Miracle-dz/UniFAR-FTUs huggingface dataset:
A MATRIX-FREE APPROACH FOR SOLVING THE GAUSSIAN PROCESS MAXIMUM LIKELIHOOD PROBLEM

Gaussian processes are the cornerstone of statistical analysis in many application areas. Nevertheless, most of the applications are limited by their need to use the Cholesky factorization in the computation of the likelihood. In this work, we present a matrix-free approach for computing the solution of the maximum likelihood problem involving Gaussian processes. The approach is based on a stochastic programming reformulation followed by sample average approximation applied to either the maximization problem or its optimality conditions. We provide statistical estimates of the approximate solution. The method is illustrated on several examples where the data is provided on a regular or irregular grid. In the latter case, the action of a covariance matrix on a vector is computed by means of fast multipole methods. For each of the examples presented, we demonstrate that the approach scales linearly with an increase in the number of sites.
Relapse prevention: A critical analysis

In the last decade the application of the relapse prevention (RP) model to both the conceptualization and the treatment of sexual offenders has emerged as an innovative approach. Underlying the treatment utility of this perspective has been a social learning view of the relapse process in addictive behavior. In this paper we critically examine both Marlatt's original RP model and Pithers' application of this perspective to the sexual offending area. After outlining its basic assumptions, we describe the RP model in some detail. Following a critique of Marlatt's theory, we examine the strengths and weaknesses of Pithers' RP approach. Finally, we conclude with some comments on the implications of our critique.
Computational Statistics and Data Analysis Bootstrap Estimated True and False Positive Rates and Roc Curve

Diagnostic studies and new biomarkers are assessed by the estimated true and false positive rates of the classification rule. One diagnostic rule is considered for high-dimensional predictor data. Cross-validation and the leave-one-out bootstrap are discussed to estimate true and false positive rates of classifiers by the machine learning methods Adaboost, Bagging, Random Forest, (penalized) logistic regression and support vector machines. The . 632+ bootstrap estimation of the misclassification error has been previously proposed to adjust the overfitting of the apparent error. This idea is generalized to the estimation of true and false positive rates. Tree-based simulation models with 8 and 50 binary non-informative variables are analysed to examine the properties of the estimators. Finally, a bootstrap estimation of receiver operating characteristic (ROC) curves is suggested and a . 632+ bootstrap estimation of ROC curves is discussed. This approach is applied to high-dimensional gene expression data of leukemia and predictors of image data for glaucoma diagnosis.
Corporate culture and organizational performance

While many culture researchers have devoted numerous articles to the nature and definitions of culture, relatively fewer articles have contributed towards culture and performance research. The purpose of this study is to investigate the possible relationships between corporate culture and organizational performance among Singaporean companies. The objectives of this study are twofold: first, it aims to investigate the validity of the culture construct. Can culture construct be operationalized along distinct, repeatable dimensions? Second, it attempts to assess how culture affects organizational performance. The organizational culture profile was used as the primary research instrument. Culture was found to impact a variety of organizational processes and performance. While more research remains to be done in this area, this study has demonstrated the power of culture in influencing organizational performance.
Serological Evidence of Widespread Circulation of West Nile Virus and Other Flaviviruses in Equines of the Pantanal, Brazil

A recent study reported neutralizing antibodies to West Nile virus (WNV) in horses from four ranches of southern Pantanal. To extend that study, a serosurvey for WNV and 11 Brazilian flaviviruses was conducted with 760 equines, 238 sheep and 61 caimans from 17 local cattle ranches. Among the tested equines, 32 were collected from a ranch where a neurologic disorder outbreak had been recently reported. The sera were initially screened by using a blocking ELISA and then titrated by 90% plaque-reduction neutralization test (PRNT90) for 12 flaviviruses. Employing the criterion of 4-fold greater titer, 78 (10.3%) equines were seropositive for Ilheus virus, 59 (7.8%) for Saint Louis encephalitis virus, 24 (3.2%) for WNV, two (0.3%) for Cacipacore virus and one (0.1%) for Rocio virus. No serological evidence was found linking the neurological disease that affected local equines to WNV. All caimans and sheep were negative by blocking ELISA for flaviviruses. There were no seropositive equines for Bussuquara, Iguape, Yellow fever and all four Dengue virus serotypes. The detection of WNV-seropositive equines in ten ranches and ILHV and SLEV-seropositive equines in fourteen ranches of two different sub-regions of Pantanal is strong evidence of widespread circulation of these flaviviruses in the region.
Robustifying AdaBoost by Adding the Naive Error Rate

AdaBoost can be derived by sequential minimization of the exponential loss function. It implements the learning process by exponentially reweighting examples according to classification results. However, weights are often too sharply tuned, so that AdaBoost suffers from the nonrobustness and overlearning. We propose a new boosting method that is a slight modification of AdaBoost. The loss function is defined by a mixture of the exponential loss and naive error loss functions. As a result, the proposed method incorporates the effect of forgetfulness into AdaBoost. The statistical significance of our method is discussed, and simulations are presented for confirmation.
Learning Across Scales - Multiscale Methods for Convolution Neural Networks

In this work, we establish the relation between optimal control and training deep Convolution Neural Networks (CNNs). We show that the forward propagation in CNNs can be interpreted as a time-dependent nonlinear differential equation and learning can be seen as controlling the parameters of the differential equation such that the network approximates the data-label relation for given training data. Using this continuous interpretation, we derive two new methods to scale CNNs with respect to two different dimensions. The first class of multiscale methods connects low-resolution and high-resolution data using prolongation and restriction of CNN parameters inspired by algebraic multigrid techniques. We demonstrate that our method enables classifying high-resolution images using CNNs trained with low-resolution images and vice versa and warm-starting the learning process. The second class of multiscale methods connects shallow and deep networks and leads to new training strategies that gradually increase the depths of the CNN while re-using parameters for initializations.
Origin of the metallicity dependence of exoplanet host stars in the protoplanetary disc mass distribution

The probability of a star hosting a planet that is detectable in radial velocity surveys increases as Ppl(Z) ! (10 Z ) 2 , where Z is stellar metallicity. Models of planet formation by core accretion reproduce this trend, since the protoplanetary disc of a high-metallicity star has a high density of solids, and so forms planetary cores which accrete gas before the primordial gas disc dissipates. This paper considers the origin of the form of the metallicity dependence of Ppl(Z). We introduce a simple model in which detectable planets form when the mass of solid material in the protoplanetary disc, Ms, exceeds a critical value. In this model, the form of Ppl(Z) is a direct reflection of the distribution of protoplanetary disc masses, Mg, and the observed metallicity relation is reproduced if P(Mg > M ") ! (M ") # 2 . We argue that a protoplanetary disc’s dust mass measured in submillimetre observations is a relatively pristine indicator of the mass available for planet-building, and find that the disc mass distribution derived from suchobservationsisconsistentwiththeobservedPpl(Z)ifasolidmassMs >0.5MJ isrequired to form detectable planets. Any planet formation model which imposes a critical solid mass for detectable planets to form would reproduce the observed metallicity relation, and core accretionmodelsareempiricallyconsistentwithsuchathresholdcriterion.Whiletheoutcome of planet formation in individual systems is debatable, we identify seven protoplanetary discs which, by rigid application of this criterion, would be expected to form detectable planets and may provide insight into the physical conditions required to form such planets. A testable prediction of the model is that the metallicity dependence should flatten both for Z > 0.5 dex and as more distant and lower mass planets are discovered. Further, combining this model with one in which the evolution of a star’s debris disc is also influenced by the solid mass in its protoplanetary disc results in the prediction that debris discs detected around stars with planets should be more infrared luminous than those around stars without planets in tentative agreement with recent observations.
Merl a Mitsubishi Electric Research Laboratory Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology Correctness of Belief Propagation in Gaussian Graphical Models of Arbitrary Topology

Local belief propagation" rules of the sort proposed by P earl 122 are guaranteed to converge to the correct posterior probabilities in singly connected graphical models. Recently, a numberof researchers have empirically demonstrated good performance of loopy belief propagation""using these same rules on graphs with loops. Perhaps the most dramatic instance is the near Shannon-limit performance of Turbo codes", whose decoding algorithm is equivalent t o loopy belief propagation. Except for the case of graphs with a single loop, there has been little theoretical understanding of the performance of loopy propagation. Here we analyze belief propagation in networks with arbitrary topologies when the nodes in the graph describe jointly Gaussian random variables. We give an analytical formula relating the true posterior probabilities with those calculated using loopy propagation. We give suucient conditions for convergence and show that when belief propagation converges it gives the correct posterior means for all graph topologies, not just networks with a single loop. The related max-product" belief propagation algorithm nds the maximum posterior probability estimate for singly connected networks. We show that, even for non-Gaussian probability distributions, the convergence points of the max-product algorithm in loopy networks are at least local maxima of the posterior probability. These results motivate using the powerful belief propagation algorithm in a broader class of networks, and help clarify the empirical performance results. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonproot educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. Abstract Local belief propagation" rules of the sort proposed by Pearl 12 are guaranteed to converge to the correct posterior probabilities in singly connected graphical models. Recently, a number of researchers have empirically demonstrated good performance of loopy belief propagation""using these same rules on graphs with loops. Perhaps the most dramatic instance is the near Shannon-limit performance of Turbo codes", whose decoding algorithm is equivalent t o l o …
What Affects Clean Delivery Kit Utilization at Birth in Nepal? A Qualitative Study

Background: Infection is one of the biggest causes of maternal and neonatal death in low-income countries. Clean Delivery Kits (CDKs) promote clean delivery and neonatal care. Our qualitative research explores reasons for low CDK utilization, and describes community perceptions of CDKs in Nepal. Methods: We conducted 18 focus group discussions and 40 interviews with CDK users and nonusers, service providers, birth attendants, and household decision makers in 6 districts. We also conducted interviews with central level personnel. CDK users were aware of its benefits, and utilization was largely compatible with birth practices. Utilization was prevented by lack of awareness about the benefits and lack of availability. Participants believed that CDKs were for home use. Conclusion: Poor promotion of CDK is related to the disjuncture of promoting CDK use, while encouraging institutional deliveries. If CDKs are made available and marketed for use in households and health institutions, utilization may increase.
Effects of Dantrolene on Ischemia-Reperfusion Injury in Animal Models

Background/Objectives Ischemia-reperfusion (IR) is the restoration of blood flow to a tissue that was formerly deficient of blood flow. Tissue damage after IR is considered an IR injury (IRI). During IR, there is an increased level of cytosolic calcium ([Ca2+]i) due to the release of calcium from mitochondrial, sarcoendoplasmic reticulum, and nuclear organelles. Dantrolene sodium (dantrolene) is a 1-[[[5-(4-nitrophenol)-2-furanyl]methylene]amino]-2, 4-imidazolidinedione sodium salt with a nonspecific mechanism, inhibiting organelle release of Ca2+ into the cytosol. This work reviews the outcomes of administering dantrolene in brain, heart, liver, and kidney animal models of IRI. Methods An extensive PubMed, MEDLINE, and MEDLAR literature review during the last 30 years on the effect of dantrolene in IRI in animal models was analyzed to determine the clinical implications of this important study. Particular attention was given to dantrolene in heart, brain, liver, and kidney IRI. Results Heart: Nine studies of heart IRI were reviewed and include an in vivo dog model (n = 1), in vivo rabbit model (n = 1), isolated dog myocardial fibers (n = 1), and isolated rat hearts (n = 6). Four studies showed decreased infarct size and increased cardiac function after IRI. One in vivo rabbit study found no difference in infarct size or cardiac function after IRI versus controls. Dantrolene may be protective or inductive of post-IRI arrhythmias depending on preestablished myocyte cycling times. Brain: Nine studies of brain IRI were reviewed and include an in vivo dog model (n = 1), in vivo gerbil model (n = 2), and in vivo rat models (n = 6). Dantrolene shows protective decreases in apoptotic markers in 6 studies, but it shows no effect on the necrotic core and mixed effects on reduction of infarct volume. One study found increased mortality in the dantrolene group. Liver: One study of in vivo rat liver IRI found that dantrolene decreased liver function tests, tissue necrosis factor α, tissue necrosis, and increased interleukin 10. Kidney: One study of in vivo rat kidney IRI showed that dantrolene had no effect. Conclusions Dantrolene shows protective effects in animal models of heart, brain, and potentially liver IRI, reinforcing the importance of calcium homeostasis during IRI. Variations of dose, timing of administration, route of administration, and outcomes between studies make definitive conclusions difficult. The nonspecific mechanism of action of dantrolene may also account for the variation among studies. Lack of studies in the liver and kidney makes any consensus in these organs premature, and thus, emphasis for this review was put on studies of the heart and brain.
Recent Developments in Covert Acoustical Communications

The topic of covert acoustical communication in air has produced public attention, lately. In 2013, we presented the fact that infected drones (e.g. laptops) might form covert acoustical mesh networks in air, only utilizing the built-in speakers and microphones. In this article, we aim to present the current state of covert acoustical communication in air. We discuss future forms of covert acoustical mesh networks, we present an alternative audio signal that is improved in terms of stealthiness, and we provide considerations on the stealthiness of covert acoustical communication in air. In order to protect computing setups from malware utilizing covert acoustical communications, we present an analysis on detection and localization mechanisms for covert acoustical transmissions. Finally, we describe the implementation of an audio intrusion detection system that is designed for automatic analysis of acoustical emanations.
Rice Consumption and Squamous Cell Carcinoma of the Skin in a United States Population

Background: Rice contains arsenic, a known skin carcinogen. Rice intake has been associated with arsenic-related skin lesions in South Asia, but its association with skin cancers is as yet unknown. Objectives: We aimed to investigate whether rice intake contributes to urinary arsenic concentration and risk of squamous cell carcinoma (SCC) of the skin in a U.S. population. Methods: Rice consumption was assessed using a food frequency questionnaire administered as part of a population-based case–control study of 487 SCC cases and 462 age- and gender-matched controls. Arsenic concentration in household tap water and urine samples were measured using inductively coupled mass spectrometry (ICP-MS) and high-resolution ICP-MS, respectively. Odds ratios (OR) for SCC associated with the frequency of rice consumption were estimated using logistic regression, with adjustment for age, gender, and caloric intake. Results: Those who reported any rice consumption had higher urinary arsenic concentrations than those who did not consume rice, and the association was most pronounced among those with <1μg/L arsenic in their household water (19.2% increase in total urinary arsenic, 95% CI: 5.0, 35.3%). Any rice consumption was associated with a 1.5-fold (95% CI: 1.1, 2.0) higher odds of SCC compared with those who reported no rice consumption, and the relation appeared to be largely among those with <1μg/L water arsenic. Conclusion: Rice consumption may be related to the occurrence of SCC in the United States, especially among those with relatively low drinking water arsenic exposure. https://doi.org/10.1289/EHP1065
Cross‐cultural predictors of mathematical talent and academic productivity

The main goal of this paper is to investigate cross‐cultural factors that predict academic ability among mathematically gifted Olympians in Finland and the United States. The following two research problems are formulated: (1) What factors contribute to or impede the development of the Olympians’ mathematic talent? and (2) Do the Olympians fulfill their potential by making contributions to their fields? The results regarding the first research question indicate that the amount of cross‐cultural distinctive factors (computer literacy) is less than the amount of connective factors (school hindrances, effort attributions, negative home influences) contributing to the development of the Mathematic Olympians’ talent. The results regarding the latter research problem show that some factors are culture invariant (socioeconomic status, effort attributions) and some are culture dependent (school hindrances, computer literacy) in relation to both US and Finnish Olympians’ later academic productivity. Results show that high school grade point averages do not necessarily predict academic productivity in Olympians’ careers.
An experimental setup for studying the effect of noise on Chua's circuit

The analog simulation of nonlinear dynamical systems is advantageous in some cases, i.e., when compared with the study using digital computers and, in particular, when one wishes to investigate the role of noise in these systems. In the present work we introduce two different methods of introducing a noise component in the most widely used chaotic circuit, namely, Chua's circuit, and apply these methods to study the effect of noise on identically driven chaotic circuits.
Normes de concrétude, de valeur d'imagerie, de fréquence subjective et de valence émotionnelle pour 866 mots

This article presents concreteness, imageability, subjective and emotional valence norms for a set of 866 words. The norms were collected from 97 participants, all French native speakers whose mean age was 23. Descriptive statistics and correlational analyses have been performed on these norms and on other estimated (age of acquistion, conceptual familiarity, image variability) and objective (word frequency) published indexes. The correlational analyses reveal the composite nature of certain estimations. In particular, subjective frequency and imageability are highly correlated with the other variables. Concreteness is highly correlated only with imageability and emotional valence, the latter which is weakly correlated with the other variables. Researchers must have at their disposal such information in order to select stimuli in factorial studies or to perform multiple regression analyses.
The effect of stratospheric sulfur from Mount Pinatubo on tropospheric oxidizing capacity and methane

The eruption of Mount Pinatubo in 1991 injected a large amount of SO2 into the stratosphere, which formed sulfate aerosols. Increased scattering and absorption of UV radiation by the enhanced stratospheric SO2 and aerosols decreased the amount of UV radiation reaching the troposphere, causing changes in tropospheric photochemistry. These changes affected the oxidizing capacity of the atmosphere and the removal rate of CH4 in the years following the eruption. We use the three‐dimensional chemistry transport model TM5 coupled to the aerosol microphysics module M7 to simulate the evolution of SO2 and sulfate aerosols from the Pinatubo eruption. Their effect on tropospheric photolysis frequencies and concentrations of OH and CH4 is quantified for the first time. We find that UV attenuation by stratospheric sulfur decreased the photolysis frequencies of both ozone and NO2 by about 2% globally, decreasing global OH concentrations by a similar amount in the first 2 years after the eruption. SO2 absorption mainly affects OH primary production by ozone photolysis, while aerosol scattering also alters OH recycling. The effect of stratospheric sulfur on global OH and CH4 is dominated by the effect of aerosol extinction, while SO2 absorption contributes by 12.5% to the overall effect in the first year after the eruption. The reduction in OH concentrations causes an increase in the CH4 growth rate of 4 and 2 ppb/yr in the first and second years after the eruption, respectively, contributing 11 Tg to the 27 Tg observed CH4 burden change in late 1991 and early 1992.
The Extrinsic Affective Simon Task.

A modified version of the Implicit Association Test (IAT) is described that is based on a comparison of perfor- mance on trials within a single task rather than on a comparison of performance on different tasks. In two experiments, participants saw white words that needed to be classified on the basis of stimulus valence and colored words that were to be classified on the basis of color. On trials where the colored word referred to a positive target concept (e.g., "flowers," "self "), performance was superior when the correct response was the response that was also assigned to positive white words. The reverse was true on trials where the colored word represented a negative target concept (e.g., "insect"). This variant of the IAT is less susceptible to nonassociative effects of task recoding and can be used to assess single and multiple attitudes.