Political Advocacy on the Web: Issue Networks in Online Debate Over the USA Patriot Act

This dissertation examines how people and organizations used the World Wide Web to discuss and debate a public policy in 2005, at a point of time when the Internet was viewed as a maturing medium for communication. Combining descriptive and quantitative frame analyses with an issue network analysis, the study evaluated the frames apparent in discourse concerning two key sections of the USA Patriot Act, while the issue network analysis probed hypertext linkages among Web pages where discussion was occurring. Sections 214 and 215 of the USA Patriot Act provided a contentious national issue with multiple stakeholders presumed to be attempting to frame issues connected to the two sections. The focus on two sections allowed frame and issue network contrasts to be made. The study sought evidence of an Internet effect to determine whether the Web, through the way people were using it, was having a polarizing, synthesizing, or fragmentizing effect on discussion and debate. Frame overlap and hypertext linkage patterns among actors in the issue networks indicated an overall tendency toward synthesis. The study also probed the degree to which there is a joining, or symbiosis, of Web content and structure, in part evidenced by whether patterns exist that like-minded groups are coming together to form online community through hypertext linkages. Evidence was found to support this conclusion among Web pages in several Internet domains, although questions remain about linking patterns among blogs due to limitations of the software used in the study. Organizational Web sites on average used a similar number of frames compared to other Web page types, including blogs. The organizational Web pages were found to be briefer in how they discussed issues, however. The study contributes to theory by offering the first known empirical study of online community formation and issue advocacy on a matter of public policy and through its finding of a linkage between Web content and Web structure. Methodologically, the study presents a flexible mixed-methods model of descriptive and quantitative approaches that appears excellently suited for Internet studies. The dissertation’s use of fuzzy clustering and discriminant analysis offer important improvements over existing approaches in factor-based frame analysis and frame mapping techniques

Efficient Decoding With Steady-State Kalman Filter in Neural Interface Systems

The Kalman filter is commonly used in neural interface systems to decode neural activity and estimate the desired movement kinematics.We analyze a low-complexity Kalman filter implementation in which the filter gain is approximated by its steady-state form, computed offline before real-time decoding commences. We evaluate its performance using human motor cortical spike train data obtained from an intracortical recording array as part of an ongoing pilot clinical trial. We demonstrate that the standard Kalman filter gain converges to within 95% of the steady-state filter gain in 1.5[plus-over-minus sign]0.5 s (mean[plus-over-minus sign]s.d.) . The difference in the intended movement velocity decoded by the two filters vanishes within 5 s, with a correlation coefficient of 0.99 between the two decoded velocities over the session length. We also find that the steady-state Kalman filter reduces the computational load (algorithm execution time) for decoding the firing rates of 25[plus-over-minus sign]3 single units by a factor of 7.0[plus-over-minus sign]0.9. We expect that the gain in computational efficiency will be much higher in systems with larger neural ensembles. The steady-state filter can thus provide substantial runtime efficiency at little cost in terms of estimation accuracy. This far more efficient neural decoding approach will facilitate the practical implementation of future large-dimensional, multisignal neural interface systems.National Institutes of Health (U.S.) (Grant R01 DC009899)National Institutes of Health (U.S.) (Grant RC1 HD063931)National Institutes of Health (U.S.) (Grant N01 HD053403)National Institutes of Health (U.S.) (Grant 5K01 NS057389)National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant R01-EB006385)United States. Dept. of Veterans Affairs (Office of Research and Development, Rehabilitation R&D Service)Massachusetts General Hospital (Deane Institute for Integrated Research on Atrial Fibrillation and Stroke)Doris Duke Charitable FoundationSpaulding Rehabilitation Hospita

Characteristics, practice patterns, and outcomes in patients with acute hypertension: European registry for Studying the Treatment of Acute hyperTension (Euro-STAT)

Although effective strategies are available for the management of chronic hypertension, less is known about treating patients with acute, severe elevations in blood pressure. Using data from the European registry for Studying the Treatment of Acute hyperTension (Euro-STAT), we sought to evaluate 'real-life' management practices and outcomes in patients who received intravenous antihypertensive therapy to treat an episode of acute hypertension.Journal Articleinfo:eu-repo/semantics/publishe

Conformal fields in the pp-wave limit

The pp-wave (Penrose limit) in conformal field theory can be viewed as a special contraction of the unitary representations of the conformal group. We study the kinematics of conformal fields in this limit in a geometric approach where the effect of the contraction can be visualized as an expansion of space-time. We discuss the two common models of space-time as carrier spaces for conformal fields: One is the usual Minkowski space and the other is the coset of the conformal group over its maximal compact subgroup. We show that only the latter manifold and the corresponding conformal representation theory admit a non-singular contraction limit. We also address the issue of correlation functions of conformal fields in the pp-wave limit. We show that they have a well-defined contraction limit if their space-time dependence merges with the dependence on the coordinates of the R symmetry group. This is a manifestation of the fact that in the limit the space-time and R symmetries become indistinguishable. Our results might find applications in actual calculations of correlation functions of composite operators in N=4 super Yang-Mills theory.Comment: LaTex, 32 pages, 1 figure, discussion of correlation functions extended; some corrections made; references adde

Representations of superconformal algebras in the AdS_7/4/CFT_6/3 correspondence

We perform a general analysis of representations of the superconformal algebras OSp(8/4,R) and OSp(8*/2N) in harmonic superspace. We present a construction of their highest-weight UIR's by multiplication of the different types of massless conformal superfields ("supersingletons"). In particular, all "short multiplets" are classified. Representations undergoing shortening have "protected dimension" and may correspond to BPS states in the dual supergravity theory in anti-de Sitter space. These results are relevant for the classification of multitrace operators in boundary conformally invariant theories as well as for the classification of AdS black holes preserving different fractions of supersymmetry.Comment: To appear in the proceedings of Strings 200

Single-neuron dynamics in human focal epilepsy

Epileptic seizures are traditionally characterized as the ultimate expression of monolithic, hypersynchronous neuronal activity arising from unbalanced runaway excitation. Here we report the first examination of spike train patterns in large ensembles of single neurons during seizures in persons with epilepsy. Contrary to the traditional view, neuronal spiking activity during seizure initiation and spread was highly heterogeneous, not hypersynchronous, suggesting complex interactions among different neuronal groups even at the spatial scale of small cortical patches. In contrast to earlier stages, seizure termination is a nearly homogenous phenomenon followed by an almost complete cessation of spiking across recorded neuronal ensembles. Notably, even neurons outside the region of seizure onset showed significant changes in activity minutes before the seizure. These findings suggest a revision of current thinking about seizure mechanisms and point to the possibility of seizure prevention based on spiking activity in neocortical neurons

HEATR2 Plays a Conserved Role in Assembly of the Ciliary Motile Apparatus

Cilia are highly conserved microtubule-based structures that perform a variety of sensory and motility functions during development and adult homeostasis. In humans, defects specifically affecting motile cilia lead to chronic airway infections, infertility and laterality defects in the genetically heterogeneous disorder Primary Ciliary Dyskinesia (PCD). Using the comparatively simple Drosophila system, in which mechanosensory neurons possess modified motile cilia, we employed a recently elucidated cilia transcriptional RFX-FOX code to identify novel PCD candidate genes. Here, we report characterization of CG31320/HEATR2, which plays a conserved critical role in forming the axonemal dynein arms required for ciliary motility in both flies and humans. Inner and outer arm dyneins are absent from axonemes of CG31320 mutant flies and from PCD individuals with a novel splice-acceptor HEATR2 mutation. Functional conservation of closely arranged RFX-FOX binding sites upstream of HEATR2 orthologues may drive higher cytoplasmic expression of HEATR2 during early motile ciliogenesis. Immunoprecipitation reveals HEATR2 interacts with DNAI2, but not HSP70 or HSP90, distinguishing it from the client/chaperone functions described for other cytoplasmic proteins required for dynein arm assembly such as DNAAF1-4. These data implicate CG31320/HEATR2 in a growing intracellular pre-assembly and transport network that is necessary to deliver functional dynein machinery to the ciliary compartment for integration into the motile axoneme

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Modulation Depth Estimation and Variable Selection in State-Space Models for Neural Interfaces

Rapid developments in neural interface technology are making it possible to record increasingly large signal sets of neural activity. Various factors such as asymmetrical information distribution and across-channel redundancy may, however, limit the benefit of high-dimensional signal sets, and the increased computational complexity may not yield corresponding improvement in system performance. High-dimensional system models may also lead to overfitting and lack of generalizability. To address these issues, we present a generalized modulation depth measure using the state-space framework that quantifies the tuning of a neural signal channel to relevant behavioral covariates. For a dynamical system, we develop computationally efficient procedures for estimating modulation depth from multivariate data. We show that this measure can be used to rank neural signals and select an optimal channel subset for inclusion in the neural decoding algorithm. We present a scheme for choosing the optimal subset based on model order selection criteria. We apply this method to neuronal ensemble spike-rate decoding in neural interfaces, using our framework to relate motor cortical activity with intended movement kinematics. With offline analysis of intracortical motor imagery data obtained from individuals with tetraplegia using the BrainGate neural interface, we demonstrate that our variable selection scheme is useful for identifying and ranking the most information-rich neural signals. We demonstrate that our approach offers several orders of magnitude lower complexity but virtually identical decoding performance compared to greedy search and other selection schemes. Our statistical analysis shows that the modulation depth of human motor cortical single-unit signals is well characterized by the generalized Pareto distribution. Our variable selection scheme has wide applicability in problems involving multisensor signal modeling and estimation in biomedical engineering systems.United States. Dept. of Defense (USAMRAA Cooperative Agreement W81XWH-09-2-0001)United States. Dept. of Veteran Affairs (B6453R)United States. Dept. of Veteran Affairs (A6779I)United States. Dept. of Veteran Affairs (B6310N)United States. Dept. of Veteran Affairs (B6459L)National Institutes of Health (U.S.) (R01 DC009899)National Institutes of Health (U.S.) (RC1 HD063931)National Institutes of Health (U.S.) (N01 HD053403)National Institutes of Health (U.S.) (DP1 OD003646)National Institutes of Health (U.S.) (TR01 GM104948)National Science Foundation (U.S.) (CBET 1159652)Wings for Life Spinal Cord Research FoundationDoris Duke FoundationMGH Neurological Clinical Research InstituteMGH Deane Institute for Integrated Research on Atrial Fibrillation and Strok