Bereavement Adaptation as Deflection Reduction: Bereaved Caregivers Define the Event of Dying

Affect control theory (ACT) has the potential to extend dominant understandings of adaptation to bereavement. Using narratives from bereaved caregivers, we assessed attributions they made about the death of a loved one from cancer. We transformed these attributions into actor-behavior-object events along the evaluation, potency, and activity dimensions of ACT. After creating hypothetical baseline deflections for events, we simulated the attributions as events in INTERACT. We found eight emergent categories of resolutions that caregivers used to make sense of the death: caregivers redefined the event to align with their sentiments about the deceased or the death. We also found racial differences in the attributions. White caregivers were more likely to blame themselves or others for the death of their loved one, while black caregivers were more willing to admit their deceased loved one’s faults. These findings demonstrate how caregivers make sense of their grief in a framework of cultural sentiments and underscore the utility of affect control theory in qualitative and theory-generating research.

Affect Control Theories: A Double Special Issue in Honor of David R. Heise

We introduce this two-part special issue that celebrates David Heise and his pathbreaking theories: affect control theory (ACT), affect control theory of the self (ACTS), and affect control theory of institutions (ACTI). These interlocking, multi-level, mathematically based theories explain a range of social processes, including impression formation, social interaction, trait and mood attributions, emotional experiences, emotion management, and identity adoption, and they do so in multiple languages and cultures. The 15 articles in this two-part issue test, apply, and develop the theories in new and innovative ways. After briefly summarizing each theory and Bayesian affect control theory (BayesACT), we highlight the key findings from each of the articles that follow.

So What if They’re Lying to Us? Comparing Rhetorical Strategies for Discrediting Sources of Disinformation and Misinformation Using an Affect-Based Credibility Rating

Despite growing research on false information, a theoretical framework to organize findings is lacking. We use affect control theory to fill this need and introduce the affect-based credibility rating for interpreting the effectiveness of rhetorical strategies in discrediting the source of falsehoods. The rating quantifies the difference in connotations between the labels used to characterize the source and an ideal, credible source. Successful discrediting amplifies the difference. We use the rating to compare rhetorical strategies for discrediting opponents as sources during rival information campaigns about the Equal Rights Amendment. We show claiming the opponent is spreading disinformation rather than misinformation (stating the opponent is spreading falsehoods deliberately, rather than unwittingly) appears more effective at discrediting, particularly when disinformation claims allege more sinister motives for lying. The new rating helps organize findings by enabling direct comparisons between strategies, thereby contributing toward efforts to detect and discredit falsehoods in media.

Weed Response to Co-Application of Herbicides and Acephate in Cotton

Determining compatibility of pesticides is important in developing effective management practices and adjusting to outbreaks of pests in cotton (Gossypium hirsutism L.). Field experiments were conducted in 2013 and 2014 to determine the effect of chloroacetamide herbicides with residual activity only and acephate with foliar activity against thrips (Frankliniella spp.) on control of emerged weeds by glyphosate, glufosinate, and a mixture of these herbicides. The residual herbicides acetochlor and S-metolachlor as well as the insecticide acephate did not affect control of emerged common ragweed (Ambrosia artemisiifolia L.) and Palmer amaranth (Amaranthus palmeri Watts.). Results from these trials indicate that weed control will not be compromised with co-application of glufosinate, glyphosate, and glufosinate plus glyphosate with acetochlor or S-metolachlor applied alone or with acephate.

CXCR6+CD4+ T cells promote mortality during Trypanosoma brucei infection

Liver macrophages internalize circulating bloodborne parasites. It remains poorly understood how this process affects the fate of the macrophages and T cell responses in the liver. Here, we report that infection by Trypanosoma brucei induced depletion of macrophages in the liver, leading to the repopulation of CXCL16-secreting intrahepatic macrophages, associated with substantial accumulation of CXCR6+CD4+ T cells in the liver. Interestingly, disruption of CXCR6 signaling did not affect control of the parasitemia, but significantly enhanced the survival of infected mice, associated with reduced inflammation and liver injury. Infected CXCR6 deficient mice displayed a reduced accumulation of CD4+ T cells in the liver; adoptive transfer experiments suggested that the reduction of CD4+ T cells in the liver was attributed to a cell intrinsic property of CXCR6 deficient CD4+ T cells. Importantly, infected CXCR6 deficient mice receiving wild-type CD4+ T cells survived significantly shorter than those receiving CXCR6 deficient CD4+ T cells, demonstrating that CXCR6+CD4+ T cells promote the mortality. We conclude that infection of T. brucei leads to depletion and repopulation of liver macrophages, associated with a substantial influx of CXCR6+CD4+ T cells that mediates mortality.

Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups

Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.

Optimization of Control Line Encapsulation Based on Numerical Simulations of Shock and Vibration

Control line integrity is fundamental to ensure operability of intelligent completion systems. Damage to control lines can normally occur during string deployment (by shock), or during productive life (by vibration-related fatigue). This work aimed to investigate how encapsulation will affect control line survivability throughout their entire life cycle. Numerical simulations were carried out using geometrical arrangements of control lines typically found in completion valves and tubings. For installation loads, lines were submitted to shock simulations, both inside and outside of protection clamps. The role of flatpack material was studied, as to which kind of material would better absorb impact energy. For productive life loads, the flow-induced vibration was taken into account for high-rate injector wells. Vibration loads were based on force results obtained by Computational Fluid Dynamics (CFD). Structural Finite Element Analysis (FEA) was performed to obtain local tensions to estimate productive life of lines.

Critiquing Child characters as Heroes, Villains, and Victims in Ru Freeman’s On Sal Mal Lane

Social behaviour and filial background define the formation and development of a character that is bound by cultural influence in South Asian fiction. Ru Freeman weaves numerous characters and their stories in a single lane as a synecdoche of Sri Lankan history. On Sal Mal Lane (2014) showcases the different social groups defining Sri Lankan conflict in the 1980s with the presence of child characters who are unaware of the extent of the ethnic conflict swirling in the background of the narrative. This paper tries to define the concepts of heroes, villains, and victims through the socio-emotional development of the characters to determine the contradiction between their intentions and subsequent actions. The study uses Character Theory and elements of Affect Control Theory for critical analysis. The paper analyses the change in personality traits of child characters in response to the violence wrought by Sri Lankan ethnic prejudices and the extent of destructive development from the unstable familial and societal environments.

Operationalizing the Relation Between Affect and Cognition With the Somatic Transform

This article introduces the somatic transform that operationalizes the relation between affect and cognition at the psychological level of analysis by capitalizing on the relation between the cognitive-denotative and affective-connotative meaning of concepts as measured with semantic differential rating scales. Following discussion of levels of analysis, the importance of language at the psychological level, and two principles (inextricability and complementarity) summarizing the relation between affect and cognition that are rendered explicit by the somatic transform, we present affect control theory (ACT) and its Bayesian extension (BayesACT) containing the somatic transform. We conclude by identifying examples of inextricability and complementarity in the social science and neuroscience literatures and discussing how our psychological model might be implemented in a realistic neural model.

Estimation of Pre-COVID19 Daily Ridership Patterns From Paper and Electronic Ticket Sales Data With Origin-Destination, Time-Of-Day, and Train-Start Detail on a Commuter Railroad: Quick-Response Big Data Analytics in a World Steeped With Tradition

Our niche method independently estimates hourly commuter rail station-to-station origin-destination (OD) matrix data each day from ticket sales and activation data from four sales channels (paper/mobile tickets, mail order, and onboard sales) by extending well-established transportation modelling methodologies. This algorithm’s features include: (1) handles multi-pack pay-per-ride fare instruments not requiring electronic validation, like ten-trip paper tickets “punched” onboard by railroad conductors; (2) correctly infers directionality for direction-agnostic ticket-types; (3) estimates unlimited ride ticket utilization patterns sufficiently precisely to inform vehicle assignment/scheduling; (4) provides integer outputs without allowing rounding to affect control totals nor introduce artifacts; (5) deals gracefully with cliff-edge changes in demand, like the COVID19 related lockdown; and (6) allocates hourly traffic to each train-start based on passenger choice. Our core idea is that the time of ticket usage is ultimately a function of the time of sale and ticket type, and mutual transformation is made via probability density functions (“patterns”) given sufficient distribution data. We generated pre-COVID daily OD matrices and will eventually extend this work to post-COVID inputs. Results were provided to operations planners using visual and tabular interfaces. These matrices represent data never previously available by any method; prior OD surveys required 100,000 respondents, and even then could neither provide daily nor hourly levels of detail, and could not monitor special event ridership nor specific seasonal travel such as summer Friday afternoons.