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Articles 781 - 810 of 11942
Full-Text Articles in Entire DC Network
Antioxidant Activity, Structural And Physical Properties Of Soy-Based Textured Vegetable Protein With Added Cannabis Leaves As Affected By Extrusion Process, Kamolwan Jangchud, Hataichanok Kantrong, Benjarat Tepsongkroh, Anuvat Jangchud, Khanchat Sangchum, Witoon Prinyawiwatkul
Antioxidant Activity, Structural And Physical Properties Of Soy-Based Textured Vegetable Protein With Added Cannabis Leaves As Affected By Extrusion Process, Kamolwan Jangchud, Hataichanok Kantrong, Benjarat Tepsongkroh, Anuvat Jangchud, Khanchat Sangchum, Witoon Prinyawiwatkul
Faculty Publications
The effects of cannabis leaf powder substituted for defatted soy flour (CP; 0%, 5%, 10% and 15%) and the moisture content of the mixture (MC; 25%, 35% and 45% on a wet basis) on physical properties and antioxidant activities of textured vegetable protein (TVP) prepared using a twin-screw extruder were studied. Increasing CP and MC decreased expansion, resulting in small air cells within the structure, which, in turn, led to an increased bulk density and decreased water absorption capacity, water holding capacity and water solubility index. After rehydration, TVP with the higher CP and MC levels tended to exhibit higher …
Mapping Literature In The Age Of Ai, Virginia Ramos
Mapping Literature In The Age Of Ai, Virginia Ramos
Comparative Woman
"Mapping literature in the age of AI" discusses the concept of "mapping", from its historical meaning to its technological meaning in the field of literature and AI tools developed in recent years and designed to "map literature". The article addresses ethics, biases, and the issue of human capacities vis a vis machine capacities, in support of the critical and crucial value of the humanities and their unavoidable relationship with GenAI.
Characterization Of Rhizosphere Microbial Diversity And Selection Of Plant-Growth-Promoting Bacteria At The Flowering And Fruiting Stages Of Rapeseed, Mengjiao Wang, Haiyan Sun, Zhimin Xu
Characterization Of Rhizosphere Microbial Diversity And Selection Of Plant-Growth-Promoting Bacteria At The Flowering And Fruiting Stages Of Rapeseed, Mengjiao Wang, Haiyan Sun, Zhimin Xu
Faculty Publications
Plant rhizosphere microorganisms play an important role in modulating plant growth and productivity. This study aimed to elucidate the diversity of rhizosphere microorganisms at the flowering and fruiting stages of rapeseed (Brassica napus). Microbial communities in rhizosphere soils were analyzed via high-throughput sequencing of 16S rRNA for bacteria and internal transcribed spacer (ITS) DNA regions for fungi. A total of 401 species of bacteria and 49 species of fungi in the rhizosphere soil samples were found in three different samples. The composition and diversity of rhizosphere microbial communities were significantly different at different stages of rapeseed growth. Plant-growth-promoting rhizobacteria (PGPRs) …
Challenges And Opportunities In Sustainability Reporting: A Focus On Small And Medium Enterprises (Smes), Santi Setyaningsih, Rosita Widjojo, Peter Kelle
Challenges And Opportunities In Sustainability Reporting: A Focus On Small And Medium Enterprises (Smes), Santi Setyaningsih, Rosita Widjojo, Peter Kelle
Faculty Publications
The purpose of the study was to observe how Small and Medium-sized Enterprises (SMEs) struggle to develop the sustainability reports that are today important and required by consumers. The rationale is that the sustainability report is influenced by governance practices, social responsibility, and environmental impact. The research successfully summarizes the barriers from 37 influential sustainability report papers by employing a thorough systematic literature review. It was based on 6 well-known databases with the limitation of exclusion criteria such as 11 years of research (2012–2023), used English, and more than 4 pages articles. According to the findings of this literature review …
Promoting Equity And Addressing Concerns In Teaching And Learning With Artificial Intelligence, Jennifer Garcia Ramos, Zakiya Wilson-Kennedy
Promoting Equity And Addressing Concerns In Teaching And Learning With Artificial Intelligence, Jennifer Garcia Ramos, Zakiya Wilson-Kennedy
Faculty Publications
This perspective article focuses on the exploration and advocacy of approaches to be considered in designing equitable learning experiences for students’ use of artificial intelligence, machine learning, and technology through the Universal Design for Learning Framework (UDL) exemplifying chemistry examples that can be applied to any course in STEM. The use of artificial intelligence (AI) and machine learning are causing disruptions within learning in higher education and is also casting a spotlight on systemic inequities particularly affecting minoritized groups broadly and in STEM fields. Particularly, the emergence of AI has focused on inequities toward minoritized students in academic and professional …
The Role Of Magnetar Transient Activity In Time-Domain And Multimessenger Astronomy, Michela Negro, George Younes, Zorawar Wadiasingh, Eric Burns, Aaron Trigg, Matthew Baring
The Role Of Magnetar Transient Activity In Time-Domain And Multimessenger Astronomy, Michela Negro, George Younes, Zorawar Wadiasingh, Eric Burns, Aaron Trigg, Matthew Baring
Faculty Publications
Time-domain and multimessenger astronomy (TDAMM) involves the study of transient and time-variable phenomena across various wavelengths and messengers. The Astro2020 Decadal Survey has identified TDAMM as the top priority for NASA in this decade, emphasizing its crucial role in advancing our understanding of the universe and driving new discoveries in astrophysics. The TDAMM community has come together to provide further guidance to funding agencies, aiming to define a clear path toward optimizing scientific returns in this research domain. This encompasses not only astronomy but also fundamental physics, offering insights into properties of gravity, the formation of heavy elements, the equation …
Efficacious Qubit Mappings For Quantum Simulations Of The 12c Rotational Band, Darin C. Mumma, Zhonghao Sun, Alexis Mercenne, Kristina D. Launey, Soorya Rethinasamy, James A. Sauls
Efficacious Qubit Mappings For Quantum Simulations Of The 12c Rotational Band, Darin C. Mumma, Zhonghao Sun, Alexis Mercenne, Kristina D. Launey, Soorya Rethinasamy, James A. Sauls
Faculty Publications
Solving atomic nuclei from first principles places enormous demands on computational resources, which grow exponentially with increasing number of particles and the size of the space they occupy. We present first quantum simulations based on the variational quantum eigensolver for the low-lying structure of the 12C nucleus that provide acceptable bound-state energies even in the presence of noise. We achieve this by taking advantage of two critical developments. First, we utilize an almost perfect symmetry of atomic nuclei that, in a complete symmetry-adapted basis, drastically reduces the size of the model space. Second, we use the efficacious Gray encoding, …
The Future Of Attosecond Science, Nirit Dudovich, Li Fang, Mette Gaarde, Ursula Keller, Alexandra Landsman, Maria Richter, Nina Rohringer, Linda Young
The Future Of Attosecond Science, Nirit Dudovich, Li Fang, Mette Gaarde, Ursula Keller, Alexandra Landsman, Maria Richter, Nina Rohringer, Linda Young
Faculty Publications
Conferences are incredible opportunities to strengthen the inclusive outlook of our scientific community. The participation of female scientists, postdocs, and graduate students in the ATTO VIII conference was remarkable, with more than 40% of female invited speakers. The Local Organizing Committee seized this opportunity to promote an atmosphere that welcomes all. An entirely female evening panel, with experience across the attosecond science spectrum, was convened to explore the Future of Attosecond Science in the evening session of Wednesday, July 13. Furthermore, a booklet entitled Perspectives in Attosecond Science was compiled by Dr. Shima Gholam-Mirzaei of the University of Ottawa and …
The Beta-Decay Paul Trap Mk Iv: Design And Commissioning, L. Varriano, G. Savard, J. A. Clark, D. P. Burdette, M. T. Burkey, A. T. Gallant, T. Y. Hirsh, B. Longfellow, N. D. Scielzo, R. Segel, E. J. Boron, M. Brodeur, N. Callahan, A. Cannon, K. Kolos, B. Liu, S. Lopez-Caceres, M. Gott, B. Maaß, S. T. Marley, C. Mohs, G. E. Morgan, P. Mueller, M. Oberling, P. D. O'Malley, W. S. Porter, Z. Purcell, D. Ray, F. Rivero, A. A. Valverde, G. L. Wilson, R. Zite
The Beta-Decay Paul Trap Mk Iv: Design And Commissioning, L. Varriano, G. Savard, J. A. Clark, D. P. Burdette, M. T. Burkey, A. T. Gallant, T. Y. Hirsh, B. Longfellow, N. D. Scielzo, R. Segel, E. J. Boron, M. Brodeur, N. Callahan, A. Cannon, K. Kolos, B. Liu, S. Lopez-Caceres, M. Gott, B. Maaß, S. T. Marley, C. Mohs, G. E. Morgan, P. Mueller, M. Oberling, P. D. O'Malley, W. S. Porter, Z. Purcell, D. Ray, F. Rivero, A. A. Valverde, G. L. Wilson, R. Zite
Faculty Publications
The Beta-decay Paul Trap is an open-geometry, linear trap used to measure the decays of 8Li and 8B to search for a tensor contribution to the weak interaction. In the latest 8Li measurement of Burkey et al. (2022), β scattering was the dominant experimental systematic uncertainty. The Beta-decay Paul Trap Mk IV reduces the prevalence of β scattering by a factor of 4 through a redesigned electrode geometry and the use of glassy carbon and graphite as electrode materials. The trap has been constructed and successfully commissioned with 8Li in a new data campaign that collected …
The Imaging X-Ray Polarimetry Explorer 2.5 Years Later, Paolo Soffitta, Luca Baldini, Wayne Baumgartner, Ronaldo Bellazzini, Stephen D. Bongiorno, Niccolò Bucciantini, Enrico Costa, Michal Dovčiak, Steven Ehlert, Philip E. Kaaret, Jeffery J. Kolodziejczak, Luca Latronico, Frédréic Marin, Alan P. Marscher, Herman L. Marshall, Giorgio Matt, Fabio Muleri, Stephen L. O'Dell, Juri Poutanen, Brian Ramsey, Roger W. Romani, Patrick Slane, Allyn F. Tennant, Roberto Turolla, Martin C. Weisskopf, Iván Agudo, Lucio Angelo Antonelli, Matteo Bachetti, Stefano Bianchi, Raffaella Bonino, Alessandro Brez, Fiamma Capitanio, Simone Castellano
The Imaging X-Ray Polarimetry Explorer 2.5 Years Later, Paolo Soffitta, Luca Baldini, Wayne Baumgartner, Ronaldo Bellazzini, Stephen D. Bongiorno, Niccolò Bucciantini, Enrico Costa, Michal Dovčiak, Steven Ehlert, Philip E. Kaaret, Jeffery J. Kolodziejczak, Luca Latronico, Frédréic Marin, Alan P. Marscher, Herman L. Marshall, Giorgio Matt, Fabio Muleri, Stephen L. O'Dell, Juri Poutanen, Brian Ramsey, Roger W. Romani, Patrick Slane, Allyn F. Tennant, Roberto Turolla, Martin C. Weisskopf, Iván Agudo, Lucio Angelo Antonelli, Matteo Bachetti, Stefano Bianchi, Raffaella Bonino, Alessandro Brez, Fiamma Capitanio, Simone Castellano
Faculty Publications
We have, at last, an observatory dedicated to X-ray polarimetry that has been operational since December 9th, 2021. The Imaging X-ray Polarimetry Explorer (IXPE) is a NASA SMEX mission, in partnership with ASI, based on three X-ray telescopes, each equipped with a polarization-sensitive detector in the focus. An extending boom was deployed in orbit, positioning the detectors at the optimal distance from the optics, which have a 4-meter focal length. The spacecraft is three-axis stabilized, providing power, attitude determination and control, transmission, and commanding capabilities. After two and a half years of observation, IXPE has detected positive polarization …
The African Light Source: History, Context And Future, Simon H. Connell, Kathleen Dollman, Gihan Kamel, Sameen A. Khan, Edward Mitchell, Sekazi K. Mtingwa, Marcus C. Newton, Prosper Ngabonziza, Emmanuel Nji, Lawrence Norris, Michele Zema
The African Light Source: History, Context And Future, Simon H. Connell, Kathleen Dollman, Gihan Kamel, Sameen A. Khan, Edward Mitchell, Sekazi K. Mtingwa, Marcus C. Newton, Prosper Ngabonziza, Emmanuel Nji, Lawrence Norris, Michele Zema
Faculty Publications
The African Light Source (AfLS) project is now almost eight years old. This article assesses the history, current context and future of the project. There is by now considerable momentum in building the user community, including deep training, facilitating access to current facilities, growing the scientific output, scientific networks and growing the local laboratory-scale research infrastructure. The Conceptual Design Report for the AfLS is in its final editing stages. This document specifies the socio-economic and scientific rationales and the technical aspects amongst others. The AfLS is supported by many national and Pan-African scientific professional bodies and voluntary associates across many …
Lsu Fall Facts, 2024, Lsu Office Of Data & Strategic Analytics
Lsu Fall Facts, 2024, Lsu Office Of Data & Strategic Analytics
Fall Facts
No abstract provided.
Feature Engineering Of Environmental Covariates Improves Plant Genomic-Enabled Prediction, Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Bernabe Cano-Paez, Gloria Isabel Huerta-Prado, Brandon Alejandro Mosqueda-González, Sofia Ramos-Pulido, Guillermo Gerard, Khalid Alnowibet, Roberto Fritsche-Neto, Abelardo Montesinos-López, José Crossa
Feature Engineering Of Environmental Covariates Improves Plant Genomic-Enabled Prediction, Osval A. Montesinos-López, Leonardo Crespo-Herrera, Carolina Saint Pierre, Bernabe Cano-Paez, Gloria Isabel Huerta-Prado, Brandon Alejandro Mosqueda-González, Sofia Ramos-Pulido, Guillermo Gerard, Khalid Alnowibet, Roberto Fritsche-Neto, Abelardo Montesinos-López, José Crossa
Faculty Publications
Introduction: Because Genomic selection (GS) is a predictive methodology, it needs to guarantee high-prediction accuracies for practical implementations. However, since many factors affect the prediction performance of this methodology, its practical implementation still needs to be improved in many breeding programs. For this reason, many strategies have been explored to improve the prediction performance of this methodology. Methods: When environmental covariates are incorporated as inputs in the genomic prediction models, this information only sometimes helps increase prediction performance. For this reason, this investigation explores the use of feature engineering on the environmental covariates to enhance the prediction performance of genomic …
Ba5sb8: The Highest Homologue Of The Family Of Binary Semiconducting Barium Antimonides Bansb2n−2 (N ≥ 2), S. M.Gayomi K. Samarakoon, Alexander Ovchinnikov, Sviatoslav Baranets, Svilen Bobev
Ba5sb8: The Highest Homologue Of The Family Of Binary Semiconducting Barium Antimonides Bansb2n−2 (N ≥ 2), S. M.Gayomi K. Samarakoon, Alexander Ovchinnikov, Sviatoslav Baranets, Svilen Bobev
Faculty Publications
A novel binary compound within the Ba–Sb phase diagram, Ba5Sb8, was synthesized by combining elements with an excess of Sb in an alumina crucible. Structural elucidation was performed using single-crystal X-ray diffraction. This compound crystallizes in the orthorhombic space group Fdd2 with unit cell parameters of a = 15.6568(13) Å, b = 35.240(3) Å, c = 6.8189(6) Å, adopting its own structure type. The most distinctive features of the structure are the eight-membered [Sb8]10− polyanionic fragments which have no known precedents among antimonides. They are separated by five Ba2+ cations, which afford the charge balance and enable adherence …
Pseudomonas Aeruginosa Gene Pa4880 Encodes A Dps-Like Protein With A Dps Fold, Bacterioferritin-Type Ferroxidase Centers, And Endonuclease Activity, Nimesha Rajapaksha, Huili Yao, Aisha Cook, Steve Seibold, Lijun Liu, Kevin P. Battaile, Leo Fontenot, Fabrizio Donnarumma, Scott Lovell, Mario Rivera
Pseudomonas Aeruginosa Gene Pa4880 Encodes A Dps-Like Protein With A Dps Fold, Bacterioferritin-Type Ferroxidase Centers, And Endonuclease Activity, Nimesha Rajapaksha, Huili Yao, Aisha Cook, Steve Seibold, Lijun Liu, Kevin P. Battaile, Leo Fontenot, Fabrizio Donnarumma, Scott Lovell, Mario Rivera
Faculty Publications
We report the biochemical, structural, and functional characterization of the protein coded by gene PA4880 in the P. aeruginosa PAO1 genome. The PA4880 gene had been annotated as coding a probable bacterioferritin. Our structural work shows that the product of gene PA4880 is a protein that adopts the Dps subunit fold, which oligomerizes into a 12-mer quaternary structure. Unlike Dps, however, the ferroxidase di-iron centers and iron coordinating ligands are buried within each subunit, in a manner identical to that observed in the ferroxidase center of P. aeruginosa bacterioferritin. Since these structural characteristics correspond to Dps-like proteins, we term the …
The Role Of Holistic Mentoring Ecosystems In Mitigating Covid-19 Pandemic Impacts On The Persistence Of Low-Income Stem Students, Raeshan D. Davis, Zakiya S. Wilson-Kennedy
The Role Of Holistic Mentoring Ecosystems In Mitigating Covid-19 Pandemic Impacts On The Persistence Of Low-Income Stem Students, Raeshan D. Davis, Zakiya S. Wilson-Kennedy
Faculty Publications
Holistic mentoring ecosystems are a comprehensive approach to addressing the diverse needs of students through interconnected support networks. While mentoring has been well-documented in existing literature, more research is needed to determine the effectiveness of mentoring ecosystems in mitigating the impact of critical junctures for vulnerable, high-attrition student populations. Guided by Tinto’s model of retention, this qualitative case study investigated the role of holistic mentoring ecosystems in mitigating the impacts of the two combined critical junctures—the COVID-19 pandemic and the first year of college—on low-income STEM undergraduates. Our findings suggest that holistic mentoring ecosystems were essential in helping students adjust …
Modelling And Simulation Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks, Shawn W. Walker
Modelling And Simulation Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks, Shawn W. Walker
Faculty Publications
This paper discusses modelling and numerical issues in the simulation of the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We propose a fully implicit, (weighted) L2 gradient flow for computing energy minimizers of the LdG model, and note a time-step restriction for the flow to be energy decreasing. Furthermore, we give a mesh size restriction, for finite-element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers, particularly when simulating cholesteric LCs that exhibit 'twist.' Furthermore, we perform a computational exploration of the model and present several numerical simulations in three dimensions, on …
Lsu General Catalog 2024-2025, Louisiana State University And Agricultural And Mechanical College
Lsu General Catalog 2024-2025, Louisiana State University And Agricultural And Mechanical College
LSU General Catalog
The LSU General Catalog describes all undergraduate and graduate departments and programs with degree requirements and courses offered for each one. The LSU General Catalog includes information on registration and financial aid as well as academic services offered to all students.
Economic, Environmental, And Social Characteristics Of E-Scooters On Lsu Campus, Mostafa Elseifi, Md Afif Rahman Chowdhury
Economic, Environmental, And Social Characteristics Of E-Scooters On Lsu Campus, Mostafa Elseifi, Md Afif Rahman Chowdhury
Data
This study provides a comprehensive evaluation of e-scooter technology, with a focus on its environmental, economic, and social impacts, particularly within university settings at the Louisiana State University (LSU) campus. A life-cycle assessment (LCA) was conducted to assess the environmental sustainability of e-scooters, encompassing all stages from raw materials acquisition to end-of-life. The analysis determined that the total CO2 emissions for an e-scooter over a five-year lifespan were approximately 389 kg, with significant reductions possible by improving the lifespan of e-scooters, integrating recycled materials, and utilizing renewable energy sources for charging batteries. The study also compared the environmental and …
Variant Of The Lactase Lct Gene Explains Association Between Milk Intake And Incident Type 2 Diabetes, Kai Luo, Guo Chong Chen, Yanbo Zhang, Jee Young Moon, Jiaqian Xing, Brandilyn A. Peters, Mykhaylo Usyk, Zheng Wang, Gang Hu, Jun Li, Elizabeth Selvin, Casey M. Rebholz, Tao Wang, Carmen R. Isasi, Bing Yu, Rob Knight, Eric Boerwinkle, Robert D. Burk, Robert C. Kaplan, Qibin Qi
Variant Of The Lactase Lct Gene Explains Association Between Milk Intake And Incident Type 2 Diabetes, Kai Luo, Guo Chong Chen, Yanbo Zhang, Jee Young Moon, Jiaqian Xing, Brandilyn A. Peters, Mykhaylo Usyk, Zheng Wang, Gang Hu, Jun Li, Elizabeth Selvin, Casey M. Rebholz, Tao Wang, Carmen R. Isasi, Bing Yu, Rob Knight, Eric Boerwinkle, Robert D. Burk, Robert C. Kaplan, Qibin Qi
Population and Public Health Science Faculty Publications
Cow’s milk is frequently included in the human diet, but the relationship between milk intake and type 2 diabetes (T2D) remains controversial. Here, using data from the Hispanic Community Health Study/Study of Latinos, we show that in both sexes, higher milk intake is associated with lower risk of T2D in lactase non-persistent (LNP) individuals (determined by a variant of the lactase LCT gene, single nucleotide polymorphism rs4988235) but not in lactase persistent individuals. We validate this finding in the UK Biobank. Further analyses reveal that among LNP individuals, higher milk intake is associated with alterations in gut microbiota (for example, …
Monitoring Of Wave, Current, And Sediment Dynamics Along The Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland, Hongqing Wang, Qin Chen, William D. Capurso, Lukasz M. Niemoczynski, Nan Wang, Ling Zhu, Gregg A. Snedden, Matt Whitbeck, Carol A. Wilson, Michael Brownley
Monitoring Of Wave, Current, And Sediment Dynamics Along The Fog Point Living Shoreline, Glenn Martin National Wildlife Refuge, Maryland, Hongqing Wang, Qin Chen, William D. Capurso, Lukasz M. Niemoczynski, Nan Wang, Ling Zhu, Gregg A. Snedden, Matt Whitbeck, Carol A. Wilson, Michael Brownley
Faculty Publications
Living shorelines with salt marsh species, rock breakwaters, and sand nourishment were built along the coastal areas in the Glenn Martin National Wildlife Refuge, Maryland, in 2016 in response to Hurricane Sandy (2012). The Fog Point living shoreline at Glenn Martin National Wildlife Refuge was designed with the “headland - breakwater - embayment” pattern. Scientists from the U.S. Geological Survey, Northeastern University, U.S. Fish and Wildlife Service, and Louisiana State University studied wave, current, and sediment dynamics to assess the effectiveness of the Fog Point living shoreline structures in terms of wave attenuation and erosion reduction. Wave gages, current meters, …
Dpal-Bert: A Faster And Lighter Question Answering Model, Lirong Yin, Lei Wang, Zhuohang Cai, Siyu Lu, Ruiyang Wang, Ahmed Alsanad, Salman A. Alqahtani, Xiaobing Chen, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng
Dpal-Bert: A Faster And Lighter Question Answering Model, Lirong Yin, Lei Wang, Zhuohang Cai, Siyu Lu, Ruiyang Wang, Ahmed Alsanad, Salman A. Alqahtani, Xiaobing Chen, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng
Faculty Publications
Recent advancements in natural language processing have given rise to numerous pre-training language models in question-answering systems. However, with the constant evolution of algorithms, data, and computing power, the increasing size and complexity of these models have led to increased training costs and reduced efficiency. This study aims to minimize the inference time of such models while maintaining computational performance. It also proposes a novel Distillation model for PAL-BERT (DPAL-BERT), specifically, employs knowledge distillation, using the PAL-BERT model as the teacher model to train two student models: DPAL-BERT-Bi and DPAL-BERT-C. This research enhances the dataset through techniques such as masking, …
Convolution-Transformer For Image Feature Extraction, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Youshuai Yang, Bo Yang, Shan Liu, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Xiaobing Chen, Wenfeng Zheng
Convolution-Transformer For Image Feature Extraction, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Youshuai Yang, Bo Yang, Shan Liu, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Xiaobing Chen, Wenfeng Zheng
Faculty Publications
This study addresses the limitations of Transformer models in image feature extraction, particularly their lack of inductive bias for visual structures. Compared to Convolutional Neural Networks (CNNs), the Transformers are more sensitive to different hyperparameters of optimizers, which leads to a lack of stability and slow convergence. To tackle these challenges, we propose the Convolution-based Efficient Transformer Image Feature Extraction Network (CEFormer) as an enhancement of the Transformer architecture. Our model incorporates E-Attention, depthwise separable convolution, and dilated convolution to introduce crucial inductive biases, such as translation invariance, locality, and scale invariance, into the Transformer framework. Additionally, we implement a …
Afbnet: A Lightweight Adaptive Feature Fusion Module For Super-Resolution Algorithms, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Haitao Ren, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng
Afbnet: A Lightweight Adaptive Feature Fusion Module For Super-Resolution Algorithms, Lirong Yin, Lei Wang, Siyu Lu, Ruiyang Wang, Haitao Ren, Ahmed Alsanad, Salman A. Alqahtani, Zhengtong Yin, Xiaolu Li, Wenfeng Zheng
Faculty Publications
At present, super-resolution algorithms are employed to tackle the challenge of low image resolution, but it is difficult to extract differentiated feature details based on various inputs, resulting in poor generalization ability. Given this situation, this study first analyzes the features of some feature extraction modules of the current super-resolution algorithm and then proposes an adaptive feature fusion block (AFB) for feature extraction. This module mainly comprises dynamic convolution, attention mechanism, and pixel-based gating mechanism. Combined with dynamic convolution with scale information, the network can extract more differentiated feature information. The introduction of a channel spatial attention mechanism combined with …
Negotiating Quotidian Justice In The Science Classroom, Christopher Irwin, Joshua Ellis
Negotiating Quotidian Justice In The Science Classroom, Christopher Irwin, Joshua Ellis
Faculty Publications
In this conceptual paper, we explore how science teachers might enact social justice through their everyday science instruction. Drawing on empirical literature and our own K-12 teaching experience, we develop a heuristic for mapping classroom discourses to engage in action and reflection to change both the world of the classroom community, and the world beyond the school. We suggest how this heuristic can be used for justice-oriented science teaching independently of (or as a supplement to) any existing frameworks for science teaching to promote social justice. Our proposed model for social justice through disciplinary science teaching frames justice not as …
Summer-Wet Hydrologic Cycle During The Middle Miocene Of The United States: New Evidence From Fossil Fungi, Jennifer M.K. O’Keefe, Matthew J. Pound, Ingrid C. Romero, Noelia B. Nuñez Otaño, Martha E. Gibson, Jessica Mccoy, Margaret E. Alden, C. Jolene Fairchild, Julia Fitzpatrick, Emily Hodgson, Taylor Horsfall, Savannah Jones, June E. Lennex-Stone, Christopher A. Marsh, Alyssa A. Patel, Tyler M. Spears, Laikin Tarlton, Liberty F. Smallwood, O. L. Vanderespt, Jeremyah R. Cabrera, Cortland F. Eble, William C. Rember, James E. Starnes, Mac H. Alford, Alyson Brink, Sophie Warny
Summer-Wet Hydrologic Cycle During The Middle Miocene Of The United States: New Evidence From Fossil Fungi, Jennifer M.K. O’Keefe, Matthew J. Pound, Ingrid C. Romero, Noelia B. Nuñez Otaño, Martha E. Gibson, Jessica Mccoy, Margaret E. Alden, C. Jolene Fairchild, Julia Fitzpatrick, Emily Hodgson, Taylor Horsfall, Savannah Jones, June E. Lennex-Stone, Christopher A. Marsh, Alyssa A. Patel, Tyler M. Spears, Laikin Tarlton, Liberty F. Smallwood, O. L. Vanderespt, Jeremyah R. Cabrera, Cortland F. Eble, William C. Rember, James E. Starnes, Mac H. Alford, Alyson Brink, Sophie Warny
Faculty Publications
Hydrologic reconstructions from North America are largely unknown for the Middle Miocene. Examination of fungal palynomorph assemblages coupled with traditional plant-based palynology permits delineation of local, as opposed to regional, climate signals and provides a baseline for study of ancient fungas. Here, the Fungi in a Warmer World project presents paleoecology and paleoclimatology of 351 fungal morphotypes from 3 sites in the United States: the Clarkia Konservat-Lagerstätte site (Idaho), the Alum Bluff site (Florida), and the Bouie River site (Mississippi). Of these, 83 fungi are identified as extant taxa and 41 are newly reported from the Miocene. Combining new plant-based …
Accelerating L-Shaped Two-Stage Stochastic Scuc With Learning Integrated Benders Decomposition, Fouad Hasan, Amin Kargarian
Accelerating L-Shaped Two-Stage Stochastic Scuc With Learning Integrated Benders Decomposition, Fouad Hasan, Amin Kargarian
Faculty Publications
Benders decomposition is widely used to solve large mixed-integer problems. This article takes advantage of machine learning and proposes a variant of Benders decomposition to tackle two-stage stochastic security-constrained unit commitment (SCUC). The problem is decomposed into a master problem (MP) and subproblems (SPs) corresponding to individual load scenarios. The primary objective is to mitigate computational expenses and memory consumption associated with Benders decomposition by generating tighter cuts and reducing the MP's dimensions. A regressor reads load profile scenarios and predicts objective function proxy values for the SPs, enabling the creation of tighter cuts for the MP. The numerical difference …
Optimizing Privacy And Utility Tradeoffs For Group Interests Through Harmonization, Bishwas Mandal, George Amariucai, Shuangqing Wei
Optimizing Privacy And Utility Tradeoffs For Group Interests Through Harmonization, Bishwas Mandal, George Amariucai, Shuangqing Wei
Faculty Publications
We propose a novel problem formulation to address the privacy-utility tradeoff, specifically when dealing with two distinct user groups characterized by unique sets of private and utility attributes. Unlike previous studies that primarily focus on scenarios where all users share identical private and utility attributes and often rely on auxiliary datasets or manual annotations, we introduce a collaborative data-sharing mechanism between two user groups through a trusted third party. This third party uses adversarial privacy techniques with our proposed data-sharing mechanism to internally sanitize data for both groups and eliminates the need for manual annotation or auxiliary datasets. Our methodology …
Communication-Efficient Admm Using Quantization-Aware Gaussian Process Regression, Aldo Duarte, Truong X. Nghiem, Shuangqing Wei
Communication-Efficient Admm Using Quantization-Aware Gaussian Process Regression, Aldo Duarte, Truong X. Nghiem, Shuangqing Wei
Faculty Publications
In networks consisting of agents communicating with a central coordinator and working together to solve a global optimization problem in a distributed manner, the agents are often required to solve private proximal minimization subproblems. Such a setting often requires a decomposition method to solve the global distributed problem, resulting in extensive communication overhead. In networks where communication is expensive, it is crucial to reduce the communication overhead of the distributed optimization scheme. Gaussian processes (GPs) are effective at learning the agents' local proximal operators, thereby reducing the communication between the agents and the coordinator. We propose combining this learning method …
Initial Exploration Of Zero-Shot Privacy Utility Tradeoffs In Tabular Data Using Gpt-4, Bishwas Mandal, George Amariucai, Shuangqing Wei
Initial Exploration Of Zero-Shot Privacy Utility Tradeoffs In Tabular Data Using Gpt-4, Bishwas Mandal, George Amariucai, Shuangqing Wei
Faculty Publications
We investigate the application of large language models (LLMs), specifically GPT-4, to scenarios involving the tradeoff between privacy and utility in tabular data. Our approach entails prompting GPT-4 by transforming tabular data points into textual format, followed by the inclusion of precise sanitization instructions in a zero-shot manner. The primary objective is to sanitize the tabular data in such a way that it hinders existing machine learning models from accurately inferring private features while allowing models to accurately infer utility-related attributes. We explore various sanitization instructions. Notably, we discover that this relatively simple approach yields performance comparable to more complex …