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1. Biological networks across scales

   https://doi.org/10.1093/icb/icab069  

   Bogdan, Paul ; Caetano-Anollés, Gustavo ; Jolles, Anna ; Kim, Hyunju ; Morris, James ; Murphy, Cheryl A ; Royer, Catherine ; Snell, Edward H ; Steinbrenner, Adam ; Strausfeld, Nicholas ( May 2021 , Integrative and Comparative Biology)

   null (Ed.)

   Synopsis Many biological systems across scales of size and complexity exhibit a time-varying complex network structure that emerges and self-organizes as a result of interactions with the environment. Network interactions optimize some intrinsic cost functions that are unknown and involve for example energy efficiency, robustness, resilience, and frailty. A wide range of networks exist in biology, from gene regulatory networks important for organismal development, protein interaction networks that govern physiology and metabolism, and neural networks that store and convey information to networks of microbes that form microbiomes within hosts, animal contact networks that underlie social systems, and networks of populations on the landscape connected by migration. Increasing availability of extensive (big) data is amplifying our ability to quantify biological networks. Similarly, theoretical methods that describe network structure and dynamics are being developed. Beyond static networks representing snapshots of biological systems, collections of longitudinal data series can help either at defining and characterizing network dynamics over time or analyzing the dynamics constrained to networked architectures. Moreover, due to interactions with the environment and other biological systems, a biological network may not be fully observable. Also, subnetworks may emerge and disappear as a result of the need for the biological system to cope with for example invaders or new information flows. The confluence of these developments renders tractable the question of how the structure of biological networks predicts and controls network dynamics. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (e.g., multifractal spectrum), which maintain stability over time through robustness and/or resilience to perturbation. Alternative, plastic networks may respond to perturbation by (adaptive to catastrophic) shifts in structure. Here, we explore the opportunity for discovering universal laws connecting the structure of biological networks with their function, positioning them on the spectrum of time-evolving network structure, i.e. dynamics of networks, from highly stable to exquisitely sensitive to perturbation. If such general laws exist, they could transform our ability to predict the response of biological systems to perturbations—an increasingly urgent priority in the face of anthropogenic changes to the environment that affect life across the gamut of organizational scales. 

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2. An Exploration of the Effects of Enterprise Social Media Use for Classroom Teams.

   Cherchiglia, L. ; Van Osch, W. ; Liang, Y. ; Averkiadi, E. ( December 2020 , SIGHCI 2020 Proceedings)

   null (Ed.)

   Cherchiglia et al. Effects of ESM Use for Classroom Teams Proceedings of the Nineteenth Annual Pre-ICIS Workshop on HCI Research in MIS, Virtual Conference, December 12, 2020 1 An Exploration of the Effects of Enterprise Social Media Use for Classroom Teams Leticia Cherchiglia Michigan State University leticia@msu.edu Wietske Van Osch HEC Montreal & Michigan State University wietske.van-osch@hec.ca Yuyang Liang Michigan State University liangyuy@msu.edu Elisavet Averkiadi Michigan State University averkiad@msu.edu ABSTRACT This paper explores the adoption of Microsoft Teams, a group-based Enterprise Social Media (ESM) tool, in the context of a hybrid Information Technology Management undergraduate course from a large midwestern university. With the primary goal of providing insights into the use and design of tools for group-based educational settings, we constructed a model to reflect our expectations that core ESM affordances would enhance students’ perceptions of Microsoft Teams’ functionality and efficiency, which in turn would increase both students’ perceptions of group productivity and students’ actual usage of Microsoft Teams for communication purposes. In our model we used three core ESM affordances from Treem and Leonardi (2013), namely editability (i.e., information can be created and/or edited after creation, usually in a collaborative fashion), persistence (i.e., information is stored permanently), and visibility (i.e., information is visible to other users). Analysis of quantitative (surveys, server-side; N=62) and qualitative (interviews; N=7) data led to intriguing results. It seems that although students considered that editability, persistency, and visibility affordances within Microsoft Teams were convenient functions of this ESM, problems when working collaboratively (such as connectivity, formatting, and searching glitches) might have prevented considerations of this ESM as fast and user-friendly (i.e., efficient). Moreover, although perceived functionality and efficiency were positively connected to group productivity, hidden/non-intuitive communication features within this ESM might help explain the surprising negative connection between efficiency and usage of this ESM for the purpose of group communication. Another explanation is that, given the plethora of competing tools specifically designed to afford seamless/optimal team communication, students preferred to use more familiar tools or tools perceived as more efficient for group communication than Microsoft Teams, a finding consistent with findings in organizational settings (Van Osch, Steinfield, and Balogh, 2015). Beyond theoretical contributions related to the impact that ESM affordances have on users’ interaction perceptions, and the impact of users’ interaction perceptions on team and system outcomes, from a strategic and practical point of view, our findings revealed several challenges for the use of Microsoft Teams (and perhaps ESM at large) in educational settings: 1) As the demand for online education grows, collaborative tools such as Microsoft Teams should strive to provide seamless experiences for multiple-user access to files and messages; 2) Microsoft Teams should improve its visual design in order to increase ease of use, user familiarity, and intuitiveness; 3) Microsoft Teams appears to have a high-learning curve, partially related to the fact that some features are hidden or take extra steps/clicks to be accessed, thus undermining their use; 4) Team communication is a complex topic which should be further studied because, given the choice, students will fall upon familiar tools therefore undermining the full potential for team collaboration through the ESM. We expect that this paper can provide insights for educators faced with the choice for an ESM tool best-suited for group-based classroom settings, as well as designers interested in adapting ESMs to educational contexts, which is a promising avenue for market expansion. 

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3. Biological Networks across Scales—The Theoretical and Empirical Foundations for Time-Varying Complex Networks that Connect Structure and Function across Levels of Biological Organization

   Paul Bogdan, Gustavo Caetano-Anolles ( May 2021 , Integrative and comparative biology)

   Many biological systems across scales of size and complexity exhibit a time-varying complex network structure that emerges and self-organizes as a result of interactions with the environment. Network interactions optimize some intrinsic cost functions that are unknown and involve for example energy efficiency, robustness, resilience, and frailty. A wide range of networks exist in biology, from gene regulatory networks important for organismal development, protein interaction networks that govern physiology and metabolism, and neural networks that store and convey information to networks of microbes that form microbiomes within hosts, animal contact networks that underlie social systems, and networks of populations on the landscape connected by migration. Increasing availability of extensive (big) data is amplifying our ability to quantify biological networks. Similarly, theoretical methods that describe network structure and dynamics are being developed. Beyond static networks representing snapshots of biological systems, collections of longitudinal data series can help either at defining and characterizing network dynamics over time or analyzing the dynamics constrained to networked architectures. Moreover, due to interactions with the environment and other biological systems, a biological network may not be fully observable. Also, subnetworks may emerge and disappear as a result of the need for the biological system to cope with for example invaders or new information flows. The confluence of these developments renders tractable the question of how the structure of biological networks predicts and controls network dynamics. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (e.g., multifractal spectrum), which maintain stability over time through robustness and/or resilience to perturbation. Alternative, plastic networks may respond to perturbation by (adaptive to catastrophic) shifts in structure. Here, we explore the opportunity for discovering universal laws connecting the structure of biological networks with their function, positioning them on the spectrum of time-evolving network structure, that is, dynamics of networks, from highly stable to exquisitely sensitive to perturbation. If such general laws exist, they could transform our ability to predict the response of biological systems to perturbations—an increasingly urgent priority in the face of anthropogenic changes to the environment that affect life across the gamut of organizational scales. 

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4. Board 354: Organizational Partnerships S-STEM Research Hub

   Knight, D. B. ( June 2023 , ASEE Annual Conference proceedings)

   The objective of the Research on Organizational Partnerships in Education and STEM (ROPES) Hub is to advance understanding of organizational partnerships that support academic pathways for domestic low-income engineering students. Partnerships across the education system are essential for improving STEM; achieving the systematic, structural, or sustainable change desired by programs such as NSF’s Scholarships for STEM Students (S-STEM) program is seldom achieved by individual isolated units and often requires partnerships across silos within an academic institution (i.e., intra-institution partnerships) and across institutions (i.e., inter-institution partnerships). However, how such partnerships are built, designed, and sustained remains a great challenge facing the field. This Hub, led by a collaborative team from Virginia Tech, Weber State University, Northern Virginia Community College, and the University of Cincinnati, is working to organize groups to conduct research focused on supporting low-income undergraduate engineering, computer science, and computing students in ways that are congruent with the institutional context and resources while going beyond the direct impact on S-STEM Scholars to impact departments and institutions involved. We are zooming in on the institutional infrastructure and collaborative work between researchers, administrators and practitioners, and policymakers. The overarching research question guiding the hub is: How can intra- and inter-institutional partnerships be designed, built, and sustained to systematically support low-income engineering student success? Answering this question requires a research hub because understanding different models of organizational partnerships—and linking such research to student outcomes across a variety of institutional contexts—requires a focus across S-STEM programs that is only enabled by a research hub approach; it cannot happen in a single S-STEM program. An important contribution of this work will be to characterize aspects of problems in which collaboration and partnerships can be most helpful—supporting low-income engineering students aiming to earn a bachelor’s degree fits these conditions, representing the kind of complex system of interacting, interdependent stakeholders with differing expertise and with no systematic organization of stakeholders. 

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5. Expertise Flows in AEC Projects: an Analysis of Multi-Level Teams for Sustainability

   Duva, Meltem ; Mollaoglu, Sinem ; Zhao, Dong ; Frank, Kenneth A. ( October 2020 , Proceedings of EPOC 2020)

   Faust, Kasey ; Kanjanabootra, Sittimont (Ed.)

   Architectural, Engineering, and Construction (AEC) project teams adopt different methods to facilitate collaboration to achieve sustainability goals, which requires a high level of expertise integration. Tracking expertise flows in interdisciplinary and inter-organizational project networks is challenging because of the unique project nature, fluid expertise boundaries, and varying project requirements. It can be even more difficult considering sustainability outcomes, due to the need for high-level expertise integration. Social network approach addresses the integration and information flow dynamics. However, there is a knowledge gap regarding what network characteristics are favorable for improved sustainability outcomes in AEC projects, how they evolve during delivery, and how relevant expertise flows through project networks. To respond to the need in the literature, this study aims to develop a holistic understanding of AEC project team networks and associated characteristics that allow experts to exchange knowledge to optimize sustainability outcomes for built environment projects. We longitudinally collected e-mail exchange, observational, and archival data during the design phase of an AEC case study project and performed Social Network Analysis (SNA) bolstered by mixed methods. Results suggest that network topology matters for AEC project teams. In other words, understanding the interactions between components of a network (e.g., expertise areas represented and distributed in the network and the number of boundary spanners) is as important as the network parameters for better sustainability outcomes. 

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