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A multi-vehicle system is composed of interconnected vehicles coordinated to complete a certain task. When controlling such systems, the aim is to obtain a coordinated behaviour through local interactions among vehicles and the surrounding environment.One motivating application is the monitoring of algal blooms; this phenomenon occurs frequently and has a substantial negative effect on the environment such as large-scale mortality of fish. In this thesis, we investigate control of multiple unmanned surface vehicles (USVs) for mobile target circumnavigation and tracking, where the target can be an algal bloom area.A protocol based on local measurements provided by the vehicles is developed to estimate the target's location and shape.Then a control strategy is derived that brings the vehicle system to the target while forming a regular polygon. More precisely, we first consider the problem of tracking a mobile target while circumnavigating it with multiple USVs. A satellite image indicates the initial location of the target, which is supposed to have an irregular dynamic shape well approximated by a circle with moving center and varying radius. Each USV is capable of measuring its distance to the boundary of the target and to its center. We design an adaptive protocol to estimate the circle's parameters based on the local measurements. A control protocol then brings the vehicles towards the target boundary as well as spreads them equidistantly along the boundary. The protocols are proved to converge to the desired state. Simulated examples illustrate the performance of the closed-loop system. Secondly, we assume that the vehicles can only measure the distance to the boundary of the target and not to its center. We propose a decentralised least-squares method for target estimation suitable for circular targets. Convergence proofs are given for also this case. An example using simulated algal bloom data shows that the method works well under realistic settings. Finally, we investigate how to extend our protocols to a quite general irregular mobile target. In this case, each vehicle communicates only with its two nearest neighbors and estimates the curvature of the target boundary using their collective measurements. We validate the performance of the protocol under various settings and target shapes through a numerical study. / Multi-fordon-styrsystem består av sammankopplade fordon som koordinerar för att slutföra en given uppgift. I sådana styrsystem är målet att få ett koordinerat beteende via lokala interaktioner mellan fordonen och miljön de vistas i. Ett motiverande exempel är övervakning av algblomning, ett fenomen som inträffar frekvent och har omfattande negativa effekter såsom kraftig mortalitet hos fiskar. I denna rapport undersöker vi hur Unmanned Surface Vehicles (USVs) kan styras för att cirkulera och spåra ett givet mobilt objekt, till exempel en yta med algblomning. Ett protokoll är utvecklat för att estimera det mobila objektets position och form, baserat på lokala mätningar utförda av fordonen, samt en reglerstrategi tas fram som styr systemet med fordon till objektet samtidigt som de formar en regelbunden polygon.   Mer precist undersöker vi först problemet att samtidigt spåra och cirkulera ett mobilt objekt med USVs. En satellitbild indikerar startpositionen av objektet, antaget att ha en irreguljär tidsvarierande form som kan approximeras väl av en cirkel med tidsberoende center och radie. Varje USV kan mäta avståndet till objektets rand och center. Vi designar ett adaptivt protokoll för att estimera cirkelns parametrar baserat på lokala mätningar. Ett reglerprotokoll styr sedan fordonen mot objektets rand samt sprider ut dem ekvidistant kring randen. Vi bevisar att protokollen konvergerar mot önskat tillstånd. Två simuleringar visar det slutna systemets prestanda.   Sedan antar vi att fordonen endast kan mäta avståndet till randen på objektet, men inte tills dess center. Vi tar fram en decentraliserad minstakvadratmetod för att estimera objektet, lämpligt för cirkulära objekt. Konvergens bevisas även i detta fall. Ett exempel med data från en simulerad algblomning visar att metoden fungerar bra under realistiska scenarion.   Slutligen undersöker vi hur protokollen kan vidareutvecklas för mobila objekt med tämligen generella irreguljära former. I detta fall antar vi att fordonen endast kan kommunicera med sina två närmaste grannar och estimera kurvan för objektets rand från deras samlade mätningar. Vi validerar protokollen via två simuleringar. / <p>QC 20200217</p>

Distinguishing 2,4-D and dicamba herbicide formulations in cotton and soybean tissue is challenging in regulation of crop injury from these herbicides. Additionally, stewardship of 2,4-D and dicamba technologies is important to maximize their longevity and efficacy. Research was conducted to (1) characterize cotton and soybean response to various formulations of 2,4-D or dicamba with or without glyphosate, (2) develop a method for classifying these formulations in crop tissue, and (3) optimize use of chloroacetamide herbicides in dicamba systems for mitigation of selection pressure on dicamba. Formulations evaluated include dicamba diglycolamine (DGA), dimethylamine (DMA), N,N-Bis-(3-aminopropyl) methylamine (BAPMA), and DGA plus potassium acetate (KAc); and 2,4-D DMA, acid, isooctyl ester (ESTER), and choline. Weed management by the chloroacetamides s-metolachlor and acetochlor was evaluated with applications preemergence (PRE), early postemergence (EP), late postemergence (LP), PRE followed by (fb) EP, PRE fb LP, and EP fb LP. Cotton and soybean response differed by 2,4-D and dicamba formulation, and glyphosate presence. Cotton yield was reduced by 200 to 500 kg ha-1 following exposure to 2,4-D choline or DMA relative to acid or ESTER. Glyphosate presence led to a reduction in cotton and soybean yield of 377 and 572 kg ha-1, respectively. Exposure to dicamba DMA resulted in a 263 kg ha-1 reduction in soybean yield relative to dicamba DGA, and glyphosate presence reduced yield by 439 and 246 kg ha-1 in cotton and soybeans, respectively. Chemometric analyses generated models capable of up to 85% accuracy in identifying dicamba formulation in cotton and soybean tissue, and up to 80% accuracy in identifying 2,4-D formulation. Split chloroacetamide applications improved cotton yield up to 60%, reduced weed densities up to 90%, and improved control up to 56% relative to single applications. Cotton height was reduced up to 23% if a single chloroacetamide application was made. Soybean yield was maximized following any chloroacetamide application timing except PRE alone, and weed control was reduced up to 31% following single chloroacetamide application relative to split applications. These results will aid regulatory bodies in managing use of new weed control technologies and will assist producers in stewarding these new technologies.

Off-target herbicide movement onto rice is an annual problem in rice-producing areas within Mississippi. In Mississippi, rice is routinely drill‐seeded in April to early May. Because these dates often coincide with preplant and/or preemergence (PRE) herbicide applications to corn (Zea mays L.), cotton (Gossypium hirsutum L.), and soybean [Glycine max (L.) Merr.], drift onto neighboring rice crops is likely to occur. Although the effects of off-target movement of paraquat on rice may not be visibly apparent, the potential effect on rough rice yield could be detrimental. Field research was conducted at the Delta Research and Extension Center in Stoneville, MS, in 2019, 2020, and 2021 to characterize rice response to exposure to a range of sub-lethal concentrations of paraquat during the vegetative and reproductive growth phases. Other field experiments characterized rice response to exposure to a sub-lethal concentration of paraquat at different stages of reproductive growth. A final field experiment evaluated rice response and barnyardgrass control with labeled herbicides after exposure to a sub-lethal concentration of paraquat.

Robotic technology is advancing out of the laboratory and into the everyday world. This world is less ordered than the laboratory and requires an increased ability to identify, target, and track objects of importance. The Bayes filter is the ideal algorithm for tracking a single target and there exists a significant body of work detailing tractable approximations of it with the notable examples of the Kalman and Extended Kalman filter. Multiple target tracking also relies on a similar principle and the Kalman and Extended Kalman filter have multi-target implementations as well. Other method include the PHD filter and Multiple Hypothesis tracker. One issue is that these methods were formulated to only track one classification of target. With the increased need for robust perception, there exists a need to develop a target tracking algorithm that is capable of identifying and tracking targets of multiple classifications. This thesis examines two of these methods: the Probability Hypothesis Density (PHD) filter and the Multiple Hypothesis Tracker (MHT). A Matlab-based simulation of an office floor plan is developed and a simulation UGV equipped with a camera is set the task of navigating the floor plan and identifying targets. Results of these experiments indicated that both methods are mathematically capable of achieving this. However, there was a significant reliance on post-processing to verify the performance of each algorithm and filter out noisy sensor inputs indicating that specific multi-target multi-class implementations of each algorithm should be implemented with a detailed and more accurate sensor model. / Mechanical Engineering

Kaiso is a novel member of the BTB/POZ (Broad complex, Tramtrak, Bric a brac,/Pox virus and zinc finger) zinc finger family of transcriptional regulators that have many roles in development and tumorigenesis. Kaiso was first identified as a binding partner for p 120ctn, an Armadillo catenin with roles in cell adhesion and stabilization of cadherins at the cell membrane. Kaiso is both an activator and repressor of gene transcription and interacts with two distinct types of DNA sequence; a consensus Kaiso binding site (KBS) TCCTGCNA and methylated CpG dinucleotide pairs (i.e. CpGCpG). Thus far p120's nuclear role is to inhibit Kaiso-mediated regulation of its target genes. Some of the Kaiso target genes identified to date include, matrilysin, rapsyn, and MTA2. The Kaiso homologue in Xenopus laevis (frog) has also been shown to regulate the cell cycle regulator CCND 1. Sequence analysis of the human CCND1 promoter revealed several potential Kaiso binding elements including both KBS and methylatable CpGs. My research demonstrated that Kaiso binds to the CCND1 promoter in vitro and in vivo to both KBS-specific and CpG-specific regions. Furthermore, I determined that Kaiso may act as either a repressor or activator of the human CCND 1 gene depending on the cellular environment. Altogether these data support my hypothesis that Kaiso is a regulator of the CCND1 gene. Future studies looking at the significance of KBS versus CpG-binding on Kaiso's mechanism of regulation are required to determine the significance of this regulation. Furthermore, studies examining the cell cycle-dependent changes in Kaiso levels may reveal how alterations in Kaiso expression affect Kaiso target genes including CCND1. / Thesis / Master of Science (MSc)

<p> Identifying motifs that are "close" to one or more substrings in each sequence in a given set of sequences and hence characterize that set is an important problem in computational biology. The target motif identification problem requires motifs that characterize one given set of sequences but are far from every substring in another given set of sequences. This problem is N P-hard and hence is unlikely to have efficient optimal solution algorithms. In this thesis, we propose a set of modifications to one of the most popular stochastic heuristics for finding motifs, Gibbs Sampling [LAB+93], which allow this heuristic to detect target motifs. We also present the results of four simulation studies and tests on real protein datasets which suggest that these modified heuristics are very good at (and are even, in some cases, necessary for) detecting target motifs.</p> / Thesis / Master of Science (MSc)