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Switchable Electrostatically Templated Polymerization

Angewandte Chemie 2022年第39期134卷

作者： Chendan Li Jose R. Magana Fabian Sobotta Junyou Wang Martien A. Cohen Stuart Bas G. P. van Ravensteijn Ilja K. Voets State Key Laboratory of Chemical Engineering and Shanghai Key Laboratory of Multiphase Materials Chemical Engineering East China University of Science and Technology 130 Meilong Road Shanghai 200237 P. R. China Institute for Complex Molecular Systems Department of Chemical Engineering and Chemistry Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands Current address: Grup d'Enginyeria de Materials (GEMAT) Institut Químic de Sarrià (IQS) Universitat Ramon Llull (URL) 08022 Barcelona Spain Current address: Department of Pharmaceutics Utrecht Institute for Pharmaceutical Sciences (UIPS) Faculty of Science Utrecht University P.O. Box 80082 3508 TB Utrecht The Netherlands

We report a switchable, templated polymerization system where the strength of the templating effect can be modulated by solution pH and/or ionic strength. The responsiveness to these cues is incorporated through a dendritic polyamidoamine-based template of which the charge density depends on pH. The dendrimers act as a template for the polymerization of an oppositely charged monomer, namely sodium styrene sulfonate. We show that the rate of polymerization and maximum achievable monomer conversion are directly related to the charge density of the template, and hence the environmental pH. The polymerization could effectively be switched “ON” and “OFF” on demand, by cycling between acidic and alkaline reaction environments. These findings break ground for a novel concept, namely harnessing co-assembly of a template and growing polymer chains with tunable association strength to create and control coupled polymerization and self-assembly pathways of (charged) macromolecular building blocks.

关键词： Complex Core Coacervate Micelles PIESA Polyelectrolytes RAFT Polymerization Templated Polymerizations

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Utilizing Cationic Vacancies and Spontaneous Polarization on Cathode to Enhance Zinc-Ion Storage and Inhibit Dendrite Growth in Zinc-Ion Batteries

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Angewandte Chemie 2023年第26期135卷

作者： Dr. Liqi Bai Zihan Hu Cheng Hu Songge Zhang Dr. Yiran Ying Yingge Zhang Lu Li Hanfang Zhang Dr. Nan Li Dr. Shanshan Shi Shuo Liu Dr. Lin Hao Tongyao Liu Prof. Hongwei Huang Prof. Haitao Huang Prof. Yihe Zhang Engineering Research Center of Ministry of Education for Geological Carbon Storage and Low Carbon Utilization of Resources Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid Wastes National Laboratory of Mineral Materials School of Material Sciences and Technology China University of Geosciences Beijing 100083 China Department of Applied Physics and Research Institute for Smart Energy The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong 999077 China Contribution: Writing - original draft (lead) Writing - review & editing (lead) Faculty of System Design and Intelligent Manufacturing Southern University of Science and Technology Nanshan District Shenzhen Guangdong 518055 China Songshan Lake Materials Laboratory Guangdong 523808 China School of Fashion and Textiles and Research Institute for Intelligent Wearable Systems The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong 999077 China

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Correction to: An empirical model for educational simulation of cervical dilation in first stage labor

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Advances in simulation (London, England) 2021年第1期6卷 34页

作者： Silvano R Gefferie Anouk W J Scholten Kim A E Wijlens M Luísa Ferreira Bastos M Beatrijs van der Hout-van der Jagt Hans Zwart Willem L van Meurs Technical Medicine University of Twente Drienerlolaan 5 7522 NB Enschede The Netherlands. Animals in Science Eurogroup for Animals Hertogstraat 29 1000 Brussels Belgium. Department of Signal Processing Systems Faculty of Electrical Engineering Eindhoven University of Technology PO Box 513 5600 MB Eindhoven The Netherlands. Department of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Drienerlolaan 5 7522 NB Enschede The Netherlands. Cardiovascular and Respiratory Physiology Group Faculty of Science and Technology University of Twente Drienerlolaan 5 7522 NB Enschede The Netherlands. vanmeurs@orange.fr.

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Titelbild: Switchable Electrostatically Templated Polymerization (Angew. Chem. 39/2022)

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Angewandte Chemie 2022年第39期134卷

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How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

arXiv

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arXiv 2023年

作者： Bosoni, Emanuele Beal, Louis Bercx, Marnik Blaha, Peter Blügel, Stefan Bröder, Jens Callsen, Martin Cottenier, Stefaan Degomme, Augustin Dikan, Vladimir Eimre, Kristjan Flage-Larsen, Espen Fornari, Marco Garcia, Alberto Genovese, Luigi Giantomassi, Matteo Huber, Sebastiaan P. Janssen, Henning Kastlunger, Georg Krack, Matthias Kresse, Georg Kühne, Thomas D. Lejaeghere, Kurt Madsen, Georg K.H. Marsman, Martijn Marzari, Nicola Michalicek, Gregor Mirhosseini, Hossein Müller, Tiziano M.A. Petretto, Guido Pickard, Chris J. Poncé, Samuel Rignanese, Gian-Marco Rubel, Oleg Ruh, Thomas Sluydts, Michael Vanpoucke, Danny E.P. Vijay, Sudarshan Wolloch, Michael Wortmann, Daniel Yakutovich, Aliaksandr V. Yu, Jusong Zadoks, Austin Zhu, Bonan Pizzi, Giovanni Institut de Ciència de Materials de Barcelona ICMAB-CSIC Campus UAB Bellaterra08193 Spain Univ. Grenoble-Alpes CEA IRIG-MEM-L Sim Grenoble38000 France LausanneCH-1015 Switzerland Institute for Materials Chemistry Technical University of Vienna Getreidemarkt 9/165-TC ViennaA-1060 Austria Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich JARA JülichD-52425 Germany Forschungszentrum Jülich JülichD-52425 Germany Department of Electromechanical Systems and Metal Engineering Ghent University Belgium Ghent University Belgium Institute of Atomic and Molecular Sciences Academia Sinica Taipei10617 Taiwan Norwegian EuroHPC Competence Center Sigma2 AS Norway SINTEF Industry Materials Physics Oslo Norway Department of Physics Science of Advanced Materials Program Central Michigan University Mount PleasantMI48859 United States Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium LausanneCH-1015 Switzerland Kongens Lyngby2800 Denmark VilligenCH-5232 Switzerland University of Vienna Faculty of Physics Center for Computational Materials Science Kolingasse 14-16 ViennaA-1090 Austria VASP Software GmbH Sensengasse 8 ViennaA-1090 Austria Helmholtz-Zentrum Dresden-Rossendorf GörlitzD-02826 Germany Center for Sustainable Systems Design University of Paderborn PaderbornD-33098 Germany OCAS NV ArcelorMittal Global R&D Gent Pres. J. F. Kennedylaan 3 ZelzateB-9060 Belgium Dynamics of Condensed Matter Theoretical Chemistry University of Paderborn PaderbornD-33098 Germany HPE HPC EMEA Research Lab BaselCH-4051 Switzerland Department of Materials Science & Metallurgy University of Cambridge 27 Charles Babbage Road CambridgeCB3 0FS United Kingdom Advanced Institute for Materials Research Tohoku University 2-1-1 Katahira Aoba Sendai980-8577 Japan Department of Materials Science and Engineering McMaster University 1280 Main Street West HamiltonONL8S 4L8 Canada ePot

In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). © 2023, CC BY.

关键词： Density functional theory

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The association for the advancement of artificial intelligence 2020 workshop program

The association for the advancement of artificial intelligen...

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作者： Bang, Grace Barash, Guy Bea, Ryan Cali, Jacques Castillo-Effen, Mauricio Chen, Xin Cynthia Chhaya, Niyati Dhoopar, Rohan Dumancic, Sebastijan Espinoza, Huáscar Farchi, Eitan Fioretto, Ferdinando Fuentetaja, Raquel Galley, Michel Geib, Christopher Hernández-Orallo, José Huang, Xiaowei Keren, Sarah Kim, Seokhwan Jaidka, Kokil Liu, Xiaomo Lu, Tyler Ma, Zhiqiang Mallah, Richard McDermid, John Michalowski, Martin Mirsky, Reuth Héigeartaigh, Seán Ó. Ramachandran, Deepak Segovia-Aguas, Javier Shaban-Nejad, Arash Shehory, Onn Shwartz, Vered Srivastava, Siddharth Talamadupula, Kartik Tang, Jian Zhang, Dell Zhang, Jian S&P Global. Western Digital University of Southampton United Kingdom Blue Prism Group PLC Lockheed Martin's Advanced Technology Laboratories ArlingtonVA United States University of Hong Kong Hong Kong Adobe Research Google Research Katholieke Universiteit Leuven Belgium Commissariat à ĺÉnergie Atomique France IBM Research Department of Electrical Engineering and Computer Science Syracuse University United States Universidad Carlos III de Madrid Spain Microsoft Research AI SIFT LLC Universitat Politècnica de València Spain Leverhulme Centre for the Future of Intelligence United Kingdom Department of Computer Science University of Liverpool United Kingdom National University of Singapore Singapore Harvard School of Engineering and Applied Sciences in the of Fields of Multiagent Environment Design and Goal Recognition Design Amazon Alexa AI Future of Life Institute United States University of York Assuring Autonomy International Program United Kingdom University of Minnesota School of Nursing MinneapolisMN United States University of Texas at Austin AustinTX United States Institut de Robòtica i Informàtica Industrial Spanish Council for Scientific Research Technical University of Catalonia Spain Oak Ridge National Laboratory Center for Biomedical Informatics Department of Pediatrics University of Tennessee Health Science Center United States Bar Ilan University Israel University of Washington SeattleWA United States Autonomous Agents and Intelligent Robots lab of the School of Computing Informatics Decision Systems Arizona State University United States DiDi AI Labs School of Industrial and System Engineering Georgia Institute of Technology United States University of London United Kingdom Microsoft Azure

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program included twenty-three workshops covering a wide range of topics in artificial intelligence. This report contains the required reports, which were submitted by most, but not all, of the workshop chairs. Copyright © 2020, Association for the Advancement of Artificial Intelligence. All rights reserved.

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Biomedical image analysis competitions: The state of current participation practice

arXiv

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arXiv 2022年

作者： Eisenmann, Matthias Reinke, Annika Weru, Vivienn Tizabi, Minu Dietlinde Isensee, Fabian Adler, Tim J. Godau, Patrick Cheplygina, Veronika Kozubek, Michal Maier-Hein, Klaus Jäger, Paul F. Kopp-Schneider, Annette Maier-Hein, Lena Ali, Sharib Gupta, Anubha Kybic, Jan Noble, Alison de Solórzano, Carlos Ortiz Pachade, Samiksha Petitjean, Caroline Sage, Daniel Wei, Donglai Wilden, Elizabeth Alapatt, Deepak Andrearczyk, Vincent Baid, Ujjwal Bakas, Spyridon Balu, Niranjan Bano, Sophia Bawa, Vivek Singh Bernal, Jorge Bodenstedt, Sebastian Casella, Alessandro Choi, Jinwook Commowick, Olivier Daum, Marie Depeursinge, Adrien Dorent, Reuben Egger, Jan Eichhorn, Hannah Engelhardt, Sandy Ganz, Melanie Girard, Gabriel Hansen, Lasse Heinrich, Mattias Heller, Nicholas Hering, Alessa Huaulmé, Arnaud Kim, Hyunjeong Li, Hongwei Bran Landman, Bennett Li, Jianning Ma, Jun Martel, Anne Martín-Isla, Carlos Menze, Bjoern Nwoye, Chinedu Innocent Oreiller, Valentin Padoy, Nicolas Pati, Sarthak Payette, Kelly Sudre, Carole van Wijnen, Kimberlin Vardazaryan, Armine Vercauteren, Tom Wagner, Martin Wang, Chuanbo Yap, Moi Hoon Yu, Zeyun Yuan, Chun Zenk, Maximilian Zia, Aneeq Zimmerer, David Bao, Rina Choi, Chanyeol Cohen, Andrew Dzyubachyk, Oleh Galdran, Adrian Gan, Tianyuan Guo, Tianqi Gupta, Pradyumna Haithami, Mahmood Ho, Edward Jang, Ikbeom Li, Zhili Luo, Zhengbo Lux, Filip Makrogiannis, Sokratis Müller, Dominik Oh, Young-Tack Pang, Subeen Pape, Constantin Polat, Gorkem Reed, Charlotte Rosalie Ryu, Kanghyun Scherr, Tim Thambawita, Vajira Wang, Haoyu Wang, Xinliang Xu, Kele Yeh, Hung Yeo, Doyeob Yuan, Yixuan Zeng, Yan Zhao, Xin Abbing, Julian Adam, Jannes Adluru, Nagesh Agethen, Niklas Ahmed, Salman Al Khalil, Yasmina Alenyà, Mireia Alhoniemi, Esa An, Chengyang Arega, Tewodros Weldebirhan Avisdris, Netanell Aydogan, Dogu Baran Bai, Yingbin Calisto, Maria Baldeon Basaran, Berke Doga Beetz, Marcel Bian, Hao Blansit, Kevin Bloch, Louise Bohnsack, Robert Bosticardo, Sara Breen, Jack Brudfors, Mikael Brüngel, Raphael Cabezas, Mariano Cacciola, Alb Heidelberg Division of Intelligent Medical Systems Germany Heidelberg HI Helmholtz Imaging Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Biostatistics Germany Heidelberg Division of Medical Image Computing Germany Heidelberg HI Applied Vision Lab Germany IT University of Copenhagen Copenhagen Denmark Centre for Biomedical Image Analysis Masaryk University Brno Czech Republic Heidelberg Interactive Machine Learning Group Germany Faculty of Mathematics and Computer Science and Medical Faculty Heidelberg University Heidelberg Germany NCT Heidelberg DKFZ University Hospital Heidelberg Germany School of Computing University of Leeds Leeds United Kingdom SBILab Department of ECE IIIT-Delhi India Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Institute of Biomedical Engineering University of Oxford United Kingdom Center for Applied Medical Research Pamplona Spain Shri Guru Gobind Singhji Institute of Engineering and Technology Maharashtra Nanded India Université de Rouen Normandie France Lausanne Switzerland School of Engineering and Applied Science Harvard University United States ICube University of Strasbourg CNRS France Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Techno-Pôle 3 Sierre3960 Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Rue du Bugnon 46 LausanneCH-1011 Switzerland University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington United States Wellcome EPSRC Centre for Interventional and Surgical Sciences University College London London United Kingdom Visual Artificial Intelligence Lab Oxford Brookes University Oxford United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Spain Dresden Fetscherstraße 74 PF 64 Dresden01307 Germany

The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known about the common practice as well as bottlenecks faced by the community in tackling the research questions posed. To shed light on the status quo of algorithm development in the specific field of biomedical imaging analysis, we designed an international survey that was issued to all participants of challenges conducted in conjunction with the IEEE ISBI 2021 and MICCAI 2021 conferences (80 competitions in total). The survey covered participants' expertise and working environments, their chosen strategies, as well as algorithm characteristics. A median of 72% challenge participants took part in the survey. According to our results, knowledge exchange was the primary incentive (70%) for participation, while the reception of prize money played only a minor role (16%). While a median of 80 working hours was spent on method development, a large portion of participants stated that they did not have enough time for method development (32%). 25% perceived the infrastructure to be a bottleneck. Overall, 94% of all solutions were deep learning-based. Of these, 84% were based on standard architectures. 43% of the respondents reported that the data samples (e.g., images) were too large to be processed at once. This was most commonly addressed by patch-based training (69%), downsampling (37%), and solving 3D analysis tasks as a series of 2D tasks. K-fold cross-validation on the training set was performed by only 37% of the participants and only 50% of the participants performed ensembling based on multiple identical models (61%) or heterogeneous models (39%). 48% of the respondents applied postprocessing steps. © 2022, CC BY.

关键词： Benchmarking

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Nanotrap-enabled quantification of KRAS-induced peptide hydroxylation in blood for cancer early detection

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Nano Research 2019年第6期12卷 1445-1452页

作者： Zaian Deng Zhen Zhao Bo Ning Jeffery Basilio Karen Mann Jie Fu Yajun Gu Yuanqing Ye Xifeng Wu Jia Fan Paul Chiao Tony Hu College of Health Science and Environmental Engineering Shenzhen Technology UniversityShenzhen 518118 China School of Biological and Health Systems Engineering Virginia G. Piper Biodesign Center for Personalized DiagnosticsThe Biodesign InstituteArizona State UniversityTempeArizona 85287USA Department of Nanomedicine Houston Methodist Research InstituteHoustonTexas 77030USA Pathology and Laboratory Medicine Weill Cornell Medical CollegeNew York New York 10065USA Center for Molecular Design and Biomimetics The Biodesign InstituteArizona State UniversityTempeArizona 85287USA Department of Laboratory Medicine Clinical CenterNational Institutes of HealthBethesdaMaryland 20892USA Department of Molecular Oncology H. Lee Moffitt Cancer CenterTampaFlorida 33612USA Department of Molecular and Cellular Oncology The University of Texas MD Anderson Cancer CenterHoustonTexas 77030USA School of Medical Laboratory Tianjin Medical UniversityTianjin 300203China Department of Epidemiology The University of Texas MD Anderson Cancer CenterHoustonTexas 77030USA

Circulating peptide is a potential source of biomarkers for cancer ***,the existence of large molecular weight proteins in plasma have a disastrous effect on circulating peptides isolating and ***,nanotrap fractionation following by mass spectrometry have been applied to quantify the levels of bradykinin (BK) and hydroxylated bradykinin (Hyp-BK) as a relative measure of KRAS-regulated prolyl-4-hydroxylase alpha-1 (P4HA1) which may serve as early diagnosis marker for pancreatic ductal adenocarcinoma (PDAC).We found that P4HA1 can be upregulated by KRASG12v,which is a PDAC driver mutation,using HPNE/KRAS and HPNE *** we revealed that P4HA1 is overexpressed in PDAC tumors,compared to normal and inflamed pancreatic *** interference revealed that P4HA1 activity was primarily responsible for Hyp-BK *** spectrometry analysis revealed that plasma Hyp-BK/BK ratio was higher in PDAC than pancreatitis patients and healthy controls,while the area under the receiver operating characteristic (ROC) curve (AUC) is 0.8209 (95%Cl,0.7269-0.9149).The Hyp-BK/BK association with PDAC was reproduced in another cohort,where this ratio was found to increase with advancing tumor *** novel findings paved the way for wider applications of Nanotrap coupled mass spectrometry as a powerful tool for revealing biosignatures from plasma.

关键词： nanotrap hydroxylation level bradykinin pancreatic ductal adenocarcinoma

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Integrating privacy enhancing techniques into blockchains using sidechains

arXiv

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arXiv 2019年

作者： Parizi, Reza M. Homayoun, Sajad Yazdinejad, Abbas Dehghantanha, Ali Choo, Kim-Kwang Raymond Department of Software Engineering and Game Development Kennesaw State University GA United States Department of Computer Engineering and Information Technology Shiraz University of Technology Shiraz Iran Faculty of Computer Engineering University of Isfahan School of Computer Science University of Guelph ON Canada Department of Information Systems and Cyber Security University of Texas San AntonioTX United States

Blockchains are turning into decentralized computing platforms and are getting worldwide recognition for their unique advantages. There is an emerging trend beyond payments that blockchains could enable a new breed of decentralized applications, and serve as the foundation for Internet's security infrastructure. The immutable nature of the blockchain makes it a winner on security and transparency;it is nearly inconceivable for ledgers to be altered in a way not instantly clear to every single user involved. However, most blockchains fall short in privacy aspects, particularly in data protection. Garlic Routing and Onion Routing are two of major Privacy Enhancing Techniques (PETs) which are popular for anonymization and security. Garlic Routing is a methodology using by I2P Anonymous Network to hide the identity of sender and receiver of data packets by bundling multiple messages into a layered encryption structure. The Onion Routing attempts to provide lowlatency Internet-based connections that resist traffic analysis, deanonymization attack, eavesdropping, and other attacks both by outsiders (e.g. Internet routers) and insiders (Onion Routing servers themselves). As there are a few controversies over the rate of resistance of these two techniques to privacy attacks, we propose a PET-Enabled Sidechain (PETES) as a new privacy enhancing technique by integrating Garlic Routing and Onion Routing into a Garlic Onion Routing (GOR) framework suitable to the structure of blockchains. The preliminary proposed GOR aims to improve the privacy of transactions in blockchains via PETES structure. Copyright © 2019, The Authors. All rights reserved.

关键词： Blockchain

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent systems and Computing 2020年 945卷 v-vii页

作者： Kulczycki, Piotr Kacprzyk, Janusz Kóczy, László T. Mesiar, Radko Wisniewski, Rafal Faculty of Physics and Applied Computer Science AGH University of Science and Technology Krakow Poland Systems Research Institute Polish Academy of Sciences Warsaw Poland Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Engineering Sciences Széchenyi István University Győr Hungary Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Electronic Systems Aalborg University Aalborg Denmark Faculty of Civil Engineering Slovak University of Technology Bratislava Slovakia

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