Applications of Genetic Algorithms to a Variety of Problems in Physics and Astronomy

Genetic algorithms are search techniques that borrow ideas from the biological process of evolution. By means of natural selection, genetic algorithms can be employed as robust numerical optimizers on problems that would normally be extremely problematic due to ill-behaved search spaces. The genetic algorithm has an advantage in that it is a global optimization strategy, as opposed to more conventional methods, which will often terminate at local maxima. The success and resourcefulness of genetic algorithms as problem-solving strategies are quickly gaining recognition among researchers of diverse areas of study. In this thesis I elaborate on applications of a genetic algorithm to several problems in physics and astronomy. First, the concepts behind functional optimization are discussed, as well as several computational strategies for locating optima. The basic ideas behind genetic algorithms and their operations are then outlined, as well as advantages and disadvantages of the genetic algorithm over the previously discussed optimization techniques. Then the results of several applications of a genetic algorithm are discussed. The majority are relatively simple problems (involving the fitting of only one or two parameters) that nicely illustrate the genetic algorithm’s approach to optimization of “fitness,” and its ability to reproduce familiar results. The last two problems discussed are non-trivial and demonstrate the genetic algorithm’s robustness. The first of these was the calculation of the mass of the radio source Sagittarius A*, believed to be a supermassive black hole at the center of the Milky Way, which required that the genetic algorithm find several orbital elements associated with an orbiting star. The results obtained with the genetic algorithm were in good agreement with those obtained by Genzel et al [19]. Then discussed was the problem of parametrization of thermonuclear reaction rates. This problem is especially interesting because attempts at fitting several rates prior to the implementation of the genetic algorithm proved to be unsuccessful. Some of the rates varied with temperature over many orders of magnitude, and required the genetic algorithm to find as many as twenty-eight parameters. A relatively good fit was obtained for all of the rates. In the applications of genetic algorithms discussed in this thesis, it has been found that they can outperform conventional optimization strategies for difficult, multidimensional problems, and can perform at least as well as conventional methods when applied to more trivial problems

Diversity As A Predictor Of Leadership Effectiveness

Drawing upon theexisting literature, this study investigated the significance of Diversity as apredictor of leadership effectiveness, as it relates to the MultidimensionalMeasure of Leader-Member Exchange (LMX-MDM).  A study of 300 working adults found that therewas a significant positive relationship between Diversity and the four LMXdimensions of Contribution, Loyalty, Affect, and Professional Respect.  Collectivism and religious affiliation wereboth strong predictors with regard to Contribution.  With regard to the dimension of Loyalty;collectivism, gender egalitarianism, and age helped to increase ratings of thesupervisor and perceptions of leadership.  Affect only had one significant predictor, collectivism. The LMX dimension of ProfessionalRespect was found to have four significant predictors, including collectivism, religiousaffiliation, age, and years as a manager.  Further regression analysis indicated that theDiversity dimension, Collectivism, was the driving factor of the relationship.  This outcome indicated that Collectivism was astrong predictor of how positively participants rated their attitudes towardtheir immediate supervisor and perceptions of leadership.  The results of this study indicate that diversity,particularly with regard to collectivism, is a positive predictor of leadershipeffectiveness using the LMX model.  Furthermore,it strengthens the argument that organizations must be prepared to re-evaluatetheir policies with regard to diversity in the organization, particularly withrespect to Collectivism

Printing of Responsive Photonic Cellulose Nanocrystal Micro-Film Arrays

Interactive materials capable of changing appearance upon exposure to external stimuli, such as photonic inks, are generally difficult to achieve on a large scale as they often require self-assembly processes that are difficult to control macroscopically. Here we overcome this problem by preparing arrays of cellulose nanocrystal (CNC) micro-films from discrete nanoliter sessile droplets. The obtained micro-films show extremely uniform and intense color, enabling exceptional consistency in optical appearance across the entire array. The color can be controlled through the initial ink formulation, enabling the printing of polychromatic dot-matrix images. Moreover, the high surface-to-volume ratio of the micro-films and the intrinsic hydrophilicity of the natural building block allow for a dramatic real-time colorimetric response to changes in relative humidity. The printed CNC micro-film arrays overcome the existing issues of scalability, optical uniformity and material efficiency, which have held back the adoption of CNC-based photonic materials in cosmetics, interactive-pigments or anti-counterfeit applications.The European Research Council [ERC-2014-STG H2020 639088], the BBSRC David Phillips Fellowship [BB/K014617/1], the EPSRC [EP/L016087/1, EP/L015978/1, EP/N016920/1], and the Winton Programme for the Physics of Sustainability

WormBase - Annotating many nematode genomes

WormBase (www.wormbase.org) has been serving the scientific community for over 11 years as the central repository for genomic and genetic information for the soil nematode Caenorhabditis elegans. The resource has evolved from its beginnings as a database housing the genomic sequence and genetic and physical maps of a single species, and now represents the breadth and diversity of nematode research, currently serving genome sequence and annotation for around 20 nematodes. In this article, we focus on WormBase’s role of genome sequence annotation, describing how we annotate and integrate data from a growing collection of nematode species and strains. We also review our approaches to sequence curation, and discuss the impact on annotation quality of large functional genomics projects such as modENCODE

Fibroblast Activation Protein specific optical imaging in Non-Small Cell Lung Cancer

Fibroblast activation protein (FAP) is a cell surface propyl-specific serine protease involved in the regulation of extracellular matrix. Whilst expressed at low levels in healthy tissue, upregulation of FAP on fibroblasts can be found in several solid organ malignancies, including non-small cell lung cancer, and chronic inflammatory conditions such as pulmonary fibrosis and rheumatoid arthritis. Their full role remains unclear, but FAP expressing cancer associated fibroblasts (CAFs) have been found to relate to a poor prognosis with worse survival rates in breast, colorectal, pancreatic, and non-small cell lung cancer (NSCLC). Optical imaging using a FAP specific chemical probe, when combined with clinically compatible imaging systems, can provide a readout of FAP activity which could allow disease monitoring, prognostication and potentially stratify therapy. However, to derive a specific signal for FAP any sequence must retain specificity over closely related endopeptidases, such as prolyl endopeptidase (PREP), and be resistant to degradation in areas of active inflammation. We describe the iterative development of a FAP optical reporter sequence which retains FAP specificity, confers resistance to degradation in the presence of activated neutrophil proteases and demonstrates clinical tractability ex vivo in NSCLC samples with an imaging platform

Ethnically diverse urban transmission networks of Neisseria gonorrhoeae without evidence of HIV serosorting

Objective We aimed to characterise gonorrhoea transmission patterns in a diverse urban population by linking genomic, epidemiological and antimicrobial susceptibility data. Methods Neisseria gonorrhoeae isolates from patients attending sexual health clinics at Barts Health NHS Trust, London, UK, during an eleven-month period underwent whole-genome sequencing and antimicrobial susceptibility testing. We combined laboratory and patient data to investigate the transmission network structure. Results One hundred and fifty-eight isolates from 158 patients were available with associated descriptive data. One hundred and twenty-nine (82%) patients identified as male and 25 (16%) as female; 4 (3%) records lacked gender information. Self-described ethnicities were: 51 (32%) English/Welsh/Scottish; 33 (21%) White, other; 23 (15%) Black British/Black African/Black, other; 12 (8%) Caribbean; 9 (6%) South Asian; 6 (4%) mixed ethnicity; 10 (6%) other; data were missing for 14 (9%). Self-reported sexual orientations were 82 (52%) men who have sex with men; 49 (31%) heterosexual; 2 (1%) bisexual; data missing for 25 individuals. Twenty-two (14%) patients were HIV-positive. Whole genome sequence data were generated for 151 isolates, which linked 75 (50%) patients to at least one other case. Using sequencing data, we found no evidence of transmission networks related to specific ethnic groups (p=0.64) or of HIV serosorting (p=0.35). Of 82 MSM/bisexual patients with sequencing data, 45 (55%) belonged to clusters of ≥2 cases, compared to 16/44 (36%) heterosexuals with sequencing data (p=0.06). Conclusion We demonstrate links between 50% of patients in transmission networks using a relatively small sample in a large cosmopolitan city. We found no evidence of HIV serosorting. Our results do not support assortative selectivity as an explanation for differences in gonorrhoea incidence between ethnic groups

Functional mapping of quantitative trait loci (QTLs) associated with plant performance in a wheat MAGIC mapping population

In crop genetic studies, the mapping of longitudinal data describing the spatio-temporal nature of agronomic traits can elucidate the factors influencing their formation and development. Here, we combine the mapping power and precision of a MAGIC wheat population with robust computational methods to track the spatio- temporal dynamics of traits associated with wheat performance. NIAB MAGIC lines were phenotyped throughout their lifecycle under smart house conditions. Growth models were fitted to the data describing growth trajectories of plant area, height, water use and senescence and fitted parameters were mapped as quantitative traits. Trait data from single time points were also mapped to determine when and how markers became and ceased to be significant. Assessment of temporal dynamics allowed the identification of marker-trait associations and tracking of trait development against the genetic contribution of key markers. We establish a data-driven approach for understanding complex agronomic traits and accelerate research in plant breeding

Mapping our Universe in 3D with MITEoR

Mapping our universe in 3D by imaging the redshifted 21 cm line from neutral hydrogen has the potential to overtake the cosmic microwave background as our most powerful cosmological probe, because it can map a much larger volume of our Universe, shedding new light on the epoch of reionization, inflation, dark matter, dark energy, and neutrino masses. We report on MITEoR, a pathfinder low-frequency radio interferometer whose goal is to test technologies that greatly reduce the cost of such 3D mapping for a given sensitivity. MITEoR accomplishes this by using massive baseline redundancy both to enable automated precision calibration and to cut the correlator cost scaling from N^2 to NlogN, where N is the number of antennas. The success of MITEoR with its 64 dual-polarization elements bodes well for the more ambitious HERA project, which would incorporate many identical or similar technologies using an order of magnitude more antennas, each with dramatically larger collecting area.Comment: To be published in proceedings of 2013 IEEE International Symposium on Phased Array Systems & Technolog