Metazoans evolved by taking domains from soluble proteins to expand intercellular communication network.

A central question in animal evolution is how multicellular animals evolved from unicellular ancestors. We hypothesize that membrane proteins must be key players in the development of multicellularity because they are well positioned to form the cell-cell contacts and to provide the intercellular communication required for the creation of complex organisms. Here we find that a major mechanism for the necessary increase in membrane protein complexity in the transition from non-metazoan to metazoan life was the new incorporation of domains from soluble proteins. The membrane proteins that have incorporated soluble domains in metazoans are enriched in many of the functions unique to multicellular organisms such as cell-cell adhesion, signaling, immune defense and developmental processes. They also show enhanced protein-protein interaction (PPI) network complexity and centrality, suggesting an important role in the cellular diversification found in complex organisms. Our results expose an evolutionary mechanism that contributed to the development of higher life forms

Prediction of monthly Arctic sea ice concentrations using satellite and reanalysis data based on convolutional neural networks

Changes in Arctic sea ice affect atmospheric circulation, ocean current, and polar ecosystems. There have been unprecedented decreases in the amount of Arctic sea ice due to global warming. In this study, a novel 1-month sea ice concentration (SIC) prediction model is proposed, with eight predictors using a deep-learning approach, convolutional neural networks (CNNs). This monthly SIC prediction model based on CNNs is shown to perform better predictions (mean absolute error - MAE - of 2.28 %, anomaly correlation coefficient - ACC - of 0.98, root-mean-square error - RMSE - of 5.76 %, normalized RMSE - nRMSE - of 16.15 %, and NSE - Nash-Sutcliffe efficiency - of 0.97) than a random-forest-based (RF-based) model (MAE of 2.45 %, ACC of 0.98, RMSE of 6.61 %, nRMSE of 18.64 %, and NSE of 0.96) and the persistence model based on the monthly trend (MAE of 4.31 %, ACC of 0.95, RMSE of 10.54 %, nRMSE of 29.17 %, and NSE of 0.89) through hindcast validations. The spatio-temporal analysis also confirmed the superiority of the CNN model. The CNN model showed good SIC prediction results in extreme cases that recorded unforeseen sea ice plummets in 2007 and 2012 with RMSEs of less than 5.0 %. This study also examined the importance of the input variables through a sensitivity analysis. In both the CNN and RF models, the variables of past SICs were identified as the most sensitive factor in predicting SICs. For both models, the SIC-related variables generally contributed more to predict SICs over ice-covered areas, while other meteorological and oceanographic variables were more sensitive to the prediction of SICs in marginal ice zones. The proposed 1-month SIC prediction model provides valuable information which can be used in various applications, such as Arctic shipping-route planning, management of the fishing industry, and long-term sea ice forecasting and dynamics

Continuity of the Explosive Percolation Transition

The explosive percolation problem on the complete graph is investigated via extensive numerical simulations. We obtain the cluster-size distribution at the moment when the cluster size heterogeneity becomes maximum. The distribution is found to be well described by the power-law form with the decay exponent $\tau = 2.06(2)$, followed by a hump. We then use the finite-size scaling method to make all the distributions at various system sizes up to $N=2^{37}$ collapse perfectly onto a scaling curve characterized solely by the single exponent $\tau$. We also observe that the instant of that collapse converges to a well-defined percolation threshold from below as $N\rightarrow\infty$. Based on these observations, we show that the explosive percolation transition in the model should be continuous, contrary to the widely-spread belief of its discontinuity.Comment: Some corrections during the revie

Leadership Development for School Principals: An Adult Learning Perspective

Although research has increasingly recognized the importance of principal leadership development for school reform, both the content and delivery system continues to be open to debate. In this paper, we review school principal leadership development and provide a conceptual framework for developing school principal leadership based on adult learning theories. We conceptualize school principals as adult educators and adult learners based on key assumptions of adult learning theories. School principals are understood as both adult educators and adult learners in that they need to develop their leadership as well as support teachers’ learning in the context of professional development. Relying on these assumptions, we draw philosophical foundations and directions for principal leadership development programs. We attest that constructivism, humanism, and critical social theory can philosophically support principal leadership development, and that leadership programs need to promote knowledgeable, practice, and reflexive leadership

Ambivalence toward bureaucracy: Responses from Korean school principals

Purpose – Given the context of accountability-driven policy environments, research has shown that school leaders perceive bureaucratic rules and protocols in negative ways, but they also utilize organizational structures and routines to lead changes. To better understand both enabling and hindering mechanisms of bureaucracy in schools, this study explores how Korean school principals understand and perceive bureaucratic structures using a lens of ambivalence. The authors draw on Weber’s theory of bureaucracy, with a particular focus on the paradoxical aspect of bureaucracy that might be experienced by individuals within the system. Design/methodology/approach – This study analyzed qualitative data collected from 26 in-depth interviews with 10 Korean school principals between 2013 and 2015. The authors used the multiple cycles of coding to explore patterns and themes that emerged from the participants’ responses. Findings – The analysis of this study showed that the participants’ ambivalent responses toward bureaucracy were particularly salient in three areas where formal organizational structures were changing through policy initiatives: teacher evaluation, electronic approval system and school-based management promoting decentralized decision making. The study participants reflected on how such changes can enable and/or hinder schools to achieve organizational goals and collective values, from the viewpoints of multiple aspects, which led to their ambivalent responses to bureaucratic structures in school settings. Originality/value – This study contributes to the understanding of school organizations by revisiting Weber’s theory of bureaucracy in school settings. Using the lens of ambivalence enabled us to reconcile school principals’ contradictory perceptions toward bureaucracy, which complicates analyses of tensions and paradoxical responses found in leadership practices within school systems