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Stepping Out On Your Algorithm -- A Love Letter
No full textWhether it is news or music, algorithms run by streaming platforms deliver us content and it gets stale and dangerous. For this Valentine's Day episode, Sunil Dasgupta talks with Poolesville, MD, resident Kevin Schramm about how he finds music regularly. Sampled music from: Stella, Magdalena Bay, Waxahatchee, MJ Lenderman, Beverly Glenn Copeland, Nourished by Time, Parannoul, Lexa Gates, William Onyeabor.https://open.spotify.com/episode/4efdmXvW6uYNBX4kIngFe
Impact of Infrastructure Investment on Port Efficiency: A Case Study of Queen Elizabeth II Quay, Sierra Leone
No full textThis study investigates the impact of infrastructure investment on port efficiency, focusing on Queen Elizabeth II Quay, in Sierra Leone. Using a mixed-methods approach, including Data Envelopment Analysis (DEA), regression analysis, and stakeholder surveys, the study evaluates the effects of infrastructure upgrades on operational efficiency, cargo throughput, and economic growth. Key findings highlight significant improvements, such as a 25% reduction in vessel turnaround times and a 30% increase in annual container throughput, attributed to investments in modern cargo handling equipment, berth expansions, and ICT systems. The study also highlights challenges, like maintenance limitations, insufficient finance, and regulatory inefficiencies, which jeopardize the long-term viability of these enhancements. Environmental factors, such as emissions from enhanced equipment, highlight the necessity of using sustainable technologies. Recommendations highlight the need to fortify public-private partnerships, improve governance structures, and include sustainable practices in forthcoming growth strategies. This study offers practical recommendations for politicians and port authorities, promoting a comprehensive strategy for infrastructure investment that harmonizes operational efficiency, stakeholder contentment, and environmental sustainability.https://www.scirp.org/journal/paperinformation?paperid=14114
Neural network-based surrogate model in postprocessing of topology optimized structures
No full textThis paper proposes a general method of creating an accurate neural network-based surrogate model for postprocessing a topologically optimized structure. When topology optimization results are converted into computer-aided design (CAD) files with smooth boundaries for manufacturability, finite element method (FEM) based stresses often do not agree with the topology optimized results due to changes of surface and mesh density. The conversion between topology optimization derived results and CAD files often requires postprocessing, an additional fine tuning of the geometry parameters to reconcile the change of the stress values. In this work, a feedforward, deep artificial neural network (DANN) is presented with varying architecture parameters that are found for each stress output of interest. This network is trained with the data based on a combination of Design of Experiments (DoE) models that have the geometry dimensions as inputs and stress readings under various loads as the outputs. A DANN-based surrogate model is constructed to enable fine tuning of all relevant stress performance metrics. This method of constructing an artificial network-based surrogate model minimizes the number of FEM computations required to generate an optimized, post-processed design. We present a case study of postprocessing a wind tunnel balance, a measurement device that yields the six force and moment components of a test aircraft. It needs to be designed considering multiple stress measures under combinations of the six loading conditions. Excellent performance of a neural network is presented in this paper in terms of accurate prediction of the highly nonlinear stresses under combinations of the six loads. Von Mises stress predictions are within 10% and axial force sensor stress predictions are within 2% for the final post-processed topology. The results support its usefulness for postprocessing of topology optimized structures.This work was supported by the National Aeronautics and Space Administration (NASA) Langley Research Center [Internship contract numbers 011042, 012053, 012951, 014070, 015326, 016042]https://link.springer.com/article/10.1007/s00521-025-11039-
To Create Is to Learn: An Examination of Experimental Archaeology Through Recreations of Preclassic and Early Classic Maya Chocolate Pots
No full textA history and discussion of experimental archaeology, followed by experiments in recreating Preclassic and Early Classic Maya chocolate pots
Understanding the Lived Experiences of Highly Educated African Immigrants in the United States: A Case Study of Nigerians Living in Maryland.
No full textD.P.A. -- The University of Baltimore, 2025Public Scholarship Project submitted to the College of Public Affairs of The University of Baltimore in partial fulfillment of the requirements for the degree
of Doctor of Public AdministrationThis study explores the underemployment of highly educated Nigerian immigrants in the United States, with a specific focus on those residing in Maryland. Despite possessing advanced academic qualifications and professional expertise, many Nigerian immigrants face systemic barriers that hinder the full utilization of their skills. The study adopts a qualitative research design in which inquiry draws on semi-structured interviews with purposefully selected participants and utilizes narrative analysis to interpret lived experiences. The study investigates the push and pull factors driving immigration, the professional challenges encountered in the host country, and the strategies employed to navigate cultural assimilation and social integration. Findings indicate that credential non-recognition, institutional discrimination, and restrictive immigration frameworks are critical obstacles to career advancement. Participants' narratives also reveal resilience and adaptation in the face of cultural dissonance, economic pressures, and identity negotiation. The research offers a nuanced understanding of how highly educated Nigerian immigrants reconstruct their professional identities while striving for economic and social mobility. Policy recommendations include reforms in foreign credential evaluation, inclusive labor market policies, and culturally responsive support systems to enhance immigrant career integration and fulfillment in the United States.https://www.africanimmigrantsproject.com
I Hate the News Mar 4
No full textThe weekly news analysis from I Hate Politics: Maryland and Virginia ask laid off federal workers to seek state jobs. Will former federal employees sign up to be public school teachers where staff shortage is acute? The Maryland State Department of Education proposes an overhaul of the high school math curriculum. Could it impact parent-favorite accelerated math instruction in elementary school? Illegal dumping in DC and Prince George’s County remains a problem. How to “buy” renewable energy without putting rooftop solar or depending on retail energy suppliers? Music by Washington DC area composer Anna Rubin.https://open.spotify.com/episode/61I4ccUrrxB0qWfUEDq8v
Effects of fire and grazing on biogeochemical cycles in Brazilian pastures using LPJmL5-Pasture-Burning
No full textAbstract. Farmers across the world frequently use fire during the winter or dry season, to remove accumulated dead pasture biomass. These fire-management practices have profound effects on vegetation, soil nutrients, and biogeochemical cycles, yet they are rarely represented in process-based fire models embedded within Dynamic Global Vegetation Models (DGVMs). We couple the Chalumeau algorithm, which estimates expected burning dates, with the SPITFIRE module in the DGVM LPJmL and enable the modelling of fire as a grassland management method. Using this model development, we examine the short- and long-term impacts of varying burning strategies, frequencies, and livestock densities across distinct regions, using Brazil as a case study. Our results show that integrating grazing and fire management leads to a gradual decline in vegetation carbon, accompanied by a substantial reduction of the ecosystem and soil nitrogen. This study emphasises the importance of incorporating such practices into DGVMs to enhance the accuracy of impact assessments for pasture management. Furthermore, our findings call for improved data collection describing fire usage methods by farmers, as well as long-term measurements, particularly on vegetation, soil carbon and nitrogen development under burning practices.The authors gratefully acknowledge the European Regional Development Fund (ERDF), the German Federal Ministry of Education and Research, and the Land Brandenburg for supporting this project by providing resources on the high-performance computing
system at the Potsdam Institute for Climate Impact Research. AI algorithms were used during the writing process to assist with English spelling, formulation, and syntax.https://egusphere.copernicus.org/preprints/2025/egusphere-2025-922
Fermi-detection of gamma-ray Emissions from the Hot Coronae of Radio-quiet Active Galactic Nuclei
No full textAuthors: (Fermi-LAT Collaboration) - Jun-Rong Liu, Jian-Min Wang, and S. Abdollahi, M. Ajello, R. Alves Batista, L. Baldini, C. Bartolini, D. Bastieri, J. Becerra Gonzalez, R. Bellazzini, B. Berenji, E. Bissaldi, R. D. Blandford, R. Bonino, P. Bruel, S. Buson, R. A. Cameron, P. A. Caraveo, E. Cavazzuti, G. Chiaro, N. Cibrario, S. Ciprini, P. Cristarella Orestano, S. Cutini, F. D’Ammando, N. Di Lalla, A. Dinesh, L. Di Venere, A. Domínguez, S. J. Fegan, A. Fiori, A. Franckowiak, Y. Fukazawa, S. Funk, P. Fusco, F. Gargano, C. Gasbarra, D. Gasparrini, S. Germani, N. Giglietto, M. Giliberti, F. Giordano, M. Giroletti, D. Green, I. A. Grenier, S. Guiriec, M. Hashizume, E. Hays, J.W. Hewitt, D. Horan, Xian Hou, C. Karwin, T. Kayanoki, M. Kuss, A. Laviron, M. Lemoine-Goumard, Jian Li†, I. Liodakis, F. Longo, F. Loparco, L. Lorusso, P. Lubrano, S. Maldera, L. Marcotulli, G. Martí-Devesa, M. N. Mazziotta, I. Mereu, P. F. Michelson, N. Mirabal, W. Mitthumsiri, T. Mizuno, M. E. Monzani, T. Morishita, A. Morselli, I. V. Moskalenko, M. Negro, R. Niwa, N. Omodei, M. Orienti, E. Orlando, J. F. Ormes, D. Paneque, G. Panzarini, M. Persic, M. Pesce-Rollins, R. Pillera, T. A. Porter, G. Principe, S. Rainò, R. Rando, B. Rani, M. Razzano, A. Reimer, O. Reimer, M. Sanchez-Conde, P. M. Saz Parkinson, D. Serini, C. Sgrò, E. J. Siskind, G. Spandre, P. Spinelli, D. J. Suson, H. Tajima, J. B. Thayer, D. F. Torres, Zi-Hao ZhaoRelativistic jets around supermassive black holes are well-known powerful γ-ray emitters. In the absence of the jets in radio-quiet active galactic nuclei, how the supermassive black holes work in γ-ray bands is still unknown despite great observational efforts in the past three decades. Here, considering the previous efforts, we carefully select an active galactic nucleus sample composed of 37 nearby Seyfert galaxies with ultrahard X-rays for γ-ray detection by excluding all potential contamination in this band. Adopting a stacking technique, we report the significant γ-ray detection (test statistic 30.6, or 5.2σ) from the sample using 15-year Fermi-LAT observations. We find the average γ-ray luminosity of the sample to be (1.5 ± 1.0) × 10⁴⁰ erg s⁻¹ at energies of 1–300 GeV. Limited by the well-known pair production from the interaction of γ-rays with low-energy photons, γ-rays of more than several giga-electronvolts are found to originate from an extended corona (~2.7 × 10⁶ gravitational radii), whereas the canonical much more compact X-ray corona (~10 gravitational radii) is responsible for γ-rays of one to several giga-electronvolts. The finding of the compact region lends strong support to the long-time theoretical expectations, but the extended corona is an unexpected finding. One promising scenario is that the electron–positron pairs produced in the compact X-ray corona would expand as a fireball, similar to that in γ-ray bursts, forming the structure of extended corona.The Fermi-LAT Collaboration acknowledges support for LAT development, operation and data analysis from NASA and DOE (United States), CEA/Irfu and IN2P3/CNRS (France), ASI and INFN (Italy), MEXT, KEK, and JAXA (Japan), and the K.A. Wallenberg Foundation, the Swedish Research Council and the National Space Board (Sweden). Science analysis support in the operations phase from INAF (Italy) and CNES (France) is also gratefully acknowledged. This work performed in part under DOE Contract DE-AC02-76SF00515. Useful discussions are acknowledged with P. Du, Y.-R. Li, Y.-J. Chen and Y.-L. Wang from IHEP AGN Group. We thank the support from NSFC(-12333003, -12273038, -11991050, -11991054), from the National Key R&D Program of China (2020YFC2201400, 2021YFA1600404).https://www.nature.com/articles/s41550-025-02538-
A Participatory and Multi-Format Approach to Introducing Undergraduates to Archival Research
No full texthttps://newprairiepress.org/ebooks/5
Nonlinearities and Heterogeneity in Firms Response to Aggregate Fluctuations: What Can We Learn From Machine Learning?
No full textFirms respond heterogeneously to aggregate fluctuations, yet standard linear models impose restrictive assumptions on firm sensitivities. Applying the Generalized Random Forest to U.S. firm-level data, we document strong nonlinearities in how firm characteristics shape responses to macroeconomic shocks. We show that nonlinearities significantly lower aggregate responses, leading linear models to overestimate the economy's sensitivity to shocks by up to 1.7 percentage points. We also find that larger firms, which carry disproportionate economic weight, exhibit lower sensitivities, leading to a median reduction in aggregate economic sensitivity of 52%. Our results highlight the importance of accounting for nonlinearities and firm heterogeneity when analyzing macroeconomic fluctuations and the transmission of aggregate shocks.https://marcoerrico.github.io/marcoerrico/EPP_2025_February.pd