Photoassisted Synthesis of Complex Polyheterocycles via ESIPT-Driven Dearomative Intramolecular Cycloadditions

This research is focused on the development of novel photoassisted synthetic methodologies that provide straightforward access to complex and diverse libraries of polyheterocycles from modularly assembled precursors. All methods are based on the dearomative cycloadditions between two components: (i) o-azaxylylenes, generated by the excited-state intramolecular proton transfer, and (ii) tethered arene groups. We have demonstrated the synthetic utility of four new photoinduced processes that yield complex products amenable for post-photochemical modifications: [4+4] Cycloaddition of o-azaxylylenes to 1,3,4-oxadiazoles with subsequent dinitrogen extrusion. This reaction furnishes compounds outfitted with epoxide fragments, which undergo ring-openings with various nucleophiles; furthermore, the oxidized products rearrange into triazocanoindolinones under Schmidt reaction conditions. [4+2] Reaction between amino-o-azaxylylenes and tethered pyrroles. The primary pyrroline photoproducts are converted into stable polyheterocycles by 1,3-dipolar cycloaddition with tosyl azide and an intramolecular Friedel-Crafts reaction. Photodearomatization of benzenoid arenes via [2+4] reactions with o-azaxylylenes. This process transforms readily available benzene units into 1,3-cyclohexadienes, which are reactive in acid-catalyzed modifications and thermal [4+2] cycloadditions. Photocascade reaction involving [2+4] photocycloaddition of tethered anilines to o-azaxylylenes followed by secondary cyclization enabled by the oxalyl linker. This transformation permits strategic installation of specific functionalities into the photoproducts, with the purpose of further ring-forming modifications

Structure control of La/B multilayer systems by partial nitridation

This PhD thesis contains a selection of thin film research results on the structure control of La/B multilayer mirrors with nm- and sub nm-thick layers, used at normal and grazing incidence of XUV radiation. Topics investigated include an improvement of the optical layer contrast, the reflectivity at 6.x nm wavelength, and the thermal stability. The approaches presented deal with in situ growth studies, deposition control and high resolution X-ray analysis

Quantum spectroscopy of plasmonic nanostructures

We use frequency entangled photons, generated via spontaneous parametric down conversion, to measure the broadband spectral response of an array of gold nanoparticles exhibiting Fano-type plasmon resonance. Refractive index sensing of a liquid is performed by measuring the shift of the array resonance. This method is robust in excessively noisy conditions compared with conventional broadband transmission spectroscopy. Detection of a refractive index change is demonstrated with a noise level 70 times higher than the signal, which is shown to be inaccessible with the conventional transmission spectroscopy. Use of low photon fluxes makes this method suitable for measurements of photosensitive bio-samples and chemical substances.Comment: 11 pages, 5 figure

ANALYZING THE IMPACT OF HISTORICAL DATA LENGTH IN NON SEASONAL ARIMA MODELS FORECASTING

Different values of minimum data requirement for ARIMA models have been proposed. It also proposed to use as much data as they are available in formulating ARIMA models. This paper studied the impact of the size of the historical data on ARIMA models in forecasting accuracy. The study used 286 weekly records of amount of solid waste generated in Arusha City to formulate four ARIMA models using different data lengths or size. The first model, M1 used 30 observations, the second model, M2 used 60 observations, the third model M3 used 120 observations and the fourth model, M4 used 260 observations all of which are the most recent. A total of 26 observations were held out for validation. The precision in forecasting was tested using MAPE, RMSE and MAD.  The results indicated variation in precision. M3 performed best in one-week ahead and 9 – 12 weeks ahead while M4 did best in 2 – 8 weeks and also for 13 weeks  and above. M1 was the worst model in forecasting. Keywords: ARIMA models, MAPE, RMSE, MAD, Forecastin

Dividend Maximization Under a Set Ruin Probability Target in the Presence of Proportional and Excess-of-loss Reinsurance

We study dividend maximization with set ruin probability targets for an insurance company whose surplus is modelled by a diffusion perturbed classical risk process. The company is permitted to enter into proportional or excess-of-loss reinsurance arrangements. By applying stochastic control theory, we derive Volterra integral equations and solve numerically using block-by-block methods. In each of the models, we have established the optimal barrier to use for paying dividends provided the ruin probability does not exceed a predetermined target. Numerical examples involving the use of both light- and heavy-tailed distributions are given. The results show that ruin probability targets result in an improvement in the optimal barrier to be used for dividend payouts. This is the case for light- and heavy-tailed distributions and applies regardless of the risk model used

Estimation of Irrigation Water Demand in Rice Production Tanzania

The agriculture sector is one of the major users of water resource for irrigation activities. In Tanzania irrigation water demand for rice is still increasing due to the area being irrigated continues to expand while the amount of water for irrigation is decreasing. The purpose of this paper was to develop the demand function for estimation of irrigation water in rice production in Tanzania. The secondary data were collected from various sources such as the Ministry of Agriculture, Food Security and Cooperatives at Statistics Unit, and relevant basin authorities and zonal irrigation units. A demand function was estimated after carrying out the relevant statistical tests. The Breush and Pagan Lagrangian Multiplier Test were used to select whether to use the Pool or Panel Data approaches. The Panel model was verified to be more suitable than the Pool model. The fixed effect and random effect were compared in the Hausman’s specification test. The price elasticity of irrigation water demand and other elasticity were also estimated using Ordinary Least Squares facilitated by STATA 11. A panel data of 16 regions of Tanzania in the period of 2007 - 2012 were used. The estimated average water demand found to be 8000m3/ha whereas water productivity in rice cultivation found to be 0.3kg/m3. Keywords: Water demand function, Water productivity, Panel data, Rice, Irrigation wate

Time Series Forecasting of Solid Waste Generation in Arusha City - Tanzania

Statistical time series modeling is widely used in prediction and forecasting studies. This study intends to analyze, compare and select the best time series model for forecasting amount of solid waste generation for the next years in Arusha city - Tanzania among ARMA/ARIMA and Exponential Smoothing models. The past data used are monthly amount of solid waste collected by the city authorities from year 2008 to 2013. The result indicated that ARIMA (1, 1, 1) outperformed other potential models in terms of MAPE, MAD and RMSE measures and hence used to forecast the amount of the solid waste generation for the next years. Keywords: ARIMA models, Exponential Smoothing models, time series, MAPE, MAD, RMS

Modeling the Impact of Immunization on the Epidemiology of Varicella Zoster Virus.

Chickenpox (also called varicella) is a disease caused by virus known as varicella-zoster virus (VZV) also known as human herpes virus 3. In this paper, a deterministic mathematical model for transmission dynamics of VZV with vaccination is formulated. The effective reproduction number is computed in order to measure the relative impact for individual or combined intervention for effective disease control.  Numerical simulations of the basic reproduction number of the model shows that, the combination of vaccination and treatment is the most effective way to combat the epidemiology of VZV in the community. Keywords: Modeling, Treatment, Vaccination, Epidemiolog