The adoption and diffusion of pro-environmental stadium design

Research question: Owners and architects face mounting pressure to incorporate environmentally sustainable features in new arenas, ballparks, and stadiums. In this study, we apply Rogers’ diffusion-of-innovations framework to highlight the key influencers and factors contributing to the decision to adopt pro-environmental initiatives. Research method: We conducted interviews with 13 senior architects whose portfolios collectively contained over 25 eco-friendly sport facilities spanning Europe, Australia, Africa, and North America. The facilities discussed were used for a variety of leagues and events, including FIFA World Cup, the Olympic and Paralympic Games, college football and basketball, Major League Baseball (MLB), and the National Football League (NFL). The data were transcribed and analyzed following the open, axial, and selective coding sequence. Results and findings: The results of the study indicated that owners and quasi-owners reviewing green facility proposals considered the input of several groups, including the design firms, the media, political leaders, environmental activists, and local citizens. According to interviewees, the primary incentives for owners and quasi-owners to adopt sustainable designs were economic savings over the life of the facility, perception-management opportunities, and demonstration of their innovativeness. Finally, facility designers predicted the diffusion of pro-environmental sport facilities would continue in the immediate future. Implications: Innovation diffusion is driven by early adopters, who prioritize an innovation\u27s relative advantage and compatibility over its complexity, lack of trialability, and lack of observability. Additionally, pro-environmental facilities are being used by organizations to demonstrate both environmental stewardship and their cultures of innovation. Future research should explore both the decision-making process and barriers to sustainable design adoption in further depth

Perceived productivity in open-plan design library: Exploring occupant behavior and perception

Libraries in higher education face drastic spatial changes, transforming spaces traditionally used for housing books to spaces for interaction and shifting from individual learning to team-based learning. This study aims to (1) identify space uses, (2) examine the environmental satisfaction, support for productivity, and perceived productivity depending on space, and (3) test their relationships. The results of 66 survey responses suggest that students still come to the library for individual study, and students in quiet zones show high environmental satisfaction. Environmental satisfaction is indirectly associated with creativity, while environmental support with acoustic comfort is directly related to concentration

Global Perspectives on Democracy and Public Stadium Finance

Arenas, ballparks, and stadiums built for professional sports teams or mega-events all around the world often come with large public costs. In democratic states, citizens are assumed to have a role in public policymaking, but previous research suggests the strength of this role can vary case-to-case. To examine the incidence of public stadium finance and public participation across the geopolitical landscape, a collective case study was employed and organized into regime type (i.e., full democracies, flawed democracies, hybrid regimes, authoritarian regimes). The results of the study show clear contrasts in the financing mechanisms within and between regime types. Additionally, each case-study grouping contained examples of citizen-led public participation, though the efficacy of these democratic actions is questionable. This review complements the growing literature on public policy and stadium finance by assessing public engagement in current stadium-subsidy debates around the world

Cracking the Code of Negative Transfer: A Cooperative Game Theoretic Approach for Cross-Domain Sequential Recommendation

This paper investigates Cross-Domain Sequential Recommendation (CDSR), a promising method that uses information from multiple domains (more than three) to generate accurate and diverse recommendations, and takes into account the sequential nature of user interactions. The effectiveness of these systems often depends on the complex interplay among the multiple domains. In this dynamic landscape, the problem of negative transfer arises, where heterogeneous knowledge between dissimilar domains leads to performance degradation due to differences in user preferences across these domains. As a remedy, we propose a new CDSR framework that addresses the problem of negative transfer by assessing the extent of negative transfer from one domain to another and adaptively assigning low weight values to the corresponding prediction losses. To this end, the amount of negative transfer is estimated by measuring the marginal contribution of each domain to model performance based on a cooperative game theory. In addition, a hierarchical contrastive learning approach that incorporates information from the sequence of coarse-level categories into that of fine-level categories (e.g., item level) when implementing contrastive learning was developed to mitigate negative transfer. Despite the potentially low relevance between domains at the fine-level, there may be higher relevance at the category level due to its generalised and broader preferences. We show that our model is superior to prior works in terms of model performance on two real-world datasets across ten different domains.Comment: Accepted at 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023

Tautomerism unveils a self-inhibition mechanism of crystallization

Modifiers are commonly used in natural, biological, and synthetic crystallization to tailor the growth of diverse materials. Here, we identify tautomers as a new class of modifiers where the dynamic interconversion between solute and its corresponding tautomer(s) produces native crystal growth inhibitors. The macroscopic and microscopic effects imposed by inhibitor-crystal interactions reveal dual mechanisms of inhibition where tautomer occlusion within crystals that leads to natural bending, tunes elastic modulus, and selectively alters the rate of crystal dissolution. Our study focuses on ammonium urate crystallization and shows that the keto-enol form of urate, which exists as a minor tautomer, is a potent inhibitor that nearly suppresses crystal growth at select solution alkalinity and supersaturation. The generalizability of this phenomenon is demonstrated for two additional tautomers with relevance to biological systems and pharmaceuticals. These findings offer potential routes in crystal engineering to strategically control the mechanical or physicochemical properties of tautomeric materials

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A mouse is an important input device that is used in most of all computer works. A mouse control time prediction model was proposed in this study. Especially, the model described the time of mouse control that made a cursor to move within path constraints. The model was developed by a laboratory experiment. Cursor movement times were measured in 36 task conditions; 3 levels of path length, 3 levels of path width and 4 levels of target???s width. 12 subjects participated in all conditions. The time of cursor movement with path constraints could be better explained by the combination of Fitts??? law with steering law(r2=0.947) than by the other models; Fitts??? law(r2=0.740), Steering law(r2=0.633) and Crossman???s model(r2=0.897). The proposed model is expected to be used in menu design or computer game design.clos

Collaborative Innovation in Professional Sport Stadium Construction: An Event History Analysis

This study identifies and empirically tests a variety of potentially important deter-minants influencing new stadium construction adoption from both a team and government perspective, while also accounting for the role of diffusion effects in new stadium construction. The sample consists of 28 Major League Baseball (MLB) franchises in 26 cities in the U.S. Given the longitudinal nature of the stadium con-struction process, event history analysis (EHA) was employed as the primary sta-tistical method. Overall, 48% of the variance was explained by the research model. Diffusion effects (measured as divisional diffusion and regional diffusion) were found to be the most meaningful to construction adoption. The significance of this study rests in its focus on identifying and empirically testing factors influencing the adoption of sport stadium construction from the perspectives of professional sport teams and governing bodies. The empirical results support Rogers (2003) diffusion of innovation theory and provide useful information to both sport managers and governments officials on key factors (e.g., diffusion effects) that may increase the prospect of stadium construction adoption

AiKPro: deep learning model for kinome-wide bioactivity profiling using structure-based sequence alignments and molecular 3D conformer ensemble descriptors

Abstract The discovery of selective and potent kinase inhibitors is crucial for the treatment of various diseases, but the process is challenging due to the high structural similarity among kinases. Efficient kinome-wide bioactivity profiling is essential for understanding kinase function and identifying selective inhibitors. In this study, we propose AiKPro, a deep learning model that combines structure-validated multiple sequence alignments and molecular 3D conformer ensemble descriptors to predict kinase-ligand binding affinities. Our deep learning model uses an attention-based mechanism to capture complex patterns in the interactions between the kinase and the ligand. To assess the performance of AiKPro, we evaluated the impact of descriptors, the predictability for untrained kinases and compounds, and kinase activity profiling based on odd ratios. Our model, AiKPro, shows good Pearson’s correlation coefficients of 0.88 and 0.87 for the test set and for the untrained sets of compounds, respectively, which also shows the robustness of the model. AiKPro shows good kinase-activity profiles across the kinome, potentially facilitating the discovery of novel interactions and selective inhibitors. Our approach holds potential implications for the discovery of novel, selective kinase inhibitors and guiding rational drug design