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Implications of Sea Breezes on Air Quality Monitoring in a Coastal Urban Environment: Evidence From High Resolution Modeling of NO2and O3

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Journal of Geophysical Research: Atmospheres 2023年第11期128卷 e2022JD037860-e2022JD037860页

作者： Bo Wang Jeffrey A. Geddes Taylor J. Adams Elena S. Lind Brian C. McDonald Jian He Colin Harkins Dan Li Gabriele G. Pfister Department of Earth and Environment Boston University MA Boston USA B. Wang Contribution: Conceptualization Methodology Formal analysis Investigation Resources Writing - original draft Writing - review & editing Visualization Contribution: Conceptualization Methodology Formal analysis Investigation Resources Data curation Writing - review & editing Supervision Project administration Funding acquisition Contribution: Resources Writing - review & editing Department of Electrical and Computer Engineering Virginia Tech VA Blacksburg USA Now at NASA Goddard Space Flight Center Greenbelt MD USA Chemical Sciences Laboratory NOAA Earth System Research Laboratories CO Boulder USA Cooperative Institute for Research in Environmental Sciences University of Colorado CO Boulder USA Contribution: Methodology Resources Writing - review & editing Atmospheric Chemistry Observations and Modeling Laboratory NCAR CO Boulder USA Contribution: Conceptualization Resources Writing - review & editing

Coastal urban environments face unique challenges associated with air quality-meteorology interactions. In this study, high resolution chemical transport modeling over the Greater Boston area was performed to improve our understanding of sea breezes impacts on the spatiotemporal variability of primary and secondary pollutants. We perform WRF-Chem simulations at 3 km resolution over June 22 to 10 July 2019 (a period that included 10 sea breeze occurrences), and use Pandora tropospheric NO 2 column, surface air quality monitoring, and vertical meteorological aircraft profiles for evaluation. The model generally reproduces observed spatiotemporal variability of air pollution during sea breezes well. Tropospheric columns of NO 2 predicted by the model and observed by the Pandora instrument show that sea breezes are associated with rapid increases and steep gradients in tropospheric NO 2 and confirm accumulation of local primary emissions. Spatial heterogeneity in tropospheric NO 2 is strongly governed by inland penetration lengths of the sea breeze front. Process diagnostics show that three sea-breeze days where O 3 observations recorded hourly concentrations >70 ppb have both efficient net chemical O 3 production in the boundary layer (>10 ppb/hr) and rapid O 3 convergence in the near-surface convergence zone (>20 ppb/hr). During sea breezes, interactions between photochemistry, the convergence zone inland penetration, and urban NO x titration effects, contribute to strong heterogeneity and high O 3 inland that is not captured by the current monitoring network. We discuss monitoring needs and model applications for the sea breeze scenarios, with broad implications for air quality monitoring in coastal urban environments. High resolution WRF-Chem modeling reproduces observed spatiotemporal variability of NO 2 and O 3 during sea breezes in the Greater Boston area Model results suggest high O 3 pollution and NO 2 column spatial variability associated with sea breezes is n

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Improving the performance of AgCdF₃-based perovskite solar cells using machine learning-driven adjustment of active layer and charge transport materials with SCAPS-1D

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Inorganic Chemistry Communications 2025年 179卷

作者： Ghosh, Avijit Zishan, Al Shahriar Moumita, Mahbuba Kumar, Yedluri Anil Roy, Anup Kumar Islam, Siful Ahmed, Shahan Anonto, Hasanur Zaman Happy, Asma Tabassum Shameem Ahsan, Md Alrafai, H.A. Hassan, Abeer A. Department of Electrical and Electronic Engineering Begum Rokeya University Rangpur 5400 Bangladesh Department of Electrical and Electronics Engineering American International University – Bangladesh 408/1 Kuratoli Road Kuril Dhaka 1229 Bangladesh Department of Mathematics Lamar University Beaumont 77705 TX United States Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai 602105 India Phillip M. Drayer Department of Electrical and Computer Engineering Lamar University TX United States Master of Science in Management Information Systems College of Business Lamar University TX United States Master of Arts in Social Research & Data Analysis Montclair State University NJ United States Department of Industrial and Systems Engineering Lamar University Beaumont 77710 TX United States Department of Chemistry Faculty of Science King Khalid University PO Box 9004 Abha 61413 Saudi Arabia

This study investigates the possibility of combining inorganic substances—which act as absorbers, HTLs) in order to produce stable, effective PSCs. A ZnSe ETL, HTLs (MoS2, MoTe2, and CuI), and an AgCdF3 perovskite ab... 详细信息

This study investigates the possibility of combining inorganic substances—which act as absorbers, HTLs) in order to produce stable, effective PSCs. A ZnSe ETL, HTLs (MoS₂, MoTe₂, and CuI), and an AgCdF₃ perovskite absorber, comprise the suggested architecture for this study. This study examines the impact of metal contacts, doping density, interface defect densities, absorber thickness, HTL and ETL layers, and defect density on the output of a solar device using the SCAPS-1D model. The investigation of how temperature impacts the performance of the proposed PSC is another important aspect of the study. By integrating the MoS₂/MoTe₂/CuI layers as an HTL with the studied structure of Al/FTO/ZnSe/AgCdF₃/HTL/Ni, the V_OC climbed to 0.834/0.910/0.969 V, the J_SC to 42.122/42.862/42.885 mA cm⁻², the PCE to 30.31/34.05/36.06 %, and the FF to 86.21/87.23/86.69 %. A machine learning model was created to forecast the solar cells’ performance metrics. The model precisely evaluates the importance of each parameter by utilizing SHAP values, providing important insights into their contributions. With an accuracy rate of around 83.75 %, machine learning predicted the performance matrix of the optimal solar cell under investigation. An affordable AgCdF₃ solar cell may be developed as a result of this study's significant findings and practical design. © 2025 Elsevier B.V.

关键词： AgCdF3 HTLs Machine learning Perovskite ZnSe ETL

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Search for the doubly charmed baryon Ω_(cc)^(+)

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science China(Physics,Mechanics & Astronomy) 2021年第10期64卷 2-13页

作者： LHCb Collaboration Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Center for High Energy Physics Tsinghua University Beijing 100084 China Institute Of High Energy Physics (IHEP) Beijing 100039 China School of Physics State Key Laboratory of Nuclear Physics and Technology Peking University Beijing 100091 China University of Chinese Academy of Sciences Beijing 100086 China Institute of Particle Physics Central China Normal University Wuhan 430079 China CNRS IN2P3-LAPP Univ. Savoie Mont Blanc Annecy France CNRS/IN2P3 LPC Université Clermont Auvergne Clermont-Ferrand France CNRS/IN2P3 CPPM Aix Marseille Univ Marseille France CNRS/IN2P3 IJCLab Université Paris-Saclay Orsay France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité CNRS/IN2P3 Paris France I. Physikalisches Institut RWTH Aachen University Aachen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Max-Planck-Institut für Kernphysik (MPIK) Heidelberg Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany School of Physics University College Dublin Dublin Ireland INFN Sezione di Bari Bari Italy INFN Sezione di Bologna Bologna Italy INFN Sezione di Ferrara Ferrara Italy INFN Sezione di Firenze Firenze Italy INFN Laboratori Nazionali di Frascati Frascati Italy INFN Sezione di Genova Genova Italy INFN Sezione di Milano Milano Italy INFN Sezione di Milano-Bicocca Milano Italy INFN Sezione di Cagliari Monserrato Italy Universita degli Studi di Padova Universita e INFN Padova Padova Italy INFN Sezione di Pisa Pisa Italy INFN Sezione di Roma La Sapienza Roma Italy INFN Sezione di Roma Tor Vergata Roma Italy Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Nikhef National Institute for Subatomic Physics and VU Unive

A search for the doubly charmed baryon ?cc+ with the decay mode c Ω_(cc)^(+)→ Ξc+K-π+ is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the LHCb experiment from 2016 to 2018, corresponding to an integrated luminosity of 5.4 fb-1. No significant signal is observed within the invariant mass range of 3.6 to 4.0 GeV/c2. Upper limits are set on the ratio R of the production cross-section times the total branching fraction of the Ω_(cc)^(+)→ Ξc+K-π+ decay with respect to the Ξcc++→ Λc+K-π+π+ decay. Upper limits at 95% credibility level for R in the range 0.005 to 0.11 are obtained for diferent hypotheses on the ?cc+ mass and lifetime in the rapidity range from 2.0 to 4.5 and transverse momentum range from 4 to 15 GeV/c.

关键词： charmed baryons limits on production of particles charmed quarks experimental tests

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Cardiac segmentation on late gadolinium enhancement MRI: A benchmark study from multi-sequence cardiac MR segmentation challenge

arXiv

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arXiv 2020年

作者： Zhuang, Xiahai Xu, Jiahang Luo, Xinzhe Chen, Chen Ouyang, Cheng Rueckert, Daniel Campello, Victor M. Lekadir, Karim Vesal, Sulaiman RaviKumar, Nishant Liu, Yashu Luo, Gongning Chen, Jingkun Li, Hongwei Ly, Buntheng Sermesant, Maxime Roth, Holger Zhu, Wentao Wang, Jiexiang Ding, Xinghao Wang, Xinyue Yang, Sen Li, Lei School of Data Science Fudan University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Biomedical Image Analysis Group Imperial College London London United Kingdom Department Mathematics & Computer Science Universitat de Barcelona Barcelona Spain Friedrich-Alexander-Universität Erlangen-Nürnberg Germany School of Computer Science and Technology Harbin Institute of Technology Harbin China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Department of Informatics Technical University of Munich Germany INRIA Université Côte d’Azur Sophia Antipolis France NVIDIA Bethesda United States School of Informatics Xiamen University Xiamen China College of Electrical Engineering Sichuan University Chengdu China Tencent AI Lab Shenzhen China

Accurate computing, analysis and modeling of the ventricles and myocardium from medical images are important, especially in the diagnosis and treatment management for patients suffering from myocardial infarction (MI). Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) provides an important protocol to visualize MI. However, automated segmentation of LGE CMR is still challenging, due to the indistinguishable boundaries, heterogeneous intensity distribution and complex enhancement patterns of pathological myocardium from LGE CMR. Furthermore, compared with the other sequences LGE CMR images with gold standard labels are particularly limited, which represents another obstacle for developing novel algorithms for automatic segmentation of LGE CMR. This paper presents the selective results from the Multi-Sequence Cardiac MR (MS-CMR) Segmentation challenge, in conjunction with MICCAI 2019. The challenge offered a data set of paired MS-CMR images, including auxiliary CMR sequences as well as LGE CMR, from 45 patients who underwent cardiomyopathy. It was aimed to develop new algorithms, as well as benchmark existing ones for LGE CMR segmentation and compare them objectively. In addition, the paired MS-CMR images could enable algorithms to combine the complementary information from the other sequences for the segmentation of LGE CMR. Nine representative works were selected for evaluation and comparisons, among which three methods are unsupervised methods and the other six are supervised. The results showed that the average performance of the nine methods was comparable to the inter-observer variations. Particularly, the top-ranking algorithms from both the supervised and unsupervised methods could generate reliable and robust segmentation results. The success of these methods was mainly attributed to the inclusion of the auxiliary sequences from the MS-CMR images, which provide important label information for the training of deep neural networks. The challeng

关键词： Magnetic resonance

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Search for the doubly charmed baryon ?cc+

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science China(Physics,Mechanics & Astronomy) 2021年第10期Mechanics & Astronomy) .卷 6-17页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti I. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bj?rn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles P. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Clif J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J. Cogan E. Cogneras L. Nikhef National Institute for Subatomic Physics Physik-Institut Universit?t Zürich Oliver Lodge Laboratory University of Liverpool Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela H.H. Wills Physics Laboratory University of Bristol Université Clermont Auvergne University of Michigan Ann Arbor United States INFN Sezione di Milano University of Cincinnati Fakult?t Physik Technische Universit?t Dortmund European Organization for Nuclear Research (CERN) School of Physics and Astronomy University of Glasgow ICCUB Universitat de Barcelona Department of Physics and Astronomy University of Manchester Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Cavendish Laboratory University of Cambridge Universidade Federal do Rio de Janeiro (UFRJ) Université Paris-Saclay INFN Sezione di Firenze INFN Sezione di Ferrara Physikalisches Institut Ruprecht-Karls-Universit?t Heidelberg Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Syracuse University Yandex School of Data Analysis Aix Marseille Univ Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Department of Physics University of Warwick Centro Brasileiro de Pesquisas Físicas (CBPF) Imperial College London INFN Sezione di Genova National University of Science and Technology “MISIS” I. Physikalisches Institut RWTH Aachen University INFN Sezione di Pisa INFN Sezione di Cagliari Institute of Nuclear Physics Moscow State University (SINP MSU) Institute of Theoretical and Experimental Physics NRC Kurchatov Institute (ITEP NRC KI) INFN Laboratori Nazionali di Frascati LPNHE Sorbonne Université Paris Diderot Sorbonne Paris Cité Universita degli Studi di Padova Universita e INFN Henryk Niewodniczanski Institute of Nuclear Physics Polish Academy of Sciences School of Physics and Technology Wuhan University University of Birmingham Università di Modena e Reggio Emilia Department of Physics U

A search for the doubly charmed baryon ?cc+with the decay mode ?cc+→Ξc+K-π+is performed using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the LHCb experiment from 2016 to 2018, corresponding to an integrated luminosity of 5.4 fb-1. No significant signal is observed within the invariant mass range of 3.6 to 4.0 GeV/c2. Upper limits are set on the ratio R of the production cross-section times the total branching fraction of the ?cc+→Ξc+K-π+decay with respect to the Ξcc++→Λc+K-π+π+decay. Upper limits at 95% credibility level for R in the range 0.005 to 0.11 are obtained for diferent hypotheses on the ?cc+mass and lifetime in the rapidity range from 2.0 to 4.5 and transverse momentum range from 4 to 15 GeV/c.

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Correction: Micronutrient intake and telomere length: findings from the UK Biobank

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European journal of nutrition 2024年第1期64卷 53页

作者： Marianna Spinou Androniki Naska Christopher P Nelson Veryan Codd Nilesh J Samani Vasiliki Bountziouka Department of Hygiene Epidemiology and Medical Statistics School of Medicine National and Kapodistrian University of Athens Athens Greece. Department of Cardiovascular Sciences University of Leicester Leicester UK. NIHR Leicester Biomedical Research Centre Glenfield Hospital Leicester UK. Department of Cardiovascular Sciences University of Leicester Leicester UK. vboun@aegean.gr. NIHR Leicester Biomedical Research Centre Glenfield Hospital Leicester UK. vboun@aegean.gr. Computer Simulation Genomics and Data Analysis Laboratory Department of Food Science and Nutrition School of the Environment University of the Aegean Ierou Lochou 10 & Makrygianni Lemnos 81400 Greece. vboun@aegean.gr. Population Policy and Practice Research and Teaching Department GOS Institute of child health UCL London UK. vboun@aegean.gr.

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From FAIR to CURE: Guidelines for Computational Models of Biological Systems

arXiv

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arXiv 2025年

作者： Sauro, Herbert M. Agmon, Eran Blinov, Michael L. Gennari, John H. Hellerstein, Joe Heydarabadipour, Adel Hunter, Peter Jardine, Bartholomew E. May, Elebeoba Nickerson, David P. Smith, Lucian P. Bader, Gary D. Bergmann, Frank Boyle, Patrick M. Dräger, Andreas Faeder, James R. Feng, Song Freire, Juliana Fröhlich, Fabian Glazier, James A. Gorochowski, Thomas E. Helikar, Tomas Hoops, Stefan Imoukhuede, Princess Keating, Sarah M. Konig, Matthias Laubenbacher, Reinhard Loew, Leslie M. Lopez, Carlos F. Lytton, William W. McCulloch, Andrew Mendes, Pedro Myers, Chris J. Myers, Jerry G. Mulugeta, Lealem Niarakis, Anna van Niekerk, David D. Olivier, Brett G. Patrie, Alexander A. Quardokus, Ellen M. Radde, Nicole Rohwer, Johann M. Sahle, Sven Schaff, James C. Sego, T.J. Shin, Janis Snoep, Jacky L. Vadigepalli, Rajanikanth Wiley, H. Steve Waltemath, Dagmar Moraru, Ion Department of Bioengineering University of Washington SeattleWA98195-5061 United States Intelligent Systems Engineering and Biocomplexity Institute Indiana University Street BloomingtonIN47408 United States Center for Cardiovascular Biology University of Washington SeattleWA98195-5061 United States eScience Institute University of Washington SeattleWA98195-5061 United States Institute for Stem Cell and Regenerative Medicine University of Washington SeattleWA98195-5061 United States School of Biological Sciences University of Bristol 24 Tyndall Avenue BristolBS8 1TQ United Kingdom Departments of Physiology & Pharmacology Neurology Downstate Health Science University BrooklynNY11203 United States Department of Neurology Kings County Hospital BrooklynNY11203 United States NASA-John H. Glenn Research Center MS 110-3 21000 Brookpark Road ClevelandOH44135 United States Center for Cell Analysis and Modeling UConn Health 263 Farmington Avenue FarmingtonCT06030-6406 United States Amsterdam Institute for Life and Environment Vrije Universiteit Amsterdam De Boelelaan 1108 Amsterdam1081 HZ Netherlands Department of Pathology and Genomic Medicine Thomas Jefferson University 1020 Locust St PhiladelphiaPA19107 United States Biological Sciences Division Pacific Northwest National Laboratory 902 Battelle Blvd RichlandWA99354 United States Auckland Bioengineering Institute University of Auckland Auckland1010 New Zealand Center of Integrative Biology University of Toulouse III-Paul Sabatier 165 Rue Marianne Grunberg-Manago Toulouse31400 France Lifeware Group Inria Building Alan Turing 1 Rue Honoré d’Estienne d’Orves Palaiseau91120 France Multiscale Modeling Group Altos Labs Redwood CityCA94065 United States partner site Tübingen Tübingen Germany Ottfried-Müller-Str. 37 Tübingen72076 Germany 06120 Germany Department of Computer Science Center for Data Science New York University New YorkNY11201 United States Department of Bi

Guidelines for managing scientific data have been established under the FAIR principles requiring that data be Findable, Accessible, Interoperable, and Reusable. In many scientific disciplines, especially computational biology, both data and models are key to progress. For this reason, and recognizing that such models are a very special type of "data", we argue that computational models, especially mechanistic models prevalent in medicine, physiology and systems biology, deserve a complementary set of guidelines. We propose the CURE principles, emphasizing that models should be Credible, Understandable, Reproducible, and Extensible. We delve into each principle, discussing verification, validation, and uncertainty quantification for model credibility;the clarity of model descriptions and annotations for understandability;adherence to standards and open science practices for reproducibility;and the use of open standards and modular code for extensibility and reuse. We outline recommended and baseline requirements for each aspect of CURE, aiming to enhance the impact and trustworthiness of computational models, particularly in biomedical applications where credibility is paramount. Our perspective underscores the need for a more disciplined approach to modeling, aligning with emerging trends such as Digital Twins and emphasizing the importance of data and modeling standards for interoperability and reuse. Finally, we emphasize that given the non-trivial effort required to implement the guidelines, the community moves to automate as many of the guidelines as possible. © 2025, CC BY.

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Global Riverine Export of Dissolved Lignin Constrained by Hydrology, Geomorphology, and Land-Cover

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Global Biogeochemical Cycles 2023年第4期37卷 e2022GB007607-e2022GB007607页

作者： Hongyan Bao Ying Wu Xiaoqian Zhan Xiaona Wang Robert G. M. Spencer Peter J. Hernes Xiaojuan Feng Li-Chin Lee Jr-Chuan Huang Jingjing Zhang Hongwei Zhao Shuh-Ji Kao Jing Zhang State Key Laboratory of Marine Environmental Science College of Ocean and Earth Sciences Xiamen University Xiamen China H. Bao and Y. Wu Contribution: Conceptualization Formal analysis Data curation Writing - original draft Writing - review & editing Funding acquisition State Key Laboratory of Estuarine and Coastal Research East China Normal University Shanghai China Contribution: Conceptualization Writing - review & editing Funding acquisition Contribution: Data curation Visualization Contribution: Data curation Department of Earth Ocean and Atmospheric Science Florida State University Tallahassee FL USA Contribution: Writing - review & editing Department of Land Air and Water Resources University of California Davis CA USA State Key Laboratory of Vegetation and Environmental Change Institute of Botany Chinese Academy of Sciences Beijing China Department of Geography National Taiwan University Taipei Taiwan State Key Laboratory of Marine Resource Utilization in South China Sea Hainan University Haikou China Center for Eco-Environment Restoration of Hainan Province College of Environment and Ecology Hainan University Haikou China Contribution: Writing - review & editing Funding acquisition Contribution: Conceptualization Writing - review & editing

The land-to-ocean export of terrestrial dissolved organic matter (tDOM) links the two largest organic carbon (OC) pools on Earth and is changing due to anthropogenic activity and climate change. Lignin phenols are often utilized as diagnostic markers for tDOM in aquatic systems, but information on the global dissolved lignin flux is still uncertain as linkages between future changes in export and global changes are poorly constrained. Thirty-two new measurements from 15 Chinese rivers and 548 measurements collected from 97 global rivers were combined to analyze its distributions, fluxes, and potential controls. Dissolved lignin concentrations (in μg L−1) varied by more than two orders of magnitude (0.7–138 μg L−1) and were positively correlated with dissolved OC (DOC) concentrations globally, suggesting coupled export of dissolved lignin and DOC. The carbon-normalized lignin yields (in mg g OC−1) varied by an order of magnitude (<1–30 mg (g OC)−1) and was significantly lower in the Arctic than in temperate and tropical rivers. Correlation analyses indicated that the dissolved lignin flux (FLignin) was mainly affected by water discharge and mean basin slope, while the area-normalized yield of dissolved lignin as well as discharge-weighted lignin concentration strongly and positively correlated with forest coverage. We, for the first time, estimated global FLignin ranges from 0.58 to 1.2 Tg yr−1 by using different approaches. Our synthesis reveals that future changes in land-cover that is driven by climate change as well as other human activities would impose a significant influence on the land-to-ocean export of tDOM.

关键词： dissolved lignin land-cover global flux terrestrial organic matter

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Target localization intervention and prognosis evaluation for an individual with mild cognitive impairment

Brain‐X

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Brain‐X 2023年第3期1卷

作者： Weiping Wang Haiyan Zhao Chang He Yuanbo Cui Zhen Wang Alexander Hramov Ping Luan Xiong Luo Jipeng Ouyang Kurths Jürgen School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan Guangdong China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Contribution: Writing - review & editing Department of Neurology Peking University Third Hospital Beijing China Contribution: Resources Zhen Wang The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi 710072 China. Contribution: Writing - original draft The 6th Research Institute of China Electronics Corporation Beijing China The Center for Optical Imagery Analysis and Learning and School of Mechanical Engineering Northwestern Polytechnical University Xi'an Shaanxi China Chang He School of Computer and Communication Engineering University of Science and Technology Beijing Beijing 100083 China. Contribution: Investigation Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Saratov State Medical University Saratov Russia Contribution: Data curation Guangdong Second Provincial General Hospital & Health Science Center Shenzhen Guangdong China Department of Neurology Shunde Hospital Southern Medical University Foshan Guangdong China Institute of Physics Humboldt-University Berlin Germany Potsdam Institute for Climate Impact Research Potsdam Germany

Currently, no specific treatments are available for Alzheimer's disease (AD). Mild cognitive impairment (MCI), the preclinical stage of AD, has a high possibility of reversing symptoms through neural regulation. A state dynamics model for single brain regions was developed to simulate blood oxygen level-dependent signals in a patient with early mild cognitive impairment. Subsequently, the analysis of functional connections was used to comprehensively consider multiple complex network centralities to locate the intervention targets, and a multiple brain region collaborative control scheme was designed. Finally, the reliability and effectiveness of the intervention were verified at the brain region and subnetwork levels. This technique provides a basis for future clinical diagnosis and treatment of AD and MCI.

关键词： adaptive pinning control Alzheimer's disease BOLD signals computational modeling Sub_network

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computer-Aided Discovery of Potent Broad-Spectrum Vaccine Adjuvants

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Angewandte Chemie 2023年第18期135卷 e202301059-e202301059页

作者： Juan Ma Shenqing Wang Chuanfang Zhao Xiliang Yan Quanzhong Ren Zheng Dong Jiahuang Qiu Yin Liu Qing'e Shan Ming Xu Bing Yan Sijin Liu State Key Laboratory of Environmental Chemistry and Ecotoxicology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 P. R. China School of Environmental Sciences University of Chinese Academy of Sciences Beijing 100049 P. R. China Contribution: Data curation (lead) Formal analysis (lead) Funding acquisition (supporting) Investigation (lead) Methodology (equal) Visualization (equal) Writing - original draft (lead) Institute of Environmental Research at Greater Bays Key Laboratory for Water Quality and Conservation of the Pearl River Delta Ministry of Education Guangzhou University Guangzhou 510006 P. R. China Contribution: Conceptualization (equal) Data curation (equal) Formal analysis (supporting) Investigation (supporting) Methodology (lead) School of Chemical Sciences University of Chinese Academy of Sciences Beijing 100049 P. R. China Contribution: Methodology (supporting) Software (lead) Visualization (lead) Contribution: Methodology (supporting) Software (lead) Visualization (supporting) Department of toxicology and sanitary chemistry School of public health Capital Medical University Beijing 100069 P. R. China Contribution: Data curation (supporting) Investigation (supporting) School of Environment Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou 330106 P. R. China Contribution: Formal analysis (supporting) Methodology (supporting) Medical Science and Technology Innovation Center Shandong First Medical University & Shandong Academy of Medical Sciences Jinan Shandong 250117 P. R. China Contribution: Investigation (supporting) Contribution: Supervision (supporting) Contribution: Conceptualization (equal) Funding acquisition (supporting) Methodology (supporting) Project administration (equal) Writing - review & editing (equal) Contribution: Conceptualization (equal) Funding acquisition (lead) Project administration (lead) Supervision (lead) Writing - review & editing (lead)

Adjuvants stimulate the immune system to vigorously respond to a vaccine. While current adjuvants such as aluminum salts and oil-in-water emulsions have been used for decades, they do not generate broad and long-lasting responses in many vaccines. Consequently, more potent adjuvants are needed. Here, using computer-aided molecule design and machine learning, we discovered 2 new, broad-spectrum adjuvants that can boost vaccine responses. Our library containing 46 toll-like receptor (TLR)-targeting agonist ligands were assembled on Au nanoparticles. Comprehensive in vitro , ex vivo and in vivo studies showed both leads promoted dendritic cell activation via multiple TLRs and enhanced antigen presentation to T cells. When used together with tumor-specific antigens to immunize mice against B16-OVA melanoma and 4T1-PD1 breast cancer, both adjuvants unleashed strong immune responses that suppressed tumor growth and lung metastases. Our results show computer-aided design and screening can rapidly uncover potent adjuvants for tackling waning immunity in current vaccines.

关键词： Cancer Immunotherapy computer-Aided Design Dendritic Cell Nano Adjuvant Pattern Recognition Receptor

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