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We know little about the mechanisms through which leader-follower dynamics during dyadic play shape infants' language acquisition. We hypothesized that infants' decisions to visually explore a specific object signal focal increases in endogenous attention, and that when caregivers respond to these proactive behaviors by naming the object it boosts infants' word learning. To examine this, we invited caregivers and their 14-mo-old infants to play with novel objects, before testing infants' retention of the novel object-label mappings. Meanwhile, their electroencephalograms were recorded. Results showed that infants' proactive looks toward an object during play associated with greater neural signatures of endogenous attention. Furthermore, when caregivers named objects during these episodes, infants showed greater word learning, but only when caregivers also joined their focus of attention. Our findings support the idea that infants' proactive visual explorations guide their acquisition of a lexicon. [ABSTRACT FROM AUTHOR]

Superhydrophobic strain sensors are highly promising for human motion and health monitoring in wet environments. However, the introduction of superhydrophobicity inevitably alters the mechanical and conductive properties of these sensors, affecting sensing performance and limiting behavior monitoring. Here, we developed an alkylated MXene–carbon nanotube/microfiber composite material (AMNCM) that is simultaneously flexible, superhydrophobic, and senses properties. Comprising a commercially available fabric substrate that is coated with a functional network of alkylated MXene/multi-walled carbon nanotubes and epoxy–silicone oligomers, the AMNCM offers high mechanical and chemical robustness, maintaining high conductivity and strain sensing properties. Furthermore, the AMNCM strain sensor achieves a gauge factor of up to 51.68 within a strain range of 80–100%, and exhibits rapid response times (125 ms) and long-term stability under cyclic stretching, while also displaying superior direct/indirect anti-fouling capabilities. These properties position the AMNCM as a promising candidate for next-generation wearable devices designed for advanced environmental interactions and human activity monitoring. [ABSTRACT FROM AUTHOR]

Significant efforts are currently being made to improve the quality of life of the older adult population. These efforts focus on aspects such as health, social interaction, and mental health. One of the approaches that has shown positive results in several studies is the application of game-based systems. These systems are not only used for entertainment, but also as tools for learning and promoting positive feelings. They are a means to overcome loneliness and isolation, as well as to improve health and provide support in daily life. However, it is important to note that, while these experiences are gradually being introduced to the older adult population, they are often designed with a younger audience in mind who are assumed to be more technologically proficient. This supposition can make older adults initially feel intimidated when interacting with this type of technology, which limits their ability to fully utilize and enjoy these technological solutions. Therefore, the purpose of this article is to apply a game experience and fun evaluation process oriented toward the older adult population based on the playability theory of human–computer interaction in virtual reality game experiences. This is expected to offer highly rewarding and pleasurable experiences, which will improve engagement with the older population and promote active and healthy aging. [ABSTRACT FROM AUTHOR]

The enantioselective mechanism of the esterase QeH against the two enantiomers of quizalofop–ethyl (QE) has been primitively studied using computational and experimental approaches. However, it is still unclear how the esterase QeH adjusts its conformation to adapt to substrate binding and promote enzyme–substrate interactions in the catalytic kinetics. The equilibrium processes of enzyme–substrate interactions and catalytic dynamics were reproduced by performing independent molecular dynamics (MD) runs on the QeH-(R)/(S)-QE complexes with a newly developed residue-specific force field (RSFF2C). Our results indicated that the benzene ring of the (R)-QE structure can simultaneously form anion–π and cation–π interactions with the side-chain group of Glu328 and Arg384 in the binding cavity of the QeH-(R)-QE complex, resulting in (R)-QE being closer to its catalytic triplet system (Ser78-Lys81-Tyr189) with the distances measured for the hydroxyl oxygen atom of the catalytic Ser78 of QeH and the carbonyl carbon atom of (R)-QE of 7.39 Å, compared to the 8.87 Å for (S)-QE, whereas the (S)-QE structure can only form an anion–π interaction with the side chain of Glu328 in the QeH-(S)-QE complex, being less close to its catalytic site. The computational alanine scanning mutation (CAS) calculations further demonstrated that the π–π stacking interaction between the indole ring of Trp351 and the benzene ring of (R)/(S)-QE contributed a lot to the binding stability of the enzyme–substrate (QeH-(R)/(S)-QE). These results facilitate the understanding of their catalytic processes and provide new theoretical guidance for the directional design of other key enzymes for the initial degradation of aryloxyphenoxypropionate (AOPP) herbicides with higher catalytic efficiencies. [ABSTRACT FROM AUTHOR]

This study was conducted to identify users' motivations for using the metaverse from a uses and gratification perspective and to identify users' categories based on their motives. In addition, this research investigated whether the degree of flow differs according to a user's motivation and segment. This study also examined the relationship between flow and the frequency of offline activity. Five motives (seeking advantages, extended social interactions, extended entertainment, virtual experience, and transfer consciousness) were identified. Among these, seeking advantage, extended social interactions, extended entertainment, and transfer consciousness positively influenced the degree of flow when using metaverse. Furthermore, among three distinct groups of metaverse users (goalless drift, pursuing a new world, and ego-boosting) the segment of pursuing a new world had the highest degree of flow. In addition, we confirmed that flow was negatively correlated with the amount of offline activity. [ABSTRACT FROM AUTHOR]

Collaborative knowledge construction (CKC) engages students work in small groups to complete specific tasks that are often open-ended, ill-structured, and beyond the knowledge and skills of the individual students in the group. Computer-supported collaborative concept mapping (CSCCM) with the support of prompts can be used to facilitate a high quality of CKC. However, previous empirical research showed complicated effects of prompts on the quality of CKC in the CSCCM environment. In this research, we developed a CSCCM platform customized with three CKC conditions (i.e., no prompt, agreement prompt, and disagreement prompt) to examine the effects of different prompts on CKC performance, process, and student perception. Results showed that the embedded disagreement prompt had the best effect on improving the quality of CKC among three conditions, regarding the peer interaction, cognitive engagement, behavioral contribution and group performance. Based on the results, this research provided theoretical implication related to transactivity, pedagogical strategy of considering advantages and disadvantages of agreement and disagreement prompts, as well as analytical implication of collecting and analyzing multi-source data with mixed methods for future research and practice. [ABSTRACT FROM AUTHOR]

The eukaryotic replisome is assembled around the CMG (CDC45-MCM-GINS) replicative helicase, which encircles the leading-strand DNA template at replication forks. When CMG stalls during DNA replication termination, or at barriers such as DNA-protein crosslinks on the leading strand template, a second helicase is deployed on the lagging strand template to support replisome progression. How these 'accessory' helicases are targeted to the replisome to mediate barrier bypass and replication termination remains unknown. Here, by combining AlphaFold structural modelling with experimental validation, we show that the budding yeast Rrm3 accessory helicase contains two Short Linear Interaction Motifs (SLIMs) in its disordered N-terminus, which interact with CMG and the leading-strand DNA polymerase Polε on one side of the replisome. This flexible tether positions Rrm3 adjacent to the lagging strand template on which it translocates, and is critical for replication termination in vitro and Rrm3 function in vivo. The primary accessory helicase in metazoa, RTEL1, is evolutionarily unrelated to Rrm3, but binds to CMG and Polε in an analogous manner, revealing a conserved docking mechanism for accessory helicases in the eukaryotic replisome. Synopsis: Accessory DNA helicases are required to overcome replisome stalling during DNA replication. This study describes a mechanism for targeting the Rrm3 accessory helicase to the budding yeast replisome via interactions with the CMG replicative helicase and DNA polymerase ε. This binding mode positions Rrm3 close to the lagging strand DNA template and is highly similar to RTEL1 in the human replisome. Budding yeast Rrm3 contains an N-terminal Intrinsically Disordered Region (IDR) that mediates its recruitment to the replisome. The Rrm3 IDR contains adjacent motifs that interact with the CMG helicase and DNA polymerase ε, positioning Rrm3 close to the lagging strand DNA template. Rrm3 binding to DNA polymerase ε is critical for Rrm3 function during DNA replication in vitro and in vivo. The metazoan accessory helicase RTEL1 interacts with CMG and DNA polymerase ε in a highly similar manner to Rrm3. Short linear interaction motifs present in accessory DNA helicases from yeast and humans mediate their interaction with the CMG replicative helicase and DNA polymerase ε. [ABSTRACT FROM AUTHOR]

Ten studies (N = 4192) demonstrated that individuals depicted as prosocial were judged to be more physically beautiful. This evaluation of prosocial individuals as more beautiful is influenced by a motivation to be associated with prosocial others. This phenomenon was observed in real‐world settings (Study 1) and applied to both men and women, both as targets and observers (Studies 2a–2b). The effect persisted in scenarios where participants imagined the target without any visual aid (Study 2c) and extended beyond metaphorical interpretations of beauty (Study 3). The effect weakened when prosocial behaviour was an isolated incident, not indicative of the target's prosocial personality (Study 4). The influence of prosociality on beauty evaluations surpassed that of other positive traits such as intelligence or humour (Study 5) and remained significant despite physical imperfections in the target's appearance (Study 6). The effect diminished in situations where forming a relationship was not feasible, thus supporting the motivated cognition rationale (Studies 7–8). These findings highlight the substantial role of prosocial behaviour in influencing evaluations of physical beauty, a crucial element in social interactions and relationship formation, often outweighing other attributes typically linked to physical appearance evaluation. [ABSTRACT FROM AUTHOR]

ABSTRACT Introduction Aim Method Results Discussion Implications for Practice Relevance Statement Studies suggest that experiences of patient participation, as described by both patients and staff, are associated with a significant caring relationship of high quality.This study aimed to investigate staffs' and patients' self‐reported perceptions on participation and the frequency and importance of verbal and social interactions in high‐security forensic psychiatry.The questionnaire Verbal and Social Interactions (VSI) was used together with the subscale Participation from Quality in Psychiatric Care (QPC). The study was conducted at a large forensic psychiatric clinic in Sweden.Staff and patients rated the frequency of VSI differently while reporting the same perceived degree of patient participation. All categories of VSI were significantly correlated with perceived level of participation with medium or small effect size for the patients.Patients' perceived participation seems to depend on verbal and social interaction within the specific categories ‘Showing interest in the patients’ feelings, experiences, and behavior’ and ‘Helping the patients establish structure and routines in their everyday life’. There was, however, a negative association for the latter.The results give a better understanding of what kind of interactions that affect patients' perceived level of participation.Patient participant is a prioritised area for development in forensic psychiatry. The study contributes to a better understanding of what types of interactions that affect the perceived level of participation, while at the same time, it shows important similarities and differences between patient and staff perspectives. [ABSTRACT FROM AUTHOR]

This paper proposes a method for multi-label visual emotion recognition that fuses fore-background features to address the following issues that visual-based multi-label emotion recognition often overlooks: the impacts of the background that the person is placed in and the foreground, such as social interactions between different individuals on emotion recognition; the simplification of multi-label recognition tasks into multiple binary classification tasks; and it ignores the global correlations between different emotion labels. First, a fore-background-aware emotion recognition model (FB-ER) is proposed, which is a three-branch multi-feature hybrid fusion network. It efficiently extracts body features by designing a core region unit (CR-Unit) that represents background features as background keywords and extracts depth map information to model social interactions between different individuals as foreground features. These three features are fused at both the feature and decision levels. Second, a multi-label emotion recognition classifier (ML-ERC) is proposed, which captures the relationship between different emotion labels by designing a label co-occurrence probability matrix and cosine similarity matrix, and uses graph convolutional networks to learn correlations between different emotion labels to generate a classifier that considers emotion correlations. Finally, the visual features are combined with the object classifier to enable the multi-label recognition of 26 different emotions. The proposed method was evaluated on the Emotic dataset, and the results show an improvement of 0.732% in the mAP and 0.007 in the Jaccard's coefficient compared with the state-of-the-art method. [ABSTRACT FROM AUTHOR]

Featured Application: We found that more students could reproduce therapeutic movement techniques by practicing with a robot that simulates the patient's pathological movements than by performing simulation exercises with other students. These results suggest that the use of simulation robots that can reproduce the pathological movements of patients may be effective in teaching therapeutic movement techniques. Furthermore, we believe that it is an effective new learning method for therapeutic movement techniques considering interpersonal infections. We aimed to compare the effects of practical learning using an educational robot arm (Samothrace: SAMO) and a student simulating a patient in students' acquisition of therapeutic motion techniques. For this study, twenty-five fourth-year students and eight therapists were included. Students were randomly assigned to the robot practice (Robo) group (n = 13) or conventional practice (Human) group (n = 12), wherein students practiced among themselves. The experimental procedure comprised a pre-practice test, practice, and post-practice test. We calculated the peak angle ratio, peak velocity, and movement time during flexion and extension using the elbow joint angle data. Machine learning was performed on students' pre-practice and used therapists' data to create identifiers that distinguish students and therapists to determine whether the students' skills improved to the level of a therapist. However, regarding other kinematics data, there were no main effects or interactions between groups pre- and post-practice. Identifiers were created from machine learning of kinematics data pre-practice, and the effect was evaluated post-practice. A higher number of students in the Robo group were determined to possess skills at a therapist's level. This study suggests the effectiveness of a simulation robot that can reproduce a patient's pathological motions in educating students on upper limb exercise therapy. [ABSTRACT FROM AUTHOR]

Previous research has shown that the relationship between a supervisor and a subordinate is crucial in shaping employee voice behaviour. However, where these relationships originate needs to be clarified. Studies on relational schemas suggest that the quality of these relationships depends on the relational schemas held by both leaders and subordinates. Unfortunately, these two research areas have developed independently and have yet to intersect, which limits our understanding of how social interactions between leaders and subordinates impact employee voice behaviour. Based on research from both domains, the current study examines how the supervisor–subordinate relational schema affects employees' voice behaviour. Our proposal, grounded in complexity theory, suggests that the expectations of both leaders and subordinates about their relationship model determine whether employees choose to voice their opinions to their leaders. Analyses of data from a survey of 416 matched pairs of leaders and subordinates in China conducted using fsQCA and LPA largely support our view. The results indicate that the configuration of the supervisor–subordinate relational schema among leaders and subordinates can predict the level of employee voice behaviour. Additionally, this configuration is a natural subset of the population. These findings have important implications for improving employee voice behaviour in organizations. [ABSTRACT FROM AUTHOR]

For better decisions in social interactions, humans often must understand the thinking of others and predict their actions. Since such predictions are uncertain, multiple predictions may be necessary for better decision-making. However, the neural processes and computations underlying such social decision-making remain unclear. We investigated this issue by developing a behavioral paradigm and performing functional magnetic resonance imaging and computational modeling. In our task, female and male participants were required to predict others' choices in order to make their own value-based decisions, as the outcome depended on others' choices. Results showed, to make choices, the participants mostly relied on a value difference (primary) generated from the case where others would make a likely choice, but sometimes they additionally used another value difference (secondary) from the opposite case where others make an unlikely choice. We found that the activations in the posterior cingulate cortex (PCC) correlated with the primary difference while the activations in the right dorsolateral prefrontal cortex (rdlPFC) correlated with the secondary difference. Analysis of neural coupling and temporal dynamics suggested a three-step processing network, beginning with the left amygdala signals for predictions of others' choices. Modulated by these signals, the PCC and rdlPFC reflect the respective value differences for self-decisions. Finally, the medial prefrontal cortex integrated these decision signals for a final decision. Our findings elucidate the neural process of constructing value-based decisions by predicting others and illuminate their key variables with social modulations, providing insight into the differential functional roles of these brain regions in this process. [ABSTRACT FROM AUTHOR]

AbstractParticipating in online mathematical discussions is a beneficial strategy to improve online math learning. Research has examined online mathematical discussions from various aspects, focusing on the content discussed, student interaction, and the technical tools facilitating student participation, but few studies have investigated the interplay among these aspects. This study draws on Communicative Ecology Theory (CET, Foth & Hearn, 2007), which conceptualizes the sustainability of online communities as influenced by discursive, social, and technical factors, to explore how students’ discursive, social, and technical participation behaviors on an online mathematical discussion board are interacted. Leveraging a dataset including more than 90,000 students and two million online discussion interactions, this study indicated that students’ engagement with technical functions, especially a communication tool and a motivation system, within the discussion board significantly facilitated their social interactions and enhanced their demonstration of mathematical knowledge, mathematical literacy, and affective control in the discussions. These findings provide insights for educators and designers of educational applications to enhance student participation in online discussions thereby improving the effectiveness of these discussions in online learning. [ABSTRACT FROM AUTHOR]

AbstractAimMethodResultsConclusionTo co-construct a dance class adapted for adolescents with cerebral palsy (CP).A three phase co-construction process with study collaborators was used to (1) define the objectives and the obstacles and opportunities related to offering a dance class in the community through three focus groups with adolescents, their parents and study partners; (2) co-create the dance class based on the results of step 1, the expertise of the research team and the logic model of the dance class; and (3) test the dance class to evaluate its effects in relation to the defined objectives.Three objectives were identified: to have fun, promote movement, and social interaction. A weekly dance class (60 min./10 wk) was continuously tested on the adolescents and adapted by the dance facilitators.To improve practices and support the implementation of dance classes for young people with CP, eight recommendations are proposed relating to the creation of adapted classes and the evaluation of their desired effects. [ABSTRACT FROM AUTHOR]

The traditional domains of land, sea, and air warfare have long held prominence, while space and cyberspace have recently gained recognition as spheres of conflict. As conflicts continue to evolve, the domains of war must expand to accommodate new dimensions of engagement and integrate them alongside those human-centred factors that have previously held considerable sway. It is imperative, therefore, to recognise culture as the sixth domain and reflect upon its profound influence on group thinking, decision-making, and behaviour. Integrating culture into the Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance, Reconnaissance and Targeting (C5ISRT) framework acknowledges its strategic relevance in shaping military strategies and responses in an increasingly complex and interconnected world. This paradigm shift highlights that the modern landscape extends beyond physical and virtual theatres to encompass the cognitive and social dimensions that define human interactions and conflicts. [ABSTRACT FROM AUTHOR]

Adolescence is a critical period for brain development in humans and stress exposure during this time can have lasting eects on behavior and brain development. Social isolation and loneliness are particularly salient stressors that lead to detrimental mental health outcomes particularly in females, although most of the preclinical work on social isolation has been done in male animals. Our lab has developed a model of post-weaning adolescent social isolation that leads to increased drug reward sensitivity and altered neuronal structure in limbic brain regions. The current study utilized this model to determine the impact of adolescent social isolation on a three-chamber social interaction task both during adolescence and adulthood. We found that while post-weaning isolation does not alter social interaction during adolescence (PND45), it has sexspecific eects on social interaction in young adulthood (PND60), potentiating social interaction in male mice and decreasing it in female mice. As early life stress can activate microglia leading to alterations in neuronal pruning, we next examined the impact of inhibiting microglial activation with daily minocycline administration during the first 3 weeks of social isolation on these changes in social interaction. During adolescence, minocycline dampened social interaction in male mice, while having no eect in females. In contrast, during young adulthood, minocycline did not alter the impact of adolescent social isolation in males, with socially isolated males exhibiting higher levels of social interaction compared to their group housed counterparts. In females, adolescent minocycline treatment reversed the eect of social isolation leading to increased social interaction in the social isolation group, mimicking what is seen in naïve males. Taken together, adolescent social isolation leads to sex-specific eects on social interaction in young adulthood and adolescent minocycline treatment alters the eects of social isolation in females, but not [ABSTRACT FROM AUTHOR]

Social interactions are often analyzed by scoring segments of predefined behavior and then statistically assessing numerical and sequential patterns to identify the structure of the encounters. However, this approach can miss the dynamics of the animals' relationship over the course of the encounter, one that often involves invariant bonds, say a nose-to-nose orientation, with many different movements performed by both partners acting to counteract each other's attempts to break or maintain the relationship. Moreover, these invariant bonds can switch from one configuration to another during an interaction, leading from one stable configuration to another. It is this stepwise sequence of configurational stabilities that lead to functional outcomes, such as mating, aggression, or predation. By focusing on the sequence of invariant relational configurations, the deep structure of interactions can be discerned. This deep structure can then be used to differentiate between compensatory movements, no matter how seemingly stereotyped they may appear, from movement patterns which are restricted to a particular form when more than one option is available. A dynamic perspective requires suitable tools for analysis, and such tools are highlighted as needed in describing particular interactions. [ABSTRACT FROM AUTHOR]

The current study synthesizes 34 effect sizes from 18 articles involving 9,271 participants to investigate how media multitasking influences enjoyment under different circumstances. The moderating effects of task combination, sample demographics, and methodological artifacts are examined. Study results indicate that task relevance boosts the positive relationship between media multitasking and enjoyment, with sample mean age and gender ratio being controlled. Sample demographics also moderate the relationship between media multitasking and enjoyment, with community samples and men reporting higher levels of enjoyment than student samples and women. Lab studies yield lower enjoyment than their non-lab counterparts; single-item measures of enjoyment generate more positive results than multi-item measures. Moreover, when studies using non-media tasks are excluded, surveys, older generations, and studies with social media interaction as the secondary task report higher multi-screening enjoyment. [ABSTRACT FROM AUTHOR]

Many biological problems are understudied due to experimental limitations and human biases. Although deep learning is promising in accelerating scientific discovery, its power compromises when applied to problems with scarcely labeled data and data distribution shifts. We develop a deep learning framework—Meta Model Agnostic Pseudo Label Learning (MMAPLE)—to address these challenges by effectively exploring out-of-distribution (OOD) unlabeled data when conventional transfer learning fails. The uniqueness of MMAPLE is to integrate the concept of meta-learning, transfer learning and semi-supervised learning into a unified framework. The power of MMAPLE is demonstrated in three applications in an OOD setting where chemicals or proteins in unseen data are dramatically different from those in training data: predicting drug-target interactions, hidden human metabolite-enzyme interactions, and understudied interspecies microbiome metabolite-human receptor interactions. MMAPLE achieves 11% to 242% improvement in the prediction-recall on multiple OOD benchmarks over various base models. Using MMAPLE, we reveal novel interspecies metabolite-protein interactions that are validated by activity assays and fill in missing links in microbiome-human interactions. MMAPLE is a general framework to explore previously unrecognized biological domains beyond the reach of present experimental and computational techniques. MMAPLE, a semi-supervised meta-learning framework, effectively addresses data scarcity and out-of-distribution challenges in deep learning. It uncovers novel drug-target, metabolite-enzyme, and microbiome-human interactions. [ABSTRACT FROM AUTHOR]

ABSTRACT Disease outbreaks are one of the key threats to great apes and other wildlife. Because the spread of some pathogens (e.g., respiratory viruses, sexually transmitted diseases, ectoparasites) are mediated by social interactions, there is a growing interest in understanding how social networks predict the chain of pathogen transmission. In this study, we built a party network from wild chimpanzees (Pan troglodytes), and used agent‐based modeling to test: (i) whether individual attributes (sex, age) predict individual centrality (i.e., whether it is more or less socially connected); (ii) whether individual centrality affects an individual's role in the chain of pathogen transmission; and, (iii) whether the basic reproduction number (R0) and infectious period modulate the influence of centrality on pathogen transmission. We show that sex and age predict individual centrality, with older males presenting many (degree centrality) and strong (strength centrality) relationships. As expected, males are more central than females within their network, and their centrality determines their probability of getting infected during simulated outbreaks. We then demonstrate that direct measures of social interaction (strength centrality), as well as eigenvector centrality, strongly predict disease dynamics in the chimpanzee community. Finally, we show that this predictive power depends on the pathogen's R0 and infectious period: individual centrality was most predictive in simulations with the most transmissible pathogens and long‐lasting diseases. These findings highlight the importance of considering animal social networks when investigating disease outbreaks. [ABSTRACT FROM AUTHOR]

This paper catalyses the academic urgency to understand agri-food system transformation pathways. Such transformation requires new food growing imaginaries of rooted in a change of thinking and ways of engaging with more-than-human perspectives. Urban spaces are hubs of human and more-than-human interactions, and urban organic farming offers an excellent site for exploring such new food growing imaginaries. The research presented here innovates theoretical and methodological knowledge in more-than-human geography. It develops alternative food growing imaginaries through a sensory ethnography at an urban organic workers’ cooperative Organiclea and visual arts methodologies. Through that, the paper brings to the fore the marginalized more-than-human perspectives by exploring more-than-human sensory Umwelts – taste and nutrition for the soil, sound for soil denizens, smell for honeybees, tactile perception for common weeds – and understanding human experience of food growing through sight. Attuning to a more-than-human sensorium broadens our knowledge of the life stories of other biotic and abiotic critters and recognizes that human and more-than-human world-making projects are interconnected. The paper concludes that sensory engagement is critical to the development of new imaginaries for a more sustainable food production. [ABSTRACT FROM AUTHOR]

Climate change affects ecosystems at several levels: by altering the spatial distribution of individual species, by locally rewiring interspecific interactions, and by reorganizing trophic networks at larger scales. The dynamics of marine food webs are becoming more and more sensitive to spatial processes and connections in the seascape. As a case study, we study the atlantification of the Barents Sea: we compare spatio-temporal subsystems at three levels: the identity of key organisms, critically important interactions and the entire food web. Network analysis offers quantitative measurements, including centrality indices, trophic similarity indices, a topological measure of interaction asymmetry and network-level measures. We found that atlantification alters the identity of key species (boreal demersals becoming hubs), results in strongly asymmetric interactions (dominated by haddock), changes the dominant regulation regime (from bottom-up to wasp-waist control) and makes the food web less modular. Since the results of food web analysis may be quite sensitive to network construction, the aggregation of food web data was explicitly studied to increase the robustness of food web analysis. We found that an alternative, mathematical aggregation algorithm better preserves some network properties (e.g. density) of the original, unaggregated network than the biologically inspired aggregation into functional groups. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'. [ABSTRACT FROM AUTHOR]

Many lateral biases exist in human behavior, often implicit and not deliberated. Romantic kissing and embracing received experimental attention in the last three decades. We investigated laterality in paintings depicting these social interactions using two methodologies to assess whether painters depicted such biases and whether these biases could be due to observers’ aesthetic preferences or painters’ ability in portraying naturalistic interactions. In Study 1, we inspected about 190,000 artworks available online to classify leftward and rightward biases in romantic kisses and embraces. The comparison of 103 paintings depicting clearly lateralized interactions revealed a significant rightward bias in romantic kissing (66%) and a trend toward a leftward bias (62%) for embraces, aligning with naturalistic studies of human interactions. In Study 2, 128 participants expressed their aesthetic preference between the paintings selected in Study 1 and their vertically mirrored versions. A preference for the original paintings over their mirrored versions emerged, especially when presented in the upper portion of the screen, but no significant preference for the typical lateralization of kissing and embracing was found. These findings suggest that artists’ alignment with naturalistic biases could be due to familiarity and exposure to asymmetric interactions rather than observers’ aesthetic preferences. [ABSTRACT FROM AUTHOR]

A-to-I RNA editing is a cellular mechanism that generates transcriptomic and proteomic diversity, which is essential for neuronal and immune functions. It involves the conversion of specific adenosines in RNA molecules to inosines, which are recognized as guanosines by cellular machinery. Despite the vast number of editing sites observed across the animal kingdom, pinpointing critical sites and understanding their in vivo functions remains challenging. Here, we study the function of an evolutionary conserved editing site in Drosophila, located in glutamate-gated chloride channel (GluCla). Our findings reveal that flies lacking editing at this site exhibit reduced olfactory responses to odors and impaired pheromone-dependent social interactions. Moreover, we demonstrate that editing of this site is crucial for the proper processing of olfactory information in projection neurons. Our results highlight the value of using evolutionary conservation as a criterion for identifying editing events with potential functional significance and paves the way for elucidating the intricate link between RNA modification, neuronal physiology, and behavior. [ABSTRACT FROM AUTHOR]

Gifted students may be at risk of school disengagement due to lacking intellectual challenges. Four talent centers were established to offer makerspace enrichment programs, because makerspace activities promote engagement and science, mathematics, and technology learning. In the current study, we investigated gifted students’ experiences with makerspace enrichment programs in Norway in terms of social aspects, learning aspects and teacher support aspects. We conducted semistructured interviews with 15 participants (15–16 years) from four different talent centers across the country. Findings suggested that the informants had an overall positive experience of participation and that most were more engaged at talent centers than at their home schools. In addition, the makerspace approaches seemed to suit gifted learners’ need for more complex subject content and facilitate interaction with peers and teachers with similar content knowledge/interest. We concluded that makerspace activities at talent centers constitute an important supplement to ordinary school for gifted students. [ABSTRACT FROM AUTHOR]

The study of social interactions lies at the core of several disciplines such as psychiatry, psychology and ethology, just to name a few. In this context, understanding the temporal patterns underlying interactive behaviors is of crucial importance. Here, we employed T-pattern detection and analysis to study social interactions in ten pairs of Wistar rats tested in an Open-Field environment. We found four different categories of interactive behaviors. One of them was of particular interest to us because it consisted of behavioral events that, taken individually, should not underlie an interaction of any kind; however, they were included in T-patterns, which is suggestive of a dyadic temporal coordination in the behavioral expression of two individuals. Within this category, we described for the first time a new subcategory of apparent interaction patterns characterized by events that one of the two rats repeats only if previously produced by the partner (i.e., behavioral mirroring). These findings are discussed in functional terms for rodents and in light of our current understanding of social interactions in humans. [ABSTRACT FROM AUTHOR]

Recent advances in high-throughput measurement technologies have enabled the analysis of molecular perturbations associated with disease phenotypes at the multi-omic level. Such perturbations can range in scale from fluctuations of individual molecules to entire biological pathways. Data-driven clustering algorithms have long been used to group interactions into interpretable functional modules; however, these modules are typically constrained to a fixed size or statistical cutoff. Furthermore, modules are often analyzed independently of their broader biological context. Consequently, such clustering approaches limit the ability to explore functional module associations with disease phenotypes across multiple scales. Here, we introduce AutoFocus, a data-driven method that hierarchically organizes biomolecules and tests for phenotype enrichment at every level within the hierarchy. As a result, the method allows disease-associated modules to emerge at any scale. We evaluated this approach using two datasets: First, we explored associations of biomolecules from the multi-omic QMDiab dataset (n = 388) with the well-characterized type 2 diabetes phenotype. Secondly, we utilized the ROS/MAP Alzheimer's disease dataset (n = 500), consisting of high-throughput measurements of brain tissue to explore modules associated with multiple Alzheimer's Disease-related phenotypes. Our method identifies modules that are multi-omic, span multiple pathways, and vary in size. We provide an interactive tool to explore this hierarchy at different levels and probe enriched modules, empowering users to examine the full hierarchy, delve into biomolecular drivers of disease phenotype within a module, and incorporate functional annotations. AutoFocus is an interactive tool to explore hierarchical frameworks of multi-omics disease associations to probe modules and test for phenotype enrichment at every level within the hierarchy and incorporates functional annotations. [ABSTRACT FROM AUTHOR]

The research aims to identify the impact of educational activities based on interactive chat in the fencing course on the skill level and social interaction among female students of the Faculty of Physical Education, Benha University, by identifying: 1- The effect of interactive chat activities on the level of learning some fencing skills among female students in the experimental group and the control group for the sample under study. 2- The effect of interactive chat activities on the level of social interaction among female students in the experimental group and the control group for the sample under study. 3- The effect of interactive chat activities on the level of learning some fencing skills and the level of social interaction among female students in the control and experimental groups for the sample under study.The researcher used the experimental method using two groups, one a control group and the other an experimental group, depending on the nature of the research. It includes female students in the second group, numbering (800) freshmen students enrolled in the Faculty of Physical Education, Benha University, for the first semester of the academic year 2023/2024 AD. The researcher selected a number of (80) female students. From the second year female students at the Faculty of Physical Education. [ABSTRACT FROM AUTHOR]

The unique characteristics of Indian trans-identity are shaped by cultural intricacies, setting it apart from its Western counterparts. Despite facing marginalisation in mainstream Indian society, the intricacies of their constructed trans-culture further complicate their experiences. According to the interactionist perspective of gender identity within sociological theory, an individual's interactions with peers, family, and society influence the development of their gender identity. Examining this concept within the diverse Indian context reveals the significant nuances of Indian trans-identity. Two Bengali-Indian films, Kaushik Ganguly's Nagarkirtan (2019) and Rituparno Ghosh's Chitrangada: The Crowning Wish (2012), depict the intense and challenging journeys of individuals embracing their trans identities. This research aims to analyse the films from an interactionist perspective, exploring how the Indian cultural discourses portrayed in the films influence the formation of trans identities. The findings suggest that the development of trans identity involves complex processes influenced by social interactions, where conflicts between one's generalised self and instinctual self arise due to sexual digression. Additionally, this study indicates that the sexual scripting of trans individuals is influenced by various factors, including class, culture, financial status, and social position, making it challenging to conform to the binary gender script of a normalised society. This qualitative research utilises the Interactionist theory of gender identity to analyse the two Bengali-Indian films. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodResultsConclusions\nIMPLICATIONS FOR REHABILITATION(1) To understand the impact of adult cochlear implantation on the partner relationship, as perceived by adult cochlear implant (CI) recipients and their intimate partners. (2) To generate a conceptual framework for guiding future research and clinical adult cochlear implantation interventions.Concept mapping, a participatory, mixed-method approach, was used for data collection, analysis and interpretation. Participants attended sessions to generate, sort and rate statements describing the changes in their relationship due to cochlear implantation. Participants included 15 CI recipients (mean age: 51.6 years; SD: 8.2) and 12 partners (mean age: 50.9 years; SD: 8.2).Five concepts emerged from the data, describing changes in the partner relationship following cochlear implantation: (1) Social Interactions, (2) Partner Involvement, (3) Communication, (4) Emotional Adjustment, and (5) Relationship Intimacy. The concept Relationship Intimacy was rated the highest in positivity and importance. Findings also underscored improved social interactions, communication dynamics, and emotional adjustment.The Relationship Intimacy cluster emerged as pivotal, highlighting its essential role in improving post-implantation relationships. CI recipients experienced enhanced autonomy, while partners’ roles evolved regarding assistance and support. The diverse effects of implantation on partner relationships highlight the importance of adopting a patient- and family-centered approach to audiological intervention.These insights on partner relationships and cochlear implantation can inform tailored pre- and ongoing post-operative counselling to support cochlear implant recipients and their partners in navigating relationship changes, emotional adjustments, and addressing communication challenges.Cochlear implantation reduces partner burden, emphasising the need for hearing healthcare professionals to facilitate partner engagement in rehabilitation approaches.Relationship intimacy, deemed the foremost positive outcome, underscores the importance of incorporating these aspects into pre- and post-operative counselling.These insights on partner relationships and cochlear implantation can inform tailored pre- and ongoing post-operative counselling to support cochlear implant recipients and their partners in navigating relationship changes, emotional adjustments, and addressing communication challenges.Cochlear implantation reduces partner burden, emphasising the need for hearing healthcare professionals to facilitate partner engagement in rehabilitation approaches.Relationship intimacy, deemed the foremost positive outcome, underscores the importance of incorporating these aspects into pre- and post-operative counselling. [ABSTRACT FROM AUTHOR]

Millions of internally displaced people are living in their own countries in a temporary status called ‘protracted displacement’, a term not without its debates. We use a social network analysis database to assess how social interactions and demographic characteristics, including the relative location of resettlement, may contribute to IDP integration during the first 2 years of displacement. Our analysis of information from 57 internally displaced individuals in the aftermath of the 2008 Russo‐Georgian War, finds that networks of persistence, rather than survival or integration, characterize patterns of protracted displacement within 2 years of displacement. This suggests a need for rethinking the mainstream definitions to ensure vital resources are provided to displaced populations to promote timely integration. [ABSTRACT FROM AUTHOR]

Legal rules are based on an imagined regulatory scene that contains presumptions about the reality a regulation addresses. Regarding automated decision-making (ADM), these include a belief in the ‘good human decision’ that is mirrored in the cautious approach in the GDPR. Yet the ‘good human decision’ defies psychological insight into human weaknesses in decision-making. Instead, it reflects a general unease about algorithmic decisions. Against this background I explore how algorithms become part of human relationships and whether the use of decision systems causes a conflict with human needs, values and the prevailing socio-legal framework. Inspired by the concept of Human-Centered AI, I then discuss how the law may address the apprehension towards decision systems. I outline a human-focused approach to regulating ADM that focuses on improving the practice of decision-making. The interaction between humans and machines is an essential part of the regulation. It must address socio-legal changes caused by decision systems both to integrate them into the existing value system and adapt the latter to changes brought forth by ADM. A human-focused approach thus connects the benefits of technology with human needs and societal values. [ABSTRACT FROM AUTHOR]

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The study examines the interaction between social capital, education, and subjective well-being in Ecuador, highlighting its impact on economic development. The study aims to understand the situation of social capital and subjective well-being and how the identified factors explain the impact on subjective well-being in the Ecuadorian population, using a descriptive and analytical approach with information from the World Value Survey database of waves 6 and 7. The main results show a significant relationship between social capital and subjective well-being, with positive influences such as justice and union membership, and negative effects of public administration and media. In conclusion, the importance of strengthening social capital and improving public services and communication to promote the well-being of the Ecuadorian population is emphasized. [ABSTRACT FROM AUTHOR]

It is necessary to say that Ash'arism is one of the sects that attracts attention in the intersectarian relationship due to its interaction with different groups. In fact, Ash'arism is known to have interacted intensively with Māturīdīsm, Hanbalism and Mu'tazila. Apart from these, it is known that especially in the Khurāsān region, Ash'arites had an intense oppositional relationship with the Karrāmiyya. It is understood that the Karrāmiyya, Hanbalism, and Zāhirīsm harshly criticized the Ash'arites' views on prophethood. In the relationship between Karrāmism and Ash'arism, the view that "the soul is considered an accident, that the soul of the Prophet Muhammad disappeared with his death, and consequently that his prophethood ended with his death" is one of the issues that came to the fore. It is clear that the ideas of the Ash'arites on prophethood are important because they were at the center of the debates between the Karrāmites and the Ash'arites in the Khurāsān region centred on Nīshāpūr for about three centuries. Particularly important representatives of 5/11th century Ash'arism, such as al-Qushayrī, made an intensive efforts to respond to their interlocutors on the subject. The fact that al-Bayhaqī, one of the representatives of Khurāsān Asharism who lived in the aforementioned century, had to leave the region where he lived in because of the Mihna of Kundurī and that he wrote a detached work on the debate with the Karrāmīs are signs that he was affected by the social consequences of the inter-sectarian struggle. In this respect, al-Bayhaqī's treatise entitled Hayāt al-anbiyā ba'da wafātihim has been accepted as a text that should be evaluated within the framework of inter-sectarian relations. In addition, later Ash'arite scholars such as al-Subkī also expressed their opinions on the subject in their works. Within the framework of the abovementioned reasons, it should be noted that this study, with the historical perspective and the in-dept study of the person and text, focuses on "the debates on the continuation of prophethood after the death of prophets, the criticisms of their opponents against the Ash'arites and the response of Ash'arism and al-Bayhaqī in particular". [ABSTRACT FROM AUTHOR]

The article aimed to identify the attitudes of media students in Jordanian universities regarding employing artificial intelligence (AI) in learning in Jordan and the most prominent challenges they face in acquiring sufficient knowledge of AI interventions. In this regard, we rely on a survey approach based on knowing the attitudes of media students regarding applications of AI in learning through their responses via a questionnaire of (33) items distributed to a random sample of 338 students. The results revealed that the most prominent trend among media students towards using AI in learning is that AI helps improve the efficiency and speed of editing processes, improves the quality of content, and enhances the learning experience. The results also showed that the fields of employing AI in learning are editing and media writing, "producing and inventing new forms of media materials," and discovering sources. The results showed that the most prominent disadvantages of employing AI in learning are weakening students' ability to develop critical thinking skills and weakening the student's direct human interaction with teachers or colleagues. It showed that the most important challenges facing media students in employing AI are the lack of awareness of the importance of using AI in education and the lack of a clear strategy in Jordanian universities for applying AI to learning. [ABSTRACT FROM AUTHOR]

Clothing has played a significant role in meeting people's basic needs for warmth and protection and social interactions, distinguishing communities, and reflecting personal differences. Research indicates clothing choices impact social perception by conveying messages through their clothes. Clothing preferences emerge as factors significantly influencing individuals' social perceptions and relationships. Therefore, it is believed an in-depth examination of the meaning of clothing for individuals and their dressing behaviors will play a critical role in understanding one's relationship with oneself and with society. This study investigated the meaning of clothing and the experiences of recurring clothing behaviors. For this aim, semi-structured interviews were conducted with six participants reporting repetitive clothing-related behaviors. All interviews were transcribed, coded, and analyzed by Interpretive Phenomenological Analysis. As a result of the analysis, it was found the meanings attributed to clothes varied in personal and social contexts. Repetitive behaviors emerged in purchasing, using, cleaning, dressing-undressing, and storing. While in purchasing, recurring behaviors had subthemes of logical and emotional choices, repetitions in using had subthemes of stability/insistency and variability/flexibility. Repetitions in cleaning included washing newly purchased or used clothing before wearing them; repetitions in dressing and undressing, dressing and undressing starting from the right side and dressing starting from the lower body, undressing beginning from the upper body; repetitions in storing had subthemes of place of use, type, season, and color. These findings showed clothing carried different meanings in personal and social realms, and clothing-related recurring behaviors were experienced differently. The results discussed considering psychological and cultural factors. [ABSTRACT FROM AUTHOR]

Social media texts like tweets and blogs are collaboratively created by human interaction. Rapidly changing trends are leading to topic drift in the social media text. This drift is usually associated with words and hashtags. However, geotags play an essential part in determining topic distribution with location context. The rate of change in the distribution of words, hashtags and geotags cannot be considered uniform and must be handled accordingly. This paper builds a topic model that associates the topic with a mixture of distributions of words, hashtags and geotags. Stochastic gradient Langevin dynamic model with varying mini-batch sizes is used to capture the changes due to the asynchronous distribution of words and tags. Topic representations with co-occurrence and location contexts are specified as hashtag context vector and geotag context vector respectively. These two vectors are jointly learned to yield topical word embedding vectors over time conditioned on hashtags and geotags that can predict location-based topical variations effectively. When evaluated with Chennai and UK geolocated Twitter data, the proposed joint topical word embedding model enhanced by the social tags context, outperforms other methods. [ABSTRACT FROM AUTHOR]

This research uses a new method called the Modified Adolescent Identity Search Algorithm (MAISA) to solve optimization problems. The identity of a teenager is a different combination of thoughts, beliefs, and abilities that are obtained by him. He communicates with other people in society and tries to use the positive or negative feedback from these social interactions to shape his identity and become an independent person. Mathematical simulation of how adolescents' personality is formed during the mentioned process causes the emergence of this algorithm. The purpose of this research is to improve the performance of the AISA algorithm in the balance between exploration and exploitation. This algorithm isn't trapped in the optimal local points due to the appropriate convergence rate and reaches the universal optimal answer quickly. One of the features of this algorithm that we can mention is its simplicity and having few setting parameters. To show the effectiveness of this algorithm, results of solving two types of problems of mathematical functions and practical examples such as large-scale truss 120, 244, 942, and 72-bar truss, are measured by other similar algorithms. The results show that this algorithm has a good performance in the optimal solution of such problems, compared to other similar algorithms. [ABSTRACT FROM AUTHOR]

Computational models of peer interaction, with or without networks, have been applied to opinion dynamics to describe social phenomena. Here, we use the Deffuant–Weisbuch (DW) model of opinion dynamics, where a confidence parameter bounds individuals' interactions, both in paradigmatic artificial networks and some social networks. The interaction of an individual with their immediate neighbors is incorporated into the model using Asch's concept of social conformity. In general, conformity facilitates consensus in networks by reducing the time required to reach a state of equilibrium and by increasing the likelihood of a single opinion value prevailing throughout the network. In real networks, a higher probability of adherence ( p Asch = 0.6 ) to the majority opinion increases the proportion of individuals in consensus within less tolerant networks ( d < 0.5 ). Conformity leads to more nodes agreeing around the same average opinion in a shorter time. [ABSTRACT FROM AUTHOR]

Background: Children with Disinhibited Social Engagement Disorder (DSED) have specific difficulties with indiscriminate sociability, yet little is known about their broader social competencies as DSED tends not to be identified within samples in the wider 'maltreatment literature.' Aim: To systematically review the literature to determine the social competencies of children with DSED. Methods: A comprehensive search following PRISMA guidelines was undertaken using PsycINFO, Medline, Embase, and Cumulative Index to Nursing & Allied Health. Results: From a total of 553 articles, 16 studies were selected and critically evaluated. Children with DSED were consistently reported to have poorer social competencies than non‐maltreated peers and environmental controls. Greater peer problems were consistently found, and they may present with poor self‐esteem/concept related to social acceptance. Findings regarding social interaction/communication skills were mixed. Limitations: 50% of studies were of moderate quality due to sampling and possible confounding variables. Conclusion: Children with DSED present with social relationship problems, beyond the core symptoms of the disorder, but the relative impact of co‐occurring neurodevelopmental conditions is not yet clear. In addition, pragmatic language and communication skills require further research. [ABSTRACT FROM AUTHOR]

The present study investigated the expression of emotions in pupils of the first five grades of primary school. The sample (N = 114) comprised pupils aged between 6.5 and 10.6 years, whose expression of emotions was observed using an observational schema. Observations were gathered in classrooms at 70 schools in different regions of Slovenia. Fourteen emotions were recognized in the pupils' expressions, with joy and anger predominating. The intensity of the expression of positive and negative emotions, as well as basic and complex emotions, was moderate, and no significant difference in intensity was observed between these categories. Boys expressed more positive, negative and basic emotions than girls. The situations that elicited emotions varied and reflected the prominent issues in school, particularly academic achievement, social interactions with teachers and classmates, and activities during lessons. The applicability of the results to teachers' work in the classroom was highlighted. [ABSTRACT FROM AUTHOR]

Tactile sensing plays a vital role in human somatosensory perception as it provides essential touch information necessary for interacting with the environment and accomplishing daily tasks. The progress in textile electronics has opened up opportunities for developing intelligent wearable devices that enable somatosensory perception and interaction. Herein, a skin‐inspired all‐textile pressure sensor (ATP) is presented that emulates the sensing and interaction functions of human skin, offering wearability, comfort, and breathability. The ATP demonstrates impressive features, including ultrahigh sensitivity (1.46 × 106 kPa−1), fast response time (1 ms), excellent stability and durability (over 2000 compression‐release cycles), a low detection limit of 10 Pa, and remarkable breathability (93.2%). The multipixel array of ATPs has been proven to facilitate static and dynamic mapping of spatial pressure, as well as pressure trajectory monitoring functions. Moreover, by integrating ATP with oscillation circuits, external force stimuli can be directly encoded into digital frequency pulses that resemble human physiological signals. The frequency of output pulses increases with the applied pressure. Consequently, an ATP‐based artificial sensory system is constructed for intelligent tactile perception. This work provides a simple and versatile strategy for practical applications of wearable electronics in the fields of robotics, sports science, and human–machine interfaces technologies. [ABSTRACT FROM AUTHOR]

For an individual to exist in a society, they must be receptive to not only signals from their natural environment but also to those from their social environment. Therefore, the human brain possesses a social cognition capable of processing, interpreting, and responding to various signals related to social interaction and relationships. Considering the prevalence of social dysfunction in neurological disorders, social cognition should now be recognized as a core area of function requiring clinical attention. To fulfill the desire to understand the motives behind the behaviors and words of the individuals one interacts with, humans utilize simulation and Theory of Mind mechanisms. In simulation technique, one puts themselves in the shoes of another person and uses themselves as their reference point. Theory of Mind, on the other hand, is the mental mechanism that a person uses every day to explain a word or attitude of another or to predict a behavior of another. One attributes independent mental states to themself and others and, accordingly, reaches certain opinions and judgments. Theory of Mind problems occur in a plenty of neurodevelopmental disorders. Although it is encountered in almost all neurological diseases, it is generally overlooked within the general picture. It can also lead to various communication problems, misunderstandings, and serious problems between neurotypical people in daily life. In this context, Theory of Mind training under the title of social cognitive skills should be included in the curriculum not only in special education and neurorehabilitation but also in formal education. [ABSTRACT FROM AUTHOR]

Recent advances in robotics technology and artificial intelligence (AI) have sparked increased interest in humanoid robots that resemble humans and social robots capable of interacting socially. Alongside this trend, a new field of robot research called human-robot interaction (HRI) is gaining prominence. The aim of this review paper is to introduce the fundamental concepts of HRI and social robots, examine their current applications in the medical field, and discuss the current and future prospects of HRI and social robots in spinal care. HRI is an interdisciplinary field where robotics, AI, social sciences, design, and various disciplines collaborate organically to develop robots that successfully interact with humans as the ultimate goal. While social robots are not yet widely deployed in clinical environments, ongoing HRI research encompasses various areas such as nursing and caregiving support, social and emotional assistance, rehabilitation and cognitive enhancement for the elderly, medical information provision and education, as well as patient monitoring and data collection. Although still in its early stages, research related to spinal care includes studies on robotic support for rehabilitation exercises, assistance in gait training, and questionnaire-based assessments for spinal pain. Future applications of social robots in spinal care will require diverse HRI research efforts and active involvement from spinal specialists. [ABSTRACT FROM AUTHOR]

In the midst of the rising issues of intolerance and radicalism occurring in various regions of Indonesia, Balun Village in Turi District, Lamongan Regency, stands out as one of the cities with a high tolerance index in East Java. This village is even known as the Pancasila Village due to the strong interfaith tolerance. The focus of this research is to examine the patterns of social interaction among different religious communities in building harmony and peaceful coexistence within the multicultural society of Balun Village, Lamongan Regency. It also aims to capture the portrait of religious moderation based on local wisdom in Balun Village to maintain interfaith harmony. The research uses qualitative fieldwork methods to clearly depict the social interactions between religious groups in fostering harmony at the research location. The approach used in this study is phenomenology to empirically understand how the residents of Balun Village, Lamongan Regency, perceive, express, and practice religious moderation based on local wisdom to maintain interfaith harmony. Data for this study were collected using two techniques: interviews and observations. Data analysis is conducted using the analytical methods of Miles, Huberman, and Saldana (2014), which include three steps: data condensation, data display, and conclusion drawing and verification. Social interactions between Muslims and non-Muslims in Balun Village, Lamongan Regency, are characterized by associative processes such as cooperation, accommodation, and acculturation. The empirical portrait of how the residents of Balun Village understand, express, and practice religious moderation based on local wisdom includes various activities such as wedding celebrations (kenduri), death rituals, communal work, arts performances, Nyadran rituals, Tunduan, and mutual cooperation in religious rituals and major religious holidays. [ABSTRACT FROM AUTHOR]

Relational event models (REMs) are the primary choice for the analysis of relational-event network data. However, the standard REM assumes static parameters, which hinders the modeling of time-varying dynamics. This assumption might be too restrictive in real-life scenarios, making a model that allows for time-varying parameters more valuable. We introduce a state-space extension of the relational event model as a way to tackle this problem. The model has three main attributes. First, it provides a statistical framework of the temporal change of the parameters. Second, it enables the forecasting of future parameter values (which can be utilized to simulate new networks that can account for temporal dynamics in out-of-sample predictions). Third, it requires smaller data structures to be loaded into computer memory compared to the standard REM; this makes the model easily scalable to large networks. We conduct empirical analyses on bike-sharing data, corporate communications, and interactions among socio-political actors to illustrate model usage and applicability. [ABSTRACT FROM AUTHOR]

The complexity of systems stems from the richness of the group interactions among their units. Classical networks exhibit identified limits in the study of complex systems, where links connect pairs of nodes, inability to comprehensively describe higher-order interactions in networks. Higher-order networks can enhance modeling capacities of group interaction networks and help understand and predict network dynamical behavior. This paper constructs a social hypernetwork with a group structure by analyzing a community overlapping structure and a network iterative relationship, and the overlapping relationship between communities is logically separated. Considering the different group behavior pattern and attention focus, we defined the group cognitive disparity, group credibility, group cohesion index, hyperedge strength to study the relationship between information dissemination and network evolution. This study shows that groups can alter the connected network through information propagation, and users in social networks tend to form highly connected groups or communities in information dissemination. Propagation networks with high clustering coefficients promote the fractal information dissemination, which in itself drives the fractal evolution of groups within the network. This study emphasizes the significant role of "key groups" with overlapping structures among communities in group network propagation. Real cases provide evidence for the clustering phenomenon and fractal evolution of networks. [ABSTRACT FROM AUTHOR]

The rise of digital social media has strengthened the coevolution of public opinions and social interactions that shape social structures and collective outcomes in increasingly complex ways. The existing literature often explores this interplay as a one-directional influence, focusing on how opinions determine social ties within adaptive networks. However, this perspective overlooks the intrinsic dynamics driving social interactions, which can significantly influence how opinions form and evolve. In this work, we address this gap, by introducing the co-evolving opinion and social dynamics using stochastic agent-based models. Agents' mobility in a social space is governed by both their social and opinion similarity with others. Similarly, the dynamics of opinion formation is driven by the opinions of agents in their social vicinity. We analyze the underlying social and opinion interaction networks and explore the mechanisms influencing the appearance of emerging phenomena, such as echo chambers and opinion consensus. To illustrate the model's potential for real-world analysis, we apply it to General Social Survey data on political identity and public opinion regarding governmental issues. Our findings highlight the model's strength in capturing the coevolution of social connections and individual opinions over time. [ABSTRACT FROM AUTHOR]