Study of spin-scan imaging for outer planets missions

The constraints that are imposed on the Outer Planet Missions (OPM) imager design are of critical importance. Imager system modeling analyses define important parameters and systematic means for trade-offs applied to specific Jupiter orbiter missions. Possible image sequence plans for Jupiter missions are discussed in detail. Considered is a series of orbits that allow repeated near encounters with three of the Jovian satellites. The data handling involved in the image processing is discussed, and it is shown that only minimal processing is required for the majority of images for a Jupiter orbiter mission

Performance-Based Quality Specifications: The Link between Product Development and Clinical Outcomes

The design of drug delivery systems and their corresponding dosing guidelines are critical product development functions supported by clinical pharmacokinetic (PK) and pharmacodynamic (PD) data. Largely, the importance of variance and covariance in product and patient attributes is poorly understood. The existence of PK/PD diversity among myriad patient sub-populations further complicates efforts to gauge the importance of product quality variation. Nevertheless, a platform capable of evaluating the effects of product and patient variability on clinical performance was constructed. This dissertation was predicated on requests to re-define pharmaceutical quality in terms of risk by relating clinical attributes to production characteristics. To avoid in vivo studies, simulated experimental trials were conducted using the model drug, theophylline, for which data and models could be acquired from the literature. Where comprehensive data were unavailable (e.g., production variability statistics), initial estimates were acquired via laboratory-scale experiments. Model asthmatic patients were generated using Monte Carlo simulation and published population distributions of various anothropometric measurements, disease rates, and lifestyle factors. Mathematical constructs for in vitro-in vivo correlations provide a linkage between Quality by Design (QbD) product and process models, PK/PD models, and patient population statistics. The combined models formed the foundation for Monte Carlo risk assessments, which characterized the risk of inefficacy and toxicity for dosing of extended-release theophylline tablets. Sensitivity analyses revealed that patient compliance and content uniformity significantly influenced the probability of observing an adverse event. The Monte Carlo risk assessment platform defined the link between the critical quality attributes (CQAs) and clinical performance (i.e., performance-based quality specifications (PBQS)). The PBQS were subsequently utilized to generate process independent design spaces conditioned on inefficacy and toxicity risk. These design spaces, which directly account for the conditional relationships between product quality and patient variability, can be transferred to a specific process via models that relate process critical control parameters to the CQAs. Process Analytical Technology, therefore, can be integrated into the QbD production environment to control the safety and efficacy of the final product. This work demonstrated that process and product knowledge can be used to estimate the risk that final product quality imparts to clinical performance

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions