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SSRN 2022年

作者： Varga, Bálint Stippinger, Marcell Benkő, Zsigmond Fabó, Dániel Halász, Péter Erőss, Loránd Somogyvári, Zoltán Telcs, András Department of Computational Sciences Wigner Research Centre for Physics BudapestH-1121 Hungary János Szentágothai Doctoral School of Neurosciences Semmelweis University BudapestH-1085 Hungary Epilepsy Center Juhász Pál National Institute of Clinical Neurosciences BudapestH-1145 Hungary EPI-HELP BudapestH-1012 Hungary Department of Functional Neurosurgery National Institute of Clinical Neurosciences BudapestH-1145 Hungary Faculty of Information Technology and Bionics Péter Pázmány Catholic University BudapestH-1083 Hungary Neuromicrosystems ltd. BudapestH-1113 Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics BudapestH-1111 Hungary Department of Quantitative Methods University of Pannonia Faculty of Business and Economics VeszprémH-8200 Hungary

Non-interventional causal discovery is a challenging task. This is particularly true for causal relations of dynamic systems with chaotic attractors. The known solutions are data-intensive and cannot detect a hidden common driver (common cause or confounder). We propose a new method which eliminates both *** method is based on Takens' embedding theorem and complexity of the rank order patterns of the embedded series measured by the compressibility usingnon-sequential recursive pair substitution. The method works on shortsamples and is capable of detecting all kinds of causal connection (including hidden common cause). The newmethod is validated on synthetic data sets and applied to two types of humanelectrophysiological data from epileptic patients. In bothcases, the method revealed self-consistent, contradiction-free and biologically relevant causal connections between the investigatedareas. Thus the method may provide additional indication for the location ofintervention for the decision making medical panel. Given the method advantages and simplicity it might be applied in many other scientific and practical areas with success. © 2022, The Authors. All rights reserved.

关键词： Time series

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Mechanism of counteraction to the external threats of economic security of enterprises

Mechanism of counteraction to the external threats of econom...

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2019 International Conference on Creative Business for Smart and Sustainable Growth, CreBUS 2019

作者： Kniazevych, Anna Shenderivska, Lina Kraichuk, Serhii Ostapchuk, Natalia Kraichuk, Alexandr Department of Management Rivne State University of Humanities Rivne Ukraine Department of Publishing Management Printing and Bookselling National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Kyiv Ukraine Department of Economic Cybernetics Rivne State University of Humanities Rivne Ukraine Department of Information and Communication Technologies and Computer Science Teaching Methods Rivne State University of Humanities Rivne Ukraine Department of Mathematics with Teaching Methods Rivne State University of Humanities Rivne Ukraine

ISBN: (纸本)9781728134673

The article determines the influence of threats on economic security of enterprises. It offers the directions of counteraction to the threats to economic security of enterprises, which involve the expansion in international markets, diversification of production, development of innovation activity by strengthening of scientific and technical interaction, which will promote a more efficient use of enterprises' potential. The article presents the proposals on improving the process of making managerial decisions for boosting the effectiveness of counteraction to the threats. It proves the necessity of using the indicator of bankruptcy probability diagnosis in the system of assessing the state of economic security of enterprises for a more complete study of the threats to economic security. The article suggests the improved mechanism of counteraction to the threats to economic security, based on the concept that takes into account the use of the opportunities provided by external and internal environments, perspective directions of development, strengthening of integration links of functional systems of the enterprise with the aim of effective counteraction to the threats to economic security and ensuring economic growth of subject of management. The article substantiates the criteria of selection of suppliers of enterprises and defines the conceptual bases of a choice of perspective for markets of the enterprises. The study also determines the necessity of adherence to the principles of complexity, professionalism, and activity with the purpose of effective work of the mechanism of counteraction to the threats to economic security. © 2019 IEEE.

关键词： International trade

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Parthenon - a performance portable block-structured adaptive mesh refinement framework

arXiv

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arXiv 2022年

作者： Grete, Philipp Dolence, Joshua C. Miller, Jonah M. Brown, Joshua Ryan, Ben Gaspar, Andrew Glines, Forrest Swaminarayan, Sriram Lippuner, Jonas Solomon, Clell J. Shipman, Galen Junghans, Christoph Holladay, Daniel Stone, James M. Roberts, Luke F. Universität Hamburg Hamburger Sternwarte Gojenbergsweg 112 Hamburg21029 Germany Department of Physics and Astronomy Michigan State University East LansingMI48824 United States Computational Physics and Methods Los Alamos National Laboratory Los AlamosNM87545 United States Center for Theoretical Astrophysics Los Alamos National Laboratory Los AlamosNM87545 United States Applied Computer Science Los Alamos National Laboratory Los AlamosNM87545 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37830 United States Eulerian Codes Los Alamos National Laboratory Los AlamosNM87545 United States School of Natural Sciences Institute for Advanced Study PrincetonNJ08544 United States

On the path to exascale the landscape of computer device architectures and corresponding programming models has become much more diverse. While various low-level performance portable programming models are available, support at the application level lacks behind. To address this issue, we present the performance portable block-structured adaptive mesh refinement (AMR) framework PARTHENON, derived from the well-tested and widely used ATHENA++ astrophysical magnetohydrodynamics code, but generalized to serve as the foundation for a variety of downstream multi-physics codes. PARTHENON adopts the KOKKOS programming model, and provides various levels of abstractions from multi-dimensional variables, to packages defining and separating components, to launching of parallel compute kernels. PARTHENON allocates all data in device memory to reduce data movement, supports the logical packing of variables and mesh blocks to reduce kernel launch overhead, and employs one-sided, asynchronous MPI calls to reduce communication overhead in multi-node simulations. Using a hydrodynamics miniapp, we demonstrate weak and strong scaling on various architectures including AMD and NVIDIA GPUs, Intel and AMD x86 CPUs, IBM Power9 CPUs, as well as Fujitsu A64FX CPUs. At the largest scale on Frontier (the first TOP500 exascale machine), the miniapp reaches a total of 1.7 × 1013 zone-cycles/s on 9,216 nodes (73,728 logical GPUs) at ≈ 92% weak scaling parallel efficiency (starting from a single node). In combination with being an open, collaborative project, this makes PARTHENON an ideal framework to target exascale simulations in which the downstream developers can focus on their specific application rather than on the complexity of handling massively-parallel, device-accelerated AMR. Copyright © 2022, The Authors. All rights reserved.

关键词： Program processors

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Design of an Infological Model for Prediction of Problems during Drilling Using Machine Learning and Systems Analysis

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IOP Conference Series: Earth and Environmental science 2022年第4期988卷

作者： A L Zolkin V D Munister R V Faizullin N N Smoktal Ph.D. in Engineering Science Senior Lecturer of Computer and Information Sciences Department of the Povolzhskiy State University of Telecommunications and Informatics Department of Mathematical Methods and Computer-Aided Design Private educational institution 'Donetsk Academy of Transport' Department of Enterprise Economics State educational institution of higher professional education 'Donetsk National Technical University' Associate Professor of the Department of Information Technologies in Public Administration Institute of Management Technologies MIREA — Russian technological university Teacher at the Department of 'Renewable Energy Sources and Electrical Systems and Networks' Sevastopol State University

The article deals with the actual problem of identification of probabilistic processes as a result of the operation of drilling rigs in the oil industry. The world experience of finding ways to solve optimal forecasting tools using machine learning is summarized. Mnemonic rule for the implementation of classification and ranking systems in the detection of feedbacks as probable indicators of complications of ongoing technological processes is implemented through the description of the formal model of the drilling process in form of a hidden Markov model. The results of evaluation of the developed mathematical apparatus in the form of predictive analytics and a cut of basic complications in the drilling process are presented. An infological diagram of the developed architectural solution of the analysis project is proposed. The results of the control algorithms formalization are given in conclusion. These results allow to ensure the effective procees modes of equipment operation and make it possible to save electricity and water.

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Effective removal of auramine O and safranin O from aqueous solutions using nickel copper ferrite magnetic nanoparticles

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Journal of Molecular Structure 2025年 1344卷

作者： Irfan Ahmad Dilshad Alhedrawie Vicky Jain Abhinav Kumar M.M Rekha Mayank Kundlas S. Sunitha Subhashree Ray Shirin Shomurotova Department of Clinical Laboratory Sciences College of Applied Medical Sciences King Khalid University Abha Saudi Arabia Department of Computer Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Techniques Engineering College of Technical Engineering The Islamic University of Babylon Babylon Iraq Marwadi University Research Center Department of Chemistry Faculty of Science Marwadi University Rajkot 360003 Gujarat India Department of Nuclear and Renewable Energy Ural Federal University Named after the First President of Russia Boris Yeltsin Ekaterinburg 620002 Russia Department of Mechanical Engineering Karpagam Academy of Higher Education Coimbatore 641021 India Department of Chemistry and Biochemistry School of Sciences Jain (Deemed to be University) Bangalore Karnataka India Centre for Research Impact and Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Department of Chemistry Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Biochemistry IMS and SUM Hospital Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar Odisha 751003 India Department of Chemistry Teaching Methods Tashkent State Pedagogical University named after Nizami Bunyodkor street 27 Tashkent Uzbekistan

Water contamination by industrial dyes has become one of the major environmental challenges in recent decades. In this study, the adsorption of auramine O (Au-O) and safranin O (Sa-O) from aqueous solutions using nickel copper ferrite magnetic nanoparticles (NiCuFe 2 O 4 NPs) were investigated. These nanoparticles were synthesized via the sol-gel method and characterized using Fourier transform infrared spectroscopy (FTIR), vibrating sample magnetometry (VSM), X-ray diffraction (XRD), energy-dispersive X-ray spectroscopy (EDX), point of zero charge (pH pzc ), and scanning electron microscopy (SEM) techniques. Key operational parameters, including pH, ultrasonic duration, adsorbent dosage, and analyte concentration, were optimized using response surface methodology (RSM) based on the Box-Behnken design. A second-order polynomial model was selected for prediction and validated through analysis of variance (ANOVA). The optimal conditions for adsorption were determined to be pH of 7, NiCuFe 2 O 4 dosage of 0.021 g, analyte concentration of 32 mg L −1 , and an ultrasound duration of 11 min. Under these conditions, the maximum removal efficiency for Au-O and Sa-O was 98.24 % and 95.77 %, respectively. The reusability tests indicated that NiCuFe 2 O 4 NPs retained their adsorption performance over four consecutive cycles without significant efficiency loss. Moreover, the adsorbent demonstrated high efficiency in treating real water samples, with removal percentages ranging from 87.35 % to 98.06 %. Therefore, NiCuFe 2 O 4 NPs can be considered a promising, cost-effective, stable, and reusable adsorbent for the treatment of industrial effluents and contaminated water resources.

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Selected methodological and practical aspects of the multi-criteria method PVM

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Procedia computer science 2019年 159卷 2267-2278页

作者： Nermend Kesra Piwowarski Mateusz Wojciech Sałabun Department of Computational Methods in Experimental Economics Faculty of Economics and Management Institute of IT in Management University of Szczecin Mickiewicza 64 Szczecin 71-101 Poland Department of Artificial Intelligence Methods and Applied Mathematics Faculty of Computer Science and Information Technology West Pomeranian University of Technology in Szczecin ul. Żołnierska 49 71-210 Szczecin Poland

In multi-criteria decision support methods a significant participation of the decision maker is required. The obtained assessment is subjective, and the decision-making process is usually difficult to automate. Limiting interaction with the decision-maker, while maintaining the characteristics of multi-criteria analysis seems to be a desirable direction of methodological research. One of the solutions going in this direction is the original multi-criteria PVM method. The applicability of the method has been verified in the context of research on the assessment of EU countries in terms of ensuring healthy living conditions.

关键词： Multiple-Criteria Decision Analysis PVM Sustainable Development Goals

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Identification of Generalized Dynamic Factor Models from mixed-frequency data

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IFAC-PapersOnLine 2018年第15期51卷 1008-1013页

作者： Anderson, B.D.O. Braumann, Alexander Deistler, Manfred Hangzhou Dianzi University China Australian National University College of Engineering and Computer Science Data61-CSIRO Australia Australia Institut für Mathematische Stochastik TU Braunschweig Germany Vienna University of Technology Institute of Statistics and Mathematical Methods in Economics Austria

Modeling of high dimensional time series by linear time series models such as vector autoregressive models is often marred by the so-called “curse of dimensionality”. In order to overcome this problem generalized linear dynamic factor models (GDFM's) maybe used. In high-dimensional time series the single univariate time series are often sampled at different frequencies. This is the so-called mixed-frequency situation. We consider identifiability of the underlying high-frequency GDFM (i.e. the GDFM generating the data at the highest sampling frequency occurring) in the case of mixed frequency data and we shortly describe two estimation procedures in this situation based on the EM algorithm. © 2018

关键词： Frequency estimation

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DPA-2: a large atomic model as a multi-task learner

arXiv

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arXiv 2023年

作者： Zhang, Duo Liu, Xinzijian Zhang, Xiangyu Zhang, Chengqian Cai, Chun Bi, Hangrui Du, Yiming Qin, Xuejian Peng, Anyang Huang, Jiameng Li, Bowen Shan, Yifan Zeng, Jinzhe Zhang, Yuzhi Liu, Siyuan Li, Yifan Chang, Junhan Wang, Xinyan Zhou, Shuo Liu, Jianchuan Luo, Xiaoshan Wang, Zhenyu Jiang, Wanrun Wu, Jing Yang, Yudi Yang, Jiyuan Yang, Manyi Gong, Fu-Qiang Zhang, Linshuang Shi, Mengchao Dai, Fu-Zhi York, Darrin M. Liu, Shi Zhu, Tong Zhong, Zhicheng Lv, Jian Cheng, Jun Jia, Weile Chen, Mohan Ke, Guolin Weinan, E. Zhang, Linfeng Wang, Han AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing100871 China University of Chinese Academy of Sciences Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China CAS Key Laboratory of Magnetic Materials and Devices Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of Sciences Ningbo315201 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China Shanghai Engineering Research Center of Molecular Therapeutics & New Drug Development School of Chemistry and Molecular Engineering East China Normal University Shanghai200062 China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States Department of Chemistry Princeton University PrincetonNJ08540 United States College of Chemistry and Molecular Engineering Peking University Beijing100871 China Yuanpei College Peking University Beijing100871 China School of Electrical Engineering and Electronic Information Xihua University Chengdu610039 China State Key Laboratory of Superhard Materials College of Physics Jilin University Changchun130012 China Key Laboratory of Material Simulation Methods & Software of Ministry of Education College of Physics Jilin University Changchun130012 China International Center of Future Science Jilin University Changchun130012 China Key Laboratory for Quantum Materials of Zhejiang Province Department of Physics School of Science Westlake University Zhejiang Hangzhou310030 China Atomistic Simulations Italia

The rapid advancements in artificial intelligence (AI) are catalyzing transformative changes in atomic modeling, simulation, and design. AI-driven potential energy models have demonstrated the capability to conduct large-scale, long-duration simulations with the accuracy of ab initio electronic structure methods. However, the model generation process remains a bottleneck for large-scale applications. We propose a shift towards a model-centric ecosystem, wherein a large atomic model (LAM), pre-trained across multiple disciplines, can be efficiently fine-tuned and distilled for various downstream tasks, thereby establishing a new framework for molecular modeling. In this study, we introduce the DPA-2 architecture as a prototype for LAMs. Pre-trained on a diverse array of chemical and materials systems using a multi-task approach, DPA-2 demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning methodologies. Our approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research. Copyright © 2023, The Authors. All rights reserved.

关键词： Multi-task learning

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The Use of Large Language Models and Their Association With Enhanced Impact in Biomedical Research and Beyond

MedComm - Future Medicine

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MedComm - Future Medicine 2025年第2期4卷

作者： Cheng, Huzi Shi, Wen Sheng, Bin Lee, Aaron Y. Car, Josip Chaudhary, Varun Atanasov, Atanas G. Liu, Nan Qiu, Yue Chen, Qingyu Wong, Tien Yin Tham, Yih-Chung Zheng, Ying-Feng Department of Psychological and Brain Sciences Indiana University Bloomington IN United States Department of Ophthalmology the First Affiliated Hospital of Guangzhou Medical University Guangzhou China Department of Computer Science and Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China MOE Key Laboratory of AI School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Department of Ophthalmology University of Washington School of Medicine Seattle WA United States Centre for Population Health Sciences Lee Kong Chian School of Medicine Nanyang Technological University Singapore Singapore Department of Primary Care and Public Health School of Public Health Imperial College London London United Kingdom Department Health Research Methods Evidence and Impact McMaster University Hamilton ON Canada Department of Surgery McMaster University Hamilton ON Canada Ludwig Boltzmann Institute Digital Health and Patient Safety Medical University of Vienna Vienna Austria Institute of Genetics and Animal Biotechnology of the Polish Academy of Sciences Jastrzebiec Poland Centre for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Tsinghua Medicine Tsinghua University Beijing China Yale School of Medicine Yale University United States Singapore Eye Research Institute Singapore National Eye Centre Singapore School of Clinical Medicine Beijing Tsinghua Changgung Hospital Beijing China Ophthalmology and Visual Sciences Academic Clinical Program Duke-NUS Medical School Singapore Centre for Innovation and Precision Eye Health and Department of Ophthalmology Yong Loo Lin School of Medicine National University of Singapore Singapore State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China

The release of ChatGPT in 2022 has catalyzed the adoption of large language models (LLMs) across diverse writing domains, including academic writing. However, this technological shift has raised critical questions regarding the prevalence of LLM usage in academic writing and its potential influence on the quality and impact of research articles. Here, we address these questions by analyzing preprint articles from arXiv, bioRxiv, and medRxiv between 2022 and 2024, employing a novel LLM usage detection tool. Our study reveals that LLMs have been widely adopted in biomedical and other types of academic writing since late 2022. Notably, we noticed that LLM usage is linked to an enhanced impact of research articles after examining their correlation, as measured by citation numbers. Furthermore, we observe that LLMs influence specific content types in academic writing, including hypothesis formulation, conclusion summarization, description of phenomena, and suggestions for future work. Collectively, our findings underscore the potential benefits of LLMs in scientific communication, suggesting that they may not only streamline the writing process but also enhance the dissemination and impact of research findings across disciplines. © 2025 The Author(s). MedComm - Future Medicine published by John Wiley & Sons Australia, Ltd on behalf of Sichuan International Medical Exchange & Promotion Association (SCIMEA).

关键词： academic writing chatGPT large language models LLM

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Learning graphons via structured gromov-wasserstein barycenters

arXiv

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arXiv 2020年

作者： Xu, Hongteng Luo, Dixin Carin, Lawrence Zha, Hongyuan Gaoling School of Artificial Intelligence Renmin University of China 59 Zhongguancun St Haidian District Beijing100872 China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China School of Computer Science and Technology Beijing Institue of Technology 5 Zhongguancun St Haidian District100811 China Department of ECE Duke University DurhamNC27708 United States School of Data Science Shenzhen Research Institute of Big Data Chinese University of Hong Kong Hong Kong

We propose a novel and principled method to learn a nonparametric graph model called graphon, which is defined in an infinite-dimensional space and represents arbitrary-size graphs. Based on the weak regularity lemma from the theory of graphons, we leverage a step function to approximate a graphon. We show that the cut distance of graphons can be relaxed to the Gromov-Wasserstein distance of their step functions. Accordingly, given a set of graphs generated by an underlying graphon, we learn the corresponding step function as the Gromov-Wasserstein barycenter of the given graphs. Furthermore, we develop several enhancements and extensions of the basic algorithm, e.g., the smoothed Gromov-Wasserstein barycenter for guaranteeing the continuity of the learned graphons and the mixed Gromov-Wasserstein barycenters for learning multiple structured graphons. The proposed approach overcomes drawbacks of prior state-of-the-art methods, and outperforms them on both synthetic and real-world data. The code is available at https://***/HongtengXu/SGWB-Graphon. © 2020, CC BY.

关键词： Graph theory

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