Colorado: Round 1 - State-Level Field Network Study of the Implementation of the Affordable Care Act

This report is part of a series of 21 state and regional studies examining the rollout of the ACA. The national network -- with 36 states and 61 researchers -- is led by the Rockefeller Institute of Government, the public policy research arm of the State University of New York, the Brookings Institution, and the Fels Institute of Government at the University of Pennsylvania.Colorado is one of fourteen states and the District of Columbia that elected to operate a state-based health insurance exchange and to expand Medicaid in 2014 as part of the rollout of the Affordable Care Act (ACA). These decisions are consistent with Colorado's approach to health care reform. Before the ACA was signed into law in 2010, the state had made incremental expansions in Medicaid eligibility and laid the groundwork for an insurance marketplace

Challenges and Good Practices in Conversational AI-Driven Service Automation

Conversational AI offers novel opportunities for companies to automate customer interactions. However, many companies grapple with effectively implementing conversational AI. Utilizing an engaged, consortium-based research approach, we examine the unique challenges faced by six companies in the insurance and banking sector while implementing conversational AI solutions and identify best practices to address these challenges. Finally, drawing upon the lessons learned, we offer guidance for developing conversational AI capabilities and fostering conversational AI success stories

In search of cues: dung beetle attraction and the significance of volatile composition of dung

Volatile organic compounds (VOCs) provide animals with multiple cues about location, type, and condition of valuable resources such as food. In particular, odour cues are often essential for the localization and discrimination of resources with patchy distribution. Dung beetles (Scarabaeoidea) rely on such scented resources to locate food for their own diet and to provision their progeny. Despite the beetles’ mostly generalist choice across dung types, several studies showed that the beetles prefer some dung types over others. Yet, the importance of VOCs for dung localization and differentiation remains unclear. In this study, we used six single chemical components (indole, skatole, phenol, butyric acid, 2-butanone, and p-cresol), two different blends of these components, and six different dung types for a detailed behavioural analysis of dung beetles. We found very little specialization of beetle species towards specific VOCs. We found that dung baits and baits with synthetic compounds attracted similar communities of dung beetles, but the visitors of synthetic baits exhibited much lower diversity and abundance. The analysis of dung scent profiles of six types of dung revealed both, unique patterns in composition and ubiquitous components such as p-cresol. However, when we used a six-component blend of synthetic compounds, it turned out to be as attractive as three of the most attractive dung types in the field. Our findings highlight the significance of key VOCs, but, moreover, that dung beetles use a blend of specific components for resource localization

An inbred line of the diploid strawberry Fragaria vesca f. semperflorens for genomic and molecular genetic studies in the Rosaceae

<p>Abstract</p> <p>Background</p> <p>The diploid woodland strawberry (<it>Fragaria vesca</it>) is an attractive system for functional genomics studies. Its small stature, fast regeneration time, efficient transformability and small genome size, together with substantial EST and genomic sequence resources make it an ideal reference plant for <it>Fragaria </it>and other herbaceous perennials. Most importantly, this species shares gene sequence similarity and genomic microcolinearity with other members of the Rosaceae family, including large-statured tree crops (such as apple, peach and cherry), and brambles and roses as well as with the cultivated octoploid strawberry, <it>F</it>. ×<it>ananassa</it>. <it>F. vesca </it>may be used to quickly address questions of gene function relevant to these valuable crop species. Although some <it>F. vesca </it>lines have been shown to be substantially homozygous, in our hands plants in purportedly homozygous populations exhibited a range of morphological and physiological variation, confounding phenotypic analyses. We also found the genotype of a named variety, thought to be well-characterized and even sold commercially, to be in question. An easy to grow, standardized, inbred diploid <it>Fragaria </it>line with documented genotype that is available to all members of the research community will facilitate comparison of results among laboratories and provide the research community with a necessary tool for functionally testing the large amount of sequence data that will soon be available for peach, apple, and strawberry.</p> <p>Results</p> <p>A highly inbred line, YW5AF7, of a diploid strawberry <it>Fragaria vesca </it>f. <it>semperflorens </it>line called "Yellow Wonder" (Y2) was developed and examined. Botanical descriptors were assessed for morphological characterization of this genotype. The plant line was found to be rapidly transformable using established techniques and media formulations.</p> <p>Conclusion</p> <p>The development of the documented YW5AF7 line provides an important tool for Rosaceae functional genomic analyses. These day-neutral plants have a small genome, a seed to seed cycle of 3.0 - 3.5 months, and produce fruit in 7.5 cm pots in a growth chamber. YW5AF7 is runnerless and therefore easy to maintain in the greenhouse, forms abundant branch crowns for vegetative propagation, and produces highly aromatic yellow fruit throughout the year in the greenhouse. <it>F. vesca </it>can be transformed with <it>Agrobacterium tumefaciens</it>, making these plants suitable for insertional mutagenesis, RNAi and overexpression studies that can be compared against a stable baseline of phenotypic descriptors and can be readily genetically substantiated.</p

Illuminating Smart City Solutions – A Taxonomy and Clusters

With urban problems intensifying, Smart City solutions are recognized by researchers and practitioners as one of the most promising solutions to make urban areas economically, environmentally, and socially sustainable. While many elements of Smart City solutions have been explored, existing works either treat Smart City solutions as technical black boxes or focus exclusively on Smart City solutions’ technical or non-technical characteristics. Therefore, to conceptualize the unique characteristics of Smart City solutions currently available, we developed a multi-layer taxonomy based on Smart City solution literature and a sample of 106 Smart City solutions. Moreover, we identified three clusters, each covering a typical combination of characteristics of Smart City solutions. We evaluated our findings by applying the Q-sort method. The results contribute to the descriptive knowledge of Smart City solutions as a first step for a theory for analyzing and enable researchers and practitioners to understand Smart City solutions more holistically

Demystifying Industrial Internet of Things start-ups – A multi-layer taxonomy

Described as a fundamental paradigm shift by researchers, the Industrial Internet of Things (IIoT) is credited with massive potential. In the context of emerging technologies, such as the IIoT, start-ups occupy a crucial role, as new technologies are often first commercialized by start-ups. Because of the rising importance of IIoT start-ups as drivers of industrial innovation, IIoT solutions demand deepened theoretical insights. As existing classification schemes in the industrial context do not sufficiently account for the ever more critical role of IIoT start-ups, we present a multi-layer taxonomy of IIoT start-up solutions. Building on state-of-the-art literature and a sample of 78 real-world IIoT start-up solutions, the taxonomy comprises ten dimensions and related characteristics structured along the three layers solution, data, and business model. The taxonomy contributes to the descriptive knowledge on the IIoT and enables researchers and practitioners to better understand IIoT start-up solutions