Ontogenetic Scaling of Poison Glands in Dendrobates Pumilio

The relationship between granular (poison) gland size and density was examined in an ontogenetic series of the strawberry dart-poison frog, Dendrobates pumilio. Specimens used in this study were collected from the La Selva Biological Station in northeastern Costa Rica. Patches of skin from the dorsal surface of seven frogs, ranging in size from 11 to 23 mm snout-vent length (SVL), were fixed and embedded in paraffin for histological sectioning. Poison gland size and density were quantified microscopically in these sections. Poison glands are uniformly distributed across the skin and mean poison gland diameter increases at a rate faster than snout-vent length from 42.5 at SVL 11mm to 120.0 at SVL 23 mm. Conversely, gland density decreases with body size from 71.9 glands/mm2 to 33.2 glands/mm2 • Due to the positive allometric growth of the poison glands, the percentage of skin surface occupied by poison glands increases from 10.1-22.1% in small frogs (SVL<18 >mm) to 50.0-65.2% in large frogs (SVL>19MM), resulting in more toxin per mm2 in the larger animals. The largest increase in toxicity is correlated temporally with the onset of sexual maturity rather than with changes in aposematic coloring.

Real-time scheduling of embedded applications on multi-core platforms

For the past several decades, we have experienced the tremendous growth, in both scale and scope, of real-time embedded systems, thanks largely to the advances in IC technology. However, the traditional approach to get performance boost by increasing CPU frequency has been a way of past. Researchers from both industry and academia are turning their focus to multi-core architectures for continuous improvement of computing performance. In our research, we seek to develop efficient scheduling algorithms and analysis methods in the design of real-time embedded systems on multi-core platforms. Real-time systems are the ones with the response time as critical as the logical correctness of computational results. In addition, a variety of stringent constraints such as power/energy consumption, peak temperature and reliability are also imposed to these systems. Therefore, real-time scheduling plays a critical role in design of such computing systems at the system level. We started our research by addressing timing constraints for real-time applications on multi-core platforms, and developed both partitioned and semi-partitioned scheduling algorithms to schedule fixed priority, periodic, and hard real-time tasks on multi-core platforms. Then we extended our research by taking temperature constraints into consideration. We developed a closed-form solution to capture temperature dynamics for a given periodic voltage schedule on multi-core platforms, and also developed three methods to check the feasibility of a periodic real-time schedule under peak temperature constraint. We further extended our research by incorporating the power/energy constraint with thermal awareness into our research problem. We investigated the energy estimation problem on multi-core platforms, and developed a computation efficient method to calculate the energy consumption for a given voltage schedule on a multi-core platform. In this dissertation, we present our research in details and demonstrate the effectiveness and efficiency of our approaches with extensive experimental results.