Showing papers by "University of Minnesota published in 2004"

Least angle regression

Abstract: The purpose of model selection algorithms such as All Subsets, Forward Selection and Backward Elimination is to choose a linear model on the basis of the same set of data to which the model will be applied. Typically we have available a large collection of possible covariates from which we hope to select a parsimonious set for the efficient prediction of a response variable. Least Angle Regression (LARS), a new model selection algorithm, is a useful and less greedy version of traditional forward selection methods. Three main properties are derived: (1) A simple modification of the LARS algorithm implements the Lasso, an attractive version of ordinary least squares that constrains the sum of the absolute regression coefficients; the LARS modification calculates all possible Lasso estimates for a given problem, using an order of magnitude less computer time than previous methods. (2) A different LARS modification efficiently implements Forward Stagewise linear regression, another promising new model selection method; this connection explains the similar numerical results previously observed for the Lasso and Stagewise, and helps us understand the properties of both methods, which are seen as constrained versions of the simpler LARS algorithm. (3) A simple approximation for the degrees of freedom of a LARS estimate is available, from which we derive a Cp estimate of prediction error; this allows a principled choice among the range of possible LARS estimates. LARS and its variants are computationally efficient: the paper describes a publicly available algorithm that requires only the same order of magnitude of computational effort as ordinary least squares applied to the full set of covariates.

Bariatric surgery: a systematic review and meta-analysis.

Abstract: ContextAbout 5% of the US population is morbidly obese. This disease remains largely refractory to diet and drug therapy, but generally responds well to bariatric surgery.ObjectiveTo determine the impact of bariatric surgery on weight loss, operative mortality outcome, and 4 obesity comorbidities (diabetes, hyperlipidemia, hypertension, and obstructive sleep apnea).Data Sources and Study SelectionElectronic literature search of MEDLINE, Current Contents, and the Cochrane Library databases plus manual reference checks of all articles on bariatric surgery published in the English language between 1990 and 2003. Two levels of screening were used on 2738 citations.Data ExtractionA total of 136 fully extracted studies, which included 91 overlapping patient populations (kin studies), were included for a total of 22 094 patients. Nineteen percent of the patients were men and 72.6% were women, with a mean age of 39 years (range, 16-64 years). Sex was not reported for 1537 patients (8%). The baseline mean body mass index for 16 944 patients was 46.9 (range, 32.3-68.8).Data SynthesisA random effects model was used in the meta-analysis. The mean (95% confidence interval) percentage of excess weight loss was 61.2% (58.1%-64.4%) for all patients; 47.5% (40.7%-54.2%) for patients who underwent gastric banding; 61.6% (56.7%-66.5%), gastric bypass; 68.2% (61.5%-74.8%), gastroplasty; and 70.1% (66.3%-73.9%), biliopancreatic diversion or duodenal switch. Operative mortality (≤30 days) in the extracted studies was 0.1% for the purely restrictive procedures, 0.5% for gastric bypass, and 1.1% for biliopancreatic diversion or duodenal switch. Diabetes was completely resolved in 76.8% of patients and resolved or improved in 86.0%. Hyperlipidemia improved in 70% or more of patients. Hypertension was resolved in 61.7% of patients and resolved or improved in 78.5%. Obstructive sleep apnea was resolved in 85.7% of patients and was resolved or improved in 83.6% of patients.ConclusionsEffective weight loss was achieved in morbidly obese patients after undergoing bariatric surgery. A substantial majority of patients with diabetes, hyperlipidemia, hypertension, and obstructive sleep apnea experienced complete resolution or improvement.

The worldwide leaf economics spectrum

Abstract: Bringing together leaf trait data spanning 2,548 species and 175 sites we describe, for the first time at global scale, a universal spectrum of leaf economics consisting of key chemical, structural and physiological properties. The spectrum runs from quick to slow return on investments of nutrients and dry mass in leaves, and operates largely independently of growth form, plant functional type or biome. Categories along the spectrum would, in general, describe leaf economic variation at the global scale better than plant functional types, because functional types overlap substantially in their leaf traits. Overall, modulation of leaf traits and trait relationships by climate is surprisingly modest, although some striking and significant patterns can be seen. Reliable quantification of the leaf economics spectrum and its interaction with climate will prove valuable for modelling nutrient fluxes and vegetation boundaries under changing land-use and climate.

Evaluating collaborative filtering recommender systems

Abstract: Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering recommender systems: the user tasks being evaluated, the types of analysis and datasets being used, the ways in which prediction quality is measured, the evaluation of prediction attributes other than quality, and the user-based evaluation of the system as a whole. In addition to reviewing the evaluation strategies used by prior researchers, we present empirical results from the analysis of various accuracy metrics on one content domain where all the tested metrics collapsed roughly into three equivalence classes. Metrics within each equivalency class were strongly correlated, while metrics from different equivalency classes were uncorrelated.

IntCal04 terrestrial radiocarbon age calibration, 0-26 cal kyr BP

Abstract: A new calibration curve for the conversion of radiocarbon ages to calibrated (cal) ages has been constructed and internationally ratified to replace IntCal98, which extended from 0-24 cal kyr BP (Before Present, 0 cal BP = AD 1950). The new calibration data set for terrestrial samples extends from 0-26 cal kyr BP, but with much higher resolution beyond 11.4 cal kyr BP than IntCal98. Dendrochronologically-dated tree-ring samples cover the period from 0-12.4 cal kyr BP. Beyond the end of the tree rings, data from marine records (corals and foraminifera) are converted to the atmospheric equivalent with a site-specific marine reservoir correction to provide terrestrial calibration from 12.4-26.0 cal kyr BP. A substantial enhancement relative to IntCal98 is the introduction of a coherent statistical approach based on a random walk model, which takes into account the uncertainty in both the calendar age and the 14C age to calculate the underlying calibration curve (Buck and Blackwell, this issue). The tree-ring data sets, sources of uncertainty, and regional offsets are discussed here. The marine data sets and calibration curve for marine samples from the surface mixed layer (Marine04) are discussed in brief, but details are presented in Hughen et al. (this issue a). We do not make a recommendation for calibration beyond 26 cal kyr BP at this time; however, potential calibration data sets are compared in another paper (van der Plicht et al., this issue).

The Spitzer Space Telescope mission

Abstract: The Spitzer Space Telescope, NASA's Great Observatory for infrared astronomy, was launched 2003 August 25 and is returning excellent scientific data from its Earth-trailing solar orbit. Spitzer combines the intrinsic sensitivity achievable with a cryogenic telescope in space with the great imaging and spectroscopic power of modern detector arrays to provide the user community with huge gains in capability for exploration of the cosmos in the infrared. The observatory systems are largely performing as expected, and the projected cryogenic lifetime is in excess of 5 years. This paper summarizes the on-orbit scientific, technical, and operational performance of Spitzer. Subsequent papers in this special issue describe the Spitzer instruments in detail and highlight many of the exciting scientific results obtained during the first 6 months of the Spitzer mission.

Anterior cingulate conflict monitoring and adjustments in control

Abstract: Conflict monitoring by the anterior cingulate cortex (ACC) has been posited to signal a need for greater cognitive control, producing neural and behavioral adjustments. However, the very occurrence of behavioral adjustments after conflict has been questioned, along with suggestions that there is no direct evidence of ACC conflict-related activity predicting subsequent neural or behavioral adjustments in control. Using the Stroop color-naming task and controlling for repetition effects, we demonstrate that ACC conflict-related activity predicts both greater prefrontal cortex activity and adjustments in behavior, supporting a role of ACC conflict monitoring in the engagement of cognitive control.

Item-based top-N recommendation algorithms

Abstract: The explosive growth of the world-wide-web and the emergence of e-commerce has led to the development of recommender systems---a personalized information filtering technology used to identify a set of items that will be of interest to a certain user. User-based collaborative filtering is the most successful technology for building recommender systems to date and is extensively used in many commercial recommender systems. Unfortunately, the computational complexity of these methods grows linearly with the number of customers, which in typical commercial applications can be several millions. To address these scalability concerns model-based recommendation techniques have been developed. These techniques analyze the user--item matrix to discover relations between the different items and use these relations to compute the list of recommendations.In this article, we present one such class of model-based recommendation algorithms that first determines the similarities between the various items and then uses them to identify the set of items to be recommended. The key steps in this class of algorithms are (i) the method used to compute the similarity between the items, and (ii) the method used to combine these similarities in order to compute the similarity between a basket of items and a candidate recommender item. Our experimental evaluation on eight real datasets shows that these item-based algorithms are up to two orders of magnitude faster than the traditional user-neighborhood based recommender systems and provide recommendations with comparable or better quality.

The problem of overfitting.

Abstract: Model fitting is an important part of all sciences that use quantitative measurements. Experimenters often explore the relationships between measures. Two subclasses of relationship problems are as follows: • Correlation problems: those in which we have a collection of measures, all of interest in their own right, and wish to see how and how strongly they are related. • Regression problems : those in which one of the measures, the dependent Variable, is of special interest, and we wish to explore its relationship with the other variables. These other variables may be called the independent Variables, the predictor Variables, or the coVariates. The dependent variable may be a continuous numeric measure such as a boiling point or a categorical measure such as a classification into mutagenic and nonmutagenic. We should emphasize that using the words ‘correlation problem’ and ‘regression problem’ is not meant to tie these problems to any particular statistical methodology. Having a ‘correlation problem’ does not limit us to conventional Pearson correlation coefficients. Log-linear models, for example, measure the relationship between categorical variables in multiway contingency tables. Similarly, multiple linear regression is a methodology useful for regression problems, but so also are nonlinear regression, neural nets, recursive partitioning and k-nearest neighbors, logistic regression, support vector machines and discriminant analysis, to mention a few. All of these methods aim to quantify the relationship between the predictors and the dependent variable. We will use the term ‘regression problem’ in this conceptual form and, when we want to specialize to multiple linear regression using ordinary least squares, will describe it as ‘OLS regression’. Our focus is on regression problems. We will use y as shorthand for the dependent variable and x for the collection of predictors available. There are two distinct primary settings in which we might want to do a regression study: • Prediction problems:We may want to make predictions of y for future cases where we know x but do not knowy. This for example is the problem faced with the Toxic Substances Control Act (TSCA) list. This list contains many tens of thousands of compounds, and there is a need to identify those on the list that are potentially harmful. Only a small fraction of the list however has any measured biological properties, but all of them can be characterized by chemical descriptors with relative ease. Using quantitative structure-activity relationships (QSARs) fitted to this small fraction to predict the toxicities of the much larger collection is a potentially cost-effective way to try to sort the TSCA compounds by their potential for harm. Later, we will use a data set for predicting the boiling point of a set of compounds on the TSCA list from some molecular descriptors. • Effect quantification:We may want to gain an understanding of how the predictors enter into the relationship that predicts y. We do not necessarily have candidate future unknowns that we want to predict, we simply want to know how each predictor drives the distribution of y. This is the setting seen in drug discovery, where the biological activity y of each in a collection of compounds is measured, along with molecular descriptors x. Finding out which descriptors x are associated with high and which with low biological activity leads to a recipe for new compounds which are high in the features associated positively with activity and low in those associated with inactivity or with adverse side effects. These two objectives are not always best served by the same approaches. ‘Feature selection’ skeeping those features associated withy and ignoring those not associated with y is very commonly a part of an analysis meant for effect quantification but is not necessarily helpful if the objective is prediction of future unknowns. For prediction, methods such as partial least squares (PLS) and ridge regression (RR) that retain all features but rein in their contributions are often found to be more effective than those relying on feature selection. What Is Overfitting? Occam’s Razor, or the principle of parsimony, calls for using models and procedures that contain all that is necessary for the modeling but nothing more. For example, if a regression model with 2 predictors is enough to explainy, then no more than these two predictors should be used. Going further, if the relationship can be captured by a linear function in these two predictors (which is described by 3 numbers sthe intercept and two slopes), then using a quadratic violates parsimony. Overfitting is the use of models or procedures that violate parsimonysthat is, that include more terms than are necessary or use more complicated approaches than are necessary. It is helpful to distinguish two types of overfitting: • Using a model that is more flexible than it needs to be. For example, a neural net is able to accommodate some curvilinear relationships and so is more flexible than a simple linear regression. But if it is used on a data set that conforms to the linear model, it will add a level of complexity without * Corresponding author e-mail: doug@stat.umn.edu. 1 J. Chem. Inf. Comput. Sci. 2004,44, 1-12

CD4+ T Cell Depletion during all Stages of HIV Disease Occurs Predominantly in the Gastrointestinal Tract

Abstract: The mechanisms underlying CD4+ T cell depletion in human immunodeficiency virus (HIV) infection are not well understood. Comparative studies of lymphoid tissues, where the vast majority of T cells reside, and peripheral blood can potentially illuminate the pathogenesis of HIV-associated disease. Here, we studied the effect of HIV infection on the activation and depletion of defined subsets of CD4+ and CD8+ T cells in the blood, gastrointestinal (GI) tract, and lymph node (LN). We also measured HIV-specific T cell frequencies in LNs and blood, and LN collagen deposition to define architectural changes associated with chronic inflammation. The major findings to emerge are the following: the GI tract has the most substantial CD4+ T cell depletion at all stages of HIV disease; this depletion occurs preferentially within CCR5+ CD4+ T cells; HIV-associated immune activation results in abnormal accumulation of effector-type T cells within LNs; HIV-specific T cells in LNs do not account for all effector T cells; and T cell activation in LNs is associated with abnormal collagen deposition. Taken together, these findings define the nature and extent of CD4+ T cell depletion in lymphoid tissue and point to mechanisms of profound depletion of specific T cell subsets related to elimination of CCR5+ CD4+ T cell targets and disruption of T cell homeostasis that accompanies chronic immune activation.

WordNet::Similarity: measuring the relatedness of concepts

Abstract: WordNet::Similarity is a freely available software package that makes it possible to measure the semantic similarity and relatedness between a pair of concepts (or synsets). It provides six measures of similarity, and three measures of relatedness, all of which are based on the lexical database WordNet. These measures are implemented as Perl modules which take as input two concepts, and return a numeric value that represents the degree to which they are similar or related.

Global patterns of plant leaf N and P in relation to temperature and latitude.

Abstract: A global data set including 5,087 observations of leaf nitrogen (N) and phosphorus (P) for 1,280 plant species at 452 sites and of associated mean climate indices demonstrates broad biogeographic patterns. In general, leaf N and P decline and the N/P ratio increases toward the equator as average temperature and growing season length increase. These patterns are similar for five dominant plant groups, coniferous trees and four angiosperm groups (grasses, herbs, shrubs, and trees). These results support the hypotheses that (i) leaf N and P increase from the tropics to the cooler and drier midlatitudes because of temperature-related plant physiological stoichiometry and biogeographical gradients in soil substrate age and then plateau or decrease at high latitudes because of cold temperature effects on biogeochemistry and (ii) the N/P ratio increases with mean temperature and toward the equator, because P is a major limiting nutrient in older tropical soils and N is the major limiting nutrient in younger temperate and high-latitude soils.

Combination of isosorbide dinitrate and hydralazine in blacks with heart failure.

Abstract: background We examined whether a fixed dose of both isosorbide dinitrate and hydralazine provides additional benefit in blacks with advanced heart failure, a subgroup previously noted to have a favorable response to this therapy. methods A total of 1050 black patients who had New York Heart Association class III or IV heart failure with dilated ventricles were randomly assigned to receive a fixed dose of isosorbide dinitrate plus hydralazine or placebo in addition to standard therapy for heart failure. The primary end point was a composite score made up of weighted values for death from any cause, a first hospitalization for heart failure, and change in the quality of life. results The study was terminated early owing to a significantly higher mortality rate in the placebo group than in the group given isosorbide dinitrate plus hydralazine (10.2 percent vs. 6.2 percent, P = 0.02). The mean primary composite score was significantly better in the group given isosorbide dinitrate plus hydralazine than in the placebo group (i0.1±1.9 vs. i0.5±2.0, P=0.01; range of possible values, –6 to +2), as were its individual components (43 percent reduction in the rate of death from any cause [hazard ratio, 0.57; P=0.01] 33 percent relative reduction in the rate of first hospitalization for heart failure [16.4 percent vs. 22.4 percent, P=0.001], and an improvement in the quality of life [change in score, i5.6±20.6 vs. i2.7±21.2, with lower scores indicating better quality of life; P=0.02; range of possible values, 0 to 105]). conclusions The addition of a fixed dose of isosorbide dinitrate plus hydralazine to standard therapy for heart failure including neurohormonal blockers is efficacious and increases survival among black patients with advanced heart failure.

Hybrid Meta Density Functional Theory Methods for Thermochemistry, Thermochemical Kinetics, and Noncovalent Interactions: The MPW1B95 and MPWB1K Models and Comparative Assessments for Hydrogen Bonding and van der Waals Interactions

Abstract: Based on the modified Perdew and Wang exchange functional (MPW) and Becke's 1995 correlation functional (B95), we developed two hybrid meta density functional theory (HMDFT) methods, namely MPW1B95 and MPWB1K. In addition, based on the new X functional of Xin and Goddard, again combined with B95 correlation functional, we developed two other new HMDFT methods, X1B95 and XB1K. MPW1B95 and X1B95 were optimized against a representative database of six atomization energies (AE6). MPWB1K and XB1K were optimized against a kinetics database of three forward barrier heights, three reverse barrier heights, and three energies of reaction for the reactions in the BH6 representative barrier height database. We compared the newly developed methods to other HMDFT and hybrid DFT methods for atomization energies, ionization potentials, electron affinities, barrier heights, saddle point geometries, hydrogen bonding, and weak van der Waals weak interactions. In addition, we optimized scaling factors for calculating zero-po...

Niche tradeoffs, neutrality, and community structure: A stochastic theory of resource competition, invasion, and community assembly

Abstract: Stochastic niche theory resolves many of the differences between neutral theory and classical tradeoff-based niche theories of resource competition and community structure. In stochastic niche theory, invading species become established only if propagules can survive stochastic mortality while growing to maturity on the resources left unconsumed by established species. The theory makes three predictions about community structure. First, stochastic niche assembly creates communities in which species dominate approximately equally wide "slices" of the habitat's spatial heterogeneity. These niche widths generate realistic distributions of species relative abundances for which, contrary to neutral theory but consistent with numerous observations, there are strong correlations among species traits, species abundances, and environmental conditions. Second, slight decreases in resource levels are predicted to cause large decreases in the probability that a propagule would survive to be an adult. These decreases cause local diversity to be limited by the inhibitory effects of resource use by established species on the establishment (recruitment) of potential invaders. If resource pulses or disturbance allowed invaders to overcome this recruitment limitation, many more species could indefinitely coexist. Third, the low invasibility of high diversity communities is predicted to result not from diversity per se, but from the uniformly low levels of resources that occur in high-diversity communities created by stochastic competitive assembly. This prediction provides a potential solution to the invasion paradox, which is the tendency for highly diverse regions to be more heavily invaded.

Personality and transformational and transactional leadership: a meta-analysis.

Abstract: This study was a meta-analysis of the relationship between personality and ratings of transformational and transactional leadership behaviors. Using the 5-factor model of personality as an organizing framework, the authors accumulated 384 correlations from 26 independent studies. Personality traits were related to 3 dimensions of transformational leadership—idealized influence–inspirational motivation (charisma), intellectual stimulation, and individualized consideration—and 3 dimensions of transactional leadership— contingent reward, management by exception–active, and passive leadership. Extraversion was the strongest and most consistent correlate of transformational leadership. Although results provided some support for the dispositional basis of transformational leadership— especially with respect to the charisma dimension— generally, weak associations suggested the importance of future research to focus on both narrower personality traits and nondispositional determinants of transformational and transactional leadership. A recent PsycINFO search revealed that 1,738 of the 15,000 articles (12%) published since 1990 on the topic of leadership included the keywords personality and leadership. Clearly, scholars have a strong and continuing interest in the dispositional bases of leadership behavior. Indeed, a meta-analysis by Lord, DeVader, and Alliger (1986) reported some associations between personality traits and perceptions of leadership. A more recent meta-analysis (Judge, Bono, Ilies, & Gerhardt, 2002) further advanced this literature, providing evidence that some traits were consistently associated with leadership emergence and effectiveness. Although these meta-analyses made an important contribution to our knowledge of the link between personality and leadership, they do not address the relationship between personality and transformational, transactional, and charismatic leadership. Given the volume of recent research attention focused on these types of leadership, it is important to understand the dispositional bases of transformational and transactional leadership. The purpose of this article was to extend what is known about the association between personality and leadership by focusing directly on the relationship between personality and the eight dimensions of transformational and transactional leadership. These leadership dimensions have been found to be valid predictors of follower job performance and satisfaction (see Fuller, Patterson, Hester, & Stringer, 1996; Lowe, Kroeck, & Sivasubramaniam, 1996). Thus, understanding the personality traits associated with transformational and charismatic leadership has important implications for the selection, training, and development of such leaders. For example, if charisma is linked to stable traits of the individual, organizations may wish to select leaders with these traits. Barling, Weber, and Kelloway (1996) demonstrated that some transformational leadership behaviors can be trained. Thus, an understanding of the role of personality can aid in determining which individuals might gain the most from such training and how training approaches might differ on the basis of trainee personality (i.e., aptitude by treatment interaction).

The roles of segmental and tandem gene duplication in the evolution of large gene families in Arabidopsis thaliana

Abstract: Background Most genes in Arabidopsis thaliana are members of gene families. How do the members of gene families arise, and how are gene family copy numbers maintained? Some gene families may evolve primarily through tandem duplication and high rates of birth and death in clusters, and others through infrequent polyploidy or large-scale segmental duplications and subsequent losses.

Mining sequential patterns by pattern-growth: the PrefixSpan approach

Abstract: Sequential pattern mining is an important data mining problem with broad applications. However, it is also a difficult problem since the mining may have to generate or examine a combinatorially explosive number of intermediate subsequences. Most of the previously developed sequential pattern mining methods, such as GSP, explore a candidate generation-and-test approach [R. Agrawal et al. (1994)] to reduce the number of candidates to be examined. However, this approach may not be efficient in mining large sequence databases having numerous patterns and/or long patterns. In this paper, we propose a projection-based, sequential pattern-growth approach for efficient mining of sequential patterns. In this approach, a sequence database is recursively projected into a set of smaller projected databases, and sequential patterns are grown in each projected database by exploring only locally frequent fragments. Based on an initial study of the pattern growth-based sequential pattern mining, FreeSpan [J. Han et al. (2000)], we propose a more efficient method, called PSP, which offers ordered growth and reduced projected databases. To further improve the performance, a pseudoprojection technique is developed in PrefixSpan. A comprehensive performance study shows that PrefixSpan, in most cases, outperforms the a priori-based algorithm GSP, FreeSpan, and SPADE [M. Zaki, (2001)] (a sequential pattern mining algorithm that adopts vertical data format), and PrefixSpan integrated with pseudoprojection is the fastest among all the tested algorithms. Furthermore, this mining methodology can be extended to mining sequential patterns with user-specified constraints. The high promise of the pattern-growth approach may lead to its further extension toward efficient mining of other kinds of frequent patterns, such as frequent substructures.

Introduction to Organic Thin Film Transistors and Design of n-Channel Organic Semiconductors

Abstract: The development of new organic semiconductors with improved performance in organic thin film transistors (OTFTs) is a major challenge for materials chemists. There is a particular need to develop air-stable n-channel (electron-conducting) organic semiconductors with performance comparable to that of p-channel (hole-conducting) materials, for organic electronics to realize the benefits of complementary circuit design, i.e., the ability to switch transistors with either positive or negative gate voltages. There have been significant advancements in the past five years. In terms of standard OTFT metrics such as the field effect mobility (μFET) and on-to-off current ratio (ION/IOFF), n-channel OTFTs have achieved performance comparable both to that of n-channel amorphous silicon TFTs and to that of the best reported p-channel (hole-conducting) OTFTs; however, issues of device stability linger. This review provides a detailed introduction to OTFTs, summarizes recent progress in the development of new n-channel...

Post-translational modification of p53 in tumorigenesis

Abstract: Interest in the tumour suppressor p53 has generated much information regarding the complexity of its function and regulation in carcinogenesis. However, gaps still exist in our knowledge regarding the role of p53 post-translational modifications in carcinogenesis and cancer prevention. A thorough understanding of p53 will be extremely useful in the development of new strategies for treating and preventing cancer, including restoration of p53 function and selective killing of tumours with mutant TP53.

Coronary-Artery Revascularization before Elective Major Vascular Surgery

Abstract: Background The benefit of coronary-artery revascularization before elective major vascular surgery is unclear. Methods We randomly assigned patients at increased risk for perioperative cardiac complications and clinically significant coronary artery disease to undergo either revascularization or no revascularization before elective major vascular surgery. The primary end point was long-term mortality. Results Of 5859 patients scheduled for vascular operations at 18 Veterans Affairs medical centers, 510 (9 percent) were eligible for the study and were randomly assigned to either coronary-artery revascularization before surgery or no revascularization before surgery. The indications for a vascular operation were an expanding abdominal aortic aneurysm (33 percent) or arterial occlusive disease of the legs (67 percent). Among the patients assigned to preoperative coronary-artery revascularization, percutaneous coronary intervention was performed in 59 percent, and bypass surgery was performed in 41 percent. T...

Object Perception as Bayesian Inference

Abstract: We perceive the shapes and material properties of objects quickly and reliably despite the complexity and objective ambiguities of natural images. Typical images are highly complex because they consist of many objects embedded in background clutter. Moreover, the image features of an object are extremely variable and ambiguous owing to the effects of projection, occlusion, background clutter, and illumination. The very success of everyday vision implies neural mechanisms, yet to be understood, that discount irrelevant information and organize ambiguous or noisy local image features into objects and surfaces. Recent work in Bayesian theories of visual perception has shown how complexity may be managed and ambiguity resolved through the task-dependent, probabilistic integration of prior object knowledge with image features.

How do suppliers benefit from information technology use in supply chain relationships

Abstract: Supply chain management systems (SCMS) championed by network leaders in their supplier networks are now ubiquitous. While prior studies have examined the benefits to network leaders from these systems, little attention has been paid to the benefits to supplier firms. This study draws from organizational theories of learning and action and transaction cost theory to propose a model relating suppliers' use of SCMS to benefits. It proposes that two patterns of SCMS use by suppliers-exploitation and exploration-create contexts for suppliers to make relationship-specific investments in business processes and domain knowledge. These, in turn, enable suppliers to both create value and retain a portion of the value created by the use of these systems in interfirm relationships. Data from 131 suppliers using an SCMS implemented by one large retailer support hypotheses that relationship-specific intangible investments play a mediating role linking SCMS use to benefits. Evidence that patterns of information technology use are significant determinants of relationship-specific investments in business processes and domain expertise provides a finer-grained explanation of the logic of IT-enabled electronic integration. The results support the vendors-to-partners thesis that IT deployments in supply chains lead to closer buyer-supplier relationships (Bakos and Brynjyolfsson 1993). The results also suggest the complementarity of the transaction-cost and resource-based views, elaborating the logic by which specialized assets can also be strategic assets.

Heading for disaster: Fusarium graminearum on cereal crops.

Abstract: SUMMARY The rapid global re-emergence of Fusarium head blight disease of wheat and barley in the last decade along with contamination of grains with mycotoxins attributable to the disease have spurred basic research on the fungal causal agent. As a result, Fusarium graminearum quickly has become one of the most intensively studied fungal plant pathogens. This review briefly summarizes current knowledge on the pathogenicity, population genetics, evolution and genomics of Fusarium graminearum. Taxonomy: Based on the sexual state Gibberella zeae (Schwein.) Petch: Superkingdom Eukaryota; Kingdom Fungi; Phylum Ascomycota; Subphylum Pezizomycotina; Class Sordariomycetidae; Subclass Hypocreomycetidae; Order Hypocreales; Family Nectriaceae; Genus Gibberella. Host range: The pathogen is capable of causing head blight or ‘scab’ on wheat (Triticum), barley (Hordeum), rice (Oryza), oats (Avena) and Gibberella stalk and ear rot disease on maize (Zea). The fungus also may infect other plant species without causing disease symptoms. Other host genera cited for Gibberella zeae or F. graminearum sensu lato (see below) are Agropyron, Agrostis, Bromus, Calamagrostis, Cenchrus, Cortaderia, Cucumis, Echinochloa, Glycine, Hierochloe, Lolium, Lycopersicon, Medicago, Phleum, Poa, Schizachyrium, Secale, Setaria, Sorghum, Spartina and Trifolium. Disease symptoms and signs: For wheat, brown, dark purple to black necrotic lesions form on the exterior surface of the florets and glume (Fig. 1). Although these lesion symptoms sometimes are referred to as scab, they are not formally related to the hyperplasia and hypertrophic epidermal growth associated with other scab diseases such as apple scab. Peduncles immediately below the inflorescence may become discoloured brown/purple. With time, tissue of the inflorescence often becomes blighted, appearing bleached and tan, while the grain within atrophies. Awns often become deformed, twisted and curved downward. In barley, infections are not always readily apparent in the field. Infected spikelets may show a browning or water-soaked appearance. Infected barley kernels show a tan to dark brown discolouration that can be similar to that caused by other kernel blighting organisms. During prolonged wet periods, pink to salmon-orange spore masses of the fungus are often seen on infected spikelets, glumes and kernels in both wheat and barley. For maize ear rot, infection occurs by way of colonizing silk and thus symptoms first appear at the ear apex. White mycelium, turning pink to red with time, colonizes kernels and may progress basipetally, covering the entire ear. Figure 1. Field-grown wheat inflorescence showing symptoms of Fusarium head blight. The third spikelet from the bottom shows a darkened necrotic lesion (‘scab’) whereas the second and fifth spikelets demonstrate tissue bleaching (‘blight’) symptoms. Photograph courtesy of Jacki Morrison, USDA ARS Cereal Disease Laboratory. Useful websites: http://www.broad.mit.edu/annotation/fungi/fusarium/mips.gsf.de/genre/proj/fusarium/ http://www.cdl.umn.edu/scab/gz-consort.html http://www.scabusa.org/

Timing, Duration, and Transitions of the Last Interglacial Asian Monsoon

Abstract: Thorium-230 ages and oxygen isotope ratios of stalagmites from Dongge Cave, China, characterize the Asian Monsoon and low-latitude precipitation over the past 160,000 years. Numerous abrupt changes in 18O/16O values result from changes in tropical and subtropical precipitation driven by insolation and millennial-scale circulation shifts. The Last Interglacial Monsoon lasted 9.7 +/- 1.1 thousand years, beginning with an abrupt (less than 200 years) drop in 18O/16O values 129.3 +/- 0.9 thousand years ago and ending with an abrupt (less than 300 years) rise in 18O/16O values 119.6 +/- 0.6 thousand years ago. The start coincides with insolation rise and measures of full interglacial conditions, indicating that insolation triggered the final rise to full interglacial conditions.