Accessing gluon polarization with high-PTP_T hadrons in SIDIS

A recent global QCD analysis of jet production and other polarized scattering data has found the presence of negative solutions for the gluon helicity distribution in the proton, $\Delta g$, along with the traditional $\Delta g > 0$ solutions. We consider polarized semi-inclusive deep-inelastic scattering for hadrons produced with large transverse momentum as a means of constraining the dependence of $\Delta g$ on the parton momentum fraction, $x$. Focusing on the double longitudinal spin asymmetry, we identify the kinematics relevant for future experiments at Jefferson Lab and the Electron-Ion Collider which are particularly sensitive to the polarized gluon channel and could discriminate between the different $\Delta g$ behaviors.Comment: 22 pages, 7 figure

Gluon helicity from global analysis of experimental data and lattice QCD Ioffe time distributions

We perform a new global analysis of spin-dependent parton distribution functions with the inclusion of Ioffe time pseudo-distributions computed in lattice QCD (LQCD), which are directly sensitive to the gluon helicity distribution, $\Delta g$. These lattice data have an analogous relationship to parton distributions as do experimental cross sections, and can be readily included in global analyses. We focus in particular on the constraining capability of current LQCD data on the sign of $\Delta g$ at intermediate parton momentum fractions $x$, which was recently brought into question by analysis of data in the absence of parton positivity constraints. We find that present LQCD data cannot discriminate between positive and negative $\Delta g$ solutions, although significant changes in the solutions for both the gluon and quark sectors are observed.Comment: 24 pages, 7 figure

Effect of intonation on Cantonese lexical tones

In tonal languages, there are potential conflicts between the F0-based changes due to the coexistence of intonation and lexical tones. In the present study, the interaction of tone and intonation in Cantonese was examined using acoustic and perceptual analyses. The acoustic patterns of tones at the initial, medial, and final positions of questions and statements were measured. Results showed that intonation affects both the F0 level and contour, while the duration of the six tones varied as a function of positions within intonation contexts. All six tones at the final position of questions showed rising F0 contour, regardless of their canonical form. Listeners were overall more accurate in the identification of tones presented within the original carrier than of the same tones in isolation. However, a large proportion of tones 33, 21, 23, and 22 at the final position of questions were misperceived as tone 25 both within the original carrier and as isolated words. These results suggest that although the intonation context provided cues for correct tone identification, the intonation-induced changes in F0 contour cannot always be perceptually compensated for, resulting in some erroneous perception of the identity of Cantonese tone. © 2006 Acoustical Society of America.published_or_final_versio

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Associating Facial Expressions and Upper-Body Gestures with Learning Tasks for Enhancing Intelligent Tutoring Systems

Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of learner’s nonverbal behaviors involving hand-over-face gestures, head and eye movements and emotions via facial expressions during learning. The proposed computer vision-based behavior monitoring method uses a low-cost webcam and can easily be integrated with modern tutoring technologies. We investigate these behaviors in-depth over time in a classroom session of 40 minutes involving reading and problem-solving exercises. The exercises in the sessions are divided into three categories: an easy, medium and difficult topic within the context of undergraduate computer science. We found that there is a significant increase in head and eye movements as time progresses, as well as with the increase of difficulty level. We demonstrated that there is a considerable occurrence of hand-over-face gestures (on average 21.35%) during the 40 minutes session and is unexplored in the education domain. We propose a novel deep learning approach for automatic detection of hand-over-face gestures in images with a classification accuracy of 86.87%. There is a prominent increase in hand-over-face gestures when the difficulty level of the given exercise increases. The hand-over-face gestures occur more frequently during problem-solving (easy 23.79%, medium 19.84% and difficult 30.46%) exercises in comparison to reading (easy 16.20%, medium 20.06% and difficult 20.18%)

An odd oxygen framework for wintertime ammonium nitrate aerosol pollution in urban areas: NOx and VOC control as mitigation strategies

Wintertime ammonium nitrate aerosol pollution is a severe air quality issue affecting both developed and rapidly urbanizing regions from Europe to East Asia. In the US, it is acute in western basins subject to inversions that confine pollutants near the surface. Measurements and modeling of a wintertime pollution episode in Salt Lake City, Utah demonstrates that ammonium nitrate is closely related to photochemical ozone through a common parameter, total odd oxygen, Ox,total. We show that the traditional NOx‐VOC framework for evaluating ozone mitigation strategies also applies to ammonium nitrate. Despite being nitrate‐limited, ammonium nitrate aerosol pollution in Salt Lake City is responsive to VOC control and, counterintuitively, not initially responsive to NOx control. We demonstrate simultaneous nitrate limitation and NOx saturation and suggest this phenomenon may be general. This finding may identify an unrecognized control strategy to address a global public health issue in regions with severe winter aerosol pollution