Real-world Interactions Research Articles

Exploring Apologizing Strategies in the Movie “Captain Marvel”

The study explored apologizing strategies within the movie "Captain Marvel" through the analysis of illocutionary speech acts. The research adopted a qualitative approach and utilized the framework of apologizing strategies developed by Kramer-Moore and Moore. The primary data sources were the movie and its script, with instances of apologizing transcribed verbatim, along with nonverbal cues. The analysis revealed two main types of apologies: expressive and directive. Expressive apologies, demonstrated by characters like Maria, Carol, and Coulson, conveyed genuine remorse and empathy to maintain harmonious interactions. On the other hand, Talos utilized directive apologies, combining sincerity with a plea for understanding and forgiveness. These findings contribute to a deeper understanding of communication dynamics within cinematic narratives and real-world interactions. Future research could explore cultural variations in apology strategies within different genres and the impact of cultural nuances on apology portrayal in films. Overall, this study provides valuable insights into the portrayal of apologizing strategies in the movie "Captain Marvel" and how they contribute to the dynamics of communication and character development. The identification of expressive and directive apology types showcases the complexity of human interactions and emotions within the context of a popular cinematic narrative.

Real-time monitoring of infant theta power during naturalistic social experiences

Infant-directed speech and direct gaze are important social cues that shape infant’s attention to their parents. Traditional methods for probing their effect on infant attention involve a small number of pre-selected screen-based stimuli, which do not capture the complexity of real-world interactions. Here, we used neuroadaptive Bayesian Optimization (NBO) to search a large ‘space’ of different naturalistic social experiences that systematically varied in their visual (gaze direct to averted) and auditory properties (infant directed speech to nonvocal sounds). We measured oscillatory brain responses (relative theta power) during episodes of naturalistic social experiences in 57 typically developing 6- to 12-month-old infants. Relative theta power was used as input to the NBO algorithm to identify the naturalistic social context that maximally elicited attention in each individual infant. Results showed that individual infants were heterogeneous in the stimulus that elicited maximal theta with no overall stronger attention for direct gaze or infant-directed speech; however, individual differences in attention towards averted gaze were related to interpersonal skills and greater likelihood of preferring speech and direct gaze was observed in infants whose parents showed more positive affect. Our work indicates NBO may be a fruitful method for probing the role of distinct social cues in eliciting attention in naturalistic social contexts at the individual level.

Using Augmented Reality Toward Improving Social Skills: Scoping Review.

Augmented reality (AR) has emerged as a promising technology in educational settings owing to its engaging nature. However, apart from applications aimed at the autism spectrum disorder population, the potential of AR in social-emotional learning has received less attention. This scoping review aims to map the range of AR applications that improve social skills and map the characteristics of such applications. In total, 2 independent researchers screened 2748 records derived from 3 databases in December 2021-PubMed, IEEE Xplore, and ACM Guide to Computing Literature. In addition, the reference lists of all the included records and existing reviews were screened. Records that had developed a prototype with the main outcome of improving social skills were included in the scoping review. Included records were narratively described for their content regarding AR and social skills, their target populations, and their outcomes. Evaluation studies were assessed for methodological quality. A total of 17 records met the inclusion criteria for this study. Overall, 10 records describe applications for children with autism, primarily teaching about reading emotions in facial expressions; 7 records describe applications for a general population, targeting both children and adults, with a diverse range of outcome goals. The methodological quality of evaluation studies was found to be weak. Most applications are designed to be used alone, although AR is well suited to facilitating real-world interactions during a digital experience, including interactions with other people. Therefore, future AR applications could endorse social skills in a general population in more complex group settings.

Strategy evolution on dynamic networks.

Models of strategy evolution on static networks help us understand how population structure can promote the spread of traits like cooperation. One key mechanism is the formation of altruistic spatial clusters, where neighbors of a cooperative individual are likely to reciprocate, which protects prosocial traits from exploitation. However, most real-world interactions are ephemeral and subject to exogenous restructuring, so that social networks change over time. Strategic behavior on dynamic networks is difficult to study, and much less is known about the resulting evolutionary dynamics. Here we provide an analytical treatment of cooperation on dynamic networks, allowing for arbitrary spatial and temporal heterogeneity. We show that transitions among a large class of network structures can favor the spread of cooperation, even if each individual social network would inhibit cooperation when static. Furthermore, we show that spatial heterogeneity tends to inhibit cooperation, whereas temporal heterogeneity tends to promote it. Dynamic networks can have profound effects on the evolution of prosocial traits, even when individuals have no agency over network structures.

A Game-Theoretical Approach to Clinical Decision Making with Immersive Visualisation

Cancer is a disease characterised by changes in combinations of genes within affected tumour cells. The deep understanding of genetic activity afforded to cancer specialists through complex genomics data analytics has advanced the clinical management of cancer by using deep machine learning algorithms and visualisation. However, most of the existing works do not integrate intelligent decision-making aids that can guide users in the analysis and exploration processes. This paper contributes a novel strategy that applies game theory within a VR-enabled immersive visualisation system designed as the decision support engine to mimic real-world interactions between stakeholders within complex relationships, in this case cancer clinicians. Our focus is to apply game theory to assist doctors in the decision-making process regarding the treatment options for rare-cancer patients. Nash Equilibrium and Social Optimality strategy profiles were used to facilitate complex analysis within the visualisation by inspecting which combination of genes and dimensionality reduction methods yields the best survival rate and by investigating the treatment protocol to form new hypotheses. Using a case simulation, we demonstrate the effectiveness of game theory in guiding the analyst with a patient cohort data interrogation system as compared to an analyst without a decision support system. Particularly, the strategy profile (t-SNE method and DNMT3B_ZBTB46_LAPTM4B gene) gains the highest payoff for the two doctors.

Effects of emotional content on social inhibition of gaze in live social and non-social situations

In real-life interactions, it is crucial that humans adequately respond to others’ emotional expressions. Emotion perception so far has mainly been studied in highly controlled laboratory tasks. However, recent research suggests that attention and gaze behaviour significantly differ between watching a person on a controlled laboratory screen compared to in real world interactions. Therefore, the current study aimed to investigate effects of emotional expression on participants’ gaze in social and non-social situations. We compared looking behaviour towards a confederate showing positive, neutral or negative facial expressions between live social and non-social waiting room situations. Participants looked more often and longer to the confederate on the screen, than when physically present in the room. Expressions displayed by the confederate and individual traits (social anxiety and autistic traits) of participants did not reliably relate to gaze behaviour. Indications of covert attention also occurred more often and longer during the non-social, than during the social condition. Findings indicate that social norm is a strong factor modulating gaze behaviour in social contexts.Protocol registrationThe stage 1 protocol for this Registered Report was accepted in principle on September 13, 2021. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.16628290.

Sosialisasi Upaya Menagani Penyalahgunaan Media Sosial di Kalangan Masyarakat Di Desa Sidorejo Kecamatan Pondok Kelapa Kabupaten Bengkulu Tengah

Social media has an influence on the larger community that is both beneficial and harmful. They help the process in real life by providing quick and comprehensive information. Additionally, owing to technical advancements that affect how simple it is to utilize social media as a communication tool, their negative consequence will be to abuse social media through crimes, fraud, and defamation. In order to help the community utilize social media responsibly, this community service aims to contribute perspective, knowledge, and understanding. This community service project is conducted in the form of socialization utilizing the lecture-based approach of information exchange, which is followed by a Q&A session or conversation between presenters and participants.The outcomes of this community service demonstrate that the community's intense use of social media must be consistent with knowledge of safe and responsible use. Through this community service project, it is intended that more individuals will learn how to use social media responsibly, enabling them to make the most of it while minimizing its negative consequences on real-world interactions.

Brain Computer Interface (BCI) Machine Learning Process: A Review

The abstraction of Brain Computer Interface (BCI) is a communication and control system that translated human mind thoughts into real-world interaction without any use of neural pathways and muscles. BCI is used as a tool to help person that suffered from impairment to be able do their daily activities independently. In general, BCI process its signal through several process such as pre-processing, and classification. However, providing information of pre-processing and classification process is barely found. Therefore, in this review paper we present the various pre-processing and classification methods that used in the BCI system application.

Stabilizing deep Q-learning with Q-graph-based bounds

State-of-the art deep reinforcement learning has enabled autonomous agents to learn complex strategies from scratch on many problems including continuous control tasks. Deep Q-networks (DQN) and deep deterministic policy gradients (DDPGs) are two such algorithms which are both based on Q-learning. They therefore all share function approximation, off-policy behavior, and bootstrapping—the constituents of the so-called deadly triad that is known for its convergence issues. We suggest to take a graph perspective on the data an agent has collected and show that the structure of this data graph is linked to the degree of divergence that can be expected. We further demonstrate that a subset of states and actions from the data graph can be selected such that the resulting finite graph can be interpreted as a simplified Markov decision process (MDP) for which the Q-values can be computed analytically. These Q-values are lower bounds for the Q-values in the original problem, and enforcing these bounds in temporal difference learning can help to prevent soft divergence. We show further effects on a simulated continuous control task, including improved sample efficiency, increased robustness toward hyperparameters as well as a better ability to cope with limited replay memory. Finally, we demonstrate the benefits of our method on a large robotic benchmark with an industrial assembly task and approximately 60 h of real-world interaction.

“I’m not a feminist, but … ”: Hegemonic femininities and women’s autonomy revisited in a Chinese university

ABSTRACT In recent years, much academic and public attention has been drawn to a “feminist awakening” in China and its domestic backlashes, especially in popular media and internet forums. Moving from the online waves of women’s agitation to real-world interactions, how do young women in urban China today understand feminism in their everyday lives? To what extent are they scrutinizing their personal experiences with what they understand as “feminist principles,” and how do they reconcile expectations and challenges from the family, school, and workplace? As my interlocutors’ experiences and narratives indicate, urban Chinese women with high educational attainments are less likely to identify with submissive female roles as daughters, wives, and mothers. However, their attitudes toward the new motto of women’s autonomy are at least equally ambivalent. Situating individual life experiences within a broader theoretical discussion on hegemonic femininities, I seek to provide a nuanced look into such ambivalence by illustrating how my interlocutors approximate multiple, sometimes contradicting, frameworks of “ideal womanhood” in narrating their hopes and dilemmas. Moreover, I suggest the “sidestepping feminism” narrative deserves more serious scholarly attention as it may open up new possibilities for enriching and theorizing women’s studies in the Chinese context.

Enhancing IT professionals' communication skills through interactive training methods

The paper deals with the issue of enhancing communication skills among IT professionals through interactive training methods. The rapid evolution of IT education, with its constantly changing content, emerging knowledge sectors, and evolving patterns of communication and interaction, necessitates urgent attention to this matter. To identify the specific communication needs across various domains, the researchers have analyzed regulations, guidelines, and certification frameworks from European nations and Ukraine. Extensive research has been conducted on interactive teaching concepts, activities, and their advantages. The study emphasizes that interactive teaching techniques can effectively facilitate the instruction of future IT workers in both general and specialized areas. The main characteristics of several interactive teaching techniques are described. To enhance the communication abilities of IT professionals, the study suggests incorporating project-based learning, brainstorming, gamification, and discussion, with a particular emphasis on English language instruction in higher education institutions. It is crucial to keep a careful balance between interactive techniques and strategic planning to foster a suitable level of comprehension in both language use and real-world interactions.

The Intelligibility of Korean-Accented English in the Lingua Franca Context

This study aimed to establish an empirical basis for prioritizing English as a Lingua Franca (ELF) instruction by evaluating the importance of “intelligibility” in communication with accented English speakers. It specifically examined the claims surrounding the Lingua Franca Core (LFC) features as the minimum requirements for intelligibility in ELF contexts. The experiment focused on the intelligibility of Korean-accented English (KoE) and general American English (AmE) to Korean-Speaking Learners (KSLs) and Japanese- Speaking Learners (JSLs). The findings indicated that AmE was more intelligible to both non-native English speaker groups. In contrast, KoE’s intelligibility was hindered by non- LFC features such as the pronunciation of the dark /l/ sound and specific vowel qualities. These results challenge the LFC proposal and suggest the need for a modified set of LFC features in ELF teaching and learning. The implications of this study are significant for English language education, highlighting the necessity of considering different accents and non-LFC features in ELF communication. By incorporating these aspects into instruction, teachers can better prepare learners for real-world interactions in diverse linguistic contexts. This approach enhances learners’ confidence and proficiency in understanding and being understood by individuals from various linguistic backgrounds, fostering successful intercultural exchanges.

Understanding non-motorists' views on automated vehicle safety through Bayesian network analysis and latent dirichlet allocation

Automated vehicles (AVs) hold great promise for creating a safer, more efficient, more equitable, and more sustainable transportation system. However, the rapid adoption of AVs requires a thorough understanding in their coexistence with the human environment in the current roadway network, particularly with respect to interactions between AVs and non-motorists. Bike Pittsburgh (BikePGH) conducted a 2019 survey to examine non-motorists' perceptions of AV safety. Using Bayesian network (BN) analysis, the study identified key factors such as safety perception, AV technology knowledge, and real-world interaction experiences that influence non-motorists' overall perception of AV safety using BikePGH survey data. The study also explored several counterfactual scenarios to gain insights into non-motorists' viewpoints on AV safety. Notably, the study found that the differences in the ways of AVs and human-driven vehicles interacted with non-motorists at intersections played a crucial role in shaping survey participants' opinions. By taking into account the key insights identified in this study, policymakers can develop evidence-based strategies to achieve sustainable urban mobility goals while ensuring the safety and well-being of all road users, particularly non-motorists.

Dynamic Representation Learning with Temporal Point Processes for Higher-Order Interaction Forecasting

The explosion of digital information and the growing involvement of people in social networks led to enormous research activity to develop methods that can extract meaningful information from interaction data. Commonly, interactions are represented by edges in a network or a graph, which implicitly assumes that the interactions are pairwise and static. However, real-world interactions deviate from these assumptions: (i) interactions can be multi-way, involving more than two nodes or individuals (e.g., family relationships, protein interactions), and (ii) interactions can change over a period of time (e.g., change of opinions and friendship status). While pairwise interactions have been studied in a dynamic network setting and multi-way interactions have been studied using hypergraphs in static networks, there exists no method, at present, that can predict multi-way interactions or hyperedges in dynamic settings. Existing related methods cannot answer temporal queries like what type of interaction will occur next and when it will occur. This paper proposes a temporal point process model for hyperedge prediction to address these problems. Our proposed model uses dynamic representation learning techniques for nodes in a neural point process framework to forecast hyperedges. We present several experimental results and set benchmark results. As far as our knowledge, this is the first work that uses the temporal point process to forecast hyperedges in dynamic networks.

Treatment Fidelity of the Family-Centered Function-Focused Care Intervention.

The purpose of the current study was to evaluate treatment fidelity (i.e., the extent to which an intervention is provided as intended) in the Family-Centered Function-Focused Care (Fam-FFC) intervention. This was a descriptive study using data collected during intervention activities throughout the course of the Fam-FFC study. Specific measures included Environment and Policy Assessments, Fam-FFC Knowledge Test, Goal Attainment Scale, Function-Focused Care Behavior Checklist, and completion of the FamPath Audit. Delivery was provided as intended. Staff demonstrated intervention skills with only one Fam-FFC research nurse needing retraining. Receipt was based on Fam-FFC Knowledge Test scores >80%, with the majority of participants reporting goal achievement as expected or higher than expected and slight improvement in environments and policies to better support Fam-FFC. Lastly, enactment was based on evidence that in 67% of observations staff provided at least one function-focused care intervention. Findings from this study will be used to adapt the intervention to reach all staff, increase ways to change environments and policies, consider ways to more comprehensively evaluate enactment of function-focused care during real-world interactions, and consider the characteristics of nursing staff and whether a relationship exists between staff characteristics and providing function-focused care. [Research in Gerontological Nursing, 16(4), 165-171.].

Convection Initiation Associated with a Boundary Layer Convergence Line over a Real-World Sharp Vegetation-Contrast Area

Abstract Convection initiation (CI) has remained a major challenge in weather forecasting worldwide. The Hetao area in North China, the location of Asia’s largest irrigation area, contains highly heterogeneous vegetation where near-surface convergence lines (boundaries) parallel to the oasis–desert border often emerge over the desert and initiate convection. This study investigated the evolution of such a boundary and its influence on the CI process where a series of cells were successively initiated along the boundary on 4 June 2013. Our results indicated that uneven surface heating across the oasis–desert border produced mesoscale thermal circulation. The westerly oasis breeze in the thermal circulation converged with the southerly background wind and formed a boundary over the desert along the high-temperature contrast line. A middle-hemisphere westerly trough further enhanced uplift and facilitated CI. Our simulation revealed that the first 30-dBZ parcels in each cell originated from either the desert side at a low level or the oasis side at a middle level, rather than from the oasis at a low level, as indicated by previous idealized studies. Southerly low-level parcels veered above the boundary and experienced a longer lifting time over the desert, while western parcels originating from the oasis experienced a shorter lifting time and smaller vertical displacement, resulting in middle-level parcels instead of low-level parcels that reached their level of free convection. Even though CI occurred over a surface boundary without a near-surface stable layer, the inflow may have originated from middle levels rather than in contact with the surface. Significance Statement The purpose of this study is to understand the evolution of a real-world near-surface convergence line and the associated deep convection initiation (CI) along the border of Asia’s largest irrigation area and the desert in northern China. Notably, previous works have mainly focused on shallow convection over uneven vegetation distributions based on idealized simulations, which may be quite different from real-world interactions between thermal circulation and background flow. Our results highlight different parcel sources in different convections initiated by the same convergence line, which is different from the idealized situation where parcels mainly originate from the low-level oasis side.

Can I Squeeze Through? Effects of Self-Avatars and Calibration in a Person-Plus-Virtual-Object System on Perceived Lateral Passability in VR.

With the popularity of Virtual Reality (VR) on the rise, creators from a variety of fields are building increasingly complex experiences that allow users to express themselves more naturally. Self-avatars and object interaction in virtual worlds are at the heart of these experiences. However, these give rise to several perception based challenges that have been the focus of research in recent years. One area that garners most interest is understanding the effects of self-avatars and object interaction on action capabilities or affordances in VR. Affordances have been shown to be influenced by the anthropometric and anthropomorphic properties of the self-avatar embodied. However, self-avatars cannot fully represent real world interaction and fail to provide information about the dynamic properties of surfaces in the environment. For example, pressing against a board to feel its rigidity. This lack of accurate dynamic information can be further amplified when interacting with virtual handheld objects as the weight and inertial feedback associated with them is often mismatched. To investigate this phenomenon, we looked at how the absence of dynamic surface properties affect lateral passability judgments when carrying virtual handheld objects in the presence or absence of gender matched body-scaled self-avatars. Results suggest that participants can calibrate to the missing dynamic information in the presence of self-avatars to make lateral passability judgments, but rely on their internal body schema of a compressed physical body depth in the absence of self-avatars.

The politics of multi-level migration policymaking: a network-centred perspective

ABSTRACT This article develops and applies an innovative methodology based on social network analysis and cluster analysis to analyze the organization of policymaking relations in multi-level political systems, focusing on the migration policy field. In doing so, it addresses four limitations of existing research on multi-layered migration policymaking, which tends to focus on policy and legal documents rather than real-world interactions, conceptualize governmental levels in morphological terms, neglect conflictual interactions, and narrowly focus on big cities. This innovative approach is applied to the heuristic case of Italian asylum policy after the 2015 “refugee crisis”, which allows to derive three conceptual claims about the organizations of multi-level migration-related policymaking interactions. First, these interactions can be highly conflictual and multi-level migration policymaking should not necessarily be seen as a negotiated order among public and non-public actors. Second, existing typologies need to be complexified, accounting for the significance of intricately nested and overlapping “multi-level networks” emerging over and above multi-layered institutional structures. Third, showing that Italian asylum policy actors interact more frequently and collaboratively with “like-minded” actors regardless of official roles and governmental levels, the article identifies a new “political” or “ideological” axis along which collaborative and conflictual relations can be organized.

What do second language speakers really need for real-world interaction? A needs analysis of L2 Chinese interactional competence

A primary undertaking in communicative language teaching is to ensure second language (L2) speakers develop the ability to interact in real-world communicative events, a skill known as interactional competence (IC). Thus far, there have been few needs analysis studies conducted on L2 IC, posing challenges when ascertaining whether the teaching and testing of L2 IC are empirically grounded. Henceforth, the researcher carried out a needs analysis to systematically investigate the IC learning needs of speakers of L2 Chinese, which in itself represents an under-investigated target language in present-day needs analysis literature. A considered methodology was utilized to elicit triangulated information from 18 participants. Content analysis of the elicited data identified seven IC learning categories: (1) social actions, (2) sociopragmatic knowledge, (3) pragmalinguistic knowledge, (4) interactional structure, (5) content knowledge, (6) linguistic resources, and (7) nonverbal resources. Results revealed disaffiliative social actions (e.g. complaining) to be most challenging. The management of social actions was mediated by speakers’ sociopragmatic knowledge (e.g. social distance) and pragmalinguistic knowledge (e.g. formality devices). Other learning categories such as interactional structure (e.g. topic development) and nonverbal resources (e.g. gaze) contributed to successful interaction at a more foundational level. Based on these findings, this article proposes a three-tier IC needs model to conceptualize the hierarchical interrelationships among the seven categories. In addition, the researcher generated lists of IC learning needs for each category and subcategory to assist language educators with developing targeted IC teaching and assessment tasks. The IC needs model and needs lists constitute a pedagogical toolkit for the systematic incorporation of IC in task-based language teaching, language curricula and language programs. This article also discusses how methodological considerations and innovations formulated in the study can contribute to needs analysis research in general.

Inter-Brain Synchrony Pattern Investigation on Triadic Board Game Play-Based Social Interaction: An fNIRS Study.

Recent advances in functional neuroimaging techniques, including methodologies such as fNIRS, have enabled the evaluation of inter-brain synchrony (IBS) induced by interpersonal interactions. However, the social interactions assumed in existing dyadic hyperscanning studies do not sufficiently emulate polyadic social interactions in the real world. Therefore, we devised an experimental paradigm that incorporates the Korean folk board game "Yut-nori" to reproduce social interactions that emulate social activities in the real world. We recruited 72 participants aged 25.2 ± 3.9 years (mean ± standard deviation) and divided them into 24 triads to play Yut-nori, following the standard or modified rules. The participants either competed against an opponent (standard rule) or cooperated with an opponent (modified rule) to achieve a goal efficiently. Three different fNIRS devices were employed to record cortical hemodynamic activations in the prefrontal cortex both individually and simultaneously. Wavelet transform coherence (WTC) analyses were performed to assess prefrontal IBS within a frequency range of 0.05-0.2 Hz. Consequently, we observed that cooperative interactions increased prefrontal IBS across overall frequency bands of interest. In addition, we also found that different purposes for cooperation generated different spectral characteristics of IBS depending on the frequency bands. Moreover, IBS in the frontopolar cortex (FPC) reflected the influence of verbal interactions. The findings of our study suggest that future hyperscanning studies should consider polyadic social interactions to reveal the properties of IBS in real-world interactions.