Showing papers by "University of Texas at Austin published in 2007"
TL;DR: The research strategy of theory building from cases, particularly multiple cases, involves using one or more cases to create theoretical constructs, propositions, and/or midrange theory from case-based, empirical evidence.
Abstract: This article discusses the research strategy of theory building from cases, particularly multiple cases. Such a strategy involves using one or more cases to create theoretical constructs, propositions, and/or midrange theory from case-based, empirical evidence. Replication logic means that each case serves as a distinct experiment that stands on its own merits as an analytic unit. The frequent use of case studies as a research strategy has given rise to some challenges that can be mitigated by the use of very precise wording and thoughtful research design.
13,581 citations
Ewan Birney, John A. Stamatoyannopoulos1, Anindya Dutta2, Roderic Guigó3 +317 more•Institutions (44)
TL;DR: Functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project are reported, providing convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts.
Abstract: We report the generation and analysis of functional data from multiple, diverse experiments performed on a targeted 1% of the human genome as part of the pilot phase of the ENCODE Project. These data have been further integrated and augmented by a number of evolutionary and computational analyses. Together, our results advance the collective knowledge about human genome function in several major areas. First, our studies provide convincing evidence that the genome is pervasively transcribed, such that the majority of its bases can be found in primary transcripts, including non-protein-coding transcripts, and those that extensively overlap one another. Second, systematic examination of transcriptional regulation has yielded new understanding about transcription start sites, including their relationship to specific regulatory sequences and features of chromatin accessibility and histone modification. Third, a more sophisticated view of chromatin structure has emerged, including its inter-relationship with DNA replication and transcriptional regulation. Finally, integration of these new sources of information, in particular with respect to mammalian evolution based on inter- and intra-species sequence comparisons, has yielded new mechanistic and evolutionary insights concerning the functional landscape of the human genome. Together, these studies are defining a path for pursuit of a more comprehensive characterization of human genome function.
5,091 citations
University of Vermont1, University of Minnesota2, University of Texas at Austin3, Hong Kong University of Science and Technology4, Osaka University5, University of Queensland6, Griffith University7, University of Illinois at Chicago8, IBM9, Nanjing University10, Imperial College London11, University of Salford12
TL;DR: This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART.
Abstract: This paper presents the top 10 data mining algorithms identified by the IEEE International Conference on Data Mining (ICDM) in December 2006: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. These top 10 algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These 10 algorithms cover classification, clustering, statistical learning, association analysis, and link mining, which are all among the most important topics in data mining research and development.
4,944 citations
TL;DR: A meta-analysis of the results shows that early math skills have the greatest predictive power, followed by reading and then attention skills, while measures of socioemotional behaviors were generally insignificant predictors of later academic performance.
Abstract: Using 6 longitudinal data sets, the authors estimate links between three key elements of school readiness--school-entry academic, attention, and socioemotional skills--and later school reading and math achievement In an effort to isolate the effects of these school-entry skills, the authors ensured that most of their regression models control for cognitive, attention, and socioemotional skills measured prior to school entry, as well as a host of family background measures Across all 6 studies, the strongest predictors of later achievement are school-entry math, reading, and attention skills A meta-analysis of the results shows that early math skills have the greatest predictive power, followed by reading and then attention skills By contrast, measures of socioemotional behaviors, including internalizing and externalizing problems and social skills, were generally insignificant predictors of later academic performance, even among children with relatively high levels of problem behavior Patterns of association were similar for boys and girls and for children from high and low socioeconomic backgrounds
4,384 citations
TL;DR: An improvement to the grid‐based algorithm of Henkelman et al. for the calculation of Bader volumes is suggested, which more accurately calculates atomic properties as predicted by the theory of Atoms in Molecules, resulting in a more robust method of partitioning charge density among atoms in the system.
Abstract: An improvement to the grid-based algorithm of Henkelman et al. for the calculation of Bader volumes is suggested, which more accurately calculates atomic properties as predicted by the theory of Atoms in Molecules. The CPU time required by the improved algorithm to perform the Bader analysis scales linearly with the number of interatomic surfaces in the system. The new algorithm corrects systematic deviations from the true Bader surface, calculated by the original method and also does not require explicit representation of the interatomic surfaces, resulting in a more robust method of partitioning charge density among atoms in the system. Applications of the method to some small systems are given and it is further demonstrated how the method can be used to define an energy per atom in ab initio calculations.
2,999 citations
Los Alamos National Laboratory1, University of Texas at Austin2, United States Department of Energy3, Argonne National Laboratory4, Oak Ridge National Laboratory5, Case Western Reserve University6, Virginia Tech7, Doshisha University8, University of Yamanashi9, Yokohama National University10, Kyoto University11, New Energy and Industrial Technology Development Organization12, Tokyo Institute of Technology13, National Institute of Advanced Industrial Science and Technology14
TL;DR: The research focuses on the durability of polymer electrolyte fuel cells (PEFCs), in particular, membrane degradation, and he has been involved in NEDO R&D research projects on PEFC durability since 2001.
Abstract: Rod Borup is a Team Leader in the fuel cell program at Los Alamos National Lab in Los Alamos, New Mexico. He received his B.S.E. in Chemical Engineering from the University of Iowa in 1988 and his Ph.D. from the University of Washington in 1993. He has worked on fuel cell technology since 1994, working in the areas of hydrogen production and PEM fuel cell stack components. He has been awarded 12 U.S. patents, authored over 40 papers related to fuel cell technology, and presented over 50 oral papers at national meetings. His current main research area is related to water transport in PEM fuel cells and PEM fuel cell durability. Recently, he was awarded the 2005 DOE Hydrogen Program R&D Award for the most significant R&D contribution of the year for his team's work in fuel cell durability and was the Principal Investigator for the 2004 Fuel Cell Seminar (San Antonio, TX, USA) Best Poster Award. Jeremy Meyers is an Assistant Professor of materials science and engineering and mechanical engineering at the University of Texas at Austin, where his research focuses on the development of electrochemical energy systems and materials. Prior to joining the faculty at Texas, Jeremy workedmore » as manager of the advanced transportation technology group at UTC Power, where he was responsible for developing new system designs and components for automotive PEM fuel cell power plants. While at UTC Power, Jeremy led several customer development projects and a DOE-sponsored investigation into novel catalysts and membranes for PEM fuel cells. Jeremy has coauthored several papers on key mechanisms of fuel cell degradation and is a co-inventor of several patents. In 2006, Jeremy and several colleagues received the George Mead Medal, UTC's highest award for engineering achievement, and he served as the co-chair of the Gordon Research Conference on fuel cells. Jeremy received his Ph.D. in Chemical Engineering from the University of California at Berkeley and holds a Bachelor's Degree in Chemical Engineering from Stanford University. Bryan Pivovar received his B.S. in Chemical Engineering from the University of Wisconsin in 1994. He completed his Ph.D. in Chemical Engineering at the University of Minnesota in 2000 under the direction of Profs. Ed Cussler and Bill Smyrl, studying transport properties in fuel cell electrolytes. He continued working in the area of polymer electrolyte fuel cells at Los Alamos National Laboratory as a post-doc (2000-2001), as a technical staff member (2001-2005), and in his current position as a team leader (2005-present). In this time, Bryan's research has expanded to include further aspects of fuel cell operation, including electrodes, subfreezing effects, alternative polymers, hydroxide conductors, fuel cell interfaces, impurities, water transport, and high-temperature membranes. Bryan has served at various levels in national and international conferences and workshops, including organizing a DOE sponsored workshop on freezing effects in fuel cells and an ARO sponsored workshop on alkaline membrane fuel cells, and he was co-chair of the 2007 Gordon Research Conference on Fuel Cells. Minoru Inaba is a Professor at the Department of Molecular Science and Technology, Faculty of Engineering, Doshisha University, Japan. He received his B.Sc. from the Faculty of Engineering, Kyoto University, in 1984 and his M.Sc. in 1986 and his Dr. Eng. in 1995 from the Graduate School of Engineering, Kyoto University. He has worked on electrochemical energy conversion systems including fuel cells and lithium-ion batteries at Kyoto University (1992-2002) and at Doshisha University (2002-present). His primary research interest is the durability of polymer electrolyte fuel cells (PEFCs), in particular, membrane degradation, and he has been involved in NEDO R&D research projects on PEFC durability since 2001. He has authored over 140 technical papers and 30 review articles. Kenichiro Ota is a Professor of the Chemical Energy Laboratory at the Graduate School of Engineering, Yokohama National University, Japan. He received his B.S.E. in Applied Chemistry from the University of Tokyo in 1968 and his Ph.D. from the University of Tokyo in 1973. He has worked on hydrogen energy and fuel cells since 1974, working on materials science for fuel cells and water electrolysis. He has published more than 150 original papers, 70 review papers, and 50 scientific books. He is now the president of the Hydrogen Energy Systems Society of Japan, the chairman of the Fuel Cell Research Group of the Electrochemical Society of Japan, and the chairman of the National Committee for the Standardization of the Stationary Fuel Cells. ABSTRACT TRUNCATED« less
2,921 citations
TL;DR: In this paper, a coherent data-generating process (DGP) is described for nonparametric estimates of productive efficiency on environmental variables in two-stage procedures to account for exogenous factors that might affect firms’ performance.
2,915 citations
TL;DR: In this article, the square root of the Laplacian (−△) 1/2 operator was obtained from the harmonic extension problem to the upper half space as the operator that maps the Dirichlet boundary condition to the Neumann condition.
Abstract: The operator square root of the Laplacian (−△) 1/2 can be obtained from the harmonic extension problem to the upper half space as the operator that maps the Dirichlet boundary condition to the Neumann condition. In this paper we obtain similar characterizations for general fractional powers of the Laplacian and other integro-differential operators. From those characterizations we derive some properties of these integro-differential equations from purely local arguments in the extension problems.
2,696 citations
20 Jun 2007
TL;DR: An information-theoretic approach to learning a Mahalanobis distance function that can handle a wide variety of constraints and can optionally incorporate a prior on the distance function and derive regret bounds for the resulting algorithm.
Abstract: In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the distance function. We express this problem as a particular Bregman optimization problem---that of minimizing the LogDet divergence subject to linear constraints. Our resulting algorithm has several advantages over existing methods. First, our method can handle a wide variety of constraints and can optionally incorporate a prior on the distance function. Second, it is fast and scalable. Unlike most existing methods, no eigenvalue computations or semi-definite programming are required. We also present an online version and derive regret bounds for the resulting algorithm. Finally, we evaluate our method on a recent error reporting system for software called Clarify, in the context of metric learning for nearest neighbor classification, as well as on standard data sets.
2,058 citations
Princeton University1, Goddard Space Flight Center2, University of Texas at Austin3, University of Toronto4, Johns Hopkins University5, Cornell University6, University of British Columbia7, University of Chicago8, Brown University9, University of Pennsylvania10, University of California, Los Angeles11
TL;DR: In this article, the authors presented a model of polarized foreground emission that captures the large angular scale characteristics of the microwave sky and analyzed the 3-year full-sky maps of the polarization and cosmological implications.
Abstract: The Wilkinson Microwave Anisotropy Probe (WMAP) has mapped the entire sky in five frequency bands between 23 and 94 GHz with polarization-sensitive radiometers. We present 3 year full-sky maps of the polarization and analyze them for foreground emission and cosmological implications. These observations open up a new window for understanding how the universe began and help set a foundation for future observations. WMAP observes significant levels of polarized foreground emission due to both Galactic synchrotron radiation and thermal dust emission. Synchrotron radiation is the dominant signal at l < 50 and ν 40 GHz, while thermal dust emission is evident at 94 GHz. The least contaminated channel is at 61 GHz. We present a model of polarized foreground emission that captures the large angular scale characteristics of the microwave sky. After applying a Galactic mask that cuts 25.7% of the sky, we show that the high Galactic latitude rms polarized foreground emission, averaged over l = 4-6, ranges from ≈5 μK at 22 GHz to 0.6 μK at 61 GHz. By comparison, the levels of intrinsic CMB polarization for a ΛCDM model with an optical depth of τ = 0.09 and assumed tensor-to-scalar ratio r = 0.3 are ≈0.3 μK for E-mode polarization and ≈0.1 μK for B-mode polarization. To analyze the maps for CMB polarization at l < 16, we subtract a model of the foreground emission that is based primarily on a scaling WMAP's 23 GHz map. In the foreground-corrected maps, we detect l(l + 1)C/2π = 0.086 ± 0.029 (μK)2. This is interpreted as the result of rescattering of the CMB by free electrons released during reionization at zr = 10.9 for a model with instantaneous reionization. By computing the likelihood of just the EE data as a function of τ we find τ = 0.10 ± 0.03. When the same EE data are used in the full six-parameter fit to all WMAP data (TT, TE, EE), we find τ = 0.09 ± 0.03. Marginalization over the foreground subtraction affects this value by δτ < 0.01. We see no evidence for B modes, limiting them to l(l + 1)C/2π = -0.04 ± 0.03 (μK)2. We perform a template fit to the E-mode and B-mode data with an approximate model for the tensor scalar ratio. We find that the limit from the polarization signals alone is r < 2.2 (95% CL), where r is evaluated at k = 0.002 Mpc-1. This corresponds to a limit on the cosmic density of gravitational waves of ΩGWh2 < 5 × 10-12. From the full WMAP analysis, we find r < 0.55 (95% CL) corresponding to a limit of ΩGWh2 < 1 × 10-12 (95% CL). The limit on r is approaching the upper bound of predictions for some of the simplest models of inflation, r ~ 0.3.
1,969 citations
TL;DR: The pseudospin associated with the valley index of carriers has an intrinsic magnetic moment, in close analogy with the Bohr magneton for the electron spin, forming the basis for the valley-based electronics applications.
Abstract: We investigate physical properties that can be used to distinguish the valley degree of freedom in systems where inversion symmetry is broken, using graphene systems as examples. We show that the pseudospin associated with the valley index of carriers has an intrinsic magnetic moment, in close analogy with the Bohr magneton for the electron spin. There is also a valley dependent Berry phase effect that can result in a valley contrasting Hall transport, with carriers in different valleys turning into opposite directions transverse to an in-plane electric field. These effects can be used to generate and detect valley polarization by magnetic and electric means, forming the basis for the valley-based electronics applications.
University of Colorado Denver1, Boston Children's Hospital2, Emory University3, Harvard University4, University of Texas at Austin5, University of Texas Southwestern Medical Center6, Cornell University7, Tulane University8, Primary Children's Hospital9, University of Pennsylvania10, University of New Mexico11, Children's Hospital Oakland Research Institute12, University of Hawaii at Manoa13, Children's Hospital of Orange County14, Oregon Health & Science University15, Children's Memorial Hospital16, Palmetto Health Richland17, Centers for Disease Control and Prevention18
TL;DR: Prophylaxis with recombinant factor VIII can prevent joint damage and decrease the frequency of joint and other hemorrhages in young boys with severe hemophilia A.
Abstract: Sixty-five boys younger than 30 months of age were randomly assigned to prophylaxis (32 boys) or enhanced episodic therapy (33 boys). When the boys reached 6 years of age, 93% of those in the prophylaxis group and 55% of those in the episodic-therapy group were considered to have normal index-joint structure on MRI (P = 0.006). The relative risk of MRI-detected joint damage with episodic therapy as compared with prophylaxis was 6.1 (95% confidence interval, 1.5 to 24.4). The mean annual numbers of joint and total hemorrhages were higher at study exit in the episodic-therapy group than in the prophylaxis group (P<0.001 for both comparisons). High titers of inhibitors of factor VIII developed in two boys who received prophylaxis; three boys in the episodic-therapy group had a life-threatening hemorrhage. Hospitalizations and infections associated with central-catheter placement did not differ significantly between the two groups. Conclusions Prophylaxis with recombinant factor VIII can prevent joint damage and decrease the frequency of joint and other hemorrhages in young boys with severe hemophilia A. (ClinicalTrials.gov number, NCT00207597.)
TL;DR: This paper examined whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns and found that the fraction of negative words in firm-specific news stories predicts low firm earnings.
Abstract: We examine whether a simple quantitative measure of language can be used to predict individual firms' accounting earnings and stock returns. Our three main findings are: (1) the fraction of negative words in firm-specific news stories forecasts low firm earnings; (2) firms' stock prices briefly underreact to the information embedded in negative words; and (3) the earnings and return predictability from negative words is largest for the stories that focus on fundamentals. Together these findings suggest that linguistic media content captures otherwise hard-to-quantify aspects of firms' fundamentals, which investors quickly incorporate in stock prices.
TL;DR: A rigorous convergence analysis is provided and exponential convergence of the “probability error” with respect to the number of Gauss points in each direction in the probability space is demonstrated, under some regularity assumptions on the random input data.
Abstract: In this paper we propose and analyze a stochastic collocation method to solve elliptic partial differential equations with random coefficients and forcing terms (input data of the model). The input data are assumed to depend on a finite number of random variables. The method consists in a Galerkin approximation in space and a collocation in the zeros of suitable tensor product orthogonal polynomials (Gauss points) in the probability space and naturally leads to the solution of uncoupled deterministic problems as in the Monte Carlo approach. It can be seen as a generalization of the stochastic Galerkin method proposed in [I. Babuscka, R. Tempone, and G. E. Zouraris, SIAM J. Numer. Anal., 42 (2004), pp. 800-825] and allows one to treat easily a wider range of situations, such as input data that depend nonlinearly on the random variables, diffusivity coefficients with unbounded second moments, and random variables that are correlated or even unbounded. We provide a rigorous convergence analysis and demonstrate exponential convergence of the “probability error” with respect to the number of Gauss points in each direction in the probability space, under some regularity assumptions on the random input data. Numerical examples show the effectiveness of the method.
TL;DR: This article investigated the relationship between two types of change-oriented leadership (transformational leadership and managerial openness) and subordinate improvement-oriented voice in a two-phase study and found that openness is more consistently related to voice, given controls for numerous individual differences in subordinates' personality, satisfaction, and job demography.
Abstract: We investigate the relationships between two types of change-oriented leadership (transformational leadership and managerial openness) and subordinate improvement-oriented voice in a two-phase study. Findings from 3,149 employees and 223 managers in a restaurant chain indicate that openness is more consistently related to voice, given controls for numerous individual differences in subordinates’ personality, satisfaction, and job demography. This relationship is shown to be mediated by subordinate perceptions of psychological safety, illustrating the importance of leaders in subordinate assessments of the risks of speaking up. Also, leadership behaviors have the strongest impact on the voice behavior of the best-performing employees.
TL;DR: Although there remain many unanswered questions, particularly regarding the mechanisms by which electrical conduction through CPs affects cells, there is already compelling evidence to demonstrate the significant impact that CPs are starting to make in the biomedical field.
TL;DR: The authors found that self-compassion helps buffer against anxiety when faced with an ego-threat in a laboratory setting, and that increases in selfcompassion occurring over a one-month interval were associated with increased psychological well-being.
TL;DR: In this article, the authors show that standard asymptotics based on the number of groups going to infinity provide a poor approximation to the finite sample distribution and propose simple two-step estimators for these cases.
Abstract: We examine inference in panel data when the number of groups is small, as is typically the case for difference-in-differences estimation and when some variables are fixed within groups. In this case, standard asymptotics based on the number of groups going to infinity provide a poor approximation to the finite sample distribution. We show that in some cases the t-statistic is distributed as t and propose simple two-step estimators for these cases. We apply our analysis to two well-known papers. We confirm our theoretical analysis with Monte Carlo simulations.
University of California, Berkeley1, Bryn Mawr College2, Food and Agriculture Organization3, San Francisco State University4, University of Rochester5, York University6, University of Reading7, University of Virginia8, University of Bayreuth9, University of Montana10, University of California, Davis11, University of Texas at Austin12, University of Göttingen13, University of California, Santa Barbara14
TL;DR: A conceptual model for exploring how one mobile-agent-based ecosystem service (MABES), pollination, is affected by land-use change, and then generalize the model to other MABES is developed.
Abstract: Many ecosystem services are delivered by organisms that depend on habitats that are segregated spatially or temporally from the location where services are provided. Management of mobile organisms contributing to ecosystem services requires consideration not only of the local scale where services are delivered, but also the distribution of resources at the landscape scale, and the foraging ranges and dispersal movements of the mobile agents. We develop a conceptual model for exploring how one such mobile-agent-based ecosystem service (MABES), pollination, is affected by land-use change, and then generalize the model to other MABES. The model includes interactions and feedbacks among policies affecting land use, market forces and the biology of the organisms involved. Animal-mediated pollination contributes to the production of goods of value to humans such as crops; it also bolsters reproduction of wild plants on which other services or service-providing organisms depend. About onethird of crop production depends on animal pollinators, while 60–90% of plant species require an animal pollinator. The sensitivity of mobile organisms to ecological factors that operate across spatial scales makes the services provided by a given community of mobile agents highly contextual. Services vary, depending on the spatial and temporal distribution of resources surrounding the site, and on biotic interactions occurring locally, such as competition among pollinators for resources, and among plants for pollinators. The value of the resulting goods or services may feed back via market-based forces to influence land-use policies, which in turn influence land management practices that alter local habitat conditions and landscape structure. Developing conceptual
TL;DR: In this article, the authors studied the problem of finding the optimal regularity result for the contact set of a function ϕ and s ∈ (0, 1) when ϕ is C 1,s or smoother, and showed that the solution u is in the space c 1,α for every α < s.
Abstract: Given a function ϕ and s ∈ (0, 1), we will study the solutions of the following obstacle problem: • u ≥ ϕ in R n , • (−� ) s u ≥ 0i nR n , • (−� ) s u(x) = 0 for those x such that u(x )>ϕ (x), • lim|x|→+∞ u(x) = 0. We show that when ϕ is C 1,s or smoother, the solution u is in the space C 1,α for every α< s. In the case where the contact set {u = ϕ} is convex, we prove the optimal regularity result u ∈ C 1,s . When ϕ is only C 1,β for a β< s, we prove that our solution u is C 1,α for every α< β. c � 2006 Wiley Periodicals, Inc.
TL;DR: A review of living ring-opening metathesis polymerization (ROMP) reactions can be found in this article, along with a discussion of state-of-the-art catalysts for use in living ROMP reactions as well as opportunities for the future.
TL;DR: In this article, the effects of task-related and bio-demographic diversity at the group-level were meta-analyzed to test the hypothesis of synergistic performance resulting from diverse employee teams.
TL;DR: In this paper, a meta-analysis spanning 203 species was conducted on published datasets from the northern hemisphere, showing that the difference in estimated response is primarily due to differences between the studies in criteria for incorporating data.
Abstract: New analyses are presented addressing the global impacts of recent climate change on phenology of plant and animal species. A meta-analysis spanning 203 species was conducted on published datasets from the northern hemisphere. Phenological response was examined with respect to two factors: distribution of species across latitudes and taxonomic affiliation or functional grouping of target species. Amphibians had a significantly stronger shift toward earlier breeding than all other taxonomic/functional groups, advancing more than twice as fast as trees, birds and butterflies. In turn, butterfly emergence or migratory arrival showed three times stronger advancement than the first flowering of herbs, perhaps portending increasing asynchrony in insect‐plant interactions. Response was significantly stronger at higher latitudes where warming has been stronger, but latitude explained o4% of the variation. Despite expectation, latitude was not yet an important predictor of climate change impacts on phenology. The only two previously published estimates of the magnitude of global response are quite different: 2.3 and 5.1daysdecade 1 advancement. The scientific community has assumed this difference to be real and has attempted to explain it in terms of biologically relevant phenomena: specifically, differences in distribution of data across latitudes, taxa or time periods. Here, these and other possibilities are explored. All analyses indicate that the difference in estimated response is primarily due to differences between the studies in criteria for incorporating data. It is a clear and automatic consequence of the exclusion by one study of data on ‘stable’ (nonresponsive) species. Once this is accounted for, the two studies support each other, generating similar conclusions despite analyzing substantially nonoverlapping datasets. Analyses here on a new expanded dataset estimate an overall spring advancement across the northern hemisphere of 2.8daysdecade 1 . This is the first quantitative analysis showing that data-sampling methodologies significantly impact global (synthetic) estimates of magnitude of global warming response.
TL;DR: Using APEX, it is demonstrated that 73% of the variance in yeast protein abundance is explained by mRNA abundance, with the number of proteins per mRNA log-normally distributed about ∼5,600 (∼540 in E. coli) protein molecules/mRNA.
Abstract: We report a method for large-scale absolute protein expression measurements (APEX) and apply it to estimate the relative contributions of transcriptional- and translational-level gene regulation in the yeast and Escherichia coli proteomes. APEX relies upon correcting each protein's mass spectrometry sampling depth (observed peptide count) by learned probabilities for identifying the peptides. APEX abundances agree with measurements from controls, western blotting, flow cytometry and two-dimensional gels, as well as known correlations with mRNA abundances and codon bias, providing absolute protein concentrations across approximately three to four orders of magnitude. Using APEX, we demonstrate that 73% of the variance in yeast protein abundance (47% in E. coli) is explained by mRNA abundance, with the number of proteins per mRNA log-normally distributed about approximately 5,600 ( approximately 540 in E. coli) protein molecules/mRNA. Therefore, levels of both eukaryotic and prokaryotic proteins are set per mRNA molecule and independently of overall protein concentration, with >70% of yeast gene expression regulation occurring through mRNA-directed mechanisms.
University of California, Santa Cruz1, University of Arizona2, University of Oxford3, Lawrence Berkeley National Laboratory4, Seoul National University5, University of California, Berkeley6, Princeton University7, University of Texas at Austin8, Max Planck Society9, University of Chicago10, National Taiwan University11, University of Florida12, University of Virginia13, Herzberg Institute of Astrophysics14, Johns Hopkins University15, New Mexico State University16
TL;DR: The DEEP2 and COMBO-17 surveys are compared to study luminosity functions of red and blue galaxies to z ~ 1, and the results imply that the number and total stellar mass of blue galaxies have been substantially constant since z = 1, whereas those of red galaxies (near L*) have been significantly rising as mentioned in this paper.
Abstract: The DEEP2 and COMBO-17 surveys are compared to study luminosity functions of red and blue galaxies to z ~ 1. The two surveys have different methods and sensitivities, but nevertheless results agree. After z ~ 1, M has dimmed by 1.2-1.3 mag for all colors of galaxies, * for blue galaxies has hardly changed, and * for red galaxies has at least doubled (our formal value is ~0.5 dex). Luminosity density jB has fallen by 0.6 dex for blue galaxies but has remained nearly constant for red galaxies. These results imply that the number and total stellar mass of blue galaxies have been substantially constant since z ~ 1, whereas those of red galaxies (near L*) have been significantly rising. To explain the new red galaxies, a ``mixed'' scenario is proposed in which star formation in blue cloud galaxies is quenched, causing them to migrate to the red sequence, where they merge further in a small number of stellar mergers. This mixed scenario matches the local boxy-disky transition for nearby ellipticals, as well as red sequence stellar population scaling laws such as the color-magnitude and Mg-? relations (which are explained as fossil relics from blue progenitors). Blue galaxies enter the red sequence via different quenching modes, each of which peaks at a different characteristic mass and time. The red sequence therefore likely builds up in different ways at different times and masses, and the concept of a single process that is ``downsizing'' (or upsizing) probably does not apply. Our claim in this paper of a rise in the number of red galaxies applies to galaxies near L*. Accurate counts of brighter galaxies on the steep part of the Schechter function require more accurate photometry than is currently available.
TL;DR: Multi-user MIMO (MU-MIMO) networks reveal the unique opportunities arising from a joint optimization of antenna combining techniques with resource allocation protocols, and brings robustness with respect to multipath richness, yielding the diversity and multiplexing gains without the need for multiple antenna user terminals.
Abstract: Multi-user MIMO (MU-MIMO) networks reveal the unique opportunities arising from a joint optimization of antenna combining techniques with resource allocation protocols. Furthermore, it brings robustness with respect to multipath richness, allowing for compact antenna spacing at the BS and, crucially, yielding the diversity and multiplexing gains without the need for multiple antenna user terminals. To realize these gains, however, the BS should be informed with the user's channel coefficients, which may limit practical application to TDD or low-mobility settings. To circumvent this problem and reduce feedback load, combining MU-MIMO with opportunistic scheduling seems a promising direction. The success for this type of scheduler is strongly traffic and QoS-dependent, however.
TL;DR: If microbial cellulose can be successfully mass produced, it will eventually become a vital biomaterial and will be used in the creation of a wide variety of medical devices and consumer products.
TL;DR: This paper develops a fast high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria, and demonstrates that the algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis, and gene network analysis.
Abstract: A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods - in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective We exploit this equivalence to develop a fast high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs Previous multilevel graph partitioning methods such as Metis have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis, and gene network analysis
Goddard Space Flight Center1, University of Toronto2, Johns Hopkins University3, Cornell University4, Princeton University5, University of British Columbia6, University of Texas at Austin7, University of Chicago8, Brown University9, University of Pennsylvania10, University of California, Los Angeles11
TL;DR: In this article, the authors presented new full-sky temperature maps in five frequency bands from 23 to 94 GHz, based on data from the first 3 years of the WMAP sky survey.
Abstract: We present new full-sky temperature maps in five frequency bands from 23 to 94 GHz, based on data from the first 3 years of the WMAP sky survey. The new maps are consistent with the first-year maps and are more sensitive. The 3 year maps incorporate several improvements in data processing made possible by the additional years of data and by a more complete analysis of the polarization signal. These include several new consistency tests as well as refinements in the gain calibration and beam response models. We employ two forms of multifrequency analysis to separate astrophysical foreground signals from the CMB, each of which improves on our first-year analyses. First, we form an improved "Internal Linear Combination" (ILC) map, based solely on WMAP data, by adding a bias-correction step and by quantifying residual uncertainties in the resulting map. Second, we fit and subtract new spatial templates that trace Galactic emission; in particular, we now use low-frequency WMAP data to trace synchrotron emission instead of the 408 MHz sky survey. The WMAP point source catalog is updated to include 115 new sources whose detection is made possible by the improved sky map sensitivity. We derive the angular power spectrum of the temperature anisotropy using a hybrid approach that combines a maximum likelihood estimate at low l (large angular scales) with a quadratic cross-power estimate for l > 30. The resulting multifrequency spectra are analyzed for residual point source contamination. At 94 GHz the unmasked sources contribute 128 ± 27 μK2 to l(l + 1)Cl/2π at l = 1000. After subtracting this contribution, our best estimate of the CMB power spectrum is derived by averaging cross-power spectra from 153 statistically independent channel pairs. The combined spectrum is cosmic variance limited to l = 400, and the signal-to-noise ratio per l-mode exceeds unity up to l = 850. For bins of width Δl/l = 3%, the signal-to-noise ratio exceeds unity up to l = 1000. The first two acoustic peaks are seen at l = 220.8 ± 0.7 and l = 530.9 ± 3.8, respectively, while the first two troughs are seen at l = 412.4 ± 1.9 and l = 675.2 ± 11.1. The rise to the third peak is unambiguous; when the WMAP data are combined with higher resolution CMB measurements, the existence of a third acoustic peak is well established. Spergel et al. use the 3 year temperature and polarization data to constrain cosmological model parameters. A simple six-parameter ΛCDM model continues to fit CMB data and other measures of large-scale structure remarkably well. The new polarization data produce a better measurement of the optical depth to reionization, τ = 0.089 ± 0.03. This new and tighter constraint on τ helps break a degeneracy with the scalar spectral index, which is now found to be ns = 0.960 ± 0.016. If additional cosmological data sets are included in the analysis, the spectral index is found to be ns = 0.947 ± 0.015.
TL;DR: In this article, the authors examined the relation of self-compassion to positive psychological health and the Wve factor model of personality and found that selfcompassion had a signi cant positive association with self-reported measures of happiness, optimism, positive aVect, wisdom, personal initiative, curiosity and exploration, agreeableness, extroversion, and conscientiousness.