Theory for Optical Absorption in Small Clusters: Dependence on Atomic Structure and Cluster Size

We present a theory which permits for the first time a detailed analysis of the dependence of the absorption spectrum on atomic structure and cluster size. Thus, we determine the development of the collective excitations in small clusters and show that their broadening depends sensitively on the tomic structure, in particular at the surface. Results for Hg_n^+ clusters show that the plasmon energy is close to its jellium value in the case of spherical-like structures, but is in general between w_p/ \wurzel{3} and w_p/ \wurzel{2} for compact clusters. A particular success of our theory is the identification of the excitations contributing to the absorption peaks.

Identifying the component structure of job satisfaction by principal components analysis among extension officers in North West Province, South Africa

The component structure of a 34-item scale measuring different aspects of job satisfaction was investigated among extension officers in North West Province, South Africa. A simple random sampling technique was used to select 40 extension officers from which data were collected. A structured questionnaire consisting of 34 job satisfaction and 10 personal characteristic items was administered to the extension officers. Items on job satisfaction were measured at interval level and analyzedwith Principal ComponentAnalysis. Most of the respondents (82.5%) weremales, between 40 to 45 years, 85% were married and 87.5% had a diploma as their educational qualification. Furthermore, 54% of the households size between 4 to 6 persons, whereas 75% were Christians. The majority of the extension officers lived in their job area (82.5), while 80% covered at least 3 communities and 3 farmer groups. In terms of number of farmers covered, only 40% of the extension officers covered more than 500 farmers and 45% travelled more than 40 km to reach their farmers. From the job satisfaction items 9 components were extracted to show areas for job satisfaction among extension officers. These were in-service training, research policies, communicating recommended practices, financial support for self and family, quality of technical help, opportunity to advance education, management and control of operations, rewarding system and sanctions. The results have several implications for motivating extension officers for high job performance especially with large number of clients and small number of extension agents.

Large-Size AlGaN/GaN HEMT Large-Signal Electrothermal Characterization and Modeling for Wireless Digital Communications

The rapid growth in high data rate communication systems has introduced new high spectral efficient modulation techniques and standards such as LTE-A (long term evolution-advanced) for 4G (4th generation) systems. These techniques have provided a broader bandwidth but introduced high peak-to-average power ratio (PAR) problem at the high power amplifier (HPA) level of the communication system base transceiver station (BTS). To avoid spectral spreading due to high PAR, stringent requirement on linearity is needed which brings the HPA to operate at large back-off power at the expense of power efficiency. Consequently, high power devices are fundamental in HPAs for high linearity and efficiency. Recent development in wide bandgap power devices, in particular AlGaN/GaN HEMT, has offered higher power level with superior linearity-efficiency trade-off in microwaves communication. For cost-effective HPA design to production cycle, rigorous computer aided design (CAD) AlGaN/GaN HEMT models are essential to reflect real response with increasing power level and channel temperature. Therefore, large-size AlGaN/GaN HEMT large-signal electrothermal modeling procedure is proposed. The HEMT structure analysis, characterization, data processing, model extraction and model implementation phases have been covered in this thesis including trapping and self-heating dispersion accounting for nonlinear drain current collapse. The small-signal model is extracted using the 22-element modeling procedure developed in our department. The intrinsic large-signal model is deeply investigated in conjunction with linearity prediction. The accuracy of the nonlinear drain current has been enhanced through several issues such as trapping and self-heating characterization. Also, the HEMT structure thermal profile has been investigated and corresponding thermal resistance has been extracted through thermal simulation and chuck-controlled temperature pulsed I(V) and static DC measurements. Higher-order equivalent thermal model is extracted and implemented in the HEMT large-signal model to accurately estimate instantaneous channel temperature. Moreover, trapping and self-heating transients has been characterized through transient measurements. The obtained time constants are represented by equivalent sub-circuits and integrated in the nonlinear drain current implementation to account for complex communication signals dynamic prediction. The obtained verification of this table-based large-size large-signal electrothermal model implementation has illustrated high accuracy in terms of output power, gain, efficiency and nonlinearity prediction with respect to standard large-signal test signals.

Effects of grassland conversion and tillage intensities on soil microbial biomass, residues and community structure

Agricultural intensification has a strong impact on level of soil organic matter (SOM), microbial biomass stocks and microbial community structure in agro-ecosystems. The size of the microbial necromass C pool could be about 40 times that of the living microbial biomass C pool in soils. Due to the specificity, amino sugar analysis gives more important information on the relative contribution of fungal and bacterial residues to C sequestration potential of soils. Meanwhile, the relationship between microbial biomass and microbial necromass in soil and its ecological significance on SOM are not fully understood and likely to be very complex in grassland soils. This thesis focuses on the effects of tillage, grassland conversion intensities and fertilisation on microbial biomass, residues and community structure. The combined analyses of microbial biomass and residue formation of both fungi and bacteria provided a unique opportunity to study the effect of tillage, grassland conversion and fertilisation on soil microbial dynamics. In top soil at 0-30 cm layer, a reduction in tillage intensity by the GRT and NT treatments increased the accumulation of saprotrophic fungi in comparison with the MBT treatment. In contrast, the GRT and NT treatments promoted AMF at the expense of saprotrophic fungi in the bottom soil layer at 30-40 cm depth. The negative relationship between the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio points to the importance of the relationship between saprotrophic fungi and biotrophic AMF for tillage-induced changes in microbial turnover of SOC. One-season cultivation of winter wheat with two tillage events led to a significant loss in SOC and microbial biomass C stocks at 0-40 cm depth in comparison with the permanent grassland, even 5 years after the tillage event. However, the tillage induced loss in microbial biomass C was roughly 40% less in the long-term than in the short-term of the current experiment, indicating a recovery process during grassland restoration. In general, mould board tillage and grassland conversion to maize monoculture promoted saprotrophic fungi at the expense of biotrophic AMF and bacteria compared to undisturbed grassland soils. Slurry application promoted bacterial residues as indicated by the decreases in both, the ergosterol to microbial biomass C ratio and the fungal C to bacterial C ratio. In addition, the lost microbial functional diversity due to tillage and maize monoculture was restored by slurry application both in arable and grassland soils. I conclude that the microbial biomass C/S ratio can be used as an additional indicator for a shift in microbial community. The strong relationships between microbial biomass and necromass indices points to the importance of saprotrophic fungi and biotrophic AMF for agricultural management induced effects on microbial turnover and ecosystem C storage. Quantitative information on exact biomass estimates of these two important fungal groups in soil is inevitably necessary to understand their different roles in SOM dynamics.