检索结果-内蒙古大学图书馆

arXiv 2021年

作者： He, Lang Niu, Mingyue Tiwari, Prayag Marttinen, Pekka Su, Rui Jiang, Jiewei Guo, Chenguang Wang, Hongyu Ding, Songtao Wang, Zhongmin Pan, Xiaoying Dang, Wei School of Computer Science and Technology Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi'an University of Posts and Telecommunications Shaanxi Xi'an710121 China Beijing100190 China Beijing100049 China Department of Computer Science Aalto University Espoo Finland School of Foreign Languages Northwest University Shaanxi Xi'an China School of Electronic Engineering Xi'an University of Posts and Telecommunications Xi'an China School of Electronics and Information Northwestern Polytechnical University Shaanxi Xi'an China Shaanxi Mental Health Center Shaanxi Xi'an710061 China

With the acceleration of the pace of work and life, people have to face more and more pressure, which increases the possibility of suffering from depression. However, many patients may fail to get a timely diagnosis due to the serious imbalance in the doctor-patient ratio in the world. Promisingly, physiological and psychological studies have indicated some differences in speech and facial expression between patients with depression and healthy individuals. Consequently, to improve current medical care, many scholars have used deep learning to extract a representation of depression cues in audio and video for automatic depression detection. To sort out and summarize these works, this review introduces the databases and describes objective markers for automatic depression estimation (ADE). Furthermore, we review the deep learning methods for automatic depression detection to extract the representation of depression from audio and video. Finally, this paper discusses challenges and promising directions related to automatic diagnosing of depression using deep learning technologies. © 2021, CC BY.

关键词： Diagnosis

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Novel Color Orthogonal Moments-Based Image Representation and Recognition

Research Square

引用

Research Square 2020年

作者： He, Bing Liu, Jun Yang, Tengfei Xiao, Bin Peng, Yanguo School of Physics and Electrical Engineering Weinan Normal University Weinan714000 China Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an University of Posts & Telecommunications Xi’an710121 China School of Computer Science and Technology Weinan Normal University Weinan714000 China School of Cyberspace Security Xi’an University of Posts & Telecommunications Xi’an710121 China Chongqing Key Laboratory of Computational Intelligence Chongqing University of Posts and Telecommunications Chongqing400065 China School of Computer Science and Technology Xidian University Xi’an710071 China

Inspired by quaternion algebra and the idea of fractional-order transformation, we propose a new set of quaternion fractional-order generalized Laguerre orthogonal moments (QFr-GLMs) based on fractional-order generalized Laguerre polynomials. Firstly, the proposed QFr-GLMs are directly constructed in Cartesian coordinate space, avoiding the need for conversion between Cartesian and polar coordinates;therefore, they are better image descriptors than circularly orthogonal moments constructed in polar coordinates. Moreover, unlike the latest Zernike moments based on quaternion and fractional-order transformations, which extract only the global features from color images, our proposed QFr-GLMs can extract both the global and local color features. This paper also derives a new set of invariant color-image descriptors by QFr-GLMs, enabling geometric-invariant pattern recognition in color images. Finally, the performances of our proposed QFr-GLMs and moment invariants were evaluated in simulation experiments of correlated color images. Both theoretical analysis and experimental results demonstrate the value of the proposed QFr-GLMs and their geometric invariants in the representation and recognition of color images. © 2020, CC BY.

关键词： Image reconstruction

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Transfer learning identifies bacterial signatures for cross-regional diagnosis of type 2 diabetes and enable stage-sensitive dietary fiber intervention

iMetaOmics

引用

iMetaOmics 2025年第2期2卷

作者： Qunye Zhang Nan Wang Fanghua Zhang Bin Chen Yihui Wang Zhongchao Wang Changying Zhao Chuandi Jin Dashuang Sheng Kaile Yue Daifeng Jiang Liaomei Gao Haohong Zhang Zixin Kang Mingyue Cheng Xiaoli Ma Haiyan Wang Dongming Hu Jun Wang Yuantao Liu Chenhong Zhou Minxiu Yao Guoping Zhao Yangang Wang Zhe Wang Kang Ning Lei Zhang Microbiome-X School of Public Health Department of Cardiology Qilu Hospital Cheeloo College of Medicine Shandong University Jinan China Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-Imaging Center of AI Biology Department of Bioinformatics and Systems Biology College of Life Science and Technology Huazhong University of Science and Technology Wuhan China Department of Endocrinology Qingdao Central Hospital University of Health and Rehabilitation Sciences (Qingdao Central Hospital) Qingdao China Qingdao University Medical Group: Department of Endocrinology and Metabolism The Affiliated Hospital of Qingdao University Department of Endocrinology and Metabolism The Third People's Hospital of Qingdao Qingdao China Shandong Academy of Sciences Science and Technology Services Platform (Shandong Academy of Sciences Foreign Students Pioneer Park) Jinan China Shandong Provincial Maternal and Child Health Care Hospital Affiliated to Qingdao University Jinan China Department of Endocrinology Qingdao Municipal Hospital (Group) Qingdao China Department of Endocrinology The Eighth People's Hospital of Qingdao Qingdao China Department of Endocrinology Qilu Hospital of Shandong University (Qingdao) Qingdao China State Key Laboratory of Microbial Technology Shandong University Qingdao China CAS Key Laboratory of Computational Biology Bio-Med Big Data Center Shanghai Institute of Nutrition and Health University of Chinese Academy of Sciences Chinese Academy of Sciences Shanghai China Department of Endocrinology & Geriatrics Shandong Provincial Hospital Affiliated to Shandong First Medical University Jinan China

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The C_(6)D_(6)detector system on the Back-n beam line of CSNS

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Radiation Detection technology and Methods 2019年第3期3卷 274-282页

作者： Jie Ren Xichao Ruan Jie Bao Guangyuan Luan Wei Jiang Qi An Huaiyong Bai Ping Cao Qiping Chen Yonghao Chen Pinjing Cheng Zengqi Cui Ruirui Fan Changqing Feng Minhao Gu Fengqin Guo Changcai Han Zijie Han Guozhu He Yongcheng He Yuefeng He Hanxiong Huang Weiling Huang Xiru Huang Xiaolu Ji Xuyang Ji Haoyu Jiang Hantao Jing Ling Kang Mingtao Kang Bo Li Lun Li Qiang Li Xiao Li Yang Li Yang Li Rong Liu Shubin Liu Xingyan Liu Yinglin Ma Changjun Ning Binbin Qi Zhaohui Song Hong Sun Xiaoyang Sun Zhijia Sun Zhixin Tan Hongqing Tang Jingyu Tang Pengcheng Wang Qi Wang Taofeng Wang Yanfeng Wang Zhaohui Wang Zheng Wang Jie Wen Zhongwei Wen Qingbiao Wu Xiaoguang Wu Xuan Wu Likun Xie Yiwei Yang Han Yi Li Yu Tao Yu Yongji Yu Guohui Zhang Jing Zhang Linhao Zhang Liying Zhang Qingmin Zhang Qiwei Zhang Xianpeng Zhang Yuliang Zhang Zhiyong Zhang Yingtan Zhao Liang Zhou Zuying Zhou Danyang Zhu Kejun Zhu Peng Zhu Key Laboratory of Nuclear Data China Institute of Atomic EnergyBeijing 102413China Institute of High Energy Physics Chinese Academy of Sciences(CAS)Beijing 100049China Dongguan Neutron Science Center Dongguan 523803China State Key Laboratory of Particle Detection and Electronics HefeiChina Department of Modern Physics University of Science and Technology of ChinaHefei 230026China State Key Laboratory of Nuclear Physics and Technology School of PhysicsPeking UniversityBeijing 100871China Institute of Nuclear Physics and Chemistry China Academy of Engineering PhysicsMianyang 621900China University of South China Hengyang 421001China Northwest Institute of Nuclear Technology Xi’an 710024China Department of Engineering and Applied Physics University of Science and Technology of ChinaHefei 230026China Xi’an Jiaotong University Xi’an 710049China Beihang University Beijing 100083China

Introduction The neutron capture cross sections are very important in the field of nuclear device design and basic physics ***-free liquid scintillator such as C_(6)D_(6)detectors are widely used in the neutron capture cross-sectional measurements for the low neutron sensitivity and fast time *** Back-n white neutron source at China Spallation Neutron Source is the first spallation white neutron source in China,and it is suitable for neutron capture cross-sectional *** and methods A C_(6)D_(6)detector system was built in the Back-n experimental *** pulse height weighting technique was used to determine the system’s detection *** response to gamma rays of the C_(6)D_(6)detector was measured,and the energy resolution function was *** Carlo simulation with Geant4 code was carried out to get the weighting function of this C_(6)D_(6)detector ***,the systematic uncertainty of the weighting function was also *** According to the experimental and simulation results,this C_(6)D_(6)detector system can be used to measure neutron capture cross section.

关键词： C6D6 detector PHWT Neutron capture cross section White neutron source

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Deploying Cationic Cellulose Nanofiber Confinement to Enable High Iodine Loadings Towards High Energy and High-Temperature Zn-I2Battery

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Angewandte Chemie 2023年第5期136卷

作者： Zhenglin Li Wenwen Cao Tao Hu Yichan Hu Rong Zhang Huilin Cui Funian Mo Chaozheng Liu Chunyi Zhi Guojin Liang Institute of Technology for Carbon Neutrality Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen 518055 China Co-Innovation Center of Efficient Processing and Utilization of Forest Resources College of Materials Science and Engineering Nanjing Forestry University Nanjing 210000 China Contribution: Data curation (lead) Investigation (lead) Methodology (lead) Writing - original draft (lead) School of Chemistry and Chemical Engineering University of Jinan Jinan 250022 China Contribution: Conceptualization (equal) Data curation (lead) Investigation (lead) Methodology (lead) School of Materials Science and Engineering Key Laboratory of Structure and Functional Regulation of Hybrid Materials Ministry of Education Anhui University Hefei 230601 China Contribution: Data curation (equal) Formal analysis (equal) Investigation (supporting) Methodology (supporting) Contribution: Conceptualization (equal) Data curation (supporting) Formal analysis (equal) Investigation (equal) Department of Materials Science and Engineering City University of Hong Kong 83 Tat Chee Avenue Kowloon Hong Kong 999077 Hong Kong Contribution: Data curation (equal) Investigation (equal) Methodology (equal) Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (equal) Investigation (equal) Shenzhen Key Laboratory of Flexible Printed Electronics Technology Center Harbin Institute of Technology Shenzhen Guangdong 518055 China Contribution: Conceptualization (lead) Data curation (lead) Resources (lead) Supervision (equal) Contribution: Conceptualization (equal) Data curation (lead) Investigation (lead) Supervision (equal) Contribution: Supervision (lead) Visualization (lead) Writing - review & editing (lead) Contribution: Conceptualization (lead) Supervision (lead) Writing - original draft (lead) Writing - review & editing (lead)

High iodine loading and high-temperature adaptability of the iodine cathode are prerequisites to achieving high energy density at full battery level and promoting the practical application for the zinc-iodine (Zn-I 2 ) battery. However, it would aggravate the polyiodide shuttle effect when employing high iodine loading and working temperature. Here, a sustainable cationic cellulose nanofiber (cCNF) was employed to confine the active iodine species through strong physiochemical adsorption to enlarge the iodine loading and stabilize it even at high temperatures. The cCNF could accommodate dual-functionality by enlarging the iodine loading and suppressing the polyiodide shuttle effect, owing to the unique framework structure with abundant surface positive charges. As a result, the iodine cathode based on the cCNF could deliver high iodine mass loading of 14.1 mg cm −2 with a specific capacity of 182.7 mAh g −1 , high areal capacity of 2.6 mAh cm −2 , and stable cycling over 3000 cycles at 2 A g −1 , thus enabling a high energy density of 34.8 Wh kg −1 and the maximum power density of 521.2 W kg −1 at a full Zn-I 2 battery level. In addition, even at a high temperature of 60 °C, the Zn-I 2 battery could still deliver a stable cycling.

关键词： Cationic Cellulose High- Temperature Battery Iodine Shuttle-Free Zn-I2 Battery

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Galaxy-galaxy lensing in the VOICE deep survey

arXiv

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arXiv 2022年

作者： Luo, Ruibiao Fu, Liping Luo, Wentao Napolitano, Nicola R. Xie, Linghua Radovich, Mario Liu, Jing Li, Rui Amaro, Valeria Chen, Zhu Liu, Dezi Fan, Zuhui Covone, Giovanni Vaccari, Mattia School of Physics and Astronomy Sun Yat-sen University Zhuhai Campus 2 Daxue Road Tangjia Zhuhai Guangdong519082 China Shanghai Key Lab for Astrophysics Shanghai Normal University Shanghai200234 China CAS Key Laboratory for Research in Galaxies and Cosmology University of Science and Technology of China Anhui Hefei230026 China Department of Astronomy School of Physical Sciences University of Science and Technology of China Anhui Hefei230026 China INAF - Osservatorio Astronomico di Padova via dell'Osservatorio 5 PadovaI-35122 Italy South-Western Institute for Astronomy Research Yunnan University Yunnan Kunming650500 China Dipartimento di Fisica E. Pancini Universita degli Studi Federio II NapoliI-80126 Italy INFN Sezione di Napoli NapoliI-80126 Italy INAF - Osservatorio Astronomico di Capodimonte Salita Moiariello 16 NapoliI-80131 Italy Inter-university Institute for Data Intensive Astronomy Department of Astronomy University of Cape Town Rondebosch Cape Town7701 South Africa Inter-university Institute for Data Intensive Astronomy Department of Physics and Astronomy University of the Western Cape Bellville Cape Town7535 South Africa INAF - Istituto di Radioastronomia via Globetti 101 Bologna40129 Italy

The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg2of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of magABis up to 26.1 (5σ limiting) in r-band. We estimate the Excess Surface Density (ESD;ΔΣ) based on galaxy-galaxy measurements around galaxies at lower redshift (0.10l∗=108.31Mo) deviates from the SHMR relation whereas all other three samples agrees well with empirical curves. We interpret this discrepancy as the effect of a low star formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area. Copyright © 2022, The Authors. All rights reserved.

关键词： Surveys

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Artificial unintelligence: Anti-intelligence of intelligent algorithms 3rd

Artificial unintelligence: Anti-intelligence of intelligent ...

引用

3rd International Conference on Intelligence science, ICIS 2018

作者： Zhang, Yuhong Nauman, Umer Information Science and Engineering College Henan University of Technology Zhengzhou450001 China Network and Data Security Key Laboratory of Sichuan University of Electronic Science and Technology Chengdu610054 China

ISBN: (纸本)9783030013127

In the age of big data, artificial intelligence (AI) algorithms play an important role in demonstrating the value of data, but its negative effects are increasingly prominent. Researchers focus more on the obvious issues like privacy protection these days, and we assume that technologies like AI will make people wiser. But due to the not-so-obvious limits of AI, it may push us to the opposite side–artificial unintelligence. In this paper, a detailed analysis of the process of value creation from data is presented first. Then, based on the above process, the role played by AI algorithms is analyzed. Next, the anti-intelligence features of AI algorithms, such as the tendency of ‘fatuous King’, the generalization of quick thinking, a faster transformation of master/slave at the individual level, and retribalization at the group level, are deeply discussed. Finally, some possilbe ways of circumventing the aforementioned problems are offered. © IFIP International Federation for Information Processing 2018.

关键词： Big data

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Negligible Ion Migration in Tin-Based and Tin-Doped Perovskites

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Angewandte Chemie 2022年第5期135卷

作者： Kester O. Ighodalo Wenjing Chen Zheng Liang Dr. Yongliang Shi Shenglong Chu Yihan Zhang Rashid Khan Hongmin Zhou Xu Pan Jiajiu Ye Prof. Zhengguo Xiao CAS Key Laboratory of Strongly-coupled Quantum Matter Physics Department of Physics University of Science and Technology of China Hefei Anhui 230026 China Contribution: Data curation (lead) Formal analysis (lead) Methodology (lead) Writing - original draft (lead) Writing - review & editing (equal) Contribution: Data curation (supporting) Formal analysis (equal) Methodology (supporting) Writing - review & editing (equal) Key Laboratory of Photovoltaic and Energy Conservation Materials Institute of Solid-State Physics Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei 230031 China Contribution: Data curation (equal) Methodology (equal) Center for Spintronics and Quantum Systems State Key Laboratory for Mechanical Behavior of Materials School of Materials Science and Engineering Xi'an Jiaotong University Xi'an Shaanxi 710049 China Contribution: Data curation (lead) Contribution: Data curation (supporting) Contribution: Writing - review & editing (supporting) Instruments Center for Physical Science University of Science and Technology of China Hefei Anhui 230026 China Contribution: Supervision (supporting) Contribution: Funding acquisition (lead) Investigation (lead) Project administration (lead) Supervision (lead) Writing - review & editing (equal)

Ion migration is a notorious phenomenon observed in ionic perovskite materials. It causes several severe issues in perovskite optoelectronic devices such as instability, current hysteresis, and phase segregation. Here, we report that, in contrast to lead halide perovskites (LHPs), no ion migration or phase segregation was observed in tin halide perovskites (THPs) under illumination or an electric field. The origin is attributed to a much stronger Sn-halide bond and higher ion migration activation energy ( E a ) in THPs, which remain nearly constant under illumination. We further figured out the threshold E a for the absence of ion migration to be around 0.65 eV using the CsSn y Pb 1-y (I 0.6 Br 0.4 ) 3 system whose E a varies with Sn ratios. Our work shows that ion migration does not necessarily exist in all perovskites and suggests metallic doping to be a promising way of stopping ion migration and improving the intrinsic stability of perovskites.

关键词： Ion Migration Light-Emitting Diodes Perovskites Solar Cells Stability

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Toward Complete Transformation of Sodium Polysulfides by Regulating the Second-Shell Coordinating Environment of Atomically Dispersed Fe

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Angewandte Chemie 2023年第26期135卷

作者： Ruilin Bai Qiaosong Lin Xinyu Li Fangxin Ling Huijuan Wang Sha Tan Lingxiang Hu Mingze Ma Prof. Xiaojun Wu Yu Shao Xianhong Rui Prof. Enyuan Hu Dr. Yu Yao Prof. Yan Yu Hefei National Research Center for Physical Sciences at the Microscale Department of Materials Science and Engineering CAS Key Laboratory of Materials for Energy Conversion University of Science and Technology of China Hefei Anhui 230026 China Contribution: Conceptualization (lead) Writing - original draft (lead) State Key Laboratory of Molecular Reaction Dynamics Dalian Institute of Chemical Physics Chinese Academy of Sciences Dalian 116023 Liaoning China University of Chinese Academy of Sciences Beijing 100049 China Contribution: Data curation (lead) Contribution: Formal analysis (equal) Contribution: Investigation (lead) Experimental Center of Engineering and Material Science University of Science and Technology of China Hefei 230026 China Contribution: Methodology (equal) Chemistry Division Brookhaven National Laboratory Upton NY USA Contribution: Resources (equal) Department of Electrical Engineering and Computer Science Institut Polytechnique de Paris 91120 Palaiseau Île-de-France France Contribution: Software (equal) Contribution: Data curation (equal) Jiujiang DeFu Technology Co. Ltd. Jiujiang Jiangxi 332000 (P. R. China School of Materials and Energy Guangdong University of Technology Guangzhou 510006 China Contribution: Validation (lead) Contribution: Methodology (lead) Contribution: Writing - review & editing (lead) National Synchrotron Radiation Laboratory Hefei Anhui 230026 China Contribution: Project administration (lead) Writing - review & editing (lead)

Room temperature sodium-sulfur (RT Na-S) batteries are highly competitive as potential energy storage devices. Nevertheless, their actually achieved reversible capacities are far below the theoretical value due to incomplete transformation of polysulfides. Herein, atomically dispersed Fe-N/S active center by regulating the second-shell coordinating environment of Fe single atom is proposed. The Fe−N 4 S 2 coordination structure with enhanced local electronic concentration around the Fermi level is revealed via synchrotron radiation X-ray absorption spectroscopy (XAS) and theoretical calculations, which can not only significantly promote the transformation kinetics of polysulfides, but induce uniform Na deposition for dendrite-free Na anode. As a result, the obtained S cathode delivers a high initial reversible capacity of 1590 mAh g −1 , nearly the theoretical value. This work opens up a new avenue to facilitate the complete transformation of polysulfides for RT Na-S batteries.

关键词： Catalysis Coordinating Environment Fe Single Atom RT Na-S Batteries Transformation Kinetics

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Introducing the DREAMS Project: DaRk mattEr and Astrophysics with Machine learning and Simulations

arXiv

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arXiv 2024年

作者： Rose, Jonah C. Torrey, Paul Villaescusa-Navarro, Francisco Lisanti, Mariangela Nguyen, Tri Roy, Sandip Kollmann, Kassidy E. Vogelsberger, Mark Cyr-Racine, Francis-Yan Medvedev, Mikhail V. Genel, Shy Anglés-Alcázar, Daniel Kallivayalil, Nitya Wang, Bonny Y. Costanza, Belén O'Neil, Stephanie Roche, Cian Karmakar, Soumyodipta Garcia, Alex M. Low, Ryan Lin, Shurui Mostow, Olivia Cruz, Akaxia Caputo, Andrea Farahi, Arya Muñoz, Julian B. Necib, Lina Teyssier, Romain Dalcanton, Julianne J. Spergel, David Department of Astronomy University of Florida GainesvilleFL32611 United States Center for Computational Astrophysics Flatiron Institute 162 5th Avenue New YorkNY10010 United States Department of Astronomy University of Virginia CharlottesvilleVA22904 United States Department of Astrophysical Sciences Princeton University Peyton Hall PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Department of Physics Kavli Institute for Astrophysics and Space Research Massachusetts Institute of Technology CambridgeMA02139 United States The NSF AI Institute for Artificial Intelligence and Fundamental Interactions CambridgeMA02139 United States Department of Physics and Astronomy University of New Mexico 210 Yale Blvd NE AlbuquerqueNM87106 United States Institute for Advanced Study School for Natural Sciences PrincetonNJ08540 United States Institute for Theory and Computation Harvard University CambridgeMA02138 United States Department of Physics and Astronomy University of Kansas LawrenceKS66045 United States Laboratory for Nuclear Science Massachusetts Institute of Technology CambridgeMA02139 United States Columbia Astrophysics Laboratory Columbia University 550 West 120th Street New YorkNY10027 United States Department of Physics University of Connecticut 196 Auditorium Road U-3046 StorrsCT06269-3046 United States McWilliams Center for Cosmology and Astrophysics Carnegie Mellon University PittsburghPA15213 United States Facultad de Ciencias Astronómicas y Geofísicas Universidad Nacional de La Plata Observatorio Astronómico Paseo del Bosque La PlataB1900FWA Argentina Department of Astronomy School of Physical Sciences University of Science and Technology of China Anhui Hefei230026 China CAS Key Laboratory for Researches in Galaxies and Cosmology School of Astronomy and Space Science University of Science and Technology of China Anhui Hefei230026 China Theoretical Physics Depa

We introduce the DREAMS project, an innovative approach to understanding the astrophysical implications of alternative dark matter models and their effects on galaxy formation and evolution. The DREAMS project will ultimately comprise thousands of cosmological hydrodynamic simulations that simultaneously vary over dark matter physics, astrophysics, and cosmology in modeling a range of systems-from galaxy clusters to ultra-faint satellites. Such extensive simulation suites can provide adequate training sets for machine-learning-based analyses. This paper introduces two new cosmological hydrodynamical suites of Warm Dark Matter, each comprised of 1024 simulations generated using the arepo code. One suite consists of uniform-box simulations covering a (25 ℎ−1 M☉)3 volume, while the other consists of Milky Way zoom-ins with sufficient resolution to capture the properties of classical satellites. For each simulation, the Warm Dark Matter particle mass is varied along with the initial density field and several parameters controlling the strength of baryonic feedback within the IllustrisTNG model. We provide two examples, separately utilizing emulators and Convolutional Neural networks, to demonstrate how such simulation suites can be used to disentangle the effects of dark matter and baryonic physics on galactic properties. The DREAMS project can be extended further to include different dark matter models, galaxy formation physics, and astrophysical targets. In this way, it will provide an unparalleled opportunity to characterize uncertainties on predictions for small-scale observables, leading to robust predictions for testing the particle physics nature of dark matter on these scales. © 2024, CC BY.

关键词： Galaxies

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