Miracle-dz/UniFAR-FTUs huggingface dataset:
Recovery from on- and off-frequency forward masking in listeners with normal and impaired hearing.

The aim of this study was to investigate the possible mechanisms underlying an effect reported earlier [Wojtczak, M. , and Oxenham, A. J. (2009). J. Acoust. Soc. Am. 125, 270-281] in normal-hearing listeners, whereby recovery from forward masking can be slower for off-frequency tonal maskers than for on-frequency tonal maskers that produce the same amount of masking at a 0-ms masker-signal delay. To rule out potential effects of confusion between the tonal signal and tonal masker, one condition used a noise-band forward masker. To test whether the effect involved temporal build-up, another condition used a short-duration (30-ms) forward masker. To test whether the effect is dependent on normal cochlear function, conditions were tested in five listeners with sensorineural hearing loss. For the 150-ms noise maskers, the data from normal-hearing listeners replicated the findings from the previous study that used tonal maskers. In contrast, no significant difference in recovery from on- and off-frequency masking was observed for the 30-ms tonal maskers in normal-hearing listeners, or for the 150-ms tonal maskers in hearing-impaired listeners. Overall, the results are consistent with a mechanism based on efferent feedback that affects the recovery from forward masking in the normal auditory system.
Vancomycin MICs do not predict the outcome of methicillin-resistant Staphylococcus aureus bloodstream infections in correctly treated patients.

BACKGROUND Recent studies have reported a greater probability of vancomycin treatment failure in methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections caused by strains with a vancomycin MIC ≥ 1.5 mg/L. However, previous reports included patients treated without adjustments based on vancomycin serum levels and with different methods to evaluate MICs, which may render different results. METHODS Over a 5 year period (2005-09), vancomycin MICs were determined for 361 MRSA isolates recovered from 309 patients with bloodstream infection using microdilution and the Etest simultaneously. The relationship between the vancomycin MICs determined by each method was assessed. To assess the outcome of patients treated with vancomycin, 104 patients for whom serum vancomycin levels had been determined were selected. RESULTS The percentage of MRSA strains with MIC values ≥ 1.5 mg/L according to the Etest was 66.5% compared with only 3.6% according to microdilution. No correlation between mortality and any MIC value obtained with either method was observed, independently of the vancomycin serum levels measured. CONCLUSIONS There is a poor correlation between vancomycin MIC values obtained by microdilution and by Etest. No association between mortality rate and any MIC value was observed, not even in patients with suboptimal vancomycin trough serum levels. These data do not support replacing or complementing the standard microdilution test with the Etest for determination of MICs of vancomycin in microbiology laboratories.
PRINCIPAL ATTITUDES REGARDING ZERO TOLERANCE AND RACIAL DISPARITIES IN SCHOOL SUSPENSIONS

Zero tolerance school discipline practices have been associated with a national increase in suspensions, a practice that has had a disproportionate negative impact on Black students. The present study investigated an association between principal attitudes toward zero tolerance and suspension rates for White and Black students in 306 Virginia high schools. Black suspension rates were more than double White suspension rates. Regression analyses controlling for student poverty and school enrollment showed that principal endorsement of zero tolerance was moderately associated with suspension rates for both White and Black students, but was not associated with the size of the racial disparity. Paired-samples t tests showed statistically significant differences in the types of offenses that resulted in suspensions, with Black students significantly more likely to be suspended for disruptive offenses and White students more likely to be suspended for alcohol- and drug-related offenses.
Risk, Recidivism, and (Re)habilitation

Project Greenlight (GL) was an innovative and intensive prison-based intervention delivered to inmates during the 8-week period immediately prior to their release from prison. Using a relatively rigorous research design, evaluators reported significant negative effects associated with the treatment at one year after release. We reassess the GL intervention over a longer follow-up period and focus on differences by risk level. Findings indicate that although the bulk of the negative effects dissipate compared with one control group, significant negative effects remain when compared with a second. More importantly, however, we find that program effects are differentially distributed by risk level in a counterintuitive direction.
UvA-DARE (Digital Academic Repository) At odds: laughing and thinking? The appreciation, processing, and persuasiveness of political satire

This study constructs and experimentally tests an integrated framework of how political attitudes are affected by political satire. On the one hand, we show that political satire affects the attitude toward the satirized subject positively via perceived funniness. This was particularly strong among those who did not perceive the satire as potentially threatening, which follows disposition theory. On the other hand, young adults were found to be more absorbed into the satirical items, which decreased counterarguing, such that the attitude toward the satirized object was affected negatively. This is consistent with entertainment-education literature and theory about people’s life stages. Investigating underlying and conditional processes thereby proved to be a valuable approach to detecting the mechanisms by which satire influences attitudes.
Meta-analysis: The Placebo Rate of Abdominal Pain Remission in Clinical Trials of Chronic Pancreatitis

Objectives Treatment of the pain caused by chronic pancreatitis (CP) is not standardized. Knowledge of the response to placebo in this setting may aid the design of future trials. We aimed at investigating the placebo effect on abdominal pain remission rates in patients with CP. Methods MEDLINE, EMBASE, and Scopus were searched, and randomized placebo-controlled trials in CP providing data on abdominal pain remission rates in placebo arms were included. Pooled estimates of the placebo rate were calculated using random-effects logistic regression analysis. Stratum-specific rates for different patients and study-level covariates were calculated to account for heterogeneity. Results Seven randomized controlled trials (202 placebo-treated patients) met the predefined criteria. The pooled estimate of the placebo rate for pain remission was 19.9% (95% confidence interval, 9%–36%). There was a statistically significant heterogeneity among the studies (I2 = 76%; P < 0.001). A multicenter design, a run-in period of less than 2 weeks, and absence of a washout in crossover trials were all significant sources of heterogeneity associated with higher placebo responses. Conclusions This meta-analysis identifies for the first time the efficacy of placebo for pain in CP and variables determining it. These data provide a sound basis for designing future placebo-controlled randomized clinical trials for the treatment of pain in CP.
Engagement Models for Adolescents in DATOS-A

Based on the importance of during-treatment activities for improving outcomes, relationships between patient background, treatment readiness, and therapeutic engagement were examined in a national sample of adolescents admitted to 20 treatment programs representing three modalities. Patients with higher readiness for treatment at intake subsequently became more therapeutically involved, replicating previous findings on relationships between motivation and engagement in adult samples. One of the most influential background factors associated with higher treatment readiness was patient relationships with family and friends. Interventions that focus on treatment readiness appear to be appropriate strategies for improving treatment engagement.
Gait Planning of Omnidirectional Walk on Inclined Ground for Biped Robots

When a biped robot moves about in a physical environment, it may encounter inclined ground. Biped walking on inclined ground still remains challenging for biped robots. Previous studies have discussed biped walking on inclined ground along specific directions. However, omnidirectional walk on inclined ground has rarely been investigated. In this paper, we propose a gait pattern generation method for omnidirectional biped walking on inclined ground. First, a model that describes the motion of biped walking on inclined ground uniformly with two angle parameters is proposed. A mathematical relationship between motions in the sagittal and coronal planes of the biped robot are presented. Then, based on nonorthogonal motion decoupling, a method that generates gait patterns for omnidirectional walking with a double support phase for biped robots is proposed. The trajectories of each foot are designated by the walking speed, step length, and walking direction. The motion trajectory of the center of mass (CoM) of the robot is planned using a linear inverted pendulum model in the sagittal and coronal planes. The motion of CoM in the sagittal and coronal planes is constrained in parallel to the gradient vector of the inclined ground and the horizontal plane, respectively. Finally, the effectiveness of the proposed gait planning method for biped walking on is validated by simulations and experiments with an actual biped robot.
Social Identity Complexity

In this article, we introduce the concept of social identity complexity—a new theoretical construct that refers to an individual's subjective representation of the interrelationships among his or her multiple group identities. Social identity complexity reflects the degree of overlap perceived to exist between groups of which a person is simultaneously a member When the overlap of multiple ingroups is perceived to be high, the individual maintains a relatively simplified identity structure whereby memberships in different groups converge to form a single ingroup identification. When a person acknowledges, and accepts, that memberships in multiple ingroups are not fully convergent or overlapping, the associated identity structure is both more inclusive and more complex. In this article, we define the concept of social identity complexity and discuss its possible antecedents and consequences. Results from initial studies support the prediction that social identity complexity is affected by stress and is related to personal value priorities and to tolerance of outgroup members.
Changes in Young People's Sexual Behavior and Attitudes, 1943–1999: A Cross-Temporal Meta-Analysis

A cross-temporal meta-analysis of 530 studies (N = 269,649) showed that young people's sexual attitudes and behavior changed substantially between 1943 and 1999, with the largest shifts occurring among girls and young women. Both young men and women became more sexually active over time, as measured by age at first intercourse (decreasing from 19 to 15 years among young women) and percentage sexually active (increasing from 13% to 47% among young women). Attitudes toward premarital intercourse became more lenient, with approval increasing from 12% to 73% among young women and from 40% to 79% among young men. Feelings of sexual guilt decreased. The correlation between attitudes and behaviors was stronger among young women. These data support theories positing that culture has a larger effect on women's sexuality.
Super Nested Arrays: Linear Sparse Arrays With Reduced Mutual Coupling—Part I: Fundamentals

In array processing, mutual coupling between sensors has an adverse effect on the estimation of parameters (e.g., DOA). While there are methods to counteract this through appropriate modeling and calibration, they are usually computationally expensive, and sensitive to model mismatch. On the other hand, sparse arrays, such as nested arrays, coprime arrays, and minimum redundancy arrays (MRAs), have reduced mutual coupling compared to uniform linear arrays (ULAs). With <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> denoting the number of sensors, these sparse arrays offer <inline-formula><tex-math notation="LaTeX">$O({N}^{2})$</tex-math></inline-formula> freedoms for source estimation because their difference coarrays have <inline-formula><tex-math notation="LaTeX"> $O({N}^{2})$</tex-math></inline-formula>-long ULA segments. But these well-known sparse arrays have disadvantages: MRAs do not have simple closed-form expressions for the array geometry; coprime arrays have holes in the coarray; and nested arrays contain a dense ULA in the physical array, resulting in significantly higher mutual coupling than coprime arrays and MRAs. This paper introduces a new array called the super nested array, which has all the good properties of the nested array, and at the same time achieves reduced mutual coupling. There is a systematic procedure to determine sensor locations. For fixed <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>, the super nested array has the same physical aperture, and the same hole-free coarray as does the nested array. But the number of sensor pairs with small separations (<inline-formula><tex-math notation="LaTeX">$\lambda /2,2\times \lambda /2$</tex-math></inline-formula>, etc.) is significantly reduced. Many theoretical properties are proved and simulations are included to demonstrate the superior performance of these arrays. In the companion paper, a further extension called the <inline-formula><tex-math notation="LaTeX">$Q$</tex-math></inline-formula>th-order super nested array is developed, which further reduces mutual coupling.
A Graph Analytical Approach for Topic Detection

Topic detection with large and noisy data collections such as social media must address both scalability and accuracy challenges. KeyGraph is an efficient method that improves on current solutions by considering keyword cooccurrence. We show that KeyGraph has similar accuracy when compared to state-of-the-art approaches on small, well-annotated collections, and it can successfully filter irrelevant documents and identify events in large and noisy social media collections. An extensive evaluation using Amazon’s Mechanical Turk demonstrated the increased accuracy and high precision of KeyGraph, as well as superior runtime performance compared to other solutions.
Immunomodulatory Effect of Continuous Venovenous Hemofiltration during Sepsis: Preliminary Data

Introduction. Severe sepsis and septic shock are the primary causes of multiple organ dysfunction syndrome (MODS), which is the most frequent cause of death in intensive care unit patients. Many pro- and anti-inflammatory mediators, such as interleukin-6 (IL-6), play a strategic role in septic syndrome. Continuous renal replacement therapy (CRRT) removes in a nonselective way pro- and anti-inflammatory mediators. Objective. To investigate the effects of continuous venovenous hemofiltration (CVVH) as an immunomodulatory treatment of sepsis in a prospective clinical study. Methods. High flux hemofiltration (Qf = 60 ml/Kg/hr) was performed for 72 hr in thirteen critically ill patients suffering from severe sepsis or septic shock with acute renal failure (ARF). IL-6 gene expression was measured by real-time PCR analysis on RNA extracted from peripheral blood mononuclear cell before beginning of treatment (T0) and after 12, 24, 48, and 72 hours (T1–4). Results. Real-time PCR analysis demonstrated in twelve patients IL-6 mRNA reduction after 12 hours of treatment and a progressive increase after 24, 48, and 72 hours. Conclusions. We suggest that an immunomodulatory effect might exist during CVVH performed in critically ill patients with severe sepsis and septic shock. Our data show that the transcriptional activity of IL-6 increases during CVVH.
REAL OPTION MODELS FOR MANAGING MANUFACTURING SYSTEM CHANGES IN THE NEW ECONOMY

ABSTRACT The manufacturing environment is becoming increasingly dynamic with upsurges in electronic-commerce, supply chain management, forecasting, and procurement and resource planning. It also includes trends toward more process data acquisition and analysis, shorter production runs, and more stringent quality requirements. These drivers lead to an opportunity for companies to collect and use information to identify changes that will affect their manufacturing systems. In conjunction with an industry partner who produces home fashion products, we developed a case-study that highlights four major manufacturing transitions: new product introduction; moving a product from research and development (R&D) to commercialization: new plant location; and starting or restarting production of existing products. These types of changes cross many levels of the operation - including the product level, plant level, and organizational level - and typically present significant operational challenges. We use this case-study to motivate the theoretical and applied research needed to support a real option framework for system changes in manufacturing. The key elements of our framework are to quantify manufacturing changes, develop a real option model for these activities, value the options to identify the best scenarios, and integrate these elements so that we can monitor and manage the overall process. The advantage of this approach is that it allows us to directly incorporate a market driven perspective, tying the manufacturing operations with the organizational economic goals.
Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure

Naive Bayesian learning has been popular in data mining applications. However, the performance of naive Bayesian learning is sometimes poor due to the unrealistic assumption that all features are equally important and independent given the class value. Therefore, it is widely known that the performance of naive Bayesian learning can be improved by mitigating this assumption, and many enhancements to the basic naive Bayesian learning have been proposed to resolve this problem including feature selection and feature weighting. In this paper, we propose a new method for calculating the weights of features in naive Bayesian learning using Kullback-Leibler measure. Empirical results are presented comparing this new feature weighting method with some other methods for a number of datasets.
Analysis of the association between socio-demographic variables, juvenile offending, and formal vs. informal juvenile justice system handling in a non-urban sample

PURPOSE: This study compares and contrasts first-time juvenile offenders enrolled in a community-based intervention program whose cases were processed either informally or formally, and examines empirically- and conceptually-relevant contributors to re-offending. METHODS: This is a longitudinal, secondary analysis of 1072 male and female offenders. The study includes descriptive univariate analyses; chi-square bivariate analyses of each independent variable with the dependent variables (level of processing and recidivism at both one and three years); and binary logistic regression analyses to identify significant predictors of the dependent variables. Independent variables include age, gender, race, family structure, marital status of biological parents, family income, number of children in the home, type of offense, program completion, and POSIT risk scores (including substance abuse, physical health, mental health, family relationships, peer relationships, educational status, and aggressive behavior/delinquency). RESULTS: Variables significantly associated with level of processing were race, gender, type of offense, marital status of the biological parents, number of children in the home, and family relationship risk. Multivariate predictors of formal levels of processing were age, gender, race, type of offense, marital status of biological parents, and the number of children in the home. For one-year recidivism, analysis showed significant associations with level of processing and educational risk. Recidivism within three years was associated with age, program completion, and educational risk. Logistic Regression models showed family income, marital status of biological parents, and program completion are predictors of one-year recidivism. For predictors of three-year recidivism, age, family income, program completion, marital status of the biological parents, and mental health risk had significant partial effects. CONCLUSION: A greater understanding of the factors that are associated with and predict level of juvenile justice processing and recidivism for first-time juvenile offenders is critical to the success of the juvenile justice system and its associated intervention efforts as this is the group of youth active in the system in the largest proportions at any given time. This study lends to that understanding and offers analysis of both male and female youth in a non-urban setting and examines how family characteristics are associated specifically with level of processing, which are unique attributes compared with juvenile justice studies in the literature.
Efficient Subspace Segmentation via Quadratic Programming

We explore in this paper efficient algorithmic solutions to robustsubspace segmentation. We propose the SSQP, namely SubspaceSegmentation via Quadratic Programming, to partition data drawnfrom multiple subspaces into multiple clusters. The basic idea ofSSQP is to express each datum as the linear combination of otherdata regularized by an overall term targeting zero reconstructioncoefficients over vectors from different subspaces. The derivedcoefficient matrix by solving a quadratic programming problem istaken as an affinity matrix, upon which spectral clustering isapplied to obtain the ultimate segmentation result. Similar tosparse subspace clustering (SCC) and low-rank representation (LRR),SSQP is robust to data noises as validated by experiments on toydata. Experiments on Hopkins 155 database show that SSQP can achievecompetitive accuracy as SCC and LRR in segmenting affine subspaces,while experimental results on the Extended Yale Face Database Bdemonstrate SSQP's superiority over SCC and LRR. Beyond segmentationaccuracy, all experiments show that SSQP is much faster than bothSSC and LRR in the practice of subspace segmentation.
Facial Expressions in Context: Electrophysiological Correlates of the Emotional Congruency of Facial Expressions and Background Scenes

Facial expressions can display personal emotions and indicate an individual’s intentions within a social situation. They are extremely important to the social interaction of individuals. Background scenes in which faces are perceived provide important contextual information for facial expression processing. The purpose of this study was to explore the time course of emotional congruency effects in processing faces and scenes simultaneously by recording event-related potentials (ERPs). The behavioral results found that the categorization of facial expression was faster and more accurate when the face was emotionally congruent than incongruent with the emotion displayed by the scene. In ERPs the late positive potential (LPP) amplitudes were modulated by the emotional congruency between faces and scenes. Specifically, happy faces elicited larger LPP amplitudes within positive than within negative scenes and fearful faces within negative scenes elicited larger LPP amplitudes than within positive scenes. The results did not find the scene effects on the P1 and N170 components. These findings indicate that emotional congruency effects could occur in late stages of facial expression processing, reflecting motivated attention allocation.