Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Applications in Genetics and Molecular Biology Empirical Bayes and Resampling Based Multiple Testing Procedure Controlling Tail Probability of the Proportion of False Positives. Empirical Bayes and Resampling Based Multiple Testing Procedure Controlling Tail Probability of the Proportion

No part of this publication may be reproduced , stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher, bepress, which has been given certain exclusive rights by the author. Statistical Applications in Genetics and Molecular Biology is produced by The Berkeley Electronic Press (bepress). Abstract Simultaneously testing a collection of null hypotheses about a data generating distribution based on a sample of independent and identically distributed observations is a fundamental and important statistical problem involving many applications. In this article we propose a new re-sampling based multiple testing procedure asymptotically controlling the probability that the proportion of false positives among the set of rejections exceeds q at level alpha, where q and alpha are user supplied numbers. The procedure involves 1) specifying a conditional distribution for a guessed set of true null hypotheses, given the data, which asymptotically is degenerate at the true set of null hypotheses, and 2) specifying a generally valid null distribution for the vector of test-statistics proposed in Pollard & van der Laan (2003), and generalized in our subsequent article Dudoit, van der Laan, & Pollard (2004), van der Laan, Dudoit, & Pollard (2004), and van der Laan, Dudoit, & Pollard (2004b). Ingredient 1) is established by fitting the empirical Bayes two component mixture model (Efron (2001b)) to the data to obtain an upper bound for marginal posterior probabilities of the null being true, given the data. We establish the finite sample rational behind our proposal, and prove that this new multiple testing procedure asymptotically controls the wished tail probability for the proportion of false positives under general data generating distributions. In addition, we provide simulation studies establishing that this method is generally more powerful in finite samples than our previously proposed augmentation multiple testing procedure (van der Laan, Dudoit, & Pollard (2004b)) and competing procedures from the literature. Finally, we illustrate our methodology with a data analysis. * We thank the referees for their helpful comments, and we also wish to thank Sandrine Dudoit for careful reading and helpful improvements.
Categorizing bugs with social networks: A case study on four open source software communities

Efficient bug triaging procedures are an important precondition for successful collaborative software engineering projects. Triaging bugs can become a laborious task particularly in open source software (OSS) projects with a large base of comparably inexperienced part-time contributors. In this paper, we propose an efficient and practical method to identify valid bug reports which a) refer to an actual software bug, b) are not duplicates and c) contain enough information to be processed right away. Our classification is based on nine measures to quantify the social embeddedness of bug reporters in the collaboration network. We demonstrate its applicability in a case study, using a comprehensive data set of more than 700, 000 bug reports obtained from the Bugzilla installation of four major OSS communities, for a period of more than ten years. For those projects that exhibit the lowest fraction of valid bug reports, we find that the bug reporters' position in the collaboration network is a strong indicator for the quality of bug reports. Based on this finding, we develop an automated classification scheme that can easily be integrated into bug tracking platforms and analyze its performance in the considered OSS communities. A support vector machine (SVM) to identify valid bug reports based on the nine measures yields a precision of up to 90.3% with an associated recall of 38.9%. With this, we significantly improve the results obtained in previous case studies for an automated early identification of bugs that are eventually fixed. Furthermore, our study highlights the potential of using quantitative measures of social organization in collaborative software engineering. It also opens a broad perspective for the integration of social awareness in the design of support infrastructures.
Particle Swarm Optimization With Recombination and Dynamic Linkage Discovery

In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 institute of electrical and electronics engineers congress on evolutionary computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.
How to Defend Humane Ideals: Substitutes for Objectivity

Contents: Acknowledgements Introduction: The Problem 1. Truth-Tests and What Has Been Lost What We Can No Longer Say Why We Must Change Part One: The Limitations of Philosophy 2. Plato and Thrasymachus 3. Truth-Tests and Proof 4. Kant and Sister Simplice Transition: An Agenda 5. Morality and Moral Debate Part Two: The Potency of Social Science 6. Race and Class Racism and Book Reviews The Marx of the Middle Classes 7. Superpeople and Supermen The Only True Social Darwinist Nietzsche and His Supermen What They Have in Common 8. Justice and Meritocracy Blacks as a Disadvantaged Group Blacks and Affirmative Action Equality and Meritocracy 9. Humanism and Postmodernism The Postmodern Agenda Humane Empiricists and the Six Balls Postmodernism and Empiricism Ex Nilhilo Nihil Fit Conclusion: Unsolved Problems 10. The Personal and the Conventional References Author Index Subject Index
Surface Microbes in the Neonatal Intensive Care Unit: Changes with Routine Cleaning and over Time

ABSTRACT Premature infants in neonatal intensive care units (NICUs) are highly susceptible to infection due to the immaturity of their immune systems, and nosocomial infections are a significant risk factor for death and poor neurodevelopmental outcome in this population. To investigate the impact of cleaning within a NICU, a high-throughput short-amplicon-sequencing approach was used to profile bacterial and fungal surface communities before and after cleaning. Intensive cleaning of surfaces in contact with neonates decreased the total bacterial load and the percentage of Streptococcus species with similar trends for total fungal load and Staphylococcus species; this may have clinical relevance since staphylococci and streptococci are the most common causes of nosocomial NICU infections. Surfaces generally had low levels of other taxa containing species that commonly cause nosocomial infections (e.g., Enterobacteriaceae) that were not significantly altered with cleaning. Several opportunistic yeasts were detected in the NICU environment, demonstrating that these NICU surfaces represent a potential vector for spreading fungal pathogens. These results underline the importance of routine cleaning as a means of managing the microbial ecosystem of NICUs and of future opportunities to minimize exposures of vulnerable neonates to potential pathogens and to use amplicon-sequencing tools for microbial surveillance and hygienic testing in hospital environments.
An Alternative Softmax Operator for Reinforcement Learning

A softmax operator applied to a set of values acts somewhat like the maximization function and somewhat like an average. In sequential decision making, softmax is often used in settings where it is necessary to maximize utility but also to hedge against problems that arise from putting all of one's weight behind a single maximum utility decision. The Boltzmann softmax operator is the most commonly used softmax operator in this setting, but we show that this operator is prone to misbehavior. In this work, we study a differentiable softmax operator that, among other properties, is a non-expansion ensuring a convergent behavior in learning and planning. We introduce a variant of SARSA algorithm that, by utilizing the new operator, computes a Boltzmann policy with a state-dependent temperature parameter. We show that the algorithm is convergent and that it performs favorably in practice.
Clinical and structural characteristics of periodontal tissues in young and old dogs.

The aim of this study was to examine some clinical and structural features of healthy periodontal tissues in young and old beagle dogs. The material consisted of 10 beagle dogs; group I (1-year old) and group II (8-9 years of age). All animals belonged to the same beagle dog colony and had been carefully monitored from birth. A given day was termed day 0 on which the teeth of all 10 dogs were scaled and polished and a 6-week period of enhanced plaque control was initiated. On day 42, clinical examinations were performed and biopsies obtained from the right mandibular 4th (4P) and 3rd (3P) premolar regions. The biopsies were prepared for histometric and morphometric analyses. Clinically, the lower premolars of the old but not the young dogs showed signs of marked wear. In the old dogs, the free gingival unit had a more curved and bulky appearance than in the young animals and in the old dogs, the free gingiva was consistently separated from the attached gingiva by a gingival groove. The histometrical dimensions of the free marginal gingiva and the width of the coronal portion of the periodontal ligament did not differ between the 2 groups of dogs. The apical cells of the junctional epithelium (aJE) in the young dogs were consistently located at the cemento-enamel junction (CEJ), whereas in the old dogs, aJE was consistently located apical to the CEJ. (ABSTRACT TRUNCATED AT 250 WORDS)
Low-angle reflectivity modeling of land clutter

In this letter, a practical mean reflectivity model of radar land clutter (LC) for the complex system design of ground-based radars involved in low-angle targets on some typical terrains is studied using the inductive reasoning method. The functional relationships between the radar parameters and radar surface clutter backscattering are analyzed. Following the recent research work in the area of reflectivity modeling of LC in the literature, the least squares method is employed to estimate the model parameters. The model is validated using reliable practical data and shown to outperform other models in accuracy.
Performance Optimization and Analysis of Blade Designs under Delay Variability

As manufacturing processes continue to shrink and supply voltages drop, timing margins due to increased process, temperature, and voltage variability become a significant portion of the clock period. An asynchronous bundled data resilient template called Blade has recently been proposed to curb these margins and thereby outperform synchronous alternatives. This paper proposes a model to analyze the performance of Blade designs and an approach to optimize it. We validate the model against gate-level simulations of a resilient 3-stage MIPS CPU implemented with Blade and use it to compare the optimal performance of Blade designs with synchronous alternatives. The results show that Blade offers up to 44% higher performance than traditional designs and 23% higher performance than Bubble Razor, the synchronous resiliency strategy with the highest reported performance.
BingocizeTM: Successful Integration of Intergenerational Service-Learning into an Exercise Science Practicum Project

Intergenerational service-learning was used to meet course learning outcomes for an exercise science practicum while increasing older adults’ physical activity participation. Five practicum students researched, planned, and executed a combination bingo and exercise program (Bingocize TM ) twice per week (45-60 minutes sessions) at a low-income independent living facility located near campus. The results of the program were positive as evidenced by achievement of student learning outcomes and improvements in older adults’ overall well-being.
Schools and Inequality: A Multilevel Analysis of Coleman's Equality of Educational Opportunity Data

Background/Context The Equality of Educational Opportunity study is widely recognized as one of the most important studies on schooling ever performed. The findings from the report have shaped the field of education, national education policies, and wider public and scholarly opinion regarding the contributions of schools and schooling to equality and productivity in the United States. Despite past reanalyses of the data and decades of research on the effects of schools as organizations, the report's fundamental finding—that a student's family background is far more important than school social composition and school resources for understanding student outcomes—still retains much of its currency. Purpose/Objective/Research Question/Focus of Study: Using the original Equality of Educational Opportunity data, this study replicated Coleman's statistical models but also applied a two-level hierarchical linear model (HLM) to measure the effects of school-level social composition, resources, teacher characteristics, and peer characteristics on ninth-grade students’ verbal achievement. Research Design HLM allows researchers to disentangle how schools and students’ family backgrounds contribute to learning outcomes. The methodology offers a clearer interpretation of the relative effects of school characteristics, including racial/ethnic composition, and family background, including race/ethnicity and social class, on students’ academic outcomes. Findings/Results Our results suggest that schools do indeed matter, in that when one examines the outcomes across the national sample of schools, fully 40% of the differences in achievement can be found between schools. Even after statistically taking into account students’ family background, a large proportion of the variation among true school means is related to differences explained by school characteristics. Within-school inequalities in the achievement outcomes for African American and White students and students from families of higher and lower social class are explained in part by teachers’ biases favoring middle-class students and by schools’ greater reliance on curriculum differentiation through the use of academic and nonacademic tracking. Conclusions/Recommendations Formal decomposition of the variance attributable to individual background and the social composition of the schools suggests that going to a high-poverty school or a highly segregated African American school has a profound effect on a student's achievement outcomes, above and beyond the effect of individual poverty or minority status. Specifically, both the racial/ethnic and social class composition of a student's school are 1 3/4 times more important than a student's individual race/ethnicity or social class for understanding educational outcomes.
Calumenin, a Ca2+-binding Protein Retained in the Endoplasmic Reticulum with a Novel Carboxyl-terminal Sequence, HDEF*

We have identified and characterized a cDNA encoding a novel Ca2+-binding protein named calumenin from mouse heart by the signal sequence trap method. The deduced amino acid sequence (315 residues) of calumenin contains an amino-terminal signal sequence and six Ca2+-binding (EF-hand) motifs and shows homology with reticulocalbin, Erc-55, and Cab45. These proteins seem to form a new subset of the EF-hand protein family expressed in the lumen of the endoplasmic reticulum (ER) and Golgi apparatus. Purified calumenin had Ca2+-binding ability. The carboxyl-terminal tetrapeptide His-Asp-Glu-Phe was shown to be responsible for retention of calumenin in ER by the retention assay, immunostaining with a confocal laser microscope, and the deglycosylation assay. This is the first report indicating that the Phe residue is included in the ER retention signal. Calumenin is expressed most strongly in heart of adult and 18.5-day embryos. The calumenin gene (Calu) was mapped at the proximal portion of mouse chromosome 7.
Ontogeny of Dopamine D1 Receptors in Rat Striatum

The development of dopamine D1 receptors in rat striatum during the early postnatal period is described, using [3H]piflutixol as ligand. Dopamine D1 receptors increase in number from day of birth until about 21 days of age, when they reach adult levels. This increase in number parallels the increase in several other dopamine markers in striatum during the same time period. The increase is reflected in an increase in Bmax of ligand binding to D1 receptors. All other properties of D1 receptors that were examined do not change throughout this developmental period and are essentially the same as those found in adult tissue. These include association and dissociation rates, affinity for piflutixol as determined by kinetic and saturation studies, and pharmacology. These studies provide a biochemical and pharmacological basis for further studies on the ontogeny of dopamine receptors and of striatum and on factors regulating development of this region.
Focal cryotherapy in the treatment of localized prostate cancer.

BACKGROUND The management choice for newly diagnosed localized prostate cancer presents a challenge to both the physician and the patient. Traditionally, surgery and radiation therapy have been the most commonly recommended options. More recently, active surveillance is recommended as the preferred management choice for a subset of men with localized, low-risk cancer. Recent reports also suggest that focal cryotherapy may be considered as a management option for selected cases of clinically localized prostate cancer. METHODS A review of the literature on focal cryotherapy from 2002 to 2012 was performed. Outcomes on cancer control, complications, and quality of life were extracted and assessed. RESULTS The biochemical disease-free survival at 5 years is comparable to whole gland treatment modalities. Complications are minimal and comparable with other local treatment modalities. CONCLUSIONS Focal cryotherapy is safe and effective, and it may improve failure rates in men who initially pursue active surveillance protocols. Early outcomes with cancer control are encouraging.
ON THE SATURATION OF THE MAGNETOROTATIONAL INSTABILITY VIA PARASITIC MODES

We investigate the stability of incompressible, exact, non-ideal magnetorotational (MRI) modes against parasitic instabilities. Both Kelvin–Helmholtz and tearing-mode parasitic instabilities may occur in the dissipative regimes accessible to current numerical simulations. We suppose that a primary MRI mode saturates at an amplitude such that its fastest parasite has a growth rate comparable to its own. The predicted alpha parameter then depends critically on whether the fastest primary and parasitic modes fit within the computational domain and whether non-axisymmetric parasitic modes are allowed. Hence, even simulations that resolve viscous and resistive scales may not saturate properly unless the numerical domain is large enough to allow the free evolution of both MRI and parasitic modes. To minimally satisfy these requirements in simulations with vertical background fields, the vertical extent of the domain should accommodate the fastest growing MRI mode while the radial and azimuthal extents must be twice as large. The fastest parasites have horizontal wavelengths roughly twice as long as the vertical wavelength of the primary.
Observer Variability in Mesothelioma Tumor Thickness Measurements: Defining Minimally Measurable Lesions

Introduction: Single time-point unidimensional tumor thickness measurements define measurable disease for clinical trial inclusion and also constitute a field in the International Association for the Study of Lung Cancer prospective mesothelioma staging database. The modified Response Evaluation Criteria in Solid Tumors (RECIST) guidelines for mesothelioma did not alter the 10-mm minimum tumor measurement recommendation. However, as computed tomography technology has advanced, we sought to examine whether interobserver agreement was acceptable at smaller tumor thickness in mesothelioma. Methods: The primary observer selected 170 discrete measurement sites from 105 thoracic computed tomography scans from 50 consenting patients with pleural mesothelioma. Sites represented a range of tumor thickness, lesion morphology, and location. The outer (parietal) tumor margin was marked at each site and presented to five additional observers, who then selected the visceral margin of the tumor to create a line segment that captured tumor thickness. Relative differences among the observer measurements were estimated using a random-effects analysis of variance model to identify the smallest tumor thickness at which linear measurements could be made reliably. Results: Systematic bias was observed, with some observers consistently measuring larger or smaller thicknesses than the thickness measured by others. The mean range across all 170 sites was 15.1% of the mean per-site measurement (SD = 9.1%; median range, 13.1%). Measurements acquired at sites with mean tumor thickness less than 7.5 mm demonstrated interobserver variability with a 75th percentile included 20% of the tumor thickness. The 95% confidence interval for relative interobserver measurement differences obtained for mean measurement lengths in the range 5 to 7.5 mm does not exceed the RECIST thresholds. Conclusions: This study has implications for the definition of minimally measurable tumor adopted by clinical trial and staging protocols. Although the statistical findings suggest that a reduction in “minimally measurable disease” from 10 mm to 5 or 7.5 mm might be warranted, clinical factors may ultimately dictate the most appropriate definition.