FISNET: A Learnable Fusion-Based Iris Segmentation Network Improving Robustness Across NIR and VIS Modalities by Geetanjali Sharma, Gaurav Jaswal, Aditya Nigam, Raghavendra Ramachandra

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Environmental knowledge to create environmental attitudes generation toward solar energy purchase by Ingrid Iovana Burgos Espinoza, Jorge Luís García Alcaraz, Alfonso Jesús Gil López, José Roberto Díaz Reza, Jorge Limón Romero

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Power–Load Relationship of Bench Press, Ballistic Bench Press, and Prone Bench Pull in International Medal-Winning Canoeists and Kayakers by Oscar Crisafulli, Matteo Fortunati, Tiziano Gemelli, Massimiliano Febbi, Patrik Drid, Stefano Ramat, Giuseppe D’Antona

“…Instantaneous displacement was measured using a linear position transducer, and PO was computed for each repetition and exercise. PU/PR was calculated upon PBP and BP. …”
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The role of educational institutions in transformations to achieve sustainable development by Olha Kurylo, Olena Kryvylova, Viktoriia Zhyhir, Valentyna Peregudova, Yuliia Bielova-Oleynik, Serhii Onyshchenko, Olena Revutska

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Pitik: A Cebuano-Binisaya Intent-Based Chatbot for Cardiovascular Disease Patient Profiling and Risk Factor Recommendations by Joseph Cedeño, Andrew Manteza, Nicole Nacar, Merhamdin Umbukan, Cherrie Muaña, Ma. Juliet Vasay-Cruz, Ceasar Ian Benablo, Kristine Mae Adlaon

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Automating sentinel-1 SLC product processing: Parallelization and optimization for efficient polarimetric parameter extraction by Hansanee Fernando, Kwabena Nketia, Thuan Ha, Sarah van Steenbergen, Heather McNairn, Steve Shirtliffe

“…Similarly, we leverage the parallelization mechanisms of R for user specific parameter extraction, which maximizes resource utilization while maintaining computational performance. • Automated Workflow for SAR Processing: Introduces an automated, user-friendly framework combining RStudio, SNAP, and PolSARpro to process unlimited Sentinel-1 Single Look Complex (S1-SLC) images, eliminating manual interaction and catering to users with minimal programming or SAR expertise. • Customizable and Scalable Processing: Leverages SNAP's base-graph templates for essential SAR processing steps (e.g., orbit determination, calibration, speckle filtering, and terrain correction) to enable batch processing and parallel computing for efficient handling of large datasets. • Interoperability and Enhanced Performance: Integrates outputs from SNAP into PolSARpro for advanced post-processing, employing R-based parallelization to optimize resource utilization and ensure efficient user-specific parameter extraction.…”
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Deterministic Calculation Method for Continuous-energy Neutron Transport Equation in No-resonance Energy-range by LIU Haopo, LI Yunzhao, WU Hongchun, CAO Liangzhi

“…The computed results were compared with the existing continuous energy probabilistic neutron transport calculation program NECP-MCX. …”

A broad antibody with enhanced HIV-1 neutralization via bispecific antibody-mediated prepositioning by Soohyun Kim, Caelan E. Radford, Duo Xu, Jianing Zhong, Jonathan Do, Dominic M. Pham, Katie A. Travisano, Maria V. Filsinger Interrante, Theodora U. J. Bruun, Valerie Rezek, Bailey Wilder, Martina Palomares, Michael S. Seaman, Scott G. Kitchen, Jesse D. Bloom, Peter S. Kim

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Organ-specific safety profile of bioinspired short antimicrobial peptides in zebrafish embryos by Sahar Isa Da’as, Sahar Isa Da’as, Hajira Afreen, Aseela Fathima, Ahmad M. Hani, Nura A. Mohamed, Md Mizanur Rahman, Patrick G. Burgon, Sergio Crovella, Haissam Abou-Saleh

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Murine hematopoietic progenitor cell lines with erythroid and megakaryocyte potential by Ruiqiong Wu, Faraz Salehi, Vanessa Redecke, Zhijun Ma, Marco Marchetti, David Finkelstein, Peng Xu, Yong Cheng, Kimberly A. Queisser, Aaron C. Petrey, Conroy O. Field, Hyun Sook Ahn, Mortimer Poncz, Mitchell J. Weiss, Hans Häcker

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Optimizing Energy Consumption for vRAN Placement in O-RAN Systems With Flexible Transport Networks by William T. Pires-JR, Gabriel M. Almeida, Sand L. Correa, Cristiano B. Both, Leizer L. Pinto, Kleber V. Cardoso

“…Additionally, most studies employing optimal solutions exhibit very limited scalability due to their high computational time. In this work, we present a comprehensive and efficient Mixed Integer Linear Programming model to minimize the energy consumption of O-RAN systems, addressing the limitations of current approaches. …”
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Numerical Study of Inclined Geometric Configurations of a Submerged Plate-Type Device as Breakwater and Wave Energy Converter in a Full-Scale Wave Channel by Vitor Eduardo Motta, Gabrielle Ücker Thum, Rafael Adriano Alves Camargo Gonçalves, Luiz Alberto Oliveira Rocha, Elizaldo Domingues dos Santos, Bianca Neves Machado, Liércio André Isoldi

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Phase II basket trial of Dual Anti-CTLA-4 and anti-PD-1 blockade in Rare Tumors (DART) SWOG S1609: pancreatic neuroendocrine neoplasm (PNEN) cohort by Ignacio I Wistuba, Jianhua Zhang, Anup Kasi, Hong Chen, Seunghee Kim-Schulze, Holden T Maecker, Elad Sharon, Razelle Kurzrock, Sacha Gnjatic, Young Kwang Chae, Jiexin Zhang, Jianjun Zhang, Sandip Pravin Patel, Cara L Haymaker, Megan Othus, Charles Blanke, Edwin Parra, Gheath Al-Atrash, Caroline Duault, J Jack Lee, Helen X Chen, Edgar Gonzalez-Kozlova, Dzifa Yawa Duose, Luisa Solis Soto, Ganiraju Manyam, Christopher W Ryan, Jillian Fisher, Bhavana Konda, Mark Walshauser, Caddie Laberiano Fernandez, Raja Luthra, Christine M Magner

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Assessing the efficacy of a virtual reality lower leg fasciotomy surgery training model compared to cadaveric training by Heather Groves, Kristina Fuller, Vondel Mahon, Steven Butkus, Amitabh Varshney, Barbara Brawn, Jonathan Heagerty, Sida Li, Eric Lee, Sarah B. Murthi, Adam C. Puche

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Factor Analysis of Semen Quality in Chicken and Its Impact on Fertility by Yunlei Li, Yanyan Sun, Aixin Ni, Hailai Hagos Tesfay, Adamu Mani Isa, Yunhe Zong, Hui Ma, Jingwei Yuan, Jilan Chen

“…This study evaluated semen samples from 210 roosters in seven chicken breeds, using a computer-aided sperm analysis (CASA) system. A multivariate approach utilizing factor analysis (FA) was applied to simplify the data. …”
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SARS-CoV-2 seroprevalence among healthcare workers in a highly vaccinated Japanese medical center from 2020–2023 by Yan Yan, Kanami Ito, Hiroshi Fukuda, Shuko Nojiri, Wataru Urasaki, Takamasa Yamamoto, Yuki Horiuchi, Satoshi Hori, Kazuhisa Takahashi, Toshio Naito, Yoko Tabe

“…Our findings indicate that robust vaccination programs may have helped alleviate symptoms but consequently caused asymptomatic spread in this hospital, especially among younger HCWs. …”
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Deep Learning for Real-Time PPE Usage Monitoring Using Wearable IMU Sensors by Pedro Carvalho da Fonseca Guimaraes, Leonardo Braga de Cristo, Marcos Eduardo Pivaro Monteiro, Joao Luiz Rebelatto, Guilherme de Santi Peron, Ohara Kerusauskas Rayel, Guilherme Luiz Moritz

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Policies on artificial intelligence chatbots among academic publishers: a cross-sectional audit by Daivat Bhavsar, Laura Duffy, Hamin Jo, Cynthia Lokker, R. Brian Haynes, Alfonso Iorio, Ana Marusic, Jeremy Y. Ng

“…Abstract Background Artificial intelligence (AI) chatbots are novel computer programs that can generate text or content in a natural language format. …”
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Science mapping analysis of challenges surrounding cloud universities and their impact on the resilience of higher education by Svitlana Tarasenko, Anna Vorontsova, Verena Régent, John Soss, Rymma Mylenkova

“…The results show a significant increase in the number of studies, especially within the fields of Computer Science and Social Sciences, dedicated to the use of cloud services and technology in education, with a growing focus on “digital twins”. …”
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Precision Weed Control Using Unmanned Aerial Vehicles and Robots: Assessing Feasibility, Bottlenecks, and Recommendations for Scaling by Shanmugam Vijayakumar, Palanisamy Shanmugapriya, Pasoubady Saravanane, Thanakkan Ramesh, Varunseelan Murugaiyan, Selvaraj Ilakkiya

“…This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. …”
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