Shadowing, Generalized hyperbolic and Aluthge transforms

In this note, we introduce the notion of $r$-homoclinic points. We show that an operator on a Banach space is hyperbolic if and only if it is shadowing and has no nonzero $r$-homoclinic points. We also solve invariant subspace problem (ISP for brevity) for shadowing operators on Banach spaces. Afterwards, we verify that the set of generalized hyperbolic operators is invariant under $\lambda$-Aluthge transforms for every $\lambda \in \left( 0,1 \right)$. Next, the Aluthge iterates of invertible operators converge to hyperbolic operators only if the initial operators are hyperbolic. Finally, we prove that the Aluthge iterates of shifted hyperbolic bilateral weighted shifts diverge and that hyperbolic bilateral weighted shifts with divergent Aluthge iterates exist

Reconstruction of Multidecadal Country-Aggregated Hydro Power Generation in Europe Based on a Random Forest Model

Hydro power can provide a source of dispatchable low-carbon electricity and a storage solution in a climate-dependent energy mix with high shares of wind and solar production. Therefore, understanding the effect climate has on hydro power generation is critical to ensure a stable energy supply, particularly at a continental scale. Here, we introduce a framework using climate data to model hydro power generation at the country level based on a machine learning method, the random forest model, to produce a publicly accessible hydro power dataset from 1979 to present for twelve European countries. In addition to producing a consistent European hydro power generation dataset covering the past 40 years, the specific novelty of this approach is to focus on the lagged effect of climate variability on hydro power. Specifically, multiple lagged values of temperature and precipitation are used. Overall, the model shows promising results, with the correlation values ranging between 0.85 and 0.98 for run-of-river and between 0.73 and 0.90 for reservoir-based generation. Compared to the more standard optimal lag approach the normalised mean absolute error reduces by an average of 10.23% and 5.99%, respectively. The model was also implemented over six Italian bidding zones to also test its skill at the sub-country scale. The model performance is only slightly degraded at the bidding zone level, but this also depends on the actual installed capacity, with higher capacities displaying higher performance. The framework and results presented could provide a useful reference for applications such as pan-European (continental) hydro power planning and for system adequacy and extreme events assessments

Education and Women in the Informal Sector: A Cross-Country Analysis

This study investigates the effects of education on the participation of women in the informal sector of 40 developing countries using OLS linear regression. Through some econometric adjustments, the final model suggests that education, represented by years of schooling, is correlated with a 2.74% increase in women’s chances of being employed in this sub-sector of the economy. This means that the better educated still end up doing the jobs that do not require such knowledge. An implication of the result is that the current way which schooling is delivered to the poor might not be the most efficient way

An Analysis of Fluvial Geomorphology Parameters Affecting Meander Migration and Dynamic Equilibrium of the White River in Arkansas

An analysis of a multitude of fluvial and morphological parameters was conducted to assess the current stability conditions of various White River reaches and to accentuate the contributions imparted by these parameters to the internal processes that governed the dynamic equilibrium within these reaches. The initial step involved the extractions and computations of pertinent fluvial and morphological parameters from the HEC-RAS Model and ArcGIS.Channel stability assessment emphasized three methodologies, namely stability assessment through parametric correlations between fluvial and morphological parameters; stability evaluation with the Rosgen Stream Classification System; and stability estimation through sediment analyses and sediment related parametric correlations. Morphological assessment implementing the Rosgen Stream Classification (RSC) system consisted of four inventory levels of classification. Sediment analyses conducted by implementing several sediment transport functions utilized the dominant bed materials attained from sieve analyses of approximately seven hundred soil samples collected from the channels of various ‘reference’ reaches

Efficient Denoising and Sharpening of Color Images through Numerical Solution of Nonlinear Diffusion Equations

The purpose of this project is to enhance color images through denoising and sharpening, two important branches of image processing, by mathematically modeling the images. Modifications are made to two existing nonlinear diffusion image processing models to adapt them to color images. This is done by treating the red, green, and blue (RGB) channels of color images independently, contrary to the conventional idea that the channels should not be treated independently. A new numerical method is needed to solve our models for high resolution images since current methods are impractical. To produce an efficient method, the solution is represented as a linear combination of sines and cosines for easier numerical treatment and then computed by a combination of Krylov subspace spectral (KSS) methods and exponential propagation iterative (EPI) methods. Numerical experiments demonstrate that the proposed approach for image processing is effective for denoising and sharpening

Cotton farming and N cycling : adaptation to climate change

Climate models have projected the atmospheric carbon dioxide (CO2) concentration will double and a 1.1-6.4oC rise in global average temperature by the end of 21st century. Simultaneously, extreme weather events including flooding and drought have been predicted to increase in frequency and intensity. Such changes are expected to have profound effects on agriculture. Soil nitrogen (N) cycling, particularly nitrification and denitrification plays an important role in the availability of N in soils for plant uptake, and hence changes in these processes due to global change may considerably influence crop productivity. These N processes are microbially driven and little is known about the role of soil microorganisms in regulating the process rates and how they respond to environmental disturbances. Therefore, my study aimed to elucidate the responses of soil nitrification to climate change and extreme weather events, and subsequent consequences for crop yields, by using cotton as a model system. Additionally, the legacy effects of extreme weather events and the impacts of added N-fertilizer on soil N, C processes and microbial communities and the subsequent consequences for crop productivity were examined. First effects of waterlogging on soil nitrification and nitrifying community in cotton farming were examined. This study was a field-based experiment conducted at the Australian Cotton Research Institute (ACRI) in Narrabri, NSW. Waterlogging events simulated by running furrow irrigation for 120 hours were applied at the early and late flowering stages, respectively. Waterlogging had strong effects on soil moisture, pH, potential nitrification rate (PNR) and soil nitrate (NO3-) concentration. The abundance of ammonia-oxidizing bacteria (AOB) decreased approximately 10-fold whereas that of ammonia-oxidizing archaea (AOA) decreased about 2-fold after waterlogging. Shifts in AOB and AOA community structures were also observed after waterlogging. Significant correlations between both AOB and AOA communities and PNR were observed; however, AOB was more strongly correlated to PNR than AOA. Significant linear negative correlations between soil moisture and ammonia-oxidizing communities and PNR were also obtained. These results indicate that waterlogging impacted on soil physicochemical properties, resulting in changes in ammonia-oxidizing communities and nitrification activity. In the second chapter, the effects of elevated temperature (+1.1oC) alone and elevated temperature in combination with elevated CO2 (550 ppm) on soil nitrification and nitrifying communities in cotton farming were investigated using field-based environmentally-controlled chambers. This study was conducted at ACRI in Narrabri, NSW. Elevated temperature did not affect soil PNR and AOB community abundance and structure. The AOA community responded significantly to elevated temperatures by increasing its abundance and shifting their community structure. Combined elevated CO2 and temperature significantly increased both AOB and AOA abundance, and resulted in shifts in AOB and AOA community structures. Both AOB and AOA communities were significantly correlated with PNR, although AOA exhibited a weaker relationship with PNR than AOB. Effects of climate factors on soil nitrification and nitrifying community depended on the stage of cotton growth since treatment effects were only observed when cotton reached the early flowering stage. Thirdly, the responses of soil N processes (nitrification, denitrification, and N mineralization), functional microbial communities, crop growth and productivity to different N fertilizer regimes (0, 100, 200 and 300 kg N/ha) after exposure to waterlogging and prolonged-drought were investigated by conducting a glass-house experiment at Western Sydney University (WSU). Prolonged-drought prior to cotton planting established a strong legacy effect on soil N processes, ammonia-oxidizing communities, nosZ-containing community, plant growth and productivity. N fertilizer application up to 300 kg N/ha could not counteract the legacy effect of prolonged drought on soils and plants although N supply improved soil fertility. These results suggest that the depleted functional microbial communities may take a long time to recover after drought. Waterlogging prior to planting had a legacy effect on soil NO3- content and the nosZ-containing community. The legacy effect of waterlogging on soil NO3- was diminished completely by N addition. Despite an increase in nosZ gene abundance due to waterlogging before sowing, soil N availability and crop growth and productivity was not impacted. However, N loss from the plant-soil system can be significant if further waterlogging occurs, thereby potentially affecting crop yields. Finally, the responses of the soil bacterial community and microbial respiration to legacy effects of waterlogging and prolonged-drought, and N fertilizer addition were also examined. This experiment was carried out to examine links between N and C cycling in farming systems. Prolonged-drought prior to planting generated a strong legacy effect on soil bacterial abundance, diversity, and composition, and microbial respiration rates. N fertilizer supply increased soil bacterial abundance and diversity, and altered bacterial community composition. However, N fertilizer application up to 300 kg N/ha could not counteract the legacy effects of prolonged-drought on the soil bacterial community. Additionally, different bacterial phyla responded differently to the legacy effects of prolonged-drought and N supply. In contrast to prolonged-drought, waterlogging did not establish a legacy effect on the soil bacterial community and microbial respiration. This suggests that the soil bacterial community might be resistant to waterlogging or recover completely upon water stress. N fertilizer supply inhibited soil microbial respiration by inhibiting C-degraded enzyme activities. Some weak but significant correlations between soil total bacterial community and microbial respiration were observed; however, addition of N fertilizer weakened these relationships further. Overall, my study provides novel evidence of soil N cycling responses to climate change and extreme weather events in cotton farming systems. My study is the first to demonstrate a legacy effect from extreme weather events and external N supply on soil N and C processes, and subsequent consequences on crop productivity. Data obtained in this study will support the development of robust predictive models and adaptation strategies to sustain crop yields under future climatic conditions via effective N management

An Empirical Analysis of the Relationship among Social Institutions and Juvenile Arrests in Virginia

The United States has unusually high rates of violence among developed nations, including the victimization of and perpetration by youth. Using Institutional Anomie Theory (IAT) as the theoretical framework, this study analyzes the relationships between social institutions and crime and the interactive relationships among the institutions in a sample of Virginia localities. Multivariate analyses are conducted to produce additive and multiplicative models, and simple slope analyses are conducted to clarify interaction/moderation effects. Findings yield mixed support for IAT. Localities with higher levels of monthly welfare per recipient (a measure of polity) have lower juvenile violent crime arrest rates, and welfare moderates the relationship between income inequality and juvenile violent crime arrests. Controlling for all variables, no support was found for the direct effects of any other institution on juvenile violent crime arrests. Policy recommendations include maintenance of welfare programs and improvement of work participation supplementary programs

Impact of a Geriatric and Palliative Medicine Clerkship on Knowledge and Attitudes about End-Of-Life Care

Previous interventions of students and residents suggest that those which employ patient encounters increases attitude towards end-of-life care and performance on a palliative care knowledge examination, but those studies did not include geriatric preceptors. From a population of third-year medical students, the researcher surveyed attitudes and tested knowledge before and after a combined geriatric and palliative clerkship to determine the impact on these outcomes and if there were any differences among the preceptor or the clinical site. After the rotation, students’ perceptions of the importance that medical students learn about how to care for dying patients of resident and attending physicians increased from 77.5% to 89.6% (p <0.001) and 87.4% to 92.9% (p = 0.001) respectively. More students agreed that physicians have a responsibility to provide bereavement care (p < 0.001) and that depression is treatable among patients with terminal illness (p = 0.017). More students disagreed that they dread having to tell patients the truth about a terminal prognosis and still maintain hope (p = 0.003), that caring for dying patients is depressing (p < 0.001), and that they feel guilty after a death (p <0.001). Test scores increased from a mean of 59.8% to 70.4% (p < 0.001). There were no differences in attitude or knowledge among the preceptors or clinical sites. This rotation was associated with an increase in attitudes and knowledge regardless of the preceptor or clinical site. Results indicated that palliative educational programs should receive more institutional support to better prepare future physicians.Curriculum and Instruction, Department o

InP and GaAs characterization with variable stoichiometry obtained by molecular spray

Both InP and GaAs surfaces were studied in parallel. A molecular spray technique was used to obtain two semiconductor surfaces with different superficial compositions. The structures of these surfaces were examined by electron diffraction. Electron energy loss was measured spectroscopically in order to determine surface electrical characteristics. The results are used to support conclusions relative to the role of surface composition in establishing a Schottky barrier effect in semiconductor devices