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Quantum Yield Bias in Materials With Lower Absorptance

Physical Review Applied 2019年第2期12卷 024022-024022页

作者： Bart van Dam Benjamin Bruhn Ivo Kondapaneni Gejza Dohnal Alexander Wilkie Jaroslav Křivánek Jan Valenta Yvo D. Mudde Peter Schall Kateřina Dohnalová Institute of Physics University of Amsterdam Science Park 904 1098 XH Amsterdam Netherlands Faculty of Mathematics and Physics Computer Graphics Group KSVI Charles University Malostranské náměstí 25 Prague 1 CZ-11800 Czech Republic Faculty of Mechanical Engineering Czech Technical University in Prague Karlovo náměstí 13 121 35 Prague 2 Czech Republic Department of Chemical Physics and Optics Faculty of Mathematics and Physics Charles University Ke Karlovu 3 Prague 2 CZ-121 16 Czech Republic

Photoluminescence (PL) quantum yield (QY), which is defined as the ratio of emitted to absorbed photons, is the central quantity that characterizes light-emitting materials. It is an important parameter to assess the light efficiency of new materials, as well as identify novel photophysical mechanisms. While QY measurements are performed as standard in research and industry, accurate measurements are challenging. Here, we show that, besides known inaccuracies, PL QY measurements exhibit a surprising systematic bias. QY values are underestimated by a factor of two or more for samples with lower absorption, which can even lead to misinterpretation of results. We combine PL QY measurements of diluted Rhodamine 6G and two different semiconductor quantum dot solutions, via the standard integrating sphere method, with analytical modeling and ray-tracing simulations and find that, independent of the setup and luminescence mechanism, all measurements suffer from the same systematic underestimation of the QY. Through statistical analysis of the measured emitted and absorbed photon numbers, we uncover the origin of this underestimation in the asymmetry of the ratio distribution for low absorption, together with setup-specific features, such as signal offsets and nonlinearities. We suggest a robust calibration procedure to correct for this bias for precise evaluation of the QY in materials used for bioimaging, biosensing, and optoelectronic or photovoltaic devices.

关键词： Light propagation, transmission & absorption Metrology Optoelectronics Semiconductor quantum optics Optical spectroscopy Optical techniques Photoluminescence Photon counting

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The Atacama Cosmology Telescope: Semi-Analytic Covariance Matrices for the DR6 CMB Power Spectra

arXiv

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arXiv 2024年

作者： Atkins, Zachary Li, Zack Alonso, David Bond, J. Richard Calabrese, Erminia Duivenvoorden, Adriaan J. Dunkley, Jo Giardiello, Serena Hervías-Caimapo, Carlos Hill, J. Colin Jense, Hidde T. Kim, Joshua Niemack, Michael D. Page, Lyman Posta, Adrien La Louis, Thibaut Moodley, Kavilan Morris, Thomas W. Naess, Sigurd Sifón, Cristóbal Wollack, Edward J. Joseph Henry Laboratories of Physics Jadwin Hall Princeton University PrincetonNJ08544 United States Lawrence Berkeley National Laboratory 1 Cyclotron Road BerkeleyCA94720 United States Berkeley Center for Cosmological Physics University of California BerkeleyCA94720 United States Canadian Institute for Theoretical Astrophysics University of Toronto McLennan Labs TorontoONM5S 3H8 Canada Department of Physics University of Oxford Denys Wilkinson Building Keble Road OxfordOX1 3RH United Kingdom School of Physics and Astronomy Cardiff University The Parade Wales CardiffCF24 3AA United Kingdom Max-Planck-Institut für Astrophysik Karl-Schwarzschild-Str. 1 Garching85748 Germany Center for Computational Astrophysics Flatiron Institute New YorkNY10010 United States Department of Astrophysical Sciences Peyton Hall Princeton University PrincetonNJ08544 United States Instituto de Astrofísica Centro de Astro-Ingeniería Facultad de Física Pontificia Universidad Católica de Chile Av. Vicuña Mackenna 4860 Macul Santiago7820436 Chile Department of Physics Columbia University New YorkNY10027 United States Department of Physics and Astronomy University of Pennsylvania 209 South 33rd Street PhiladelphiaPA19104 United States Department of Physics Cornell University IthacaNY14853 United States Department of Astronomy Cornell University IthacaNY14853 United States Université Paris-Saclay CNRS IN2P3 IJCLab Orsay91405 France Astrophysics Research Centre University of KwaZulu-Natal Westville Campus Durban4041 South Africa School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Westville Campus Durban4041 South Africa Department of Physics Yale University New HavenCT06511 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Institute of Theoretical Astrophysics University of Oslo Norway Instituto de Física Pontificia Universidad Católica de Valparaíso

The Atacama Cosmology Telescope Data Release 6 (ACT DR6) power spectrum is expected to provide state-of-the-art cosmological constraints, with an associated need for precise error modeling. In this paper we design, and evaluate the performance of, an analytic covariance matrix prescription for the DR6 power spectrum that sufficiently accounts for the complicated ACT map properties. We use recent advances in the literature to handle sharp features in the signal and noise power spectra, and account for the effect of map-level anisotropies on the covariance matrix. In including inhomogeneous survey depth information, the resulting covariance matrix prescription is structurally similar to that used in the Planck Cosmic Microwave Background (CMB) analysis. We quantify the performance of our prescription using comparisons to Monte Carlo simulations, finding better than 3% agreement. This represents an improvement from a simpler, pre-existing prescription, which differs from simulations by ∼ 16%. We develop a new method to correct the analytic covariance matrix using simulations, after which both prescriptions achieve better than 1% agreement. This correction method outperforms a commonly used alternative, where the analytic correlation matrix is assumed to be accurate when correcting the covariance. Beyond its use for ACT, this framework should be applicable for future high resolution CMB experiments including the Simons Observatory (SO). Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology

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A Temporally and Spatially Explicit, Mechanistic Estimation of Ragweed Pollen Concentrations Across Europe

SSRN

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SSRN 2023年

作者： Makra, László Matyasovszky, István Tusnády, Gábor Ziska, Lewis H. Hess, Jeremy J. Nyúl, László G. Chapman, Daniel S. Coviello, Luca Gobbi, Andrea Jurman, Giuseppe Furlanello, Cesare Brunato, Mauro Damialis, Athanasios Charalampopoulos, Athanasios Müller-Schärer, Heinz Schneider, Norbert Szabó, Bence Sümeghy, Zoltán Páldy, Anna Magyar, Donát Bergmann, Karl-Christian Deák, Áron József Mikó, Edit Thibaudon, Michel Oliver, Gilles Albertini, Roberto Bonini, Maira Šikoparija, Branko Radišić, Predrag Mitrović Josipović, Mirjana Gehrig, Regula Severova, Elena Rodinkova, Victoria Palamarchuk, Olena Stjepanović, Barbara Ianovici, Nicoleta Berger, Uwe Kofol Seliger, Andreja Rybníček, Ondřej Myszkowska, Dorota Dąbrowska-Zapart, Katarzyna Majkowska-Wojciechowska, Barbara Weryszko-Chmielewska, Elzbieta Grewling, Lukasz Rapiejko, Piotr Malkiewicz, Malgorzata Šaulienė, Ingrida Shalaboda, Valentina Prykhodo, Olexander Maleeva, Anna Ščevková, Jana Bullock, James M. Institute of Economics and Rural Development Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Department of Meteorology Eötvös Loránd University P.O.B. 32 Budapest1518 Hungary Alfréd Rényi Institute of Mathematics P.O.B 127 Budapest1364 Hungary Mailman School of Public Health Columbia University New YorkNY10032 United States Department of Global Health University of Washington SeattleWA98105 United States Department of Image Processing and Computer Graphics University of Szeged P.O.B. 652 Szeged6701 Hungary Biological and Environmental Sciences Faculty of Natural Sciences University of Stirling Scotland StirlingFK9 4LA United Kingdom University of Trento Enogis s.r.l. Trento Italy Bruno Kessler Foundation Trento Italy HK3 Lab Orobix Life Srl Rovereto Bergamo Italy Department of Information Engineering and Computer Science University of Trento Trento Italy Terrestrial Ecology and Climate Change Department of Ecology School of Biology Aristotle University of Thessaloniki ThessalonikiGR-54124 Greece Departement of Biology Unit of Ecology and Evolution University of Fribourg FribourgCH-1700 Switzerland National Institute of Environmental Health Albert Flórián út 2-6 Budapest1097 Hungary Institute of Allergology Charité Hindenburgdamm 30 Berlin12203 Germany Institute of Animal Science and Wildlife Management Faculty of Agriculture University of Szeged Andrássy út 15 Hódmezővásárhely6800 Hungary Réseau National de Surveillance Aérobiologique 11 chemin de la Creuzille Le Plat du Pin Brussieu696905 France Laboratory of Hygiene and Aerobiology Department of Medicine and Surgery University of Parma U.O. Medicina Interna di Continuità Azienda Ospedaliero-Universitaria di Parma Via Gramsci 14 Parma43126 Italy Hygiene and Public Health Service via Spagliardi 19 Parabiago Milan20015 Italy BioSensе Institute Research Institute for Information Technologies in Biosystems University of Novi Sad Dr

Ongoing and future climate change driven expansion of aeroallergen-producing plant species comprise a major human health problem across Europe and elsewhere. There is an urgent need to produce accurate, temporally dynamic maps at the continental level, especially in the context of climate uncertainty. This study aimed to restore missing daily ragweed pollen data sets for Europe, to produce phenological maps of ragweed pollen, resulting in the most complete and detailed high-resolution ragweed pollen concentration maps to date. To achieve this, we developed two statistical procedures, a Gaussian method (GM) and deep learning (DL) for restoring missing daily ragweed pollen data sets, based on the plant’s reproductive and growth (phenological, pollen production and frost-related) characteristics. DL model performances were consistently better for estimating annual total pollen concentrations than those of the GM approach. These are the first published modeled maps using altitude correction and phenology to recover missing pollen information. We created a web page (http://***/), including daily ragweed pollen concentration data sets of the stations examined and their restored daily data, allowing one to upload newly measured or recovered daily data. Generation of these maps provides a means to track pollen impacts in the context of climatic shifts, identify geographical regions with high pollen exposure, determine areas of future vulnerability, apply spatially-explicit mitigation measures and prioritize management interventions. © 2023, The Authors. All rights reserved.

关键词： Climate change

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Skully an educational web application for the human skull

Skully an educational web application for the human skull

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Workshops on Image processing for the medicine, 2016

作者： Bertelshofer, Franziska Brehm, Oliver Fitzner, Paul Lammert, Jacqueline Paulsen, Friedrich Janka, Rolf Greiner, Günther Computer Graphics Group Friedrich-Alexander-University Erlangen-Nuremberg Germany Institute of Anatomy II Friedrich-Alexander-University Erlangen-Nuremberg Germany Institute of Radiology Friedrich-Alexander-University Erlangen-Nuremberg Germany

ISBN: (纸本)9783662494646

One fundamental topic in anatomy is the structure of the human skull. Common sources for studying are books, atlases and other two dimensional material which makes it hard to optimally locate the separate parts of the human skull in three dimensional space and understand the relations between them. We developed a browser application visualizing three dimensional models of the human skull. The user can interact with those models, e.g. move them freely to gain insight in the three dimensional structure and position of the single bones, highlight separate bones or groups of them and view textual annotations. In a developer mode those annotations can be edited easily by anatomy experts or course tutors to contain all relevant information. Furthermore the application is platform independent, it can used on e.g. computers with different operating systems, tablets and mobile phones. © Springer-Verlag Berlin Heidelberg 2016.

关键词： Bone

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Measurement of the and cross-sections in pp collisions at TeV with the ATLAS detector

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The European Physical Journal C 2024年第1期84卷 1-34页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N. J. Abidi, S. H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. S. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Addepalli, S. V. Addison, M. J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A. A. Afik, Y. Agaras, M. N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W. S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Tamlihat, M. Ait Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T. P. A. Akimov, A. V. Akiyama, D. Akolkar, N. N. Khoury, K. Al Alberghi, G. L. Albert, J. Albicocco, P. Albouy, G. L. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H. M. J. Ali, S. Alibocus, S. W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B. M. M. Allen, J. F. Flores, C. A. Allendes Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Estevez, M. Alvarez Fernandez, A. Alvarez Cardoso, M. Alves Alviggi, M. G. Aly, M. Coutinho, Y. Amaral Ambler, A. Amelung, C. Amerl, M. Ames, C. G. Amidei, D. Dos Santos, S. P. Amor Amos, K. R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J. K. Andrean, S. Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Anthony, M. T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Pozo, J. A. Aparisi Aparo, M. A. Bella, L. Aperio Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A. T. H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N. A. Assahsah, J. Assamagan, K. Astalos, R. Atashi, S. Atkin, R. J. Atkinson, M. Atmani, H. Atmasiddha, P. A. Augsten, K. Auricchio, S. Auriol, A. D. Austrup, V. A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A. J. Bailey, V. R. Baines, J. T. Baines, L. Bakalis, C. Baker, O. K. Bakos, E. Gupta, D. Bakshi Balakrishnan, V. Balasubramanian, R. Baldin, E. M. Balek, P. Ballabene, E. Balli, F. Baltes, L. M. Balunas, CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton USA Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France Faculty of Physics and Applied Computer Science AGH University of Krakow Kraków Poland Department of Physics University of Toronto Toronto Canada Department of Physics Brandeis University Waltham USA School of Physics and Astronomy University of Manchester Manchester UK Department of Physics Northern Illinois University DeKalb USA Department of Physics Istanbul University Istanbul Türkiye Particle Physics Department Rutherford Appleton Laboratory Didcot UK Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz USA CERN Geneva Switzerland Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Affiliated with an international laboratory covered by a cooperation agreement with CERN Geneva Switzerland Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Department of Physics McGill University Montreal Canada Dep

The inclusive Higgs boson production cross-section is measured in the di-photon and the $$ZZ^* \rightarrow 4 \ell $$ decay channels using 31.4 and 29.0 fb $$^{-1}$$ of pp collision data respectively, collected with the ATLAS detector at a centre-of-mass energy of $$\sqrt{s}=13.6$$ $$\text {TeV}$$ . To reduce the model dependence, the measurement in each channel is restricted to a particle-level phase space that closely matches the channel’s detector-level kinematic selection, and it is corrected for detector effects. These measured fiducial cross-sections are $$\sigma _{\textrm{fid},\gamma \gamma } = $$ $$76^{+14}_{-13}$$ fb, and $$\sigma _{\textrm{fid},4 \ell } =$$ $$2.80\, \pm \, 0.74$$ fb, in agreement with the corresponding Standard Model predictions of $$67.6 \pm 3.7 $$ fb and $$3.67 \pm 0.19 $$ fb. Assuming Standard Model acceptances and branching fractions for the two channels, the fiducial measurements are extrapolated to the full phase space yielding total cross-sections of $$\sigma (pp \rightarrow H) = 67^{+12}_{-11}$$ pb and $$46 \pm 12$$ pb at 13.6 $$\text {TeV}$$ from the di-photon and $$ZZ^* \rightarrow 4 \ell $$ measurements respectively. The two measurements are combined into a total cross-section measurement of $$\sigma (pp \rightarrow H)= 58.2 \pm 8.7$$ pb, to be compared with the Standard Model prediction of $$\sigma (pp \rightarrow H)_\textrm{SM} = 59.9 \pm 2.6 $$ pb.

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Measurement of the production cross-section of and mesons in pp collisions at TeV with the ATLAS detector

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The European Physical Journal C 2024年第2期84卷 1-30页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N. J. Abidi, S. H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B. S. Bourdarios, C. Adam Adamczyk, L. Addepalli, S. V. Addison, M. J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A. A. Afik, Y. Agaras, M. N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W. S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T. P. A. Akimov, A. V. Akiyama, D. Akolkar, N. N. Al Khoury, K. Alberghi, G. L. Albert, J. Albicocco, P. Albouy, G. L. Alderweireldt, S. Aleksa, M. Aleksandrov, I. N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H. M. J. Ali, S. Alibocus, S. W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B. M. M. Allen, J. F. Allendes Flores, C. A. Allport, P. P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M. G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C. G. Amidei, D. Amor Dos Santos, S. P. Amos, K. R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J. K. Andrean, S. Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A. V. Annovi, A. Antel, C. Anthony, M. T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J. A. Aparo, M. A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arbiol Val, S. J. Arcangeletti, C. Arce, A. T. H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N. A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R. J. Atkinson, M. Atmani, H. Atmasiddha, P. A. Augsten, K. Auricchio, S. Auriol, A. D. Austrup, V. A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Baer, T. M. Bagnaia, P. Bahmani, M. Bailey, A. J. Bailey, V. R. Baines, J. T. Baines, L. Baker, O. K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E. M. Balek, P. Ballabene, E. Balli, F. Baltes, L. M. Balunas, W. K. CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman USA II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton USA Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London UK LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France Faculty of Physics and Applied Computer Science AGH University of Krakow Kraków Poland Department of Physics Brandeis University Waltham USA School of Physics and Astronomy University of Manchester Manchester UK Department of Physics Northern Illinois University DeKalb USA Department of Physics Istanbul University Istanbul Türkiye Particle Physics Department Rutherford Appleton Laboratory Didcot UK Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz USA CERN Geneva Switzerland Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Affiliated with an International Laboratory Covered by a Cooperation Agreement with CERN Geneva Switzerland Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Department of Physics McGill University Montreal Canada Department of Physics Royal Holloway University of London Egham

Measurements of the differential production cross-sections of prompt and non-prompt $$J/\psi $$ and $$\psi (2{\textrm{S}})$$ mesons with transverse momenta between 8 and 360 GeV and rapidity in the range $$|y|<2$$ are reported. Furthermore, measurements of the non-prompt fractions of $$J/\psi $$ and $$\psi (2{\textrm{S}})$$ , and the prompt and non-prompt $$\psi (2{\textrm{S}})$$ -to- $$J/\psi $$ production ratios, are presented. The analysis is performed using 140 fb $$^{-1}$$ of $$\sqrt{s}=13$$ TeV pp collision data recorded by the ATLAS detector at the LHC during the years 2015–2018.

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Perturbation-Theory Machine Learning (PTML) Multilabel Model of the ChEMBL Dataset of Preclinical Assays for Antisarcoma Compounds

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ACS OMEGA 2020年第42期5卷 27211-27220页

作者： Cabrera-Andrade, Alejandro Lopez-Cortes, Andres Munteanu, Cristian R. Pazos, Alejandro Perez-Castillo, Yunierkis Tejera, Eduardo Arrasate, Sonia Gonzalez-Diaz, Humbert Grupo de Bio-Quimioinformática Universidad de Las Américas de los Granados Avenue Quito 170125 Ecuador Carrera de Enfermerı́a Facultad de Ciencias de la Salud Universidad de Las Américas de los Granados Avenue Quito 170125 Ecuador RNASA-IMEDIR Computer Sciences Faculty University of A Coruña A Coruña 15071 Spain Centro de Investigación Genética y Genómica Facultad de Ciencias de la Salud Eugenio Espejo Universidad UTE Mariscal Sucre Avenue Quito 170129 Ecuador Biomedical Research Institute of A Coruña (INIBIC) University Hospital Complex of A Coruña (CHUAC) A Coruña 15006 Spain Centro de Investigación en Tecnologías de la Información y las Comunicaciones (CITIC) Campus de Elviña s/n A Coruña 15071 Spain Escuela de Ciencias Fı́sicas y Matemáticas Universidad de Las Américas de los Granados Avenue Quito 170125 Ecuador Facultad de Ingenierı́a y Ciencias Aplicadas Universidad de Las Américas de los Granados Avenue Quito 170125 Ecuador Department of Organic Chemistry II and Basque Center for Biophysics University of Basque Country UPV/EHU Leioa 48940 Biscay Spain Ikerbasque Basque Foundation for Science Bilbao 48011 Biscay Spain

Sarcomas are a group of malignant neoplasms of connective tissue with a different etiology than carcinomas. The efforts to discover new drugs with antisarcoma activity have generated large datasets of multiple preclinical assays with different experimental conditions. For instance, the ChEMBL database contains outcomes of 37,919 different antisarcoma assays with 34,955 different chemical compounds. Furthermore, the experimental conditions reported in this dataset include 157 types of biological activity parameters, 36 drug targets, 43 cell lines, and 17 assay organisms. Considering this information, we propose combining perturbation theory (PT) principles with machine learning (ML) to develop a PTML model to predict antisarcoma compounds. PTML models use one function of reference that measures the probability of a drug being active under certain conditions (protein, cell line, organism, etc.). In this paper, we used a linear discriminant analysis and neural network to train and compare PT and non-PT models. All the explored models have an accuracy of 89.19-95.25% for training and 89.22-95.46% in validation sets. PTML-based strategies have similar accuracy but generate simplest models. Therefore, they may become a versatile tool for predicting antisarcoma compounds.

关键词： Assays Chemical specificity Molecular modeling Mathematical methods Bioactivity

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Critical current density in advanced superconductors

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Progress in Materials science 2026年 155卷

作者： H.S. Ruiz J. Hänisch M. Polichetti A. Galluzzi L. Gozzelino D. Torsello S. Milošević-Govedarović J. Grbović-Novaković O.V. Dobrovolskiy W. Lang G. Grimaldi A. Crisan P. Badica A.M. Ionescu P. Cayado R. Willa B. Barbiellini S. Eley A. Badía–Majós School of Engineering and Space Park Leicester University of Leicester University Rd Leicester LE1 7RH United Kingdom Karlsruhe Institute of Technology Institute for Technical Physics Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen 76344 Germany Department of Physics “E.R. Caianiello” University of Salerno via Giovanni Paolo II 132 Fisciano (SA) 84084 Italy Consiglio Nazionale delle Ricerche CNR-SPIN c/o Università di Salerno- via Giovanni Paolo II 132 Fisciano (SA) 84084 Italy Department of Applied Science and Technology Politecnico di Torino Corso Duca degli Abruzzi 24 Torino 10129 Italy Istituto Nazionale di Fisica Nucleare Sezione di Torino Via P. Giuria 1 Torino 10125 Italy University of Belgrade Vinča Institute of Nuclear Sciences National Institute of Republic of Serbia Centre of Excellence for Hydrogen and Renewable Energy - CONVINCE Mike Petrovića Alasa 12-14 Belgrade 11000 Serbia Cryogenic Quantum Electronics EMG and LENA Technische Universität Braunschweig Hans-Sommer-Str. 66 Braunschweig 38106 Germany Faculty of Physics University of Vienna Boltzmanngasse 5 Vienna 1090 Austria National Institute of Materials Physics 405A Atomistilor Str. Magurele 077125 Romania University of Geneva Department of Quantum Matter Physics (DQMP) Quai Ernest-Ansermet 24 Geneva 1211 Switzerland Departamento de Física Universidad de Oviedo Campus Llamaquique C/ Calvo Sotelo s/n Oviedo 33007 Spain Institute for Theoretical Condensed Matter Physics Karlsruhe Institute of Technology Wolfgang-Gaede Strasse 1 Karlsruhe D-76131 Germany Institute of Systems Engineering School of Engineering HES-SO Valais-Wallis rue de l’Industrie 23 Sion CH-1950 Switzerland Department of Physics School of Engineering Science LUT University Yliopistonkatu 34 Lappeenranta FI-53850 Finland Quantum Materials and Sensing Institute Department of Physics Northeastern University 147 S Bedford St Burlington MA 01803 USA Department of Physics Colorado School of Mines Golden Co

This review paper delves into the concept of critical current density ( J c ) in high-temperature superconductors (HTS) across macroscopic, mesoscopic, and microscopic perspectives. Through this exploration, a comprehensive range of connections is unveiled aiming to foster advancements in the physics, materials science, and the engineering of applied superconductors. Beginning with the macroscopic interpretation of J c as a central material law, the review traces its development from C.P. Bean’s foundational work to modern extensions. Mesoscopic challenges in understanding vortex dynamics and their coherence with thermodynamic anisotropy regimes are addressed, underscoring the importance of understanding the limitations and corrections implicit in the macroscopic measurement of J c , linked with mesoscopic phenomena such as irradiation effects, defect manipulation, and vortex interactions. The transition to supercritical current densities is also discussed, detailing the superconductor behavior beyond critical thresholds with a focus on flux-flow instability regimes relevant to fault current limiters and fusion energy magnets. Enhancing J c through tailored material microstructures, engineered pinning centers, grain boundary manipulation, and controlled doping is explored, along with radiation techniques and their impact on large-scale energy systems. Emphasizing the critical role of J c , this review focuses on its physical optimization and engineering manipulation, highlighting its significance across diverse sectors.

关键词： Superconductivity Superconducting materials Critical current density Vortices High temperature superconductors Flux flow instabilities Flux creep Flux pinning Vortex–defect interactions

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A distributed neural network architecture for robust non-linear spatio-temporal prediction

arXiv

引用

arXiv 2019年

作者： Karlbauer, Matthias Otte, Sebastian Lensch, Hendrik P.A. Scholten, Thomas Wulfmeyer, Volker Butz, Martin V. University of Tübingen Neuro-Cognitive Modeling Group Sand 14 Tübingen72076 Germany University of Tübingen Soil Science and Geomorphology Rümelinstraße 19-23 Tübingen72070 Germany University of Tübingen Computer Graphics Maria-von-Linden-Straße 6 Tübingen72076 Germany University of Hohenheim Institute for Physics and Meteorology Garbenstraße 30 Stuttgart70599 Germany

We introduce a distributed spatio-temporal artificial neural network architecture (DISTANA). It encodes mesh nodes using recurrent, neural prediction kernels (PKs), while neural transition kernels (TKs) transfer information between neighboring PKs, together modeling and predicting spatio-temporal time series dynamics. As a consequence, DISTANA assumes that generally applicable causes, which may be locally modified, generate the observed data. DISTANA learns in a parallel, spatially distributed manner, scales to large problem spaces, is capable of approximating complex dynamics, and is particularly robust to overfitting when compared to other competitive ANN models. Moreover, it is applicable to heterogeneously structured meshes. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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You better watch out: US COVID-19 wave dynamics versus vaccination strategy

arXiv

引用

arXiv 2020年

作者： Cacciapaglia, Giacomo Cot, Corentin Islind, Anna Sigridur Óskarsdóttir, María Sannino, Francesco UMR5822 CNRS IN2P3 VilleurbanneF-69622 France University of Lyon Université Claude Bernard Lyon 1 LyonF-69001 France Department of Computer Science Reykjavík University Menntavegur 1 Reykjavík102 Iceland CP3-Origins Danish Institute for Advanced Study University of Southern Denmark Campusvej 55 OdenseDK-5230 Denmark Dipartimento di Fisica E. Pancini Università di Napoli Federico II INFN sezione di Napoli Complesso Universitario di Monte S. Angelo Edificio 6 via Cintia Napoli80126 Italy

We employ the epidemic Renormalization Group (eRG) framework to understand, reproduce and predict the COVID-19 pandemic diffusion across the US. The human mobility across different geographical US divisions is modelled via open source flight data alongside the impact of social distancing for each such division. We analyse the impact of the vaccination strategy on the current pandemic wave dynamics in the US. We observe that the ongoing vaccination campaign will not impact the current pandemic wave and therefore strict social distancing measures must still be enacted. To curb the current and the next waves our results indisputably show that vaccinations alone are not enough and strict social distancing measures are required until sufficient immunity is achieved. Our results are essential for a successful vaccination strategy in the US. © 2020, CC BY.

关键词： Vaccines

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