Article
Computer Science, Interdisciplinary Applications
Xinxin Yue, Jian Zhang, Weijie Gong, Min Luo, Libin Duan
Summary: The novel PCE-HDMR algorithm proposed in this article integrates PCE with Cut-HDMR to provide simple and explicit approximations for a wide range of high-dimensional problems efficiently. Comprehensive comparisons on various mathematical functions and engineering examples show that PCE-HDMR has superior accuracy and robustness in terms of both global and local error metrics.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2021)
Article
Engineering, Mechanical
Jie Liu, Yue Zhao, Fei Lei, Fei Ding
Summary: This paper proposes the Net-HDMR method based on the Cut-HDMR framework for approximating complex high-dimensional engineering design problems. The method incorporates two novel modeling approaches that enhance the accuracy and efficiency of HDMR. The proposed method is validated through numerical benchmark examples and an engineering problem of thermal stress and deformation analysis for a jet engine turbine blade.
JOURNAL OF MECHANICAL DESIGN
(2023)
Article
Engineering, Mechanical
Qi Zhang, Yizhong Wu, Li Lu, Ping Qiao
Summary: This study proposes a new standalone HDMR metamodeling technique called Dendrite-HDMR, which provides succinct and explicit expressions and demonstrates higher accuracy and stability in improving the model through the adaptive sampling strategy KKMC.
JOURNAL OF MECHANICAL DESIGN
(2022)
Article
Computer Science, Artificial Intelligence
Evrim Korkmaz Ozay, Burcu Tunga
Summary: A novel pansharpening method based on Adaptive High Dimensional Model Representation is proposed in this article, which optimizes HDMR components and weighting factors to reduce spectral distortion and improve image quality.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
J. V. Thomas Abraham, A. Muralidhar, Kamsundher Sathyarajasekaran, N. Ilakiyaselvan
Summary: The digestive tract is affected by digestive ailments, including heartburn, cancer, IBS, and lactose intolerance. Different surgical treatments, such as laparoscopy, open surgery, and endoscopy, can be used to treat digestive diseases. This paper proposes transfer-learning models with pre-trained models to identify and classify digestive diseases.
Article
Biochemical Research Methods
Wei Peng, Sichen Yi, Wei Dai, Jianxin Wang
Summary: This study introduces a new method RLAG that identifies potential cancer driver genes by combining network structure and node attributes, and then prioritizes them based on importance. In the prediction of driver genes for lung cancer, breast cancer, and prostate cancer, the method outperforms other state-of-the-art methods.
Article
Engineering, Chemical
Haoxing Li, Jianhong Lei, Ming Jia, Hongpeng Xu, Shaohua Wu
Summary: This paper proposes a new biomass gasification technology combining solar thermal and supercritical water gasification, and solves the intermittent operation issue with a molten salt energy storage system. The high dimensional model representation (HDMR) approach is used to predict the gas production and lower heating value, and validated with experimental data. Multi-objective optimization results for five different types of biomass are discussed.
Article
Biochemical Research Methods
Xiwen Zhang, Weiwen Wang, Chuan-Xian Ren, Dao-Qing Dai
Summary: This article introduces a representation learning method for multiple biological networks. The method utilizes denoised diffusion and graph regularized integration to handle noise and spurious edges, while preserving the common structure and specific information of different networks, resulting in useful representation features.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Engineering, Civil
Jingliang Duan, Dongjie Yu, Shengbo Eben Li, Wenxuan Wang, Yangang Ren, Ziyu Lin, Bo Cheng
Summary: In this paper, a new state representation method called encoding sum and concatenation (ESC) is proposed for decision-making in autonomous driving. Unlike existing methods, ESC can handle variable number of surrounding vehicles without pre-defined sorting rules. The proposed method uses a feature neural network to encode the feature of each surrounding vehicle and obtain a representation vector. Experiments show that using ESC representation improves the policy learning accuracy by 62.2% compared to fixed-permutation representation.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Rabi Shaw, Bidyut Kr. Patra
Summary: Flipped learning is an effective teaching method accomplished through pre-loaded lecture videos and in-class activities. However, the inability to monitor students' learning progress during video lectures may impact learning outcomes.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Materials Science, Multidisciplinary
Dimitri Pimenov, Alex Kamenev, Andrey Chubukov
Summary: Forward scattering and backscattering are crucial in the physics of two-dimensional interacting fermions, leading to nonanalytic behavior in the fermionic scattering rate. Higher powers of ln(omega) are found in the backscattering contribution at higher orders. By extending Fermi liquid to a certain limit, planar processes dominate and provide insights into the scattering rate behavior in different interaction scenarios.
Article
Spectroscopy
Danying Ma, Linwei Shang, Jinlan Tang, Yilin Bao, Juanjuan Fu, Jianhua Yin
Summary: By combining Raman spectroscopy and one-dimensional convolutional neural network (1D-CNN) algorithm, this study successfully achieved high classification performance for automatic diagnosis of breast cancer. Analysis of Raman spectra from patient breast samples, development and training of a 1D-CNN model improved the efficiency of breast cancer diagnosis.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2021)
Article
Computer Science, Artificial Intelligence
Arul Antran Vijay Subramanian, Jothi Prakash Venugopal
Summary: Breast cancer is a leading cause of death in women worldwide. Accurate medical diagnosis is crucial for reducing fatality rates. This paper proposes a deep ensemble network method for classifying and predicting breast cancer, using machine learning techniques to improve accuracy and aid in early detection and treatment.
COMPUTATIONAL INTELLIGENCE
(2023)
Article
Cell Biology
Bolin Chen, Yourui Han, Xuequn Shang, Shenggui Zhang
Summary: Identifying disease related genes is crucial in bioinformatics. Deep learning methods have been successful, but often do not address gene multifunctionality and the scale-free property of biological networks well. A novel network representation method was proposed to tackle these challenges, showing promising results in numerical experiments.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Biochemical Research Methods
Qiguo Dai, Ziqiang Liu, Zhaowei Wang, Xiaodong Duan, Maozu Guo
Summary: The study introduced a hybrid graph representation learning framework called GraphCDA for predicting circRNA-disease associations. Experimental results showed that GraphCDA outperformed other methods on public databases and achieved good performance even with a small training set.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Physics, Applied
Yisen Wang, Alexei Goun, Francois Laforge, Zachary Quine, Herschel Rabitz
Summary: By using nonlinear optical techniques to control bidirectional optogenetic switches, the selectivity of the photoactivation step can be enhanced beyond the effects of traditional linear excitation with monochromatic CW light. Simulating spectral features and employing stimulated depletion quenching as a nonlinear optical strategy can effectively improve the dynamic range of bidirectional switches.
APPLIED PHYSICS LETTERS
(2021)
Article
Physics, Multidisciplinary
Benjamin Russell, Re-Bing Wu, Herschel Rabitz
Summary: This study investigates the control landscapes of closed quantum systems beyond the dipole approximation by including a polarizability term in the Hamiltonian. Singular controls are analyzed as potential landscape traps, with a comparison to the dipole approximation results. The addition of a polarizability term removes traps from the control landscape and restores controllability in otherwise uncontrollable dipole coupled systems.
FRONTIERS IN PHYSICS
(2021)
Article
Automation & Control Systems
Daoyi Dong, Chuan-Cun Shu, Jiangchao Chen, Xi Xing, Hailan Ma, Yu Guo, Herschel Rabitz
Summary: This study investigates two classes of quantum control problems in the context of ultrafast laser control of quantum systems using frequency-domain optimization algorithms. In the first class, a known system model is utilized with a gradient-based optimization algorithm to find an optimal control field. In the second class, an experimental system with an unknown model is considered, and a mixed strategy differential evolution algorithm is used to search for optimal control fields.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Article
Public, Environmental & Occupational Health
Emanuele Borgonovo, Genyuan Li, John Barr, Elmar Plischke, Herschel Rabitz
Summary: This study explores various aspects of global sensitivity analysis when analysts have the option to use different plausible distributions for model inputs. The uniqueness of sensitivity measures is lost when exploring results under each distribution, and independence is sacrificed when aggregating distributions. Removing the unique distribution assumption impacts the mathematical properties of variance-based sensitivity analysis and affects result interpretation.
Article
Mathematics, Interdisciplinary Applications
John Barr, Herschel Rabitz
Summary: This paper describes a method for global sensitivity analysis based on embedding the joint probability distribution of multiple outputs into RKHS and measuring the distance between embeddings using maximum mean discrepancy. This method has the advantage of easy computability for high-dimensional outputs and determining the influence of input parameters on different features.
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
(2022)
Article
Biology
Caleb Deen Bastian, Hershel Rabitz
Summary: This study investigates the search for a replicase in low-dimensional RNA sequences using a mathematical model and stochastic simulation methods. The results show that the hitting and establishment of a high-fidelity replicator depend on polymerase fitness and sequence similarity landscapes, with hitting probability influenced by landscape curvature and hitting time by sequence dimension.
Article
Biochemistry & Molecular Biology
Fernando Bergasa-Caceres, Herschel A. Rabitz
Summary: This paper proposes the application of the folding interdiction target region (FITR) strategy for therapeutic drug design against Ebola virus and influenza A. It predicts target regions on relevant structural proteins of both viruses and discusses the challenges in designing effective therapeutic drugs using the predicted peptide candidates.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Review
Automation & Control Systems
Xiaozhen Ge, Re-Bing Wu, Herschel Rabitz
Summary: This review explores the landscapes of hybrid quantum-classical optimization algorithms prevalent in rapidly developing quantum technologies. It discusses how the objective function is computed by a quantum system while the optimizer is classical. The review shows that the landscape's geometry undergoes morphological changes from trap-free to rugged landscapes, eventually leading to barren-plateau landscapes where the optimizer can hardly move. This unified view is crucial for understanding different systems and finding ways to avoid traps or plateaus.
ANNUAL REVIEWS IN CONTROL
(2022)
Article
Biochemistry & Molecular Biology
Fernando Bergasa-Caceres, Herschel A. Rabitz
Summary: This article investigates the initial contact formation events along the folding pathway of the DNA-binding domain of p53 and the intermolecular events leading to its conversion into a prion-like form upon incubation with peptide P8(250-257). The calculations employ the sequential collapse model (SCM) to identify the segments involved in the initial contacts formation. Experimental evidence shows that the incubation of p53 with peptide P8(250-257) leads to an amyloid conformational transition. The findings suggest that disrupted initial contacts and enhanced folding through less stable contacts may contribute to core p53 amyloid misfolding.
Article
Chemistry, Physical
Herschel Rabitz, Benjamin Russell, Tak-San Ho
Summary: This Perspective explores the surprising ease of achieving optimal control of nonlinear phenomena in quantum and classical complex systems. It proposes a unified explanation based on the concept of control landscapes, where the same set of three underlying assumptions apply. Despite the high dimensionality of control variables, relatively short searches are typically required.
JOURNAL OF PHYSICAL CHEMISTRY A
(2023)
Article
Mechanics
Zachary Quine, Alexei Goun, Francois Laforge, Herschel Rabitz, Chung K. Law
Summary: We propose a simple optical method for generating chemical concentration maps of mixing fluids using a chemically sensitive dye. This method detects the dye through planar laser induced fluorescence. We demonstrate the application of this method by investigating the collision and mixing of two microdroplets composed of different fluids.
Article
Engineering, Industrial
John Barr, Herschel Rabitz
Summary: This paper presents a new kernel-based global sensitivity analysis (GSA) tool for single input-output data sets, with three key advances: (1) a new numerical estimator that shows empirical improvement over previous procedures; (2) a computational method for generating inner statistical functions from a single data set; (3) a theoretical extension defining conditional sensitivity indices for capturing shared information about the output when input-input correlations exist. Utilizing these indices, a decomposition of output uncertainty based on optimal learning sequence of input variables is derived, remaining consistent with input correlations. The new methodology is validated on benchmark systems, providing valuable insights.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2023)
Article
Chemistry, Physical
Alexei Goun, Esther Frederick, Ali O. Er, Steven L. Bernasek, Herschel Rabitz
Summary: In this study, successful laser control of a surface reaction was demonstrated by combining adaptive feedback control (AFC) technique with surface sensitive spectroscopy. The experiment determined the optimally shaped laser pulse for laser induced deprotonation of the hydroxyl group of phenol bound to a silicon dioxide substrate. The versatile combination of AFC with HD-VSFG provides a potential route to control a wide range of surface reactions.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Chemistry, Physical
Yisen Wang, Francois Laforge, Alexei Goun, Herschel Rabitz
Summary: Double resonance excitation combines vibrational and electronic molecular transitions, making it suitable for microscopy and effective for detecting chromophores at low concentrations. Although it has a low quantum yield, repeated excitations can build up biochemically relevant concentrations. Using non-resonant Raman pre-excitation is a viable option for double resonance excitation.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2022)
Article
Quantum Science & Technology
Alicia B. Magann, Gerard McCaul, Herschel A. Rabitz, Denys I. Bondar
Summary: The paper introduces an approach based on quantum tracking control to determine the relative concentrations of constituents in a quantum mixture. The method has important applications in chemistry, biology, and materials science, and shows strong performance in both gas phase and solid-state materials.