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Innovative graduate program in computational science and engineering

Innovative graduate program in computational science and eng...

2005 ASEE Annual Conference and Exposition: The Changing Landscape of engineering and Technology Education in a Global World

作者： Kelkar, Ajit D. Mohan, Ram Tang, Guoqing Radhakrishnan, N. Murray, Kenneth Computational Science and Engineering Program North Carolina A and T State University Greensboro NC 27411 United States Computational Science and Engineering Program United States Department of Mechanical Engineering North Carolina A and T State University United States Department of Mathematics North Carolina A and T State University United States Research and Economic Development North Carolina A and T State University United States Graduate School Academic Affairs North Carolina A and T State University United States North Carolina A and T State University United States

North Carolina Agricultural and Technical State University (NCA&T) has established a master's degree program in computational science and engineering (CSE). The CSE master's program would have three tracks with a focus on computational science, but distinguish across the domain areas of specialization. The goal of the track is to produce biological and life scientists, business professionals and economists and agricultural scientists with focus and expertise in computational sciences and the primary domain areas.

关键词： Curricula

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Adaptive Input Sampling: A Novel Approach for Efficient Object Detection in High Resolution Traffic Monitoring Images

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IEEE Access 2025年 13卷 73003-73021页

作者： Gebre, Tewodros Syum Wasehun, Eden Tsehaye Dorbu, Freda Elikem Agboola, Gazali Oluwasegun Hashemi-Beni, Leila Karimoddini, Ali NC AandT State University Applied Science and Technology Program GreensboroNC United States NC AandT State University Department of Computational Data Science and Engineering GreensboroNC United States NC AandT State University Geomatics Program Department of Built Environment GreensboroNC United States NC AandT State University Department of Electrical and Computer Engineering GreensboroNC United States

Real-time traffic monitoring is crucial for efficient transportation management, but it poses significant computational challenges, particularly when dealing with high-resolution videos. Most modern traffic monitoring systems employ object detection models followed by object tracking models, which require processing every frame of the video footage to detect and track vehicles. However, even efficient object detection models are computationally expensive, making it difficult to process high-resolution videos in real-time. To address this challenge, we introduce an Adaptive Input Sampler (AIS) as a preprocessing module that selectively activates the object detector only when vehicles are present in the scene. The AIS targets the area of the frame where vehicles are detected and samples that area without compressing the sample, thereby reducing the computational load on the object detector. By doing so, the AIS enables significant computational savings, especially when fewor no vehicles are present in the monitored scene. Our experiments demonstrate that the AIS achieves 96.40% traffic counting accuracy and 95.60% classification accuracy, while reducing the data size for analysis by up to 79.00%. AIS presents a promising solution to optimize the volume of input data in traffic monitoring applications, improve computational efficiency, and speed up inference results. © 2013 IEEE.

关键词： Footage counters

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GeoRefineNet: A Multistage Framework for Enhanced Cephalometric Landmark Detection in CBCT Images Using 3D Geometric Information 17th

GeoRefineNet: A Multistage Framework for Enhanced Cephalome...

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17th Asian Conference on Computer Vision, ACCV 2024

作者： Viriyasaranon, Thanaporn Ma, Serie Choi, Jang-Hwan Department of Computational Medicine Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Division of Mechanical and Biomedical Engineering Graduate Program in System Health Science and Engineering Ewha Womans University Seoul Korea Republic of Department of Artificial Intelligence Ewha Womans University Seoul Korea Republic of

ISBN: (纸本)9789819609000

The precise detection of cephalometric landmarks on two-dimensional (2D) radiographs or three-dimensional (3D) computed tomography (CT) images is a fundamental step in various medical fields, especially in research on orthodontics and maxillofacial surgery. Deep learning-based detectors have demonstrated remarkable accuracy in 2D cephalometric analysis, whereas conventional single-view approaches are limited by their reliance on information from a single perspective. This study proposes GeoRefineNet, a novel multistage framework that leverages information from multiple CT scans acquired at various angles. By incorporating geometric knowledge through a 3D heatmap reconstruction process, GeoRefineNet improves robustness, accuracy, and adaptability to various cephalometric configurations. The proposed framework predicts 3D landmark positions on CT images, effectively addressing challenges associated with high-dimensional input data and limited training examples. GeoRefineNet surpasses the existing state-of-the-art models in the 2D and 3D domains, as demonstrated by its superior performance on numerical and clinical datasets. These findings indicate that GeoRefineNet offers a promising avenue for improving the accuracy and reliability of cephalometric landmark detection fostering further advances in clinical diagnosis and treatment planning. Our code is available at https://***/Thanaporn09/***. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Computerized tomography

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Comments on "relaxed Conditions for the Input-to-State Stability of Switched Nonlinear Time-Varying Systems"

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IEEE Transactions on Automatic Control 2025年

作者： Şahan, Gökhan Trenn, Stephan Izmir Institute of Technology Department of Mathematics and Computational Science and Engineering Program Urla Izmir Turkey University of Groningen Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence Groningen9722BA Netherlands

This study addresses the deficiencies in the assumptions of the results in Chen and Yang, 2017 [1] due to the lack of uniformity. We first show the missing hypothesis by presenting a counterexample. Then we prove why they are wrong in that form and show the errors in the proof of the main result of [1]. Next, we compare the assumptions and related results of [1] with similar works in the literature. Lastly, we give suggestions to complement the shortcomings of the hypotheses and thus correct them. © 1963-2012 IEEE.

关键词： Nonlinear simulations

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Synergetic effects of multiple junction and surface hydroxyl in Cu/CuO/Cu2O/TiO2 heterostructures towards highly efficient photocatalysts for hydrogen generation

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Materials science for Energy Technologies 2025年 8卷 131-142页

作者： Subagyo, Riki Anindika, Garcelina Rizky Aufkani, Afif Akmal Zhang, Lei Ardhyananta, Hosta Burhan, R.Y. Perry Nugraheni, Zjahra Vianita Akhlus, Syafsir Bahruji, Hasliza Prasetyoko, Didik Wellia, Diana Vanda Ivansyah, Atthar Luqman Arramel Kusumawati, Yuly Department of Chemistry Faculty of Science and Analytic Data Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Center of Excellence Applied Physics and Chemistry Nano Center Indonesia Jl PUSPIPTEK South Tangerang Banten15314 Indonesia Department of Physics National University of Singapore Singapore117551 Singapore Department of Materials and Metallurgical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Surabaya60111 Indonesia Centre of Advanced Material and Energy Science Universiti Brunei Darussalam Jalan Tungku Link BE 1410 Brunei Department of Chemistry Faculty of Mathematics and Natural Sciences Universitas Andalas Padang25163 Indonesia Master Program in Computational Science Faculty of Mathematics and Natural Science Institut Teknologi Bandung Jalan Ganesha No. 10 Bandung40132 Indonesia Instrumentation and Computational Physics Research Group Department of Physics Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jalan Ganesha No.10 West Java Bandung40132 Indonesia

The implementation of titanium dioxide (TiO2) as a photocatalyst material in hydrogen (H2) evolution reaction (HER) has embarked renewed interest in the past decade. Rapid electron-hole pairs recombination and wide band gap of a photo-sensitive material of TiO2 are detrimental toward the targeted catalytical reaction. In this study, we present the rational design, fabrication, photocatalytic performance of TiO2-Cu/CuO/Cu2O heterostructures (CuTi) using viable chemical reduction method. The Z-scheme and S-scheme are succesfully generated across the TiO2/CuO/Cu2O interfaces, while the Schottky junction arises on the Cu perimeters. This is evidenced from the blue shifted about 0.3 eV of Cu 2p core level determined by using X-ray photoemission spectroscopy (XPS), in combination with the formation of inverse V-shape of the Mott-Schottky plots. In addition, we find that Cu/CuO/Cu2O facilitates photon absorption range up to the visible region. The multiple heterojunction and the large number of OHsurface enhanced charge carrier transfer are associated to the suppression of photoluminescence (PL) intensity, high surface hydroxyl (OHsurface) density in CuTi probed by XPS, and fast electron transfer based on the electrochemical measurements. The presence of OHsurface inhibits the recombination of electron. A significant H2 photogeneration rate enhancement is achieved when an optimized 5 wt% Cu/CuO/Cu2O concentration is used on TiO2 to achieve 7,157.19 μmol·g−1 (1,789.30 μmol·g−1·h−1). Based on this finding, zero emission energy innitiative could be materialized under multiple heterojunctions in photocatalytic process is beneficial for enhancing the H2 production. © 2025 The Authors

关键词： Titanium dioxide

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Molecular architecture of mammalian pyruvate dehydrogenase complex

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Protein & Cell 2025年第1期16卷 72-78页

作者： Maofei Chen Yutong Song Sensen Zhang Yitang Zhang Xudong Chen Minghui Zhang Meng Han Xin Gao Sai Li Maojun Yang Tsinghua-Peking Center for Life Sciences Beijing Frontier Research Center for Biological StructureSchool of Life SciencesTsinghua UniversityBeijing 100084China Ministry of Education Key Laboratory of Protein Science Tsinghua UniversityBeijing 100084China State Key Laboratory of Membrane Biology Tsinghua UniversityBeijing 100084China Department of Biochemistry and Molecular Biology School of Basic Medical SciencesShenzhen University Health Science CenterShenzhen 518060China Protein Research Technology Center Protein Chemistry and Omics PlatformSchool of Life SciencesTsinghua UniversityBeijing 100084China Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Kingdom of Saudi Arabia Cryo-EM Facility Center Southern University of Science and TechnologyShenzhen 518055China Beijing Life Science Academy Beijing 102209China

Dear Editor,Pyruvate dehydrogenase complex(PDHc) is a large multienzyme assembly(Mr = 4–10 million Daltons) consisting of three essential components: pyruvate dehydrogenase(E1p), dihydrolipoyl transacetylase(E2p), and dihydrolipoyl dehydrogenase(E3). These three enzymes perform distinct functions sequentially to catalyze the oxidative decarboxylation of pyruvate with formation of nicotinamide adenine dinucleotide(NADH) and acetyl-coenzyme A(Patel and Roche, 1990).

关键词： sequentially oxidative Dalton

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A novel biomechanical model of the proximal mouse forelimb predicts muscle activity in optimal control simulations of reaching movements

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Journal of Neurophysiology 2025年第4期133卷 1266-1278页

作者： Gilmer, Jesse I. Coltman, Susan K. Cuenu, Geraldine Hutchinson, John R. Huber, Daniel Person, Abigail L. Borno, Mazen Al Department of Computer Science and Engineering Computational Bioscience Program University of Colorado Denver j Anschutz Medical Campus Denver CO United States Department of Basic Neuroscience University of Geneva Geneva Switzerland Department of Physiology and Biophysics University of Colorado Denver j Anschutz Medical Campus Denver CO United States Department of Comparative Biomedical Sciences Royal Veterinary College London United Kingdom Department of Kinesiology The Pennsylvania State University University Park PA United States

Mice are key model organisms in neuroscience and motor systems physiology. Fine motor control tasks performed by mice have become widely used in assaying neural and biophysical motor system mechanisms. Although fine motor tasks provide useful insights into behaviors that require complex multi-joint motor control, there is no previously developed physiological biomechanical model of the adult mouse forelimb available for estimating kinematics, muscle activity, or kinetics during behaviors. Here, we developed a musculoskeletal model based on high-resolution imaging of the mouse forelimb that includes muscles spanning the neck, trunk, shoulder, and limbs. Physics-based optimal control simulations of the forelimb model were used to estimate in vivo muscle activity present when constrained to the tracked kinematics during reaching movements. The activity of a subset of muscles was recorded and used to assess the accuracy of the muscle patterning in simulation. We found that the synthesized muscle patterning in the forelimb model had a strong resemblance to empirical muscle patterning, suggesting that our model has utility in providing a realistic set of estimated muscle excitations over time when given a kinematic template. The strength of the similarity between empirical muscle activity and optimal control predictions increases as mice performance improves throughout learning of the reaching task. Our computational tools are available as open-source in the OpenSim physics and modeling platform. Our model can enhance research into limb control across broad research topics and can inform analyses of motor learning, muscle synergies, neural patterning, and behavioral research that would otherwise be inaccessible. NEW & NOTEWORTHY Investigations into motor planning and execution lack an accurate and complete model of the forelimb, which could bolster or expand on findings. We sought to construct such a model using high-detail scans of murine anatomy and prior research into

关键词： biophysical models motor control muscle patterning optimal control reaching behaviors

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Correction: Materials laboratories of the future for alloys, amorphous, and composite materials (MRS Bulletin, (2025), 50, 2, (190-207), 10.1557/s43577-024-00846-y)

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MRS Bulletin 2025年 1-2页

作者： Banerjee, Sarbajit Meng, Y. Shirley Minor, Andrew M. Zhang, Minghao Zaluzec, Nestor J. Chan, Maria K.Y. Seidler, Gerald McComb, David W. Agar, Joshua Mukherjee, Partha P. Melot, Brent Chapman, Karena Guiton, Beth S. Klie, Robert F. McCue, Ian D. Voyles, Paul M. Robertson, Ian Li, Ling Chi, Miaofang Destino, Joel F. Devaraj, Arun Marquis, Emmanuelle A. Segre, Carlo U. Liu, Huinan H. Yang, Judith C. Momeni, Kasra Misra, Amit Abdolrahim, Niaz Medvedeva, Julia E. Cai, Wenjun Sehirlioglu, Alp Dizbay-Onat, Melike Mehta, Apurva Graham-Brady, Lori Maruyama, Benji Rajan, Krishna Warner, Jamie H. Taheri, Mitra L. Kalinin, Sergei V. Reeja-Jayan, B. Schwarz, Udo D. Simon, Sindee L. Brown, Craig M. Department of Chemistry and Department of Materials Science & Engineering Texas A & M University College Station United States Pritzker School of Molecular Engineering The University of Chicago Chicago United States Department of Materials Science & Engineering University of California Berkeley Berkeley United States National Center for Electron Microscopy Molecular Foundry Lawrence Berkeley National Laboratory Berkeley United States Center for Nanoscale Materials Argonne National Laboratory Lemont United States Department of Physics University of Washington Seattle United States Department of Materials Science & Engineering The Ohio State University Columbus United States Department of Mechanical Engineering and Mechanics Drexel University Philadelphia United States School of Mechanical Engineering Purdue University West Lafayette United States Department of Chemistry University of Southern California Los Angeles United States Department of Chemistry Stony Brook University The State University of New York Stony Brook United States Department of Chemistry University of Kentucky Lexington United States Department of Physics University of Illinois at Chicago Chicago United States Department of Materials Science & Engineering Northwestern University Evanston Bangladesh Department of Materials Science & Engineering University of Wisconsin–Madison Madison United States Department of Materials Science and Engineering University of Pennsylvania Philadelphia United States Department of Mechanical Engineering and Materials Science Duke University Durham United States Department of Chemistry Creighton University Omaha United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory Richland United States Department of Materials Science & Engineering University of Michigan–Ann Arbor Ann Arbor United States Department of Physics Illinois Institute of Technology Chicago United States Department of Bioengineering and the Mater

This article was updated to correct Minghao Zhang’s affiliation from "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA" to "Pritzker School of Molecular engineering, The University of Chicago, Chicago, USA;Argonne National Laboratory, Lemont, USA." Argonne National Laboratory was left off the original publication. © The Author(s) 2025.

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Improving energy conversion efficiency of ion-driven artificial muscles based on carbon nanotube yarn

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Journal of Power Sources 2025年 646卷

作者： Hyeon, Jae Sang Wang, Qiong Tawfick, Sameh Lee, JeongA Smith, Kyle C. Zhang, Mengmeng Park, Jong Woo Song, Gyu Hyeon Wang, Zhong Fang, Shaoli Baughman, Ray H. Kim, Seon Jeong Department of Biomedical Engineering and Electronic Engineering Hanyang University Seoul04763 Korea Republic of Department of Mechanical Science and Engineering Grainger College of Engineering University of Illinois at Urbana-Champaign Urbana61801 United States Department of Materials Science and Engineering Grainger College of Engineering University of Illinois at Urbana-Champaign Urbana61801 United States Beckman Institute for Advanced Science and Technology Grainger College of Engineering University of Illinois at Urbana-Champaign Urbana61801 United States Computational Science and Engineering Program Grainger College of Engineering University of Illinois at Urbana-Champaign Urbana61801 United States Alan G. MacDiarmid NanoTech Institute University of Texas at Dallas Richardson75080 United States

While artificial muscles provide giant work and power densities compared to natural muscles, their reported energy conversion efficiencies have so far been low. We here demonstrate a tension optimization process (TOP) for fabricating coiled carbon nanotube artificial muscles having record efficiencies. These TOP muscles were made by applying about 20 times higher tensile stress during pre-coiling twist insertion than the tensile stress applied during coiling, resulting in high twist density and high spring index. The TOP muscles driven by the tetrabutylammonium cation provide 6.1 J/g contractile work, which is ∼152 times the maximum capability of human skeletal muscles, and 13.1 % contractile energy efficiency. In addition, the contractile energy efficiency of the TOP muscles driven by the bis(trifluoromethanesulfonyl)imide anion is maximized to 38.8 % by minimizing side redox reactions. In the case of full-cycle actuation, which considers the whole cycle of contraction and relaxation, we increased the full-cycle energy conversion efficiency of TOP muscles to 6.7 %, which is 4.5 times that previously reported for ion-driven artificial muscles. © 2025 Elsevier B.V.

关键词： Energy conversion efficiency

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Unbiased Parameter Estimation for Bayesian Inverse Problems

arXiv

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arXiv 2025年

作者： Chada, Neil K. Jasra, Ajay Maama, Mohamed Tempone, Raul Department of Mathematics City University of Hong Kong China School of Data Science The Chinese University of Hong Kong Shenzhen CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a solution of a differential equation and, even if exact solutions are available, an analytical intractability of the marginal likelihood and its associated gradient, which is used for parameter estimation. The focus of this article is to deliver unbiased estimates of the unknown parameters, that is, stochastic estimators that, in expectation, are equal to the maximizer of the marginal likelihood, and possess no numerical approximation error. Based upon the ideas of [4] we develop a new approach for unbiased parameter estimation for Bayesian inverse problems. We prove unbiasedness and establish numerically that the associated estimation procedure is faster than the current state-of-the-art methodology for this problem. We demonstrate the performance of our methodology on a range of problems which include a PDE and ODE. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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