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In the past decade, numerous methods have been developed to analyze in-vivo calcium imaging data that involves complex techniques such as overlapping signals segregation and motion artifact correction. The hypothesis used to detect calcium signal is the spatiotemporal sparsity of calcium signal, and these methods are unable to identify the passive cells that are not actively firing during the time frame in the video. Statistics regarding the percentage of cells in each frame of view can be critical for the analysis of calcium imaging data for human induced pluripotent stem cells derived neurons and astrocytes.
The objective of this research is to develop a simple and efficient semi-automated pipeline for analysis of in-vitro calcium imaging data. The region of interest (ROI) based image segmentation is used to extract the data regarding intensity fluctuation caused by calcium concentration changes in each cell. It is achieved by using two approaches: basic image segmentation approach and a machine learning approach. The intensity data is evaluated using a custom-made MATLAB that generates statistical information and graphical representation of the number of spiking cells in each field of view, the number of spikes per cell and spike height.
Fourteen native lizard species inhabit the desert surrounding Phoenix, AZ, USA, but only two species persist within heavily developed areas. This pattern is best explained by a combination of socioeconomic status, land cover, and location. Lizard diversity is highest in affluent areas and lizard abundance is greatest near large patches of open desert. The percentage of building cover has a strong negative impact on both diversity and abundance. Despite Phoenix's intense urban heat island effect, which strongly constrains the potential activity and microhabitat use of lizards in summer, thermal patterns have not yet impacted their distribution and relative abundance at larger scales.
The study finds that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling during the day. A further analysis of the surface energy balance shows that the decrease in surface Albedo and increase effective emissivity play an important role in shaping the local climate change over urban areas. The emerging urban structures slow down the diurnal wind circulation over the city due to an increased effective surface roughness. This leads to a secondary modification of temperature due to the interaction between the mechanical and thermodynamic effects of urbanization.
The simulations for the five desert cities for 1985 and 2010 further confirm a common pattern of the climatic effect of urbanization with significant nighttime warming and moderate daytime cooling. This effect is confined to the urban area and is not sensitive to the size of the city or the detail of land cover in the surrounding areas. The pattern of nighttime warming and daytime cooling remains robust in the simulations for the future climate of the five cities using the projected 2030 land-use maps. Inter-city differences among the five urban areas are discussed.
The Kilombero Valley lies at the intersection of a network of protected areas that cross Tanzania. The wetlands and woodlands of the Valley, as well as the forest of surrounding mountains are abundant in biodiversity and are considered to be critical areas for conservation. This area, however, is also the home to more than a half million people, primarily poor smallholder farmers. In an effort to support the livelihoods and food security of these farmers and the larger Tanzanian population, the country has recently targeted a series of programs to increase agricultural production in the Kilombero Valley and elsewhere in the country. Bridging concepts and methods from land change science, political ecology, and sustainable livelihoods, I present an integrated assessment of the linkages between development and conservation efforts in the Kilombero Valley and the implications for food security.
This dissertation uses three empirical studies to understand the process of development in the Kilombero Valley and to link the priorities and perceptions of conservation and development efforts to the material outcomes in food security and land change. The first paper of this dissertation examines the changes in land use in the Kilombero Valley between 1997 and 2014 following the privatization of agriculture and the expansion of Tanzania’s Kilimo Kwanza program. Remote sensing analysis reveals a two-fold increase in agricultural area during this short time, largely at the expense of forest. Protected areas in some parts of the Valley appear to be deterring deforestation, but rapid agricultural growth, particularly surrounding a commercial rice plantation, has led to loss of extant forest and sustained habitat fragmentation. The second paper focuses examines livelihood strategies in the Valley and claims regarding the role of agrobiodiversity in food security.
The results of household survey reveal no difference or lower food security among households that diversify their agricultural activities. Some evidence, however, emerges regarding the importance of home gardens and crop diversification for dietary diversity. The third paper considers the competing discourses surrounding conservation and development in the Kilombero Valley. Employing q-method, this paper discerns four key viewpoints among various stakeholders in the Valley. While there are some apparently intractable distinctions between among these discourses, consensus regarding the importance of wildlife corridors and the presence of boundary-crossing individuals provide the promise of collaboration and compromise.
In the context of noise detection, this work proposes perceptual-based full-reference and no-reference objective image quality metrics by integrating perceptually weighted local noise into a probability summation model. Results are reported on both the LIVE and TID2008 databases. The proposed metrics achieve consistently a good performance across noise types and across databases as compared to many of the best very recent quality metrics. The proposed metrics are able to predict with high accuracy the relative amount of perceived noise in images of different content.
In the context of blur detection, existing approaches are either computationally costly or cannot perform reliably when dealing with the spatially-varying nature of the defocus blur. In addition, many existing approaches do not take human perception into account. This work proposes a blur detection algorithm that is capable of detecting and quantifying the level of spatially-varying blur by integrating directional edge spread calculation, probability of blur detection and local probability summation. The proposed method generates a blur map indicating the relative amount of perceived local blurriness. In order to detect the flat
ear flat regions that do not contribute to perceivable blur, a perceptual model based on the Just Noticeable Difference (JND) is further integrated in the proposed blur detection algorithm to generate perceptually significant blur maps. We compare our proposed method with six other state-of-the-art blur detection methods. Experimental results show that the proposed method performs the best both visually and quantitatively.
This work further investigates the application of the proposed blur detection methods to image deblurring. Two selective perceptual-based image deblurring frameworks are proposed, to improve the image deblurring results and to reduce the restoration artifacts. In addition, an edge-enhanced super resolution algorithm is proposed, and is shown to achieve better reconstructed results for the edge regions.
Findings indicate that the deployment of green roofs will cool the urban environment in daytime and warm it at night, via evapotranspiration and soil insulation. At the annual scale, green roofs are effective in decreasing building energy demands for both summer cooling and winter heating. For cities in arid and semiarid environments, an optimal trade-off between water and energy resources can be achieved via innovative design of smart urban irrigation schemes, enabled by meticulous analysis of the water-energy nexus. Using water-saving plants alleviates water shortage induced by population growth, but comes at the price of an exacerbated urban thermal environment. Realizing the potential water buffering capacity of urban green infrastructure is crucial for the long-term water sustainability and subsequently multisector sustainability of cities. Environmental performance of urban green infrastructure is determined by land-atmosphere interactions, geographic and meteorological conditions, and hence it is recommended that analysis should be conducted on a city-by-city basis before actual implementation of green infrastructure.
damage, immune system activation, impaired protein function, or aberrant DNA methylation. In the case of DNA methylation, I demonstrate that inhibiting DNA methylation dynamics can impair long-term memory formation, while the nurse-to- forager transition is not altered. These experiments could serve as the bases for and reference groups of studies testing the effects of metal or metalloid toxicity on DNA methylation. Each potential mechanism provides an avenue for investigating how neural function is influenced by the physiological status of non-neural organs. And from an ecological perspective, my results highlight the need for environmental policy to consider sublethal effects in determining safe environmental toxin loads for honey bees and other insect pollinators.