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The doctor will polygraph you now

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Npj health systems

Npj health systems 2024年第1期1卷 1页

作者： James Anibal Jasmine Gunkel Shaheen Awan Hannah Huth Hang Nguyen Tram Le Jean-Christophe Bélisle-Pipon Micah Boyer Lindsey Hazen Yael Bensoussan David Clifton Bradford Wood Center for Interventional Oncology Clinical Center National Institutes of Health (NIH) Bethesda MD USA. Computational Health Informatics Lab Institute of Biomedical Engineering Department of Engineering Science University of Oxford Oxford UK. Department of Bioethics National Institutes of Health (NIH) Bethesda MD USA. Department of Communication Sciences & Disorders University of Central Florida Orlando FL USA. Global Infectious Disease Program Georgetown University Washington DC USA. College of Engineering University of South Florida Tampa FL USA. Faculty of Health Sciences Simon Fraser University Burnaby BC Canada. USF Health Voice Center Department of Otolaryngology-Head & Neck Surgery University of South Florida Tampa FL USA.

Artificial intelligence (AI) methods have been proposed for the prediction of social behaviors that could be reasonably understood from patient-reported information. This raises novel ethical concerns about respect, privacy, and control over patient data. Ethical concerns surrounding clinical AI systems for social behavior verification can be divided into two main categories: (1) the potential for inaccuracies/biases within such systems, and (2) the impact on trust in patient-provider relationships with the introduction of automated AI systems for "fact-checking", particularly in cases where the data/models may contradict the patient. Additionally, this report simulated the misuse of a verification system using patient voice samples and identified a potential LLM bias against patient-reported information in favor of multi-dimensional data and the outputs of other AI methods (i.e., "AI self-trust"). Finally, recommendations were presented for mitigating the risk that AI verification methods will cause harm to patients or undermine the purpose of the healthcare system.

关键词： Ethics Machine learning science, technology and society

SI-spreading-based network embedding in static and temporal networks

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arXiv 2020年

作者： Zhan, Xiu-Xiu Li, Ziyu Masuda, Naoki Holme, Petter Wang, Huijuan Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Department of Mathematics University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be connected. Classic network embedding algorithms are random-walk-based. They sample trajectory paths via random walks and generate node pairs from the trajectory paths. The node pair set is further used as the input for a Skip-Gram model, a representative language model that embeds nodes (which are regarded as words) into vectors. In the present study, we propose to replace random walk processes by a spreading process, namely the susceptible-infected (SI) model, to sample paths. Specifically, we propose two SI-spreading-based algorithms, SINE and TSINE, to embed static and temporal networks, respectively. The performance of our algorithms is evaluated by the missing link prediction task in comparison with state-of-the-art static and temporal network embedding algorithms. Results show that SINE and TSINE outperform the baselines across all six empirical datasets. We further find that the performance of SINE is mostly better than TSINE, suggesting that temporal information does not necessarily improve the embedding for missing link prediction. Moreover, we study the effect of the sampling size, quantified as the total length of the trajectory paths, on the performance of the embedding algorithms. The better performance of SINE and TSINE requires a smaller sampling size in comparison with the baseline algorithms. Hence, SI-spreading-based embedding tends to be more applicable to large-scale networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Network embeddings

EMPRESS. XII. Statistics on the Dynamics and Gas Mass Fraction of Extremely-Metal Poor Galaxies

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arXiv 2023年

作者： Xu, Yi Ouchi, Masami Isobe, Yuki Nakajima, Kimihiko Ozaki, Shinobu Bouché, Nicolas F. Wise, John H. Emsellem, Eric Kusakabe, Haruka Hattori, Takashi Nagao, Tohru Chiaki, Gen Fukushima, Hajime Harikane, Yuichi Hayashi, Kohei Hirai, Yutaka Kim, Ji Hoon Maseda, Michael V. Nagamine, Kentaro Shibuya, Takatoshi Sugahara, Yuma Yajima, Hidenobu Aoyama, Shohei Fujimoto, Seiji Fukushima, Keita Hatano, Shun Inoue, Akio K. Ishigaki, Tsuyoshi Kawasaki, Masahiro Kojima, Takashi Komiyama, Yutaka Koyama, Shuhei Koyama, Yusei Lee, Chien-Hsiu Matsumoto, Akinori Mawatari, Ken Moriya, Takashi J. Motohara, Kentaro Murai, Kai Nishigaki, Moka Onodera, Masato Ono, Yoshiaki Rauch, Michael Saito, Tomoki Sasaki, Rin Suzuki, Akihiro Takeuchi, Tsutomu T. Umeda, Hiroya Umemura, Masayuki Watanabe, Kuria Yabe, Kiyoto Zhang, Yechi Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwanoha Chiba Kashiwa277-8582 Japan Department of Astronomy Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan University of Tokyo Chiba Kashiwa277-8583 Japan Department of Physics Graduate School of Science The University of Tokyo 7-3-1 Hongo Bunkyo Tokyo113-0033 Japan Univ Lyon Univ Lyon1 ENS de Lyon CNRS Centre de Recherche Astrophysique de Lyon UMR5574 Saint-Genis-LavalF-69230 France Center for Relativistic Astrophysics School of Physics Georgia Institute of Technology AtlantaGA30332 United States European Southern Observatory Karl-Schwarzschild-Straße 2 Garching85748 Germany Observatoire de Genéve Université de Genéve 51 Ch. des Maillettes Versoix1290 Switzerland 650 North A’ohoku Place HiloHI96720 United States Research Center for Space and Cosmic Evolution Ehime University Bunkyo-cho 2-5 Ehime Matsuyama790-8577 Japan Center for Computational Sciences University of Tsukuba Ten-nodai 1-1-1 Tsukuba Ibaraki305-8577 Japan Department of Physics and Astronomy University College London Gower Street LondonWC1E 6BT United Kingdom National Institute of Technology Ichinoseki College Hagisho Ichinoseki021-8511 Japan Astronomical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Miyagi Sendai980-8578 Japan Department of Physics and Astronomy University of Notre Dame 225 Nieuwland Science Hall Notre DameIN46556 United States Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Center Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Department of Astronomy University of Wisconsin-Madison 475 N. Charter Street MadisonWI53706 United States Theoretical Astrophysics Department of Earth & Space S

We present demography of the dynamics and gas-mass fraction of 33 extremely metal-poor galaxies (EMPGs) with metallicities of 0.015 − 0.195 Zo and low stellar masses of 104 − 108 Mo in the local universe. We conduct deep optical integral-field spectroscopy (IFS) for the low-mass EMPGs with the medium high resolution (R = 7500) grism of the 8m-Subaru FOCAS IFU instrument by the EMPRESS 3D survey, and investigate Hα emission of the EMPGs. Exploiting the resolution high enough for the low-mass galaxies, we derive gas dynamics with the Hα lines by the fitting of 3-dimensional disk models. We obtain an average maximum rotation velocity (vrot) of 15 ± 3 km s−1 and an average intrinsic velocity dispersion (σ0) of 27 ± 10 km s−1 for 15 spatially resolved EMPGs out of the 33 EMPGs, and find that all of the 15 EMPGs have vrot/σ0 rot/σ0 with the decreasing stellar mass and metallicity. We derive the gas mass fraction (fgas) for all of the 33 EMPGs, and find no clear dependence on stellar mass and metallicity. These vrot/σ0 and fgas trends should be compared with young high-z galaxies observed by the forthcoming JWST IFS programs to understand the physical origins of the EMPGs in the local universe. © 2023, CC BY.

关键词： Galaxies

Chemical complexity of phosphorous bearing species in various regions of the interstellar medium

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arXiv 2021年

作者： Sil, Milan Srivastav, Satyam Bhat, Bratati Mondal, Suman Kumar Gorai, Prasanta Ghosh, Rana Shimonishi, Takashi Chakrabarti, Sandip K. Sivaraman, Bhalamurugan Pathak, Amit Nakatani, Naoki Furuya, Kenji Das, Ankan Indian Centre for Space Physics 43 Chalantika Garia Station Road Kolkata700084 India Department of Physics Institute of Science Banaras Hindu University Varanasi221005 India Department of Space Earth & Environment Chalmers University of Technology GothenburgSE-412 96 Sweden Center for Transdisciplinary Research Niigata University Nishi-ku Niigata950-2181 Japan Environmental Science Program Department of Science Faculty of Science Niigata University Nishi-ku Niigata950-2181 Japan Physical Research Laboratory Navrangpura Ahmedabad380009 India Institute for Catalysis Hokkaido University N21W10 Kita-ku Sapporo Hokkaido001-0021 Japan Department of Chemistry Graduate School of Science and Engineering Tokyo Metropolitan University 1-1 Minami-Osawa Hachioji Tokyo192-0397 Japan Center for Computational Sciences University of Tsukuba Tsukuba305-8577 Japan National Astronomical Observatory of Japan Tokyo181-8588 Japan

Phosphorus related species are not known to be as omnipresent in space as hydrogen, carbon, nitrogen, oxygen, and sulfur-bearing species. Astronomers spotted very few P-bearing molecules in the interstellar medium and circumstellar envelopes. Limited discovery of the P-bearing species imposes severe constraints in modeling the P-chemistry. In this paper, we carry out extensive chemical models to follow the fate of P-bearing species in diffuse clouds, photon-dominated or photodissociation regions (PDRs), and hot cores/corinos. We notice a curious correlation between the abundances of PO and PN and atomic nitrogen. Since N atoms are comparatively abundant in diffuse clouds and PDRs than in the hot core/corino region, PO/PN reflects 1 in the late warm-up evolutionary phase of the hot core/corino regions. During the end of the post-warm-up phase, we obtain PO/PN > 1 for hot core and 3along with various impurities. We notice that SO2overlaps with the PH3bending-scissoring modes around ∼ (1000 - 1100) cm-1. We also find that the presence of CO2can strongly influence the intensity of the stretching modes around ∼ 2400 cm-1of PH3 © 2021, CC0.

关键词： Radiative transfer

Seebeck coefficient in a cuprate superconductor: Particle-hole asymmetry in the strange metal phase and Fermi surface transformation in the pseudogap phase

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arXiv 2021年

作者： Gourgout, A. Grissonnanche, G. Laliberté, F. Ataei, A. Chen, L. Verret, S. Zhou, J.-S. Mravlje, J. Georges, A. Doiron-Leyraud, N. Taillefer, Louis Institut Quantique Département de physique and RQMP Université de Sherbrooke SherbrookeQC Canada Laboratory of Atomic and Solid State Physics Cornell University IthacaNY United States Kavli Institute at Cornell for Nanoscale Science IthacaNY United States Materials Science and Engineering Program/Mechanical Engineering University of Texas - Austin AustinTX United States Department of Theoretical Physics Institute Jožef Stefan Ljubljana Slovenia Collège de France 11 place Marcelin Berthelot Paris France Center for Computational Quantum Physics Flatiron Institute New YorkNY United States CPHT CNRS Ecole Polytechnique IP Paris Palaiseau France DQMP Université de Genève Geneva Switzerland Canadian Institute for Advanced Research TorontoON Canada

We report measurements of the Seebeck effect in both the ab plane (Sa) and along the c axis (Sc) of the cuprate superconductor La1:6-xNd0:4SrxCuO4(Nd-LSCO), performed in magnetic fields large enough to suppress superconductivity down to low temperature. We use the Seebeck coefficient as a probe of the particle-hole asymmetry of the electronic structure across the pseudogap critical doping p∗ = 0:23. Outside the pseudogap phase, at p = 0:24 > p∗, we observe a positive and essentially isotropic Seebeck coefficient as T → 0. That S > 0 at p = 0:24 is at odds with expectations given the electronic band structure of Nd-LSCO above p∗ and its known electron-like Fermi surface. We can reconcile this observation by invoking an energy-dependent scattering rate with a particle-hole asymmetry, possibly rooted in the non-Fermi liquid nature of cuprates just above p∗. Inside the pseudogap phase, for p Copyright © 2021, The Authors. All rights reserved.

关键词： Electronic structure

SeqScreen: a biocuration platform for robust taxonomic and biological process characterization of nucleic acid sequences of interest

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SeqScreen: a biocuration platform for robust taxonomic and b...

IEEE International Conference on Bioinformatics and Biomedicine

作者： Dreycey Albin Dan Nasko R. A. Leo Elworth Jacob Lu Advait Balaji Christian Diaz Nidhi Shah Jeremy Selengut Chris Hulme-Lowe Pravin Muthu Gene Godbold Mikael Lindvall Madeline Diep Adam Porter Mihai Pop Krista Ternus Todd J. Treangen Program in Systems Synthetic and Physical Biology Rice University Center for Bioinformatics and Computational Biology University of Maryland Department of Computer Science Rice University Signature Science LLC Fraunhofer Center for Experimental Software Engineering Department of Computer Science University of Maryland

ISBN: (纸本)9781728118680

Rapid advancements in synthetic biology and nucleic acid synthesis, in particular concerns about its intentional or accidental misuse, call for more sophisticated screening tools to identify genes of interest within short sequence fragments. One major gap in predicting genes of concern is the inadequacy of current tools and ontologies to describe the specific biological processes of pathogenic proteins. The objective of this work is to design software that sensitively assigns taxonomic classifications, functional annotations, and biological processes of interest to short nucleotide sequences of unknown origin (50bp-1,000bp). The overarching goal is to perform sensitive characterization of short sequences and highlight specific pathogenic biological processes of interest (BPoIs). The SeqScreen software executes these tasks in analytical workflows with Nextflow and outputs results in a tab-delimited report. Local and global alignments differentiate hits to taxonomically-related sequences from similar but unrelated sequences, and an ensemble approach leverages multiple tools and databases to assign a variety of functional terms to each query sequence. Final biological process assessments are made from the predicted functional annotations, which leverage information in pre-existing databases, as well as new custom biocurations. Machine learning models predict each biological process of interest on large protein databases before incorporation into the SeqScreen framework to streamline computational efficiency, ensure reproducible results, allow for version control, and facilitate the review of the automated predictions by expert biocurators. The SeqScreen source code is available at .

关键词： Biological Process interest Base Sequence Nucleic acids Version control protein database Database synthetic biology ANNOTATIONS Leverage

Modeling subgrid-scale force and divergence of heat flux of compressible isotropic turbulence by artificial neural network

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Physical Review Fluids 2019年第10期4卷 104605-104605页

作者： Chenyue Xie Ke Li Chao Ma Jianchun Wang Shenzhen Key Laboratory of Complex Aerospace Flows Center for Complex Flows and Soft Matter Research Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Shenzhen 518055 People's Republic of China Institute of Computational Mathematics and Scientific Engineering Computing Chinese Academy of Sciences Beijing 100190 People's Republic of China The Program in Applied and Computational Mathematics Princeton University Princeton New Jersey 08544 USA

In this paper, the subgrid-scale (SGS) force and the divergence of SGS heat flux of compressible isotropic turbulence are modeled directly by an artificial neural network (ANN), which serves as a data-driven SGS modeling tool for large-eddy simulations (LESs). The unclosed SGS force and divergence of SGS heat flux are modeled based on the local stencil geometry with Galilean invariance. The input features include the first-order and second-order derivatives of filtered velocity and temperature, filtered density, and its first-order derivative. It is shown that the proposed ANN-F7 model shows an advantage over the gradient model in the a priori test. Specifically, the ANN-F7 model gives larger correlation coefficients and smaller relative errors than the gradient model. In an a posteriori analysis, the ANN-F7 model performs better than the dynamic Smagorinsky model (DSM) and dynamic mixed model (DMM) in the prediction of the statistical properties of flow fields at the Taylor microscale Reynolds number Reλ ranging from 180 to 250. The DSM and DMM models lead to the typical tilted spectral distribution of velocity, where low wave numbers are too energy rich, while those near the cutoff are damped too strongly. In contrast, it is shown that the velocity spectrum predicted by the ANN-F7 model almost overlaps with the filtered direct numerical simulation data. Besides, the ANN-F7 model reconstructs the probability density functions of SGS force and divergence of SGS heat flux much better than the DSM and DMM models. An artificial neural network with reasonable physical input features can deepen our understanding of turbulence modeling.

关键词： Compressible flows Turbulence Artificial neural networks

Rewriting regulatory DNA to dissect and reprogram gene expression

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Cell 2025年

作者： Martyn, Gabriella E. Montgomery, Michael T. Jones, Hank Guo, Katherine Doughty, Benjamin R. Linder, Johannes Bisht, Deepa Xia, Fan Cai, Xiangmeng S. Chen, Ziwei Cochran, Kelly Lawrence, Kathryn A. Munson, Glen Pampari, Anusri Fulco, Charles P. Sahni, Nidhi Kelley, David R. Lander, Eric S. Kundaje, Anshul Engreitz, Jesse M. Department of Genetics Stanford University School of Medicine Stanford 94305 CA United States Basic Science and Engineering Initiative Stanford Children's Health Betty Irene Moore Children's Heart Center Stanford 94305 CA United States Calico Life Sciences LLC South San Francisco 94080 CA United States Department of Genitourinary Medical Oncology Division of Cancer Medicine The University of Texas MD Anderson Cancer Center Houston 77030 TX United States Department of Genomic Medicine The University of Texas MD Anderson Cancer Center Houston 77030 TX United States Department of Epigenetics and Molecular Carcinogenesis The University of Texas MD Anderson Cancer Center Houston 77230 TX United States Department of Bioengineering Stanford University Stanford 94305 CA United States Department of Computer Science Stanford University Stanford 94305 CA United States Novo Nordisk Foundation Center for Genomic Mechanisms of Disease Broad Institute of MIT and Harvard Cambridge 02142 MA United States Gene Regulation Observatory Broad Institute of MIT and Harvard Cambridge 02142 MA United States Broad Institute of MIT and Harvard Cambridge 02142 MA United States Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer Center Houston 77230 TX United States Quantitative and Computational Biosciences Program Baylor College of Medicine Houston 77030 TX United States Department of Biology MIT Cambridge 02139 MA United States Department of Systems Biology Harvard Medical School Boston 02115 MA United States Stanford Cardiovascular Institute Stanford University Stanford 94305 CA United States

Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context. © 2025 Elsevier Inc.

关键词： CRISPR enhancers gene regulation high-throughput screening non-coding variants predictive models prime editing RNA FlowFISH sequence design transcription factors

Correction to: Large-scale dynamics have greater role than thermodynamics in driving precipitation extremes over India

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Climate Dynamics 2021年第9期57卷 2937-2937页

作者： Sudharsan, Naveen Karmakar, Subhankar Fowler, Hayley J. Hari, Vittal Environmental Science and Engineering Department Indian Institute of Technology Bombay Mumbai India Interdisciplinary Program in Climate Studies Indian Institute of Technology Bombay Mumbai India Centre for Urban Science and Engineering Indian Institute of Technology Bombay Mumbai India School of Engineering Newcastle University Newcastle-upon-Tyne UK Department of Computational Hydrosystems Helmholtz Centre for Environmental Research UFZ Leipzig Germany