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Conference
BIS

“Visualizing Aggregated Biological Pathway Relations”

The Genescene development team has constructed an aggregation interface for automatically-extracted biomedical pathway
relations that is intended to help researchers identify and process relevant information from the vast digital library of abstracts found in the National Library of Medicine’s PubMed collection.
Users view extracted relations at various levels of relational granularity in an interactive and visual node-link interface. Anecdotal feedback reported here suggests that this multigranular visual paradigm aligns well with various research tasks,
helping users find relevant articles and discover new information.
Details
Academic Journal
BIS

“Visualizing Basic Accounting Flows: Does XBRL + Model + Animation = Understanding?”

The usefulness of XBRL (eXtensible Business Reporting Language) in facilitating efficient data sharing is clear, but widespread use of XBRL also promises to support more effective analysis processes. This format should allow managers, investors, regulators, and students to aggregate, compare and analyze financial information. This study explores an XBRL-based visualization tool that maps the organization of financial statements captured in the XBRL formalism into a graphical representation that organizes, depicts, and animates financial data. We show that our tool integrates and presents profitability, liquidity, financing, and market value data in a manner recognizable to business students. Our findings suggest the promise of XBRL-based visualization tools both in helping students grasp basic accounting concepts and in facilitating financial analysis in general.
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Conference
BIS

“Visualizing basic accounting flows: does XBRL + model + animation = understanding?”

The usefulness of XBRL (eXtensible Business Reporting Language) in facilitating efficient data sharing is clear, but widespread use of XBRL also promises to support more effective analysis processes. Representing traditional financial statements in this electronic and interoperable format should allow managers, investors, regulators, and importantly students to aggregate, compare and analyze financial information. Processing such data requires an understanding of the underlying paradigms embedded in consolidated sets of financial statements. This work explores the feasibility and effectiveness of an XBRL-based visualization tool, presenting an organizational framework, mapping that framework to financial statements and the XBRL formalism, and demonstrating a visual representation that organizes, depicts, and animates financial data. We show that our tool integrates and presents profitability, liquidity, financing, and market value data in a manner recognizable to business students in introductory financial accounting classes. This preliminary finding suggests the promise of XBRL-based visualization tools both in helping students grasp basic accounting concepts and in facilitating financial analysis in general.
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Academic Journal
Business Law

“Watered Down Voices, Watered Down Justice: A Demand for Polycentricism, Demosprudence, and Praxis in WOTUS Regulatory Reform”

For decades, science has demonstrated that discrete populations have been disproportionately forced to suffer the horrors of living in areas contaminated by toxic and hazardous substances. Communities of color, indigenous communities, and other marginalized communities continuously endure the effects of multigenerational water, air, and land pollution. Whether intentionally or not, EPA and regulatory elites have promulgated so-called “neutral rules” that have resulted in a systemic and ever-expanding national environmental caste. For this to end, EPA must stop being a knowing or unknowing participant in regulatory oppression and become an active agent of regulatory change.
EPA is required to take environmental justice concerns into account when promulgating new regulations; amplifying the voices of traditionally subordinated affected communities is an essential element of this goal. Nevertheless, EPA lacks a systematic method to incorporate direct outreach to and engagement of impacted communities, and has no detailed outline or specific strategy to ensure that the voices of impacted communities are heard. Thus, the Trump Administration was able to promulgate new regulations related to the definition of “waters of the United States” (WOTUS) that are likely to have significant negative impacts on water quality, much of which will be borne by disenfranchised communities, while affording those communities little to no voice in the regulatory process.
This Article maintains that the Biden EPA should adopt a sociolegal approach, informed by the theoretical principles of polycentrism and demosprudence, to address systematic and decades-long environmental injustices. This approach would help shift and redistribute power from environmental regulatory elites to the people most affected by environmental harms. Using the case study of WOTUS regulatory reform, we argue that the Biden EPA has a perfect opportunity to create a more inclusive regulatory process that expands the power of historically disenfranchised people, while addressing known harms that will result from the current regulations. The Biden EPA could use WOTUS reform to establish a new paradigm for expanding the power of non-elites and create a model for a more equitable form of regulatory decision-making and a more democratic form of governance.
Details
Academic Journal
Supply Chain

“Watt’s Next: Navigating the Surge in Electric Vehicle Adoption and its Implications for Grid Operations”

As policy decisions pave the way for more Electric Vehicles (EVs) on the road, there is expected to be a tremendous strain on the utility grid. Managing this strain requires careful planning for (and possibly control of) EV charging. This may include the utility firm managing intra-day demand variations using grid-scale batteries, and influencing the charging operations of some fraction of EVs (via active or passive managed charging program), including the possible use of Vehicle-to-Grid (V2G) technologies. A managed charging program must be carefully designed, accounting for EV users' driving patterns and range anxieties. In this paper, we take the perspective of an integrated energy system planner, who seeks to minimize generation and emissions costs arising from the electricity and transpotation sectors. Using a stylized analytical model that considers two periods per day (peak and off-peak), we derive optimal grid operations in the presence of a fraction of EV owners who sign up to a managed charging program. We characterize the optimal operating policy and show that EVs and grid-scale batteries can be substitutes or complements in the energy planner's portfolio. We demonstrate the validity of all our findings numerically using a higher fidelity 24-hour model calibrated to real data from the PJM interconnection. Our results suggest that a long-term outlook on navigating EV adoption should focus on managing more EV charging, rather than installing a lot of stationary battery capacity or promoting V2G.
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Academic Journal
Business Analytics

“Wavelet Methods in Interpolation of High-Frequency Spatial-Temporal Pressure”

The location-scale and whitening properties of wavelets make them more favorable for interpolating high-frequency monitoring data than Fourier-based methods. In the past, wavelets have been used to simplify the dependence structure in multiple time or spatial series, but little has been done to apply wavelets as a modeling tool in a space–time setting, or, in particular, to take advantage of the localization of wavelets to capture the local dynamic characteristics of high-frequency meteorological data. This paper analyzes minute-by-minute atmospheric pressure data from the Atmospheric Radiation Measurement program using different wavelet coefficient structures at different scales and incorporating spatial structure into the model. This approach of modeling space–time processes using wavelets produces accurate point predictions with low uncertainty estimates, and also enables interpolation of available data from sparse monitoring stations to a high density grid and production of meteorological maps on large spatial and temporal scales.
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