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Historically, architectural research into the resilience and the potential for adaptation tended to put more focus on the physical aspects of the built environment at the expense of the social and cultural values which are embedded in the everyday making of built form and space. This research is interested in accentuating the social and cultural context much more than the mere physical element of the built form. It sets out to explore approaches to resilience and adaptation in the global South through the use of local building materials, and to rethink the idea of what is local in a given context. It is interested in examining how collaborative construction and architectural enterprises in the global South address the existing levels of indigenous knowledge and local skills in order to cope with adverse climatic conditions and poverty. The research investigates the work of community-driven initiatives involved in small-scale adaptation projects primarily through the lens of a construction project for a small community building in rural Ghana. Secondary case studies include initiatives, projects and organisations located in four different countries namely Pakistan, Swaziland, Algeria, and Zimbabwe. Moreover it focuses on themes such as the very central relationship between architectural education and practice on the one hand, and building materials, approaches to resilience and adaptation through the use of local materials, ethnographic approaches to research and design, training and collaborations on the other. The research uses a methodology, which is based on qualitative data collection, and includes a mixture of creative methods such as, participant observation and participation, semi-structured and unstructured audio-recorded interviews, informal conversations as well as the use of social media such as Facebook as being the second ‘virtual site’. It is argued that the syncretism of multi-site ethnographic approach and participatory design methods enables solutions, which can contribute to longer-term sustainable adaptation in this context. Drawing on its main research site and primary fieldwork in Abetenim, a remote village in southern Ghana, and the researcher’s role as a community architect and participant in the Earth Architecture construction workshop through a non-profit organisation (NGO), it discusses how the use of ethnography as part of architectural praxis facilitates the holistic understanding of the local context and informs the design process. It feeds off Anthropological research as a typical methodological approach through participant observation and participation, in order to rethink architecture from a broader cultural perspective. This allows the author to critique local situations and frame questions, which directly inform the design process in this context. Simultaneously it reflects on the need to integrate social, physical and cultural change in order to effect broader changes in the community. Hence, the research sets out to explore the compromise between the global and local perspectives. It investigates how an NGO’s prescriptive narrative of using local materials like earth, in the construction of new projects may be adapted and translated into the local reality, and looks at the process of the ‘on the ground’ experience through direct involvement in community architecture and building. It considers the relationship between culture and nature; the intimate relationship between nature and architecture and how this challenges architectural education in the West. Finally, the process of selecting building materials addresses distinct layers of collaboration among the local community, the members of the NGO, and local institutions. Thus the value of collaboration with local actors within research in the global South is emphasized, as the very praxis of collaboration is employed as a method in the implementation of such projects.

This study commenced with an investigation into a total synthesis of the antibiotic platensimycin 1.1 in chapter one. The key reaction for accessing the synthetically challenging fused ring system involved a meta-photocycloaddition reaction and the chapter one describes our attempts at the syntheses of the key substrates. Much of the chemistry was unsuccessful however we were able to attempt a key photochemical reaction however the desired compound was not obtained. On the basis of these outcomes we refocused our efforts towards the syntheses of kainic acid 2.1 and allokaininc acid 2.2 in chapter two. We aimed to devise a stereoselective synthesis of both kainic acid 2.1 and the allokainic acid 2.2, utilising the diastereofacial selectivity inherent in the previously synthesised oxazolidinone 2.240. Oxazolidinone 2.240 was subjected to a stereo and regiocontrolled 1,3-dipolar cycloaddition to give isoxazole 2.279. Reduction, followed by dehydration of isoxazole 2.279 gave the enone 2.287 which forms the Michael acceptor in the key Michael addition reaction. The 1,4 addition on enone 2.287, gave the two diastereomers 2.328 and 2.329 which underwent sequential Wittig reaction, and Krapcho decarboxylation to give the formal synthesis of allokainic acid 2.2 and epikainate 2.346 respectively. An investigation was also conducted with the aim of altering the stereochemistry of the dicarboxylic group in compound 2.329, in order to produce a novel route to the stereoselective synthesis of kainic acid 2.1.

Levees are earthen structures constructed to mitigate flooding in low-lying areas. Although levee systems can reduce flood risks, they cannot completely eliminate them. Failures within flood control systems due to inadequate maintenance or strong water currents can lead to significant property damage and catastrophic loss of life, as was seen during Hurricane Katrina. Consequently, regular inspections are essential to identify and address any issues with the levees promptly. However, current inspection methods rely on manual techniques that are time-consuming, labor-intensive, and prone to human error. Therefore, this study proposes using deep learning models for more efficient and frequent assessment of levee systems. The research suggests employing deep-learning architectures to detect three primary deficiencies: cracks, sand boils, and seepages using a semantic segmentation approach. The proposed models focus on lightweight designs, incorporating transfer learning techniques and enhancing feature representation to improve the accuracy and efficiency of fault segmentation using images within flood control systems. Moreover, these models are evaluated with real-world data specific to levees, allowing for their effectiveness in handling various faults exhibiting variations and complexity. As a result, the research enables pixel-level fault detection for AI-based inspection of levee systems, providing valuable support to existing assessment procedures. Furthermore, the study's findings have the potential to extend beyond levee inspection, with implications for broader applications of deep learning in semantic segmentation for real-world scenarios. Keywords: Levee; Faults; Deep learning; Images; Detection; Segmentation

The pecan nut is an important nut fruit in the USA economy, contributing more than $3.5 billion to the country's economy. The optimal time of different orchard activities like irrigation management, pesticide spray, and harvest time is difficult to identify. The growth and development of nuts as a function of heat units can be modeled to optimally time orchard activities according to a biological calendar. Our objective was to compare various nonlinear growth models and determine which best fit pecan nut development (i.e., embryo, shell, and shuck). Gompertz and Logistic functions were fitted to the pecan data. The models were fitted separately for each environment (year x location) using data collected at 4 locations in 2019 and 1 in 2020. For 2019, each location resulted in shuck and embryo development having the best fit using the Gompertz model, while the shell development was best using a logistic model. In contrast, in 2019 and 2020 with one location, Gompertz best fits embryo and logistic for shell and shuck development. This information will aid in the development of online producer tools. Pecans are reported to have alternate or masting phenomena because of irregular nut production, which is believed to be caused by carbohydrate depletion. The nonstructural carbohydrate concentration of wood and bark was determined throughout the growing season in 2019 and 2020. We found the current season shoot supports growth of the nut, while the one- year old shoot stores reserves each following year. Our result showed that there is difference in carbohydrate concentration between two years. Low starch concentration throughout the thousands of samples tested implies there could be more than two years of low production and indicate that pecan might have a masting phenomenon. Additional research was carried out to assess pecan response to varying irrigation levels. Nut size was influenced by water stress, but this response varied with cultivar. For shell hardening, the research objective was to determine how shell hardening restricts the weevil infection. The result showed that the weevil oviposits mainly in the suture where the hardness is less. Furthermore, there was a difference in the hardness of the shell among the variety. This information will be helpful in or breeder to increase tolerance or avoidance of the pest.

Semiconductor quantum dots are of remarkable interest as a versatile light-harvesting material in solar cells and a lot of other applications. Quantum dots are very tiny molecules and its efficient use in photovoltaics requires a considerable separation between holes and excited electrons so that they do not recombine to produce photons again. The research contained in this thesis investigates the use of Carbon-based quantum dots - Carbon NanoDots(CNDs) or Nanodiamonds - for charge separation to facilitate its use in photovoltaics. The electronic and optical properties of quantum dots are primarily dependent on their size due to quantum confinement. However, their properties can also be tuned by using other means. The introduction of organic ligands on the surface is one of thosemeans. Our research primarily investigates the effect of functionalizing the CND surface with 4-ethynyl-N,N-bis(4-methoxyphenyl)aniline (MeOTPA) on its electronic and optical properties.All the calculations for electronic properties are done under the theoretical framework of Density Function Theory(DFT) using a package called Spanish Initiative for Electronic Simulations with Thousands of Atoms(SIETA). The optical properties are calculated using a Time-Dependant DFT package called Fast Absorption Simulation using TD-DFT(FAST). The results suggest that charge separation is possible in CNDs. The dependence of charge separation on the size of the quantum dot is also seen. The use of ligand also seems to sensitize CND to visible light.

Adhesive bonding has become an ideal joining method in structural applications which can join similar or dissimilar materials. This is a common application in aircraft, automobiles, and naval applications, in which a gradual replacement process is ideal to design the new composite structures. Epoxy adhesive joints offer excellent adhesion properties, good corrosion resistance, high strength to weight ratio, requiring relatively low cure temperatures. Despite these advantages, epoxy resins inherently have low fracture toughness due to high cross-linking density, which limits their general usage in structural applications. In the view of structural applications, the development of high strength epoxy adhesive joints is essential to enhance their structural integrity. In this research, high-performance epoxy composite adhesive materials are developed by adding different types of carbon nanomaterials and triblock copolymers (BCPs). A Diglycidyl ether of Bisphenol-A (DGEBA) based epoxy with was used an adhesive. The bulk properties such as Tensile strength, Young's modulus and fracture toughness (GIc) are 69 MPa, 2.8 GPa and 314 J/m2 respectively. Two different carbon nanomaterials such as carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) were incorporated to enhance the strength and stiffness of the epoxy adhesives. Ultrasonication ozonolysis (USO) treatment was performed on CNT and GNPs to improve the interfacial adhesion between the CNTs and epoxy matrix and to enhance the performance of the epoxy adhesive joints. Two different types of BCPs such as methyl methacrylate-butyl methacrylate-methyl methacrylate (MAM) and styrene -butadiene-methylmethacrylate (SBM) were employed to toughen the epoxy matrix. The effect of different weight fractions of untreated and functionalized carbon nanomaterials, BCP addition and the hybrid effect of carbon nanomaterials and BCP addition on the shear strength of the adhesive joints was studied by conducting single lapix shear tests. The bond thickness of 0.15 mm was maintained to achieve maximum joint performance. The lap shear strength of the adhesive joints was found to have increased with the incorporation of carbon nanomaterials, up to certain weight fraction. The functionalization of carbon nanomaterials showed further improvement in the lap shear strength as compared to the untreated nanomaterials. On the other hand, the addition of the BCPs leads to a significant increase in the lap shear strength compared to the pure epoxy and the carbon-reinforced epoxy joints. Particularly, the SBM copolymer showed a significant increase over the MAM copolymer, indicating the sensitivity of the BCP chemistry and the relative effect of the different nanophase morphologies and the associated cavitation mechanisms that contribute to the increased epoxy toughening. The lap shear strength was further increased with the addition of carbon nanomaterials in the BCP/epoxy adhesives, suggesting that the combination of carbon nanomaterials and BCP interact favourably to enhance the shear strength of the adhesive joints. The mechanical and fracture behaviour of the developed epoxy composite adhesives were systematically evaluated by bonding thick aluminium adherends using standard test methods such as double lap shear joint, tensile butt joint, long crack extension tests to observe the effect of co-addition of carbon nanomaterials and BCP under various loading conditions. The results showed that the hybrid composite adhesive joints exhibited a significant increase in joint strength and the fracture toughness with the balanced stiffness compared to that of the unmodified epoxy. The fracture surfaces of the adhesive joints were investigated using FEG-SEM to discover the mechanisms of the increase in the mechanical performance and fracture resistance of the developed epoxy composite adhesives. Fracture analysis revealed that the nanoadditives acted synergistically to increase fracture ductility which contributed to increase the strength and fracture toughness. Rheological studies were carried out to observe the effect of the addition of carbon nanomaterials and the BCPs on the viscosity of the epoxy and to understand thex processability of the developed epoxy mixtures before the addition of hardener. The molecular interactions between the functionalized carbon nanomaterials, BCP and the epoxy matrix of the developed epoxy composite adhesives were analysed in detail by using Fourier transform infrared spectroscopy. The influence of the addition of carbon nanomaterials and BCP additions on the thermal stability and electrical conductivity of epoxy composite adhesives were also studied. The glass transition and decomposition temperatures of the developed epoxy adhesives were found to be relatively unaffected. The electrical conductivity of the developed epoxy adhesive joints was increased with the addition of CNTs, which is four orders of magnitude higher compared with the unmodified epoxy and BCP/EP joints

Transposable Elements (TEs) or jumping genes are the DNA sequences that have an intrinsic capability to move within a host genome from one genomic location to another. Studies show that the presence of a TE within or adjacent to a functional gene may alter its expression. TEs can also cause an increase in the rate of mutation and can even promote gross genetic arrangements. Thus, the proper classification of the identified jumping genes is important to understand their genetic and evolutionary effects. While computational methods have been developed that perform either binary classification or multi-label classification of TEs, few studies have focused on their hierarchical classification. The existing methods have limited accuracy in classifying TEs. In this study, we examine the performance of a variety of machine learning (ML) methods and propose a robust augmented Stacking-based ML method, ClassifyTE, for the hierarchical classification of TEs with high accuracy.

Websites are the most convenient way to present and disseminate information to the maximum number of people in the world. The web browsers are the means to render the information on web page, the basic building blocks of a website, and web programming is the basic structure (architecture) of each web page.The thesis on "Web Design, Development and Security" is a complete analysis of website design and development. Web sites should be able to present abundant information to a visitor in well organized manner. In addition, there must be a reliable transfer of secure information between server and client. There exist other major factors such as user friendliness, layout, simplicity, ease of rendering in the browser and so on that are closely related with the quality of website. This thesis will elaborate on a number of issues that are related with web design and development. These principles will be illustrated and demonstrated in the design of some websites that I have designed so far.

Many real-world problems could be formulated in a way to fit the necessary form for discrete optimization. Discrete optimization problems can be solved by numerous different techniques that have developed over time. Some of the techniques provide optimal solution(s) to the problem and some of them give "good enough" solution(s). The fundamental reason for developing techniques capable of producing solutions that are not necessarily optimal is the fact that many discrete optimization problems are NP-complete. Metaheuristic algorithms are a common name for a set of general-purpose techniques developed to provide solution(s) to the problems associated with discrete optimization. Mostly the techniques are based on natural metaphors. Discrete optimization could be applied to countless problems in transportation engineering. Recently, researchers started studying the behavior of social insects (ants) in an attempt to use the swarm intelligence concept to develop artificial systems with the ability to search a problem's solution space in a way that is similar to the foraging search by a colony of social insects. The development of artificial systems does not entail the complete imitation of natural systems, but explores them in search of ideas for modeling. This research is partially devoted to the development of a new system based on the foraging behavior of bee colonies — Bee System. The Bee System was tested through many instances of the Traveling Salesman Problem. Many transportation-engineering problems, besides being of combinatorial nature, are characterized by uncertainty. In order to address these problems, the second part of the research is devoted to development of the algorithms that combine the existing results in the area of swarm intelligence (The Ant System) and approximate reasoning. The proposed approach — Fuzzy Ant System is tested on the following two examples: Stochastic Vehicle Routing Problem and Schedule Synchronization in Public Transit.