MARS
MARS is a repository service of Mason Publishing and the Data and Digital Scholarship Services (DDSS) at the George Mason University Libraries. MARS provides enduring, stable, well-indexed access to a wide range of scholarship from the Mason community, such as Electronic Theses and Dissertations (ETDs), articles, presentations, reports, and creative work. Learn more about publishing, sharing, and preserving research data with the George Mason University Institutional Dataverse, and our other repository services.
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Recent Submissions
Congressional Budget Scoring Reform: Improving Transparency and Accuracy
Lin, Yenting
This paper addresses a persistent and dangerous loophole in the U.S. budget process: the lack of transparency and accountability in fiscal scoring. As the 2025 tax debate looms, we argue that current practices around budget estimates are not only misleading but structurally enable irresponsible policymaking.
Our research shows how selective use of assumptions, inconsistent methodologies, and partisan incentives have eroded public trust and undermined the credibility of fiscal policy. In response, we propose a targeted, rule-based reform package to strengthen fiscal transparency and restore democratic accountability. Specifically, we call for (1) the mandatory public disclosure of budget scoring assumptions, (2) the requirement of both static and dynamic scoring for all major legislation, and (3) the creation of a bipartisan oversight board to monitor and enforce compliance. By illuminating how opaque budget scoring practices distort economic debates and shield lawmakers from fiscal consequences, we make the case for urgent structural reform.
Without these changes, the 2025 tax negotiations risk repeating past failures—producing policies that are fiscally unsound, politically polarizing, and democratically unaccountable.
GEWEX Quarterly, Vol. 33, No. 4
(2023-11) Polcher, Jan; Byrnes, Danyka; Becker, Paige; Koren, Gerbrand; Attig Bahar, Faten; Rabanal, Valentina; YESS Executive Committee; Isemer, Hans-Jörg; Schmetz, Johannes; Dera, Jerzy; Keevallik, Sirje; Meier, Markus; Omstedt, Anders; Quante, Markus; Reckermann, Marcus; Rockel, Burkhardt; Vonder Haar, Thomas; Stackhouse, Paul; Rossow, William B.; Hao, Dalei; Sinha, Eva; Bond-Lamberty, Ben; Taylor, Patrick C.; Schmidt, Sebastian; van Oevelen, Peter; Zeng, Xubin; Verhoef, Anne; Findell, Kirsten L.; Sobolowski, Stefan; Prein, Andreas F.; Mayer, Stephanie; Sorteberg, Asgeir; Rasmussen, Roy; Hendricks Franssen, Harrie-Jan; Zeng, Yijian
This issue of GEWEX Quarterly contains the articles on the following: a commentary on creating a shared vocabulary for the climate science community; an elevator pitch workshop and more offerings from H3S; looking at global inequalities in environmental research and balancing data-intensive and fundamental climate research with YESS; a tribute to Ehrhard Raschke, a founder of BALTEX, ISCCP, and BSRN, as well as an early SSG member; coupling human and Earth system models in E3SM-GCAM; the ARCSIX campaign to investigate the influences of radiation-cloud-aerosol-sea ice coupling in the Arctic climate system; a report from the GEWEX SSG-35 meeting held in Santiago, Chile; focusing on the importance of observations to assess model behavior, improving parameterizations, and understanding how land-atmosphere interactions are changing in a warming world during the 2023 GLASS Panel Meeting in Hohenheim, Germany; convection-permitting modeling for mountainous and high latitudes at the 7th Convection-Permitting Modeling Workshop; and the latest in land surface modeling trends, developments, and opportunities.
Graphene Oxide-Based Resistive Humidity Sensor for Non-Contact Monitoring of Human Breathing Patterns
(2025-05-12) Naemidehkharghani, Mehrdad; Peixoto, Nathalia
This work presents a simple, low-cost, and effective resistive humidity sensor based on graphene oxide for monitoring human breathing patterns in a non-contact manner. The sensor was fabricated by drop-casting a graphene oxide suspension onto a commercial Zensor TE100 platform with printed electrodes. A voltage divider circuit paired with an op-amp was used to convert the sensor’s resistance changes into measurable voltage signals, which were recorded using MATLAB’s analog input interface. The sensor reliably detected various breathing patterns—mouth and nasal breathing, single and continuous cycles, and both low- and high-intensity airflow. Results show that exhaled humidity significantly decreases the sensor’s resistance, producing a clear signal during each breath. Notably, high-intensity exhalation led to baseline drift, likely due to deeper water molecule adsorption within the porous graphene oxide structure. This behavior highlights the material’s sensitivity and reveals both opportunities and challenges for long-term respiration monitoring. Overall, the study demonstrates the potential of graphene oxide humidity sensors for wearable or ambient respiratory health monitoring applications.
IMU Position Tracking Improvement Through Filtering
(2025-05-12) Krush, Chris; Szuscik, Julian; Peixoto, Nathalia
When GPS, GNSS, or other position reporting systems cannot be used, position can be estimated through a process called dead reckoning. The position is calculated by taking a previously known position and using acceleration and velocity to determine the current position. Inertial Measurement Units (IMU) can be used for such applications. IMUs report the acceleration acting on the sensor. This measurement is then integrated once to give velocity and then again to give position. Due to the multiple layers of integration to get position data out of the sensor, noise and offset cause compounding error in the estimated position[2]. These adverse effects on the output of the IMU can be mitigated through filtering. This project implements three different types of filters and compares the position tracking results. The filters implemented are low/band-pass filtering, linear fitting, and Kalman filter as described in Robust M-M unscented Kalman filtering for GPS/IMU navigation [1].
Smart Occupancy Monitoring
(2025-05-10) Mandale, Rutuja Prakash; Peixoto, Nathalia
Retrieving real-time or historic occupancy and environmental conditions data of public spaces still need significant developments. The Smart Occupancy Monitoring (SOM) system addresses this by proposing an end-to-end solution. IoT-enabled devices equipped with sensors collect occupancy and temperature data, transmitted via MQTT for real-time analysis. A centralized dashboard visualizes space utilization and environmental metrics, enhancing operational efficiency and user experience. Testing across enclosed and open spaces demonstrated over 20% energy savings and improved space utilization by 4%. Future enhancements include battery operated devices and network-independent operations.