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In an influential paper, Fox & Thompson (1990) argue that the grammar of relative clauses in spoken American English is affected by interactive and cognitive factors pertaining to the communication situation. Existential sentences containing a relative clause as well as an overt locative expression figure prominently in their analysis. The present paper examines Fox & Thompson’s analysis of such sentences in the light of a wide range of data. It is shown that the generalizations they make on the basis of their limited corpus (25 tokens) rest on false premises. Their analysis fails to take account of some of the most salient properties inherent in existential sentences in all varieties of English; it also disregards relevant cross-linguistic data. An alternative analysis is offered.

Perception results from the interplay of sensory input and prior knowledge. Despite behavioral evidence that long-term priors powerfully shape perception, the neural mechanisms underlying these interactions remain poorly understood. We obtained direct cortical recordings in neurosurgical patients as they viewed ambiguous images that elicit constant perceptual switching. We observe top-down influences from the temporal to occipital cortex, during the preferred percept that is congruent with the long-term prior. By contrast, stronger feedforward drive is observed during the non-preferred percept, consistent with a prediction error signal. A computational model based on hierarchical predictive coding and attractor networks reproduces all key experimental findings. These results suggest a pattern of large-scale information flow change underlying long-term priors’ influence on perception and provide constraints on theories about long-term priors’ influence on perception., Priors learnt from lifetime experiences influence perception. The authors show that when perception is congruent with a long-term prior, there is increased top-down input in the ventral visual stream, whereas bottom-up input is enhanced when perception is incongruent with prior.

Although the correlation between general cognitive ability (g) and performance on speeded cognitive tasks is well-established, there is need for a better understanding of how successive stages of processing contribute to this relationship. Previous research suggests that g is primarily associated with the rapidity of decision-making rather than perceptual processing of stimuli; the implication is that g should statistically interact with a manipulation affecting the difficulty of the decision process, while simultaneously failing to interact with a perceptual manipulation. We applied Sternberg's method of additive factors to test this hypothesis in two reaction time tasks, each of which systematically manipulated the demands on perceptual acuity and decision-making. With a total of 773 participants, we found evidence of an interaction between a short-form measure of g and the decisional-but not perceptual-manipulations. This pattern was found in both number-comparison (Experiment 1) and tone-comparison (Experiment 2) tasks. Additionally, diffusion modeling of the Experiment 1 results revealed that the diffusion rate (v) is associated with g and affected by an informational attribute of the stimulus (numerical magnitude) but not a perceptual attribute (contrast); the nondecision time (Ter) is not associated with g and shows the opposite pattern of selective influence. Taken together, these findings add to the evidence for a theoretical framework partitioning reaction time into several processing stages, of which only the decision-making stage is associated with g. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

In the conditions of an intensive information flow and the expansion of the authors rights, there has been a change in the ways of working with scientific texts, in filling them with meaning. Working on text transformation, in whatever forms it may take place, is the most important activity for mastering the scientific language. Sketching (the method of visual notes) can be successfully used in teaching at a higher school, since it stimulates the cognitive activity of students from understanding the authors intention of the text to its transformation and giving personal meaning. Sketching is a convenient tool for the perception and processing of scientific information. These are polycode texts in which information is transmitted by verbal and non-verbal figurative and pictorial means. It is also a method for rendering the content. These are also techniques for working with texts that make it easier for students to work with complex information (facilitate the perception and understanding of their content). This paper gives recommendations on the use of sketching for students to study texts on the history and methodology of biology. Mastering the basics of in-depth understanding and creative reproduction of the text, their repeated playback provides the basis for the development of the teachers professionalism.

Low trust levels among project parties are generally believed to harm construction project performance, but the role of trust in the context of information flow and solving design quality problems (DQP) remains understudied. Whereas lean design management research highlights the importance of managing information flow, few studies have investigated the association between trust, information flow and DQP (or any combination thereof). This exploratory study investigates the association between trust and information flow in design projects and how these factors influence design quality. The paper presents a conceptual framework based on existing research on building design management and trust in a project context. The framework is elaborated on and validated using a single case study approach with multiple sites. The results indicate that even though the trust trend in the project is somewhat negatively connected to the overall amount of work and work in progress of DQP, increasing trust is not a prerequisite for solving DQP and that owners and contractors can have opposite opinions on the trust level. This study contributes to ongoing discussions about trust, information flow and design management and suggests that teams should focus on improving communication and collaboration to compensate for low trust levels.

This paper investigated the coherent functions of interrogative mood metaphors in an academic context based on Halliday' model of mood metaphor [1] and Zhu's theory of thematic progression (TP) pattern [2]. With a focus on the strategies of linking the themes and rhemes in the metaphorical clause to those of surrounding clauses, this paper identified three main modes of information flow patterns. In the mood metaphor (S) and the sentence before it (S-1), the information current is often progressed in a concentrated way since the metaphorical questions often serve as enforcements of its former sentence. Concentrated Progression is also often used in the S and the sentence after it (S+1) to answer the previous metaphorical questions, serving the purpose of appealing to authority. Besides, Constant Progression, as a simple liner pattern of message current, occurs in S and S+1 to enhance the reading comprehensibility when introducing a concept to readers or to highlight the key viewpoints as evaluating the proposition in S. This paper has pedagogical implications for academic reading and writing practices of native and non-native researchers.

Visual perception of actions is supported by a network of brain regions in the occipito-temporal, parietal, and premotor cortex in the primate brain, known as the Action Observation Network (AON). Although there is a growing body of research that characterizes the functional properties of each node of this network, the communication and direction of information flow between the nodes is unclear. According to the predictive coding account of action perception (Kilner, Friston, & Frith, 2007a; 2007b), this network is not a purely feedforward system but has backward connections through which prediction error signals are communicated between the regions of the AON. In the present study, we investigated the effective connectivity of the AON in an experimental setting where the human subjects' predictions about the observed agent were violated, using fMRI and Dynamical Causal Modeling (DCM). We specifically examined the influence of the lowest and highest nodes in the AON hierarchy, pSTS and ventral premotor cortex, respectively, on the middle node, inferior parietal cortex during prediction violation. Our DCM results suggest that the influence on the inferior parietal node is through a feedback connection from ventral premotor cortex during perception of actions that violate people's predictions.

How do group dynamics affect individuals within the group? How do individuals, in turn, affect group dynamics? As society comes together, individuals affect the group dynamics and vice versa. Social dynamics look at group dynamics, its effect on individuals, conformity, leadership, networks, and more. In the past two decades, the game theoretic Parrondo’s paradox has been used to model and explain the different aspects of social dynamics. Two losing games can be combined in a certain manner to give a winning outcome—this is known as Parrondo’s paradox. In this review, the connections between Parrondo’s paradox and social dynamics are discussed with emphasis on (i) cooperation and competition, (ii) resource redistribution and social welfare, and (iii) information flow and decision-making.

Much recent work has illuminated the growth, innovation, and prosperity of entire cities, but there is relatively less evidence concerning the growth and prosperity of individual neighborhoods. In this paper we show that diversity of amenities within a city neighborhood, computed from openly available points of interest on digital maps, accurately predicts human mobility (“flows”) between city neighborhoods and that these flows accurately predict neighborhood economic productivity. Additionally, the diversity of consumption behaviour or the diversity of flows together with geographic centrality and population density accurately predicts neighborhood economic growth, even after controlling for standard factors such as population, etc. We develop our models using geo-located purchase data from Istanbul, and then validate the relationships using openly available data from Beijing and several U.S. cities. Our results suggest that the diversity of goods and services within a city neighborhood is the largest single factor driving both human mobility and economic growth.

In animal societies, individuals may take on different roles to fulfil their own needs and the needs of their groups. Ant colonies display high levels of organisational complexity, with ants fulfilling different roles at different timescales (what is known as task allocation). Factors affecting task allocation can be at the individual level (e.g., physiology), or at the group level (e.g., the network of interactions). We focus on group level processes by exploring the relationship between interaction networks, task allocation and task switching using a previously published dataset (Mersch et al., 2013) tracking the behaviour of six Camponotus fellah colonies over 41 days. In our new analyses, our goal was to better explain the noisy process of task switching beyond simple age polyethism. First, we investigated the architecture of interaction networks using node (individual) level network measures and their relation to the individual’s task – foraging, cleaning or nursing – and whether or not the ant switched tasks. We then explored how noisy information propagation was among ants, as a function of the colony composition (how many ants carried out which tasks), through the information-theoretic metric of Effective Information. Our results show that interaction history was tied to task allocation: ants who switched to a task are more likely to have interacted with other ants carrying out that task. The degree to which interactions related to task allocation, as well as the noise in those interactions, depended on which groups of ants were interacting. Overall, we showed that colony cohesion was stable even as ant-level network measures varied more for ants when they switched functional groups; thus, ant colonies maintained a high level of information flow as determined by network analysis, and ant functional groups played different roles in maintaining colony cohesion through varied information flows.HighlightsWe analysed the interaction networks of six Camponotus fellah coloniesWe tested how centrality and information flow were tied to task switchingNode-level network metrics and the information theoretic measure of Effective Information explained differences among functional groupsInteractions were correlated with task switching, but the strength of the correlation differed across functional groups

Multivoxel pattern analysis (MVPA) has become a standard tool for decoding mental states from brain activity patterns. Recent studies have demonstrated that MVPA can be applied to decode activity patterns of a certain region from those of the other regions. By applying a similar region-to-region decoding technique, we examined whether the information represented in the visual areas can be explained by those represented in the other visual areas. We first predicted the brain activity patterns of an area on the visual pathway from the others, then subtracted the predicted patterns from their originals. Subsequently, the visual features were derived from these residuals. During the visual perception task, the elimination of the top-down signals enhanced the simple visual features represented in the early visual cortices. By contrast, the elimination of the bottom-up signals enhanced the complex visual features represented in the higher visual cortices. The directions of such modulation effects varied across visual perception/imagery tasks, indicating that the information flow across the visual cortices is dynamically altered, reflecting the contents of visual processing. These results demonstrated that the distillation approach is a useful tool to estimate the hidden content of information conveyed across brain regions.

Social networks are known for their decentralization and democracy. Each individual has a chance to participate and influence any discussion. Even with all the freedom, people’s behavior falls under patterns that are observed in numerous situations. In this paper, we propose a methodology that defines and searches for common communication patterns in topical networks on Twitter. We analyze clusters according to four traits: number of nodes the cluster has, their degree and betweenness centrality values, number of node types, and whether the cluster is open or closed. We find that cluster structures can be defined as (a) fixed, meaning that they are repeated across datasets/topics following uniform rules, or (b) variable if they follow an underlying rule regardless of their size. This approach allows us to classify 90% of all conversation clusters, with the number varying by topic. An increase in cluster size often results in difficulties finding topological shape rules, however, these types of clusters tend to exhibit rules regarding their node relationships in the form of centralization. Most individuals do not enter large-scale discussions on Twitter, meaning that the simplicity of communication clusters implies repetition. In general, power laws apply for the influencer connection distribution (degree centrality) even in topical networks.

Feelings of community increase information flow, cooperation, support, and a sense of commitment toward group goals. Many studies have explored the significance of sense of community and collaborat...

Sosyal medyanın gelişmesi ile birlikte geleneksel medyanın sınırlı etkileşimi, tek yönlü bilgi akışı sağlayan ve kullanıcı katılımına olanak tanımayan pasif yapısı yerini kullanıcıların yorumlarını, ürettikleri içerikleri ve kişisel görüş ve deneyimlerini paylaşmasına izin veren yeni medya araçlarına bırakmıştır. Sosyal medya uygulamaları birçok olumlu özelliği beraberinde getirmesine karşın birtakım sosyal sorunlara da neden olduğu söylenebilir. Sosyal medya platformları aracılığı ile tekrardan dolaşıma sokulan ırkçı, cinsiyetçi ve şiddet içerikli söylemlerin kullanıcılar tarafından sanal ve kamuya açık ortamlarda paylaşılması da günümüzde önemli bir sorun olarak karşımıza çıkmaktadır. İnsanlar sosyal medyada daha fazla etkileşim, beğeni ya da karşıt görüş alma amacıyla kendi görüş ve fikirlerini çok daha sert, direkt ve hedef göstererek belirtebilmektedirler. Nefret söylemi olarak kabul edilen bu tarz söylemler insan haklarına yönelik önemli bir tehdit unsuru olarak değerlendirilmektedir. Nefret söylemlerinin en çok kullanıldığı alanlardan birisi de futboldur. Kimi kullanıcılar sosyal medya ortamları vasıtasıyla şiddet dilini kullanarak futbolculara ya da futbolun diğer unsurlarına yönelik nefret içerikli söylemler üretmektedir. Nefret söylemleri yüzünden mağduriyet yaşayan futbolcuların başında ise Türk asıllı Alman futbolcu Mesut Özil gelmektedir. Mesut Özil’in 2018 yılında Rusya’da düzenlenen Dünya Kupası sonrasında kendisine yönelik ırkçı ifadeler yüzünden Milli Takımı bıraktığını açıklamasından sonra sosyal medyada konu ile ilgili kullanıcıların paylaştıkları içerikler söylem analizi yöntemi ile incelenmiştir. İnceleme sonucunda Özil’in nefret söylemi olarak adlandırılabilecek birçok ifadeye maruz kaldığı tespit edilmiştir. Bu çalışma sosyal medyada yer alan futbola ilişkin nefret söylemlerini ortaya çıkarmak ve bu konuda en azından futbol seyircisinde ve futbol medyasında farkındalık oluşturmak açısından önemlidir.

Este artigo investiga as funções linguísticas responsáveis pela organização textual do discurso. Mais especificamente, descreve o sistema semântico-discursivo de mensagem, o qual responde pelo gerenciamento da produção e acúmulo de significado no texto. Para tanto, explora a estrutura do discurso tendo como ponto de partida a relação entre esse e a gramática oracional que o realiza. Em seguida, descreve cada opção do sistema, bem como a forma como opera ao longo do fluxo textual, e assim assumindo valor nas relações que estabelece frente a outras opções. Para promover a descrição, utilizou-se o português brasileiro como língua de investigação. Um corpus com 100 mil tokens foi compilado com base na tipologia da língua no contexto de cultura. Os textos foram analisados segundo a manifestação estrutural, relações funcionais entre opções sistêmicas, e o significado gerado pela organização discursiva das mensagens. Ao final, o artigo mostra como as diferentes opções de mensagem pré-selecionam funções na gramática, fazendo com que cada mensagem seja contextualizada, incorporando-se ao texto de forma a dar algum direcionamento à fase a qual pertence. O artigo mostra ainda o potencial sistêmico pelo qual diferentes tipos de texto determinam opções distintas na gramática e semântica textuais This paper aims at describing the systemic organization of the discourse textual component. It focuses on the discourse semantic system of message – the system pre-selected by periodicity that is responsible for accumulating meaning in text. In order to do so, the paper takes Brazilian Portuguese as language under investigation. It explores Brazilian Portuguese’s discourse structure departing from its relation to clause grammar as well as patterns of discourse composing text. A corpus of a 100,000 tokens was compiled according to the typology of language in the context of culture. After identifying grammatical functions pre-selected by message, the paper describes different message structural patterns and offers the motivation for features as well as their agnating patterns and levels of delicacy. Results show how different choices in the system shape information flow and explains the relationship between text type and different configurations of textual grammar and discourse semantics.

Humans are fast and accurate when they recognize familiar faces. Previous neurophysiological studies have shown enhanced representations for the dichotomy of familiar vs. unfamiliar faces. As familiarity is a spectrum, however, any neural correlate should reflect graded representations for more vs. less familiar faces along the spectrum. By systematically varying familiarity across stimuli, we show a neural familiarity spectrum using electroencephalography. We then evaluated the spatiotemporal dynamics of familiar face recognition across the brain. Specifically, we developed a novel informational connectivity method to test whether peri-frontal brain areas contribute to familiar face recognition. Results showed that feed-forward flow dominates for the most familiar faces and top-down flow was only dominant when sensory evidence was insufficient to support face recognition. These results demonstrate that perceptual difficulty and the level of familiarity influence the neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition.

Human movement is essentially the process of moving one or more body parts to a specific location along a certain trajectory. A person observing the movement might be able to recognize it through the spatial pathway alone. Kendon (Kendon, 2004) holds the view that willingly or not, humans, when in co-presence, continuously inform one another about their intentions, interests, feelings and ideas by means of visible bodily action. Analysis of face-toface interaction has shown that bodily action can play a crucial role in the process of interaction and communication. Kendon states that expressive actions like greeting, threat and submission often play a central role in social interaction. In order to access the expressive content of movements theoretically, a notational system is needed. Rudolf Laban, (1879-1958) was a notable central European dance artist and theorist, whose work laid the foundations for Laban Movement Analysis (LMA). Used as a tool by dancers, athletes, physical and occupational therapists, it is one of the most widely used systems of human movement analysis. Robotics has already acknowledged the evidence that human movements could be an important cue for Human-Robot Interaction. Sato et al. (Sato et al., 1996), while defining the requirements for 'human symbiosis robotics' state that those robots should be able to use non-verbal media to communicate with humans and exchange information. As input modalities on a higher abstraction level they define channels on language, gesture and unconscious behavior. This skill could enable the robot to actively perceive human behavior, whether conscious and unconscious. Human intention could be understood, simply by observation, allowing the system to achieve a certain level of friendliness, hospitality and reliance. Fong, Nourbakhsh and Dautenhahn (Fong et al., 2003) state in their survey on 'socially interactive robots' that the design of sociable robots needs input from research concerning social learning and imitation, gesture and natural language communication, emotion and recognition of interaction patterns. Otero et al. suggest (Otero et al., 2006) that the interpretation of a person’s motion within its environment can enhance Human-Robot Interaction in several ways. They point out, that a recognized action can help the robot to plan its future tasks and goals, that the information flow during interaction can be extended and additional cues, like speech recognition, can be supported. Otero et al. state that body motion and context provide in many situations enough information to derive the person’s current activity.

The modeling of conversational context plays a vital role in emotion recognition from conversation (ERC). In this paper, we put forward a novel idea of encoding the utterances with a directed acyclic graph (DAG) to better model the intrinsic structure within a conversation, and design a directed acyclic neural network, namely DAG-ERC, to implement this idea. In an attempt to combine the strengths of conventional graph-based neural models and recurrence-based neural models, DAG-ERC provides a more intuitive way to model the information flow between long-distance conversation background and nearby context. Extensive experiments are conducted on four ERC benchmarks with state-of-the-art models employed as baselines for comparison. The empirical results demonstrate the superiority of this new model and confirm the motivation of the directed acyclic graph architecture for ERC., Accepted to ACL-IJCNLP 2021 main conference

Studying brain function is a challenging task. In the past, we could only study brain anatomical structures post-mortem, or infer brain functions from clinical data of patients with a brain injury. Nowadays technology, such as functional magnetic resonance imaging (fMRI), enable non-invasive brain activity observation. Several approaches have been proposed to interpret brain activity data. The brain connectivity model is a graphical tool that represents the interaction between brain regions, during certain states. It depicts how a brain region cause changes to other parts of the brain, which can be implied as information flow. This model can be used to help interpret how the brain works. There are several mathematical frameworks that can be used to infer the connectivity model from brain activity signals. Granger causality is one such approach and is one of the first that has been applied to brain activity data. However, due to the concept of the framework, such as the use of pairwise correlation, combined with the limitation of brain activity data such as low temporal resolution in case of fMRI signal, makes the interpretation of the connectivity difficult. We therefore propose the application of the Tigramite causal discovery framework on fMRI data. The Tigramite framework uses measures such as causal effect to analyze causal relations in the system. This enables the framework to identify both direct and indirect pathways or connectivities. In this paper, we applied the framework to the Human Connectome Project motor task-fMRI dataset. We then present the results and discuss how the framework improves interpretability of the connectivity model. We hope that this framework will help us understand more complex brain functions such as memory, consciousness, or the resting-state of the brain, in the future.

In this study, we report the investigations conducted on the mimetic behavior of a new humanoid robot called Alter3. Alter3 autonomously imitates the motions of a person in front of it and stores the motion sequences in its memory. Alter3 also uses a self-simulator to simulate its own motions before executing them and generates a self-image. If the visual perception (of a person's motion being imitated) and the imitating self-image differ significantly, Alter3 retrieves a motion sequence closer to the target motion from its memory and executes it. We investigate how this mimetic behavior develops interacting with human, by analyzing memory dynamics and information flow between Alter3 and a interacting person. One important observation from this study is that when Alter3 fails to imitate a person's motion, the person tend to imitate Alter3 instead. This tendency is quantified by the alternation of the direction of information flow. This spontaneous role-switching behavior between a human and Alter3 is a way to initiate personality formation (i.e., personogenesis) in Alter3.

Nowadays, open-domain dialogue models can generate acceptable responses according to the historical context based on the large-scale pre-trained language models. However, they generally concatenate the dialogue history directly as the model input to predict the response, which we named as the flat pattern and ignores the dynamic information flow across dialogue utterances. In this work, we propose the DialoFlow model, in which we introduce a dynamic flow mechanism to model the context flow, and design three training objectives to capture the information dynamics across dialogue utterances by addressing the semantic influence brought about by each utterance in large-scale pre-training. Experiments on the multi-reference Reddit Dataset and DailyDialog Dataset demonstrate that our DialoFlow significantly outperforms the DialoGPT on the dialogue generation task. Besides, we propose the Flow score, an effective automatic metric for evaluating interactive human-bot conversation quality based on the pre-trained DialoFlow, which presents high chatbot-level correlation ($r=0.9$) with human ratings among 11 chatbots. Code and pre-trained models will be public. \footnote{\url{https://github.com/ictnlp/DialoFlow}}, Comment: ACL2021 main conference (long paper)

In the modern world of high technologies and high information transmission rates, should be considered the features, possibilities, and quality of perception of this information by the student. In language teaching process, where the whole palette of various aspects is presented, this issue acquires as additional and extremely relevant. In the information flow, the recipient must be able to determine the main thing, recognize the main characteristics of the described phenomenon. In addition, the trainee must have the main skills of perception, memorization, rethinking and categorizing the information. This is important to take into focus four main types of channels of information broadcasting and perception. In this regard, the subject of this research are four types of representative systems: visual, audial, kinesthetic and discrete. As a method in the process of researching this topic, we have elected comparative historical, based on recent studies of these issues as a domestic linguistic school and European colleagues. The result of the analysis is a proposal developed by the author for the formation of the body of the lesson, taking into account the representative systems with the application in language student groups. The author concludes that it seems very important and effective to any teacher to accumulate and apply the knowledge about the type of information perception of students for their successful perception, memorization and playback of linguistic information.

This paper deals with the problem of identifying cultural replicators and providing a plausible replication model for culture. Depending on what kind of information is considered to be replicated, the different evolutionary models of cultural transmission are clustered into three main groups which are referred to as externalism, internalism and multi-substratism. From these, internalism is argued to be the most plausible position, but it fails in explaining how cultural information can be faithfully replicated in our species despite essentially depending on individual processes of intentional inference. It is concluded that no author seems to have fittingly adopted a categorization model stemmed from a usage-based perspective, and such a model would entail a feedback dynamic in category formation which could allow for an a posteriori purification of the input information flow. This way, categorization would partially equate the role of DNA in genetic transmission cycles., En este artículo se aborda la problemática de la identificación de los replicadores culturales y la elaboración de un modelo de replicación cultural verosímil. De acuerdo con el tipo de información que se supone objeto de replicación agrupamos los diversos modelos evolutivos de transmisión cultural en tres grandes categorías, que denominamos externalismo, internalismo y polisustratismo. De ellas, argumentamos por qué, a nuestro juicio, el internalismo es la opción más adecuada; si bien los modelos internalistas no suelen dar cuenta satisfactoriamente de cómo la información cultural puede haber alcanzado un cierto grado de fidelidad en la transmisión pese a depender de procesos individuales de inferencia intencional. Concluimos que ningún autor parece haber adoptado un modelo adecuado de categorización fundamentado en una perspectiva basada en el uso. Tal modelo implicaría una dinámica de retroalimentación en la formación de las categorías que podría permitir la depuración a posteriori del flujo de información entrante.

International ‘naming and shaming’ campaigns rely on domestic civil society organizations (CSOs) for information on local human rights conditions. To stop this flow of information, some governments restrict CSOs, for example by limiting their access to funding. Do such restrictions reduce international naming and shaming campaigns that rely on information from domestic CSOs? This article argues that on the one hand, restrictions may reduce CSOs’ ability and motives to monitor local abuses. On the other hand, these organizations may mobilize against restrictions and find new ways of delivering information on human rights violations to international publics. Using a cross-national dataset and in-depth evidence from Egypt, the study finds that low numbers of restrictions trigger shaming by international non-governmental organizations. Yet once governments impose multiple types of restrictions, it becomes harder for CSOs to adapt, resulting in fewer international shaming campaigns.

Neuronal oscillations route external and internal information across brain regions. In the olfactory system, the two central nodes—the olfactory bulb (OB) and the piriform cortex (PC)—communicate with each other via neural oscillations to shape the olfactory percept. Communication between these nodes have been well characterized in non-human animals but less is known about their role in the human olfactory system. Using a recently developed and validated EEG-based method to extract signals from the OB and PC sources, we show in healthy human participants that there is a bottom-up information flow from the OB to the PC in the beta and gamma frequency bands, while top-down information from the PC to the OB is facilitated by delta and theta oscillations. Importantly, we demonstrate that there was enough information to decipher odor identity above chance from the low gamma in the OB-PC oscillatory circuit as early as 100 ms after odor onset. These data further our understanding of the critical role of bidirectional information flow in human sensory systems to produce perception. However, future studies are needed to determine what specific odor information is extracted and communicated in the information exchange.

Honeybees can be directed to profitable food sources by following waggle dances performed by other bees. Followers can often choose between using this social information or relying on memories about food sources they have visited in the past, so-called private information. While the circumstances that favour the use of either social or private information have received considerable attention, still little is known about the neurophysiological basis of information use. We hypothesized that octopamine and dopamine, two biogenic amines with important functions in reward signalling and learning, affect dance use in honeybees. We orally administered octopamine and dopamine when bees collected food at artificial feeders and tested if this affected interest in dance information about a new food source. We predicted that octopamine reduces interest in dances and strengthens private information use via an increase in the perceived value of the previously exploited resource. Since dopamine has been shown to lower reward perception, we expected it to act in the opposite direction. Octopamine-treated foragers indeed followed 32% fewer dances than control bees and increased the use of private information. Conversely, dopamine-treated bees followed dances 15% longer than control bees, but surprisingly did not use social information more. Overall, our results suggest that biogenic amine signalling affects interactions among dancers and dance followers and, thus, information flow about high-quality food sources.

Humans are fast and accurate when they recognize familiar faces. Previous neurophysiological studies have shown enhanced representations for the dichotomy of familiar vs. unfamiliar faces. As familiarity is a spectrum, however, any neural correlate should reflect graded representations for more vs. less familiar faces along the spectrum. By systematically varying familiarity across stimuli, we show a neural familiarity spectrum using electroencephalography. We then evaluated the spatiotemporal dynamics of familiar face recognition across the brain. Specifically, we developed a novel informational connectivity method to test whether peri-frontal brain areas contribute to familiar face recognition. Results showed that feed-forward flow dominates for the most familiar faces and top-down flow was only dominant when sensory evidence was insufficient to support face recognition. These results demonstrate that perceptual difficulty and the level of familiarity influence the neural representation of familiar faces and the degree to which peri-frontal neural networks contribute to familiar face recognition.

Remembering is a reconstructive process, yet little is known about how the reconstruction of a memory unfolds in time in the human brain. Here, we used reaction times and EEG time-series decoding to test the hypothesis that the information flow is reversed when an event is reconstructed from memory, compared to when the same event is initially being perceived. Across three experiments, we found highly consistent evidence supporting such a reversed stream. When seeing an object, low-level perceptual features were discriminated faster behaviourally, and could be decoded from brain activity earlier, than high-level conceptual features. This pattern reversed during associative memory recall, with reaction times and brain activity patterns now indicating that conceptual information was reconstructed more rapidly than perceptual details. Our findings support a neurobiologically plausible model of human memory, suggesting that memory retrieval is a hierarchical, multi-layered process that prioritises semantically meaningful information over perceptual details., Little is known about how the reconstruction of a memory unfolds in time in the human brain. Here, the authors provide evidence that the process of reconstructing the memory of an object involves a reversal of the information flow involved in the actual perception of that object.

Using molecular profiles to predict the drug response is of practical importance in precision medicine and have been extensively studied. Due to the complexity of molecular information, the existing methods couldn't capture enough information and their prediction performances are not satisfying. In this study, we propose a method called DIMDRP (double iteration method for drug response prediction) which improves a lot in the prediction accuracy. DIMDRP integrates several important molecular information including miRNA expression, drug chemical structure, target interaction, drug-target interaction and cell line-drug response, and constructs a heterogeneous network. Then an improved information flow iteration algorithm is used to calculate association scores of cell line-drug responses, and we prioritize the cell lines for each query drug. The cross-validation experiments show that the average area under curve (AUC) of DIMDRP is as high as 0.8953, and two other measurement metrics are applied to assess the performance. When compared to other approaches, our method shows a significant advantage for all metrics. We also consider the specific tissue condition into our competition from a practical aspect. Last, a case is studied to predict novel cell line-drug responses, some of which can be evidenced by previous experiments.

Individuals use various strategies to cope with challenging emotions such as anxiety. Mindful acceptance involves broadening attentional scope and fully experiencing present moment sensory feelings (whether pleasant or unpleasant) without judgment or elaboration. In contrast, narrative-evaluation involves focusing on a narrow band of sensory experience and generating an elaborate narrative about the meaning and desirability of one’s emotional feelings. The current study examined brain network organization during these strategies using graph theoretic analyses. We used a naturalistic task paradigm in which participants reflected on an anxiety-provoking issue from their personal lives and adopted each strategy in different blocks. Compared to narrative-evaluation, mindful acceptance was associated with: (i) increased global network connectivity; (ii) greater integration of interoceptive regions (mid and posterior insula) into large-scale networks; (iii) reorganization of motivational circuits including a shift in the striatum’s network assignment from the default network to the salience network; and (iv) a shift from default network to frontoparietal control network (FPCN) regions as central hubs that coordinate information flow. Functional connectivity patterns within the left FPCN were associated with acceptance reports. Thus, broadening attentional scope during mindful acceptance is supported by a more globally interconnected neural landscape, as well as greater information flow through FPCN regions that underlie metacognitive awareness and cognitive control.

Textbooks are a central pedagogical resource for science teachers. As such, they have been a subject of enduring interest in science education research, with many questioning whether their quality has improved over the past decades. In this paper, we examined the prose quality of an expository text on coral reefs in seven successive editions of one popular environmental science textbook. Specifically, using tools from systemic functional linguistics, we analyzed two discursive aspects that impact the comprehensibility of the texts – how causation is construed and how information is structured. Our analyses reveal that the prose quality of the texts on coral reefs has improved, regressed, or remained the same. In the area of causation, cause–effect relationships are construed in increasingly implicit ways, with causes and effects consistently constructed as grammatical abstractions that bury human or social agencies. In the area of information flow, semantic leaps and semantic ambiguities are reduced across the sample texts analyzed, which places fewer text processing demands on the reader. Our study suggests that writing a perfectly considerate text is a tall task and that micro-linguistic analysis can illuminate the comprehension challenges that school textbooks present to students and inform efforts to improve students’ science literacy.

Psychological construction models of emotion state that emotions are variable concepts constructed by fundamental psychological processes, whereas according to basic emotion theory, emotions cannot be divided into more fundamental units and each basic emotion is represented by a unique and innate neural circuitry. In a previous study, we found evidence for the psychological construction account by showing that several brain regions were commonly activated when perceiving different emotions (i.e. a general emotion network). Moreover, this set of brain regions included areas associated with core affect, conceptualization and executive control, as predicted by psychological construction models. Here we investigate directed functional brain connectivity in the same dataset to address two questions: 1) is there a common pathway within the general emotion network for the perception of different emotions and 2) if so, does this common pathway contain information to distinguish between different emotions? We used generalized psychophysiological interactions and information flow indices to examine the connectivity within the general emotion network. The results revealed a general emotion pathway that connects neural nodes involved in core affect, conceptualization, language and executive control. Perception of different emotions could not be accurately classified based on the connectivity patterns from the nodes of the general emotion pathway. Successful classification was achieved when connections outside the general emotion pathway were included. We propose that the general emotion pathway functions as a common pathway within the general emotion network and is involved in shared basic psychological processes across emotions. However, additional connections within the general emotion network are required to classify different emotions, consistent with a constructionist account. ispartof: NeuroImage vol:172 pages:250-262 ispartof: location:United States status: published

The article is deals with the theoretical analysis of scientific literature in reference to using of clip chaoticness in order to actualize the absurdity of the content of information on the territory of cyberspace as the latest manipulative technology of goal-oriented influence on the individual and mass consciousness. Such concepts as clip chaoticness of cyberspace, logic of absurdity, absurdization, clip culture, clip thinking, conceptual thinking, etc. are revealed. The newest informational-communicative technologies, which can lead to fatal dangerous consequences for our society, are described. It is stated that the clip chaoticness of cyberspace as a means of absurdization and the manipulative technology of social and psychological influence in the information space primarily focus on the partial or complete "disbalance" of the harmonious correlation between the conceptual and the clip levels of thinking. This, by turns, tells that the information flows of various political, social, economic, religious, and spiritual institutions are fighting for the corresponding symbolic capital, the right and the opportunity to transform it relative to the main goals of their social projects, using the latest technologies of the modern scientific world to create the clip chaoticness in the areas of cyberspace. Creating chaos using absurdism testifies that the growth of clip culture in the information space can lead to uncontrollability of informational-communicative flows (absurdity grows into the process of absurdization, clip chaoticness – in clips chaotization). This is explained by the fact that information flows at the present stage already can work with different intensity of the submission of information, and the "necessary" intensity is difficult to maintain in a competitive conditions (depending on the intensity and saturation of the information flow the influence on the society may change), especially there is no guarantee that one or the other flow will not amenable to information attack. Only this already indicates that chaoticness of clip in the areas of the informational space is difficult to control for today. And in fact it becomes impossible to control artificially created chaoticness in the information flow, for example, on such two parallels as clip and explanation of absurd actions by creation of controlled or organized chaos. In final result, it will not be the clip chaoticness, but the clip chaotization (a constant increasing and growth of chaos), which in fact at all is already impossible to control and constrain at the present stage of formation of technological progress. Relevant existing institutions of information security will not be able to stop widespread chaoticness, that’s why the creation of algorithms for timely prediction of such catastrophic flows at the stage of their formation is the urgent need. It is substantiated that technological progress has led to a change in the informational-communicative means and to the formation of the latest varieties of human intellectual activity. It is concluded that the evolutionary period of change in human consciousness is in full swing, the personality has not yet reached the level of development, in order as a result of the chaoticness of informational-communicative flows (marathons) be able to transform her cognitive-strategic potential and have time to engage in effective information processing for a short period of time at an adequate level. And this, at the same time, provides the opportunity to apply manipulative technologies of the influence on individual and social consciousness. Key words: clip chaoticness of cyberspace, logic of absurd, reduction to absurdity, clip culture, clip thinking, conceptual thinking.

Summary Visual attention allows observers to change the influence of different parts of a visual scene on their behavior, suggesting that information can be flexibly shared between visual cortex and neurons involved in decision making. We investigated the neural substrate of flexible information routing by analyzing the activity of populations of visual neurons in the medial temporal area (MT) and oculo-motor neurons in the superior colliculus (SC) while rhesus monkeys switched spatial attention. We demonstrated that attention increases the efficacy of visuomotor communication: trial-to-trial variability in SC population activity could be better predicted by the activity of the MT population (and vice versa) when attention was directed toward their joint receptive fields. Surprisingly, this improvement in prediction was not explained by changes in the dimensionality of the shared subspace or in the magnitude of local or shared pairwise noise correlations. These results lay a foundation for future theoretical and experimental studies into how visual attention can flexibly change information flow between sensory and decision neurons.

Comprehending speech in our native language is an impressionistically effortless and routine task. We often give little consideration to its complexity. Only in particularly challenging situations (e.g., in noisy environments, when hearing significantly accented speech) do some of these intricacies become apparent. Higher-order knowledge constrains sensory perception and has been demonstrated to play a crucial role in other domains of human language processing. Moreover, incorporating measures of brain activity during online speech comprehension has just begun to highlight the extent to which top-down information flow and predictive processes are integral to sensory perception. This review argues that our phonological system, at a relatively abstract level, is one such source of higher-order knowledge. In particular, I discuss the extent to which phonological distinctive features play a role in perception and predictive processing during speech comprehension with reference to behavioral and neurophysiological data. This line of research represents a tractable linking of linguistic theory with models of perception and speech comprehension in the brain.

The increasing requirements regarding quality assurance and processes traceability require the implementation of continuous improvement procedures, with a view of maintaining the company’s levels of competitiveness and satisfaction for its customers in terms of quality. The optimization of information flows and manufacturing processes are, in general, extremely important factors in any company’s life. It is therefore important that companies quickly self-adapt to this kind of reality and adopt policies of product innovation and standardization of its production processes, in order to allow rapid adaptation to the constant market changes. The present work aims to identify problems and finding solutions through a combination of PDCA (Plan-Do-Check-Act) cycle, 5S (Seiri, Seiton, Seiso, Seiketsu, Shitzuke) and 5W2H (5 Whys + 2 Hows) tools those can be implemented into a program of continuous improvement, with a view of standardizing of processes, ensuring real profits in products typically with critical added-value. The combination of tools was implemented and the results have been checked, showing a significant impact in the Weaving production process, with gains of 10% in the useful available time by the operator.

The article raises the problem of the English-language media discourse which in its interaction with the basic psychological mechanisms of human consciousness (goal-setting, attitude and reflection) at the age of digitalization has created a new form of media discourse environment providing communication and influence on both native English speakers and non-native ones. The theoretical, as well as statistical and content analyses conducted in the research, allowed identifying two media blocks (two types of media discourses) in the English-speaking media world that have different goal-setting mechanisms, attitudes and reflection levels. The findings of the study based on the example of a political theme zone frequently circulated in the English-language media discourse demonstrated how the interaction and mutual influence between the psychological mechanisms and the media discourse are changed and depend on whether the information flow is generated by the institutional English-language media discourse or it is presented and promoted by individual media actors.

This chapter assumes that both religion and the media are connected by their truth-seeking function. While the religious function seeks to integrate human beings into a transcendent world harmonious with nature, the media equivalent seeks to promote self-governance for peace. Drawing insights from contemporary African experiences, this chapter identifies the problem of intolerance, and the question of information flow about Africa and its people, as respective problems of religion and the media. It argues that these twin challenges of contemporary African life are so pervasive that they demand socio-ethical analysis. Through a purely existentialist reflection, it evaluates the socio-ethical issues arising from the religion and media challenges.

Classical accounts of child language learning invoke memory limits as a pressure to discover sparse, language-like representations of speech, while more recent proposals stress the importance of prediction for language learning. In this study, we propose a broad-coverage unsupervised neural network model to test memory and prediction as sources of signal by which children might acquire language directly from the perceptual stream. Our model embodies several likely properties of real-time human cognition: it is strictly incremental, it encodes speech into hierarchically organized labeled segments, it allows interactive top-down and bottom-up information flow, it attempts to model its own sequence of latent representations, and its objective function only recruits local signals that are plausibly supported by human working memory capacity. We show that much phonemic structure is learnable from unlabeled speech on the basis of these local signals. We further show that remembering the past and predicting the future both contribute to the linguistic content of acquired representations, and that these contributions are at least partially complementary.

The most critical decisions usually involve several decision makers with different roles and opportunities to commit key resources. Several group decision-making (GDM) approaches can support the identification of a joint or compromise decision in less conflicting settings, where there is a group of subjects (e.g’, partners) who pursue a common overall objective. However, considering the uncertainty in future events and complexity of modern-day systems, decision processes do not always produce beneficial results or give the participants a positive perception of their role in the process. Group decision-making should then take into consideration some aspects that might insure future resilience and sustainability, particularly the achievement of the objectives in view of future risks and the transparency and participation that are needed to limit problems in the implementation phase of the decision. The literature survey presented in this study identified a research gap regarding GDM. Differently from traditional GDM, which was first discussed in the early 1980s and whose body of knowledge is pretty defined, resilient and sustainable GDM (R&S GDM) is fairly new. The main objective of this study is then identifying the main attributes for supporting sustainable and resilient group decisions. To this aim, a preliminary focused systematic review was conducted to study the existing group decision-making methods in the literature and how the concepts of sustainability and resilience have been employed. After defining the search keywords and exclusion criteria for the individuation of the articles, the first screening process was carried out and the most relevant articles were selected. The last steps of the systematic review were the classification of the articles and the full paper examination to extract the main factors of R&S GDM. Seven attributes were listed as the key factors of R&S GDM. In light of those factors, a group decision process concerning an injection moulding line in Tajikistan was investigated. The case study highlighted that over self-confidence, information flow and transparency were the main reasons for faulty decisions, thus suggesting that information system and information fluidity play an important role in R&S GDM. Finally, the most important managerial implications of R&S GDM are reported.

Status hierarchies are perhaps the single most important form of social structure within groups, ubiquitous and affecting groups’ information flow, decision-making, and performance as well as the behavior and outcomes of individual members. The extent to which individuals are able to accurately perceive and navigate their groups’ status hierarchies may thus be a critical determinant of their success. Research to date, however, has not yet fully examined the role of individuals’ perceptions of status hierarchies. We introduce the concept of perceived status hierarchies, or individuals’ mental representations of their groups’ status hierarchies. Across four field studies, involving students in university cohorts and working adults, we find substantial variance in individuals’ perceived status hierarchies, and that individuals with more accurate status perceptions exhibit higher performance. Analyses of individuals’ networking behavior reveals that individuals with more accurate perceived status hierarchies seek out contact with higher status others on average, which mediates the positive association between accuracy and performance. This work makes important contributions by extending existing theories of status, connecting the literatures on status and social networks, and providing a thorough investigation into the consequences of accurate perceptions of social structure for individuals. (PsycInfo Database Record (c) 2020 APA, all rights reserved)

How to generate relevant and informative response is one of the core topics in response generation area. Following the task formulation of neural machine translation, previous works mainly consider response generation task as a mapping from a source sentence to a target sentence. However, the dialogue model tends to generate safe, commonplace responses (e.g., I don't know) regardless of the input, when learning to maximize the likelihood of response for the given message in an almost loss-less manner just like MT. Different from existing works, we propose a Global-Local Selective Encoding model (GLSE) to extend the seq2seq framework to generate more relevant and informative responses. Specifically, two types of selective gate network are introduced in this work: (i) A local selective word-sentence gate is added after encoding phase of Seq2Seq learning framework, which learns to tailor the original message information and generates a selected input representation. (ii) A global selective bidirectional-context gate is set to control the bidirectional information flow from a BiGRU based encoder to decoder. Empirical studies indicate the advantage of our model over several classical and strong baselines.

Alongside its many advantages, the Internet presents a variety of challenges and risks to adolescents. From a perspective focusing on information flow processes, this study distinguishes between risks resulting from _exposure to information_, i.e. exposure of adolescents to inappropriate content: Harmful, sexual or violent, and risks resulting from _exposure of information_, i.e. disclosure of personal information online, privacy harms inflicted by the user or others, misuse of personal information which can result in identity theft, physical and sexual assault. The study examines gender differences in perceptions regarding adolescents’ online uses, habits and risks, and whether these lead to differences in emphasis of educational messages delivered by parents and teachers to adolescents. Based on a mixed-method study combining survey conducted among 513 adolescents and 50 semi-structured interviews with educators and adolescents, the findings illustrate how a common perception that girls share more personal information online and are (consequently) more vulnerable to online predators leads to more emphasis given on implications of personal information disclosure in messages delivered to girls. On the other hand, boys are considered naughty and nosy, searching for “forbidden”, mainly sexual, content, and emphasis is given on limiting and monitoring their searches and video consumption. Apparently, although parents, teachers and adolescents proclaim to be aware of the similar risks to boys and girls online, there is a message interwoven in internet safety education discourse: Girls are to be aware of others looking to harm them, and boys are to be aware of themselves, their curiosity and evil inclination.

International audience; This paper proposes a new collaborative and inclusive model for Knowledge Organization Systems (KOS) for sustaining cultural heritage and language diversity. It is based on contributions of end-users as well as scientific and scholarly communities from across borders, languages, nations, continents, and disciplines. It consists in collecting knowledge about all worldwide translations of one original work and sharing that data through a digital and interactive global knowledge map. Collected translations are processed in order to build multilingual parallel corpora for a large number of under-resourced languages as well as to highlight the transnational circulation of knowledge. Building such corpora is vital in preserving and expanding linguistic and traditional diversity. Our first experiment was conducted on the world-famous and well-traveled American novel Adventures of Huckleberry Finn by the American author Mark Twain. This paper reports on 10 parallel corpora that are now sentence-aligned pairs of English with Basque (an European under-resourced language), Bulgarian, Dutch, Finnish, German, Hungarian, Polish, Portuguese, Russian, and Ukrainian, processed out of 30 collected translations.

Visual perception of actions is supported by a network of brain regions in the occipito-temporal, parietal, and premotor cortex in the primate brain, known as the Action Observation Network (AON). Although there is a growing body of research that characterizes the functional properties of each node of this network, the communication and direction of information flow between the nodes is unclear. According to the predictive coding account of action perception, this network is not a purely feedforward system but has feedback connections through which prediction error signals are communicated between the regions of the AON. In the present study, we investigated the effective connectivity of the AON in an experimental setting where the human subjects’ predictions about the observed agent were violated, using fMRI and Dynamical Causal Modeling (DCM). We specifically examined the influence of the lowest and highest nodes in the AON hierarchy, pSTS and ventral premotor cortex, respectively, on the middle node, inferior parietal cortex during prediction violation. Our DCM results suggest that the influence on the inferior parietal node is through a feedback connection from ventral premotor cortex during perception of actions that violate people’s predictions.

The brain is the most important organ of the human body, and the conversations between the brain and an apparatus can not only reveal a normally functioning or a dysfunctional brain but also can modulate the brain. Here, the apparatus may be a nonbiological instrument, such as a computer, and the consequent brain–computer interface is now a very popular research area with various applications. The apparatus may also be a biological organ or system, such as the gut and muscle, and their efficient conversations with the brain are vital for a healthy life. Are there any common bases that bind these different scenarios? Here, we propose a new comprehensive cross area: Bacomics, which comes from brain–apparatus conversations (BAC) + omics. We take Bacomics to cover at least three situations: (1) The brain is normal, but the conversation channel is disabled, as in amyotrophic lateral sclerosis. The task is to reconstruct or open up new channels to reactivate the brain function. (2) The brain is in disorder, such as in Parkinson’s disease, and the work is to utilize existing or open up new channels to intervene, repair and modulate the brain by medications or stimulation. (3) Both the brain and channels are in order, and the goal is to enhance coordinated development between the brain and apparatus. In this paper, we elaborate the connotation of BAC into three aspects according to the information flow: the issue of output to the outside (BAC-1), the issue of input to the brain (BAC-2) and the issue of unity of brain and apparatus (BAC-3). More importantly, there are no less than five principles that may be taken as the cornerstones of Bacomics, such as feedforward and feedback control, brain plasticity, harmony, the unity of opposites and systems principles. Clearly, Bacomics integrates these seemingly disparate domains, but more importantly, opens a much wider door for the research and development of the brain, and the principles further provide the general framework in which to realize or optimize these various conversations.

Individuals increasingly rely on the Internet, and social media in particular, for health-related information. A recent survey reports that 80% of Internet users search for health information online. In the present study, we employ Twitter data to understand content characteristics and the patterns of content flow of the conversations about the HPV vaccine debate. Approaching the HPV vaccine conversations on Twitter as a social network, we can identify key self-formed subgroups-clusters of users who create "siloes" of interactions and information flow. Combining network analysis, computer-aided content analysis, and human-coded content analysis, we explored the communication dynamics within the groups in terms of group members' affective and cognitive characteristics. Our findings show that positive emotion is positively correlated with cluster density, an indicator of strong ties and rapid information flow. In the case of negative emotion, we found that anger is a significant negative predictor for graph density. We also found a correlation between certainty and tentativeness; both at cluster as well as at tweet level, suggesting that clusters bring together people who are sure about the HPV vaccine and people who are exploring for answers.

The formation of ethnic identity factors in childhood are discussed. The lower age limit and the forms of the first manifestations of the ethnic children self-consciousness are established. Theoretical foundations are presented. Methodological tools using in an empirical study of the ethnic identity of preschoolers and primary school age children, the forms of its manifestation and the psychological factors of its development are presented. The structure of ethnic identity is determined in the early stages of its manifestation and the relationship with the intellectual, emotional and social maturation of the child. It has been empirically established that first submissions on an own ethnic group and on oneself as its representative are simplified and significantly related to the level of emotional, intellectual and social maturation of a child. It is shown that these structures in the child’s psyche become information filters from the external environment and provide the formation of an image of himself and his group. The higher the level of their maturation, the more diverse complex of typical features, which a child is capable of reflexing, the richer and more complex understanding of himself and his ethnic group. It is shown that at this stage of age development there is an uncritical perception of their ethnic identity due to imitation and the desire for similarity with their loved ones. It has been established that among the diverse information flow language and national clothes make the greatest contribution to the image formation of their ethnic culture at this age stage.

Conversation has been a primary means for the exchange of information since ancient times. Understanding patterns of information flow in conversations is a critical step in assessing and improving communication quality. In this paper, we describe COnversational DYnamics Model (CODYM) analysis, a novel approach for studying patterns of information flow in conversations. CODYMs are Markov Models that capture sequential dependencies in the lengths of speaker turns. The proposed method is automated and scalable, and preserves the privacy of the conversational participants. The primary function of CODYM analysis is to quantify and visualize patterns of information flow, concisely summarized over sequential turns from one or more conversations. Our approach is general and complements existing methods, providing a new tool for use in the analysis of any type of conversation. As an important first application, we demonstrate the model on transcribed conversations between palliative care clinicians and seriously ill patients. These conversations are dynamic and complex, taking place amidst heavy emotions, and include difficult topics such as end-of-life preferences and patient values. We perform a versatile set of CODYM analyses that (a) establish the validity of the model by confirming known patterns of conversational turn-taking and word usage, (b) identify normative patterns of information flow in serious illness conversations, and (c) show how these patterns vary across narrative time and differ under expressions of anger, fear and sadness. Potential applications of CODYMs range from assessment and training of effective healthcare communication to comparing conversational dynamics across language and culture, with the prospect of identifying universal similarities and unique "fingerprints" of information flow., Comment: 34 pages, 20 figures, submitted to PLOS One (in review)

Today’s young generation prefers searching for information over the Internet. Whatever information is easily obtained quickly on smartphones through the web and or social media such as Instagram or YouTube. Search for beauty information is done because of curiosity or find the beauty products they need. Looking for information on beauty, YouTube is a form of video impression to be an easier choice than to be able to surf the web first. The aim of the study wanted to know what kind of video was used by the young generation in search of information about beauty and how the adolescent’s reaction was in seeing YouTube’s beauty video views. The method of this study is qualitative research. This study conducted a beauty video view analysis on YouTube and in strengthening the data was conducted interviews. The results showed that YouTuber can influence the audience to see its channel. The beauty of animation video has not been able to give more reliable results in watching the impression.