Multidifferential study of identified charged hadron distributions in ZZ-tagged jets in proton-proton collisions at s=\sqrt{s}=13 TeV

Jet fragmentation functions are measured for the first time in proton-proton collisions for charged pions, kaons, and protons within jets recoiling against a $Z$ boson. The charged-hadron distributions are studied longitudinally and transversely to the jet direction for jets with transverse momentum 20 $< p_{\textrm{T}} < 100$ GeV and in the pseudorapidity range $2.5 < \eta < 4$. The data sample was collected with the LHCb experiment at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 1.64 fb$^{-1}$. Triple differential distributions as a function of the hadron longitudinal momentum fraction, hadron transverse momentum, and jet transverse momentum are also measured for the first time. This helps constrain transverse-momentum-dependent fragmentation functions. Differences in the shapes and magnitudes of the measured distributions for the different hadron species provide insights into the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb public pages

Study of the B−→Λc+Λˉc−K−B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

The decay $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ is studied in proton-proton collisions at a center-of-mass energy of $\sqrt{s}=13$ TeV using data corresponding to an integrated luminosity of 5 $\mathrm{fb}^{-1}$ collected by the LHCb experiment. In the $\Lambda_{c}^+ K^{-}$ system, the $\Xi_{c}(2930)^{0}$ state observed at the BaBar and Belle experiments is resolved into two narrower states, $\Xi_{c}(2923)^{0}$ and $\Xi_{c}(2939)^{0}$, whose masses and widths are measured to be $$m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV},$$ where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt $\Lambda_{c}^{+} K^{-}$ sample. Evidence of a new $\Xi_{c}(2880)^{0}$ state is found with a local significance of $3.8\,\sigma$, whose mass and width are measured to be $2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV}$ and $12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}$, respectively. In addition, evidence of a new decay mode $\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-}$ is found with a significance of $3.7\,\sigma$. The relative branching fraction of $B^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-}$ with respect to the $B^{-} \to D^{+} D^{-} K^{-}$ decay is measured to be $2.36 \pm 0.11 \pm 0.22 \pm 0.25$, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

Measurement of the ratios of branching fractions R(D∗)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

The ratios of branching fractions $\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu})$ and $\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu})$ are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb${ }^{-1}$ of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode $\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}$. The measured values are $\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024$ and $\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066$, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is $\rho=-0.43$. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

Exploring Multidimensional Trust : Shaping Child-Robot Creative Collaborations in Education

As trust plays a pivotal role in maintaining long-term interactions between children and robots, it is vital to comprehend how children conceptualise trust and the factors influencing their trust in robots. This thesis examines the impact of social robots' behaviours and attributes on children's trust, relationship formation, and task performance in collaborative educational scenarios. A systematic review of child-robot interaction (cHRI) literature identified two primary dimensions of trust: social trust and competency trust. The literature suggests a lack of consensus about how different robot behaviours and attributes affect these two dimensions of trust, as evidence points to different directions. To address these gaps, a collaborative storytelling game was developed to facilitate interactions between children and social robots, aiming to study trust dynamics and enhance learning by fostering children's creativity. The research also examined the impact of robot-related factors, such as behaviour and appearance, on children's interactions with robots. Empirical evidence suggests that while making robots look and behave more like humans is critical for competency trust and task performance, lower human-like attributes are more crucial for developing social trust and relationship formation with robots. Other factors, like time, provide insights into children's trust dynamics. Thus, this thesis explores the role of repeated interactions with artificial agents, indicating that children's competency trust in robots changes over time. This thesis offers significant contributions to the cHRI community. Firstly, it demonstrates that trust is a multidimensional construct that is complex to capture, highlighting the need for reliable, objective measures tailored to the task and intended trust dimension. Secondly, it emphasises the importance of balancing human likeness with social robots when collaborating with children in educational scenarios. Lastly, it proposes that to sustain trustworthy long-term interactions in education; social robots should adapt their behaviour to provide scaffolding, as children will be more inclined to rely on them for learning support as time progresses

Exploring Multidimensional Trust : Shaping Child-Robot Creative Collaborations in Education

As trust plays a pivotal role in maintaining long-term interactions between children and robots, it is vital to comprehend how children conceptualise trust and the factors influencing their trust in robots. This thesis examines the impact of social robots' behaviours and attributes on children's trust, relationship formation, and task performance in collaborative educational scenarios. A systematic review of child-robot interaction (cHRI) literature identified two primary dimensions of trust: social trust and competency trust. The literature suggests a lack of consensus about how different robot behaviours and attributes affect these two dimensions of trust, as evidence points to different directions. To address these gaps, a collaborative storytelling game was developed to facilitate interactions between children and social robots, aiming to study trust dynamics and enhance learning by fostering children's creativity. The research also examined the impact of robot-related factors, such as behaviour and appearance, on children's interactions with robots. Empirical evidence suggests that while making robots look and behave more like humans is critical for competency trust and task performance, lower human-like attributes are more crucial for developing social trust and relationship formation with robots. Other factors, like time, provide insights into children's trust dynamics. Thus, this thesis explores the role of repeated interactions with artificial agents, indicating that children's competency trust in robots changes over time. This thesis offers significant contributions to the cHRI community. Firstly, it demonstrates that trust is a multidimensional construct that is complex to capture, highlighting the need for reliable, objective measures tailored to the task and intended trust dimension. Secondly, it emphasises the importance of balancing human likeness with social robots when collaborating with children in educational scenarios. Lastly, it proposes that to sustain trustworthy long-term interactions in education; social robots should adapt their behaviour to provide scaffolding, as children will be more inclined to rely on them for learning support as time progresses

Understanding Children's Trust Development through Repeated Interactions with a Virtual Social Robot

Studies in Child-Robot Interaction have shown that children form first impressions of a robot's trustworthiness that might influence how they interact with social robots in long-term interactions. However, how children's trust in robots evolves and how it relates to relationship formation is not well understood. This study investigates the effects of repeated encounters with a virtual social robot on children's social and competency trust in social robots and their relationship formation. We developed an online storytelling game with the Furhat robot, where 25 children (9-12 years old) played with the robot over two sessions with seven days of zero exposure in between. Results show that children's competency trust improved with time. We also found empirical evidence that children felt closer to the robot in the second encounter. This work enriches the scientific understanding of children's trust development in social robots over extended periods of time in child-robot collaborative interactions

Reward seeking or loss aversion? : impact of regulatory focus theory on emotional induction in children and their behavior towards a

According to psychology research, emotional induction has positive implications in many domains such as therapy and education. Our aim in this paper was to manipulate the Regulatory Focus Theory to assess its impact on the induction of regulatory focus related emotions in children in a pretend play scenario with a social robot. The Regulatory Focus Theory suggests that people follow one of two paradigms while attempting to achieve a goal; by seeking gains (promotion focus - associated with feelings of happiness) or by avoiding losses (prevention focus - associated with feelings of fear).We conducted a study with 69 school children in two different conditions (promotion vs. prevention). We succeeded in inducing happiness emotions in the promotion condition and found a resulting positive effect of the induction on children's social engagement with the robot. We also discuss the important implications of these results in both educational and child robot interaction fields. Part of proceedings: ISBN 978-1-4503-8096-6QC 20220309</p

The Effects of Robot’s Facial Expressions on Children’s First Impressions of Trustworthiness

Facial expressions of emotions influence the perception of robots in first encounters. People can judge trustworthiness, likability, and aggressiveness in a few milliseconds by simply observing other individuals' faces. While first impressions have been extensively studied in adult-robot interaction, they have been addressed in child-robot interaction only rarely. This knowledge is crucial, as the first impression children build of robots might influence their willingness to interact with them over extended periods of time, for example in applications where robots play the role of companions or tutors. The present study focuses on investigating the effects of facial expressions of emotions on children's perceptions of trust towards robots during first encounters. We constructed a set of facial expressions of happiness and anger varying in terms of intensity. We implemented these facial expressions onto a Furhat robot that was either male-like or female-like. 129 children were exposed to the robot's expressions for a few seconds. We asked them to evaluate the robot in terms of trustworthiness, likability, and competence and investigated how emotion type, emotion intensity, and gender-likeness affected the perception of the robot. Results showed that a few seconds are enough for children to make a trait inference based on the robot's emotion. We observed that emotion type, emotion intensity, and gender-likeness did not directly affect trust, but the perception of likability and competence of the robot served as facilitator to judge trustworthiness

The Effects of Motivational Strategies and Goal Attainment on Children’s Trust in a Virtual Social Robot : A Pilot Study

Understanding the way different robot’s strategies affect children’s perceptions of social robots is crucial for a trustworthy child-robot relationship. This paper presents a preliminary study on whether motivational strategies based on Regulatory Focus Theory and goal attainment affect children’s perception of a virtual social robot when solving a task. The ongoing pandemic (COVID-19) is altering the way we perform research. Hence, we designed a fully autonomous game with a virtual social robot. In an online user study, 25 children (8 to 17 years old) played a regulatory focus goal-oriented game with a virtual child-like version of the Furhat robot. We evaluated children’s perceptions of the robot’s social trust, competency trust, and likability. Also, we assessed the children’s affective state (valence and arousal) before and after playing the game. Our preliminary results show that in the prevention condition, fulfilling the goal elicited less happiness in children. Surprisingly, we observed a trend increase in the social and competency trust elicited by the virtual robot when children were prevented from fulfilling the goal of the task. We discuss the results and the effects of online setups on conducting user studies with children

A Meta-analysis on Children’s Trust in Social Robots

Although research on children’s trust in social robots is increasingly growing in popularity, a systematic understanding of the factors which influence children’s trust in robots is lacking. In addition, meta-analyses in child–robot-interaction (cHRI) have yet to be popularly adopted as a method for synthesising results. We therefore conducted a meta-analysis aimed at identifying factors influencing children’s trust in robots. We constructed four meta-analytic models based on 20 identified studies, drawn from an initial pool of 414 papers, as a means of investigating the effect of robot embodiment and behaviour on both social and competency trust. Children’s pro-social attitudes towards social robots were also explored. There was tentative evidence to suggest that more human-like attributes lead to less competency trust in robots. In addition, we found a trend towards the type of measure that was used (subjective or objective) influencing the direction of effects for social trust. The meta-analysis also revealed a tendency towards under-powered designs, as well as variation in the methods and measures used to define trust. Nonetheless, we demonstrate that it is still possible to perform rigorous analyses despite these challenges. We also provide concrete methodological recommendations for future research, such as simplifying experimental designs, conducting a priori power analyses and clearer statistical reporting