A sermon, preached in Boston, July 23, 1812, the day of the publick fast, appointed by the Executive of the Commonwealth of Massachusetts, in consequence of the declaration of war against Great Britain

Published at the request of the hearers Printed by Greenough and Stebbins

A sermon, preached in Hingham and Quincy, 20th August 1812, the day of the national fast, on account of the war with Great Britain

Printed by Joshua Belcher

The Salmon Algorithm - A New Population Based Search Metaheuristic

This thesis introduces the Salmon Algorithm, a search meta-heuristic which can be used for a variety of combinatorial optimization problems. This algorithm is loosely based on the path finding behaviour of salmon swimming upstream to spawn. There are a number of tunable parameters in the algorithm, so experiments were conducted to find the optimum parameter settings for different search spaces. The algorithm was tested on one instance of the Traveling Salesman Problem and found to have superior performance to an Ant Colony Algorithm and a Genetic Algorithm. It was then tested on three coding theory problems - optimal edit codes, optimal Hamming distance codes, and optimal covering codes. The algorithm produced improvements on the best known values for five of six of the test cases using edit codes. It matched the best known results on four out of seven of the Hamming codes as well as three out of three of the covering codes. The results suggest the Salmon Algorithm is competitive with established guided random search techniques, and may be superior in some search spaces.

A Multi-Objective Genetic Algorithm with Side Effect Machines for Motif Discovery

Understanding the machinery of gene regulation to control gene expression has been one of the main focuses of bioinformaticians for years. We use a multi-objective genetic algorithm to evolve a specialized version of side effect machines for degenerate motif discovery. We compare some suggested objectives for the motifs they find, test different multi-objective scoring schemes and probabilistic models for the background sequence models and report our results on a synthetic dataset and some biological benchmarking suites. We conclude with a comparison of our algorithm with some widely used motif discovery algorithms in the literature and suggest future directions for research in this area.

THE INFLUENCE OF LENGTH CHANGE SPEED AND DIRECTION ON DYNAMIC FUNCTION POTENTIATION IN FAST MOUSE MUSCLE

The purpose of this study was to test the hypothesis that the potentiation of dynamic function was dependent upon both length change speed and direction. Mouse EDL was cycled in vitro (250 C) about optimal length (Lo) with constant peak strain (± 2.5% Lo) at 1.5,3.3 and 6.9 Hz before and after a conditioning stimulus. A single pulse was applied during shortening or lengthening and peak dynamic (concentric or eccentric) forces were assessed at Lo. Stimulation increased peak concentric force at all frequencies (range: 19±1 to 30 ± 2%) but this increase was proportional to shortening speed, as were the related changes to concentric work/power (range: -15 ± 1 to 39 ± 1 %). In contrast, stimulation did not increase eccentric force, work or power at any frequency. Thus, results reveal a unique hysteresis like effect for the potentiation of dynamic output wherein concentric and eccentric forces increase and decrease, respectively, with work cycle frequency.

New Contig Creation Algorithm for the de novo DNA Assembly Problem

DNA assembly is among the most fundamental and difficult problems in bioinformatics. Near optimal assembly solutions are available for bacterial and small genomes, however assembling large and complex genomes especially the human genome using Next-Generation-Sequencing (NGS) technologies is shown to be very difficult because of the highly repetitive and complex nature of the human genome, short read lengths, uneven data coverage and tools that are not specifically built for human genomes. Moreover, many algorithms are not even scalable to human genome datasets containing hundreds of millions of short reads. The DNA assembly problem is usually divided into several subproblems including DNA data error detection and correction, contig creation, scaffolding and contigs orientation; each can be seen as a distinct research area. This thesis specifically focuses on creating contigs from the short reads and combining them with outputs from other tools in order to obtain better results. Three different assemblers including SOAPdenovo [Li09], Velvet [ZB08] and Meraculous [CHS+11] are selected for comparative purposes in this thesis. Obtained results show that this thesis’ work produces comparable results to other assemblers and combining our contigs to outputs from other tools, produces the best results outperforming all other investigated assemblers.

A Study of Ordered Gene Problems Featuring DNA Error Correction and DNA Fragment Assembly with a Variety of Heuristics, Genetic Algorithm Variations, and Dynamic Representations

Ordered gene problems are a very common classification of optimization problems. Because of their popularity countless algorithms have been developed in an attempt to find high quality solutions to the problems. It is also common to see many different types of problems reduced to ordered gene style problems as there are many popular heuristics and metaheuristics for them due to their popularity. Multiple ordered gene problems are studied, namely, the travelling salesman problem, bin packing problem, and graph colouring problem. In addition, two bioinformatics problems not traditionally seen as ordered gene problems are studied: DNA error correction and DNA fragment assembly. These problems are studied with multiple variations and combinations of heuristics and metaheuristics with two distinct types or representations. The majority of the algorithms are built around the Recentering- Restarting Genetic Algorithm. The algorithm variations were successful on all problems studied, and particularly for the two bioinformatics problems. For DNA Error Correction multiple cases were found with 100% of the codes being corrected. The algorithm variations were also able to beat all other state-of-the-art DNA Fragment Assemblers on 13 out of 16 benchmark problem instances.

Disease-Gene Association Using a Genetic Algorithm

Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

The Fast Regulation of Photosynthesis in Diatoms: an inquiry into the physiological and physical origins of non-photochemical chlorophyll fluorescence quenching.

Diatoms are renowned for their robust ability to perform NPQ (Non-Photochemical Quenching of chlorophyll fluorescence) as a dissipative response to heightened light stress on photosystem II, plausibly explaining their dominance over other algal groups in turbulent light environs. Their NPQ mechanism has been principally attributed to a xanthophyll cycle involving the lumenal pH regulated reversible de-epoxidation of diadinoxanthin. The principal goal of this dissertation is to reveal the physiological and physical origins and consequences of the NPQ response in diatoms during short-term transitions to excessive irradiation. The investigation involves diatom species from different originating light environs to highlight the diversity of diatom NPQ and to facilitate the detection of core mechanisms common among the diatoms as a group. A chiefly spectroscopic approach was used to investigate NPQ in diatom cells. Prime methodologies include: the real time monitoring of PSII excitation and de-excitation pathways via PAM fluorometry and pigment interconversion via transient absorbance measurements, the collection of cryogenic absorbance spectra to measure pigment energy levels, and the collection of cryogenic fluorescence spectra and room temperature picosecond time resolved fluorescence decay spectra to study excitation energy transfer and dissipation. Chemical inhibitors that target the trans-thylakoid pH gradient, the enzyme responsible for diadinoxanthin de-epoxidation, and photosynthetic electron flow were additionally used to experimentally manipulate the NPQ response. Multifaceted analyses of the NPQ responses from two previously un-photosynthetically characterised species, Nitzschia curvilineata and Navicula sp., were used to identify an excitation pressure relief ‘strategy’ for each species. Three key areas of NPQ were examined: (i) the NPQ activation/deactivation processes, (ii) how NPQ affects the collection, dissipation, and usage of absorbed light energy, and (iii) the interdependence of NPQ and photosynthetic electron flow. It was found that Nitzschia cells regulate excitation pressure via performing a high amplitude, reversible antenna based quenching which is dependent on the de-epoxidation of diadinoxanthin. In Navicula cells excitation pressure could be effectively regulated solely within the PSII reaction centre, whilst antenna based, diadinoxanthin de-epoxidation dependent quenching was implicated to be used as a supplemental, long-lasting source of excitation energy dissipation. These strategies for excitation balance were discussed in the context of resource partitioning under these species’ originating light climates. A more detailed investigation of the NPQ response in Nitzschia was used to develop a comprehensive model describing the mechanism for antenna centred non-photochemical quenching in this species. The experimental evidence was strongly supportive of a mechanism whereby: an acidic lumen triggers the diadinoxanthin de-epoxidation and protonation mediated aggregation of light harvesting complexes leading to the formation of quencher chlorophyll a-chlorophyll a dimers with short-lived excited states; quenching relaxes when a rise in lumen pH triggers the dispersal of light harvesting complex aggregates via deprotonation events and the input of diadinoxanthin. This model may also be applicable for describing antenna based NPQ in other diatom species.

Using PageRank Algorithm in Analyzing Dictionary Graphs and PageRank in Dynamic Graphs

In this thesis we are going to analyze the dictionary graphs and some other kinds of graphs using the PagerRank algorithm. We calculated the correlation between the degree and PageRank of all nodes for a graph obtained from Merriam-Webster dictionary, a French dictionary and WordNet hypernym and synonym dictionaries. Our conclusion was that PageRank can be a good tool to compare the quality of dictionaries. We studied some artificial social and random graphs. We found that when we omitted some random nodes from each of the graphs, we have not noticed any significant changes in the ranking of the nodes according to their PageRank. We also discovered that some social graphs selected for our study were less resistant to the changes of PageRank.

Myosin Regulatory Light Chain Phosphorylation and Its Effect on the Contractile Economy of Mouse Fast Muscle

Activated by elevations in myoplasmic calcium concentration, myosin light chain kinase (skMLCK) phosphorylates the regulatory light chains (RLCs) of fast muscle myosin. This covalent modification potentiates force production, but requires an investment of ATP. Our objective was to investigate the effect of RLC phosphorylation on the contractile economy (mechanical output:metabolic input) of fast twitch skeletal muscle. Extensor digitorum longus muscles isolated from Wildtype and skMLCK-/- mice mounted in vitro (25°C) were subjected to repetitive low-frequency stimulation (10Hz,15s) known to cause activation of skMLCK, and staircase potentiation of force. With a 3-fold increase in RLC phosphate content, Wildtype generated 44% more force than skMLCK-/- muscles over the stimulation period (P = .002), without an accompanied increase in energy cost (P = .449). Overall, the contractile economy of Wildtype muscles, with an intact RLC phosphorylation mechanism, was 73% greater than skMLCK /- muscles (P = .043), demonstrating an important physiological function of skMLCK during repetitive contractile activity.

Letter to S.D. Woodruff in order to give Mr. Woodruff and idea of how fast the interest payments are made to the company

Letter (incomplete) to S.D. Woodruff in order to give Mr. Woodruff an idea of how fast the interest payments are made to the company. The letter is slightly water damaged. The text is affected, but legible. The signature is missing. Feb. 8, 1883.