consumption.&nbsp