Showing papers by "University of Illinois at Urbana–Champaign published in 2007"

Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques

Abstract: The many different techniques for maximum power point tracking of photovoltaic (PV) arrays are discussed. The techniques are taken from the literature dating back to the earliest methods. It is shown that at least 19 distinct methods have been introduced in the literature, with many variations on implementation. This paper should serve as a convenient reference for future work in PV power generation.

Occurrence, genotoxicity, and carcinogenicity of regulated and emerging disinfection by-products in drinking water: a review and roadmap for research.

Abstract: Disinfection by-products (DBPs) are formed when disinfectants (chlorine, ozone, chlorine dioxide, or chloramines) react with naturally occurring organic matter, anthropogenic contaminants, bromide, and iodide during the production of drinking water. Here we review 30 years of research on the occurrence, genotoxicity, and carcinogenicity of 85 DBPs, 11 of which are currently regulated by the U.S., and 74 of which are considered emerging DBPs due to their moderate occurrence levels and/or toxicological properties. These 74 include halonitromethanes, iodo-acids and other unregulated halo-acids, iodo-trihalomethanes (THMs), and other unregulated halomethanes, halofuranones (MX [3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone] and brominated MX DBPs), haloamides, haloacetonitriles, tribromopyrrole, aldehydes, and N-nitrosodimethylamine (NDMA) and other nitrosamines. Alternative disinfection practices result in drinking water from which extracted organic material is less mutagenic than extracts of chlorinated water. However, the levels of many emerging DBPs are increased by alternative disinfectants (primarily ozone or chloramines) compared to chlorination, and many emerging DBPs are more genotoxic than some of the regulated DBPs. Our analysis identified three categories of DBPs of particular interest. Category 1 contains eight DBPs with some or all of the toxicologic characteristics of human carcinogens: four regulated (bromodichloromethane, dichloroacetic acid, dibromoacetic acid, and bromate) and four unregulated DBPs (formaldehyde, acetaldehyde, MX, and NDMA). Categories 2 and 3 contain 43 emerging DBPs that are present at moderate levels (sub- to low-mug/L): category 2 contains 29 of these that are genotoxic (including chloral hydrate and chloroacetaldehyde, which are also a rodent carcinogens); category 3 contains the remaining 14 for which little or no toxicological data are available. In general, the brominated DBPs are both more genotoxic and carcinogenic than are chlorinated compounds, and iodinated DBPs were the most genotoxic of all but have not been tested for carcinogenicity. There were toxicological data gaps for even some of the 11 regulated DBPs, as well as for most of the 74 emerging DBPs. A systematic assessment of DBPs for genotoxicity has been performed for approximately 60 DBPs for DNA damage in mammalian cells and 16 for mutagenicity in Salmonella. A recent epidemiologic study found that much of the risk for bladder cancer associated with drinking water was associated with three factors: THM levels, showering/bathing/swimming (i.e., dermal/inhalation exposure), and genotype (having the GSTT1-1 gene). This finding, along with mechanistic studies, highlights the emerging importance of dermal/inhalation exposure to the THMs, or possibly other DBPs, and the role of genotype for risk for drinking-water-associated bladder cancer. More than 50% of the total organic halogen (TOX) formed by chlorination and more than 50% of the assimilable organic carbon (AOC) formed by ozonation has not been identified chemically. The potential interactions among the 600 identified DBPs in the complex mixture of drinking water to which we are exposed by various routes is not reflected in any of the toxicology studies of individual DBPs. The categories of DBPs described here, the identified data gaps, and the emerging role of dermal/inhalation exposure provide guidance for drinking water and public health research.

Framing, Agenda Setting, and Priming: The Evolution of Three Media Effects Models

Abstract: This special issue of Journal of Communication is devoted to theoretical explanations of news framing, agenda setting, and priming effects. It examines if and how the three models are related and what potential relationships between them tell theorists and researchers about the effects of mass media. As an introduction to this effort, this essay provides a very brief review of the three effects and their roots in media-effects research. Based on this overview, we highlight a few key dimensions along which one can compare, framing, agenda setting, and priming. We conclude with a description of the contexts within which the three models operate, and the broader implications that these conceptual distinctions have for the growth of our discipline. doi:10.1111/j.1460-2466.2006.00326.x In 1997, Republican pollster Frank Luntz sent out a 222-page memo called ‘‘Language of the 21st century’’ to select members of the U.S. Congress. Parts of the memo soon spread among staffers, members of Congress, and also journalists. Luntz’s message was simple: ‘‘It’s not what you say, it’s how you say it’’ (Luntz, in press). Drawing on various techniques for real-time message testing and focus grouping, Frank Luntz had researched Republican campaign messages and distilled terms and phrases that resonated with specific interpretive schemas among audiences and therefore helped shift people’s attitudes. In other words, the effect of the messages was not a function of content differences but of differences in the modes of presentation. The ideas outlined in the memo were hardly new, of course, and drew on decades of existing research in sociology (Goffman, 1974), economics (Kahneman & Tversky, 1979), psychology (Kahneman & Tversky, 1984), cognitive linguistics (Lakoff, 2004), and communication (Entman, 1991; Iyengar, 1991). But Frank Luntz was the first professional pollster to systematically use the concept of framing as a campaign tool. The Democratic Party soon followed and George Lakoff published Don’t Think of an

Graph Embedding and Extensions: A General Framework for Dimensionality Reduction

Abstract: A large family of algorithms - supervised or unsupervised; stemming from statistics or geometry theory - has been designed to provide different solutions to the problem of dimensionality reduction Despite the different motivations of these algorithms, we present in this paper a general formulation known as graph embedding to unify them within a common framework In graph embedding, each algorithm can be considered as the direct graph embedding or its linear/kernel/tensor extension of a specific intrinsic graph that describes certain desired statistical or geometric properties of a data set, with constraints from scale normalization or a penalty graph that characterizes a statistical or geometric property that should be avoided Furthermore, the graph embedding framework can be used as a general platform for developing new dimensionality reduction algorithms By utilizing this framework as a tool, we propose a new supervised dimensionality reduction algorithm called marginal Fisher analysis in which the intrinsic graph characterizes the intraclass compactness and connects each data point with its neighboring points of the same class, while the penalty graph connects the marginal points and characterizes the interclass separability We show that MFA effectively overcomes the limitations of the traditional linear discriminant analysis algorithm due to data distribution assumptions and available projection directions Real face recognition experiments show the superiority of our proposed MFA in comparison to LDA, also for corresponding kernel and tensor extensions

Putting the S back in corporate social responsibility: A multilevel theory of social change in organizations

Abstract: We provide a multilevel theoretical model to understand why business organizations are increasingly engaging in corporate social responsibility (CSR) initiatives and thereby exhibiting the potential to exert positive social change. Our model integrates theories of organizational justice, corporate governance, and varieties of capitalism to argue that organizations are pressured to engage in CSR by many different actors, each driven by instrumental, relational, and moral motives. We conclude by highlighting empirical questions for future research and discussing some managerial implications. Economic progress, through a fair and open world trading system is essential to tackle poverty and ensure a safer more secure world for everyone now and for future generations. The challenges remain of ensuring that the benefits of that progress reach all sectors in all countries and are not at the expense of the environment (Sir Stephen Timms, U.K. Minister for CSR, Royal In

Estimation of total phenolic content and other oxidation substrates in plant tissues using Folin-Ciocalteu reagent.

Abstract: Non-structural phenolic compounds perform a variety of functions in plants, including acting as antioxidants. We describe a microplate-adapted colorimetric total phenolics assay that utilizes Folin-Ciocalteu (F-C) reagent. The F-C assay relies on the transfer of electrons in alkaline medium from phenolic compounds to phosphomolybdic/phosphotungstic acid complexes, which are determined spectroscopically at 765 nm. Although the electron transfer reaction is not specific for phenolic compounds, the extraction procedure eliminates approximately 85% of ascorbic acid and other potentially interfering compounds. This assay is performed in microcentrifuge tubes and assessed in a 96-well plate reader. At least 64 samples can be processed in 1 d.

The Power of Personality: The Comparative Validity of Personality Traits, Socioeconomic Status, and Cognitive Ability for Predicting Important Life Outcomes:

Abstract: The ability of personality traits to predict im- portant life outcomes has traditionally been questioned because of the putative small effects of personality. In this article, we compare the predictive validity of personality traits with that of socioeconomic status (SES) and cogni- tive ability to test the relative contribution of personality traits to predictions of three critical outcomes: mortality, divorce, andoccupationalattainment.Onlyevidence from prospective longitudinal studies was considered. In addi- tion, an attempt was made to limit the review to studies that controlled for important background factors. Results showed that the magnitude of the effects of personality traits on mortality, divorce, and occupational attainment wasindistinguishablefrom the effectsofSES and cognitive ability on these outcomes. These results demonstrate the influence of personality traits on important life outcomes, highlight the need to more routinely incorporate measures of personality into quality of life surveys, and encourage further research about the developmental origins of per- sonality traits and the processes by which these traits in- fluence diverse life outcomes.

The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions.

Abstract: This review summarizes current understanding of the mechanisms that underlie the response of photosynthesis and stomatal conductance to elevated carbon dioxide concentration ([CO2]), and examines how downstream processes and environmental constraints modulate these two fundamental responses. The results from free-air CO2 enrichment (FACE) experiments were summarized via meta-analysis to quantify the mean responses of stomatal and photosynthetic parameters to elevated [CO2]. Elevation of [CO2] in FACE experiments reduced stomatal conductance by 22%, yet, this reduction was not associated with a similar change in stomatal density. Elevated [CO2] stimulated light-saturated photosynthesis (Asat) in C3 plants grown in FACE by an average of 31%. However, the magnitude of the increase in Asat varied with functional group and environment. Functional groups with ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco)-limited photosynthesis at elevated [CO2] had greater potential for increases in Asat than those where photosynthesis became ribulose-1,5-bisphosphate (RubP)-limited at elevated [CO2]. Both nitrogen supply and sink capacity modulated the response of photosynthesis to elevated [CO2] through their impact on the acclimation of carboxylation capacity. Increased understanding of the molecular and biochemical mechanisms by which plants respond to elevated [CO2], and the feedback of environmental factors upon them, will improve our ability to predict ecosystem responses to rising [CO2] and increase our potential to adapt crops and managed ecosystems to future atmospheric [CO2].

Pyrosequencing enumerates and contrasts soil microbial diversity

Abstract: Estimates of the number of species of bacteria per gram of soil vary between 2000 and 8.3 million (Gans et al., 2005; Schloss and Handelsman, 2006). The highest estimate suggests that the number may be so large as to be impractical to test by amplification and sequencing of the highly conserved 16S rRNA gene from soil DNA (Gans et al., 2005). Here we present the use of high throughput DNA pyrosequencing and statistical inference to assess bacterial diversity in four soils across a large transect of the western hemisphere. The number of bacterial 16S rRNA sequences obtained from each site varied from 26,140 to 53,533. The most abundant bacterial groups in all four soils were the Bacteroidetes, Betaproteobacteria and Alphaproteobacteria. Using three estimators of diversity, the maximum number of unique sequences (operational taxonomic units roughly corresponding to the species level) never exceeded 52,000 in these soils at the lowest level of dissimilarity. Furthermore, the bacterial diversity of the forest soil was phylum rich compared to the agricultural soils, which are species rich but phylum poor. The forest site also showed far less diversity of the Archaea with only 0.009% of all sequences from that site being from this group as opposed to 4%-12% of the sequences from the three agricultural sites. This work is the most comprehensive examination to date of bacterial diversity in soil and suggests that agricultural management of soil may significantly influence the diversity of bacteria and archaea.

Google news personalization: scalable online collaborative filtering

Abstract: Several approaches to collaborative filtering have been studied but seldom have studies been reported for large (several millionusers and items) and dynamic (the underlying item set is continually changing) settings. In this paper we describe our approach to collaborative filtering for generating personalized recommendations for users of Google News. We generate recommendations using three approaches: collaborative filtering using MinHash clustering, Probabilistic Latent Semantic Indexing (PLSI), and covisitation counts. We combine recommendations from different algorithms using a linear model. Our approach is content agnostic and consequently domain independent, making it easily adaptable for other applications and languages with minimal effort. This paper will describe our algorithms and system setup in detail, and report results of running the recommendations engine on Google News.

Frequent pattern mining: current status and future directions

Abstract: Frequent pattern mining has been a focused theme in data mining research for over a decade. Abundant literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to numerous research frontiers, such as sequential pattern mining, structured pattern mining, correlation mining, associative classification, and frequent pattern-based clustering, as well as their broad applications. In this article, we provide a brief overview of the current status of frequent pattern mining and discuss a few promising research directions. We believe that frequent pattern mining research has substantially broadened the scope of data analysis and will have deep impact on data mining methodologies and applications in the long run. However, there are still some challenging research issues that need to be solved before frequent pattern mining can claim a cornerstone approach in data mining applications.

Self-healing materials with microvascular networks

Abstract: Self-healing polymers composed of microencapsulated healing agents exhibit remarkable mechanical performance and regenerative ability, but are limited to autonomic repair of a single damage event in a given location. Self-healing is triggered by crack-induced rupture of the embedded capsules; thus, once a localized region is depleted of healing agent, further repair is precluded. Re-mendable polymers can achieve multiple healing cycles, but require external intervention in the form of heat treatment and applied pressure. Here, we report a self-healing system capable of autonomously repairing repeated damage events. Our bio-inspired coating-substrate design delivers healing agent to cracks in a polymer coating via a three-dimensional microvascular network embedded in the substrate. Crack damage in the epoxy coating is healed repeatedly. This approach opens new avenues for continuous delivery of healing agents for self-repair as well as other active species for additional functionality.

Trajectory clustering: a partition-and-group framework

Abstract: Existing trajectory clustering algorithms group similar trajectories as a whole, thus discovering common trajectories. Our key observation is that clustering trajectories as a whole could miss common sub-trajectories. Discovering common sub-trajectories is very useful in many applications, especially if we have regions of special interest for analysis. In this paper, we propose a new partition-and-group framework for clustering trajectories, which partitions a trajectory into a set of line segments, and then, groups similar line segments together into a cluster. The primary advantage of this framework is to discover common sub-trajectories from a trajectory database. Based on this partition-and-group framework, we develop a trajectory clustering algorithm TRACLUS. Our algorithm consists of two phases: partitioning and grouping. For the first phase, we present a formal trajectory partitioning algorithm using the minimum description length(MDL) principle. For the second phase, we present a density-based line-segment clustering algorithm. Experimental results demonstrate that TRACLUS correctly discovers common sub-trajectories from real trajectory data.

The use of logit and probit models in strategic management research: Critical issues

Abstract: The logit and probit models have become critical parts of the management researcher's analytical arsenal, growing rapidly from almost no use in the 1980s to appearing in 15% of all articles published in Strategic Management Journal in 2005. However, a review of three top strategy journals revealed numerous areas in their use and interpretation where current practice fell short of ideal. Failure to understand how these models differ from ordinary least squares can lead researchers to misunderstand their statistical results and draw incorrect conclusions regarding the theory they are testing. Based on a review of the methodological literature and recent empirical papers in three leading strategy journals, this paper identifies four critical issues in their use: interpreting coefficients, modeling interactions between variables, comparing coefficients between groups (e.g., foreign and domestic firms), and measures of model fit. For each issue, the paper provides a background, a review of current practice, and recommendations for best practice. A concluding section presents overall implications for the conduct of research with logit and probit models, which should assist both authors and readers of strategic management research. Copyright © 2007 John Wiley & Sons, Ltd.

Exploring Intuition and its Role in Managerial Decision Making

Abstract: We review and reconceptualize “intuition,” defining intuitions as affectively charged judgments that arise through rapid, nonconscious, and holistic associations. In doing so, we delineate intuition from other decision-making approaches (e.g., insight, rational). We also develop a model and propositions that incorporate the role of domain knowledge, implicit and explicit learning, and task characteristics on intuition effectiveness. We close by suggesting directions for future research on intuition and its applications to managerial decision making. The human brain can be a magnificent synthesizer of disparate pieces of nebulous information, and often formal techniques and procedures thwart and inhibit this mysterious mechanism from operating efficiently (Raiffa, 1968: 272).

High-resolution electrohydrodynamic jet printing

Abstract: Efforts to adapt and extend graphic arts printing techniques for demanding device applications in electronics, biotechnology and microelectromechanical systems have grown rapidly in recent years. Here, we describe the use of electrohydrodynamically induced fluid flows through fine microcapillary nozzles for jet printing of patterns and functional devices with submicrometre resolution. Key aspects of the physics of this approach, which has some features in common with related but comparatively low-resolution techniques for graphic arts, are revealed through direct high-speed imaging of the droplet formation processes. Printing of complex patterns of inks, ranging from insulating and conducting polymers, to solution suspensions of silicon nanoparticles and rods, to single-walled carbon nanotubes, using integrated computer-controlled printer systems illustrates some of the capabilities. High-resolution printed metal interconnects, electrodes and probing pads for representative circuit patterns and functional transistors with critical dimensions as small as 1 μm demonstrate potential applications in printed electronics.

Barcodes: The persistent topology of data

Abstract: This article surveys recent work of Carlsson and collaborators on applications of computational algebraic topology to problems of feature detection and shape recognition in high-dimensional data. The primary mathematical tool considered is a homology theory for point-cloud data sets — persistent homology — and a novel representation of this algebraic characterization — barcodes. We sketch an application of these techniques to the classification of natural images. 1. The shape of data When a topologist is asked, “How do you visualize a four-dimensional object?” the appropriate response is a Socratic rejoinder: “How do you visualize a threedimensional object?” We do not see in three spatial dimensions directly, but rather via sequences of planar projections integrated in a manner that is sensed if not comprehended. We spend a significant portion of our first year of life learning how to infer three-dimensional spatial data from paired planar projections. Years of practice have tuned a remarkable ability to extract global structure from representations in a strictly lower dimension. The inference of global structure occurs on much finer scales as well, with regards to converting discrete data into continuous images. Dot-matrix printers, scrolling LED tickers, televisions, and computer displays all communicate images via arrays of discrete points which are integrated into coherent, global objects. This also is a skill we have practiced from childhood. No adult does a dot-to-dot puzzle with anything approaching anticipation. 1.1. Topological data analysis. Problems of data analysis share many features with these two fundamental integration tasks: (1) how does one infer high dimensional structure from low dimensional representations; and (2) how does one assemble discrete points into global structure. The principal themes of this survey of the work of Carlsson, de Silva, Edelsbrunner, Harer, Zomorodian, and others are the following: (1) It is beneficial to replace a set of data points with a family of simplicial complexes, indexed by a proximity parameter. This converts the data set into global topological objects. (2) It is beneficial to view these topological complexes through the lens of algebraic topology — specifically, via a novel theory of persistent homology adapted to parameterized families. (3) It is beneficial to encode the persistent homology of a data set in the form of a parameterized version of a Betti number: a barcode. The author gratefully acknowledges the support of DARPA # HR0011-07-1-0002. The work reviewed in this article is funded by the DARPA program TDA: Topological Data Analysis.

MadGraph/MadEvent v4: the new web generation

Abstract: We present the latest developments of the MadGraph/MadEvent Monte Carlo event generator and several applications to hadron collider physics. In the current version events at the parton, hadron and detector level can be generated directly from a web interface, for arbitrary processes in the Standard Model and in several physics scenarios beyond it (HEFT, MSSM, 2HDM). The most important additions are: a new framework for implementing user-defined new physics models; a standalone running mode for creating and testing matrix elements; generation of events corresponding to different processes, such as signal(s) and backgrounds, in the same run; two platforms for data analysis, where events are accessible at the parton, hadron and detector level; and the generation of inclusive multi-jet samples by combining parton-level events with parton showers. To illustrate the new capabilities of the package some applications to hadron collider physics are presented: 1) Higgs search in pp \to H \to W^+W^-: signal and backgrounds. 2) Higgs CP properties: pp \to H jj$in the HEFT. 3) Spin of a new resonance from lepton angular distributions. 4) Single-top and Higgs associated production in a generic 2HDM. 5) Comparison of strong SUSY pair production at the SPS points. 6) Inclusive W+jets matched samples: comparison with the Tevatron data. Comment: 38 pages, 15 figures

Twenty years of research on cytokine-induced sickness behavior

Abstract: Cytokine-induced sickness behavior was recognized within a few years of the cloning and expression of interferon-α, IL-1 and IL-2, which occurred around the time that the first issue of Brain, Behavior, and Immunity was published in 1987. Phase I clinical trials established that injection of recombinant cytokines into cancer patients led to a variety of psychological disturbances. It was subsequently shown that physiological concentrations of proinflammatory cytokines that occur after infection act in the brain to induce common symptoms of sickness, such as loss of appetite, sleepiness, withdrawal from normal social activities, fever, aching joints and fatigue. This syndrome was defined as sickness behavior and is now recognized to be part of a motivational system that reorganizes the organism’s priorities to facilitate recovery from the infection. Cytokines convey to the brain that an infection has occurred in the periphery, and this action of cytokines can occur via the traditional endocrine route via the blood or by direct neural transmission via the afferent vagus nerve. The finding that sickness behavior occurs in all mammals and birds indicates that communication between the immune system and brain has been evolutionarily conserved and forms an important physiological adaptive response that favors survival of the organism during infections. The fact that cytokines act in the brain to induce physiological adaptations that promote survival has led to the hypothesis that inappropriate, prolonged activation of the innate immune system may be involved in a number of pathological disturbances in the brain, ranging from Alzheimer’s disease to stroke. Conversely, the newly-defined role of cytokines in a wide variety of systemic co-morbid conditions, ranging from chronic heart failure to obesity, may begin to explain changes in the mental state of these subjects. Indeed, the newest findings of cytokine actions in the brain offer some of the first clues about the pathophysiology of certain mental health disorders, including depression. The time is ripe to begin to move these fundamental discoveries in mice to man and some of the pharmacological tools are already available to antagonize the detrimental actions of cytokines.

High-performance electronics using dense, perfectly aligned arrays of single-walled carbon nanotubes

Abstract: †Single-walled carbon nanotubes (SWNTs) have many exceptional electronic properties. Realizing the full potential of SWNTs in realistic electronic systems requires a scalable approach to device and circuit integration. We report the use of dense, perfectly aligned arrays of long, perfectly linear SWNTs as an effective thin-film semiconductor suitable for integration into transistors and other classes of electronic devices. The large number of SWNTs enable excellent device-level performance characteristics and good device-to-device uniformity, even with SWNTs that are electronically heterogeneous. Measurements on p- and n-channel transistors that involve as many as 2,100 SWNTs reveal device-level mobilities and scaled transconductances approaching 1,000 cm 2 V 21 s 21 and 3,000 S m 21 , respectively, and with current outputs of up to 1 A in devices that use interdigitated electrodes. PMOS and CMOS logic gates and mechanically flexible transistors on plastic provide examples of devices that can be formed with this approach. Collectively, these results may represent a route to large-scale integrated nanotube electronics.

Fitting photosynthetic carbon dioxide response curves for C3 leaves

Abstract: Photosynthetic responses to carbon dioxide concentration can provide data on a number of important parameters related to leaf physiology. Methods for fitting a model to such data are briefly described. The method will fit the following parameters: Vcmax, J, TPU, Rd and gm [maximum carboxylation rate allowed by ribulose 1·5-bisphosphate carboxylase/oxygenase (Rubisco), rate of photosynthetic electron transport (based on NADPH requirement), triose phosphate use, day respiration and mesophyll conductance, respectively].The method requires at least five data pairs of net CO2 assimilation (A) and [CO2] in the intercellular airspaces of the leaf (Ci) and requires users to indicate the presumed limiting factor. The output is (1) calculated CO2 partial pressure at the sites of carboxylation, Cc, (2) values for the five parameters at the measurement temperature and (3) values adjusted to 25 °C to facilitate comparisons. Fitting this model is a way of exploring leaf level photosynthesis. However, interpreting leaf level photosynthesis in terms of underlying biochemistry and biophysics is subject to assumptions that hold to a greater or lesser degree, a major assumption being that all parts of the leaf are behaving in the same way at each instant.

A Predictably Selective Aliphatic C-H Oxidation Reaction for Complex Molecule Synthesis

Abstract: Realizing the extraordinary potential of unactivated sp3 C–H bond oxidation in organic synthesis requires the discovery of catalysts that are both highly reactive and predictably selective. We report an iron (Fe)–based small molecule catalyst that uses hydrogen peroxide (H2O2) to oxidize a broad range of substrates. Predictable selectivity is achieved solely on the basis of the electronic and steric properties of the C–H bonds, without the need for directing groups. Additionally, carboxylate directing groups may be used to furnish five-membered ring lactone products. We demonstrate that these three modes of selectivity enable the predictable oxidation of complex natural products and their derivatives at specific C–H bonds with preparatively useful yields. This type of general and predictable reactivity stands to enable aliphatic C–H oxidation as a method for streamlining complex molecule synthesis.

Accurate, Dense, and Robust Multi-View Stereopsis

Abstract: This paper proposes a novel algorithm for calibrated multi-view stereopsis that outputs a (quasi) dense set of rectangular patches covering the surfaces visible in the input images. This algorithm does not require any initialization in the form of a bounding volume, and it detects and discards automatically outliers and obstacles. It does not perform any smoothing across nearby features, yet is currently the top performer in terms of both coverage and accuracy for four of the six benchmark datasets presented in [20]. The keys to its performance are effective techniques for enforcing local photometric consistency and global visibility constraints. Stereopsis is implemented as a match, expand, and filter procedure, starting from a sparse set of matched keypoints, and repeatedly expanding these to nearby pixel correspondences before using visibility constraints to filter away false matches. A simple but effective method for turning the resulting patch model into a mesh appropriate for image-based modeling is also presented. The proposed approach is demonstrated on various datasets including objects with fine surface details, deep concavities, and thin structures, outdoor scenes observed from a restricted set of viewpoints, and "crowded" scenes where moving obstacles appear in different places in multiple images of a static structure of interest.

The How, Whom, and Why of Parents’ Involvement in Children’s Academic Lives: More Is Not Always Better

Abstract: A key goal of much educational policy is to help parents become involved in children’s academic lives. The focus of such efforts, as well as much of the extant research, has generally been on increasing the extent of parents’ involvement. However, factors beyond the extent of parents’ involvement may be of import. In this article, the case is made that consideration of the how, whom, and why of parents’ involvement in children’s academic lives is critical to maximizing its benefits. Evidence is reviewed indicating that how parents become involved determines in large part the success of their involvement. It is argued as well that parents’ involvement may matter more for some children than for others. The issue of why parents should become involved is also considered. Implications for future research and interventions are discussed.

Technical outcomes of sentinel-lymph-node resection and conventional axillary-lymph-node dissection in patients with clinically node-negative breast cancer: results from the NSABP B-32 randomised phase III trial

Abstract: Summary Background The goals of axillary-lymph-node dissection (ALND) are to maximise survival, provide regional control, and stage the patient. However, this technique has substantial side-effects. The purpose of the B-32 trial is to establish whether sentinel-lymph-node (SLN) resection can achieve the same therapeutic goals as conventional ALND but with decreased side-effects. The aim of this paper is to report the technical success and accuracy of SLN resection plus ALND versus SLN resection alone. Methods 5611 women with invasive breast cancer were randomly assigned to receive either SLN resection followed by immediate conventional ALND (n=2807; group 1) or SLN resection without ALND if SLNs were negative on intraoperative cytology and histological examination (n=2804; group 2) in the B-32 trial. Patients in group 2 underwent ALND if no SLNs were identified or if one or more SLNs were positive on intraoperative cytology or subsequent histological examination. Primary endpoints, including survival, regional control, and morbidity, will be reported later. Secondary endpoints are accuracy and technical success and are reported here. This trial is registered with the Clinical Trial registry, number NCT00003830. Findings Data for technical success were available for 5536 of 5611 patients; 75 declined protocol treatment, had no SLNs removed, or had no SLN resection done. SLNs were successfully removed in 97·2% of patients (5379 of 5536) in both groups combined. Identification of a preincision hot spot was associated with greater SLN removal (98·9% [5072 of 5128]). Only 1·4% (189 of 13171) of SLN specimens were outside of axillary levels I and II. 65·1% (8571 of 13 171) of SLN specimens were both radioactive and blue; a small percentage was identified by palpation only (3·9% [515 of 13 171]). The overall accuracy of SLN resection in patients in group 1 was 97·1% (2544 of 2619; 95% CI 96·4–97·7), with a false-negative rate of 9·8% (75 of 766; 95% CI 7·8–12·2). Differences in tumour location, type of biopsy, and number of SLNs removed significantly affected the false-negative rate. Allergic reactions related to blue dye occurred in 0·7% (37 of 5588) of patients with data on toxic effects. Interpretation The findings reported here indicate excellent balance in clinical patient characteristics between the two randomised groups and that the success of SLN resection was high. These findings are important because the B-32 trial is the only trial of sufficient size to provide definitive information related to the primary outcome measures of survival and regional control. Removal of more than one SLN and avoidance of excisional biopsy are important variables in reducing the false-negative rate.

All About Maude - A High-Performance Logical Framework: How to Specify, Program, and Verify Systems in Rewriting Logic

Abstract: I: Core Maude.- Using Maude.- Syntax and Basic Parsing.- Functional Modules.- A Hierarchy of Data Types: From Trees to Sets.- System Modules.- Playing with Maude.- Module Operations.- Predefined Data Modules.- Specifying Parameterized Data Structures in Maude.- Object-Based Programming.- Model Checking Invariants Through Search.- LTL Model Checking.- Reflection, Metalevel Computation, and Strategies.- Metaprogramming Applications.- Mobile Maude.- User Interfaces and Metalanguage Applications.- II: Full Maude.- Full Maude: Extending Core Maude.- Object-Oriented Modules.- III: Applications and Tools.- A Sampler of Application Areas.- Some Tools.- IV: Reference.- Debugging and Troubleshooting.- Complete List of Maude Commands.- Core Maude Grammar.

Visual servo control. II. Advanced approaches [Tutorial]

Abstract: This article is the second of a two-part tutorial on visual servo control. In this tutorial, we have only considered velocity controllers. It is convenient for most of classical robot arms. However, the dynamics of the robot must of course be taken into account for high speed task, or when we deal with mobile nonholonomic or underactuated robots. As for the sensor, geometrical features coming from a classical perspective camera is considered. Features related to the image motion or coming from other vision sensors necessitate to revisit the modeling issues to select adequate visual features. Finally, fusing visual features with data coming from other sensors at the level of the control scheme will allow to address new research topics

Early Adolescents' Perceptions of the Classroom Social Environment, Motivational Beliefs, and Engagement.

Abstract: This research examined whether 5th-grade students' (N = 602) perceptions of the classroom social environment (teacher support, promotion of mutual respect, promotion of task-related interaction, student support) were related to their engagement in the classroom (self-regulation and task-related interaction) and whether those relations were mediated by personal motivational beliefs (mastery goals, academic and social efficacy). Teacher support, promotion of interaction, and student support were related to both types of engagement, and those relations were fully or partially mediated by motivational beliefs. Relations with promoting mutual respect were not significant.

Instance Weighting for Domain Adaptation in NLP

Abstract: Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting perspective. We formally analyze and characterize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, corresponding to the different distributions of instances and classification functions in the source and the target domains. We then propose a general instance weighting framework for domain adaptation. Our empirical results on three NLP tasks show that incorporating and exploiting more information from the target domain through instance weighting is effective.