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arXiv 2023年

作者： Biswas, Abhijit Xu, Rui Alvarez, Gustavo A. Zhang, Jin Christiansen-Salameh, Joyce Puthirath, Anand B. Burns, Kory Hachtel, Jordan A. Li, Tao Iyengar, Sathvik Ajay Gray, Tia Li, Chenxi Zhang, Xiang Kannan, Harikishan Elkins, Jacob Pieshkov, Tymofii S. Vajtai, Robert Birdwell, A. Glen Neupane, Mahesh R. Garratt, Elias J. Ivanov, Tony Pate, Bradford B. Zhao, Yuji Zhu, Hanyu Tian, Zhiting Rubio, Angel Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Max Planck Institute for the Structure and Dynamics of Matter Center for Free-Electron Laser Science Luruper Chaussee 149 22761 Germany Department of Materials Science & Engineering University of Virginia CharlottesvilleVA22904 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States DEVCOM Army Research Laboratory RF Devices and Circuits AdelphiMD20783 United States Chemistry Division Naval Research Laboratory WashingtonDC20375 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Flatiron Institute New YorkNY10010 United States

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, we suggest an alternative, simple and scalable approach where nanocrystalline two-dimensional (2D) film on three-dimensional (3D) substrates yield twisted-interface-dependent properties. Ultrawidebandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong nonlinear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. Our work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology. © 2023, CC BY.

关键词： Harmonic generation

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Parameterized complexity of fair vertex evaluation problems 44

Parameterized complexity of fair vertex evaluation problems

引用

44th International Symposium on Mathematical Foundations of computer science, MFCS 2019

作者： Knop, Dušan Masařík, Tomáš Toufar, Tomáš Algorithmics and Computational Complexity Faculty IV TU Berlin Department of Theoretical Computer Science Faculty of Information Technology Czech Technical University in Prague Prague Czech Republic Department of Applied Mathematics Charles University Prague Czech Republic Faculty of Mathematics Informatics and Mechanics University of Warsaw Poland Computer Science Institute Charles University Prague Czech Republic

ISBN: (纸本)9783959771177

A prototypical graph problem is centered around a graph-theoretic property for a set of vertices and a solution to it is a set of vertices for which the desired property holds. The task is to decide whether, in the given graph, there exists a solution of a certain quality, where we use size as a quality measure. In this work, we are changing the measure to the fair measure (cf. Lin and Sahni [27]). The fair measure of a set of vertices S is (at most) k if the number of neighbors in the set S of any vertex (in the input graph) does not exceed k. One possible way to study graph problems is by defining the property in a certain logic. For a given objective, an evaluation problem is to find a set (of vertices) that simultaneously minimizes the assumed measure and satisfies an appropriate formula. More formally, we study the MSO Fair Vertex Evaluation, where the graph-theoretic property is described by an MSO formula. In the presented paper we show that there is an FPT algorithm for the MSO Fair Vertex Evaluation problem for formulas with one free variable parameterized by the twin cover number of the input graph and the size of the formula. One may define an extended variant of MSO Fair Vertex Evaluation for formulas with free variables;here we measure a maximum number of neighbors in each of the sets. However, such variant is W[1]-hard for parameter even on graphs with twin cover one. Furthermore, we study the Fair Vertex Cover (Fair VC) problem. Fair VC is among the simplest problems with respect to the demanded property (i.e., the rest forms an edgeless graph). On the negative side, Fair VC is W[1]-hard when parameterized by both treedepth and feedback vertex set of the input graph. On the positive side, we provide an FPT algorithm for the parameter modular width. © Dušan Knop,Tomáš Masařík, and Tomáš Toufar.

关键词： Parameter estimation

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CAUSAL MACHINE LEARNING FOR HIGH-DIMENSIONAL MEDIATION ANALYSIS USING INTERVENTIONAL EFFECTS MAPPED TO A TARGET TRIAL

arXiv

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arXiv 2025年

作者： Chen, Tong Vansteelandt, Stijn Burgner, David Mansell, Toby Moreno-Betancur, Margarita Clinical Epidemiology and Biostatistics Unit Murdoch Children’s Research Institute Melbourne Dental School University of Melbourne Australia Department of Applied Mathematics Computer Science and Statistics Ghent University Belgium Inflammatory Origins Murdoch Children’s Research Institute Department of Paediatrics University of Melbourne Australia Clinical Epidemiology and Biostatistics Unit Murdoch Children’s Research Institute Department of Paediatrics University of Melbourne Australia

Causal mediation analysis examines causal pathways linking exposures to disease. The estimation of interventional effects, which are mediation estimands that overcome certain identifiability problems of natural effects, has been advanced through causal machine learning methods, particularly for high-dimensional mediators. Recently, it has been proposed interventional effects can be defined in each study by mapping to a target trial assessing specific hypothetical mediator interventions. This provides an appealing framework to directly address real-world research questions about the extent to which such interventions might mitigate an increased disease risk in the exposed. However, existing estimators for interventional effects mapped to a target trial rely on singly-robust parametric approaches, limiting their applicability in high-dimensional settings. Building upon recent developments in causal machine learning for interventional effects, we address this gap by developing causal machine learning estimators for three interventional effect estimands, defined by target trials assessing hypothetical interventions inducing distinct shifts in joint mediator distributions. These estimands are motivated by a case study within the Longitudinal Study of Australian Children, used for illustration, which assessed how intervening on high inflammatory burden and other noninflammatory adverse metabolomic markers might mitigate the adverse causal effect of overweight or obesity on high blood pressure in adolescence. We develop one-step and (partial) targeted minimum loss-based estimators based on efficient influence functions of those estimands, demonstrating they are root-n consistent, efficient, and multiply robust under certain conditions. Copyright © 2025, The Authors. All rights reserved.

关键词： Learning algorithms

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Bridging the gap: Machine learning to resolve improperly modeled dynamics

arXiv

引用

arXiv 2020年

作者： Qraitem, Maan Kularatne, Dhanushka Forgoston, Eric Hsieh, M. Ani Department of Computer Science Colby College WatervilleME04901 United States Mechanical Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States Department of Applied Mathematics and Statistics Montclair State University MontclairNJ07043 United States

We present a data-driven modeling strategy to overcome improperly modeled dynamics for systems exhibiting complex spatio-temporal behaviors. We propose a Deep Learning framework to resolve the differences between the true dynamics of the system and the dynamics given by a model of the system that is either inaccurately or inadequately described. Our machine learning strategy leverages data generated from the improper system model and observational data from the actual system to create a neural network to model the dynamics of the actual system. We evaluate the proposed framework using numerical solutions obtained from three increasingly complex dynamical systems. Our results show that our system is capable of learning a data-driven model that provides accurate estimates of the system states both in previously unobserved regions as well as for future states. Our results show the power of state-of-the-art machine learning frameworks in estimating an accurate prior of the system’s true dynamics that can be used for prediction up to a finite horizon. Copyright © 2020, The Authors. All rights reserved.

关键词： Dynamics

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Superior Neural Network for Distinguishing Between Atomic Species

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Microscopy and Microanalysis 2021年第S1期27卷 466-468页

作者： Matthew Helmi Leth Larsen William Bang Lomholdt Anders Siig Dreisig Stig Helveg Ole Winther Thomas Hansen Jakob Schiøtz Technical University of Denmark United States Center for Visualizing Catalytic Processes (VISION) Department of Physics Technical University of Denmark DK-2800 Kgs. Lyngby Denmark. Kongens Lyngby Hovedstaden Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby Hovedstaden Denmark DTU Nanolab Technical University of Denmark Kgs. Lyngby Hovedstaden Denmark Department of Physics Technical University of Denmark Kongens Lyngby Hovedstaden Denmark

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An enhanced Walrus Optimizer with opposition-based learning and mutation strategy for data clustering

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Array 2025年 26卷

作者： Abualigah, Laith Alomari, Saleh Ali Almomani, Mohammad H. Zitar, Raed Abu Migdady, Hazem Saleem, Kashif Smerat, Aseel Snasel, Vaclav Ezugwu, Absalom E. Computer Science Department Al al-Bayt University Mafraq25113 Jordan Faculty of Science and Information Technology Jadara University Irbid21110 Jordan Department of Mathematics Facility of Science The Hashemite University P.O box 330127 Zarqa13133 Jordan Faculty of Engineering and Computing Liwa College Abu Dhabi United Arab Emirates CSMIS Department Oman College of Management and Technology Barka320 Oman Department of Computer Science & Engineering College of Applied Studies & Community Service King Saud University Riyadh11362 Saudi Arabia Faculty of Educational Sciences Al-Ahliyya Amman University Amman19328 Jordan Computer Technologies Engineering Mazaya University College Nasiriyah Iraq Faculty of Electrical Engineering and Computer Science VŠB-Technical University of Ostrava Poruba-Ostrava 70800 Czech Republic Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom2520 South Africa

Data clustering plays a crucial role in various domains, such as image processing, pattern recognition, and data mining. Traditional clustering techniques often suffer from limitations like sensitivity to initialization, poor convergence, and entrapment in local optima. To address these challenges, this paper proposes an Enhanced Walrus Optimizer (IWO) tailored for clustering tasks. The proposed IWO integrates two powerful strategies–Opposition-Based Learning (OBL) and Mutation Search Strategy (MSS)–to improve population diversity and prevent premature convergence, thereby enhancing both exploration and exploitation capabilities. These enhancements enable more accurate and stable identification of cluster centers. The effectiveness of IWO is validated through extensive experiments on multiple benchmark clustering datasets and compared against several state-of-the-art metaheuristic algorithms, including PSO, GWO, AOA, and others. The results demonstrate that IWO achieves better results, indicating improved compactness and separation of clusters. Statistical validation using p-values and ranking scores further confirms the superiority of the proposed method. These findings suggest that IWO offers a robust and flexible framework for solving complex clustering problems. Future work will explore hybrid deep learning-integrated models and parallel implementations to enhance scalability. © 2025

关键词： Swarm intelligence

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Redundant Queueing System with Hysteresis Backup Server Connection Strategy 1

引用

18th International Conference on Information Technologies and Mathematical Modelling, ITMM 2019

作者： Klimenok, Valentina Dudin, Alexander Vishnevsky, Vladimir Department of Applied Mathematics and Computer Science Belarusian State University Minsk220030 Belarus Institute of Control Sciences of Russian Academy of Sciences and Closed Corporation "Information and Networking Technologies" Moscow Russia

ISBN: (数字)9783030333881

ISBN: (纸本)9783030333874

We consider an unreliable queueing system which can be used for modeling a broadband hybrid communication channel consisting FSO (Free Space Optics) channel and radio wave channel. The radio channel is backup and is connected when the optical channel is not available. In order to save energy, a hysteresis strategy for connecting a backup channel is used. This strategy is given by two thresholds: and If the main channel fails, the backup channel connects to information transmission if the number i of customers in the system is such that If during backup channel operation the number of customers in the system becomes such that then the backup channel is disabled and the current customer continues to be serviced at the main server. If at some point in time the number i of customers in the system becomes such that then the system works in the mode in which it worked until that time. We describe the system operation by two-dimensional Markov chain, calculate the steady state distribution and the main performance characteristics of the system. We introduce the cost function and present the example of numerical optimisation consisting in choosing the threshold values minimizing the cost function. © 2019, Springer Nature Switzerland AG.

关键词： Cost functions

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Derivation of Gauge Symmetries in Supergravity with a Cosmological Constant in 2 + 1 Dimensions

arXiv

引用

arXiv 2020年

作者： McKeon, D.G.C. Department of Applied Mathematics University of Western Ontario LondonONN6A 5B7 Canada Department of Mathematics and Computer Science Algoma University Sault Ste. MarieONP6A 2G4 Canada

The canonical structure of supergravity with a cosmological constant is analyzed in 2 + 1 dimensions using the Dirac constraint formalism. Using the approach of Henneaux, Teitelboim and Zanelli, the first class constraints are used to find the local gauge symmetries of this model. Provided the cosmological constant is negative, this novel gauge algebra closes, without having to invoke the equations of motion or introducing auxiliary fields. There are two Bosonic and one Fermionic gauge symmetries. Copyright © 2020, The Authors. All rights reserved.

关键词： Gravity waves

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On the classification of quaternary optimal Hermitian LCD codes

arXiv

引用

arXiv 2020年

作者： Araya, Makoto Harada, Masaaki Department of Computer Science Shizuoka University Hamamatsu432-8011 Japan Research Center for Pure and Applied Mathematics Graduate School of Information Sciences Tohoku University Sendai980-8579 Japan

We propose a method for a classification of quaternary Hermitian LCD codes having large minimum weights. As an example, we give a classification of quaternary optimal Hermitian LCD codes of dimension 3. Copyright ...

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Web-based rule-based expert system to screen postpartum depression

引用

IOP Conference Series: Materials science and Engineering 2021年第1期1108卷

作者： D Mufidati M N Widyawati S Suryono Postgraduate Program in Applied Midwifery Science Poltekkes Kemenkes Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

The high prevalence of postpartum depression significantly increases maternal morbidity. Lack of diagnosis for postpartum depression results in mothers missing early treatment necessary. The traditional screening method using questionnaire presents its own disadvantage in diagnosis. Therefore, development of postpartum screening method that focuses on ease in implementation is very much needed to improve postpartum maternal health. This paper proposes a screening information system for postpartum depression to help its proper treatment. This research employed the rule-based method to diagnose postpartum depression and the expert system to input symptoms data that will result in diagnoses. Respondents input symptoms data to be diagnosed by the system. The system then automatically generate output of suggested treatment based on expert input associated with the diagnoses the system is working on. This research employed the Randomized Control Trial method with Control Group Pre and Post Tests Design. Samples of this research were 52 postpartum mothers consisting of 26 respondents in the system group, and the other 26 in the manual group. Results show that 42.31% (n=11) of mothers suffer from postpartum depression. There is a significant difference in EPDS score prior to and after the use of the information system (P=0.000). The system also successfully generated very high TAM score, meaning that it is capable of postpartum screening along with ease of use and some other advantages. Therefore, screening for postpartum depression using information system is very effective and ensures proper and timely treatment.

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