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Articles 90541 - 90570 of 5205434
Full-Text Articles in Entire DC Network
Vultures, Bryan M. Kluever, Lee A. Humberg, Scott C. Barras
Vultures, Bryan M. Kluever, Lee A. Humberg, Scott C. Barras
Wildlife Damage Management Technical Series
Fact sheet about vultures including information about human--wildlife conflicts, the vulture roost, affects on livestock, structures, human health and safety, identification of damage, management methods, legal considerations, and economics. Also included is an overview of the species.
Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Bruce I. Dvorak, David M. Admiraal, Pavel Shrestha
Characterization Of Sediment Loads And Size Distribution In Nebraska Roadway Runoff, Bruce I. Dvorak, David M. Admiraal, Pavel Shrestha
Nebraska Department of Transportation: Research Reports
The Nebraska Department of Transportation (NDOT) must manage sediment, and pollutant loads from roadway runoff to meet stormwater regulations. The SAFL Baffle, a hydrodynamic separator used by NDOT, depends on reliable estimates of total suspended solids (TSS) and particle size distribution (PSD). However, limited data exists for Nebraska roadways. In this study stormwater runoff was monitored at four NDOT-maintained sites, two in Lincoln and two in Beatrice, over 1.5 years to characterize TSS and PSD and to evaluate SAFL Baffle performance using the SHSAM model. Results showed large variability across sites and seasons. Median TSS ranged from 158 to 580 …
26 Conference - Advancing Manufacture Of Cell And Gene Therapies Ix, John Moscariello, Corinne Hoesli, Bruno Marques
26 Conference - Advancing Manufacture Of Cell And Gene Therapies Ix, John Moscariello, Corinne Hoesli, Bruno Marques
Advancing Manufacture of Cell and Gene Therapies IX [2026]
No abstract provided.
A Runtime-Adaptive Transformer Neural Network Accelerator On Fpgas, Ehsan Kabir, Jason D. Bakos, David Andrews, Miaoqing Huang
A Runtime-Adaptive Transformer Neural Network Accelerator On Fpgas, Ehsan Kabir, Jason D. Bakos, David Andrews, Miaoqing Huang
Electrical Engineering and Computer Science Faculty Publications and Presentations
Transformer neural networks (TNN) excel in natural language processing (NLP), machine translation, and computer vision (CV) without relying on recurrent or convolutional layers. However, they have high computational and memory demands, particularly on resource constrained devices like FPGAs. Moreover, transformer models vary in processing time across applications, requiring custom models with specific parameters. Designing custom accelerators for each model is complex and time-intensive. Some custom accelerators exist with no runtime adaptability, and they often rely on sparse matrices to reduce latency. However, hardware designs become more challenging due to the need for application-specific sparsity patterns. This paper introduces ADAPTOR, a …
The Religious Groups Of Mecca And Medina In The Sixth And Seventh Centuries Ce, Ilkka Linstedt
The Religious Groups Of Mecca And Medina In The Sixth And Seventh Centuries Ce, Ilkka Linstedt
Abdou Filali-Ansary Occasional Paper Series
Ancient and modern urban centres have been important loci for encounters between individuals of different identities. In this article, I present Mecca and Medina as multi-religious towns in the pre-Islamic and early Islamic periods of the sixth and seventh centuries ce. Mecca was a very small town, but the Kaaba shrine there served as a regional pilgrimage site that drew people from different faith communities. Medina was a larger settlement with a significant Jewish population. Jews, Christians and others (‘pagans’) lived in both towns. Some of these ‘others’ had also adopted some of the basic ideas of monotheism, although they …
M 221.01: Introduction To Linear Algebra, Emily F. Stone
M 221.01: Introduction To Linear Algebra, Emily F. Stone
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Hth 475e.01: Legal And Ethical Issues In Health And Exercise Professions, Charles G. Palmer
Hth 475e.01: Legal And Ethical Issues In Health And Exercise Professions, Charles G. Palmer
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 584.01: Topics In Combinatorics And Optimization - The Probablistic Method, Cory T. Palmer
M 584.01: Topics In Combinatorics And Optimization - The Probablistic Method, Cory T. Palmer
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 225.01: Introduction To Discrete Mathematics, Esmaeil Parsa
M 225.01: Introduction To Discrete Mathematics, Esmaeil Parsa
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 462.01: Theoretical Big Data Analysis, Javier Perez-Alvaro
M 462.01: Theoretical Big Data Analysis, Javier Perez-Alvaro
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Kin 441.01: Seminar In Sport Psychology, Melanie L. Mcgrath
Kin 441.01: Seminar In Sport Psychology, Melanie L. Mcgrath
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Nutr 441.01: Nutrition For Sport And Exercise, Charles L. Dumke
Nutr 441.01: Nutrition For Sport And Exercise, Charles L. Dumke
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 151.01: Precalculus, Esmaeil Parsa
M 151.01: Precalculus, Esmaeil Parsa
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Stat 342.01: Probability And Simulation, Jakob B. Oetinger
Stat 342.01: Probability And Simulation, Jakob B. Oetinger
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 491.01: The Geometry Of Surfaces, Eric B. Chesboro
M 491.01: The Geometry Of Surfaces, Eric B. Chesboro
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Hhp 525.01: Advanced Biomechanics, Matthew W. Bundle
Hhp 525.01: Advanced Biomechanics, Matthew W. Bundle
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 121.01: College Algebra, Apala Mandal
M 121.01: College Algebra, Apala Mandal
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 567.01: Advanced Big Data Analytics Projects, Javier Perez-Alvaro
M 567.01: Advanced Big Data Analytics Projects, Javier Perez-Alvaro
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Kin 447.01: Professional Writing In Integrative Physiology, Melanie L. Mcgrath
Kin 447.01: Professional Writing In Integrative Physiology, Melanie L. Mcgrath
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Kin 483.00: Exercise, Disease And Aging, Ron Michalak
Kin 483.00: Exercise, Disease And Aging, Ron Michalak
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 118.01: Mathematics For Music Enthusiasts, Mark Kayll
M 118.01: Mathematics For Music Enthusiasts, Mark Kayll
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Kin 106.01: Foundations Of Exercise Science Lab, Melanie L. Mcgrath
Kin 106.01: Foundations Of Exercise Science Lab, Melanie L. Mcgrath
University of Montana Course Syllabi, 2026-2030
No abstract provided.
Kin 205.01: Foundations Of Integrative Physiology And Athletic Training, Melanie L. Mcgrath
Kin 205.01: Foundations Of Integrative Physiology And Athletic Training, Melanie L. Mcgrath
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 307.01: Introduction To Abstract Mathematics, Elizabeth A. Gillaspy
M 307.01: Introduction To Abstract Mathematics, Elizabeth A. Gillaspy
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 591.01: The Geometry Of Surfaces, Eric B. Chesboro
M 591.01: The Geometry Of Surfaces, Eric B. Chesboro
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 522.01: Advanced Algebra Ii, Nikolaus Vonessen
M 522.01: Advanced Algebra Ii, Nikolaus Vonessen
University of Montana Course Syllabi, 2026-2030
No abstract provided.
M 133.01: Geometry And Measurement For Elementary School Teachers, Frederick Peck
M 133.01: Geometry And Measurement For Elementary School Teachers, Frederick Peck
University of Montana Course Syllabi, 2026-2030
No abstract provided.
2026 Tennessee Valley Authority's Payments In Lieu Of Taxes Annual Report To The Tennessee General Assembly
Taxes Reports
No abstract provided.
From Care To Capital: Rethinking Resilience In The Philippine Labor Export System, Alexa J. Abendano
From Care To Capital: Rethinking Resilience In The Philippine Labor Export System, Alexa J. Abendano
Senior Theses
Global migration has been a defining feature of the neoliberal world economy due to its ability to transform how nations manage care, labor and survival across borders. Within this system, the Philippines stands out as a country that has institutionalized labor migration as a development strategy since the 1970s. This paper examines how the Philippines states labor export policy shapes the vulnerability and resilience of migrant care workers, specifically those employed as domestic helpers in Hong Kong. By drawing on scholarship about global care economies, remittances, precarity, neoliberalism and resilience, this paper analyzes how emotional and reproductive labor are commodified …
Prediction Of First And Multiple Antiretroviral Therapy Interruptions In People Living With Hiv: Comparative Survival Analysis Using Cox And Explainable Machine Learning Models, Donald Salami, Emily Koech, Janet Turan, Kristen Stafford, Lilly Nyagah, Stephen Ohakanu, Anthony Ngugi, Manhattan Charurat
Prediction Of First And Multiple Antiretroviral Therapy Interruptions In People Living With Hiv: Comparative Survival Analysis Using Cox And Explainable Machine Learning Models, Donald Salami, Emily Koech, Janet Turan, Kristen Stafford, Lilly Nyagah, Stephen Ohakanu, Anthony Ngugi, Manhattan Charurat
Institute for Human Development, East Africa
Background: The Cox proportional hazards (CPH) model is a common choice for analyzing time-to-treatment interruptions in patients on antiretroviral therapy (ART), valued for its straightforward interpretability and flexibility in handling time-dependent covariates. Machine learning (ML) models have increasingly been adapted for handling temporal data, with added advantages of handling complex, nonlinear relationships and large datasets, and providing clear practical interpretations.
Objective: This study aims to compare the predictive performance of the traditional CPH model and ML models in predicting treatment interruptions among patients on ART, while also providing both global and individual-level explanations to support personalized, data-driven interventions …