Miracle-dz/UniFAR-FTUs huggingface dataset:
Active exploration: simultaneous sampling and labeling for large graphs

Modern information networks, such as social networks, are often characterized with large sizes and dynamic changing structures. To analyze these networks, existing solutions commonly rely on graph sampling techniques to reduce network sizes, and then carry out succeeding mining processes, such as labeling network nodes to build classification models. Such a sampling-then-labeling paradigm assumes that the whole network is available for sampling and the sampled network is useful for all subsequent tasks (such as network classification). Yet real-world networks are rarely immediately available unless the sampling process progressively crawls every single node and its connections. Meanwhile, without knowing the underlying analytic objective, the sampled network can hardly produce quality results. In this paper, we propose an Active Exploration framework for large graphs where the goal is to carry out network sampling and node labeling at the same time. To achieve this goal, we consider a network as a Markov chain and compute its stationary distribution by using supervised random walks. The stationary distribution of the sampled network help identify important nodes to be explored in the next step, and the labeling process labels the most informative node which in turn strengthens the sampling process. The mutually and simultaneously enhanced sampling and labeling processes ensure that the final network contains a maximum number of nodes directly related to the underlying mining tasks.
A Scalable and Skew-insensitive Algorithm for Join Operations using Map/Reduce Model

For over a decade, Map/Reduce has become a prominent programming model to handle vast amounts of raw data in large scale systems. This model ensures scalability, reliability and availability aspects with reasonable query processing time. However these large scale systems still face some challenges\,: data skew, task imbalance, high disk i/o and redistribution costs can have disastrous effects on performance. In this paper, we introduce MRFA-Join algorithm: a new Frequency Adaptive algorithm based on Map/Reduce Programming model and distributed histograms for join processing on large-scale datasets. A cost analysis of this algorithm shows that our approach is insensitive to data skew and ensures perfect balancing properties during all stages of join computation. Performances have been experimented on Grid'5000 infrastructure.
Age-related differences in construal level theory: implications for product concept testing

decontextualized, and high-level terms (Liberman and Trope 1998). As such, people considering near future-events are more likely to focus on the details of an event than those considering distant-future events (Trope and Liberman 2000). In an early study on the effect of temporal distance on construal, Liberman and Trope (1998) asked respondents to describe either near (i.e., tomorrow) or distant (i.e., sometime next year) future events. They found that people have concrete and detailed representation for nearfuture rather than for distant-future events. For example, in the distant future ‘‘making a list’’ was described as ‘‘getting organized,’’ whereas in the near future this activity was described as ‘‘writing things down. ’’ In another example, ‘‘paying the rent’’ was described as ‘‘maintaining a place to live’’ in the distant future and as ‘‘writing a check’’ in the near future. In a more recent study, Fujita et al. (2008) argue that the temporal distance of attitude objects systematically changes what features of an attitude object are attended to and perceived as relevant. When attitude objects are temporally distant (vs. near), arguments highlighting primary (vs. secondary) features, desirability (vs. feasibility) features, and general classes (vs. specific cases) are found to be more effective for persuasion because increasing temporal
Accuracy of Fitbit Wristbands in Measuring Sleep Stage Transitions and the Effect of User-Specific Factors

Background It has become possible for the new generation of consumer wristbands to classify sleep stages based on multisensory data. Several studies have validated the accuracy of one of the latest models, that is, Fitbit Charge 2, in measuring polysomnographic parameters, including total sleep time, wake time, sleep efficiency (SE), and the ratio of each sleep stage. Nevertheless, its accuracy in measuring sleep stage transitions remains unknown. Objective This study aimed to examine the accuracy of Fitbit Charge 2 in measuring transition probabilities among wake, light sleep, deep sleep, and rapid eye movement (REM) sleep under free-living conditions. The secondary goal was to investigate the effect of user-specific factors, including demographic information and sleep pattern on measurement accuracy. Methods A Fitbit Charge 2 and a medical device were used concurrently to measure a whole night’s sleep in participants’ homes. Sleep stage transition probabilities were derived from sleep hypnograms. Measurement errors were obtained by comparing the data obtained by Fitbit with those obtained by the medical device. Paired 2-tailed t test and Bland-Altman plots were used to examine the agreement of Fitbit to the medical device. Wilcoxon signed–rank test was performed to investigate the effect of user-specific factors. Results Sleep data were collected from 23 participants. Sleep stage transition probabilities measured by Fitbit Charge 2 significantly deviated from those measured by the medical device, except for the transition probability from deep sleep to wake, from light sleep to REM sleep, and the probability of staying in REM sleep. Bland-Altman plots demonstrated that systematic bias ranged from 0% to 60%. Fitbit had the tendency of overestimating the probability of staying in a sleep stage while underestimating the probability of transiting to another stage. SE>90% (P=.047) was associated with significant increase in measurement error. Pittsburgh sleep quality index (PSQI)<5 and wake after sleep onset (WASO)<30 min could be associated to significantly decreased or increased errors, depending on the outcome sleep metrics. Conclusions Our analysis shows that Fitbit Charge 2 underestimated sleep stage transition dynamics compared with the medical device. Device accuracy may be significantly affected by perceived sleep quality (PSQI), WASO, and SE.
Stock Market Predictability: Is it There? A Critical Review

This paper aims to survey selected recent papers presenting new evidence on an age-old question in financial economics: “Are stock market returns predictable? ”. The hypothesis that equity returns are predictable (specifically at long horizons) has been called a “new fact in finance” by Cochrane (1999). Thus, stock market predictability is now taken almost as a feature of the data. However, there is less consensus on what drives this predictability. It may reflect time-varying risk premiums, it may reflect irrational behavior on the part of market participants, or it may simply not present in the data — a statistical fluke due to poor statistical inference. It is this last possibility that seems to gain increasing credibility considering the long list of authors criticizing the statistical methodologies in the predictability literature. The results of these studies typically show that findings against the constant expected excess return hypothesis based on standard statistical inference can appear much more significant than they really are. Of course, the strength and usefulness of these critical results are still hotly debated — consistently evaluating their significance is thus no easy task. Still, they raise questions about the implications of these findings for the way academics and practitioners use financial theory. In particular, the implications for the asset management industry (and dynamic asset allocation strategies) may be serious. ∗Department of Finance, WWZ University of Basel, Holbeinstrasse 12, 4051 Basel, Switzerland; Phone: +41-61-267 33 07, Mail: david.rey@unibas.ch. Preliminary version. We thank Stefan Beiner and especially Daniel Hoechle for helpful comments and discussions. Financial support from the National Center of Competence in Research “Financial Valuation and Risk Management” (NCCR FINRISK) is gratefully acknowledged. The NCCR FINRISK is a research program supported by the Swiss National Science Foundation. A short version appears in Financial Markets and Portfolio Management 17/3, 2003 (Current Research Topics).
Beneficial Effects of Sitostanol on the Attenuated Immune Function in Asthma Patients: Results of an In Vitro Approach

Background In vitro and animal studies have suggested that plant sterols and stanols increase cytokine production by T-helper-1 cells. This may be beneficial for patient groups characterized by a T-helper-2 dominant immune response, e.g. asthma patients. (1) to evaluate whether sitostanol induces a T-helper-1 shift in peripheral blood mononuclear cells (PBMCs) from asthma patients, and (2) to unravel the role of regulatory T-cells in this respect. Methodology/Principal Findings PBMCs from 10 asthma patients and 10 healthy subjects were isolated and incubated with 1.2 µM sitostanol, while stimulated with 5 µg/ml PHA. Similar amounts of cholesterol were used to determine whether effects were specific for plant stanols or for sterols in general. Changes in cytokine production were measured using antibody arrays and ELISAs. Changes in regulatory T-cell population size were measured by flow cytometry, using intracellular Foxp3 staining. Sitostanol increased production of IFNγ by 6.5% and IL-2 by 6.0% compared to cholesterol (p<0.01). No changes in IL-4 and IL-13 were found. Interestingly, this effect was only present in PBMCs from asthma patients. The number of Foxp3+ cells tended to increase and their activity, measured by IL-10 production, increased after sitostanol treatment in PBMCs from asthma patients compared to controls by 32.3% (p = 0.077) and 13.3% (p<0.05), respectively. Conclusions/Significance Altogether, the sitostanol-induced Thelper-1 shift in PBMCs from asthma patients and the stimulating effects of sitostanol on Treg cell numbers and activity indicate a possible novel approach for plant stanol ester enriched functional foods in the amelioration of asthmatic symptoms. Functional effects, however, require further evaluation.
Government at Risk

The findings, interpretations, and conclusions expressed here are those of the author(s) and do not necessarily reflect the views of the Board of Executive Directors of the World Bank or the governments they represent. The World Bank cannot guarantee the accuracy of the data included in this work. The boundaries, colors, denominations, and other information shown on any map in this work do not imply on the part of the World Bank any judgment of the legal status of any territory or the endorsement or acceptance of such boundaries. The material in this work is copyrighted. No part of this work may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or inclusion in any information storage and retrieval system, without the prior written permission of the World Bank. The World Bank encourages dissemination of its work and will normally grant permission promptly. For permission to photocopy or reprint, please send a request with complete information to the Foreword In public finance, it no longer suffices for analysts and institutions to focus solely on budget revenues and expenditures. Recent history demonstrates that fiscal performance and, in turn, economic development can be seriously disrupted by the sudden, unexpected costs of hidden contingent liabilities and other unanticipated fiscal risks. During the second half of the 1990s, unreported contingent liabilities and related fiscal risks contributed to economic crises and disrupted growth in a number of developing countries, motivating stepped-up efforts at the World Bank to devise new concepts and tools for analyzing and managing public finance. With the aim of improving the analysis of fiscal risks and supporting policy advice in this area, the Economic Policy Unit of the Bank's Poverty Reduction and Economic Management Network established the Quality of Fiscal Adjustment Thematic Group. This book was produced as part of the effort by this Thematic Group to promote new thinking about public finance. We now know that conventional frameworks for fiscal analysis that concentrate on direct, explicit liabilities fail to address contingent fiscal risks. For example, fiscal sustainability analysis that focuses, as is typically the case, on the officially reported budget deficits fails to detect possible future increases in government debt and payments that may emerge from both explicit and implicit government guarantees on enterprise credit, state insurance schemes, exchange rate guarantees, and commitments to assist failed banks. Similarly, the government budget process and …
Analysis of QRS Detection Algorithm for Cardiac Abnormalities - A Review

This work investigates and compares a set of efficient techniques to extract and select striking features from th e ECG data applicable in automatic cardiac beat classification. Each method was applied to a pre-selected data segment from the MIT-BIH (Massachusetts Institute of Technology / Beth Isrel Hospital) database. The classification and optimization of different heart beat methods were performed based upon the extracted features (morphological and statistical feature). The morphological features were found as the most important for arrhythmia classification. However, because of ECG signal variability in different patients, the statistical approach is favoured for a precise and robust feature extraction. Amo ng all these feature extraction, feature selection, classification a nd optimization techniques, SVM based PSO gives higher classification accuracy with curse of dimensionality.
On low-frequency electric power generation with PZT ceramics

Piezoelectric materials have long been used as sensors and actuators, however their use as electrical generators is less established. A piezoelectric power generator has great potential for some remote applications such as in vivo sensors, embedded MEMS devices, and distributed networking. Such materials are capable of converting mechanical energy into electrical energy, but developing piezoelectric generators is challenging because of their poor source characteristics (high voltage, low current, high impedance) and relatively low power output. In the past these challenges have limited the development and application of piezoelectric generators, but the recent advent of extremely low power electrical and mechanical devices (e.g., MEMS) make such generators attractive. This paper presents a theoretical analysis of piezoelectric power generation that is verified with simulation and experimental results. Several important considerations in designing such generators are explored, including parameter identification, load matching, form factors, efficiency, longevity, energy conversion and energy storage. Finally, an application of this analysis is presented where electrical energy is generated inside a prototype Total Knee Replacement (TKR) implant.
Effects of Dual-Channel Functional Electrical Stimulation on Gait Performance in Patients with Hemiparesis

The study objective was to assess the effect of functional electrical stimulation (FES) applied to the peroneal nerve and thigh muscles on gait performance in subjects with hemiparesis. Participants were 45 subjects (age 57.8 ± 14.8 years) with hemiparesis (5.37 ± 5.43 years since diagnosis) demonstrating a foot-drop and impaired knee control. Thigh stimulation was applied either to the quadriceps or hamstrings muscles, depending on the dysfunction most affecting gait. Gait was assessed during a two-minute walk test with/without stimulation and with peroneal stimulation alone. A second assessment was conducted after six weeks of daily use. The addition of thigh muscles stimulation to peroneal stimulation significantly enhanced gait velocity measures at the initial and second evaluation. Gait symmetry was enhanced by the dual-channel stimulation only at the initial evaluation, and single-limb stance percentage only at the second assessment. For example, after six weeks, the two-minute gait speed with peroneal stimulation and with the dual channel was 0.66 ± 0.30 m/sec and 0.70 ± 0.31 m/sec, respectively (P < 0.0001). In conclusion, dual-channel FES may enhance gait performance in subjects with hemiparesis more than peroneal FES alone.
Automatic Identification of Sports Video Highlights using Viewer Interest Features

Classification of viewer interest using facial expression and heart rate facilitates automatic identification of interest evoking video segments. Sports video is suitable for testing the effectiveness of such a system as it has structured segments with distinguishable highlight events. Previous work has not investigated the differences in viewer interest characteristics from one sports type to another, which is crucial for appropriate classification methodology. Thus, it is still unclear whether a universal classification model can be used for analyzing viewer interest for all types of sports. This paper addresses this gap by demonstrating a significant difference (p < 0.05) in the distributions of viewer interest data in soccer compared to tennis. Based on this finding, this paper proposes an adoption of Gaussian mixture models (GMM) to integrate sports-specific and sports-independent approaches for identifying video segments, which would be of potential interest to individual viewers. The approaches achieve 52% to 64% accuracy, demonstrating that sports-specific approach gets better performance.
Effective superpotentials for B-branes in Landau-Ginzburg models

We compute the partition function for the topological Landau-Ginzburg B-model on the disk. This is done by treating the worldsheet superpotential perturbatively. We argue that this partition function as a function of bulk and boundary perturbations may be identified with the effective D-brane superpotential in the target spacetime. We point out the relationship of this approach to matrix factorizations. Using these methods, we prove a conjecture for the effective superpotential of Herbst, Lazaroiu and Lerche for the A-type minimal models. We also consider the Landau-Ginzburg theory of the cubic torus where we show that the effective superpotential, given by the partition function, is consistent with the one obtained by summing up disk instantons in the mirror A-model. This is done by explicitly constructing the open-string mirror map.
Assessing the Behavior and Needs of Veterans with Traumatic Brain Injury in Washington State Prisons: Establishing a Foundation for Policy, Practice, and Education

Abstract A growing awareness of justice-involved veterans is revealing how little is known about this population, to what extent they have experienced a traumatic brain injury (TBI), and how this may relate to institutional behavior, participation in programs, and use of institutional resources. The current study identifies the prevalence of incarcerated veterans in Washington State who have experienced a TBI and how a TBI history may affect their prison experience and use of prison resources. The results of our study show that incarcerated veterans in Washington State with a moderate-to-severe TBI are more likely to use medical services, commit violent infractions, be placed in maximum custody (solitary confinement), and less likely to complete vocational and job skills programs. The importance of these findings to policy and practice is discussed.
Simple Likelihood and Probability Calculations for Linkage Analysis

SUMMARY Linkage analysis using all available pedigree data can be extremely complicated. We point out that by suitably restricting the data to the most informative nuclear families, we may be able to make a simple analysis for linkage between two loci without too much loss of information. The method can be readily extended to cases of heterogeneity, where there may be more than one cause of the disease or other apparently inherited character under consideration.
Structure and Hue Similarity for Color Image Quality Assessment

An improved model (SHSIM) for color image quality assessment is proposed in this paper, which is based on the fact that structural and color information are all important for human viewers to evaluate images quality. The relative importance values of two components are determined through the experiments. Our experimental results indicate that SHSIM performs a little better than SSIM which focus on structural information of images, and better than CD-PSNR which works with color information only.
Frontiers in Aging Neuroscience Aging Neuroscience

improvements in cognitive function are associated with increased gray matter volume (Colcombe et al., 2003, 2006). Recently, it has been shown that aerobic fitness is associated with increased hip-pocampal volumes (Erickson et al., 2009) and improved brain blood flow (Swain et al., 2003; Pereira et al., 2007), findings that are particularly important considering the role of the hippocam-pus in memory processing. In addition to the observed structural changes in the brain, research indicates that exercise can alter brain activity associated with cognitive tasks (Colcombe et al., 2004) and functional connectivity (Voss et al., 2010). Here, we argue that using network science techniques to study the brain as an integrated network can begin to elucidate the mechanisms underlying the known hippocampal changes associated with exercise. These network science techniques can determine whole-brain summary network metrics, which describe various global brain network properties, such as global clustering or network-wide average path length. In fact, summary metrics extracted from whole-brain networks can exhibit changes in various study populations, However, such changes are insensitive to the regional specificity of the human brain. Our belief is that network metrics are best evaluated at the local/regional level
MobiScape: WWW browsing under disconnected and semi-connected operation

Although some browsers, such as Netscape, already o(cid:11)er some support for operation under low bandwidth connections, present WWW navigation tools are still unsuited for mobile environments. When bandwidth is low and connection time is expensive, clients cannot af-ford long sessions. MobiScape uses the proxy interface, present on modern navigation tools, to intercept the HTTP data (cid:13)ow, compress it, and apply caching, hoarding and prefetching policies on both the mobile host and support station. Both layers (two peer-to- peer proxies) have associated pro(cid:12)le scripts that control part of their behaviour. The SS layer will try to keep a given subset of remote pages in local store and up-to-date, and will ocasionaly prefetch. The MH layer will hoard accordingly to its pro(cid:12)le, trying to minimize the need for a connection. Both layers maximize the use of the cache space by also using dynamic caching policies. (cid:3)
Single image super-resolution via online dictionary learning with double regularization parameters

The performance of single image super-resolution (SR) based on sparse coding is promising but the artifacts are obvious. In order to promote the SR efficiency, the proposed algorithm employs Online Dictionary Learning (ODL) to train the overcomplete dictionaries separately to reduce the artifacts. It sets two different regularization parameters in the phases of dictionary learning and image reconstruction. They are tuned independently to get the best results. In the experiments, the PSNRs are 0.41dB higher than Sparse Coding Super-Resolution (SCSR) and 0.28dB higher than ODL SR algorithm in average. The proposed method can eliminate the artifacts and recover the texture details efficiently.