A compressive sensing algorithm for attitude determination

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 29-30).We propose a framework for compressive sensing of images with local distinguishable objects, such as stars, and apply it to solve a problem in celestial navigation. Specifically, let x [epsilon] RN be an N-pixel image, consisting of a small number of local distinguishable objects plus noise. Our goal is to design an m x N measurement matrix A with m << N, such that we can recover an approximation to x from the measurements Ax. We construct a matrix A and recovery algorithm with the following properties: (i) if there are k objects, the number of measurements m is O((klog N)/(log k)), undercutting the best known bound of O(klog(N/k)) (ii) the matrix A is ultra-sparse, which is important when the signal is weak relative to the noise, and (iii) the recovery algorithm is empirically fast and runs in time sub-linear in N. We also present a comprehensive study of the application of our algorithm to attitude determination, or finding one's orientation in space. Spacecraft typically use cameras to acquire an image of the sky, and then identify stars in the image to compute their orientation. Taking pictures is very expensive for small spacecraft, since camera sensors use a lot of power. Our algorithm optically compresses the image before it reaches the camera's array of pixels, reducing the number of sensors that are required.by Rishi Vijay Gupta.M.Eng

Precision targeting of preventative therapy for tuberculosis

Background: Scale-up of preventative treatment for tuberculosis (TB) represents a cornerstone of global control efforts. I examined a range of approaches to enable more precise targeting of preventative treatment to people at highest risk. Methods: I evaluated whether prognostic tests for TB (tuberculin skin test (TST), QuantiFERON Gold-in-tube (QFT-GIT) and T-SPOT.TB) may be optimised by implementing higher thresholds, or by a newer generation assay (QuantiFERON-TB Gold Plus; QFT-Plus). Next, I conducted a systematic review and individual participant data meta-analysis (IPD-MA) to examine TB risk among people tested for latent infection (LTBI) in settings with low TB transmission and to develop a multivariable prognostic model for incident TB. Finally, I performed a systematic review and IPD-MA of whole-blood RNA sequencing data to evaluate blood transcriptomic signatures as next-generation biomarkers. Results: In a UK cohort of 9,610 adults, higher TST, QFT-GIT and T-SPOT.TB results were associated with increased incident TB risk. Implementing higher cut-offs led to a marginal improvement in positive predictive value, but at the cost of a marked loss in sensitivity. The newer generation QFT-Plus had similar predictive ability. In a pooled dataset of >80,000 participants from 18 cohort studies, TB risk was heterogeneous among people with LTBI, even after stratification by indication for testing. I developed and validated a multivariable prognostic model, which incorporates quantitative LTBI test results and clinical covariates, and demonstrated strong potential for clinical utility to inform provision of preventative treatment. Among 1,126 whole-blood RNA sequencing samples, eight transcriptomic signatures (comprising 1-25 transcripts) performed similarly for predicting incident TB, but only met global accuracy benchmarks over a 3-6 month time-horizon. Conclusions: Personalised risk estimates integrating quantitative LTBI test results and clinical covariates may facilitate more precise targeting of preventative treatment. Blood transcriptomic biomarkers show promise, but only represent short-term TB risk. Future research priorities are highlighted

Compulsory Licensing in TRIPS: Chinese and Indian Comparative Advantage in the Manufacture and Exportation of Green Technologies

Challengers to the United States’ global influence, such as Brazil, China, and India, have criticized heavy polluters like the United States and the United Kingdom for significantly contributing to the world’s total carbon emissions but failing to share its green technologies with the rest of the world. Utilizing Rio+20 to redefine Article 31(b) of the World Trade Organization’s Trade-Related Aspects of Intellectual Property Rights (TRIPS) agreement should create an international framework for transfer of green technology through a patent process called compulsory licensing. Compulsory licensing allows a country to bypass a patent and create a generic copy of a technology by licensing it within its borders