Analysis Of Interaction Patterns Research Articles (Page 4)

Therapeutic interaction has been considered one of the main factors of change in psychotherapy, and its investigation is called process research. Audio and video recording sessions are used to code behaviors which, subsequently, permit the analysis of interaction patterns. The objectives of the study were the presentation of part of a coding system called “Multidimensional System for Categorization of Behaviors in Therapeutic Interaction” and the evaluation of agreement between observers in its use. From a systematic assessment of the literature regarding the classification of vocal verbal behavior, it was found that the existing category systems were not satisfactory for the study of behavior analytic therapy, thus requiring the construction of a new system. A System for Coding Verbal Therapist Behavior was developed containing 16 categories, nine of vocal verbal behavior, three for non-vocal verbal behavior and four residual categories. A standardized training for observers was also developed. Its application to one participant produced satisfactory Kappa indexes of agreement ranging from 0.67 to 0.84. The implications of using the system for process research in behavior analytic therapy and in other therapeutic modalities in its different stages are discussed as well as the possibility of using the instrument and its training software for teaching therapeutic skills.

The Gaussian-based 3D-QSAR studies for 58 selective COX-2 (cyclooxygenase-2) inhibitors belonging to benzopyran chemical class were performed. Partial least squares analysis produced statistically significant model with (R training 2 =0.866) and predictability (Q training 2 =0.66, Q test 2 =0.846). The 3D-QSAR model includes steric, electrostatic, hydrophobic, and hydrogen bond acceptor field indicators, whereas the potential field contributions indicate that the steric and hydrophobic features of the molecules play an important role in governing their biological activity. A molecular docking simulation and protein-ligand interaction pattern analysis reveal the importance of Tyr-361 and Ser-516 of the COX-2 active site for X-ray crystal structures and this class of molecules. Thus the combined approach of ligand-based and structure-based models provided an improved understanding in the interaction between benzopyran chemical class and COX-2 inhibition, which will guide the future identification of more potent anti-inflammatory drugs.

This study aims to investigate the interaction patterns between the teacher and students or among students themselves in a Korean elementary English classroom by analysing classroom talk and by focusing on the types of the teacher’s questions and feedback as well as the use of L1 and L2. This analysis is used to determine the influence of such interaction on the students’ communicative skills in English. A female teacher in Gyeonggi province and a 6th-grade class participated in the data collection. This study included data from video or audio recordings, interviews, field notes, self-assessments, and portfolios. The transcribed data were analysed using Tsui’s (1994) framework and Verplaetse’s (1995, 2000) coding system. The results of this analysis indicated that the interaction patterns varied between participants into three groups: teacher-initiated talk (e.g., T-S talk) vs students-initiated talk (e.g., S-T talk & S-S talk). At the beginning stage of lesson, the teacher-initiated talk made up the majority of talk in English, and facilitated the students’ involvement in classroom learning including their language use. In the S-S talk, the students were involved in interaction which occurred naturally without the teacher’s control.

Evolution of drug-resistant Mycobacterium strains threatens the TB treatment and control programs globally. Rifampicin (RIF) is an important first line antitubercular drug. Resistance to Rifampicin is caused mainly by mutations in its target RNA polymerase beta subunit protein (RpoB). RpoB contains a Rifampicin resistance determining region (RRDR) and has several potent sites for mutations. In this study, we have investigated mutations of a single site (H451) to eight different amino acids, involved in RIF resistance. Long-term molecular dynamics simulations were performed on wild type (WT) and mutant protein structures and various structural analysis were carried out to elucidate the dynamic behavior of WT and mutant forms. Essential dynamics uncovered the difference in conformational flexibility and collective modes of motions between WT and mutants. MMPBSA calculations and interaction pattern analysis revealed the binding site relocation in some mutants. This study presents an exhaustive analysis of RIF binding to the WT and mutant RpoB and clearly highlights structural mechanism for differences in stable binding of Rifampicin with WT than the mutant targets. J. Cell. Biochem. 118: 4594-4606, 2017. © 2017 Wiley Periodicals, Inc.

Target structure-guided virtual screening (VS) is a versatile, powerful, and inexpensive alternative to experimental high-throughput screening (HTS). To discover potent CYP1A1 enzyme inhibitors for cancer chemoprevention, a commercial library of 50 000 small molecules was utilized for VS guided by both ligand and structure-based strategies. For experimental validation, 300 ligands were proposed based on combined analysis of fitness scores from ligand based e-pharmacophore screening and docking score, prime MMGB/SA binding affinity and interaction pattern analysis from structure-based VS. These 300 compounds were screened, at 10 μM concentration, for in vitro inhibition of CYP1A1-Sacchrosomes (yeast-derived microsomal enzyme) in the ethoxyresorufin-O-de-ethylase assay. Thirty-two compounds displayed >50% inhibition of CYP1A1 enzyme activity at 10 μM. 2-Phenylimidazo-[1,2-a]quinoline (5121780, 119) was found to be the most potent with 97% inhibition. It also inhibited ∼95% activity of CYP1B1 and CYP1A2, the other two CYP1 enzymes. The compound 5121780 (119) showed high selectivity toward inhibition of CYP1 enzymes with respect to CYP2 and CYP3 enzymes (i.e., there was no detectable inhibition of CYP2D6/CYP2C9/CYP2C19 and CYP3A4 at 10 μM). It was further investigated in live CYP-expressing human cell system, which confirmed that compound 5121780 (119) potently inhibited CYP1A1, CYP1A2, CYP1B1 enzymes with IC50 values of 269, 30, and 56 nM, respectively. Like in Sacchrosomes, inhibition of CYP2D6/CYP2C9/CYP2C19 and CYP3A4 enzymes, expressed within live human cells, could hardly be detected at 10 μM. The compound 119 rescued CYP1A1 overexpressing HEK293 cells from CYP1A1 mediated benzo[a]pyrene (B[a]P) toxicity and also overcame cisplatin resistance in CYP1B1 overexpressing HEK293 cells. Molecular dynamics simulations of 5121780 (119) with CYP1 enzymes was performed to understand the interaction pattern to CYP isoforms. Results indicate that VS can successfully be used to identify promising CYP1A1 inhibitors, which may have potential in the development of novel cancer chemo-preventive agents.

Protein-ligand interactions are the fundamental basis for molecular design in pharmaceutical research, biocatalysis, and agrochemical development. Especially hydrogen bonds are known to have special geometric requirements and therefore deserve a detailed analysis. In modeling approaches a more general description of hydrogen bond geometries, using distance and directionality, is applied. A first study of their geometries was performed based on 15 protein structures in 1982. Currently there are about 95 000 protein-ligand structures available in the PDB, providing a solid foundation for a new large-scale statistical analysis. Here, we report a comprehensive investigation of geometric and functional properties of hydrogen bonds. Out of 22 defined functional groups, eight are fully in accordance with theoretical predictions while 14 show variations from expected values. On the basis of these results, we derived interaction geometries to improve current computational models. It is expected that these observations will be useful in designing new chemical structures for biological applications.

The High Quality Communication intervention aims to stimulate interpersonal communication between individuals with congenital deaf-blindness (CDB) and their social partners. Found effective in multiple-case experiments, the intervention is based on Trevarthen's theory of inter-subjective development (Bråten & Trevarthen, 2007), which describes children's innate and developing ability to share subjective states in interpersonal communication and social partners' mediating role in this development. One implication of this theory is that social partners can support the emergence of higher-complexity communication behaviors in individuals who are still developing these behaviors. To test this proposition, communication patterns between individuals with CDB and their parents, teachers, and professional caregivers were analyzed. Analysis of two-event sequences of communicative behaviors showed a highly significant correspondence between the behavior of the social partner and the subsequent behavior of the individual with CDB, confirming that social partners can scaffold higher-complexity communication within interpersonal communication.

This article examines with whom political journalists interact on Twitter and what information they share. These relations are explored by combining a content analysis and a network analysis of interaction patterns. The activities published on journalists’ personal accounts are studied. Prior research has shown that elite journalists, in particular, mainly seek to remain gatekeepers and tend to normalize emerging communication spaces. Only one-quarter of the parliamentary correspondents in the German Federal Press Conference had an individual Twitter profile as of February 2014. The content analysis of all tweets published during a week in March 2014 (N = 2210) reveals that German political journalists clearly normalize Twitter to fit existing practices: the journalists mostly tweeted about publicly relevant communication and reported in an information-oriented style. Transparency was limited on their topics of interest, and they did not provide direct opportunities for the audience to become more active in the news-creation process. The network analysis shows that the correspondents especially incorporated politicians into their regular circle of contacts. Nevertheless, the interaction networks were clearly dominated by exchanges between journalists. In this way, journalists’ tweets allow us to observe expert talks rather than encouraging users to participate in a discussion.

Abstract Connectivist learning is interaction‐centered learning. A framework describing interaction and cognitive engagement in connectivist learning was constructed using logical reasoning techniques. The framework and analysis was designed to help researchers and learning designers understand and adapt the characteristics and principles of interaction in connectivist learning contexts. In this study empirical evidence to support and further develop this framework is presented. This study analyzed 6 weeks of data harvested from the daily newsletter, Twitter, and a Facebook group in a well‐known cMOOC led by George Siemens and Stephen Downes. These text transcripts were analyzed using a deductive approach of qualitative content analysis. This study revealed the main activity patterns of participants as they engage in four levels of interaction (operation interaction, wayfinding interaction, sensemaking interaction, and innovation interaction) during the MOOC. Generally the framework serves as a conceptual model to understand and to analyze the interaction in this cMOOC, although some implied interaction is hard to recognize and categorize. The relationship of the four levels of interaction and the role of each element in the framework were explored with the intent of offering the framework as a conceptual and analytic tool to guide both researchers and practitioners in designing and studying connectivist learning.

This article examines how Members of the German Bundestag (MdBs) used Twitter in the context of the country’s 2013 federal elections. In particular, we explore the dynamics in the MdBs’ use of Twitter during different periods of the electoral term: How do the tweeting habits of MdBs differ by party before and during the election campaign in (a) public versus personal communication and (b) campaign versus policy messages? How are the selection of interaction partners, centralization on leading actors, and reciprocity of the MdBs’ Twitter networks affected by election campaigning? We address these questions by conducting a content analysis combined with a network analysis of interaction patterns. The comparative application of both methods explains the differences of MdBs’ networks. The comparison clearly exhibits election campaign-driven changes related to the amount of activity and the character of tweeted messages. During the campaign period, MdBs’ tweets clearly discussed specific policies less than before. Tweeting about one’s personal life occurred also less frequently in the final campaign stage. Instead, the MdBs mainly complement other forms of election campaigning through a vivid metacommunication on campaign developments. Network relations reflect these variations and were less often reciprocated in proximity to the election and showed a higher degree of group homophily. We also found a substantial representation of print and broadcast media actors in the examined @reply networks. It is likely that these interactions and conversations with journalists are part of an MdB’s individual performance of “news management.”

Abstract This paper is based on the analysis of a focus group interview of a moderator and a group of undergraduate students on the topic of self-regulation of learning. The purpose of the investigation was to identify interaction patterns that appeared in the talk of participants and the moderator. In the stream of communication two rudimentary interaction patterns were recognized. The first pattern was named the Catalogue. It consists of a sequence of turns of participants who respond to a request of the moderator and who provide their answers, one by one, without reacting on the content of the previous partner(s) talk. The other interaction pattern was called the Domino. In this pattern participants respond to each other. The Catalogue pattern prevailed in the interview. Alongside with identification of patterns of interaction the study demonstrated the functions of the common ground and its accomplishment in the talk of the moderator and participants.

We study companies that do not produce a sustainability report in contexts where institutionalisation is assumed. Based on a careful analysis of interaction patterns between non-reporting companies, sustainability interest groups, and peer organisations, we find patterns of discursive and material isomorphism that suggest sustainability reporting is confined to an issues-based field, rather than spreading as an institutionalised practice across the business community. We argue that the issues-based field exerts only weak pressure for sustainability reporting, and that encouraging more firms to report rests on understanding what influences companies to interact more widely to become part of this field.

This paper explores the impact of communication protocols on the development of collective identity in networked movements. It focuses primarily on how communication protocols change patterns of interactions and power relationships among the constituents of social movements. The paper suggests that the communication protocols of commercial social networking media lead to organizational centralization and fragmentation in social movements by eroding one of the preconditions of collective identity, namely solidarity. The empirical material presented is part of a PhD dissertation on a political protest movement and their use of Facebook as a core communication and organizational platform. The data gathering is multi-methodological and relies on both qualitative and quantitative data collection techniques in the form of a historical analysis of interaction patterns, and a content analysis of online conversations among activists.

We introduce a new architecture for e-textbooks which contains two navigational aids: an index and a concept map. We report results from an evaluation in a university setting with 99 students. The interaction sequences of the users were captured during the user study. We found several clusters of user interaction types in our data. Three separate user types were identified based on the interaction sequences: passive user, term clicker, and concept map user. We also discovered that with the concept map interface users started to interact with the application significantly sooner than with the index interface. Overall, our findings suggest that analysis of interaction patterns allows deeper insights into the use of e-textbooks than is afforded by summative evaluation.

Listening to 21st century literacies: Prehistory of writing in an academic discipline

A data-driven system-identification technique is explored for proper orthogonal decomposition (POD)-based reduced-order unsteady simulation integrated with time-resolved particle-image-velocimetry/particle-tracking-velocimetry (PIV/PTV) feedback. Principal interaction pattern analysis is extended to calculate a nonlinear transfer function for the POD-mode evolution. Compared with the transfer function derived from the Galerkin projection of the Navier–Stokes equation, instability is suppressed in this approach by introducing a specific norm to be minimized. A feedback loop is implemented such that multiple POD modes obtained by the snapshot method can be stably tracked and assimilated into the PIV/PTV measurement over time. The proposed algorithm is demonstrated by solving a planar-jet problem at \(Re \approx 2{,}000\). Suitable feedback gain is analyzed, and the capability for data assimilation is discussed.

<p>Discussions are commonly used in online teaching and have been shown to foster student learning and collaboration. This case study uses content analysis to explore the interaction patterns of student online discussions during a semester-long teacher preparation course using concepts from sociometry. Findings suggest that interaction patterns were influenced by the content of student posts. Online discussions in this case were found to be an equitable form of collaborative learning, enabling each student to have a voice. There were, however, indications that gendered ways of knowing may play a role in the content of interaction, if not in the patterns themselves.</p>

The purpose of this study was to analyze the interaction patterns of elementary English classes in terms of the taking of turns, number of words used,...

(375) - Weighted Gene Co-expression Network Analysis Reveals Distinct Interaction Patterns in Failing and Recovering Human Myocardium

A methodology for interactive mining and visual analysis of clinical event patterns using electronic health record data