5,392 research outputs found
A Spark Of Emotion: The Impact of Electrical Facial Muscle Activation on Emotional State and Affective Processing
Facial feedback, which involves the brain receiving information about the activation of facial muscles, has the potential to influence our emotional states and judgments. The extent to which this applies is still a matter of debate, particularly considering a failed replication of a seminal study. One factor contributing to the lack of replication in facial feedback effects may be the imprecise manipulation of facial muscle activity in terms of both degree and timing. To overcome these limitations, this thesis proposes a non-invasive method for inducing precise facial muscle contractions, called facial neuromuscular electrical stimulation (fNMES). I begin by presenting a systematic literature review that lays the groundwork for standardising the use of fNMES in psychological research, by evaluating its application in existing studies. This review highlights two issues, the lack of use of fNMES in psychology research and the lack of parameter reporting. I provide practical recommendations for researchers interested in implementing fNMES. Subsequently, I conducted an online experiment to investigate participants' willingness to participate in fNMES research. This experiment revealed that concerns over potential burns and involuntary muscle movements are significant deterrents to participation. Understanding these anxieties is critical for participant management and expectation setting. Subsequently, two laboratory studies are presented that investigated the facial FFH using fNMES. The first study showed that feelings of happiness and sadness, and changes in peripheral physiology, can be induced by stimulating corresponding facial muscles with 5âseconds of fNMES. The second experiment showed that fNMES-induced smiling alters the perception of ambiguous facial emotions, creating a bias towards happiness, and alters neural correlates of face processing, as measured with event-related potentials (ERPs). In summary, the thesis presents promising results for testing the facial feedback hypothesis with fNMES and provides practical guidelines and recommendations for researchers interested in using fNMES for psychological research
Southern Adventist University Undergraduate Catalog 2023-2024
Southern Adventist University\u27s undergraduate catalog for the academic year 2023-2024.https://knowledge.e.southern.edu/undergrad_catalog/1123/thumbnail.jp
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
âOh my god, how did I spend all that money?â: Lived experiences in two commodified fandom communities
This research explores the role of commodification in participation in celebrity-centric fandom communities, applying a leisure studies framework to understand the constraints fans face in their quest to participate and the negotiations they engage in to overcome these constraints.
In fan studies scholarship, there is a propensity to focus on the ways fans oppose commodified industry structures; however, this ignores the many fans who happily participate within them. Using the fandoms for the pop star Taylor Swift and the television series Supernatural as case studies, this project uses a mixed-methodological approach to speak directly to fans via surveys and semistructured interviews to develop an understanding of fansâ lived experiences based on their own words.
By focusing on celebrity-centric fandom communities rather than on the more frequently studied textual fandoms, this thesis turns to the role of the celebrity in fansâ ongoing desire to participate in commodified spaces. I argue that fans are motivated to continue spending money to participate within their chosen fandom when this form of participation is tied to the opportunity for engagement with the celebrity. While many fans seek community from their fandom participation, this research finds that for others, social ties are a secondary outcome of their overall desire for celebrity attention, which becomes a hobby in which they build a âleisure careerâ (Stebbins 2014). When fans successfully gain attention from their celebrity object of fandom, they gain status within their community, creating intra-fandom hierarchies based largely on financial resources and on freedom from structural constraints related to education, employment, and caring.
Ultimately, this thesis argues that the broad neglect of celebrity fandom practices means we have overlooked the experiences of many fans, necessitating a much broader future scope for the field
Reducing Library Anxiety in the Information Seeking Behavior Of First Year College Students
This study explored the use of interactive technology to reduce library anxiety in the information seeking behavior of first year students enrolled in a historically Black college or university. Based on the research focus, the following questions were formulated: What are the determinants for reducing library anxiety in first year college studentsâ information seeking behavior? Related questions were formatted to test the hypotheses and for data collection:
(1) Can interactive applications included as part of the information retrieval process decrease library anxiety?
(2) Can familiarity, as measured by a pre and post survey, decrease library anxiety? Interactive applications may include virtual and augmented reality, online chat, games and artificial intelligence technology. These are relatively new forms of technology used in education, and research indicates that these technologies promote immersive experiences that can contribute to learning. The research hypothesized that these technologies may also increase familiarity of the library and the related resources, which may reduce library anxiety. This research may provide vital information to higher education administrators and librarians to ensure that all students receive adequate resources to find information needed for their classes and that barriers that prevent progress in studentâs education are removed.
Keywords: information seeking behavior, library anxiety, virtual reality, augmented realit
Sensing Collectives: Aesthetic and Political Practices Intertwined
Are aesthetics and politics really two different things? The book takes a new look at how they intertwine, by turning from theory to practice. Case studies trace how sensory experiences are created and how collective interests are shaped. They investigate how aesthetics and politics are entangled, both in building and disrupting collective orders, in governance and innovation. This ranges from populist rallies and artistic activism over alternative lifestyles and consumer culture to corporate PR and governmental policies. Authors are academics and artists. The result is a new mapping of the intermingling and co-constitution of aesthetics and politics in engagements with collective orders
SHARP: Sparsity and Hidden Activation RePlay for Neuro-Inspired Continual Learning
Deep neural networks (DNNs) struggle to learn in dynamic environments since
they rely on fixed datasets or stationary environments. Continual learning (CL)
aims to address this limitation and enable DNNs to accumulate knowledge
incrementally, similar to human learning. Inspired by how our brain
consolidates memories, a powerful strategy in CL is replay, which involves
training the DNN on a mixture of new and all seen classes. However, existing
replay methods overlook two crucial aspects of biological replay: 1) the brain
replays processed neural patterns instead of raw input, and 2) it prioritizes
the replay of recently learned information rather than revisiting all past
experiences. To address these differences, we propose SHARP, an efficient
neuro-inspired CL method that leverages sparse dynamic connectivity and
activation replay. Unlike other activation replay methods, which assume layers
not subjected to replay have been pretrained and fixed, SHARP can continually
update all layers. Also, SHARP is unique in that it only needs to replay few
recently seen classes instead of all past classes. Our experiments on five
datasets demonstrate that SHARP outperforms state-of-the-art replay methods in
class incremental learning. Furthermore, we showcase SHARP's flexibility in a
novel CL scenario where the boundaries between learning episodes are blurry.
The SHARP code is available at
\url{https://github.com/BurakGurbuz97/SHARP-Continual-Learning}
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