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science Bulletin 2019年第20期64卷 1532-1539页

作者： Xue Jia Chuantian Zuo Shuxia Tao Kuan Sun Yixin Zhao Shangfeng Yang Ming Cheng Mingkui Wang Yongbo Yuan Junliang Yang Feng Gao Guichuan Xing Zhanhua Wei Lijun Zhang Hin-Lap Yip Mingzhen Liu Qing Shen Longwei Yin Liyuan Han Shengzhong Liu Lianzhou Wang Jingshan Luo Hairen Tan Zhiwen Jin Liming Ding Center for Excellence in Nanoscience(CAS) Key Laboratory of Nanosystem and Hierarchical Fabrication(CAS)National Center for Nanoscience and TechnologyBeijing100190China University of Chinese Academy of Sciences Beijing100049China CSIRO Manufacturing Bag10Clayton SouthVictoria3169Australia Center for Computational Energy Research Department of Applied PhysicsEindhoven University of Technology5600MB EindhovenThe Netherlands MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems Chongqing UniversityChongqing400044China School of Environmental Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Department of Materials Science and Engineering University of Science and Technology of ChinaHefei230026China Institute for Energy Research Jiangsu UniversityZhenjiang212013China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and TechnologyWuhan430074China School of Physics and Electronics Central South UniversityChangsha410083China Department of Physics Chemistry and BiologyLinkoping UniversitySE-58183 LinkopingSweden Institute of Applied Physics and Materials Engineering University of MacaoMacao999078China College of Materials Science&Engineering Huaqiao UniversityXiamen361021China College of Materials Science and Engineering Jilin UniversityChangchun130012China State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou510640China Center for Applied Chemistry School of Materials and EnergyUniversity of Electronic Science and Technology of ChinaChengdu611731China Faculty of Informatics and Engineering The University of Electro-CommunicationsTokyo182-8585Japan School of Materials Science and Engineering Shandong UniversityJinan250061China State Key Laboratory of Metal Matrix Composites School of Materials Science and EngineeringShanghai Jiao Tong UniversityShanghai200240China Shaanxi Key Laboratory for Advanced Energy Devices Shaanxi Normal UniversityXi’an710119China

Owing to its nice performance, low cost, and simple solution-processing, organic-inorganic hybrid perovskite solar cell(PSC) becomes a promising candidate for next-generation high-efficiency solar *** power conversion efficiency(PCE) has boosted from 3.8% to 25.2% over the past ten years. Despite the rapid progress in PCE, the device stability is a key issue that impedes the commercialization of PSCs. Recently, all-inorganic cesium lead halide perovskites have attracted much attention due to their better stability compared with their organic-inorganic counterpart. In this progress report, we summarize the properties of CsPb(IxBr1-x)3 and their applications in solar cells. The current challenges and corresponding solutions are discussed. Finally, we share our perspectives on CsPb(IxBr1-x)3 solar cells and outline possible directions to further improve the device performance.

关键词： Perovskite solar cells Cesium lead halide perovskites Power conversion efficiency Stability

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Enhanced microwave absorption through structural and magnetic optimization in Sm-doped BiFeO3 composites

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Ceramics International 2025年

作者： Tho, P.T. Hung, L.X. Tran, N. Dat, T.Q. Binh, V.D. Yen, N.T.K. Ho, T.A. Luu, T.A. Hung, N.Q. Tuan, N.Q. Xuan, C.T.A. Laboratory of Magnetism and Magnetic Materials Science and Technology Advanced Institute Van Lang University Ho Chi Minh City70000 Viet Nam Faculty of Applied Technology School of Technology Van Lang University Ho Chi Minh City70000 Viet Nam Institute of Research and Development Duy Tan University Da Nang50000 Viet Nam Faculty of Natural Sciences Duy Tan University Da Nang50000 Viet Nam Department of Physics Le Quy Don Technical University Hanoi10000 Viet Nam Department of Mechanical Engineering Viet Tri University of Industry Viet Tri35100 Viet Nam Faculty of Engineering Physics and Nanotechnology VNU University of Engineering and Technology Vietnam National University 144 Xuan Thuy Cau Giay Hanoi10000 Viet Nam Center for Nuclear Technologies Vietnam Atomic Energy Institute Ho Chi Minh City70000 Viet Nam Institute of Fundamental and Applied Sciences Duy Tan University Ho Chi Minh City70000 Viet Nam The University of Danang - University of Science and Education Da Nang50000 Viet Nam Institute of Science and Technology TNU-University of Sciences Thai Nguyen24000 Viet Nam

Electromagnetic wave (EMW) pollution has recently emerged as one of the dangerous issues for human beings, leading to many attempts to fabricate high-efficiency EMW absorption materials. In this work, Sm-doped BiFeO3 (Bi1–xSmxFeO3) with high doping concentration has been fabricated, and its microwave absorption properties in relation to structural and magnetic properties have been studied. Bi1–xSmxFeO3 (BSF) samples transformed from the R3c phase to Pbam and Pnma phases, whereas the x = 0.10 sample exhibited only a single R3c phase. Magnetic hysteresis loops of BSF samples changed from a slim loop to a robust one as the modulated spiral spin structure was partially disrupted and dismantled in the rhombohedral and orthorhombic phases, respectively. The synergistic effects of structural transformation and variation of magnetic properties of BSF samples led to their outstanding microwave absorption capabilities, with all samples absorbing over 99.9 % of microwave energy. Impressively, the x = 0.16 sample could achieve a reflection loss (RL) value as high as −50.81 dB with a thin thickness of 1.9 mm. In addition, the samples with x = 0.10 and x = 0.20 exhibited substantial effective absorption bandwidth (EAB) values of 5.80 and 5.48 GHz, respectively, at a thickness of approximately 2.7 mm. These impressive RL and EAB values proved that BSF samples could be applied for practical applications in microwave absorption and shielding fields. © 2025 Elsevier Ltd and Techna Group S.r.l.

关键词： Impedance matching (electric)

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Corrigendum to “Submerged photocatalytic membrane reactor with suspended and immobilized N-doped TiO 2 under visible irradiation for diclofenac removal from wastewater” [Process Saf. Environ. Protect. 142 (2020) 229–237]

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Process Safety and Environmental Protection 2021年 152卷 730-731页

作者： Van-Huy Nguyen Quoc Ba Tran Xuan Cuong Nguyen Le Thanh Hai Thi Thanh Tam Ho Mohammadreza Shokouhimehr Dai-Viet N. Vo Su Shiung Lam Hai Phong Nguyen Cong Tin Hoang Quang Viet Ly Wanxi Peng Soo Young Kim Tra Van Tung Quyet Van Le Puangrat Kajitvichyanukul Department for Management of Science and Technology Development Ton Duc Thang University Ho Chi Minh City Vietnam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Vietnam Institute of Research and Development Duy Tan University Da Nang 550000 Vietnam Faculty of Environmental and Chemical Engineering Duy Tan University Da Nang 550000 Vietnam Institute for Environment and Resource Vietnam National University Ho Chi Minh City Ho Chi Minh 740500 Vietnam Department of Environment An Giang University An Giang Vietnam Department of Materials Science and Engineering Research Institute of Advanced Materials Seoul National University Seoul 08826 Republic of Korea Center of Excellence for Green Energy and Environmental Nanomaterials (CE@GrEEN) Nguyen Tat Thanh University 300A Nguyen Tat Thanh District 4 Ho Chi Minh City 755414 Vietnam Pyrolysis Technology Research Group Institute of Tropical Aquaculture and Fisheries (Akuatrop) & Institute of Tropical Biodiversity and Sustainable Development (Bio-D Tropika) Universiti Malaysia Terengganu 21030 Kuala Terengganu Terengganu Malaysia Department of Chemistry University of Sciences Hue University 77 Nguyen Hue Street Hue City Vietnam Faculty of Environmental Science University of Sciences Hue University 77 Nguyen Hue Street Hue City Vietnam State Key Laboratory of Separation Membrane and Membrane Processes National Center for International Joint Research on Membrane Science and Technology School of Materials Science and Engineering Tiangong University Tianjin 300387 China Henan Province Engineering Research Center for Biomass Value-added Products School of Forestry Henan Agricultural University Zhengzhou 450002 China Department of Materials Science and Engineering Korea University 145 Anam-ro Seongbuk-gu Seoul 02841 Republic of Korea Faculty of Environmental Engineering Department of Civil Engineering Naresuan University Phitsanulok 65000 Thailand Department of Environmental Engineering Faculty of E

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Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

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Computing and Software for Big science 2024年第1期8卷 1-36页

作者： Hayrapetyan, A. Tumasyan, A. Adam, W. Andrejkovic, J.W. Bergauer, T. Chatterjee, S. Damanakis, K. Dragicevic, M. Hussain, P.S. Jeitler, M. Krammer, N. Li, A. Liko, D. Mikulec, I. Schieck, J. Schöfbeck, R. Schwarz, D. Sonawane, M. Templ, S. Waltenberger, W. Wulz, C.-E. Darwish, M.R. Janssen, T. Mechelen, P. Van Bols, E.S. D’Hondt, J. Dansana, S. De Moor, A. Delcourt, M. Faham, H. El Lowette, S. Makarenko, I. Müller, D. Sahasransu, A.R. Tavernier, S. Tytgat, M. Onsem, G. P. Van Putte, S. Van Vannerom, D. Clerbaux, B. Das, A.K. De Lentdecker, G. Favart, L. Gianneios, P. Hohov, D. Jaramillo, J. Khalilzadeh, A. Khan, F.A. Lee, K. Mahdavikhorrami, M. Malara, A. Paredes, S. Thomas, L. Bemden, M. Vanden Velde, C. Vander Vanlaer, P. De Coen, M. Dobur, D. Hong, Y. Knolle, J. Lambrecht, L. Mestdach, G. Amarilo, K. Mota Rendón, C. Samalan, A. Skovpen, K. Bossche, N. Van Den Linden, J. van der Wezenbeek, L. Benecke, A. Bethani, A. Bruno, G. Caputo, C. Delaere, C. Donertas, I.S. Giammanco, A. Jaffel, K. Jain, Sh. Lemaitre, V. Lidrych, J. Mastrapasqua, P. Mondal, K. Tran, T.T. Wertz, S. Alves, G.A. Coelho, E. Hensel, C. De Oliveira, T. Menezes Moraes, A. Teles, P. Rebello Soeiro, M. Júnior, W. L. Aldá Pereira, M. Alves Gallo Filho, M. Barroso Ferreira Malbouisson, H. Brandao Carvalho, W. Chinellato, J. Da Costa, E.M. Da Silveira, G.G. De Jesus Damiao, D. De Souza, S. Fonseca De Souza, R. Gomes Martins, J. Herrera, C. Mora Mundim, L. Nogima, H. Pinheiro, J.P. Santoro, A. Sznajder, A. Thiel, M. Pereira, A. Vilela Bernardes, C.A. Calligaris, L. Tomei, T. R. Fernandez Perez Gregores, E.M. Mercadante, P.G. Novaes, S.F. Orzari, B. Padula, Sandra S. Aleksandrov, A. Antchev, G. Hadjiiska, R. Iaydjiev, P. Misheva, M. Shopova, M. Sultanov, G. Dimitrov, A. Litov, L. Pavlov, B. Petkov, P. Petrov, A. Shumka, E. Keshri, S. Thakur, S. Cheng, T. Javaid, T. Yuan, L. Hu, Z. Liu, J. Yi, K. Chen, G.M. Chen, H.S. Chen, M. Iemmi, F. Jiang, C.H. Kapoor, A. Liao, H. Liu, Z.-A. Sharma, R. Song, J.N. Tao, J. Wang, C. Wang, J. Wang, Z. Zhang, H. Agapitos Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia Faculty of Science University of Split Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Escuela Politecnica Nacional Quito Ecuador Universidad San Francisco de Quito Quito Ecuador Academy of Scientific Research and Technology of the Arab Republic of Egypt Egyptian Network of High Energy Physics Cairo Egypt Center for High Energy Physics (CHEP-FU) Fayoum University El-Fayoum Egypt National Institute of Chemical Physics and Biophysic

Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors. © The Author(s) 2024.

关键词： CMS Machine learning Offline and computing

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Cosmic-Ray Boron Flux Measured from 8.4 GeV/n to 3.8 TeV/n with the Calorimetric Electron Telescope on the International Space Station

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Physical Review Letters 2022年第25期129卷 251103-251103页

作者： O. Adriani Y. Akaike K. Asano Y. Asaoka E. Berti G. Bigongiari W. R. Binns M. Bongi P. Brogi A. Bruno J. H. Buckley N. Cannady G. Castellini C. Checchia M. L. Cherry G. Collazuol G. A. de Nolfo K. Ebisawa A. W. Ficklin H. Fuke S. Gonzi T. G. Guzik T. Hams K. Hibino M. Ichimura K. Ioka W. Ishizaki M. H. Israel K. Kasahara J. Kataoka R. Kataoka Y. Katayose C. Kato N. Kawanaka Y. Kawakubo K. Kobayashi K. Kohri H. S. Krawczynski J. F. Krizmanic P. Maestro P. S. Marrocchesi A. M. Messineo J. W. Mitchell S. Miyake A. A. Moiseev M. Mori N. Mori H. M. Motz K. Munakata S. Nakahira J. Nishimura S. Okuno J. F. Ormes S. Ozawa L. Pacini P. Papini B. F. Rauch S. B. Ricciarini K. Sakai T. Sakamoto M. Sasaki Y. Shimizu A. Shiomi P. Spillantini F. Stolzi S. Sugita A. Sulaj M. Takita T. Tamura T. Terasawa S. Torii Y. Tsunesada Y. Uchihori E. Vannuccini J. P. Wefel K. Yamaoka S. Yanagita A. Yoshida K. Yoshida W. V. Zober Department of Physics Department of Physics University of Florence Via Sansone 1–50019 Sesto Fiorentino Italy INFN Sezione di Florence Via Sansone 1–50019 Sesto Fiorentino Italy Waseda Research Institute for Science and Engineering Waseda University 17 Kikuicho Shinjuku Tokyo 162-0044 Japan JEM Utilization Center Human Spaceflight Technology Directorate Japan Aerospace Exploration Agency 2-1-1 Sengen Tsukuba Ibaraki 305-8505 Japan Institute for Cosmic Ray Research The University of Tokyo 5-1-5 Kashiwa-no-Ha Kashiwa Chiba 277-8582 Japan Department of Physical Sciences Earth and Environment University of Siena via Roma 56 53100 Siena Italy INFN Sezione di Pisa Polo Fibonacci Largo B. Pontecorvo 3–56127 Pisa Italy Department of Physics and McDonnell Center for the Space Sciences Washington University One Brookings Drive St. Louis Missouri 63130-4899 USA Heliospheric Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA Center for Space Sciences and Technology University of Maryland Baltimore County 1000 Hilltop Circle Baltimore Maryland 21250 USA Astroparticle Physics Laboratory NASA/GSFC Greenbelt Maryland 20771 USA Center for Research and Exploration in Space Sciences and Technology NASA/GSFC Greenbelt Maryland 20771 USA Institute of Applied Physics (IFAC) National Research Council (CNR) Via Madonna del Piano 10 50019 Sesto Fiorentino Italy Department of Physics and Astronomy Louisiana State University 202 Nicholson Hall Baton Rouge Louisiana 70803 USA Department of Physics and Astronomy University of Padova Via Marzolo 8 35131 Padova Italy INFN Sezione di Padova Via Marzolo 8 35131 Padova Italy Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Sagamihara Kanagawa 252-5210 Japan Kanagawa University 3-27-1 Rokkakubashi Kanagawa Yokohama Kanagawa 221-8686 Japan Faculty of Science and Technology Graduate School of Science and Technology Hirosaki University 3 Bunkyo Hiros

We present the measurement of the energy dependence of the boron flux in cosmic rays and its ratio to the carbon flux in an energy interval from 8.4 GeV/n to 3.8 TeV/n based on the data collected by the Calorimetric Electron Telescope (CALET) during ∼6.4 yr of operation on the International Space Station. An update of the energy spectrum of carbon is also presented with an increase in statistics over our previous measurement. The observed boron flux shows a spectral hardening at the same transition energy E0∼200 GeV/n of the C spectrum, though B and C fluxes have different energy dependences. The spectral index of the B spectrum is found to be γ=−3.047±0.024 in the interval 25

关键词： Cosmic ray & astroparticle detectors Cosmic ray acceleration Cosmic ray composition & spectra Cosmic ray propagation Cosmic ray sources Cosmic rays & astroparticles

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Toward separation and purification of chlorogenic acid from Lonicerae Japonicae Flo (honeysuckle) using melamine–formaldehyde aerogel: A green and efficient approach

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Chemical Engineering Journal 2024年 500卷

作者： Yong Zhu Bingmin Wu Songyan Xia Guangzhen Zheng Juanjuan Cheng Song Huang Qingping Xiong Jing Chen Hailun Li Hajime Hirao Yisheng He Jihang Chen Shenzhen Key Laboratory of Steroid Drug Discovery and Development School of Medicine The Chinese University of Hong Kong Shenzhen Guangdong 518172 China Key Laboratory for Palygorskite Science and Applied Technology of Jiangsu Province Huaiyin Institute of Technology Huai’an Jiangsu 223003 China Shenzhen Futian Biomedical Innovation R&D Center The Chinese University of Hong Kong Shenzhen Guangdong 518000 China National Engineering Research Center for Modernization of Traditional Chinese Medicine Guangzhou University of Chinese Medicine Guangzhou Guangdong 510006 China Warshel Institute for Computational Biology School of Medicine The Chinese University of Hong Kong Shenzhen Guangdong 518172 China Department of Nephrology Affiliated Huai’an Hospital of Xuzhou Medical University Huai’an Jiangsu 223002 China

The separation and purification of chlorogenic acid (CA) from honeysuckle is a challenging yet significant task in the food industry. Traditional methods, such as precipitation and chromatography methods, often suffer from secondary pollution or low efficiency. This paper proposes a green and efficient adsorption method for separating CA from honeysuckle using melamine–formaldehyde aerogel (MFa) nanomaterial. The synthesis of MFa adsorbent with developed mesoporous material is crucial for achieving high efficiency. The optimal conditions for CA adsorption were determined to be an MFa dose of 0.03 g, a pH value of 3.72, and an adsorption temperature of 18.89 ℃. Under these conditions, a CA adsorption capacity of 151.84 mg/g and an adsorption ratio of 69.58 % were achieved, demonstrating the superior performance of the MFa method. Most notably, the purity of CA improved significantly from 10.50 % to 60.50 %, a marked enhancement improvement over traditional sorption resins. Additionally, the superior antioxidant effect of CA treated with the MFa method was confirmed at both the chemical assay and cytological levels. Affinity analysis and MD simulations revealed that CA adsorption is primarily driven by electrostatic interaction. This study not only addresses current limitations of honeysuckle but also broadens the application pontential of aerogel in food and medicine industries.

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Facile synthesis of boric acid-activated biochar from water hyacinth: Enhanced antibiotic adsorption and mechanistic insights

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Chemical Engineering science 2025年 316卷

作者： Van Dien Dang Duy Quang Dao Ha Huu Do Iqra Rabani Chi Van Nguyen Hai Bang Truong Faculty of Biology and Environment Ho Chi Minh City University of Industry and Trade 140 Le Trong Tan Tan Phu district Ho Chi Minh 700000 Vietnam Institute of Research and Development Duy Tan University Da Nang 550000 Vietnam School of Engineering and Technology Duy Tan University Da Nang 550000 Vietnam NTT Hi-Tech Institute Nguyen Tat Thanh University Ho Chi Minh City 700000 Vietnam Antwerp engineering photoelectrochemistry and sensing (A-PECS) University of Antwerp Groenenborgerlaan 171 2020 Antwerp Belgium Center for Innovative Materials and Architectures Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Vietnam Optical Materials Research Group Science and Technology Advanced Institute Van Lang University Ho Chi Minh City Vietnam Faculty of Applied Technology School of Technology Van Lang University Ho Chi Minh City Vietnam

The widespread antibiotic pollution in water poses serious environmental and health risks. This study synthesized boric acid-activated biochar from water hyacinth to enhance antibiotic adsorption. Using sonication and one-step activation pyrolysis, the optimized adsorbent (BBC-21-800) was produced with a 2:1 boric acid-to-biomass ratio at 800 °C, achieving a tetracycline adsorption capacity of 127.2 ± 1.6 mg g −1 . Boric acid activation increased surface area by 4.4 times (790 m 2 g −1 ), structural defects, and functional groups, enhancing adsorption efficiency. Isotherm and kinetic studies confirmed physisorption, with contributions from mass transfer and diffusion. Comprehensive computational modeling linked experimental results to non-covalent interactions, primarily hydrogen bonding and van der Waals forces. −BOH functional groups played a key role, while B-doped atoms had minimal impact. The process was spontaneous and exothermic. BBC-21-800 exhibited broad-spectrum antibiotic removal and extended exhaustion times in fixed-bed adsorption, demonstrating its potential for practical water treatment applications.

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In-Plane Magnetic Field Evaluation with 0.47-nm Resolution by Aberration-Corrected 1.2-MV Holography Electron Microscope

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Microscopy and Microanalysis 2019年第S2期25卷 54-55页

作者： Tanigaki, Toshiaki Akashi, Tetsuya Yoshida, Takaho Harada, Ken Ishizuka, Kazuo Ichimura, Masahiko Murakami, Yasukazu Mitsuishi, Kazutaka Tomioka, Yasuhide Shindo, Daisuke Yu, Xiuzhen Tokura, Yoshinori Shinada, Hiroyuki Research & Development Group Hitachi Ltd. Hatoyama Japan RIKEN Center for Emergent Matter Science (CEMS) Wako Japan HREM Research Inc. Matsukazedai Japan Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Fukuoka Japan National Institute for Materials Science Tsukuba Japan National Institute of Advanced Industrial Science and Technology (AIST) Tsukuba Japan Institute of Multidisciplinary Research for Advanced Materials Tohoku University Sendai Japan Department of Applied Physics The University of Tokyo Tokyo Japan

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The CMS Statistical Analysis and Combination Tool: Combine

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Computing and Software for Big science 2024年第1期8卷 1-45页

作者： Zhokin, A. Zhizhin, I. Zarubin, A. Yuldashev, B.S. Voytishin, N. Vorotnikov, G. Vorobyev, A. Volkov, P. Uzunian, A. Uvarov, L. Toropin, A. Tlisova, I. Teryaev, O. Terkulov, A. Tcherniaev, E. Sulimov, V. Sosnov, D. Smirnov, V. Slabospitskii, S. Skovpen, Y. Shulha, S. Shmatov, S. Shalaev, V. Savrin, V. Savina, M. Radchenko, O. Popov, V. Polikarpov, S. Perfilov, M. Perelygin, V. Palichik, V. Oreshkin, V. Obraztsov, S. Nikitenko, A. Murzin, V. Matveev, V. Malakhov, A. Makarenko, V. Lychkovskaya, N. Levchenko, P. Lanev, A. Krasnikov, N. Kozyrev, A. Korenkov, V. Konstantinov, D. Kodolova, O. Klyukhin, V. Kirsanov, M. Kirpichnikov, D. Kirakosyan, M. Kim, V. Karneyeu, A. Karjavine, V. Kachanov, V. Ivanov, Y. Gribushin, A. Gorbunov, I. Golutvin, I. Golubev, N. Golovtcov, V. Gninenko, S. Gavrilov, V. Gavrilov, G. Dudko, L. Dubinin, M. Druzhkin, D. Dimova, T. Dermenev, A. Chistov, R. Chekhovsky, V. Chadeeva, M. Bunichev, V. Budkouski, D. Borshch, V. Boos, E. Blinov, V. Babaev, A. Azarkin, M. Aushev, T. Andreev, Yu. Andreev, V. Alexakhin, V. Afanasiev, S. Warden, A. Vetens, W. Tsoi, H.F. Teague, D. Smith, W.H. Sharma, V. Shang, V. Savin, A. Pinna, D. Pétré, L. Parida, G. Mondal, S. Mohammadi, A. Mallampalli, A. Sreekala, J. Madhusudanan Loveless, R. Lanaro, A. Koraka, C.K. Herve, A. Herndon, M. He, H. Galloni, C. Everaerts, P. De Bruyn, I. Dasu, S. Bose, T. Black, K. Banerjee, S. Aravind, A. Karchin, P.E. Bhattacharya, S. Neu, C. Ledovskoy, A. Hirosky, R. Hakala, J. Cox, B. Cardwell, B. Viinikainen, J. Velkovska, J. Tuo, S. Sheldon, P. Romeo, F. Melo, A. Elayavalli, R. Kunnawalkam Johns, W. Gurrola, A. Greene, S. Chen, Y. Appelt, E. Volobouev, I. Peltola, T. Mankel, A. Lee, S.W. Lamichhane, K. Kazhykarim, Y. Hussain, A. Hegde, V. Gogate, N. Damgov, J. Akchurin, N. Safonov, A. Rathjens, D. Overton, D. Mueller, R. Luo, S. Kim, H. Kamon, T. Huang, T. Gilmore, J. Eusebi, R. Bouhali, O. Akhter, T. Ahmad, M. Aebi, D. Spanier, S. Nibigira, E. Lee, L. Karunarathna, N. Kanuganti, A.R. Holmes, T. Higginbotham, S. Fiorendi, S. Delannoy Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Universiteit Antwerpen Antwerpen Belgium Vrije Universiteit Brussel Brussel Belgium Université Libre de Bruxelles Bruxelles Belgium Ghent University Ghent Belgium Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Instituto De Alta Investigación Universidad de Tarapacá Casilla 7 D Arica Chile Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Guangdong Provincial Key Laboratory of Nuclear Science and Guangdong-Hong Kong Joint Laboratory of Quantum Matter South China Normal University Guangzhou China Sun Yat-Sen University Guangzhou China University of Science and Technology of China Hefei China Nanjing Normal University Nanjing China Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) Institute of Modern Physics Fudan University Shanghai China Zhejiang University Hangzhou Zhejiang China Universidad de Los Andes Bogota Venezuela Universidad de Antioquia Medellin Colombia Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture University of Split Split Croatia Faculty of Science University of Split Split Croatia Institute Rudjer Boskovic Zagreb Croatia University of Cyprus Nicosia Cyprus Charles University Prague Czech Republic Universidad San Francisco de Quito Quito Ecuador Egyptian Network of High Energy Physics Academy of Scientific Research and Technology of the Arab Republic of Egypt Cairo Egypt Center for High

This paper describes the Combine software package used for statistical analyses by the CMS Collaboration. The package, originally designed to perform searches for a Higgs boson and the combined analysis of those searches, has evolved to become the statistical analysis tool presently used in the majority of measurements and searches performed by the CMS Collaboration. It is not specific to the CMS experiment, and this paper is intended to serve as a reference for users outside of the CMS Collaboration, providing an outline of the most salient features and capabilities. Readers are provided with the possibility to run Combine and reproduce examples provided in this paper using a publicly available container image. Since the package is constantly evolving to meet the demands of ever-increasing data sets and analysis sophistication, this paper cannot cover all details of Combine. However, the online documentation referenced within this paper provides an up-to-date and complete user guide. © CERN, for the benefit of the CMS Collaboration 2024.

关键词： CMS Combine Higgs Higgs boson Statistics

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Why is the Winner the Best?

Why is the Winner the Best?

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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