Article
Chemistry, Multidisciplinary
Edward C. Burks, Dustin A. Gilbert, Peyton D. Murray, Chad Flores, Thomas E. Felter, Supakit Charnvanichborikarn, Sergei O. Kucheyev, Jeffrey D. Colvin, Gen Yin, Kai Liu
Summary: This study achieved free-standing, interconnected metallic nanowire networks with low density, and proposed a new research direction in exploring 3-dimensional nanomagnetism and magnetization reversal mechanisms. These findings provide new possibilities for developing 3-dimensional integrated magnetic devices for various applications.
Article
Chemistry, Multidisciplinary
Dhritiman Bhattacharya, Zhijie Chen, Christopher J. Jensen, Chen Liu, Edward C. Burks, Dustin A. Gilbert, Xixiang Zhang, Gen Yin, Kai Liu
Summary: Interconnected magnetic nanowire networks show promise for 3D information storage and integrated neuromorphic computing. Discrete propagation of magnetic states driven by magnetic field and current is observed in these networks, resulting in distinct magnetoresistance features. The pinning of domain walls at the intersections of nanowires leads to the observed phenomenon.
Article
Quantum Science & Technology
Cristhian Roman-Vicharra, James J. Cai
Summary: In this study, a quantum circuit model was proposed to infer gene regulatory networks (GRNs) from single-cell transcriptomic data. The model utilized qubit entanglement to simulate interactions between genes, showing competitive performance and potential for further exploration. The application of the quantum GRN modeling approach to human lymphoblastoid cells successfully predicted regulatory interactions between genes and estimated the strength of these interactions. This work highlights the potential of quantum computing in biology for a better understanding of single-cell GRNs.
NPJ QUANTUM INFORMATION
(2023)
Article
Computer Science, Information Systems
Chaowei Fang, Haibin Tian, Dingwen Zhang, Qiang Zhang, Jungong Han, Junwei Han
Summary: This paper proposes a novel framework based on densely nested top-down flows for salient object detection. The framework enhances the propagation of high-level features, alleviates the gradient vanishing issues, and improves memory efficiency. The integration of this framework with EfficientNet leads to a highly light-weighted SOD model.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Article
Engineering, Electrical & Electronic
Federico Chiariotti, Olga Vikhrova, Beatriz Soret, Petar Popovski
Summary: Age of Information (AoI) is a critical metric for Internet of Things (IoT) applications, where fresh updates from sensors are essential. The development of edge computing solutions has reduced communication delays but processing time at the edge node must be considered. Reliable system design in terms of freshness requires understanding the full distribution of the Peak AoI (PAoI).
IEEE TRANSACTIONS ON COMMUNICATIONS
(2021)
Article
Psychology, Multidisciplinary
Yan Ma
Summary: The study reveals that communication strategies have a significant impact on organizational commitment and faculty engagement, with information flow and information feedback being particularly influential. However, information adequacy only affects organizational commitment. Faculty engagement mediates the relationship between information flow and organizational commitment, as well as between information feedback and organizational commitment. The study contributes both theoretically, by examining different communication strategies, and practically, by offering valuable insights for educational institutes.
FRONTIERS IN PSYCHOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Wenwen Ye, Shengping Li
Summary: The flow direction algorithm (FDA) is a physics-based meta-heuristic optimization algorithm that has been successfully applied in various fields. However, FDA lacks rigorous convergency analysis and faces issues such as premature convergence, lack of diversity, and imbalance between exploitation and exploration. This paper introduces the supermartingale convergence theorem to analyze FDA's global convergence and proposes an improved version called guided flow direction algorithm (GFDA) to enhance diversity and exploration. Experimental studies demonstrate the superiority of GFDA over other algorithms using multiple benchmark functions and constrained optimization problems.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Biochemistry & Molecular Biology
Meghan D. J. Bragdon, Nikit Patel, James Chuang, Ethan Levien, Caleb J. Bashor, Ahmad S. Khalil
Summary: This study demonstrates that high regulatory specificity can be achieved through cooperative multivalent interactions among artificial zinc-finger-based transcription factors. This mechanism effectively prevents aberrant misregulation of the host cell genome, resulting in genetic and functional stability of synthetic gene circuits.
Article
Automation & Control Systems
Yun Xiang, Chong Lin, Bing Chen, Qing-Guo Wang
Summary: This paper proposes a new decentralized adaptive event-triggered scheme and introduces a method for H infinity performance analysis of filter error system using fuzzy line-integral method. The sufficient conditions for meeting H infinity performance of the filter error system are established through the combination of Wirtinger-based inequality and extended reciprocally convex matrix inequality.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Computer Science, Artificial Intelligence
Shaocheng Tong, Yongming Li, Yanjun Liu
Summary: This article investigates an adaptive neural network decentralized output-feedback control design for uncertain large-scale interconnected nonlinear systems. The proposed control method ensures semiglobal uniform ultimate boundedness of the closed-loop system, with tracking and observer errors converging to a small neighborhood of the origin. The key contribution is removing the restrictive assumption that virtual and control gain functions in each subsystem must be constants.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Mathematics, Applied
Pratap Anbalagan, Evren Hincal, Raja Ramachandran, Dumitru Baleanu, Jinde Cao, Michal Niezabitowski
Summary: This manuscript focuses on the stability and synchronization of fractional-order delayed gene regulatory networks (FODGRNs) using the Razumikhin approach. Unique to this work is the exploration of global Mittag-Letter stability of FODGRNs based on the fractional-order Lyapunov Razumikhin approach. By designing controllers and utilizing the fractional Razumikhin theorem, global Mittag-Letter synchronization and adaptive synchronization for master-slave systems were achieved, with the applicability of the results justified through numerical cases.
Article
Computer Science, Artificial Intelligence
Qian Li, YuFeng Xie, XinHong Wu, Yunpeng Xiao
Summary: Traditional prediction models of rumor forwarding based solely on explicit network topology are not effective due to the lack of consideration for homogeneity and antagonism among multi-type rumor messages. This study proposes a user behavior prediction model based on implicit links and multi-type rumor messages to address these problems. By considering user interactions and similarities comprehensively, implicit links among non-friends are mined using the K-dimension-tree algorithm to improve the network topology. The advantages of graph convolutional networks (GCNs) model in network representation are utilized to fully represent rumor information, user characteristics, and network structure, resulting in improved generalization ability of the proposed model.
KNOWLEDGE-BASED SYSTEMS
(2023)
Article
Physics, Multidisciplinary
Li Cao, Haibo Zhao, Xiaoying Wang, Xuming An
Summary: In this study, a competitive information propagation model considering multi-layer network topology and individual adaptive behavior is proposed. The theoretical stability of information equilibria is proven through the calculation of the basic reproduction number. Additionally, an optimal control problem is formulated and the effectiveness of the proposed control strategies is evaluated through numerical experiments.
FRONTIERS IN PHYSICS
(2023)
Article
Biochemical Research Methods
Haonan Feng, Ruiqing Zheng, Jianxin Wang, Fang-Xiang Wu, Min Li
Summary: Gene regulatory networks play a crucial role in biological processes, and existing expression data can be used to infer these networks using computational methods. However, identifying indirect regulatory links remains a challenge. In this study, a novel information-theory-based method is proposed to improve the identification of regulatory relationships between genes.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Mathematics, Interdisciplinary Applications
Lu Wang, Xujun Yang, Hongjun Liu, Xiaofeng Chen
Summary: This paper investigates the synchronization in finite time of fractional-order complex-valued gene networks with time delays. Several sufficient conditions for the synchronization in finite time of the relevant network models are explored using feedback controllers and adaptive controllers. The setting time of the response is then estimated using the theory of fractional calculus. Finally, a numerical example is presented to validate the theoretical results, demonstrating that the setting time based on the adaptive controller is shorter than that based on the feedback controller.
FRACTAL AND FRACTIONAL
(2023)
Article
Multidisciplinary Sciences
Patrick W. Kudella, Alexei Tkachenko, Annalena Salditt, Sergei Maslov, Dieter Braun
Summary: Through templated ligation reactions, the study found that linking short oligomers from a random sequence pool reduces the sequence space of product strands, resulting in long, highly structured sequences with low entropy. This self-selecting ligation reaction can be restarted by only a few majority sequences, providing a favorable starting point for Darwinian evolution in an RNA world scenario.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Multidisciplinary Sciences
Akshit Goyal, Tong Wang, Veronika Dubinkina, Sergei Maslov
Summary: Combining ecology-based computational methods and optimization techniques, GutCP predicts a large number of experimentally untested cross-feeding interactions in the human gut microbiome. It has the potential to improve microbial community models and predict the metabolic profile of the gut.
NATURE COMMUNICATIONS
(2021)
Article
Multidisciplinary Sciences
Alexei Tkachenko, Sergei Maslov, Ahmed Elbanna, George N. Wong, Zachary J. Weiner, Nigel Goldenfeld
Summary: Research shows that during the early stages of an epidemic, a transient collective immunity state may emerge as herd immunity forms, but this state is fragile and fades over time, meaning that the infection peak does not necessarily indicate long-lasting herd immunity; factors such as seasonal changes can lead to subsequent waves.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Biology
Michael Doebeli, Eduardo Cancino Jaque, Yaroslav Ispolatov
Summary: The competitive exclusion principle suggests that the number of coexisting species is limited by resources or similarity in resource use, but mathematical and eco-evolutionary models show that boom-bust dynamics may lead to the evolution and maintenance of more diversity.
COMMUNICATIONS BIOLOGY
(2021)
Review
Biochemical Research Methods
Fangfang Xia, Jonathan Allen, Prasanna Balaprakash, Thomas Brettin, Cristina Garcia-Cardona, Austin Clyde, Judith Cohn, James Doroshow, Xiaotian Duan, Veronika Dubinkina, Yvonne Evrard, Ya Ju Fan, Jason Gans, Stewart He, Pinyi Lu, Sergei Maslov, Alexander Partin, Maulik Shukla, Eric Stahlberg, Justin M. Wozniak, Hyunseung Yoo, George Zaki, Yitan Zhu, Rick Stevens
Summary: To enable personalized cancer treatment, machine learning models have been developed to predict drug response based on tumor and drug features. This study used machine learning to analyze five publicly available cell line-based data sets and rigorously evaluated the model generalizability between different studies. The results showed that a multitasking deep neural network achieved the best cross-study generalizability, with models trained on the CTRP data set providing the most accurate predictions on testing data, and the gCSI data set being the most predictable among the cell line data sets.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Ilan N. Rubin, Iaroslav Ispolatov, Michael Doebeli
Summary: Recent studies have shown that natural populations may get stuck in low diversity states following an adaptive radiation, due to mutations of small phenotypic effect. These low diversity states can be maintained by limited resources and finite population sizes, despite the presence of higher-diversity stable states.
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Multidisciplinary Sciences
Zihan Wang, Akshit Goyal, Veronika Dubinkina, Ashish B. George, Tong Wang, Yulia Fridman, Sergei Maslov
Summary: Many microbes grow diauxically, utilizing resources one at a time rather than simultaneously. This study developed a minimal model of diauxic microbial communities assembling in a serially diluted culture, providing testable predictions for the assembly of natural as well as synthetic communities of diauxically shifting microorganisms.
NATURE COMMUNICATIONS
(2021)
Article
Biology
Alexei Tkachenko, Sergei Maslov, Tong Wang, Ahmed Elbana, George N. Wong, Nigel Goldenfeld
Summary: This article discusses the importance of dynamic heterogeneity in the spread of epidemics, and demonstrates the emergence of a new long timescale by integrating the stochastic dynamics of social activity into traditional epidemiological models.
Article
Multidisciplinary Sciences
Viktor Mamontov, Alexander Martynov, Natalia Morozova, Anton Bukatin, Dmitry B. Staroverov, Konstantin A. Lukyanov, Yaroslav Ispolatov, Ekaterina Semenova, Konstantin Severinov
Summary: This study demonstrates that plasmids can persist for multiple generations in certain Escherichia coli cell lineages under continuous targeting by the type I-E CRISPR-Cas system. The researchers propose that this complex dynamic process provides long-term benefits for bacterial populations by maintaining mobile genetic elements in some cells, leading to phenotypic diversification and rapid changes in the population structure to meet the demands of a changing environment.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2022)
Article
Multidisciplinary Sciences
Diana Rose E. Ranoa, Robin L. Holland, Fadi G. Alnaji, Kelsie J. Green, Leyi Wang, Richard L. Fredrickson, Tong Wang, George N. Wong, Johnny Uelmen, Sergei Maslov, Zachary J. Weiner, Alexei Tkachenko, Hantao Zhang, Zhiru Liu, Ahmed Ibrahim, Sanjay J. Patel, John M. Paul, Nickolas P. Vance, Joseph G. Gulick, Sandeep Puthanveetil Satheesan, Isaac J. Galvan, Andrew Miller, Joseph Grohens, Todd J. Nelson, Mary P. Stevens, P. Mark Hennessy, Robert C. Parker, Edward Santos, Charles Brackett, Julie D. Steinman, Melvin R. Fenner, Kirstin Dohrer, Michael DeLorenzo, Laura Wilhelm-Barr, Brian R. Brauer, Catherine Best-Popescu, Gary Durack, Nathan Wetter, David M. Kranz, Jessica Breitbarth, Charlie Simpson, Julie A. Pryde, Robin N. Kaler, Chris Harris, Allison C. Vance, Jodi L. Silotto, Mark Johnson, Enrique Andres Valera, Patricia K. Anton, Lowa Mwilambwe, Stephen P. Bryan, Deborah S. Stone, Danita B. Young, Wanda E. Ward, John Lantz, John A. Vozenilek, Rashid Bashir, Jeffrey S. Moore, Mayank Garg, Julian C. Cooper, Gillian Snyder, Michelle H. Lore, Dustin L. Yocum, Neal J. Cohen, Jan E. Novakofski, Melanie J. Loots, Randy L. Ballard, Mark Band, Kayla M. Banks, Joseph D. Barnes, Iuliana Bentea, Jessica Black, Jeremy Busch, Abigail Conte, Madison Conte, Michael Curry, Jennifer Eardley, April Edwards, Therese Eggett, Judes Fleurimont, Delaney Foster, Bruce W. Fouke, Nicholas Gallagher, Nicole Gastala, Scott A. Genung, Declan Glueck, Brittani Gray, Andrew Greta, Robert M. Healy, Ashley Hetrick, Arianna A. Holterman, Nahed Ismail, Ian Jasenof, Patrick Kelly, Aaron Kielbasa, Teresa Kiesel, Lorenzo M. Kindle, Rhonda L. Lipking, Yukari C. Manabe, Reubin McGuffin, Kenton G. McHenry, Agha Mirza, Jada Moseley, Heba H. Mostafa, Melody Mumford, Kathleen Munoz, Arika D. Murray, Moira Nolan, Nil A. Parikh, Andrew Pekosz, Janna Pflugmacher, Janise M. Phillips, Collin Pitts, Mark C. Potter, James Quisenberry, Janelle Rear, Matthew L. Robinson, Edith Rosillo, Leslie N. Rye, MaryEllen Sherwood, Anna Simon, Jamie M. Singson, Carly Skadden, Tina H. Skelton, Charlie Smith, Mary Stech, Ryan Thomas, Matthew A. Tomaszewski, Erika A. Tyburski, Scott Vanwingerden, Evette Vlach, Ronald S. Watkins, Karriem Watson, Karen C. White, Timothy L. Killeen, Robert J. Jones, Andreas C. Cangellaris, Susan A. Martinis, Awais Vaid, Christopher B. Brooke, Joseph T. Walsh, Ahmed Elbanna, William C. Sullivan, Rebecca L. Smith, Nigel Goldenfeld, Timothy M. Fan, Paul J. Hergenrother, Martin D. Burke
Summary: This study reports on a case study at the University of Illinois at Urbana-Champaign, where a program of public health measures and other non-pharmaceutical interventions were employed to keep classrooms and laboratories open during the COVID-19 pandemic. The results showed that fast/frequent testing and other interventions helped mitigate transmission of SARS-CoV-2 at the university.
NATURE COMMUNICATIONS
(2022)
Article
Biochemical Research Methods
Yulia Fridman, Zihan Wang, Sergei Maslov, Akshit Goyal
Summary: Recent observations have shown that closely related strains of the same microbial species can stably coexist in different environments. A consumer-resource model of microbial ecosystems suggests that differentiation of strains based on their growth rates in high and low nutrient conditions enables coexistence. The model also demonstrates that between 1 and 3 strains of a species typically coexist, consistent with experimental observations.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Computer Science, Artificial Intelligence
Tong Wang, Xu-Wen Wang, Kathleen A. Lee-Sarwar, Augusto A. Litonjua, Scott T. Weiss, Yizhou Sun, Sergei Maslov, Yang-Yu Liu
Summary: The authors introduce a deep learning method called mNODE for predicting metabolic profiles of microbial communities. mNODE outperforms existing methods and can reveal microbe-metabolite interactions, providing valuable insights for precision nutrition research.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Biology
Yaroslav Ispolatov, Carlos Doebeli, Michael Doebeli
Summary: In models for the evolution of predation, predation ability is often assumed to be a result of the relative morphological and physiological traits of interacting species. This study explores a model where predation ability evolves independently as a phenotypic feature, so that even when morphological or physiological traits allow for predation, it only occurs if individuals have evolved sufficiently high predation ability. The model not only identifies the conditions for the emergence of predation, but also reproduces multilevel food webs with top predators not necessarily having size superiority.
JOURNAL OF THEORETICAL BIOLOGY
(2023)
Article
Biochemical Research Methods
Ananthan Nambiar, Simon Liu, Maeve Heflin, John Malcolm Forsyth, Sergei Maslov, Mark Hopkins, Anna Ritz
Summary: The scientific community is generating protein sequence information rapidly, but only a small fraction can be experimentally validated. We propose a Transformer neural network that fine-tunes task-agnostic sequence representations for protein prediction tasks, achieving satisfactory results.
JOURNAL OF COMPUTATIONAL BIOLOGY
(2023)
Meeting Abstract
Pharmacology & Pharmacy
F. Rashid, V. Dubinkina, S. Maslov, J. Irudayaraj
INTERNATIONAL JOURNAL OF TOXICOLOGY
(2022)
