A numerical study of Richtmyer–Meshkov instability in continuously stratified fluids

Theory and calculations are presented for the evolution of Richtmyer–Meshkov instability in two-dimensional continuously stratified fluid layers. The initial acceleration and subsequent instability of the fluid layer are induced by means of an impulsive pressure distribution. The subsequent dynamics of the fluid layer are then calculated numerically using the incompressible equations of motion. Initial conditions representing single-scale perturbations and multiple-scale random perturbations are considered. It is found that the growth rates for Richtmyer–Meshkov instability of stratified fluid layers are substantially lower than those predicted by Richtmyer for a sharp fluid interface with an equivalent jump in density. A frozen field approximation for the early-time dynamics of the instability is proposed, and shown to approximate the initial behavior of the layer over a time equivalent to the traversal of several layer thicknesses. It is observed that the nonlinear development of the instability results in the formation of plumes of penetrating fluid. Late in the process, the initial momentum deposited by the impulse is primarily used in the internal mixing of the layer rather than in the overall growth of the stratified layer. At intermediate times, some evidence for the existence of scaling behavior in the width of the mixing layer of the instability is observed for the multiple-scale random perturbations, but not for the single-scale perturbations. The time variation of the layer thickness differs from the scaling derived using ideas of self-similarity due to Barenblatt [Non-Linear Dynamics and Turbulence, edited by G. I. Barenblatt, G. Ioos, and D. D. Joseph (Pitman, Boston, 1983), p. 48] even at low Atwood ratio, presumably because of the inhomogeneity and anisotropy due to the excitation of vortical plumes

Mixing and non-mixing local minima of the entropy contrast for blind source separation

In this paper, both non-mixing and mixing local minima of the entropy are analyzed from the viewpoint of blind source separation (BSS); they correspond respectively to acceptable and spurious solutions of the BSS problem. The contribution of this work is twofold. First, a Taylor development is used to show that the \textit{exact} output entropy cost function has a non-mixing minimum when this output is proportional to \textit{any} of the non-Gaussian sources, and not only when the output is proportional to the lowest entropic source. Second, in order to prove that mixing entropy minima exist when the source densities are strongly multimodal, an entropy approximator is proposed. The latter has the major advantage that an error bound can be provided. Even if this approximator (and the associated bound) is used here in the BSS context, it can be applied for estimating the entropy of any random variable with multimodal density.Comment: 11 pages, 6 figures, To appear in IEEE Transactions on Information Theor

Effective Approaches to Attention-based Neural Machine Translation

An attentional mechanism has lately been used to improve neural machine translation (NMT) by selectively focusing on parts of the source sentence during translation. However, there has been little work exploring useful architectures for attention-based NMT. This paper examines two simple and effective classes of attentional mechanism: a global approach which always attends to all source words and a local one that only looks at a subset of source words at a time. We demonstrate the effectiveness of both approaches over the WMT translation tasks between English and German in both directions. With local attention, we achieve a significant gain of 5.0 BLEU points over non-attentional systems which already incorporate known techniques such as dropout. Our ensemble model using different attention architectures has established a new state-of-the-art result in the WMT'15 English to German translation task with 25.9 BLEU points, an improvement of 1.0 BLEU points over the existing best system backed by NMT and an n-gram reranker.Comment: 11 pages, 7 figures, EMNLP 2015 camera-ready version, more training detail

The collective consciousness of Information Technology research: The significance and value of research projects. A. The views of IT researchers

This research seeks to reveal the different perceptual worlds in a research community, with the longterm intent of fostering increased understanding and hence collaboration. In the relatively new field of information technology (IT) research, available evidence suggests that a shared understanding of the research object or territory does not yet exist. This has led to the development of different perceptions amongst IT researchers of what constitutes significant and valuable research. A phenomenological approach is used to elicit data from a diverse range of IT researchers in semistructured interviews. This data is presented to show (1) the variation in meaning associated with the idea of significance and value and (2) the awareness structures through which participants experience significance and value. An Outcome Space represents the interrelation between those different ways of seeing, revealing a widening awareness. Five categories of ways of seeing the significance and value of research projects were found: The Personal Goals Conception, The Research Currency Conception, The Design of the Research Project Conception, The Outcomes for the Technology End User Conception and The Solving Real-World Problems Conception. These are situated within three wider perceptual boundaries: The Individual, The Research Community and Humankind. The categories are described in detail, demonstrated with participants’ quotes and illustrated with diagrams. A tentative comparison is made between this project and a similar investigation of IT professionals’ ways of seeing the significance and value of IT research projects. Finally, some recommendations for further research are made

The collective consciousness of Information Technology research: The significance and value of research projects. B. The views of IT industry professionals

This research seeks to reveal the different perceptual worlds in a research community, with the longterm intent of fostering increased understanding and hence collaboration. In the relatively new field of information technology (IT) research, available evidence suggests that a shared understanding of the research object or territory does not yet exist. This has led to the development of different perceptions amongst IT researchers of what constitutes significant and valuable research. Phenomenological methodology is used to elicit data from a diverse range of IT industry professionals in semi-structured interviews. This data is presented to show (1) the variation in meaning associated with the idea of significance and value and (2) the awareness structures through which participants experience significance and value. An Outcome Space represents the interrelation between those different ways of seeing, revealing a widening awareness. Five categories of ways of seeing the significance and value of research projects were found: The Personal Goals Conception, The Commercial Goals Conception, The Outcomes for the Technology End User Conception, The Solving Real-World Problems Conception and The Design of the Research Project Conception. These are situated within three wider perceptual boundaries: The Individual, The Enterprise and Society. The categories are described in detail, demonstrated with participants’ quotes and illustrated with diagrams. A tentative comparison is made between this project and a similar investigation of IT researchers’ ways of seeing the significance and value of IT research projects. Finally, some recommendations for further research are made

The Collective Consciousness of Information Technology Research: Ways of seeing Information Technology Research: Its Objects and Territories

The collective consciousness of effective groups of researchers is characterised by shared understandings of their research object or territory. In the relatively new field of information technology research, rapid expansion and fragmentation of the territory has led to different perceptions about what constitutes information technology research. This project explores a facet of the collective consciousness of disparate groups of researchers and lays a foundation for constructing shared research objects. Making IT researchers’ ways of seeing explicit may help us understand some of the complexities associated with inter and intra disciplinary collaboration amongst research groups, and the complexities associated with technology transfer to industry. This report analyses IT research, its objects and territories, as they are constituted by IT researchers associated with the sub-disciplines of information systems, computer science and information security. A phenomenographic approach is used to elicit data from a diverse range of IT researchers in semistructured interviews. This data is analysed to show (1) the variation in meaning associated with the idea of IT research and (2) the awareness structures through which participants experience variation in ways of seeing the object and territories of IT research. An Outcome Space represents the interrelation between different ways of seeing the territory. Eight ways of seeing IT research, its objects and territories, were found: The Technology Conception, The Information Conception, The Information and Technology Conception, The Communication Conception, The Ubiquitous Conception, The Sanctioned Conception, The Dialectic Conception and The Constructed Conception. These are described in detail and illustrated with participants’ quotes. Finally, some recommendations for further research are made

Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach

Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are essential in determining the cell's fate. Here our goal is the identification of perturbed pathways from high-throughput gene expression data. We develop a three-level hierarchical model, where (i) the first level captures the relationship between gene expression and biological pathways using confirmatory factor analysis, (ii) the second level models the behavior within an underlying network of pathways induced by an unknown perturbation using a conditional autoregressive model, and (iii) the third level is a spike-and-slab prior on the perturbations. We then identify perturbations through posterior-based variable selection. We illustrate our approach using gene transcription drug perturbation profiles from the DREAM7 drug sensitivity predication challenge data set. Our proposed method identified regulatory pathways that are known to play a causative role and that were not readily resolved using gene set enrichment analysis or exploratory factor models. Simulation results are presented assessing the performance of this model relative to a network-free variant and its robustness to inaccuracies in biological databases

Hypocretin-1 receptors regulate the reinforcing and reward-enhancing effects of cocaine: pharmacological and behavioral genetics evidence.

Considerable evidence suggests that transmission at hypocretin-1 (orexin-1) receptors (Hcrt-R1) plays an important role in the reinstatement of extinguished cocaine-seeking behaviors in rodents. However, far less is known about the role for hypocretin transmission in regulating ongoing cocaine-taking behavior. Here, we investigated the effects of the selective Hcrt-R1 antagonist SB-334867 on cocaine intake, as measured by intravenous (IV) cocaine self-administration in rats. The stimulatory effects of cocaine on brain reward systems contribute to the establishment and maintenance of cocaine-taking behaviors. Therefore, we also assessed the effects of SB-334867 on the reward-enhancing properties of cocaine, as measured by cocaine-induced lowering of intracranial self-stimulation (ICSS) thresholds. Finally, to definitively establish a role for Hcrt-R1 in regulating cocaine intake, we assessed IV cocaine self-administration in Hcrt-R1 knockout mice. We found that SB-334867 (1-4 mg/kg) dose-dependently decreased cocaine (0.5 mg/kg/infusion) self-administration in rats but did not alter responding for food rewards under the same schedule of reinforcement. This suggests that SB-334867 decreased cocaine reinforcement without negatively impacting operant performance. SB-334867 (1-4 mg/kg) also dose-dependently attenuated the stimulatory effects of cocaine (10 mg/kg) on brain reward systems, as measured by reversal of cocaine-induced lowering of ICSS thresholds in rats. Finally, we found that Hcrt-R1 knockout mice self-administered far less cocaine than wildtype mice across the entire dose-response function. These data demonstrate that Hcrt-R1 play an important role in regulating the reinforcing and reward-enhancing properties of cocaine and suggest that hypocretin transmission is likely essential for establishing and maintaining the cocaine habit in human addicts

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

BACKGROUND: Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. RESULTS: S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. CONCLUSIONS: This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved.Published versio