Structural color, which arises from the interaction of light with micro- and nanostructured materials, has been recognized as an environmentally sustainable alternative to traditional dyes and pigments. In this study, Direct Ink Writing has been utilized as the additive manufacturing technique for fabricating structurally colored materials which here, are bottlebrush block copolymers. The experimental workflow has been integrated with an artificial intelligence-driven optimization process, enabling an efficient exploration of the printing parameter space. Image analysis techniques have been employed to characterize the resultant color profiles, with hue in the HSV color space serving as the primary objective function for optimization. The development of software architecture that facilitates real-time data collection and feedback has been undertaken in collaboration with the National Center for Supercomputing Applications (NCSA). Preliminary results have demonstrated the feasibility of the proposed approach in tuning structural coloration, while ongoing efforts aim to enhance automation capabilities and expand the scope of parameter optimization.

Federal agricultural, conservation and food assistance programs are critical policies for the agricultural and food sectors. Historically, these policies have been reauthorized by the United States Congress every five years. Also known as the Farm Bill, it authorizes four major categories of mandatory spending programs, distributing benefits to those entitled to receive them. These four categories align with the following titles in the Farm Bill: Title I: Commodities; Title II: Conservation; Title XI: Crop Insurance; and the Supplemental Nutrition Assistance Program under Title IV: Nutrition. We present the Policy Design Lab, a comprehensive web platform for data visualization and analysis of policy data. The core goal is to better inform policymakers, the public and other stakeholders to improve policy understanding, as well as to provide comparative analysis of policy design alternatives and innovations. It provides a powerful tool for designing, considering and evaluating different scenarios by visualizing data and modeling the likely outcomes of the various designs. We describe the main modules of this web platform, the design and development process, and the integration of two models that support policy analysis and design.

Social construction is a theoretical position that social reality is created through the humans' definition and interaction as opposed to something that exists by default. As one type of social reality, juvenile delinquency is perceived as part of social problems, deeply contextualized and socially constructed in American society. The social construction of juvenile delinquency started far earlier than the first juvenile court in 1899 in the U.S. Scholars have tried traditional historical analysis to explore the timeline of the social construction of juvenile delinquency in the past, but it is inefficient to examine hundred years of documents using traditional paper-pencil documenting method. We propose to research, develop and apply image and text analysis methods to analyze hundreds of years of newspaper data and show a clear development of social construction of juvenile delinquency in American society. The project aims to explore questions around how the media started depicting certain types of juvenile behavior as delinquency, how they described those behaviors; who are those juveniles (age, race, gender, family background, community background, etc.), how other social institutions treat those juveniles in those stories; how the depiction of juvenile delinquency has changed during the past 100 years; whether the analysis results support social construction perspective in terms of juvenile delinquency or not. In this paper, we present our ongoing work of doing image analysis on the newspaper collection from the Library of Congress Chronicling America website, initial results, observations, current conclusions, and future work.