Article
Multidisciplinary Sciences
John E. Fleming, Vaclav Kremen, Ro'ee Gilron, Nicholas M. Gregg, Mayela Zamora, Derk-Jan Dijk, Philip A. Starr, Gregory A. Worrell, Simon Little, Timothy J. Denison
Summary: Biological rhythms play a crucial role in physiology and pathophysiology. However, the influence of these rhythms on bioelectronic medicine has been difficult to analyze due to limitations in current neuromodulation device technology. As new devices are developed to overcome these limitations, it is important to incorporate chronobiological considerations in their control structures to maximize the benefits of neuromodulation therapy.
Article
Cell Biology
Nicolette Driscoll, Brian Erickson, Brendan B. Murphy, Andrew G. Richardson, Gregory Robbins, Nicholas Apollo, Georgios Mentzelopoulos, Tyler Mathis, Kanit Hantanasirisakul, Puneet Bagga, Sarah E. Gullbrand, Matthew Sergison, Ravinder Reddy, John A. Wolf, H. Isaac Chen, Timothy H. Lucas, Timothy R. Dillingham, Kathryn A. Davis, Yury Gogotsi, John D. Medaglia, Flavia Vitale
Summary: MXtrodes are a class of soft, high-resolution, large-scale bioelectronic interfaces enabled by Ti3C2 MXene and scalable solution processing. They exhibit superior electro-chemical properties compared to conventional materials, do not require conductive gels, and have been validated in various applications.
SCIENCE TRANSLATIONAL MEDICINE
(2021)
Article
Materials Science, Multidisciplinary
Xiaomin Luo, Ying Liu, Rong Qin, Fen Ao, Xuechuan Wang, Huijie Zhang, Min Yang, Xinhua Liu
Summary: Inspired by natural skin, a multifunctional hydrogel (CHHCMgel) with various features such as flexibility, antibacterial properties, electrical activity, bioadhesive ability, self-healing ability, and hemostatic properties, has been developed. CHHCMgel possesses adjustable mechanical and bioelectroactive characteristics, fast gelation time, and repeatable adhesion. Furthermore, it exhibits high biocompatibility and extensive antibacterial activity.
APPLIED MATERIALS TODAY
(2022)
Review
Biochemistry & Molecular Biology
Maifu Yu, Pin Sun, Changkai Sun, Wei-Lin Jin
Summary: Neurodegenerative diseases are common and difficult to treat, but cell therapy shows promise. Endogenous neural stem cells (eNSCs) have potential but are currently underexplored. This article compares stem cell transplantation with eNSC-based therapy and highlights the potential of combining eNSCs with developing technologies, such as bioelectronic medicine and biomaterials.
TRENDS IN MOLECULAR MEDICINE
(2023)
Article
Chemistry, Multidisciplinary
Shirley L. Yitzhak-David, Menahem Y. Rotenberg
Summary: Electroceuticals have great potential for both basic research and clinical applications, but the invasive nature of the leads is a major limitation. To address this issue, leadless bio-modulation technologies, such as optoelectronic devices and materials, have been proposed. This perspective article highlights the recent advances in this field and discusses their limitations and potential.
CELL REPORTS PHYSICAL SCIENCE
(2023)
Article
Multidisciplinary Sciences
Patrick D. Ganzer, Masoud S. Loeian, Steve R. Roof, Bunyen Teng, Luan Lin, David A. Friedenberg, Ian W. Baumgart, Eric C. Meyers, Keum S. Chun, Adam Rich, Allison L. Tsao, William W. Muir, Doug J. Weber, Robert L. Hamlin
Summary: This study demonstrates an artificially intelligent and responsive bioelectronic medicine system that supplements myocardial sensory networks for the reliable detection and correction of myocardial ischemia. Trained artificial neural networks can accurately decode cardiovascular stress and myocardial ischemia, and controlled vagus nerve stimulation significantly mitigates the physiological features of myocardial ischemia. The study also explores variants of artificial neural networks for clinically relevant needs, such as interpretable visualizations and unsupervised detection of emerging cardiovascular stress.
Article
Engineering, Chemical
Rajendran Shankar, Narayanan Ganesh, Robert Cep, Rama Chandran Narayanan, Subham Pal, Kanak Kalita
Summary: The optimization of industrial processes is crucial for profitability and sustainability. This paper proposes a hybrid metaheuristic algorithm, PSO-GSA, which combines the iterative improvement capability of PSO and GSA for selecting optimal process parameter levels. Comparisons on two real-world case studies show that the PSO-GSA algorithm outperforms traditional algorithms in finding significantly better solutions.
Article
Operations Research & Management Science
Kwassi Joseph Dzahini
Summary: This work introduces an algorithm designed to optimize differentiable objective functions computed through a stochastically noisy blackbox. The analysis aims to show the expected number of iterations required to drive the norm of the gradient below a given threshold. The proposed method's convergence rate is similar to other stochastic optimization methods and deterministic direct-search methods with a dependence on epsilon.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Abdesslem Layeb
Summary: This article introduces a new population-based optimization algorithm called Tangent Search Algorithm (TSA) for solving optimization problems. The TSA utilizes a mathematical model based on the tangent function to move a given solution towards a better solution, balancing between exploitation and exploration search. It also incorporates a novel escape procedure to avoid local minima and an adaptive variable step-size for enhanced convergence capacity. Experimental results show that the TSA algorithm yields promising and competitive results in various tests, demonstrating its simplicity, efficiency, and requirement of only a small number of user-defined parameters.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Chemistry, Analytical
Youngjun Cho, Heejae Shin, Jaeu Park, Sanghoon Lee
Summary: Research has proposed a neural interface for modulating peripheral nerves, including autonomic nerves, which requires stability, ease of implantation, and biocompatibility.
Article
Automation & Control Systems
Jordan J. Romvary, Giulio Ferro, Rabab Haider, Anuradha M. Annaswamy
Summary: This article introduces a unified framework for distributed convex optimization using a algorithm called proximal atomic coordination (PAC). The convergence of PAC is proven in both objective values and distance to feasibility. Various decomposition strategies and coordination graphs are explored in relation to the convergence rate of PAC. Additionally, the algorithmic complexity of PAC is compared with another popular distributed algorithm. The advantages of PAC are enumerated, including its relevance to privacy. The theoretical results are validated using a power distribution grid model in the context of the optimal power flow problem.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Mathematics, Applied
Joel Blot, Hasan Yilmaz
Summary: In this paper, we establish the differentiability properties of the value function for static optimization problems in an abstract infinite dimensional setting, and apply it to problems of calculus of variations. We lighten the assumptions of existing results by using Gateaux and Hadamard differentials and also utilize recently established Multipliers Rules.
JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS
(2022)
Article
Mathematics
Mohammed H. Qais, Hany M. Hasanien, Rania A. Turky, Saad Alghuwainem, Marcos Tostado-Veliz, Francisco Jurado
Summary: This paper presents a novel metaheuristic optimization algorithm called the circle search algorithm (CSA) that is inspired by the geometrical features of circles. The CSA is evaluated against other algorithms through independent experiments using a variety of functions and engineering problems, and the results show that CSA outperforms other algorithms in terms of convergence speed and robustness to high-dimensional problems. Therefore, CSA is a promising algorithm for solving various optimization problems.
Article
Computer Science, Artificial Intelligence
Benson Shu Yan Lam, Alan Wee-Chung Liew
Summary: This paper proposes a BQP solver that alternates between deterministic search and stochastic neighborhood search to tackle large BQP problems. Experimental results demonstrate that the proposed solver outperforms other methods in terms of solution quality and computational complexity.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Multidisciplinary Sciences
Hueseyin Demirci, Niluefer Yurtay, Yueksel Yurtay, Esin Ayse Zaimoglu
Summary: In this study, a new metaheuristic algorithm called Electrical Search Algorithm (ESA) was proposed. ESA is based on the movement of electricity in high-resistive areas. It has a unique initialization scheme and utilizes unique exploration and exploitation strategies. ESA differs from other metaheuristics in terms of its initialization scheme, pole search mechanism, and update strategy of the best solutions. It was tested on benchmark functions and a clustering problem, and compared with other algorithms.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Article
Biophysics
Elif Kubat Oktem, Karen Mruk, Joshua Chang, Ata Akin, William R. Kobertz, Robert H. Brown
JOURNAL OF BIOLOGICAL PHYSICS
(2016)
Article
Multidisciplinary Sciences
Joshua Chang, David Paydarfar
SCIENTIFIC REPORTS
(2018)
Article
Infectious Diseases
Sun-Young Kim, Steven Sweet, Joshua Chang, Sue J. Goldie
BMC INFECTIOUS DISEASES
(2011)
Article
Mathematical & Computational Biology
Joshua Chang, David Paydarfar
JOURNAL OF COMPUTATIONAL NEUROSCIENCE
(2014)
Correction
Multidisciplinary Sciences
Joshua Chang, David Paydarfar
SCIENTIFIC REPORTS
(2018)
Article
Mathematics, Applied
Joshua Chang, Varun Sridhar, David Paydarfar
Proceedings Paper
Engineering, Biomedical
Joshua Chang, David Paydarfar
2015 7TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER)
(2015)
Article
Optics
Leaf A. Jiang, Eric A. Dauler, Joshua T. Chang
