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3,218 results on '"Wang Xingyu"'

1. Robot path planning method based on improved ant colony algorithm

Author

Wang Xingyu, Hu Yanhai, Xu Jianlei, and Chen Haihui

Subjects
improved ant colony algorithm, robot, grid method, a* algorithm, Electronics, TK7800-8360
Abstract

An improved ant colony algorithm is provided according to the disadvantage of slow convergence and easy to fall into local optimal solution of traditional ant colony algorithm in robot route planning. The raster method is used to build the path matrix, and a corner heuristic function is established to increase the probability of selecting a specified path and improve the search speed of the algorithm. Combining A* algorithm with improved ant colony algorithm, an improved distance heuristic is proposed to avoid falling into local optimal solution. A pheromone volatile factor which can be changed according to the number of iterations was proposed to enhance the global search ability. Based on the related data analysis, the improved ant colony algorithm is better than Ant Colony Algorithm with Multiple Inspired Factor(ACAM )algorithm in resolving problems such as slow convergence rate and preventing entering local optimal solution.

Published
2023
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2. Response of carbon budget to climate change of the alpine meadow in Gannan using the CENTURY model

Author

Teddy Nkrumah, Zhang Meiling, Nazieh Stephen, and Wang Xingyu

Subjects
alpine meadow, century model, climate change, mann–kendall analysis, net ecosystem productivity, Environmental technology. Sanitary engineering, TD1-1066, Environmental sciences, GE1-350
Abstract

Alpine meadows have become particularly vulnerable to climate change. Variations in precipitation and temperature affect the ecological production of a region. The matrices for ecosystem change include net primary production (NPP), net photosynthesis (PsnNet), and net ecosystem production (NEP), of which NEP is the most important. Using the CENTURY model for alpine meadows, we investigated the response of NEP to climate change from 1969 to 2018 in Gannan, Gansu Province, China. The distribution pattern of NEP in Gannan was simulated with the model. The Mann–Kendall trend test was used to analyze the interannual variation of NEP for the individual counties and the entire study area over a 50-year period. The results showed the annual NEP distribution pattern varied widely in the region, with the highest NEP values in the southeastern part while the northwestern part showed the lowest. The highest NEP was measured in summer with sufficient precipitation and higher temperatures, whereas the lowest values occurred in winter. The total carbon sequestered in the Gannan alpine meadow over the last 50 years was 43580.9 gC, with the average annual NEP of the alpine meadow being approximately 813.62 gC m−2 year−1. Due to the combined effects of precipitation and temperature variations, NEP exhibits significant seasonal and interannual variations. The simulated NEP values of the seven counties fluctuated over the last 50 years, with each county showing an upward trend and the simulated NEP in the entire Gannan area also showing a clear upward trend that mutated around the year 1990. Both precipitation and temperature were found to be significantly and positively correlated with NEP. Precipitation was a significant driving factor, while temperature interacted with precipitation on the carbon budget. The carbon budget in the alpine meadow was stabilized by increasing precipitation and temperature. Estimates from NEP were in satisfactory correlation with measurements (r2=0.74, n=25 at p

Published
2022
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3. Practice and experience of shift rotation in the general ward, CCU and catheterization unit of cardiology (心内科普通病房、CCU、导管室轮转实施及体会)

Author

ZHOU Xiaoyan (周晓艳), SHEN Juan (沈娟), WANG Zhaojia (王兆嘉), SUN Tingting (孙婷婷), ZHANG Yue (张悦), WANG Xingyu (王星予), CUI Liu (崔柳), and TANG Shuo (唐硕)

Subjects
cardiovascular disease, nursing management, cardiac care unit, catheter, human resource, 心血管疾病, 护理管理, 心血管重症监护病房, 导管, 人力资源, Nursing, RT1-120
Abstract

This paper summarized the practice and experience of shift rotation in the general ward, CCU and catheterization unit of cardiology. The practice of shift rotation included rotation background of rotation, setting up of a team of clinical teachers, establishing the teaching program, training before shift rotation and related assessment. Nurses were trained in professional skills, and implementation of shift rotation had relieved pressure on nursing human resources. (本文主要对心内科普通病房、CCU和导管室3个护理单元实施轮转的相关经验进行总结, 主要包括轮转的背景、带教老师的确定、教学内容的制定、轮转前的培训以及相关考核等, 通过实施轮转, 护士的业务能力明显提高, 缓解了科室人力资源紧张的情况。)

Published
2021
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4. Logic-of-Thought: Injecting Logic into Contexts for Full Reasoning in Large Language Models

Author

Liu, Tongxuan, Xu, Wenjiang, Huang, Weizhe, Wang, Xingyu, Wang, Jiaxing, Yang, Hailong, and Li, Jing

Subjects
Computer Science - Computation and Language
Abstract

Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks but their performance in complex logical reasoning tasks remains unsatisfactory. Although some prompting methods, such as Chain-of-Thought, can improve the reasoning ability of LLMs to some extent, they suffer from an unfaithful issue where derived conclusions may not align with the generated reasoning chain. To address this issue, some studies employ the approach of propositional logic to further enhance logical reasoning abilities of LLMs. However, the potential omissions in the extraction of logical expressions in these methods can cause information loss in the logical reasoning process, thereby generating incorrect results. To this end, we propose Logic-of-Thought (LoT) prompting which employs propositional logic to generate expanded logical information from input context, and utilizes the generated logical information as an additional augmentation to the input prompts, thereby enhancing the capability of logical reasoning. The LoT is orthogonal to existing prompting methods and can be seamlessly integrated with them. Extensive experiments demonstrate that LoT boosts the performance of various prompting methods with a striking margin across five logical reasoning tasks. In particular, the LoT enhances Chain-of-Thought's performance on the ReClor dataset by +4.35%; moreover, it improves Chain-of-Thought with Self-Consistency's performance on LogiQA by +5%; additionally, it boosts performance of Tree-of-Thoughts on ProofWriter dataset by +8%., Comment: 20 pages

Published
2024

5. GroupDebate: Enhancing the Efficiency of Multi-Agent Debate Using Group Discussion

Author

Liu, Tongxuan, Wang, Xingyu, Huang, Weizhe, Xu, Wenjiang, Zeng, Yuting, Jiang, Lei, Yang, Hailong, and Li, Jing

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse NLP tasks. Extensive research has explored how to enhance the logical reasoning abilities such as Chain-of-Thought, Chain-of-Thought with Self-Consistency, Tree-Of-Thoughts, and multi-agent debates. In the context of multi-agent debates, significant performance improvements can be achieved with an increasing number of agents and debate rounds. However, the escalation in the number of agents and debate rounds can drastically raise the tokens cost of debates, thereby limiting the scalability of the multi-agent debate technique. To better harness the advantages of multi-agent debates in logical reasoning tasks, this paper proposes a method to significantly reduce token cost in multi-agent debates. This approach involves dividing all agents into multiple debate groups, with agents engaging in debates within their respective groups and sharing interim debate results between groups. Comparative experiments across multiple datasets have demonstrated that this method can reduce the total tokens by up to 51.7% during debates and while potentially enhancing accuracy by as much as 25%. Our method significantly enhances the performance and efficiency of interactions in the multi-agent debate., Comment: 18 pages

Published
2024

6. VersiCode: Towards Version-controllable Code Generation

Author

Wu, Tongtong, Wu, Weigang, Wang, Xingyu, Xu, Kang, Ma, Suyu, Jiang, Bo, Yang, Ping, Xing, Zhenchang, Li, Yuan-Fang, and Haffari, Gholamreza

Subjects
Computer Science - Software Engineering, Computer Science - Computation and Language
Abstract

Large Language Models (LLMs) have made tremendous strides in code generation, but existing research fails to account for the dynamic nature of software development, marked by frequent library updates. This gap significantly limits LLMs' deployment in realistic settings. In this paper, we propose two novel tasks aimed at bridging this gap: version-specific code completion (VSCC) and version-aware code migration (VACM). In conjunction, we introduce VersiCode, a comprehensive Python dataset specifically designed to evaluate LLMs on these two tasks, together with a novel evaluation metric, Critical Diff Check (CDC@1), which assesses code generation against evolving API requirements. We conduct an extensive evaluation on VersiCode, which reveals that version-controllable code generation is indeed a significant challenge, even for GPT-4o and other strong frontier models. We believe the novel tasks, dataset, and metric open up a new, important research direction that will further enhance LLMs' real-world applicability. The code and resources can be found at https://github.com/wutong8023/VersiCode.

Published
2024

7. Insights into Deep Learning Refactoring: Bridging the Gap Between Practices and Expectations

Author

Wang, SiQi, Hu, Xing, Wang, Bei, Yao, WenXin, Xia, Xin, and Wang, XingYu

Subjects
Computer Science - Software Engineering
Abstract

With the rapid development of deep learning, the implementation of intricate algorithms and substantial data processing have become standard elements of deep learning projects. As a result, the code has become progressively complex as the software evolves, which is difficult to maintain and understand. Existing studies have investigated the impact of refactoring on software quality within traditional software. However, the insight of code refactoring in the context of deep learning is still unclear. This study endeavors to fill this knowledge gap by empirically examining the current state of code refactoring in deep learning realm, and practitioners' views on refactoring. We first manually analyzed the commit history of five popular and well-maintained deep learning projects (e.g., PyTorch). We mined 4,921 refactoring practices in historical commits and measured how different types and elements of refactoring operations are distributed and found that refactoring operation types' distribution in deep learning projects is different from it in traditional Java software. We then surveyed 159 practitioners about their views of code refactoring in deep learning projects and their expectations of current refactoring tools. The result of the survey showed that refactoring research and the development of related tools in the field of deep learning are crucial for improving project maintainability and code quality, and that current refactoring tools do not adequately meet the needs of practitioners. Lastly, we provided our perspective on the future advancement of refactoring tools and offered suggestions for developers' development practices., Comment: 24 pages, 18 figures

Published
2024

10. Performance assessment of a liquid desiccant system for formaldehyde removal based on a novel criterion

Author

Hu Jiachun, Wen Lixia, Wang Xingyu, and Fu Huangxi

Subjects
liquid desiccant, formaldehyde removal, desiccant condition, dehumidification, Environmental sciences, GE1-350
Abstract

In the era of requirements in indoor air quality, liquid desiccant (LD) dehumidification is regarded as an energy-saving method removing indoor air contaminants during the dehumidification process, which has made considerable progress in recent years. Many previous studies have confirmed that the heat and mass transfer characteristics associated with absorption characteristics and thermophysical properties in LDs play a vital role in contaminants removal performance. The main purpose of this research is to numerically assess the indoor formaldehyde removal performance of a LD dehumidification system with different LDs. In order to make a fair assessment, a novel criterion based on the same temperature and the same vapor pressure which is the same desiccant condition is proposed. A numerical model integrated with heat, moisture, and formaldehyde transfer is used to predict the system performance. This model can rationally simulate the formaldehyde removal performance of the LD dehumidification system by inputting various operating parameters, including indoor air status parameters and outdoor air status parameters. The simulation results show that the number of mass transfer units of formaldehyde (NTUmf) plays a key role in the formaldehyde removal performance. The formaldehyde removal performances decrease with the increase of temperature and humidity ratio of return air, while they increase with the increase of temperature and humidity ratio of fresh air. With the aforementioned results, the study is expected to be beneficial to further improve the removal ability and potential of LD systems for indoor formaldehyde.

Published
2022
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11. ModuleGuard:Understanding and Detecting Module Conflicts in Python Ecosystem

Author

Zhu, Ruofan, Wang, Xingyu, Liu, Chengwei, Xu, Zhengzi, Shen, Wenbo, Chang, Rui, and Liu, Yang

Subjects
Computer Science - Software Engineering, D.2, K.6.3
Abstract

Python has become one of the most popular programming languages for software development due to its simplicity, readability, and versatility. As the Python ecosystem grows, developers face increasing challenges in avoiding module conflicts, which occur when different packages have the same namespace modules. Unfortunately, existing work has neither investigated the module conflict comprehensively nor provided tools to detect the conflict. Therefore, this paper systematically investigates the module conflict problem and its impact on the Python ecosystem. We propose a novel technique called InstSimulator, which leverages semantics and installation simulation to achieve accurate and efficient module extraction. Based on this, we implement a tool called ModuleGuard to detect module conflicts for the Python ecosystem. For the study, we first collect 97 MC issues, classify the characteristics and causes of these MC issues, summarize three different conflict patterns, and analyze their potential threats. Then, we conducted a large-scale analysis of the whole PyPI ecosystem (4.2 million packages) and GitHub popular projects (3,711 projects) to detect each MC pattern and analyze their potential impact. We discovered that module conflicts still impact numerous TPLs and GitHub projects. This is primarily due to developers' lack of understanding of the modules within their direct dependencies, not to mention the modules of the transitive dependencies. Our work reveals Python's shortcomings in handling naming conflicts and provides a tool and guidelines for developers to detect conflicts., Comment: The paper was accepted by ICSE24

Published
2024
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14. Gemini: A Family of Highly Capable Multimodal Models

Author

Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Published
2023

15. Electronic Phase Propagation Speed in BaFe$_2$As$_2$ Revealed by Dilatometry

Author

Qin, Xin, Wang, Xingyu, Hong, Wenshan, Geng, Mengqiao, Li, Yuan, Luo, Huiqian, Li, Shiliang, and Liu, Yang

Subjects
Condensed Matter - Superconductivity, Condensed Matter - Materials Science, Condensed Matter - Strongly Correlated Electrons
Abstract

Thermal expansion offers deep insights into phase transitions in condensed matter physics. Utilizing an advanced AC-temperature dilatometer with picometer resolution, this study clearly resolves the antiferromagnetic and structural transition in BaFe$_2$As$_2$. The implementation of temperature oscillation reveals a hysteresis near the transition temperature $T_\mathrm{N}$ with unprecedented resolution. Unexpectedly, we find that the hysteretic width exhibits a universal dependence on the parameters of temperature oscillation and the sample's longidutinal dimension, which in turn reveals a finite transition speed. Our quantitative analysis shows that this phase boundary propagates at a mere 188 $\mu$m/s - a speed seven orders of magnitude slower than acoustic waves. It suggests a hidden thermodynamic constraint imposed by the electronic degrees of freedom. Our research not only sheds light on the dynamics of phase transitions between different correlated phases, but also establishes high precision dilatometry as a powerful tool for material studies. This measurement technique, when properly modified, can be extended to studies of other material properties such as piezoelectric, magneto-restriction, elastic modulus, etc.

Published
2023

23. Strongly Efficient Rare-Event Simulation for Regularly Varying L\'evy Processes with Infinite Activities

Author

Wang, Xingyu and Rhee, Chang-Han

Subjects
Mathematics - Probability
Abstract

In this paper, we address rare-event simulation for heavy-tailed L\'evy processes with infinite activities. The presence of infinite activities poses a critical challenge, making it impractical to simulate or store the precise sample path of the L\'evy process. We present a rare-event simulation algorithm that incorporates an importance sampling strategy based on heavy-tailed large deviations, the stick-breaking approximation for the extrema of L\'evy processes, the Asmussen-Rosi\'nski approximation, and the randomized debiasing technique. By establishing a novel characterization for the Lipschitz continuity of the law of L\'evy processes, we show that the proposed algorithm is unbiased and strongly efficient under mild conditions, and hence applicable to a broad class of L\'evy processes. In numerical experiments, our algorithm demonstrates significant improvements in efficiency compared to the crude Monte-Carlo approach., Comment: 53 pages, 1 figure

Published
2023

24. Computational prediction of ideal strength for a material

Author

Wang, Zixun, Wang, Xingyu, Song, Xianqi, Zhang, Xinxin, Liu, Hanyu, and Zhang, Miao

Subjects
Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

The ideal strength is crucial for predicting material behavior under extreme conditions, which can provide insights into material limits, guide design and engineer for enhanced performance and durability. In this work, we present a method within an allows for the estimation of tensile, shear, and indentation strengths in any crystallographic direction or plane. We have examined the strain-stress relationships of several well-known structures and compared our findings with previous work, demonstrating the effectiveness of our approach. Moreover, we performed extensive investigations into the indentation strength of hexagonal WC, \b{eta}-SiC, and MgA$l_2O_4$. The current study uncovers the modes of structural deformation and the underlying atomistic mechanisms. The insights gained from this study have significant implications for the further exploration and design of superhard materials., Comment: 15 pages,7 figures

Published
2023

25. Large Deviations and Metastability Analysis for Heavy-Tailed Dynamical Systems

Author

Wang, Xingyu and Rhee, Chang-Han

Subjects
Mathematics - Probability
Abstract

This paper introduces novel frameworks for large deviations and metastability analysis in heavy-tailed stochastic dynamical systems. We develop and apply these frameworks within the context of stochastic difference equation $X^\eta_{j+1}(x) = X^\eta_{j}(x) + \eta a\big( X^\eta_{j}(x)\big) + \eta \sigma\big( X^\eta_{j}(x)\big)Z_{j+1}$ and its variation with truncated dynamics $X^{\eta|b}_{j+1}(x) = X^{\eta|b}_{j}( x) + \varphi_b\big(\eta a\big( X^{\eta|b}_{j}( x)\big) + \eta \sigma\big( X^{\eta|b}_{j}( x)\big) Z_{j+1}\big)$, where $\varphi_b(x) = (x/\|x\|)\max\{\|x\|, b\}$. The truncation operator $\varphi_b(\cdot)$ is often introduced as a modulation mechanism in heavy-tailed systems, such as stochastic gradient descent algorithms in deep learning. Thus, it is crucial to successfully analyze both $X^{\eta}_{j}(x)$ and $X^{\eta|b}_{j}(x)$. We establish locally uniform sample-path large deviations for both processes and translate these asymptotics into precise characterizations of the joint distributions of the first exit times and exit locations. Our large deviations asymptotics are sharp enough to rigorously characterize \emph{the catastrophe principle} by establishing the distributional limit of the sample paths conditional on the rare events of interest, thereby revealing the most likely paths through which rare events arise in heavy-tailed dynamical systems. Moreover the resulting limit theorem unveils a discrete hierarchy of phase transitions (i.e., exit times) as the truncation threshold $b$ varies. Together, these developments serve as a heavy-tailed counterpart of the classical Freidlin-Wentzell theory. We also present the corresponding results for continuous-time processes in the appendix.

Published
2023

28. Availability and affordability of blood pressure-lowering medicines and the effect on blood pressure control in high-income, middle-income, and low-income countries: an analysis of the PURE study data

Author

Marjan W Attaei, MA, Rasha Khatib, PhD, Prof Martin McKee, DSc, Prof Scott Lear, PhD, Prof Gilles Dagenais, MD, Ehimario U Igumbor, PhD, Khalid F AlHabib, MD, Prof Manmeet Kaur, PhD, Lanthe Kruger, PhD, Prof Koon Teo, PhD, Fernando Lanas, MD, Khalid Yusoff, MD, Aytekin Oguz, MD, Prof Rajeev Gupta, PhD, Afzalhussein M Yusufali, MD, Ahmad Bahonar, MD, Prof Raman Kutty, MD, Prof Annika Rosengren, MD, Prof Viswanathan Mohan, DSc, Prof Alvaro Avezum, PhD, Prof Rita Yusuf, PhD, Prof Andrzej Szuba, PhD, Sumathy Rangarajan, MSc, Clara Chow, PhD, Prof Salim Yusuf, DPhil, S Yusuf, S Rangarajan, K K Teo, C K Chow, M O'Donnell, A Mente, D Leong, A Smyth, P Joseph, S Islam, M Zhang, W Hu, C Ramasundarahettige, G Wong, L Dayal, A Casanova, M Dehghan, G Lewis, A Aliberti, A Reyes, A Zaki, B Lewis, B Zhang, D Agapay, D Hari, E Milazzo, E Ramezani, F Hussain, F Shifaly, I Kay, J Rimac, J Swallow, L Heldman, M(a) Mushtaha, M(o) Mushtaha, M Trottier, N Aoucheva, N Kandy, P Mackie, R Solano, S Chin, S Ramacham, S Shahrook, S Trottier, T Tongana, W ElSheikh, J Lindeman, M McQueen, K Hall, J Keys, X Wang, J Keneth, A Devanath, R Diaz, A Orlandini, B Linetsky, S Toscanelli, G Casaccia, JM Maini Cuneo, O Rahman, R Yusuf, AK Azad, KA Rabbani, HM Cherry, A Mannan, I Hassan, AT Talukdar, RB Tooheen, MU Khan, M Sintaha, T Choudhury, R Haque, S Parvin, A Avezum, GB Oliveira, CS Marcilio, AC Mattos, K Teo, J Dejesus, W Elsheikh, G Dagenais, P Poirier, G Turbide, D Auger, A LeBlanc De Bluts, MC Proulx, M Cayer, N Bonneville, S Lear, D Gasevic, E Corber, V de Jong, I Vukmirovich, A Wielgosz, G Fodor, A Pipe, A Shane, F Lanas, P Seron, S Martinez, A Valdebenito, M Oliveros, Li Wei, Liu Lisheng, Chen Chunming, Wang Xingyu, Zhao Wenhua, Zhang Hongye, JiaXuan, Hu Bo, Sun Yi, Bo Jian, Zhao Xiuwen, Chang Xiaohong, Chen Tao, Chen Hui, Deng Qing, Cheng Xiaoru, He Xinye, Li Jian, Li Juan, Liu Xu, Ren Bing, Wang Wei, Wang Yang, Yang Jun, Zhai Yi, Zhu Manlu, Lu Fanghong, Wu Jianfang, Li Yindong, Hou Yan, Zhang Liangqing, Guo Baoxia, Liao Xiaoyang, Zhang Shiying, BianRongwen, TianXiuzhen, Li Dong, Chen Di, Wu Jianguo, Xiao Yize, Liu Tianlu, Zhang Peng, Dong Changlin, Li Ning, Ma Xiaolan, Yang Yuqing, Lei Rensheng, Fu Minfan, He Jing, Liu Yu, Xing Xiaojie, Zhou Qiang, P Lopez-Jaramillo, PA Camacho Lopez, R Garcia, LJA Jurado, D Gómez-Arbeláez, JF Arguello, R Dueñas, S Silva, LP Pradilla, F Ramirez, DI Molina, C Cure-Cure, M Perez, E Hernandez, E Arcos, S Fernandez, C Narvaez, J Paez, A Sotomayor, H Garcia, G Sanchez, T David, A Rico, P Mony, M Vaz, A V Bharathi, S Swaminathan, K Shankar, AV Kurpad, KG Jayachitra, N Kumar, HAL Hospital, V Mohan, M Deepa, K Parthiban, M Anitha, S Hemavathy, T Rahulashankiruthiyayan, D Anitha, K Sridevi, R Gupta, RB Panwar, I Mohan, P Rastogi, S Rastogi, R Bhargava, R Kumar, J S Thakur, B Patro, PVM Lakshmi, R Mahajan, P Chaudary, V Raman Kutty, K Vijayakumar, K Ajayan, G Rajasree, AR Renjini, A Deepu, B Sandhya, S Asha, HS Soumya, R Kelishadi, A Bahonar, N Mohammadifard, H Heidari, K Yusoff, TST Ismail, KK Ng, A Devi, NM Nasir, MM Yasin, M Miskan, EA Rahman, MKM Arsad, F Ariffin, SA Razak, FA Majid, NA Bakar, MY Yacob, N Zainon, R Salleh, MKA Ramli, NA Halim, SR Norlizan, NM Ghazali, MN Arshad, R Razali, S Ali, HR Othman, CWJCW Hafar, A Pit, N Danuri, F Basir, SNA Zahari, H Abdullah, MA Arippin, NA Zakaria, I Noorhassim, MJ Hasni, MT Azmi, MI Zaleha, KY Hazdi, AR Rizam, W Sazman, A Azman, R Khatib, U Khammash, A Khatib, R Giacaman, R Iqbal, A Afridi, R Khawaja, A Raza, K Kazmi, A Dans, HU Co, JT Sanchez, L Pudol, C Zamora-Pudol, LAM Palileo-Villanueva, MR Aquino, C Abaquin, SL Pudol, ML Cabral, W Zatonski, A Szuba, K Zatonska, R Ilow#, M Ferus, B Regulska-Ilow, D Różańska, M Wolyniec, KF AlHabib, A Hersi, T Kashour, H Alfaleh, M Alshamiri, HB Altaradi, O Alnobani, A Bafart, N Alkamel, M Ali, M Abdulrahman, R Nouri, A Kruger, H H Voster, A E Schutte, E Wentzel-Viljoen, FC Eloff, H de Ridder, H Moss, J Potgieter, AA Roux, M Watson, G de Wet, A Olckers, JC Jerling, M Pieters, T Hoekstra, T Puoane, E Igumbor, L Tsolekile, D Sanders, P Naidoo, N Steyn, N Peer, B Mayosi, B Rayner, V Lambert, N Levitt, T Kolbe-Alexander, L Ntyintyane, G Hughes, R Swart, J Fourie, M Muzigaba, S Xapa, N Gobile, K Ndayi, B Jwili, K Ndibaza, B Egbujie, A Rosengren, K Bengtsson Boström, U Lindblad, P Langkilde, A Gustavsson, M Andreasson, M Snällman, L Wirdemann, K Pettersson, E Moberg, K Yeates, J Sleeth, K Kilonzo, A Oguz, AAK Akalin, KBT Calik, N Imeryuz, A Temizhan, E Alphan, E Gunes, H Sur, K Karsidag, S Gulec, Y Altuntas, AM Yusufali, W Almahmeed, H Swidan, EA Darwish, ARA Hashemi, N Al-Khaja, JM Muscat-Baron, SH Ahmed, TM Mamdouh, WM Darwish, MHS Abdelmotagali, SA Omer Awed, GA Movahedi, H Al Shaibani, RIM Gharabou, DF Youssef, AZS Nawati, ZAR Abu Salah, RFE Abdalla, SM Al Shuwaihi, MA Al Omairi, OD Cadigal, R.S. Alejandrino, J Chifamba, L Gwaunza, G Terera, C Mahachi, P Murambiwa, T Machiweni, and R Mapanga

Subjects
Public aspects of medicine, RA1-1270
Abstract

Background: Hypertension is considered the most important risk factor for cardiovascular diseases, but its control is poor worldwide. We aimed to assess the availability and affordability of blood pressure-lowering medicines, and the association with use of these medicines and blood pressure control in countries at varying levels of economic development. Methods: We analysed the availability, costs, and affordability of blood pressure-lowering medicines with data recorded from 626 communities in 20 countries participating in the Prospective Urban Rural Epidemiological (PURE) study. Medicines were considered available if they were present in the local pharmacy when surveyed, and affordable if their combined cost was less than 20% of the households' capacity to pay. We related information about availability and affordability to use of these medicines and blood pressure control with multilevel mixed-effects logistic regression models, and compared results for high-income, upper-middle-income, lower-middle-income, and low-income countries. Data for India are presented separately because it has a large generic pharmaceutical industry and a higher availability of medicines than other countries at the same economic level. Findings: The availability of two or more classes of blood pressure-lowering drugs was lower in low-income and middle-income countries (except for India) than in high-income countries. The proportion of communities with four drug classes available was 94% in high-income countries (108 of 115 communities), 76% in India (68 of 90), 71% in upper-middle-income countries (90 of 126), 47% in lower-middle-income countries (107 of 227), and 13% in low-income countries (nine of 68). The proportion of households unable to afford two blood pressure-lowering medicines was 31% in low-income countries (1069 of 3479 households), 9% in middle-income countries (5602 of 65 471), and less than 1% in high-income countries (44 of 10 880). Participants with known hypertension in communities that had all four drug classes available were more likely to use at least one blood pressure-lowering medicine (adjusted odds ratio [OR] 2·23, 95% CI 1·59–3·12); p

Published
2017
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31. Effects of background music on objective and subjective performance measures in an auditory BCI

Author

Sijie Zhou, Brendan Z Allison, Andrea Kübler, Andrzej Cichocki, Wang Xingyu, and Jing Jin

Subjects
auditory, Brain Computer Interface, Event-related potentials, Music background, Audio stimulus, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Several studies have explored brain computer interface (BCI) systems based on auditory stimuli, which could help patients with visual impairments. Usability and user satisfaction are important considerations in any BCI. Although background music can influence emotion and performance in other task environments, and many users may wish to listen to music while using a BCI, auditory and other BCIs are typically studied without background music. Some work has explored the possibility of using polyphonic music in auditory BCI systems. However, this approach requires users with good musical skills, and has not been explored in online experiments. Our hypothesis was that an auditory BCI with background music would be preferred by subjects over a similar BCI without background music, without any difference in BCI performance. We introduce a simple paradigm (which does not require musical skill) using percussion instrument sound stimuli and background music, and evaluated it in both offline and online experiments. The result showed that subjects preferred the auditory BCI with background music. Different performance measures did not reveal any significant performance effect when comparing background music vs. no background. Since the addition of background music does not impair BCI performance but is preferred by users, auditory (and perhaps other) BCIs should consider including it. Our study also indicates that auditory BCIs can be effective even if the auditory channel is simultaneously otherwise engaged.

Published
2016
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32. Optimizing the face Paradigm of BCI system by modified Mismatch Negative paradigm

Author

Siejie Zhou, Jing Jin, and Wang Xingyu

Subjects
Brain Computer Interface, P300, N400, Online system, face paradigm, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Many recent studies have focused on improving the performance of event-related potential (ERP) based brain computer interfaces (BCIs). The use of a face pattern has been shown to obtain high classification accuracies and information transfer rates (ITRs) by evoking discriminative ERPs (N200 and N400) in addition to P300 potentials. Recently, it has been proved that the performance of traditional P300-based BCIs could be improved through a modification of the mismatch pattern. In this paper, a mismatch inverted face pattern (MIF-pattern) was presented to improve the performance of the inverted face pattern (IF-pattern), one of the state of the art patterns used in visual-based BCI systems. Ten subjects attended in this experiment. The result showed that the mismatch inverted face pattern could evoke significantly larger vertex positive potentials (p

Published
2016
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33. A Study of the Impact of Digital Transformation on the Risk Level of Commercial Banks

Author

Wang, Xingyu, Qi, Mengjie, Dou, Runliang, Editor-in-Chief, Liu, Jing, Editor-in-Chief, Khasawneh, Mohammad T., Editor-in-Chief, Balas, Valentina Emilia, Series Editor, Bhowmik, Debashish, Series Editor, Khan, Khalil, Series Editor, Masehian, Ellips, Series Editor, Mohammadi-Ivatloo, Behnam, Series Editor, Nayyar, Anand, Series Editor, Pamucar, Dragan, Series Editor, Shu, Dewu, Series Editor, Haldorai, Anandakumar, editor, Singh, Dilbag, editor, Kumar, Anil, editor, Talpur, Mir Sajjad Hussain, editor, and Djeddi, Chawki, editor

Published
2024
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36. A Framework for Intelligent Generation of Intrusion Detection Rules Based on Grad-CAM

Author

Wang, Xingyu, Bao, Huaifeng, Li, Wenhao, Chen, Haoning, Wang, Wen, Liu, Feng, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Franco, Leonardo, editor, de Mulatier, Clélia, editor, Paszynski, Maciej, editor, Krzhizhanovskaya, Valeria V., editor, Dongarra, Jack J., editor, and Sloot, Peter M. A., editor

Published
2024
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41. In-plane anisotropic response to the uniaxial pressure in the hidden order state of URu$_2$Si$_2$

Author

Wang, Xingyu, Gong, Dongliang, Liu, Bo, Ma, Xiaoyan, Zhao, Jinyu, Wang, Pengyu, Sheng, Yutao, Guo, Jing, Sun, Liling, Zhang, Wen, Lai, Xinchun, Tan, Shiyong, Yang, Yi-feng, and Li, Shiliang

Subjects
Condensed Matter - Strongly Correlated Electrons
Abstract

We studied the uniaxial-pressure dependence of the resistivity for URu$_{2-x}$Fe$_x$Si$_2$ samples with $x$ = 0 and 0.2, which host a hidden order (HO) and a large-moment antiferromagnetic (LMAFM) phase, respectively. For both samples, the elastoresistivity $\zeta$ shows a seemingly divergent behavior above the transition temperature $T_0$ and a quick decrease below it. We found that the temperature dependence of $\zeta$ for both samples can be well described by assuming the uniaxial pressure effect on the gap or certain energy scale except for $\zeta_{(110)}$ of the $x$ = 0 sample, which exhibits a non-zero residual value at 0 K. We show that this provides a qualitative difference between the HO and LMAFM phases. Our results suggest that there is an in-plane anisotropic response to the uniaxial pressure that only exists in the hidden order state without necessarily breaking the rotational lattice symmetry., Comment: 6 pages, 3 figures

Published
2022
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