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1. A Framework to Support Co-Design Exploration of Manufacturing Supply Networks for Resilience

   https://doi.org/10.1115/DETC2024-146295  

   Baby, Mathew; Mukundan, Pooja; Nellippallil, Anand Balu (August 2024, American Society of Mechanical Engineers)

   Abstract Manufacturing Supply Networks (MSNs) involve group decisions to achieve group goals and network decisions to achieve network goals. These decisions are made across multiple levels of a decision hierarchy. Given the frequent disruptions in MSNs, ‘resilience’ — the ability to maintain satisfactory network functionality despite disruptions, is a vital network goal. When designing MSNs for resilience, the resilience and group goals often conflict, requiring simultaneous consideration of network and group decisions. Limited information in the early stages of MSN design necessitates focusing on design exploration. Hence, facilitating ‘co-design exploration’ — a simultaneous exploration of network and group solution spaces is crucial. Current approaches for designing MSNs for resilience do not support simultaneous consideration of network and group decisions. To bridge this gap, we present the Co-Design Exploration of MSNs for Resilience (CoDE-MR) framework to facilitate co-design exploration of the network and the groups. CoDE-MR framework allows designers to model multilevel network and group decisions and their interactions, manage disruptions, and visualize and simultaneously explore the multilevel network and group solution spaces. In the framework, we integrate a combination of Preemptive and Archimedean formulations of the coupled-compromise Decision Support Problem construct with Resilience Index metric and interpretable Self-Organizing Map (iSOM)-based visualization to facilitate co-design exploration of MSNs for resilience. The framework’s efficacy is demonstrated using a steel MSN test problem, considering network and group decisions across two levels. The use of information flow and generic constructs makes the framework generic and well-suited for co-design exploration of multilevel systems to ensure resilience. 

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2. When perceived similarity overrides demographic similarity: examining influences on STEM students’ developmental mentor networks

   https://doi.org/10.1186/s40594-024-00480-9  

   Pedersen, Rachelle; Woodcock, Anna; Schultz, P Wesley; Hernandez, Paul R (December 2024, International Journal of STEM Education)

   Abstract BackgroundWhile dyadic faculty–mentored relationship research currently saturates the mentoring literature, recent developments suggest the need for a broader consideration of a student's mentor network. Research taking a network approach may provide deeper insights into the formation and benefits of mentorship for undergraduate students in science, technology, engineering, and mathematics (STEM) disciplines. Utilizing Developmental Mentor Network Theory and ego-centric social network analysis, this pre-registered study evaluates how the characteristics of mentees and mentors relate to both the content of support and structure of mentor networks in a large sample of White and Hispanic/Latino(a) STEM undergraduates across 12 universities. ResultsResults were nuanced but showed that perceived psychological similarity with their mentor(s) predicted both dyadic and network average levels of mentor support (i.e., psychosocial, career, role modeling) and relational satisfaction. Furthermore, results point to homophily and engagement in undergraduate research effects on mentor network structures. ConclusionsThese findings highlight the importance of using a network approach to deepen our understanding of the factors (e.g., psychological similarity) that may influence the formation and maintenance of robust and diverse supportive mentoring networks. 

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3. Using network visualizations to engage elementary students in locally relevant data literacy

   https://doi.org/10.1108/ILS-06-2023-0069  

   Zhou, Mengxi; Steinberg, Selena; Stiso, Christina; Danish, Joshua A.; Craig, Kalani (December 2023, Information and Learning Sciences)

   PurposeThis study aims to explore how network visualization provides opportunities for learners to explore data literacy concepts using locally and personally relevant data. Design/methodology/approachThe researchers designed six locally relevant network visualization activities to support students’ data reasoning practices toward understanding aggregate patterns in data. Cultural historical activity theory (Engeström, 1999) guides the analysis to identify how network visualization activities mediate students’ emerging understanding of aggregate data sets. FindingsPre/posttest findings indicate that this implementation positively impacted students’ understanding of network visualization concepts, as they were able to identify and interpret key relationships from novel networks. Interaction analysis (Jordan and Henderson, 1995) of video data revealed nuances of how activities mediated students’ improved ability to interpret network data. Some challenges noted in other studies, such as students’ tendency to focus on familiar concepts, are also noted as teachers supported conversations to help students move beyond them. Originality/valueTo the best of the authors’ knowledge, this is the first study the authors are aware of that supported elementary students in exploring data literacy through network visualization. The authors discuss how network visualizations and locally/personally meaningful data provide opportunities for learning data literacy concepts across the curriculum. 

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4. Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds

   https://doi.org/10.1038/s41398-021-01708-w  

   Sripada, Chandra; Angstadt, Mike; Taxali, Aman; Kessler, Daniel; Greathouse, Tristan; Rutherford, Saige; Clark, D. Angus; Hyde, Luke W.; Weigard, Alex; Brislin, Sarah J.; et al (December 2021, Translational Psychiatry)

   Abstract Convergent research identifies a general factor (“P factor”) that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging. We studied 11,875 9- and 10-year olds from the Adolescent Brain and Cognitive Development (ABCD) study, of whom 6593 had high-quality resting-state scans. Network contingency analysis was used to identify altered interconnections associated with the P factor among 16 large-scale networks. These connectivity changes were then further characterized with quadrant analysis that quantified the directionality of P factor effects in relation to neurotypical patterns of positive versus negative connectivity across connections. The results showed that the P factor was associated with altered connectivity across 28 network cells (i.e., sets of connections linking pairs of networks); p PERMUTATION values < 0.05 FDR-corrected for multiple comparisons. Higher P factor scores were associated with hypoconnectivity within default network and hyperconnectivity between default network and multiple control networks. Among connections within these 28 significant cells, the P factor was predominantly associated with “attenuating” effects (67%; p PERMUTATION  < 0.0002), i.e., reduced connectivity at neurotypically positive connections and increased connectivity at neurotypically negative connections. These results demonstrate that the general factor of psychopathology produces attenuating changes across multiple networks including default network, involved in spontaneous responses, and control networks involved in cognitive control. Moreover, they clarify mechanisms of transdiagnostic risk for psychopathology and invite further research into developmental causes of distributed attenuated connectivity. 

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5. Offline memory replay in recurrent neuronal networks emerges from constraints on online dynamics

   https://doi.org/10.1113/JP283216  

   Milstein, Aaron D.; Tran, Sarah; Ng, Grace; Soltesz, Ivan (August 2023, The Journal of Physiology)

   AbstractDuring spatial exploration, neural circuits in the hippocampus store memories of sequences of sensory events encountered in the environment. When sensory information is absent during ‘offline’ resting periods, brief neuronal population bursts can ‘replay’ sequences of activity that resemble bouts of sensory experience. These sequences can occur in either forward or reverse order, and can even include spatial trajectories that have not been experienced, but are consistent with the topology of the environment. The neural circuit mechanisms underlying this variable and flexible sequence generation are unknown. Here we demonstrate in a recurrent spiking network model of hippocampal area CA3 that experimental constraints on network dynamics such as population sparsity, stimulus selectivity, rhythmicity and spike rate adaptation, as well as associative synaptic connectivity, enable additional emergent properties, including variable offline memory replay. In an online stimulus‐driven state, we observed the emergence of neuronal sequences that swept from representations of past to future stimuli on the timescale of the theta rhythm. In an offline state driven only by noise, the network generated both forward and reverse neuronal sequences, and recapitulated the experimental observation that offline memory replay events tend to include salient locations like the site of a reward. These results demonstrate that biological constraints on the dynamics of recurrent neural circuits are sufficient to enable memories of sensory events stored in the strengths of synaptic connections to be flexibly read out during rest and sleep, which is thought to be important for memory consolidation and planning of future behaviour.image Key pointsA recurrent spiking network model of hippocampal area CA3 was optimized to recapitulate experimentally observed network dynamics during simulated spatial exploration.During simulated offline rest, the network exhibited the emergent property of generating flexible forward, reverse and mixed direction memory replay events.Network perturbations and analysis of model diversity and degeneracy identified associative synaptic connectivity and key features of network dynamics as important for offline sequence generation.Network simulations demonstrate that population over‐representation of salient positions like the site of reward results in biased memory replay. 

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