A Novel Notion of Local and Nonlocal Deformation-Gamuts to Model Elastoplastic Deformation

Localization and nonlocalization are characterized as a measure of degrees of separation between two material points in material’s discrete framework and as a measure of unshared and shared information, respectively, manifested as physical quantities between them, in the material’s continuous domain. A novel equation of motion to model the deformation dynamics of material is proposed. The shared information between two localizations is quantified as nonlocalization via a novel multiscale notion of Local and Nonlocal Deformation-Gamuts or DG Localization and Nonlocalization. Its applicability in continuum mechanics to model elastoplastic deformation is demonstrated. It is shown that the stress–strain curves obtained using local and nonlocal deformation-gamuts are found to be in good agreement with the Ramberg–Osgood equation for the material considered. It is also demonstrated that the cyclic strain hardening exponent and cyclic stress–strain coefficient computed using local and nonlocal deformation-gamuts are comparable with the experimental results as well as the theoretical estimations published in the open literature.

Humans depart from optimal computational models of interactive decision-making during competition under partial information

Decision making under uncertainty in multiagent settings is of increasing interest in decision science. The degree to which human agents depart from computationally optimal solutions in socially interactive settings is generally unknown. Such understanding provides insight into how social contexts affect human interaction and the underlying contributions of Theory of Mind. In this paper, we adapt the well-known ‘Tiger Problem’ from artificial-agent research to human participants in solo and interactive settings. Compared to computationally optimal solutions, participants gathered less information before outcome-related decisions when competing than cooperating with others. These departures from optimality were not haphazard but showed evidence of improved performance through learning. Costly errors emerged under conditions of competition, yielding both lower rates of rewarding actions and accuracy in predicting others. Taken together, this work provides a novel approach and insights into studying human social interaction when shared information is partial.

Review and Analysis on Filtering of Unwanted Multimedia Messages from Online Social Network User Walls

When it comes to sharing and exchanging various types of information, online social networks (OSNs) have become an increasingly popular and interactive medium in today's world. People who are connected to blogs and social networks see all of the publicly shared information, and it has a profound effect on the human mind. Messages or comments posted on a wall, a public or private area, may include unnecessary information or sensitive data. Thus, online social networks can benefit from information filtering, which can be used to help users organise messages written in public areas by removing unnecessary words. An information filtering system proposed in this paper may allow OSN users to control the posting and commenting on their walls directly. Every time a user posts a message, the message is intercepted by the filtered wall, which then applies Filtering and Black List Rules to it. The message will appear on the user's wall if it is not filtered or blacklisted. Keywords: Content Based Message Filtering, Demographic Filtering, Collaborative Filtering.

A Normative Framework for Sharing Information Online

People have always shared information through chains and networks of testimony. It is arguably part of what makes us human and enables us to live in cooperative communities with populations greater than 150 or so. The invention of the internet and the rise of social media have turbocharged our ability to share information. This chapter develops a normative epistemic framework for sharing information online. This framework takes into account both ethical and epistemic considerations that are intertwined in typical cases of online testimony. The authors argue that, while the current state of affairs is not entirely novel, recent technological developments call for a rethinking of the norms of testimony, as well as the articulation of a set of virtuous dispositions that people would do well to cultivate in their capacity as conduits (not just sources or receivers) of information.

Implications of online incidental and selective exposure for political emotions: Affective polarization during elections

The Internet and social media create an environment in which individuals can selectively approach information supporting their political worldviews while also being incidentally exposed to socially shared information that challenges their beliefs. These competing information consumption patterns may help explain whether and how digital media contribute to affective polarization (i.e. affect-based division between political groups). This study examines how pro-attitudinal selective exposure and counter-attitudinal incidental exposure in tandem influence political emotions. Using data from 2, two-wave panel surveys conducted during the 2016 and 2020 US presidential elections, our findings demonstrate that seeking consonant political information is consistently associated with anger toward political opponents and enthusiasm toward like-minded partisans. In contrast, despite the purported democratic benefits endowed on political disagreement, cross-cutting incidental exposure does not temper political emotional responses associated with pro-attitudinal selective exposure. However, we find little evidence that unexpected exposure to disagreeable information backfires either.

Bridge Over Troubled Water: Shared Understanding Bridges Individual and Collective Resources in Developing Team Resilience in Professional Football

This study explored how coaches facilitate coordinated activities through shared understanding in the processes of team resilience development. Constructs of shared information that underpin synchronised actions and behaviour in a team are investigated through individual experiences with a dialogic “we” perspective of appropriating and handling challenging situations. Interactional key elements underpin coordinated task actions within the team. Experiences of both players and coaches are investigated through semi-structured interviews and complementary texts such as an observation log and coach-meeting reports, originating as part of an action research process in the team environment. The interaction model is developed in the exploratory journey during the season with the team. The model suggests key strategic elements that help to bridge shared appropriation of information to strengthen role interactions between team members handling challenging situations. Coaching practise, which connects the interaction model to different team resources of coordinating activities in the development process, still needs to be explored from different contextual perspectives and environments, within the development of team resilience.

An efficient scRNA-seq dropout imputation method using graph attention network

Background Single-cell sequencing technology can address the amount of single-cell library data at the same time and display the heterogeneity of different cells. However, analyzing single-cell data is a computationally challenging problem. Because there are low counts in the gene expression region, it has a high chance of recognizing the non-zero entity as zero, which are called dropout events. At present, the mainstream dropout imputation methods cannot effectively recover the true expression of cells from dropout noise such as DCA, MAGIC, scVI, scImpute and SAVER. Results In this paper, we propose an autoencoder structure network, named GNNImpute. GNNImpute uses graph attention convolution to aggregate multi-level similar cell information and implements convolution operations on non-Euclidean space on scRNA-seq data. Distinct from current imputation tools, GNNImpute can accurately and effectively impute the dropout and reduce dropout noise. We use mean square error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC) and Cosine similarity (CS) to measure the performance of different methods with GNNImpute. We analyze four real datasets, and our results show that the GNNImpute achieves 3.0130 MSE, 0.6781 MAE, 0.9073 PCC and 0.9134 CS. Furthermore, we use Adjusted rand index (ARI) and Normalized mutual information (NMI) to measure the clustering effect. The GNNImpute achieves 0.8199 (ARI) and 0.8368 (NMI), respectively. Conclusions In this investigation, we propose a single-cell dropout imputation method (GNNImpute), which effectively utilizes shared information for imputing the dropout of scRNA-seq data. We test it with different real datasets and evaluate its effectiveness in MSE, MAE, PCC and CS. The results show that graph attention convolution and autoencoder structure have great potential in single-cell dropout imputation.

The Emergence and Benefits of Social Relationships in Two Community-Based Dementia Choirs

Community choir participation for persons with dementia (PwD) confers benefits to health and well-being, including the benefit of socializing which can reduce feelings of loneliness and social isolation. Using the concept of social capital, this study examines the degree to which two intergenerational Voices in Motion choirs facilitate the development of social relationships between PwD, caregivers, and high school students. Data collection involved interviews with 17 dyads of PwD and caregivers, completion of a social relationship questionnaire, and focus groups with a total of 29 high school students. The results show a gradual increase in the level of interactions between all participants, with students in particular interacting more frequently with PwD. Over time, trust and reciprocity emerged within the choirs as more people shared information about themselves. Students’ understanding of dementia changed over time as they learned to appreciate PwD as unique human beings with rich life stories and experiences.

Good Trouble Along the Winding Road: Disruption and Accomplishment

The establishment of a accreditation body for gerontology degree programs was seen as disruptive. Many key leaders were against creating such a body and wanted this to be delayed or to never happen. In 2012, the AGHE Accreditation Task Force was established with a Competency Work Group and an Organization Work Group..There have been 5 programs evaluated with a number of schools/university currently in process. The task force filed documents for creating a legal entity and obtaining non-profit status for the new Accreditation for Gerontology Education Council. The Task Force developed the dimensions for program evaluation based on the Competencies and shared information with AGHE members. The Task Force obtained start-up funding for the organization and identified the first programs for accreditation and has been providing outreach and guidance to new programs. There is continual refinement of the process.