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2,787 results on '"Li, James"'

1. Total Outcome Logic: Proving Termination and Nontermination in Programs with Branching

Author

Li, James, Zilberstein, Noam, and Silva, Alexandra

Subjects
Computer Science - Logic in Computer Science
Abstract

While there is a long tradition of reasoning about termination (and nontermination) in the context of program analysis, specialized logics are typically needed to give different termination guarantees. This includes partial correctness, where termination is not guaranteed, and total correctness, where it is guaranteed. We present Total Outcome Logic, a single logic which can express the full spectrum of termination conditions and program properties offered by the aforementioned logics. Total Outcome Logic extends termination and incorrectness reasoning across different kinds of branching effects, so that a single metatheory powers this reasoning in different kinds of programs, including nondeterministic and probabilistic. We demonstrate the utility of this approach through a variety of case studies.

Published
2024

2. Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction

Author

Jia, Guochong, Ping, Jie, Guo, Xingyi, Yang, Yaohua, Tao, Ran, Li, Bingshan, Ambs, Stefan, Barnard, Mollie E., Chen, Yu, Garcia-Closas, Montserrat, Gu, Jian, Hu, Jennifer J., Huo, Dezheng, John, Esther M., Li, Christopher I., Li, James L., Nathanson, Katherine L., Nemesure, Barbara, Olopade, Olufunmilayo I., Pal, Tuya, Press, Michael F., Sanderson, Maureen, Sandler, Dale P., Shu, Xiao-Ou, Troester, Melissa A., Yao, Song, Adejumo, Prisca O., Ahearn, Thomas, Brewster, Abenaa M., Hennis, Anselm J. M., Makumbi, Timothy, Ndom, Paul, O’Brien, Katie M., Olshan, Andrew F., Oluwasanu, Mojisola M., Reid, Sonya, Butler, Ebonee N., Huang, Maosheng, Ntekim, Atara, Qian, Huijun, Zhang, Haoyu, Ambrosone, Christine B., Cai, Qiuyin, Long, Jirong, Palmer, Julie R., Haiman, Christopher A., and Zheng, Wei

Published
2024
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8. OSC Community Lab: The Integration Test Bed for O-RAN Software Community

Author

Bimo, Fransiscus Asisi, Feliana, Ferlinda, Liao, Shu-Hua, Lin, Chih-Wei, Kinsey, David F., Li, James, Jana, Rittwik, Wright, Richard, and Cheng, Ray-Guang

Subjects
Computer Science - Networking and Internet Architecture
Abstract

O-RAN Software Community (OSC) is an open-source project collaborated by O-RAN Alliance and Linux Foundation, aiming to develop reference software components based on 3GPP and O-RAN Alliance specifications. The OSC has twelve projects. Among them, the Integration and Testing (INT) project is responsible for testing the requirements documented in each release for end-to-end and use case testing. Three OSC Community Laboratories were built to speed up the integration and interoperability testing among different projects. This paper summarizes the software components developed by OSC projects and the status of the three OSC Community Laboratories. The activities of each laboratory, how the community collaborates, and the challenges we encountered along the way were elaborated.

Published
2022

9. A Scalable Blockchain-based Smart Contract Model for Decentralized Voltage Stability Using Sharding Technique

Author

Honari, Kimia, Zhou, Xiaotian, Rouhani, Sara, Dick, Scott, Liang, Hao, Li, James Miller, and Miller, James

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Blockchain technologies are one possible avenue for increasing the resilience of the Smart Grid, by decentralizing the monitoring and control of system-level objectives such as voltage stability protection. They furthermore offer benefits in data immutability and traceability, as blockchains are cryptographically secured. However, the performance of blockchain-based systems in real-time grid monitoring and control has never been empirically tested. This study proposes implementing a decentralized voltage stability algorithm using blockchain-based smart contracts, as a testbed for evaluating the performance of blockchains in real-time control. We furthermore investigate sharding mechanisms as a means of improving the system's scalability with fixed computing resources. We implement our models as a proof-of-concept prototype system using Hyperledger Fabric as our blockchain platform, the Matpower library in MATLAB as our power system simulator, and Hyperledger Caliper as our performance evaluation tool. We found that sharding does indeed lead to a substantial improvement in system scalability for this domain, measured by both transaction success rates and transaction latency., Comment: 8 pages

Published
2022

11. Venus as an Exoplanet: I. An Initial Exploration of the 3-D Energy Balance for a CO$_{2}$ Exoplanetary Atmosphere Around an M-Dwarf Star

Author

Parkinson, Christopher D., Bougher, Stephen W., Mills, Franklin P., Brecht, Amanda, Li, James, Yung, Yuk L., Hu, Renyu, and Gronoff, Guillaume

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract

The chemical evolution of an exoplanetary Venus-like atmosphere is dependent upon the ultraviolet to near ultraviolet (FUV-NUV) radiation ratio from the parent star, the balance between CO$_{2}$ photolysis and recombination via reactions that depend on the water abundance, and various catalytic chemical cycles. In this study, we use a three-dimensional (3-D) model to simulate conditions for a Venus-like exoplanet orbiting the M-dwarf type star GJ 436 by varying the star/planet distance and considering the resultant effects on heating/cooling and dynamics. The simulation includes the middle and upper atmosphere (<40 mbar). Overall, these model comparisons reveal that the impact of extreme ultraviolet to ultraviolet (EUV-UV) heating on the energy balance shows both radiative and dynamical processes are responsible for driving significant variations in zonal winds and global temperature profiles at < 10$^{-5}$ mbar. More specifically, CO$_{2}$ 15-${\mu}$m cooling balances EUV/UV and Near InfraRed (NIR) heating at altitudes below 10$^{-7}$ mbar pressure with a strong maximum balance for pressures at ~10$^{-5}$ mbar, thus explaining the invariance of the temperature distribution at altitudes below 10$^{-5}$mbar pressure for all cases. Our model comparisons also show that moderate changes in NIR heating result in relatively small changes in neutral temperature in the upper atmosphere, and virtually no change in the middle atmosphere. However, with larger changes in the NIR heating profile, much greater changes in neutral temperature occur in the entire upper and middle atmosphere studied., Comment: 44 pages, 11 Figures, 3 tables

Published
2022

12. Computer-aided diagnosis for the resect-and-discard strategy for colorectal polyps: a systematic review and meta-analysis

Author

Carrara, Silvia, Fugazza, Alessandro, Capogreco, Antonio, Massimi, Davide, Djinbachian, Roupen, Takishima, Kazumi, Mochizuki, Kenichi, Miyata, Yuki, Mochida, Kentaro, Akimoto, Yoshika, Kuroki, Takanori, Morita, Yuriko, Shiina, Osamu, Kato, Shun, Barua, Ishita, Holme, Øyvind, Wieszczy, Paulina, Løberg, Magnus, Kalager, Mette, Gulati, Shraddha, Williams, Sophie, Hayee, Bu, Patel, Mehul, Gunasingam, Nishmi, Kent, Alexandra, Emmanuel, Andrew, Haji, Amyn, Itoh, Hayato, Mori, Kensaku, Nemoto, Tetsuo, Munck, Carl, Aksel Nilsen, Jens, Astrup Hvattum, Stine, Oskar Frigstad, Svein, Tandberg, Petter, Lanza, Davide, Bonanno, Giacomo, Hassan, Cesare, Rizkala, Tommy, Mori, Yuichi, Spadaccini, Marco, Misawa, Masashi, Antonelli, Giulio, Rondonotti, Emanuele, Dekker, Evelien, Houwen, Britt B S L, Pech, Oliver, Baumer, Sebastian, Li, James Weiquan, von Renteln, Daniel, Haumesser, Claire, Maselli, Roberta, Facciorusso, Antonio, Correale, Loredana, Menini, Maddalena, Schilirò, Alessandro, Khalaf, Kareem, Patel, Harsh, Radadiya, Dhruvil K, Bhandari, Pradeep, Kudo, Shin-ei, Sultan, Shahnaz, Vandvik, Per Olav, Sharma, Prateek, Rex, Douglas K, Foroutan, Farid, and Repici, Alessandro

Published
2024
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16. Mechanistic insights into consumption of the food additive xanthan gum by the human gut microbiota.

Author

Ostrowski, Matthew, La Rosa, Sabina, Kunath, Benoit, Robertson, Andrew, Pereira, Gabriel, Hagen, Live, Varghese, Neha, Qiu, Ling, Yao, Tianming, Flint, Gabrielle, Li, James, McDonald, Sean, Buttner, Duna, Pudlo, Nicholas, Schnizlein, Matthew, Young, Vincent, Brumer, Harry, Schmidt, Thomas, Terrapon, Nicolas, Lombard, Vincent, Henrissat, Bernard, Hamaker, Bruce, Eloe-Fadrosh, Emiley, Tripathi, Ashootosh, Pope, Phillip, and Martens, Eric

Subjects
Animals, Dietary Fiber, Food Additives, Gastrointestinal Microbiome, Humans, Mice, Polysaccharides, Bacterial
Abstract

Processed foods often include food additives such as xanthan gum, a complex polysaccharide with unique rheological properties, that has established widespread use as a stabilizer and thickening agent. Xanthan gums chemical structure is distinct from those of host and dietary polysaccharides that are more commonly expected to transit the gastrointestinal tract, and little is known about its direct interaction with the gut microbiota, which plays a central role in digestion of other dietary fibre polysaccharides. Here we show that the ability to digest xanthan gum is common in human gut microbiomes from industrialized countries and appears contingent on a single uncultured bacterium in the family Ruminococcaceae. Our data reveal that this primary degrader cleaves the xanthan gum backbone before processing the released oligosaccharides using additional enzymes. Some individuals harbour Bacteroides intestinalis that is incapable of consuming polymeric xanthan gum but grows on oligosaccharide products generated by the Ruminococcaceae. Feeding xanthan gum to germfree mice colonized with a human microbiota containing the uncultured Ruminococcaceae supports the idea that the additive xanthan gum can drive expansion of the primary degrader Ruminococcaceae, along with exogenously introduced B. intestinalis. Our work demonstrates the existence of a potential xanthan gum food chain involving at least two members of different phyla of gut bacteria and provides an initial framework for understanding how widespread consumption of a recently introduced food additive influences human microbiomes.

Published
2022

17. ST-PCNN: Spatio-Temporal Physics-Coupled Neural Networks for Dynamics Forecasting

Author

Huang, Yu, Li, James, Shi, Min, Zhuang, Hanqi, Zhu, Xingquan, Chérubin, Laurent, VanZwieten, James, and Tang, Yufei

Subjects
Computer Science - Machine Learning
Abstract

Ocean current, fluid mechanics, and many other spatio-temporal physical dynamical systems are essential components of the universe. One key characteristic of such systems is that certain physics laws -- represented as ordinary/partial differential equations (ODEs/PDEs) -- largely dominate the whole process, irrespective of time or location. Physics-informed learning has recently emerged to learn physics for accurate prediction, but they often lack a mechanism to leverage localized spatial and temporal correlation or rely on hard-coded physics parameters. In this paper, we advocate a physics-coupled neural network model to learn parameters governing the physics of the system, and further couple the learned physics to assist the learning of recurring dynamics. A spatio-temporal physics-coupled neural network (ST-PCNN) model is proposed to achieve three goals: (1) learning the underlying physics parameters, (2) transition of local information between spatio-temporal regions, and (3) forecasting future values for the dynamical system. The physics-coupled learning ensures that the proposed model can be tremendously improved by using learned physics parameters, and can achieve good long-range forecasting (e.g., more than 30-steps). Experiments, using simulated and field-collected ocean current data, validate that ST-PCNN outperforms existing physics-informed models.

Published
2021

18. Diversity and the Hierarchical Taxonomy of Psychopathology (HiTOP)

Author

Rodriguez-Seijas, Craig, Li, James J., Balling, Caroline, Brandes, Cassandra, Bernat, Edward, Boness, Cassandra L., Forbes, Miriam K., Forbush, Kelsie T., Joyner, Keanan J., Krueger, Robert F., Levin-Aspenson, Holly F., Michelini, Giorgia, Ro, Eunyoe, Rutter, Lauren, Stanton, Kasey, Tackett, Jennifer L., Waszczuk, Monika, and Eaton, Nicholas R.

Published
2023
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20. Ataluren delays loss of ambulation and respiratory decline in nonsense mutation Duchenne muscular dystrophy patients.

Author

Muntoni, Francesco, Penematsa, Vinay, Jiang, Joel, Kristensen, Allan, Bibbiani, Francesco, Goodwin, Elizabeth, Gordish-Dressman, Heather, Morgenroth, Lauren, Werner, Christian, Li, James, Able, Richard, Trifillis, Panayiota, Tulinius, Már, and McDonald, Craig

Subjects
Study 019, ataluren, dystrophin, efficacy, loss of ambulation, nonsense mutation Duchenne muscular dystrophy, respiratory function, Codon, Nonsense, Humans, Muscular Dystrophy, Duchenne, Oxadiazoles, Walking
Abstract

Aim: We investigated the effect of ataluren plus standard of care (SoC) on age at loss of ambulation (LoA) and respiratory decline in patients with nonsense mutation Duchenne muscular dystrophy (nmDMD) versus patients with DMD on SoC alone. Patients & methods: Study 019 was a long-term Phase III study of ataluren safety in nmDMD patients with a history of ataluren exposure. Propensity score matching identified Study 019 and CINRG DNHS patients similar in disease progression predictors. Results & conclusion: Ataluren plus SoC was associated with a 2.2-year delay in age at LoA (p = 0.0006), and a 3.0-year delay in decline of predicted forced vital capacity to

Published
2022

21. Cell‐to‐cell and type‐to‐type heterogeneity of signaling networks: insights from the crowd

Author

Gabor, Attila, Tognetti, Marco, Driessen, Alice, Tanevski, Jovan, Guo, Baosen, Cao, Wencai, Shen, He, Yu, Thomas, Chung, Verena, Bodenmiller, Bernd, Saez‐Rodriguez, Julio, Prusokas, Augustinas, Prusokas, Alidivinas, Retkute, Renata, Rajasekar, Anand, Raman, Karthik, Sudhakar, Malvika, Rengaswamy, Raghunathan, Shih, Edward SC, Kim, Min‐jeong, Cho, Changje, Kim, Dohyang, Oh, Hyeju, Hwang, Jinseub, Jongtae, Kim, Nam, Yeongeun, Yoon, Sanghoo, Kwon, Taeyong, Lee, Kyeongjun, Chaudhary, Sarika, Sharma, Nehal, Bande, Shreya, Cankut Cubuk, Gao Gao fan zhu, Gundogdu, Pelin, Dopazo, Joaquin, Rian, Kinza, Loucera, Carlos, Falco, Matias M, Garrido‐Rodriguez, Martin, Peña‐Chilet, Maria, Chen, Huiyuan, Turu, Gabor, Hunyadi, Laszlo, Misak, Adam, Zhou, Lisheng, Jiang, Xiaoqing, Zhang, Pieta, Rai, Aakansha, Kutum, Rintu, Rana, Sadhna, Srinivasan, Rajgopal, Pradhan, Swatantra, Li, James, Bajic, Vladimir, Van Neste, Christophe, Barradas‐bautista, Didier, Albarade, Somayah Abdullah, Nikolskiy, Igor, Sinkala, Musalula, Tran, Duc, Nguyen, Hung, Nguyen, Tin, Wu, Alexander, DeMeo, Benjamin, Hie, Brian, Singh, Rohit, Liu, Jiwei, Chen, Xueer, Saiz, Leonor, Vilar, Jose MG, Qiu, Peng, Gosain, Akash, Dhall, Anjali, Bajaj, Dinesh, Kaur, Harpreet, Bagaria, Krishna, Chauhan, Mayank, Sharma, Neelam, Raghava, Gajendra, Patiyal, Sumeet, Hao, Jianye, Peng, Jiajie, Ning, Shangyi, Ma, Yi, Wei, Zhongyu, Aalto, Atte, Goncalves, Jorge, Mombaerts, Laurent, Dai, Xinnan, Zheng, Jie, Mundra, Piyushkumar, Xu, Fan, Wang, Jie, Kant Singh, Krishna, and Lee, Mingyu

Subjects
Cancer, Breast Cancer, 1.1 Normal biological development and functioning, Underpinning research, Generic health relevance, Breast Neoplasms, Female, Humans, Machine Learning, Proteins, Signal Transduction, cell signaling, crowdsourcing, mass cytometry, predictive modeling, single cell, Single Cell Signaling in Breast Cancer DREAM Consortium members, Biochemistry and Cell Biology, Other Biological Sciences, Bioinformatics
Abstract

Recent technological developments allow us to measure the status of dozens of proteins in individual cells. This opens the way to understand the heterogeneity of complex multi-signaling networks across cells and cell types, with important implications to understand and treat diseases such as cancer. These technologies are, however, limited to proteins for which antibodies are available and are fairly costly, making predictions of new markers and of existing markers under new conditions a valuable alternative. To assess our capacity to make such predictions and boost further methodological development, we organized the Single Cell Signaling in Breast Cancer DREAM challenge. We used a mass cytometry dataset, covering 36 markers in over 4,000 conditions totaling 80 million single cells across 67 breast cancer cell lines. Through four increasingly difficult subchallenges, the participants predicted missing markers, new conditions, and the time-course response of single cells to stimuli in the presence and absence of kinase inhibitors. The challenge results show that despite the stochastic nature of signal transduction in single cells, the signaling events are tightly controlled and machine learning methods can accurately predict new experimental data.

Published
2021

25. Accuracy of Computer-aided Diagnosis in Colonoscopy Varies According to Polyp Location: A Systematic Review and Meta-analysis

Author

Rizkala, Tommy, Hassan, Cesare, Mori, Yuichi, Spadaccini, Marco, Antonelli, Giulio, Dekker, Evelien, Houwen, Britt B.S.L., Pech, Oliver, Baumer, Sebastian, Rondonotti, Emanuele, Radaelli, Franco, Li, James Weiquan, von Renteln, Daniel, Misawa, Masashi, Facciorusso, Antonio, Maselli, Roberta, Carrara, Silvia, Fugazza, Alessandro, Capogreco, Antonio, Khalaf, Kareem, Patel, Harsh, Sharma, Prateek, Rex, Douglas, and Repici, Alessandro

Published
2024
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30. Sequential transarterial chemoembolisation and stereotactic body radiotherapy followed by immunotherapy as conversion therapy for patients with locally advanced, unresectable hepatocellular carcinoma (START-FIT): a single-arm, phase 2 trial

Author

Chiang, Chi Leung, Chiu, Keith Wan Hang, Chan, Kenneth Sik Kwan, Lee, Francis Ann Shing, Li, James Chun Bong, Wan, Catherine Wing Suet, Dai, Wing Chiu, Lam, Tai Chung, Chen, Wenqi, Wong, Natalie Sean Man, Cheung, Andy Lai Yin, Lee, Venus Wan Yan, Lau, Vince Wing Hang, El Helali, Aya, Man, Kwan, Kong, Feng Ming (Spring), Lo, Chung Mau, and Chan, Albert Chi-Yan

Published
2023
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34. Semisupervised Learning on Heterogeneous Graphs and its Applications to Facebook News Feed

Author

Ju, Cheng, Li, James, Wasti, Bram, and Guo, Shengbo

Subjects
Computer Science - Social and Information Networks, Computer Science - Information Retrieval, Computer Science - Machine Learning, Computer Science - Multimedia
Abstract

Graph-based semi-supervised learning is a fundamental machine learning problem, and has been well studied. Most studies focus on homogeneous networks (e.g. citation network, friend network). In the present paper, we propose the Heterogeneous Embedding Label Propagation (HELP) algorithm, a graph-based semi-supervised deep learning algorithm, for graphs that are characterized by heterogeneous node types. Empirically, we demonstrate the effectiveness of this method in domain classification tasks with Facebook user-domain interaction graph, and compare the performance of the proposed HELP algorithm with the state of the art algorithms. We show that the HELP algorithm improves the predictive performance across multiple tasks, together with semantically meaningful embedding that are discriminative for downstream classification or regression tasks.

Published
2018

38. Correction: Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

Author

Tiwari, Arun K., Zai, Clement C., Altar, C. Anthony, Tanner, Julie-Anne, Davies, Paige E., Traxler, Paul, Li, James, Cogan, Elizabeth S., Kucera, Matthew T., Gugila, Ana, Braganza, Nicole, Emmerson, Heather, Zai, Gwyneth, Müller, Daniel J., Levitan, Robert, Kloiber, Stefan, Daskalakis, Zafiris J., Frey, Benicio N., Bowen, James M., Tarride, Jean-Eric, Tytus, Richard, Chandrasena, Ranjith, Voudouris, Nicholas, Taylor, Valerie H., Tempier, Raymond, Sharma, Verinder, Vasudev, Akshya, Dzongowski, Peter, Pliamm, Lew, Greenspoon, Todd, Dechairo, Bryan M., and Kennedy, James L.

Published
2022
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40. Clinical utility of combinatorial pharmacogenomic testing in depression: A Canadian patient- and rater-blinded, randomized, controlled trial

Author

Tiwari, Arun K., Zai, Clement C., Altar, C. Anthony, Tanner, Julie-Anne, Davies, Paige E., Traxler, Paul, Li, James, Cogan, Elizabeth S., Kucera, Matthew T., Gugila, Ana, Braganza, Nicole, Emmerson, Heather, Zai, Gwyneth, Müller, Daniel J., Levitan, Robert, Kloiber, Stefan, Daskalakis, Zafiris J., Frey, Benicio N., Bowen, James M., Tarride, Jean-Eric, Tytus, Richard, Chandrasena, Ranjith, Voudouris, Nicholas, Taylor, Valerie H., Tempier, Raymond, Sharma, Verinder, Vasudev, Akshya, Dzongowski, Peter, Pliamm, Lew, Greenspoon, Todd, Dechairo, Bryan M., and Kennedy, James L.

Published
2022
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42. Narrow-Band Imaging

Author

Li, James Weiquan, Ang, Tiing Leong, Chiu, Philip W. Y., editor, Sano, Yasushi, editor, Uedo, Noriya, editor, and Singh, Rajvinder, editor

Published
2021
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43. Statistical Modeling of GxE

Author

Jolicoeur-Martineau, Alexia, Li, James J., Greenwood, Celia M. T., Wazana, Ashley, editor, Székely, Eszter, editor, and Oberlander, Tim F., editor

Published
2021
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45. Microstructural neural correlates of maximal grip strength in autistic children: the role of the cortico-cerebellar network and attention-deficit/hyperactivity disorder features

Author

Surgent, Olivia, primary, Guerrero-Gonzalez, Jose, additional, Dean, Douglas C., additional, Adluru, Nagesh, additional, Kirk, Gregory R., additional, Kecskemeti, Steven R., additional, Alexander, Andrew L., additional, Li, James J., additional, and Travers, Brittany G., additional

Published
2024
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47. Rotational Thromboelastometry (ROTEM) reduces the need for pre-emptive transfusion in cirrhosis: A randomized controlled Trial (NCT:05698134).

Author

Kumar, Rahul, primary, Ng, Xiang Long Louis, additional, Wong, Yu Jun, additional, Tan, Chin Kimg, additional, Wang, Louis Zizhao, additional, Qiu, Tian Yu, additional, Wong, Benny, additional, Lin, Kenneth Weicong, additional, Li, James Weiquan, additional, Kwek, Andrew Boon Eu, additional, Ang, Tiing Leong, additional, Gokhle, Roshni Sadashiv, additional, and Sivanath, Tirukonda Prasanna, additional

Published
2024
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50. Survey on the perceptions of Asian endoscopists to artificial intelligence

Author

Lee, Jonathan, primary, QUEK, Sabrina Xin Zi, additional, KOO, Chieh Sian, additional, LIU, Lin, additional, LEUNG, Wai Keung, additional, TANG, Raymond Shing Yan, additional, Chung, Hyunsoo, additional, ZHANG, Xuesong, additional, ICHIMASA, Katsuro, additional, NGO, Denis, additional, MARALIT, Ruter, additional, DAO, Viet Hang, additional, KHIEN, Vu Van, additional, DUSEJA, Ajay, additional, PRATAP, Nitesh, additional, LEE, Yeong Yeh, additional, RENALDI, Kaka, additional, SIM, Shi Min, additional, WU, Clement Chun Ho, additional, LI, James Weiquan, additional, TAN, Jarrod Kah Hwee, additional, KOH, Calvin Jianyi, additional, and SO, Jimmy Bok Yan, additional

Published
2024
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