Space current division in small pentodes

Thesis (B.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering, 1948.by James Darr, Jr. and Solomon Manber.B.S

New developments in cognitive behavioral therapy as the first-line treatment of insomnia

Insomnia is the most common sleep disorder. Psychological, behavioral, and biological factors are implicated in the development and maintenance of insomnia as a disorder, although the etiology of insomnia remains under investigation, as it is still not fully understood. Cognitive behavioral therapy for insomnia (CBTI) is a treatment for insomnia that is grounded in the science of behavior change, psychological theories, and the science of sleep. There is strong empirical evidence that CBTI is effective. Recognition of CBTI as the first-line treatment for chronic insomnia (National Institutes of Health consensus, British Medical Association) was based largely on evidence of its efficacy in primary insomnia. The aim of this article is to provide background information and review recent developments in CBTI, focusing on three domains: promising data on the use of CBTI when insomnia is experienced in the presence of comorbid conditions, new data on the use of CBTI as maintenance therapy, and emerging data on the delivery of CBTI through the use of technology and in primary care settings

Document Retrieval on Repetitive Collections

Document retrieval aims at finding the most important documents where a pattern appears in a collection of strings. Traditional pattern-matching techniques yield brute-force document retrieval solutions, which has motivated the research on tailored indexes that offer near-optimal performance. However, an experimental study establishing which alternatives are actually better than brute force, and which perform best depending on the collection characteristics, has not been carried out. In this paper we address this shortcoming by exploring the relationship between the nature of the underlying collection and the performance of current methods. Via extensive experiments we show that established solutions are often beaten in practice by brute-force alternatives. We also design new methods that offer superior time/space trade-offs, particularly on repetitive collections.Comment: Accepted to ESA 2014. Implementation and experiments at http://www.cs.helsinki.fi/group/suds/rlcsa

Tracing diagnosis trajectories over millions of patients reveal an unexpected risk in schizophrenia.

The identification of novel disease associations using big-data for patient care has had limited success. In this study, we created a longitudinal disease network of traced readmissions (disease trajectories), merging data from over 10.4 million inpatients through the Healthcare Cost and Utilization Project, which allowed the representation of disease progression mapping over 300 diseases. From these disease trajectories, we discovered an interesting association between schizophrenia and rhabdomyolysis, a rare muscle disease (incidence < 1E-04) (relative risk, 2.21 [1.80-2.71, confidence interval = 0.95], P-value 9.54E-15). We validated this association by using independent electronic medical records from over 830,000 patients at the University of California, San Francisco (UCSF) medical center. A case review of 29 rhabdomyolysis incidents in schizophrenia patients at UCSF demonstrated that 62% are idiopathic, without the use of any drug known to lead to this adverse event, suggesting a warning to physicians to watch for this unexpected risk of schizophrenia. Large-scale analysis of disease trajectories can help physicians understand potential sequential events in their patients

PET Respiratory Motion Correction in Simultaneous PET/MR

In Positron Emission Tomography (PET) imaging, patient motion due to respiration can lead to artefacts and blurring, in addition to quantification errors. The integration of PET imaging with Magnetic Resonance (MR) imaging in PET/MR scanners provides spatially aligned complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET data. In this thesis, we form a methodology for respiratory motion correction of PET data, and show it can improve PET image quality. The approach is practical, having minimal impact on clinical PET/MR protocols, with no need for external respiratory monitoring, using standard MR sequences and minimal extra acquisition time. First we validate the use of PET-derived respiratory signal to use for motion tracking, that uses raw PET data only, via Principal Component Analysis (PCA), then set up the tools to carry out PET Motion Compensated Image Reconstruction (MCIR). We introduce a joint PET-MR motion model, using one minute of PET and MR data to provide a motion model that captures inter-cycle and intra-cycle breathing variations. Different motion models (one/two surrogates, linear/polynomial) are evaluated on dynamic MR data sets. Finally we apply the methodology on 45 clinical PET-MR patient datasets. Qualitative PET reconstruction improvements and artefact reduction are assessed with visual analysis, and quantitative improvements are calculated using Standardised Uptake Value (SUV) changes in avid lesions. Lesion detectability changes are explored with a study where two radiologists identify lesions or ’hot spots’, with confidence levels, in uncorrected and motion-corrected images. In summary, we developed a methodology for motion correction in PET/MR by using a joint motion model and demonstrated the capability of a joint PET-MR motion model to predict respiratory motion by showing significantly improved image quality of PET data, with one minute of extra scan time, and no external hardware

Faster algorithms for 1-mappability of a sequence

In the k-mappability problem, we are given a string x of length n and integers m and k, and we are asked to count, for each length-m factor y of x, the number of other factors of length m of x that are at Hamming distance at most k from y. We focus here on the version of the problem where k = 1. The fastest known algorithm for k = 1 requires time O(mn log n/ log log n) and space O(n). We present two algorithms that require worst-case time O(mn) and O(n log^2 n), respectively, and space O(n), thus greatly improving the state of the art. Moreover, we present an algorithm that requires average-case time and space O(n) for integer alphabets if m = {\Omega}(log n/ log {\sigma}), where {\sigma} is the alphabet size

Scheduling Jobs in Flowshops with the Introduction of Additional Machines in the Future

This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/expert-systems-with-applications/.The problem of scheduling jobs to minimize total weighted tardiness in flowshops,\ud with the possibility of evolving into hybrid flowshops in the future, is investigated in\ud this paper. As this research is guided by a real problem in industry, the flowshop\ud considered has considerable flexibility, which stimulated the development of an\ud innovative methodology for this research. Each stage of the flowshop currently has\ud one or several identical machines. However, the manufacturing company is planning\ud to introduce additional machines with different capabilities in different stages in the\ud near future. Thus, the algorithm proposed and developed for the problem is not only\ud capable of solving the current flow line configuration but also the potential new\ud configurations that may result in the future. A meta-heuristic search algorithm based\ud on Tabu search is developed to solve this NP-hard, industry-guided problem. Six\ud different initial solution finding mechanisms are proposed. A carefully planned\ud nested split-plot design is performed to test the significance of different factors and\ud their impact on the performance of the different algorithms. To the best of our\ud knowledge, this research is the first of its kind that attempts to solve an industry-guided\ud problem with the concern for future developments