Fuelwood collection and consumption: a case study in Lupeta Tanzania

Fuelwood is a major resource in rural areas. Fuelwood collection and consumption habits were monitored in Lupeta, Tanzania through household interviews and fuelwood collection walks. Social dimensions, economic aspects of fuelwood, and alternative fuel sources were also examined. The study found that for all wealth classes, fuelwood is the primary source of fuel used within the village, with the middle and upper classes occasionally supplementing fuelwood with charcoal. Women collect and consume fuelwood for cooking. The majority of women (69%) prefer to use charcoal because fuelwood collection is labor intensive and time consuming. While the use of charcoal would provide more time for other required household activities, local economic constraints inhibit their adoption. The fuel shift from biomass fuels to transition fuels is happening slowly in Lupeta from fuelwood to charcoal. As fuelwood becomes scarcer, improved methods will need to be adopted or the fuel source will change.

Molecular interaction between perthiolated [beta]-cyclodextrin (CD) and the guests molecules adamantaneacetic acid (AD) and ferroceneacetic acid (FC); and the effect of the interaction on the electron transition of CD anchored particles

The molecular interactions between the host molecule, perthiolated beta-cyclodextrin (CD), and the guest molecules, adamantaneacetic acid (AD) and ferroceneacetic acid (FC), have been inestigated theoretically in both the gas and aqueous phases. The major computations have been carried out at the theoretical levels, RHF/6-31G and B3LYP/6- 31G. MP2 electronic energies were also computed based at the geometries optimized by both the RHF and B3LYP methods in the gas phase to establish a better estimate of the correlation effect. The solvent phase computations were completed at the RHF/6-31G and B3LYP/6-31G levels using the PCM model. The most stable structures optimized in gas phase by both the RHF and B3LYP methods were used for the computations in solution. A method to systematically manipulate the relative position and orientation between the interacting molecules is proposed. In the gas phase, six trials with different host-guest relative positions and orientations were completed successfully with the B3LYP method for both the CD-AD and CD-FC complexes. Only four trials were completed with RHF method. In the gas phase, the best results from the RHF method gives for the association Gibbs free energy (ΔG°) values equal to -32.21kj/mol for CD-AD and -25.73kj/mol for CD-FC. And the best results from the B3LYP method have ΔG° equal to -47.57kj/mol for CD-AD and -41.09kj/mol for CD-FC. The MP2 correction significantly lowers ΔG° based on the geometries from both methods. For the RHF structure, the MP2 computations lowered ΔG° to -60.64kj/mol for CD-AD and -54.10 for CD-FC. For the structure from the B3LYP method, it was reduced to -59.87 kj/mol for CD-AD and -54.84 kj/mol for CDFC. The RHF solvent phase calculations yielded following results: ΔG°(aq) equals 107.2kj/mol for CD-AD and 111.4kj/mol for CD-FC. Compared with the results from the RHF method, the B3LYP method provided clearly better solvent phase results with ΔG° (aq) equal to 38.64kj/mol for CD-AD and 39.61kj/mol for CD-FC. These results qualitatively explain the experimental observations. However quantitatively they are in poor agreement with the experimental values available in the literature and those recently published by Liu et al. And the reason is believed to be omission of hydrophobic contribution to the association. Determining the global geometrical minima for these very large systems was very difficult and computationally time consuming, but after a very thorough search, these were identified. A relevant result of this search is that when the complexes, CD-AD and CD-FC, are formed, the AD and FC molecules are only partially embedded inside the CD cavity. The totally embedded complexes were found to have significantly higher energies. The semiempirical method, ZINDO, was employed to investigate the effect of complexation on the first electronic excitation of CD anchored to a metal nano-particle. The computational results revealed that after complexation to FC, the transition intensity declines to about 25% of the original value, and after complexation with AD, the intensity drops almost 50%. The tighter binding and transition intensity of CD-AD qualitatively agrees with the experimental result that the addition of AD to a solution of CD and FC restores the fluorescence of CD that was quenched by the addition of FC. A method to evaluate the “hydrophobic force” effect is proposed for future work.

DATA DRIVEN INTELLIGENT AGENT NETWORKS FOR ADAPTIVE MONITORING AND CONTROL

To analyze the characteristics and predict the dynamic behaviors of complex systems over time, comprehensive research to enable the development of systems that can intelligently adapt to the evolving conditions and infer new knowledge with algorithms that are not predesigned is crucially needed. This dissertation research studies the integration of the techniques and methodologies resulted from the fields of pattern recognition, intelligent agents, artificial immune systems, and distributed computing platforms, to create technologies that can more accurately describe and control the dynamics of real-world complex systems. The need for such technologies is emerging in manufacturing, transportation, hazard mitigation, weather and climate prediction, homeland security, and emergency response. Motivated by the ability of mobile agents to dynamically incorporate additional computational and control algorithms into executing applications, mobile agent technology is employed in this research for the adaptive sensing and monitoring in a wireless sensor network. Mobile agents are software components that can travel from one computing platform to another in a network and carry programs and data states that are needed for performing the assigned tasks. To support the generation, migration, communication, and management of mobile monitoring agents, an embeddable mobile agent system (Mobile-C) is integrated with sensor nodes. Mobile monitoring agents visit distributed sensor nodes, read real-time sensor data, and perform anomaly detection using the equipped pattern recognition algorithms. The optimal control of agents is achieved by mimicking the adaptive immune response and the application of multi-objective optimization algorithms. The mobile agent approach provides potential to reduce the communication load and energy consumption in monitoring networks. The major research work of this dissertation project includes: (1) studying effective feature extraction methods for time series measurement data; (2) investigating the impact of the feature extraction methods and dissimilarity measures on the performance of pattern recognition; (3) researching the effects of environmental factors on the performance of pattern recognition; (4) integrating an embeddable mobile agent system with wireless sensor nodes; (5) optimizing agent generation and distribution using artificial immune system concept and multi-objective algorithms; (6) applying mobile agent technology and pattern recognition algorithms for adaptive structural health monitoring and driving cycle pattern recognition; (7) developing a web-based monitoring network to enable the visualization and analysis of real-time sensor data remotely. Techniques and algorithms developed in this dissertation project will contribute to research advances in networked distributed systems operating under changing environments.