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"It is here our footsteps / we must trace:" Maine Indian Claims Settlement Act Anxiety Reflected In Indigenous and Non-Indigenous Literature Post-1980
No full textThe Maine Indian Claims Settlement Act of 1980 forced Maine residents to redefine their identities in relation to land, ownership, and heritage. The Act, built upon centuries of colonialism, disregard for legislature dictating protections for Indigenous peoples in the now United States of American, and illegal land transactions, struck fear in all Maine inhabitants as white Mainers feared their homes, and rights as American citizens, would be forfeited by a distant federal government, and members of the Wabanaki Confederacy – the Penobscot, Passamaquoddy, Mi’kmaq, and Maliseet – recognized the Act as colonialism in the modern-day. This thesis studies the cultural reaction of Maine residents by analyzing five works of literature by white and Indigenous Maine authors who discuss their outrage, anxiety, and interpretations of the MICSA post-1980 to determine how residents, rather than scholars or government officials, understood the implications of the legislation in their daily lives
Multi-wavelength observations of a jet launch in real time from the post-changing-look Active Galaxy 1ES 1927+654
No full textWe present results from a high cadence multi-wavelength observational campaign of the enigmatic changing look AGN 1ES 1927+654 from May 2022- April 2024, coincident with an unprecedented radio flare (an increase in flux by a factor of over a few months) and the emergence of a spatially resolved jet at pc scales (Meyer et al. 2024). Companion work has also detected a recurrent quasi-periodic oscillation (QPO) in the keV band with an increasing frequency ( mHz) over the same period (Masterson et al., 2025). During this time, the soft X-rays ( keV) monotonically increased by a factor of , while the UV emission remained near-steady with variation and the keV flux showed variation by a factor . The weak variation of the keV X-ray emission and the stability of the UV emission suggest that the magnetic energy density and accretion rate are relatively unchanged, and that the jet could be launched due to a reconfiguration of the magnetic field (toroidal to poloidal) close to the black hole. Advecting poloidal flux onto the event horizon would trigger the Blandford-Znajek (BZ) mechanism, leading to the onset of the jet. The concurrent softening of the coronal slope (from to ), the appearance of a QPO, and low coronal temperature ( keV) during the radio outburst suggest that the poloidal field reconfiguration can significantly impact coronal properties and thus influence jet dynamics. These extraordinary findings in real time are crucial for coronal and jet plasma studies, particularly as our results are independent of coronal geometry.The material is based upon work supported by NASA under award number 80GSFC21M0002. JS acknowledges the Czech Science Foundation project No.22-22643S. SL is thankful to Jay Friedlander who has created the graphics of the jet and the heated gas (Fig 6). Claudio Ricci acknowledges support from Fondecyt Regular grant 1230345 and ANID BASAL project FB210003. FR and SB acknowledge funding from PRIN MUR 2022 SEAWIND 2022Y2T94C, supported by European Union - Next Generation EU. SB acknowledges support from INAF LG 2023 BLOSSOM. Main Pal thanks the support of the Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune through the Visiting Associate Programme. Matt Nicholl is supported by the European Research Council (ERC) under the European Union抯 Horizon 2020 research and innovation programme (grant agreement No. 948381) and by UK Space Agency Grant No. ST/Y000692/1. SL, EM and EB acknowledge support from NSF-BSF grant numbers: NSF-2407801, BSF-2023752.http://arxiv.org/abs/2501.0234
Decentralized Federated Learning in Metacomputing Based on Directed Acyclic Graph with Optimized Tip Selector
No full textMetacomputing optimizes distributed computing resources to enhance federated learning systems by enabling efficient resource allocation, improved scheduling, and greater scalability, thereby addressing challenges in large-scale and dynamic environments. This paper proposes an innovative framework integrating Directed Acyclic Graph (DAG) technology with federated learning within a metacomputing environment. The key contributions include a three-layer decentralized federated learning model integrating DAG and metacomputing to enhance resilience and scalability, two advanced tip selection models LazyEval Tip Selector and Precision Tip Selector to optimize node selection and improve data flow, and a Benchmark Improvement Protocol (BIP) for efficient node publishing and role adaptation.The BIP ensures that only high-performing models are published by comparing new models against established benchmarks, which enhances node collaboration and optimizes resource allocation. LazyEval Tip Selector minimizes redundant computations by leveraging a global cache and employing a lazy evaluation strategy, thereby improving computational efficiency. On the other hand, Precision Tip Selector uses a precise scoring mechanism to ensure accurate tip selection, thereby enhancing the robustness and reliability of the entire system. Collectively, these innovations enhance model training efficiency, support real-time updates, and improve the scalability of federated learning systems, making them well-suited for managing complex, dynamic environments.This work was supported in part by Taishan Scholar Project under Grant tsqnz20230602, Natural Science Foundation of Shandong Province under Grant ZR2024MF115 and ZR2023LZH010, Youth Innovation University Team Project in Shandong under Grant 2022KJ062 and Independent Innovation Fund of China University of Petroleum (East China) under Grant 22CX06056A (Corresponding Author: Fei Luo).https://ieeexplore.ieee.org/abstract/document/1083510
A combined Quantum Monte Carlo and DFT study of the strain response and magnetic properties of two-dimensional (2D) 1T-VSe₂ with charge density wave
No full textTwo-dimensional (2D) 1T-VSe₂ has prompted significant interest due to the discrepancies regarding alleged ferromagnetism (FM) at room temperature, charge density wave (CDW) states and the interplay between the two. We employed a combined Diffusion Monte Carlo (DMC) and density functional theory (DFT) approach to accurately investigate the magnetic properties and response of strain of monolayer 1T-VSe₂. Our calculations show the delicate competition between various phases, revealing critical insights into the relationship between their energetic and structural properties. We went on to perform Classical Monte Carlo simulations informed by our DMC and DFT results, and found the magnetic transition temperature (Tc) of the undistorted (non-CDW) FM phase to be 228 K and the distorted (CDW) phase to be 68 K. Additionally, we studied the response of biaxial strain on the energetic stability and magnetic properties of various phases of 2D 1T-VSe₂ and found that small amounts of strain can enhance the Tc, suggesting a promising route for engineering and enhancing magnetic behavior. Finally, we synthesized 1T-VSe₂ and performed Raman spectroscopy measurements, which were in close agreement with our calculated results. Our work emphasizes the role of highly accurate DMC methods in advancing the understanding of monolayer 1T-VSe₂ and provides a robust framework for future studies of 2D magnetic materials.This work was supported by the National Science Foundation through the Division of Materials Research under NSF Grant No. DMR-2213398. The authors thank the National Institute of Standards and Technology for funding, computational, and data-management resources. Work by N.G. was supported by the National Institute of Standards and Technology Summer Undergraduate Research Fellowship program. Work by K.S. and J.T.K. (discussion, analysis of QMC calculations) was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, as part of the Computational Materials Sciences Program and Center for Predictive Simulation of Functional Materials. Work by T. B. (discussion, analysis of DFT+U calculations) was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. F.A. and B.D. would like to acknowledge the support of Mr. Peter Morrison and the Office of Naval Research under Contract No. N00014- 21-WX-01248. Research at the United States Naval Academy (M.E.J.) was supported by the Office of Naval Research under Contract No. N0001423WX02132.https://pubs.acs.org/doi/full/10.1021/acsnano.4c1591
Do Local Conditions Determine the Direction of Science? Evidence from Land Grant Colleges
No full textWe quantify the extent to which land grant colleges were located in counties that grow different crops than the rest of their states, which we call agricultural unrepresentativeness. We find that land grant colleges located in agriculturally unrepresentative counties tended to produce research focusing on more unrepresentative crops. We find similar results when exploiting historical college site selection natural experiments to identify exogenous variation in the agricultural unrepresentativeness of the college county. Moreover, we find that colleges in agriculturally unrepresentative locations created more geographically limited productivity spillovers.https://www.sciencedirect.com/science/article/pii/S001449832500016
Custom multi-component force transducer design using topology optimization
No full textThis paper proposes an innovative design framework for a multi-component force transducer subject to reversible load direction using topology optimization. Multi-component force transducers are used widely in industries ranging from robotics to healthcare. In this work, the proposed design framework is applied to a specific force transducer, a wind tunnel balance used within aeronautic ground testing. The axial component is one of the six components of the wind tunnel balance, and this component is difficult to design because the axial force is typically much smaller than other force components. This paper uses topology optimization to obtain a non-intuitive axial component design. To realize the design requirements, a new design formulation is suggested to amplify the gauge reading under a small axial loading and to suppress the gauge reading under nonaxial loadings. Prototypes are manufactured and their performances are experimentally verified. The proposed framework can be applied to any type of force transducer that needs to amplify a response from a certain force and to suppress the other responses.The authors gratefully acknowledge NASA Langley Research Center and the National Institute of Aerospace for their support from Prime Contract No. NNL13AA08B, Subcontract No. T19-601049-UMBC.https://iopscience.iop.org/article/10.1088/2631-8695/ada33e/met
YOLO based Ocean Eddy Localization with AWS SageMaker
No full textOcean eddies play a significant role both at the sea surface and beneath it, contributing to the sustainability of marine ecosystems and influencing broader oceanic and climatic behaviors. Investigating ocean eddies is essential for monitoring changes in the Earth’s oceans and their impact on climate. This study focuses on benchmarking the performance of state-of-theart YOLO (You Only Look Once) models for locating small-scale (<20km) ocean eddies using satellite remote sensing images. We leverage AWS SageMaker for this evaluation, utilizing both single and multi-GPU configurations to explore the feasibility and efficiency of deploying AI applications in cloud-based environments. This research not only assesses the effectiveness of SageMaker in handling complex Earth science data but also provides insights into deployment challenges, resource management for large-scale data, and the overall user experience. The findings highlight the strengths and limitations of using SageMaker for remote sensing applications and suggest potential future research directions. Our code is open-sourced at https://shorturl.at/hcjmq.https://ieeexplore.ieee.org/abstract/document/1082528
The hybrid approach to monitoring: a remote Rapid Assessment Protocol (RAP) complements existing monitoring tools for oyster restoration and management
No full textAccurate and efficient monitoring of oyster reefs is critical for fisheries management and restoration. However, monitoring subtidal reefs requires labor-intensive methods, such as sampling by SCUBA divers. A new Rapid Assessment Protocol (RAP) based on the collection of underwater imagery from random replicate points across a reef expands the toolkit for oyster reef monitoring. This study tests how the qualitative RAP compares to existing quantitative monitoring tools to inform approaches that combine methods and improve monitoring. We surveyed paired unrestored harvested reefs and restored sanctuary oyster reefs in the upper, middle, and lower Chesapeake Bay (United States) to compare the RAP to diver-collected oyster metrics across management types and salinities. At each site, we compared the RAP's categorical habitat scores (based on percent cover and relative reef height in images) with physical metrics from synchronous diver collections, including live oyster density and biomass, on the same reef quadrats (n = 64). High RAP scores successfully captured high oyster density, biomass, reef height, rugosity, and multiple size classes. At lower RAP scores, the physical metrics often differed between RAP scores on unrestored harvested reefs, but not restored sanctuary reefs. This study highlights the value of underwater video in increasing monitoring efficiency with respect to time investment, while providing different habitat data than physical metrics. We describe how the RAP can be used in combination with more intensive, physical monitoring tools for restoration and fisheries management. The results of the RAP can inform oyster management in Chesapeake Bay and can be adapted for use worldwide.We would like to acknowledge assistance in site selection fromR. Lipcius, J. Lazar, and D. Schulte, as well as assistance withfield data collection by K. Richie and J. Olsen. Z. Anchondoprovided tributary-specific biomass data. We thank the RAPworkgroup for feedback: A. Colden, D. Myers, R. Lipcius,L. Kellogg, R. Seitz, R. Burke, S. Coleman, O. Caretti,J. Lazar, D. Bruce, J. Spires, and S. Westby. We also thank theNational Oceanic and Atmospheric Administration (NOAA)Chesapeake Bay Office, Maryland Oyster Workgroup, and Vir-ginia Oyster Workgroup for feedback. A.M.T. was funded byNOAA Award NA21NMF0080474.https://onlinelibrary.wiley.com/doi/abs/10.1111/rec.1437
Astronomers Observe Real-time Formation Of Black Hole Jets For The First Time
No full textPhotographer - Marlayna Demondhttps://umbc.edu/stories/black-hole-jets-observed-forming-in-real-time
Water Flow Detection Device Based on Sound Data Analysis and Machine Learning to Detect Water Leakage
No full textIn this paper, we introduce a novel mechanism that uses machine learning techniques to detect water leaks in pipes. The proposed simple and low-cost mechanism is designed that can be easily installed on building pipes with various sizes. The system works based on gathering and amplifying water flow signals using a mechanical sound amplifier. Then sounds are recorded and converted to digital signals in order to be analyzed. After feature extraction and selection, deep neural networks are used to discriminate between with and without leak pipes. The experimental results show that this device can detect at least 100 milliliters per minute (mL/min) of water flow in a pipe so that it can be used as a core of a water leakage detection system.http://arxiv.org/abs/2501.1115