Miracle-dz/UniFAR-FTUs huggingface dataset:
Prospective association between e‐cigarette use frequency patterns and cigarette smoking abstinence among adult cigarette smokers in the United States

Abstract Aims To estimate the association of longitudinal patterns of e‐cigarette use with cigarette smoking abstinence, after accounting for time‐dependent confounding and selection bias. Design Secondary analysis of longitudinal national cohort data. Using marginal structural models and four waves of the population assessment of tobacco and health (wave 1, 2013–14; wave 2, 2014–15; wave 3, 2015–16; wave 4, 2016–18), we estimated the association of vaping frequency across waves 2 and 3 with 12‐month sustained cigarette smoking abstinence at wave 4, adjusting for time‐dependent confounders at waves 1 and 2 and selection bias due to drop‐out with inverse probability of treatment and censoring weights. Setting United States. Participants/cases A total of 5699 adults (18+ years) who smoked cigarettes and did not vape at wave 1. Measurements The exposure was vaping frequency at waves 2 and 3 (non‐use, non‐daily use, daily use), representing nine possible combinations of vaping frequency across two waves. Non‐use at both waves was the exposure reference group. The primary outcome was sustained 12‐month cigarette smoking abstinence at wave 4. Findings Among 5699 adults who smoked cigarettes at wave 1, a total of 560 (9.8%) reported smoking abstinence at wave 4. Compared with nonuse at both waves, daily vaping at both waves [risk ratio (RR) = 3.82, 95% confidence interval (CI) = 2.59–5.64] and non‐use at wave 2 followed by daily vaping at wave 3 (RR = 2.50, 95% CI = 1.66–3.77) were positively associated with smoking abstinence; non‐daily vaping at both waves was inversely associated with smoking abstinence (RR = 0.28, 95% CI = 0.11–0.75). Results persisted after accounting for misclassification of e‐cigarette use and cigarette smoking abstinence and after restricting to participants with plans to quit smoking. Conclusions In a US cohort of adult smokers, longitudinal patterns of vaping frequency appear to predict smoking abstinence, even after accounting for several sources of systematic error. Consistent daily vaping is associated with increased chances of cigarette smoking abstinence, while consistent non‐daily vaping is associated with decreased chances of smoking abstinence.
LOCAL ENVIRONMENTAL EFFECTS ON AGN ACTIVITIES

< 19) sampleof galaxies via visual inspection and the de nition of galaxy pair systems based on the Sloan Digital SkySurvey Data Release 7 in order to con rm the e ects of galaxy interaction on AGN activities. We foundthat local environmental e ects such as galaxy interaction have an inuence on the enhancement of thefrequency and the strength of the AGN activity. This article is the summary of the paper which will besubmitted soon.Key words: galaxies: active - galaxies: interactions1. INTRODUCTIONActive Galactic Nucleus (AGN) are one of the most pow-erful objects in the universe. These days, it is gener-ally accepted that AGNs are powered by the accretionof materials onto a supermassive black hole (SMBH;Lynden-Bell et al., 1969), which is located in the centerof the galaxy. Over the last few decades, there have beenmany studies of the physical mechanisms powering theAGN. Several mechanisms, including stellar winds, diskinstabilities and galaxy-galaxy interactions, have beenproposed to explain this phenomenon, but the primarymechanism that turns a quiescent SMBH into an AGNis still unclear.Of these mechanisms, galaxy mergers provide an ap-pealing mechanism for triggering galactic nuclear ac-tivities, as modern cosmology predicts that there arefrequent interactions between a galaxy and its environ-ment during its evolution. Many statistical studies havebeen undertaken with large samples, to investigate thelink between AGN host galaxies and their environments.Some found some hints for the positive e ects of envi-ronments on AGN activity (Miller et al., 2003; Kau -mann et al., 2004; Serber et al., 2006; Alonso et al.,2007; Koss et al., 2010; Schawinski et al., 2010; Ellisonet al., 2011; Silverman et al., 2011; Liu et al., 2012),but others found no signi cant evidence (Schmitt, 2001;Grogin et al., 2005; Coldwell & Lambas, 2006; Gabor etal., 2009; Sabater et al., 2012). Several factors includingAGN diagnostics, data sets, and particularly the de ni-tion of the merger criteria, may contribute to these con-troversial results. In this study, we tried to statistically nd the link between the local environment surroundinggalaxies and galactic activity, using homogeneous sam-http://pkas.kas. orgples.2. DATA & METHODOLGYUsing the nearby(0.01< z <0.05) volume-limited(M
THE INFLUENCE OF THE SKIN FATIGUE, ITS PERSPIRATION AND THE TIME OF STIMULATION IN MEASUREMENT OF THE ACTIVE POINTS ON HUMAN SKIN

Our contribution deals with the human skin voltage chart measurement. The human skin has a certain impedance or resistance - it can be relatively easily described and simulated using a substitute electric circuit. But the skin also contains parts with measurably lower impedance and different electric properties – we can show them clearly by measurement of voltage chart. We have concentrated our effort on finding and following measurements of active points on certain part of the skin's surface, to acknowledge their existence and positions through a measuring process. The parameters of the measured voltage chart are influenced by the amplitude, frequency, the shape of the measuring electric signal and the parameters of skin-electrode connection changing in time. We focused our research effort in this paper to measure the influence of the time of external stimulation, irritation and a contact press on skin surface together with the skin fatigue and perspiration effects.
Diagnosis of Subclinical Endometritis and its Effect on Reproductive Performance

Chronic endometritis is a common disorder in postpartum dairy cows. It causes depressed reproductive performance in the current lactation and economic losses. In practice, rectal palpation and/or vaginoscopy are popular methods for the diagnosis of endometritis. The objective of this study was to evaluate a cytological method (cytobrush) as a diagnostic tool to detect subclinical endometritis (SE) in dairy cows and to quantify its effect on reproductive performance.
University of Birmingham Ribonuclease inhibitor 1 regulates erythropoiesis by controlling GATA1 mRNA translation

Ribosomal proteins (RP) regulate specific gene expression by selectively translating subsets of mRNAs. Indeed, in Diamond-Blackfan anemia and 5q – syndrome, mutations in RP genes lead to a specific defect in erythroid gene translation and cause anemia. Little is known about the molecular mechanisms of selective mRNA translation and involvement of ribosomal-associated factors in this process. Ribonuclease inhibitor 1 (RNH1) is a ubiquitously expressed protein that binds to and inhibits pancreatic-type ribonucleases. Here, we report that RNH1 binds to ribosomes and regulates erythropoiesis by controlling translation of the erythroid transcription factor GATA1. Rnh1 -deficient mice die between embryonic days E8.5 and E10 due to impaired production of mature erythroid cells from progenitor cells. In Rnh1 -deficient embryos, mRNA levels of Gata1 are normal, but GATA1 protein levels are decreased. At the molecular level, we found that RNH1 binds to the 40S subunit of ribosomes and facilitates polysome formation on Gata1 mRNA to confer transcript-specific translation. Further, RNH1 knockdown in human CD34 + progenitor cells decreased erythroid differentiation without affecting myelopoiesis. Our results reveal an unsuspected role for RNH1 in the control of GATA1 mRNA translation and erythropoiesis. In Rnh1 -deficient embryos, mRNA levels of Gata1 are normal, but GATA1 protein levels are decreased. At the molecular level, we found that RNH1 binds to the 40S subunit of ribosomes and facilitates polysome formation on Gata1 mRNA to confer transcript-specific translation. Further, RNH1 knockdown in human CD34 + progenitor cells decreased erythroid differentiation without affecting myelopoiesis. Our results reveal an unsuspected role for RNH1 in the control of GATA1 mRNA translation and erythropoiesis.
Dynamics and noise radiation of multiple bubbles in compressible fluid using boundary integral equation

Purpose – The purpose of this paper is to research the interaction between multiple bubbles and their noise radiation considering the influence of compressibility. The influences of bubble spacing, initial inner pressure, buoyance and phase difference are presented with different bubbles arrangements. Design/methodology/approach – Based on wave equation, the new boundary integral equation considering the compressibility is given by the matching between prophase and anaphase approximation of bubble motion and solved with boundary element method. The time-domain characteristics of noise induced by multiple bubbles are obtained by the moving boundary Kirchhoff integral equation. With the surface discretization and coordinate transformation, the bubbles surface is treated as a moving deformable boundary and noise source, and the integral is implemented on the surface directly. Findings – Numerical results show the manner of jet generation will be affected by the phase difference between bubbles. With the incr.
Wang, Yin and Hamilton, Antonia F. de C. (2013) Understanding the role of the ‘self’ in the social priming

People have a tendency to unconsciously mimic other’s actions. This mimicry has been regarded as a prosocial response which increases social affiliation. Previous research on social priming of mimicry demonstrated an assimilative relationship between mimicry and prosociality of the primed construct: prosocial primes elicit stronger mimicry whereas antisocial primes decrease mimicry. The present research extends these findings by showing that assimilative and contrasting primeto-behavior effect can both happen on mimicry. Specifically, experiment 1 showed a robust contrast priming effect where priming antisocial behaviors induces stronger mimicry than priming prosocial behaviors. In experiment 2, we manipulated the self-relatedness of the pro/antisocial primes and further revealed that prosocial primes increase mimicry only when the social primes are self-related whereas antisocial primes increase mimicry only when the social primes are self-unrelated. In experiment 3, we used a novel cartoon movie paradigm to prime pro/antisocial behaviors and manipulated the perspectivetaking when participants were watching these movies. Again, we found that prosocial primes increase mimicry only when participants took a first-person point of view whereas antisocial primes increase mimicry only when participants took a third-person point of view, which replicated the findings in experiment 2. We suggest that these three studies can be best explained by the active-self theory, which claims that the direction of prime-to-behavior effects depends on how primes are processed in relation to the ‘self’. Citation: Wang Y, Hamilton AFd C (2013) Understanding the Role of the ‘Self’ in the Social Priming of Mimicry. PLoS ONE 8(4): e60249. doi:10.1371/ journal.pone. 0060249 Editor: Manos Tsakiris, Royal Holloway, University of London, United Kingdom Received December 20, 2012; Accepted February 24, 2013; Published April 2, 2013 Copyright: 2013 Wang, Hamilton. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was supported by Economic and Social Research Council (ESRC: http://www.esrc.ac.uk/) Small Research Grant ES/J006793/1 (to AH). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: mirrorneuronwang@gmail.com
Life Skills Training On Couples’ Stress and Anxiety About To Marriage

The purpose of this study is to investigate the effect of life skills training on couples’ stress and anxiety about to marriage. The statistical population of the study is all couples about to marriage, who consult pre-marriage counseling centers. After initial examination, 40 girls about to marriage were selected (20 girls in the experimental group and 20 girls in the control group) and randomly divided into two groups. The research instruments were anxiety questionnaire and perceived stress questionnaire. (Cohen et al, 1988). Data were analyzed into descriptive and inferential statistics. At the descriptive level the mean and standard deviation and at the inferential level covariance analysis were used. The results showed that life skills training can reduce the anxiety and stress of couples about to marriage.
Dynamics of bubble clusters

A mathematical model which describes the behavior of a gas bubble cluster in an external acoustic field is presented. According to this model the bubbles of different ambient radii are assumed to be submerged into a spherical liquid volume. The boundary of this volume is considered as a cluster’s boundary. This model includes a set of coupled Rayleigh-type equations for bubble radii and cluster radius. The dynamics of a single bubble cluster excited by external periodic pressure is considered. The problem has been solved numerically under the assumption of spherically-symmetric oscillations of bubbles and the cluster’s boundary. A synchronization phenomenon has been found; namely, the numerical results have shown that bubbles of different initial radii in a cluster collapse in phase. Moreover, it has been noted that at some parameter values such a synchronization may lead to the intensification of bubble collapse.
Gradient-based methods for quantitative photoacoustic tomography

Photoacoustic tomography (PAT) is showing its potential as a non-invasive biomedical imaging modality, and interest in the field is growing rapidly. The images possess excellent contrast, high spatial resolution and good specificity, however, they are largely qualitative and not directly representative of the optically absorbing structures of interest. Quantitative PAT (QPAT) aims to determine quantitatively accurate spatial maps of the underlying tissue chromophores, in order to obtain highly-resolved images of functional information such as blood oxygen saturation and haemoglobin concentration. PAT images are inherently three-dimensional (3D), and their high resolution means that the data sets are of an extremely large scale; a typical problem can easily possess 10⁷ unknowns. Existing methods for QPAT have failed to address their applicability to real, 3D PAT images, either by making restrictive approximations to the light model or by using computational intensive techniques which are impractical for large-scale data sets. This thesis develops a practical inversion method for the full and general QPAT problem, in which the tissue geometry is arbitrary, the optical coefficients are unknown and the data is large-scale. The accuracy of the inversion method is ensured by use of the radiative transfer equation (RTE), which provides a highly accurate description of the propagation of light within biological tissue. Using the RTE, a thorough investigation into the effects of errors in the scattering coefficient on the reconstructed absorption coefficient is performed. Computational efficiency in the inversion is provided through an adjoint-assisted, gradient-based minimisation scheme, which iteratively adjusts the parameters of interest until the model prediction matches the measured data. Since the RTE proves too computationally intensive for large data sets, an extension to 3D simulated data is facilitated by the incorporation of the δ-Eddington approximation, thereby providing an accurate, efficient inversion method for QPAT that may be readily applied to experimental data.
Enhanced gradient-based MCMC in discrete spaces

The recent introduction of gradient-based MCMC for discrete spaces holds great promise, and comes with the tantalising possibility of new discrete counterparts to celebrated continuous methods such as MALA and HMC. Towards this goal, we introduce several discrete Metropolis-Hastings samplers that are conceptually-inspired by MALA, and demonstrate their strong empirical performance across a range of challenging sampling problems in Bayesian inference and energy-based modelling. Methodologically, we identify why discrete analogues to preconditioned MALA are generally intractable, motivating us to introduce a new kind of preconditioning based on auxiliary variables and the `Gaussian integral trick'.
Cluster Statistics in Expansive Combinatorial Structures

We develop a simple and unified approach to investigate several aspects of the cluster statistics of random expansive (multi-)sets. In particular, we determine the limiting distribution of the size of the smallest and largest clusters, we establish all moments of the distribution of the number of clusters, and we prove a local limit theorem for that distribution. Our proofs combine effectively two simple ingredients: an application of the saddle-point method through the well-known framework of $H$-admissibility, and an ingenious idea by Erd\H{o}s and Lehner that utilizes the elementary inclusion/exclusion principle.
Learning while Acquisition: Towards Active Learning Framework for Beamforming in Ultrasound Imaging

In the recent past, there have been many efforts to accelerate adaptive beamforming for ultrasound (US) imaging using neural networks (NNs). However, most of these efforts are based on static models, i.e., they are trained to learn a single adaptive beamforming approach (e.g., minimum variance distortionless response (MVDR)) assuming that they result in the best image quality. Moreover, the training of such NNs is initiated only after acquiring a large set of data that consumes several gigabytes (GBs) of storage space. In this study, an active learning framework for beamforming is described for the first time in the context of NNs. The best quality image chosen by the user serves as the ground truth for the proposed technique, which trains the NN concurrently with data acqusition. On average, the active learning approach takes 0.5 seconds to complete a single iteration of training.
RASIPAM: Interactive Pattern Mining of Multivariate Event Sequences in Racket Sports

Experts in racket sports like tennis and badminton use tactical analysis to gain insight into competitors' playing styles. Many data-driven methods apply pattern mining to racket sports data — which is often recorded as multivariate event sequences — to uncover sports tactics. However, tactics obtained in this way are often inconsistent with those deduced by experts through their domain knowledge, which can be confusing to those experts. This work introduces RASIPAM, a RAcket-Sports Interactive PAttern Mining system, which allows experts to incorporate their knowledge into data mining algorithms to discover meaningful tactics interactively. RASIPAM consists of a constraint-based pattern mining algorithm that responds to the analysis demands of experts: Experts provide suggestions for finding tactics in intuitive written language, and these suggestions are translated into constraints to run the algorithm. RASIPAM further introduces a tailored visual interface that allows experts to compare the new tactics with the original ones and decide whether to apply a given adjustment. This interactive workflow iteratively progresses until experts are satisfied with all tactics. We conduct a quantitative experiment to show that our algorithm supports real-time interaction. Two case studies in tennis and in badminton respectively, each involving two domain experts, are conducted to show the effectiveness and usefulness of the system.
IMUNet: Efficient Regression Architecture for IMU Navigation and Positioning

Data-driven based method for navigation and positioning has absorbed attention in recent years and it outperforms all its competitor methods in terms of accuracy and efficiency. This paper introduces a new architecture called IMUNet which is accurate and efficient for position estimation on edge device implementation receiving a sequence of raw IMU measurements. The architecture has been compared with one dimension version of the state-of-the-art CNN networks that have been introduced recently for edge device implementation in terms of accuracy and efficiency. Moreover, a new method for collecting a dataset using IMU sensors on cell phones and Google ARCore API has been proposed and a publicly available dataset has been recorded. A comprehensive evaluation using four different datasets as well as the proposed dataset and real device implementation has been done to prove the performance of the architecture. All the code in both Pytorch and Tensorflow framework as well as the Android application code have been shared to improve further research.
The Unnecessity of Assuming Statistically Independent Tests in Bayesian Software Reliability Assessments

When assessing a software-based system, the results of Bayesian statistical inference on operational testing data can provide strong support for software reliability claims. For inference, this data (i.e., software successes and failures) is often assumed to arise in an independent, identically distributed (i.i.d.) manner. In this paper we show how conservative Bayesian approaches make this assumption unnecessary, by incorporating one's doubts about the assumption into the assessment. We derive conservative confidence bounds on a system's probability of failure on demand (pfd), when operational testing reveals no failures. The generality and utility of the confidence bounds are illustrated in the assessment of a nuclear power-plant safety-protection system, under varying levels of skepticism about the i.i. d. assumption. The analysis suggests that the i.i. d. assumption can make Bayesian reliability assessments extremely optimistic – such assessments do not explicitly account for how software can be very likely to exhibit no failures during extensive operational testing despite the software's pfd being undesirably large.
Analysing Parallel Complexity of Term Rewriting

We revisit parallel-innermost term rewriting as a model of parallel computation on inductive data structures and provide a corresponding notion of runtime complexity parametric in the size of the start term. We propose automatic techniques to derive both upper and lower bounds on parallel complexity of rewriting that enable a direct reuse of existing techniques for sequential complexity. The applicability and the precision of the method are demonstrated by the relatively light effort in extending the program analysis tool AProVE and by experiments on numerous benchmarks from the literature.