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"McClellan, James"
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Joint seismic data denoising and interpolation with double-sparsity dictionary learning
Seismic data quality is vital to geophysical applications, so that methods of data recovery, including denoising and interpolation, are common initial steps in the seismic data processing flow. We present a method to perform simultaneous interpolation and denoising, which is based on double-sparsity dictionary learning. This extends previous work that was for denoising only. The original double-sparsity dictionary learning algorithm is modified to track the traces with missing data by defining a masking operator that is integrated into the sparse representation of the dictionary. A weighted low-rank approximation algorithm is adopted to handle the dictionary updating as a sparse recovery optimization problem constrained by the masking operator. Compared to traditional sparse transforms with fixed dictionaries that lack the ability to adapt to complex data structures, the double-sparsity dictionary learning method learns the signal adaptively from selected patches of the corrupted seismic data, while preserving compact forward and inverse transform operators. Numerical experiments on synthetic seismic data indicate that this new method preserves more subtle features in the data set without introducing pseudo-Gibbs artifacts when compared to other directional multi-scale transform methods such as curvelets.
Journal Article
Nanofiltered C1 Inhibitor Concentrate for Treatment of Hereditary Angioedema
A recently developed preparation of C1 inhibitor concentrate was evaluated in patients with hereditary angioedema in two trials. In the acute-attack treatment trial, the time to relief of an acute attack of angioedema was significantly shorter with the C1 inhibitor than with placebo. In the prophylaxis trial, the attack rate over a 12-week period was significantly lower with the C1 inhibitor than with placebo.
Hereditary angioedema due to C1 inhibitor deficiency is an autosomal dominant disorder characterized by recurrent episodes of angioedema that typically involve the extremities, abdomen, external genitalia, face, or oropharynx.
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Abdominal attacks of angioedema, which are caused by local mucosal swelling, are often associated with severe abdominal pain, nausea, and vomiting. Such attacks frequently lead to hospitalization and occasionally to unnecessary exploratory surgery.
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Laryngeal attacks are associated with a substantial risk of death.
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Two forms of hereditary angioedema have been defined: type I (accounting for 85% of cases) is characterized by low antigenic and functional levels of C1 inhibitor, whereas type . . .
Journal Article
My Life with Trains
Named one of the \"75 People You Should Know\" by Trains Magazine, Jim McClellan was a railroading legend and one of the railroad industry's titans. An iconic and innovative executive, McClellan participated in the creation of both Amtrak and Conrail and worked for the Norfolk Southern, the New York Central, US Railway Association, and the Federal Railroad Administration. My Life with Trains combines a world-class photographer's love of railroading with the insights of a government and railroad official. The book provides a short historical overview of the changes in the industry, recounts McClellan's experience at various railroads, and offers personal reflections on a lifetime of working with and chasing trains. Expertly detailed with over 250 stunning color photographs, My Life with Trains covers sixty years as observed by a legendary railroad strategist.
eBook
High-resolution seismic event detection using local similarity for Large-N arrays
We develop a novel method for seismic event detection that can be applied to large-N arrays. The method is based on a new detection function named local similarity, which quantifies the signal consistency between the examined station and its nearest neighbors. Using the 5200-station Long Beach nodal array, we demonstrate that stacked local similarity functions can be used to detect seismic events with amplitudes near or below noise levels. We apply the method to one-week continuous data around the 03/11/2011 Mw 9.1 Tohoku-Oki earthquake, to detect local and distant events. In the 5–10 Hz range, we detect various events of natural and anthropogenic origins, but without a clear increase in local seismicity during and following the surface waves of the Tohoku-Oki mainshock. In the 1-Hz low-pass-filtered range, we detect numerous events, likely representing aftershocks from the Tohoku-Oki mainshock region. This high-resolution detection technique can be applied to both ultra-dense and regular array recordings for monitoring ultra-weak micro-seismicity and detecting unusual seismic events in noisy environments.
Journal Article
Placing language in an integrated understanding system
Language is crucial for human intelligence, but what exactly is its role? We take language to be a part of a system for understanding and communicating about situations. In humans, these abilities emerge gradually from experience and depend on domain-general principles of biological neural networks: connection-based learning, distributed representation, and context-sensitive, mutual constraint satisfaction-based processing. Current artificial language processing systems rely on the same domain general principles, embodied in artificial neural networks. Indeed, recent progress in this field depends on query-based attention, which extends the ability of these systems to exploit context and has contributed to remarkable breakthroughs. Nevertheless, most current models focus exclusively on language-internal tasks, limiting their ability to perform tasks that depend on understanding situations. These systems also lack memory for the contents of prior situations outside of a fixed contextual span. We describe the organization of the brain’s distributed understanding system, which includes a fast learning system that addresses the memory problem. We sketch a framework for future models of understanding drawing equally on cognitive neuroscience and artificial intelligence and exploiting query-based attention. We highlight relevant current directions and consider further developments needed to fully capture human-level language understanding in a computational system.
Journal Article
The cancer stem cell model: B cell acute lymphoblastic leukaemia breaks the mould
See related article in EMBO Molecular Medicine
http://dx.doi.org/10.1002/emmm.201201703
Journal Article
Harold Dorn, 1928-2011
An obituary for the historian of science and technology, Harold Dorn (1928–2011), that surveys his life and career from their Bronx origins, to his training in engineering, a Princeton Ph.D. in the history of science, and ultimately roles as a professor and administrator at the Stevens Institute of Technology. The personal and historiographical influences of Marxism, materialism, and World War II on Dorn and his work are examined, notably in his chef-d'œuvre, The Geography of Science (Johns Hopkins University Press, 1991). His life-long scholarly interests in the historical connections between technology and science, in invention and innovation, and in defending free speech are likewise treated.
Journal Article
