Deterministic Sampling and Range Counting in Geometric Data Streams

We present memory-efficient deterministic algorithms for constructing epsilon-nets and epsilon-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. We show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. We use these techniques to approximate several robust statistics of geometric data streams, including Tukey depth, simplicial depth, regression depth, the Thiel-Sen estimator, and the least median of squares. Our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are inverse-polylogarithmic. We also include a lower bound for non-iceberg geometric queries.Comment: 12 pages, 1 figur

Minimizing the stabbing number of matchings, trees, and triangulations

The (axis-parallel) stabbing number of a given set of line segments is the maximum number of segments that can be intersected by any one (axis-parallel) line. This paper deals with finding perfect matchings, spanning trees, or triangulations of minimum stabbing number for a given set of points. The complexity of these problems has been a long-standing open question; in fact, it is one of the original 30 outstanding open problems in computational geometry on the list by Demaine, Mitchell, and O'Rourke. The answer we provide is negative for a number of minimum stabbing problems by showing them NP-hard by means of a general proof technique. It implies non-trivial lower bounds on the approximability. On the positive side we propose a cut-based integer programming formulation for minimizing the stabbing number of matchings and spanning trees. We obtain lower bounds (in polynomial time) from the corresponding linear programming relaxations, and show that an optimal fractional solution always contains an edge of at least constant weight. This result constitutes a crucial step towards a constant-factor approximation via an iterated rounding scheme. In computational experiments we demonstrate that our approach allows for actually solving problems with up to several hundred points optimally or near-optimally.Comment: 25 pages, 12 figures, Latex. To appear in "Discrete and Computational Geometry". Previous version (extended abstract) appears in SODA 2004, pp. 430-43

Examining the Psychometric Properties of the CEAC (Comparing e-Cigarette and Cigarette) Questionnaire and Its Usefulness as a Predictor of e-Cigarette Use

Background: Electronic cigarette (e-cigarette) use continues to rise, while there is conflicting evidence about the health effects of its use. As such, research is needed to better determine risks factors for e-cigarette use. Accumulating evidence suggests that attitudes toward e-cigarette use could be a potential risk factor for e-cigarette use. Objectives: This study sought to examine the psychometric properties of the Comparing E-cigarette And Cigarette questionnaire (CEAC), and to replicate a structural model of the relationship between impulsive-related personality traits and e-cigarette use mediated by positive attitudes toward e-cigarettes. Methods: Participants were 525 adults (mean age = 33.42, SD = 11.27) who completed the CEAC and UPPS-P (trait impulsivity) questionnaires online. Results: Confirmatory factor analysis of the CEAC replicated the a priori factor structure of the questionnaire reasonably well (χ2(df = 32) =172.85, CFI = 0.94, TLI = 0.91, RMSEA = 0.09 (0.08–0.11, 90% Confidence Interval, SRMR = 0.06). Structural path analysis showed that deficits in conscientiousness was significantly negatively related to e-cigarette attitudes (β = –0.20, p = .01), while urgency (β = 0.19, p = .018) showed a significant positive relationship to e-cigarette attitudes. E-cigarette users showed significantly more positive attitudes toward e-cigarettes than nonusers (β = 0.59, p < .001). No significant direct effects were found between impulsivity-related traits and e-cigarette use. Conclusions: The present study suggests that impulsivity-related traits and attitudes toward e-cigarettes are likely to be important risk factors for e-cigarette use. Future prospective and experimental studies should test if the causal model described in this study predicts risk for e-cigarette use, and whether this model could therefore be used to guide strategies for reducing risk for e-cigarette use

Genome-wide approaches for identification of nuclear receptor target genes

Large-scale genomics analyses have grown by leaps and bounds with the rapid advances in high throughput DNA sequencing and synthesis techniques. Nuclear receptor signaling is ideally suited to genomics studies because receptors function as ligand-regulated gene switches. This review will survey the strengths and limitations of three major classes of high throughput techniques widely used in the nuclear receptor field to characterize ligand-dependent gene regulation: expression profiling studies (microarrays, SAGE and related techniques), chromatin immunoprecipitation followed by microarray (ChIP-on-chip), and genome-wide in silico hormone response element screens. We will discuss each technique, and how each has contributed to our understanding of nuclear receptor signaling

Measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM)

© 2008 Sladek et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background Understanding how doctors think may inform both undergraduate and postgraduate medical education. Developing such an understanding requires valid and reliable measurement tools. We examined the measurement properties of the Inventory of Cognitive Bias in Medicine (ICBM), designed to tap this domain with specific reference to medicine, but with previously questionable measurement properties. Methods First year postgraduate entry medical students at Flinders University, and trainees (postgraduate doctors in any specialty) and consultants (N = 348) based at two teaching hospitals in Adelaide, Australia, completed the ICBM and a questionnaire measuring thinking styles (Rational Experiential Inventory). Results Questions with the lowest item-total correlation were deleted from the original 22 item ICBM, although the resultant 17 item scale only marginally improved internal consistency (Cronbach's α = 0.61 compared with 0.57). A factor analysis identified two scales, both achieving only α = 0.58. Construct validity was assessed by correlating Rational Experiential Inventory scores with the ICBM, with some positive correlations noted for students only, suggesting that those who are naïve to the knowledge base required to "successfully" respond to the ICBM may profit by a thinking style in tune with logical reasoning. Conclusion The ICBM failed to demonstrate adequate content validity, internal consistency and construct validity. It is unlikely that improvements can be achieved without considered attention to both the audience for which it is designed and its item content. The latter may need to involve both removal of some items deemed to measure multiple biases and the addition of new items in the attempt to survey the range of biases that may compromise medical decision making

Genetic Evaluation of Cardiomyopathy - a Heart Failure Society of America Practice Guideline

This guideline describes the approach and expertise needed for the genetic evaluation of cardiomyopathy. First published in 2009 by the Heart Failure Society of America (HFSA), this guidance has now been updated in collaboration with the American College of Medical Genetics and Genomics (ACMG). The writing group, composed of cardiologists and genetics professionals with expertise in adult and pediatric cardiomyopathy, reflects the emergence and increased clinical activity devoted to cardiovascular genetic medicine. The genetic evaluation of cardiomyopathy is a rapidly emerging key clinical priority, as high throughput sequencing is now feasible for clinical testing, and conventional interventions can improve survival, reduce morbidity, and enhance quality of life. Moreover, specific interventions may be guided by genetic analysis. A systematic approach is recommended: always a comprehensive family history; an expert phenotypic evaluation of the proband and at-risk family members to confirm a diagnosis and guide genetic test selection and interpretation; referral to expert centers as needed; genetic testing, with pre- and post-test genetic counseling; and specific guidance as indicated for drug and device therapies. The evaluation of infants and children demands special expertise. The approach to manage secondary and incidental sequence findings as recommended by the ACMG is provided

Low-cost, handheld near-infrared spectroscopy for root dry matter content prediction in cassava

Open Access Journal; Published online: 31 Mar 2022Over 800 million people across the tropics rely on cassava (Manihot esculenta Crantz) as a major source of calories. While the root dry matter content (RDMC) of this starchy root crop is important for both producers and consumers, characterization of RDMC by traditional methods is time-consuming and laborious for breeding programs. Alternate phenotyping methods have been proposed but lack the accuracy, cost, or speed ultimately needed for cassava breeding programs. For this reason, we investigated the use of a low-cost, handheld near-infrared spectrometer (740–1070 nm) for field-based RDMC prediction in cassava. Oven-dried measurements of RDMC were paired with 21,044 scans of roots of 376 diverse genotypes from 10 field trials in Nigeria and grouped into training and test sets based on cross-validation schemes relevant to plant breeding programs. Mean partial least squares regression model performance ranged from R2P = 0.62–0.89 for within-trial predictions, which is within the range achieved with laboratory-grade spectrometers in previous studies. Relative to other factors, model performance was highly affected by the inclusion of samples from the same environment in both the training and test sets. With appropriate model calibration, the tested spectrometer will allow for field-based collection of spectral data with a smartphone for accurate RDMC prediction and potentially other quality traits, a step that could be easily integrated into existing harvesting workflows of cassava breeding programs

Germline DDX41 mutations cause ineffective hematopoiesis and myelodysplasia

DDX41 mutations are the most common germline alterations in adult myelodysplastic syndromes (MDSs). The majority of affected individuals harbor germline monoallelic frameshift DDX41 mutations and subsequently acquire somatic mutations in their other DDX41 allele, typically missense R525H. Hematopoietic progenitor cells (HPCs) with biallelic frameshift and R525H mutations undergo cell cycle arrest and apoptosis, causing bone marrow failure in mice. Mechanistically, DDX41 is essential for small nucleolar RNA (snoRNA) processing, ribosome assembly, and protein synthesis. Although monoallelic DDX41 mutations do not affect hematopoiesis in young mice, a subset of aged mice develops features of MDS. Biallelic mutations in DDX41 are observed at a low frequency in non-dominant hematopoietic stem cell clones in bone marrow (BM) from individuals with MDS. Mice chimeric for monoallelic DDX41 mutant BM cells and a minor population of biallelic mutant BM cells develop hematopoietic defects at a younger age, suggesting that biallelic DDX41 mutant cells are disease modifying in the context of monoallelic DDX41 mutant BM

Developing autonomous learning in first year university students using perspectives from positive psychology

Autonomous learning is a commonly occurring learning outcome from university study, and it is argued that students require confidence in their own abilities to achieve this. Using approaches from positive psychology, this study aimed to develop confidence in first‐year university students to facilitate autonomous learning. Psychological character strengths were assessed in 214 students on day one at university. Two weeks later their top three strengths were given to them in study skills modules as part of a psycho‐educational intervention designed to increase their self‐efficacy and self‐esteem. The impact of the intervention was assessed against a control group of 40 students who had not received the intervention. The results suggested that students were more confident after the intervention, and that levels of autonomous learning increased significantly compared to the controls. Character strengths were found to be associated with self‐efficacy, self‐esteem and autonomous learning in ways that were theoretically meaningful